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Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Is there an association between disease ignorance and selfrated health? The HUNT Study, a cross-sectional survey Journal: BMJ Open rp Fo Manuscript ID: Article Type: Date Submitted by the Author: Complete List of Authors: bmjopen-2014-004962 Research 29-Jan-2014 Secondary Subject Heading: Epidemiology, Public health, Diabetes and endocrinology Hypertension < CARDIOLOGY, General diabetes < DIABETES & ENDOCRINOLOGY, Thyroid disease < DIABETES & ENDOCRINOLOGY, PRIMARY CARE w ie Keywords: General practice / Family practice ev <b>Primary Subject Heading</b>: rr ee Jørgensen, Pål; Norwegian University of Science and Technology, Department of Public Health and General Practice Langhammer, Arnulf; Norwegian University of Science and Technology, HUNT Research Centre Krokstad, Steinar; Norwegian University of Science and Technology, HUNT Research Centre Forsmo, Siri; Norwegian University of Science and Technology, Department of Public Health and General Practice ly on For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 1 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 1 of 18 Disease ignorance and self-rated health, any relationship? The HUNT Study, a cross-sectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad, Siri Forsmo Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway Pål Jørgensen PhD Candidate HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Arnulf Langhammer Professor, Head of HUNT Databank HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Steinar Krokstad Professor, Head of HUNT Research Center Department of Public Health and General Practice, Norwegian University of Science and Technology, Siri Forsmo Professor, Head of Department rr ee rp Fo Correspondence to: P Jørgensen pal_jorgensen@ntnu.no ev Keywords: Self-rated health, awareness, hypothyroidism, diabetes, hypertension. Word count: 2995 w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 2 of 18 ABSTRACT Objective To explore if awareness versus unawareness of thyroid dysfunction, diabetes mellitus or hypertension is associated with self-rated health. Design Large-scale, cross sectional population based study. The association between thyroid function, diabetes mellitus, and blood pressure and self-rated health was explored by multiple rp Fo logistic regression analysis. Setting The second survey of the Nord-Trøndelag Health Study, HUNT2, 1995-97. Participants 33,734 persons aged 40-70 years. ee Primary outcome measures Logistic regression was used to estimate odds ratios for good rr self-rated health as a function of thyroid status, diabetes mellitus status and blood pressure status. ev Results Persons aware of their hypothyroidism, diabetes mellitus, or hypertension reported ie poorer self-rated health than individuals without such conditions. Women with unknown and w subclinical hypothyroidism reported better self-rated health than women with normal thyroid status. Both in women and men, unknown and probable diabetes, as well as unknown on mild/moderate hypertension was not associated with poorer health. Further, persons with unknown severe hypertension reported better health than normotensive persons. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Conclusions People with undiagnosed, but prevalent hypothyroidism, diabetes mellitus, and hypertension often have good self-rated health, whilst when aware of their diagnoses, they report reduced self-rated health. Use of screening, more sensitive tests, and widened diagnostic criteria might have a negative effect on perceived health in the population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 2 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 3 of 23 BMJ Open Page 3 of 18 STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths • Sample from a large-scale, general population • High-prevalent diseases under study; ensuring statistical power in subgroup analyses Limitations rp Fo • Study mainly based on self-reported data • Cross-sectional study; susceptibility to confounding and impossibility to assume causal relationships INTRODUCTION ev rr ee Guidelines for prevention and treatment have been developed for most high prevalent diseases in western countries aiming for reduction of morbidity and mortality by interventions mainly in primary health care (PHC). w ie In the society there seems to be an increasing conviction of achievable zero-vision regarding on risks and diseases. Part of the strategy is to detect risk factors and pre-diseases in even earlier stages. From a secondary or tertiary health care level, this might seem reasonable since ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 intervention on many individuals with specific risk factors presumably can prevent or delay disease or progression of disease. Further, health authorities and hospital clinicians regularly raise concern of the lack of detection of risk factors, of subclinical conditions and of achieving treatment goals.[1-7] Norwegian studies have shown that guidelines are often difficult to implement and adhere to in PHC.[8 9] According to guidelines, most individuals would be defined as at risk and resources needed to handle this appropriately could destabilize the entire health care system.[10-12] An American review pointed out knowledge, attitude, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 4 of 18 and behaviour as barriers of physician’s adherence to clinical guidelines.[13] In an already complex and busy PHC-setting, one might expect that resources used for disease prevention and case finding have to compete with resources for handling acknowledged disease. Also, physicians might want to avoid increasing disease related burden for patients, in line with the old wisdom; “primum non nocere”.[14] Thus the risk and disease zero-visions in society and among politicians are seldom shared by PHC professionals. rp Fo When guidelines, mainly based on research from high risk hospital populations, are applied on low risk populations in PHC, more healthy individuals are identified as being at risk or are given diagnoses. Also the widened inclusion criteria for diagnoses in general and use of more ee sensitive tests contribute to define more individuals at risk or as unhealthy.[15] Possible undesirable outcomes of such strategies remain unclear. rr Self-rated health (SRH) is a valid and widely used measure of general health in epidemiologic ev research.[16-19] It is associated with several clinical conditions often seen in PHC, with ie recovery [20-23] and is found to predict morbidity, sick leave, and disability pension,[24 25] as well as mortality.[26 27] The majority of studies describing association between labelling w of disease per se and SRH have focused on arterial hypertension.[28-31] However, one study on has indicated reduced SRH among individuals labelled with thyroid dysfunctions.[32] ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The aim of this study was to investigate whether persons’ awareness versus unawareness of thyroid dysfunction, diabetes mellitus, or hypertension was associated with their SRH, as reported in a population-based health study in Norway. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 4 of 23 Page 5 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 5 of 18 METHODS Study population The data sample in this study stem from the second wave of the Nord-Trøndelag Health Study (HUNT2) conducted in 1995-97 in the county of Nord-Trøndelag, Norway. All individuals aged 20 years and older, living in the county, were invited (94,194 individuals). In all, 66.7% rp Fo of men (n=30,860) and 75.5% of women (n=35,280) participated. The survey consisted of both questionnaires and measurements, and is described previously in detail.[33 34] In our study we included answers from the main questionnaire and the baseline measurements for persons aged 40-70 years. The age span was chosen because thyroid stimulating hormone ee (TSH) was analysed in all women and in 50% of men at this age, of a rather low disease rr burden in people younger than 40 years, and of a lower attendance rate under and above this age span. A total of 24,950 individuals had TSH measurements and answered thyroid ev questions, thus were eligible for analysis on thyroid dysfunction, whilst in the analysis of ie diabetes mellitus and blood pressure, 33,734 individuals were included in all. Self-rated health w on The first question in the main questionnaire in HUNT2, answered before attending the examination stations, was “How is your health at the moment?”. The four answer alternatives ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 were dichotomized into poor or good (reference); good covering the answers “good” and “very good”, poor covering “poor” and “not so good”. Thyroid function The participants answered questions on history of hypo- and hyperthyroidism, goitre, other thyroid diseases, and treatment with thyroxin, radio-iodine, surgery, or thyreostatic medication. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 6 of 18 Serum TSH and free T4 were analysed at the Hormone laboratory, Aker University Hospital, Norway. The laboratory reference value for TSH, as defined prior to the survey, was 0.2-4.5 mU/L and for free T4 8.0-20.0 pmol/L. If TSH was <0.2 mU/L or >4.0 mU/L, and/or if the participant reported any thyroid disease, serum free T4 was also measured.[35] Individuals reporting no previous thyroid disease and having TSH within reference range rp Fo were categorized as “no thyroid disease” and chosen as reference category. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 <8.0 pmol/L was defined as unknown hypothyroidism. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 8.0 – 20.0 pmol/L was defined as subclinical hypothyroidism. Individuals reporting ee hypothyroidism and use of thyroxin were classified as having known hypothyroidism, regardless of the TSH and T4 levels. Affirmative answers to other thyroid related questions or rr measures outside reference range in the remainders were classified as other thyroid dysfunction. w ie Diabetes mellitus ev Diabetes mellitus was assessed through self-report and blood samples. Serum glucose was analysed at Levanger Hospital, Norway. Those reporting no diabetes and having normal on glucose levels (<5.5 mmol/L) were classified as “no diabetes” and were chosen as reference ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 category. No self-reported diabetes and non-fasting glucose >11.0 mmol/L was categorized as unknown diabetes, whereas no diabetes and non-fasting glucose 5.5-11.0 mmol/L was categorized as probable diabetes. Self-reported diabetes was classified as known diabetes regardless of the glucose level. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 6 of 23 Page 7 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 7 of 18 Blood pressure In the questionnaire participants were asked about the doctor’s advice after the latest blood pressure measurement prior to participation in HUNT. The answer categories were: “no follow-up and no medication necessary”, “recommended follow-up examination but not to take medicine”, “start or continue taking medicine for high blood pressure”, or “never rp Fo measured”. At HUNT2, mean systolic and mean diastolic arterial blood pressure (BP) of measurement 2 and 3 was categorized into normal (systolic (s) BP < 140 mmHg and diastolic (d) BP < 90 mmHg), mild hypertension (sBP 140-159 mmHg and dBP <100 mmHg or sBP <160 mmHg and dBP 90-99 mmHg), moderate hypertension (sBP 160-179 mmHg and dBP ee <109 mmHg or sBP <180 mmHg and dBP 100-109 mmHg), and severe hypertension (sBP>180 mmHg or dBP>110 mmHg). We constructed a new variable to define rr normotensive (reference), unknown mild- and moderate hypertensive, unknown severe ev hypertensive, and known hypertensive persons on the basis of self-report and measures. Statistical analysis w ie The descriptive analyses of the study population were stratified by gender, and we used chisquare tests to examine any difference in proportions of SRH between the independent on variables. Gender-stratified multiple logistic regression were used to estimate odds ratio (OR) ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 with 95% confidence intervals (CI) for good SRH, as a function of thyroid status, diabetes mellitus status and blood pressure status, in separate univariate and multivariate analyses for each condition. Age, smoking, alcohol consumption, body mass index (BMI), working- and educational status, and self-reported limiting long-term illness or injury are associated with SRH[36] and the diseases under study, but likely not affected by SRH or the diseases. Hence, these For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 8 of 18 variables were included, a priori, as confounders in the models. Age was categorized into age groups; 40-49 years, 50-59 years, and 60-70 years. Smoking status was categorized into never smoked daily, previous daily smoker, and current daily smoker. Alcohol units (AU) were defined as number of glasses of wine, beer or liquor. Those reporting to be teetotalers or to have alcohol intake less than four times a month or less than seven AU per two weeks were categorized as low consumers, those reporting drinking five to eight times a month or 8-14 rp Fo AU per two weeks as moderate consumers, and those drinking more often than eight times a month or more than 14 AU as heavy consumers. BMI (kg/m2) was calculated of measured height and weight and categorized according to The World Health Organization’s (WHO) ee definition; underweight (18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.029.9 kg/m2) and obese (>30.0 kg/m2). People reporting paid- or self-employed work were rr classified as working, otherwise as not working. Educational level was categorized into <10 ev years, 10-12 years and >12 years. We chose affirmative answer to the question “Do you suffer from any long-term illness or injury (at least one year) of a physical or psychological nature ie that impairs your functioning in your everyday life?” to represent all relevant chronic medical conditions that could confound the results. w on To examine whether the association of the three disease statuses with SRH differed by categories of the other independent variables, we used likelihood ratio-tests with p-value for ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 statistical interaction. We tested for multicollinearity between the independent variables, by linear regression. In an additional analysis, the association between SRH and having had one or more medical consultations during the last year was investigated by logistic regression models, stratified by gender, both in the total study population and after exclusion of persons with diagnoses under study. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 8 of 23 Page 9 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 9 of 18 All analyses were preformed with IBM SPSS Statistics version 20 for windows. The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. RESULTS In all age categories, a higher proportion of men than women reported good SRH (p<0.001), rp Fo and in both sexes, the proportion reporting good SRH declined by age (p<0.002) (Table 1). The proportion reporting good SRH was lower in overweight, obese, and underweight women, than in normal weight women (p<0.001). In men the proportion reporting good SRH declined between the normal weight group to overweight-, obese-, and underweight group ee (p<0.001). In previous and current female smokers, a lower proportion reported good SRH rr compared to non smokers (p<0.001). In men, the proportion reporting good SRH was higher among non smokers than among previous and current smokers (p<0.001), whereas there was ev no difference between previous and current smokers. The proportion reporting good SRH was ie higher in moderate and heavy alcohol consumers than in low consumers, increased with education and was higher for participants in paid work (p<0.001). Underweight men and w persons with “any long-term impairment” had the lowest proportion reporting good SRH of all groups. There was no multicollinearity between the independent variables. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Thyroid function Thyroid dysfunctions, both known and unknown were more often observed among women than among men (p<0.001) (Table 1). Women with known hypothyroidism had lower odds of reporting good SRH (OR 0.49 (95% CI 0.41 to 0.59) compared to women without thyroid disease in the adjusted analyses, but women with unknown or subclinical hypothyroidism had For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 10 of 18 84% and 48% higher odds, respectively, of reporting good SRH compared to the odds of women without thyroid disease (Table 2). A corresponding, but non-significant pattern was found among men. Diabetes mellitus The prevalence of unknown, probable, and known diabetes was slightly higher in men than in rp Fo women (p<0.001) (Table 1). Women with known diabetes mellitus had lower odds of good SRH than those without diabetes in the adjusted analyses; OR 0.53 (95% CI 0.41 to 0.69), whereas in women with unknown or possible diabetes mellitus, the odds of good SRH were similar to the odds among persons without diabetes, in the adjusted analyses (Table 2). In ee men, the association of diabetes status with SRH differed by levels of education. Among men rr without higher education (12 years or less), the odds of good SRH were as in the main-effect model (Table 2). However in men with higher education, the ORs of good SRH were barely ev significantly lower among men with unknown diabetes (OR 0.29 (95% CI 0.09-1.00)) and ie among men with possible diabetes (OR 0.79 (95% CI 0.63-1.00)) compared to men without diabetes. Among men with known diabetes in this stratum, the OR of good SRH was 0.31 w (95% CI 0.17-0.54) compared to men without diabetes. Blood pressure ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The prevalence of unknown mild and moderate hypertension was higher in men than in women (p<0.001). Unknown severe hypertension and known hypertension were equally distributed between women and men (Table 1). Women with known hypertension had lower odds of reporting good SRH than normotensive women, in the adjusted analyses. The figures were similar in men (Table 2). In contrast; compared to normotensive women, those with unknown severe hypertension had 52 % higher odds of reporting good SRH, with similar For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 10 of 23 Page 11 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 11 of 18 figures in men. Persons with unknown mild and moderate hypertension reported good SRH similar to the normotensive ones. Additional analyses Women with poor SRH had more than six times the odds of those with good SRH to have had a medical consultation during the last year; OR 6.29 (95% CI 5.47 to 7.22). For men the rp Fo corresponding OR was 5.53 (95% CI 4.86 to 6.29). After exclusion of persons with diagnosed thyroid disease, diabetes mellitus, known hypertension, and “any long-term disease”, the corresponding OR was 3.71 (95% CI 2.90 to 4.73), with similar figures in men. DISCUSSION rr ee This large population-based study showed that persons with known thyroid dysfunction, diabetes mellitus, and hypertension were less likely to report good SRH than those without ev such conditions. Less expected, persons with unknown and subclinical hypothyroidism were more likely to report good SRH than those without thyroid disease. Similarly, those with ie unknown severe hypertension were more likely to report good SRH, compared to persons w with normal blood pressure. In general, persons with unknown diabetes and unknown on mild/moderate hypertension, reported good health, just like the reference group. Although both a qualitative and quantitative measure of association, the estimated ORs in our ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 study will, if interpreted as relative risks, overestimate the case, because the prevalence of good SRH is high in all groups.[37] The main strengths of this study were the numbers of participants, that the diseases we studied were high-prevalent, and that we could assume representativeness to the general population regarding the variables included. It is known that individuals with high burden of symptoms are less likely to attend surveys, but so far there has been little evidence that non-participation For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 12 of 18 on this basis introduce substantial bias in associational studies.[38] We studied diseases with generally low symptom-burden, and expect selection bias to be negligible. The main limitation was possibly that we relied on self-reported data on both dependent and independent variables. The validity of self reported measures relevant for this study is questionable. However, if any, there should be a non-differential misclassification, that only rp Fo should underestimate the associations found. There is always a possibility of residual confounding in non-randomized study designs, and due to the observational, cross-sectional design we neither can assume a causal relationship. ee Bias due to differential detection of disease in the study population could lead to a type 1 error. Hypothyroidism and diabetes mellitus are often associated with vague symptoms such rr as tiredness and weakness. These symptoms are strongly associated with reduced SRH.[39] It ev is likely that presenting such symptoms for the GP would result in measurements of TSH, free T4, and serum glucose, thus reveal any related dysfunction. Low self-perceived health ie increases the probability to visit a GP.[40] The social security covers most costs related to w clinical measurements and blood sampling in Norway, thus we expect GPs to have a low threshold to measure thyroid function, blood pressure or glucose levels. People who do not on consult their GP will not have diseases with mild or no symptoms diagnosed, and their ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 personality could be characterized by less worrying and more optimistic attitude to health being reflected in better SRH.[41] On the other hand, the association between known disease and poor SRH could in fact be explained physiologically due to the pathological effect of disease. Lack of corresponding association between ignored, but prevalent disease and poor SRH is not in line with this For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 12 of 23 Page 13 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 13 of 18 hypothesis, rising question of a possible adverse effect of disease labelling. However, confounding by severity of disease cannot be ruled out. Due to low numbers of persons having unknown hypothyroidism and diabetes mellitus, the results should be interpreted with caution. On the other hand, there were high numbers in the subclinical and probable groups, and analyses of these groups did not show any associations rp Fo with poor SRH, also rising question of a possible disease labelling effect. Consistent findings regarding unknown, subclinical, and probable disease, versus known disease, could indicate a potential adverse effect of disease labelling. Although early detection of disease is protective on morbidity and mortality for many diseases, low SRH is also shown ee to be associated morbidity and mortality.[25-27] This is an important aspect in the debate of presymptomatic case-finding. ev rr The BMJ's Too Much Medicine campaign aims to highlight the threat to human health posed by overdiagnosis and the waste of resources on unnecessary care (http://www.bmj.com/too- ie much-medicine). American data have shown that the majority of all health care includes w preference-sensitive and supply-sensitive services. The extent of these services varies greatly without necessarily leading to better health.[42 43] A great deal of activity in such services is on based on identifying subclinical disease. The negative health effect this might have, ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 modulated through reduced SRH, can explain why population mortality is not reduced in areas with high frequency of diagnoses. Both public and academic debates are often characterised by the conviction that all medical treatment is efficient. Wennberg showed that a relatively small proportion of all medical treatment is indisputably good for health.[44] The concern for unrevealed risk factors and subclinical conditions might lead to unnecessary costly health care interventions, increase For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 14 of 18 supply-sensitive services without positive health effect and have a negative influence on people’s general and self-perceived health causing more harm than good.[15] Of ethical reasons, the possible causal effect of disease labelling on SRH is impossible to assess in a randomized controlled trial. Our study emphasizes the need for more prospective research to investigate potential health effects of disease labelling and early diagnosis. rp Fo CONCLUSION Our data suggest that early identification of disease may imply a negative effect on SRH and thereby eventually cause more harm than good. On a population level, such efforts might ee increase the costs in health care and the proportion of supply-sensitive services without any documented positive health effect. More research is needed concerning the possible adverse rr effects of disease labelling on SRH and mortality. FOOTNOTES ev Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Contributors All authors meet the four criteria for authorship recommended by the International Committee of Medical Journal Editors. SF, AL, and SK have been active supervisors in study conception, design, conduct, interpretation, and reporting. PJ analyzed the data and drafted the manuscript. Critical revisions were done by all supervisors and all authors approved the final version of the manuscript. SF, AL, SK and PJ are joint guarantors. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 14 of 23 Page 15 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 15 of 18 Acknowledgements The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology NTNU), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. The authors would like to thank Bjørn Olav Åsvold for his contribution in planning of the thyroid-part of the study. Transparency declaration PJ affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there were no discrepancies from the study as planned. Ethical approval The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. rp Fo Funding No external funding. PJ received a PhD-grant, funded by the Norwegian University of Science and Technology, NTNU. Data sharing statement No additional data available. w ie ev rr ee ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 16 of 18 1. Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ 2005;31(4):564-71 doi: 10.1177/0145721705279050[published Online First: Epub Date]|. 2. Borzecki AM, Wong AT, Hickey EC, et al. Hypertension control: how well are we doing? Arch Intern Med 2003;163(22):2705-11 doi: 10.1001/archinte.163.22.2705[published Online First: Epub Date]|. 3. Andros V, Egger A, Dua U. Blood pressure goal attainment according to JNC 7 guidelines and utilization of antihypertensive drug therapy in MCO patients with type 1 or type 2 diabetes. J Manag Care Pharm 2006;12(4):303-9 4. Liddy C, Singh J, Hogg W, et al. Quality of cardiovascular disease care in Ontario, Canada: missed opportunities for prevention - a cross sectional study. BMC Cardiovasc Disord 2012;12:74 doi: 10.1186/1471-2261-12-74[published Online First: Epub Date]|. 5. Huebschmann AG, Mizrahi T, Soenksen A, et al. Reducing clinical inertia in hypertension treatment: a pragmatic randomized controlled trial. J Clin Hypertens (Greenwich) 2012;14(5):322-9 doi: 10.1111/j.1751-7176.2012.00607.x[published Online First: Epub Date]|. 6. Alkerwi Aa, Pagny S, Lair M-L, et al. Level of Unawareness and Management of Diabetes, Hypertension, and Dyslipidemia among Adults in Luxembourg: Findings from ORISCAV-LUX Study. PLoS One 2013;8(3):e57920 doi: 10.1371/journal.pone.0057920[published Online First: Epub Date]|. 7. Khan N, Chockalingam A, Campbell NR. Lack of control of high blood pressure and treatment recommendations in Canada. Can J Cardiol 2002;18(6):657-61 8. Hetlevik I, Holmen J, Kruger O, et al. Fifteen years with clinical guidelines in the treatment of hypertension - still discrepancies between intentions and practice. Scand J Prim Health Care 1997;15(3):134-40 doi: Doi 10.3109/02813439709018503[published Online First: Epub Date]|. 9. Hetlevik I, Holmen J, Midthjell K. Treatment of diabetes mellitus - physicians' adherence to clinical guidelines in Norway. Scand J Prim Health Care 1997;15(4):193-97 doi: Doi 10.3109/02813439709035027[published Online First: Epub Date]|. 10. Petursson H, Getz L, Sigurdsson JA, et al. Current European guidelines for management of arterial hypertension: Are they adequate for use in primary care? Modelling study based on the Norwegian HUNT 2 population. BMC Fam Pract 2009;10 doi: Artn 70 Doi 10.1186/1471-229610-70[published Online First: Epub Date]|. 11. Petursson H, Getz L, Sigurdsson JA, et al. Can individuals with a significant risk for cardiovascular disease be adequately identified by combination of several risk factors? Modelling study based on the Norwegian HUNT 2 population. J Eval Clin Pract 2009;15(1):103-09 doi: DOI 10.1111/j.1365-2753.2008.00962.x[published Online First: Epub Date]|. 12. Getz L, Sigurdsson JA, Hetlevik I, et al. Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. Br Med J 2005;331(7516):551-54A doi: DOI 10.1136/bmj.38555.648623.8F[published Online First: Epub Date]|. 13. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 1999;282(15):1458-65 doi: 10.1001/jama.282.15.1458[published Online First: Epub Date]|. 14. Smith CM. Origin and uses of primum non nocere--above all, do no harm! J Clin Pharmacol 2005;45(4):371-7 doi: 10.1177/0091270004273680[published Online First: Epub Date]|. 15. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. Br Med J 2012;344 doi: Artn E3502 Doi 10.1136/Bmj.E3502[published Online First: Epub Date]|. 16. Miilunpalo S, Vuori I, Oja P, et al. Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 16 of 23 Page 17 of 23 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 17 of 18 working-age population. J Clin Epidemiol 1997;50(5):517-28 doi: S0895-4356(97)00045-0 [pii][published Online First: Epub Date]|. 17. Meurer LN, Layde PM, Guse CE. Self-rated health status: a new vital sign for primary care? WMJ 2001;100(7):35-9 18. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-5 doi: 59/5/342 [pii] 10.1136/jech.2004.021204[published Online First: Epub Date]|. 19. Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24(3):218-24 20. Bopp M, Braun J, Gutzwiller F, et al. Health risk or resource? Gradual and independent association between self-rated health and mortality persists over 30 years. PLoS One 2012;7(2):e30795 doi: 10.1371/journal.pone.0030795 PONE-D-11-20499[pii][published Online First: Epub Date]|. 21. Moller L, Kristensen TS, Hollnagel H. Self rated health as a predictor of coronary heart disease in Copenhagen, Denmark. J Epidemiol Community Health 1996;50(4):423-8 22. Kaplan GA, Goldberg DE, Everson SA, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol 1996;25(2):259-65 doi: Doi 10.1093/Ije/25.2.259[published Online First: Epub Date]|. 23. Krokstad S, Johnsen R, Westin S. Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol 2002;31(6):1183-91 doi: 10.1093/ije/31.6.1183[published Online First: Epub Date]|. 24. Halford C, Wallman T, Welin L, et al. Effects of self-rated health on sick leave, disability pension, hospital admissions and mortality. A population-based longitudinal study of nearly 15,000 observations among Swedish women and men. BMC Public Health 2012;12:1103 doi: 10.1186/1471-2458-12-1103[published Online First: Epub Date]|. 25. Latham K, Peek CW. Self-Rated Health and Morbidity Onset Among Late Midlife US Adults. J Gerontol B-Psychol 2013;68(1):107-16 doi: DOI 10.1093/geronb/gbs104[published Online First: Epub Date]|. 26. Benyamini Y, Idler EL. Community studies reporting association between self-rated health and mortality - Additional studies, 1995 to 1998. Res Aging 1999;21(3):392-401 doi: Doi 10.1177/0164027599213002[published Online First: Epub Date]|. 27. Nielsen AB, Siersma V, Hiort LC, et al. Self-rated general health among 40-year-old Danes and its association with all-cause mortality at 10-, 20-, and 29 years' follow-up. Scand J Public Health 2008;36(1):3-11 doi: 10.1177/1403494807085242[published Online First: Epub Date]|. 28. Barger SD, Muldoon MF. Hypertension labelling was associated with poorer self-rated health in the Third US National Health and Nutrition Examination Survey. J Hum Hypertens 2006;20(2):117-23 doi: 10.1038/sj.jhh.1001950[published Online First: Epub Date]|. 29. Bloom JR, Monterossa S. Hypertension Labeling and Sense of Well-Being. Am J Public Health 1981;71(11):1228-32 doi: Doi 10.2105/Ajph.71.11.1228[published Online First: Epub Date]|. 30. Moum T, Naess S, Sorensen T, et al. Hypertension Labeling, Life Events and Psychological WellBeing. Psychol Med 1990;20(3):635-46 31. Macdonald LA, Sackett DL, Haynes RB, et al. Labelling in hypertension: A review of the behavioural and psychological consequences. J Chronic Dis 1984;37(12):933-42 doi: http://dx.doi.org/10.1016/0021-9681(84)90070-5[published Online First: Epub Date]|. 32. Bianchi GP, Zaccheroni V, Solaroli E, et al. Health-related quality of life in patients with thyroid disorders - A study based on Short-Form 36 and Nottingham Health Profile Questionnaires. Qual Life Res 2004;13(1):45-54 doi: Doi 10.1023/B:Qure.0000015315.35184.66[published Online First: Epub Date]|. 33. Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag Health Study 1995-97 (HUNT 2): objectives, methods, and participation. Norsk Epidemiol 2003 13 (1 ):19-32 w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 18 of 18 34. Krokstad S, Langhammer A, Hveem K, et al. Cohort Profile: The HUNT Study, Norway. Int J Epidemiol 2012 doi: dys095 [pii] 10.1093/ije/dys095[published Online First: Epub Date]|. 35. Bjoro T, Holmen J, Kruger O, et al. Prevalence of thyroid disease, thyroid dysfunction and thyroid peroxidase antibodies in a large, unselected population. The Health Study of Nord-Trondelag (HUNT). Eur J Endocrinol 2000;143(5):639-47 doi: 1430639 [pii][published Online First: Epub Date]|. 36. Giron P. Determinants of self-rated health in Spain: differences by age groups for adults. Eur J Public Health 2012;22(1):36-40 doi: 10.1093/eurpub/ckq133[published Online First: Epub Date]|. 37. Davies HTO, Crombie IK, Tavakoli M. When can odds ratios mislead? Br Med J 1998;316(7136):989-91 38. Langhammer A, Krokstad S, Romundstad P, et al. The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms. BMC Med Res Methodol 2012;12:143 doi: 10.1186/1471-2288-12-143[published Online First: Epub Date]|. 39. Molarius A, Janson S. Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol 2002;55(4):364-70 doi: http://dx.doi.org/10.1016/S0895-4356(01)00491-7[published Online First: Epub Date]|. 40. Hansen AH, Halvorsen PA, Ringberg U, et al. Socio-economic inequalities in health care utilisation in Norway: a population based cross-sectional survey. BMC Health Serv Res 2012;12:336 doi: 10.1186/1472-6963-12-336[published Online First: Epub Date]|. 41. Vingilis E, Wade T, Seeley J. Predictors of adolescent health care utilization. J Adolesc 2007;30(5):773-800 doi: http://dx.doi.org/10.1016/j.adolescence.2006.10.001[published Online First: Epub Date]|. 42. Welch HG, Sharp SM, Gottlieb DJ, et al. Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries. JAMA 2011;305(11):1113-8 doi: 10.1001/jama.2011.307[published Online First: Epub Date]|. 43. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138(4):288-98 44. Wennberg JE. Tracking medicine. A researcher’s quest to understand health care. Oxford: Oxford University Press, 2010. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 18 of 23 Page 19 of 23 BMJ Open Table 1. Good self-rated health (SRH good) by sex and characteristics of the study population Study population (n= 33,734) Men (n=16,220) Women (n=17,514) % SRH good (%) n % SRH good (%) 7058 5709 4747 40.3 32.6 27.1 77.6 64.4 56.6 6517 5328 4375 40.2 32.8 27.0 81.7 72.1 59.6 6821 7026 3489 104 0.6 39.1 40.3 20.0 58.4 72.8 68.5 56.5 4804 8694 2635 35 0.2 29.7 53.8 16.3 42.9 75.3 73.6 64.8 6973 4651 5763 40.1 26.7 33.1 70.3 68.0 64.3 4849 6105 5172 30.1 37.9 32.0 80.0 69.8 69.1 88.7 8.8 2.6 66.7 76.8 76.3 11488 2839 1375 73.2 18.1 8.8 71.0 78.7 78.3 ee n 14888 1471 430 rr 48.5 33.9 17.7 60.5 72.8 80.0 5711 6615 3339 36.5 42.2 21.3 63.1 76.0 84.7 11539 5627 67.2 32.8 77.1 49.0 12309 3665 77.1 22.9 79.9 49.2 10348 6275 59.1 35.8 9912 5829 63.0 37.0 88.7 46.0 14373 107 466 858 872 86.2 0.6 2.8 5.1 5.2 68.7 78.5 75.0 48.9 61.4 7804 16 150 124 180 94.3 0.2 1.8 1.5 2.2 72.1 68.8 66.4 58.1 56.2 11279 46 5728 395 64.6 0.3 32.8 2.3 69.4 52.2 65.9 43.1 9196 88 6392 482 56.9 0.5 39.6 3.0 74.6 67.8 71.5 49.5 9135 4473 403 3327 52.6 25.8 2.4 19.2 72.4 67.9 70.7 54.0 6858 5343 349 3498 42.7 33.3 2.2 21.8 77.5 74.7 73.8 59.6 w ie ev 8133 5682 2962 85.9 39.8 ly on Age group 40-50 years 51-60 years 61-70 years BMI (kg/m2) <18,5 18,5-24,9 25,0-29,9 >30 (0.4% missing) Smoking status Never smoked daily Previous daily smoker Daily smoker (0.7% missing) Alcohol use None to low intake Moderate intake High intake (3.7% missing) Educational level < 10 years 10 – 12 years > 12 years (3.8% missing) Employed Yes No (1.8% missing) Any long-term impairment No Yes (4.1% missing) Thyroid function No thyroid disease Unknown hypothyroidism Subclinical hypothyroidism Known hypothyroidism Other thyroid dysfunction (1.3% missing) Diabetes mellitus No diabetes Unknown diabetes Probable diabetes Known diabetes (0.4% missing) Blood pressure status Normotensive Unknown mild/moderate hypertension Unknown severe hypertension Known hypertension (0.9% missing) rp Fo 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open Table 2. The association between self-rated health and thyroid function, diabetes mellitus and blood pressure. Odds ratio (OR) of good self-rated health and 95% confidence intervals (95% CI), crude and adjusted for age, other long-term illness or injury that impairs function in everyday life, smoking habits, alcohol use, educational level, work status and body mass index. Cases with missing data were excluded from the analyses. Fo Women Thyroid function No thyroid dysfunction Unknown hypothyroidism Subclinical hypothyroidism Known hypothyroidism Other thyroid dysfunction Diabetes mellitus No diabetes Unknown diabetes Probable diabetes Known diabetes Blood pressure No hypertension Unknown mild/moderate hypertension Unknown severe hypertension Known hypertension OR (95% CI) Crude n rp 12476 92 394 718 729 9946 39 4797 318 8180 3787 325 2745 Adjusted 1.00 1.66 (1.05-2.64) 1.37 (1.10-1.69) 0.44 (0.38-0.50) 0.72 (0.63-0.83) ee rr 1.00 0.48 (0.27-0.86) 0.85 (0.80-0.91) 0.33 (0.27-0.41) 1.00 0.81 (0.75-0.87) 0.92 (0.74-1.15) 0.45 (0.41-0.49) Men OR (95% CI) Crude n Adjusted 1.00 1.84 (1.02-3.33) 1.48 (1.13-1.94) 0.49 (0.41-0.59) 0.77 (0.65-0.93) 7045 14 128 107 163 1.00 0.85 (0.30-2.45) 0.77 (0.54-1.08) 0.54 (0.37-0.77) 0.50 (0.37-0.67) 1.00 1.28 (0.35-4.65) 1.13 (0.72-1.76) 0.69 (0.44-1.09) 0.58 (0.41-0.84) 1.00 0.66 (0.32-1.37) 1.01 (0.92-1.10) 0.53 (0.41-0.69) 8464 82 5759 395 1.00 0.72 (0.46-1.13) 0.86 (0.80-0.92) 0.33 (0.28-0.40) 1.00 1.03 (0.59-1.81) 0.99 (0.91-1.08) 0.55 (0.43-0.70) 1.00 1.10 (0.99-1.22) 1.52 (1.14-2.02) 0.69 (0.61-0.77) 6378 4837 308 3118 1.00 0.86 (0.79-0.93) 0.85 (0.77-1.08) 0.43 (0.39-0.47) 1.00 1.01 (0.92-1.12) 1.48 (1.09-2.02) 0.64 (0.57-0.72) ev iew on ly For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Page 20 of 23 Page 21 of 23 BMJ Open What is already known on this topic Awareness of thyroid dysfunction, diabetes mellitus, and hypertension is associated with reduced self-rated health Screening, increasingly sensitive diagnostic tests, and widened diagnostic criteria will define more healthy people as sick What this study adds rp Fo Unawareness of hypothyroidism, diabetes mellitus, or hypertension is not associated with reduced self-rated health w ie ev rr ee ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cross-sectional studies Section/Topic Title and abstract Item # 1 Introduction Recommendation Reported on page # Fo (a) Indicate the study’s design with a commonly used term in the title or the abstract 2 (b) Provide in the abstract an informative and balanced summary of what was done and what was found 2 rp Background/rationale 2 Explain the scientific background and rationale for the investigation being reported Objectives 3 State specific objectives, including any prespecified hypotheses Study design 4 Present key elements of study design early in the paper Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 5 Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants 5 Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if Data sources/ 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe Bias 9 Describe any efforts to address potential sources of bias Study size 10 Explain how the study size was arrived at Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and ee Methods rr 4 2-3 ev applicable measurement iew comparability of assessment methods if there is more than one group on why Statistical methods 12 3-4 (a) Describe all statistical methods, including those used to control for confounding ly (b) Describe any methods used to examine subgroups and interactions (c) Explain how missing data were addressed 5-8 5-8 7-8 5 5-8 7-8 8 Table 2 (d) If applicable, describe analytical methods taking account of sampling strategy - (e) Describe any sensitivity analyses - Results For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Page 22 of 23 Page 23 of 23 Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, 5 confirmed eligible, included in the study, completing follow-up, and analysed Descriptive data 14* (b) Give reasons for non-participation at each stage 5 (c) Consider use of a flow diagram - Fo (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders rp Table 1 (b) Indicate number of participants with missing data for each variable of interest Table 1 Outcome data 15* Report numbers of outcome events or summary measures Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included Table 1 ee Table 2 Page 9-11 (b) Report category boundaries when continuous variables were categorized rr 5-7 (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses ev Discussion - 10-11 Key results 18 Summarise key results with reference to study objectives Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias 11-13 Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence 13-14 Generalisability 21 Discuss the generalisability (external validity) of the study results 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on Other information Funding which the present article is based iew 11 on 11 ly 15 *Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies. Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 BMJ Open Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Is there an association between disease ignorance and selfrated health? The HUNT Study, a cross-sectional survey Journal: BMJ Open rp Fo Manuscript ID: Article Type: Date Submitted by the Author: Complete List of Authors: bmjopen-2014-004962.R1 Research 28-Apr-2014 Secondary Subject Heading: Epidemiology, Public health, Diabetes and endocrinology Hypertension < CARDIOLOGY, General diabetes < DIABETES & ENDOCRINOLOGY, Thyroid disease < DIABETES & ENDOCRINOLOGY, PRIMARY CARE w ie Keywords: General practice / Family practice ev <b>Primary Subject Heading</b>: rr ee Jørgensen, Pål; Norwegian University of Science and Technology, Department of Public Health and General Practice Langhammer, Arnulf; Norwegian University of Science and Technology, HUNT Research Centre Krokstad, Steinar; Norwegian University of Science and Technology, HUNT Research Centre Forsmo, Siri; Norwegian University of Science and Technology, Department of Public Health and General Practice ly on For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 1 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 1 of 22 Is there an association between disease ignorance and self-rated health? The HUNT Study, a crosssectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad, Siri Forsmo Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway Pål Jørgensen PhD Candidate HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Arnulf Langhammer Professor, Head of HUNT Databank HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Steinar Krokstad Professor, Head of HUNT Research Center Department of Public Health and General Practice, Norwegian University of Science and Technology, Siri Forsmo Professor, Head of Department rr ee rp Fo Correspondence to: P Jørgensen pal_jorgensen@ntnu.no ev Keywords: Self-rated health, awareness, hypothyroidism, diabetes, hypertension. Word count: 3359 w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 2 of 22 ABSTRACT Objective To explore if awareness versus unawareness of thyroid dysfunction, diabetes mellitus or hypertension is associated with self-rated health. Design Large-scale, cross sectional population based study. The association between thyroid function, diabetes mellitus, and blood pressure and self-rated health was explored by multiple rp Fo logistic regression analysis. Setting The second survey of the Nord-Trøndelag Health Study, HUNT2, 1995-97. Participants 33,734 persons aged 40-70 years. ee Primary outcome measures Logistic regression was used to estimate odds ratios for good rr self-rated health as a function of thyroid status, diabetes mellitus status and blood pressure status. ev Results Persons aware of their hypothyroidism, diabetes mellitus, or hypertension reported ie poorer self-rated health than individuals without such conditions. Women with unknown and w subclinical hypothyroidism reported better self-rated health than women with normal thyroid status. Both in women and men, unknown and probable diabetes, as well as unknown on mild/moderate hypertension was not associated with poorer health. Further, persons with unknown severe hypertension reported better health than normotensive persons. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Conclusions People with undiagnosed, but prevalent hypothyroidism, diabetes mellitus, and hypertension often have good self-rated health, whilst when aware of their diagnoses, they report reduced self-rated health. Use of screening, more sensitive tests, and widened diagnostic criteria might have a negative effect on perceived health in the population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 2 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 3 of 43 BMJ Open Page 3 of 22 STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths • Sample from a large-scale, general population • High-prevalent diseases under study; ensuring statistical power in subgroup analyses Limitations rp Fo • Study mainly based on self-reported data • Cross-sectional study; susceptibility to confounding and impossibility to assume causal relationships INTRODUCTION ev rr ee Guidelines for prevention and treatment have been developed for most high prevalent diseases in western countries aiming for reduction of morbidity and mortality by interventions mainly in primary health care (PHC). w ie In the society there seems to be an increasing conviction of achievable zero-vision regarding on risks and diseases. Part of the strategy is to detect risk factors and pre-diseases in even earlier stages. From a secondary or tertiary health care level, this might seem reasonable since ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 intervention on many individuals with specific risk factors presumably can prevent or delay disease or progression of disease. Further, health authorities and hospital clinicians regularly raise concern of the lack of detection of risk factors, of subclinical conditions and of achieving treatment goals.[1-7] Norwegian studies have shown that guidelines are often difficult to implement and adhere to in PHC.[8 9] According to guidelines, most individuals would be defined as at risk and resources needed to handle this appropriately could destabilize the entire health care system.[10-12] An American review pointed out knowledge, attitude, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 4 of 22 and behaviour as barriers of physician’s adherence to clinical guidelines.[13] In an already complex and busy PHC-setting, one might expect that resources used for disease prevention and case finding have to compete with resources for handling acknowledged disease. Also, physicians might want to avoid increasing disease related burden for patients, in line with the old wisdom; “primum non nocere”.[14] Thus the risk and disease zero-visions in society and among politicians are seldom shared by PHC professionals. rp Fo When guidelines, mainly based on research from high risk hospital populations, are applied on low risk populations in PHC, more healthy individuals are identified as being at risk or are given diagnoses. Also the widened inclusion criteria for diagnoses in general and use of more ee sensitive tests contribute to define more individuals at risk or as unhealthy.[15] Possible undesirable outcomes of such strategies remain unclear. rr Self-rated health (SRH) is a valid and widely used measure of general health in epidemiologic ev research.[16-19] It is associated with several clinical conditions often seen in PHC, with ie recovery [20-23] and is found to predict morbidity, sick leave, and disability pension,[24 25] as well as mortality.[26-28] The majority of studies describing association between labelling w of disease per se and SRH have focused on arterial hypertension.[29-32] However, one study on has indicated reduced SRH among individuals labelled with thyroid dysfunctions.[33] ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The aim of this study was to investigate whether persons’ awareness versus unawareness of thyroid dysfunction, diabetes mellitus, or hypertension was associated with their SRH, as reported in a population-based health study in Norway. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 4 of 43 Page 5 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 5 of 22 METHODS Study population The data sample in this study stem from the second wave of the Nord-Trøndelag Health Study (HUNT2) conducted in 1995-97 in the county of Nord-Trøndelag, Norway. All individuals aged 20 years and older, living in the county, were invited (94,194 individuals). In all, 66.7% rp Fo of men (n=30,860) and 75.5% of women (n=35,280) participated. The survey consisted of both questionnaires and measurements, and is described previously in detail.[34 35] In our study we included answers from the main questionnaire and the baseline measurements for persons aged 40-70 years. The age span was chosen because thyroid stimulating hormone ee (TSH) was analysed in all women and in 50% of men at this age, of a rather low disease rr burden in people younger than 40 years, and of a lower attendance rate under and above this age span. A total of 24,950 individuals had TSH measurements and answered thyroid ev questions, thus were eligible for analysis on thyroid dysfunction, whilst in the analysis of ie diabetes mellitus and blood pressure, 33,734 individuals were included in all. Self-rated health w on The first question in the main questionnaire in HUNT2, answered before attending the examination stations, was “How is your health at the moment?”, with answer alternatives; ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 “very good”, “good”, “not so good”, and “poor”. This short version of SRH measure is shown to be a valid predictor of mortality. [18 28 36 37] We dichotomized the answers into “good” (very good, good) and “poor” (not so good, poor). Dichotomization of multinomial SRH is commonly performed, and has been validated by Manor et. al.[38] Thyroid function For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 6 of 22 The participants answered questions on history of hypo- and hyperthyroidism, goitre, other thyroid diseases, and treatment with thyroxin, radio-iodine, surgery, or thyreostatic medication. Serum TSH and free T4 were analysed at the Hormone laboratory, Aker University Hospital, Norway. The laboratory reference value for TSH, as defined prior to the survey, was 0.2-4.5 rp Fo mU/L and for free T4 8.0-20.0 pmol/L. If TSH was <0.2 mU/L or >4.0 mU/L, and/or if the participant reported any thyroid disease, serum free T4 was also measured.[39] Individuals reporting no previous thyroid disease and having TSH within reference range were categorized as “no thyroid disease” and chosen as reference category. No previous ee thyroid disease combined with TSH >4.5 mU/L and free T4 <8.0 pmol/L was defined as rr unknown hypothyroidism. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 8.0 – 20.0 pmol/L was defined as subclinical hypothyroidism. Individuals reporting ev hypothyroidism and use of thyroxin were classified as having known hypothyroidism, ie regardless of the TSH and T4 levels. Affirmative answers to other thyroid related questions or measures outside reference range in the remainders were classified as other thyroid dysfunction. ly on Diabetes mellitus w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Diabetes mellitus was assessed through self-report and blood samples. Serum glucose was analysed at Levanger Hospital, Norway. Those reporting no diabetes and having normal glucose levels (<5.5 mmol/L) were classified as “no diabetes” and were chosen as reference category. No self-reported diabetes and non-fasting glucose >11.0 mmol/L was categorized as unknown diabetes, whereas no diabetes and non-fasting glucose 5.5-11.0 mmol/L was For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 6 of 43 Page 7 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 7 of 22 categorized as probable diabetes. Self-reported diabetes was classified as known diabetes regardless of the glucose level. Blood pressure In the questionnaire participants were asked about the doctor’s advice after the latest blood pressure measurement prior to participation in HUNT. The answer categories were: “no rp Fo follow-up and no medication necessary”, “recommended follow-up examination but not to take medicine”, “start or continue taking medicine for high blood pressure”, or “never measured”. At HUNT2, mean systolic and mean diastolic arterial blood pressure (BP) of measurement 2 and 3 was categorized into normal (systolic (s) BP < 140 mmHg and diastolic ee (d) BP < 90 mmHg), mild hypertension (sBP 140-159 mmHg and dBP <100 mmHg or sBP rr <160 mmHg and dBP 90-99 mmHg), moderate hypertension (sBP 160-179 mmHg and dBP <109 mmHg or sBP <180 mmHg and dBP 100-109 mmHg), and severe hypertension ev (sBP>180 mmHg or dBP>110 mmHg). We constructed a new variable to define ie normotensive (reference), unknown mild- and moderate hypertensive, unknown severe hypertensive, and known hypertensive persons on the basis of self-report and measures. w Statistical analysis on The descriptive analyses of the study population were stratified by gender, and we used chi- ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 square tests to examine any difference in proportions of SRH between the independent variables. Gender-stratified multiple logistic regression were used to estimate odds ratio (OR) with 95% confidence intervals (CI) for good SRH, as a function of thyroid status, diabetes mellitus status and blood pressure status, in separate unadjusted, age adjusted, and multi adjusted analyses for each condition. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 8 of 22 Age, smoking, alcohol consumption, body mass index (BMI), working- and educational status, and self-reported limiting long-term illness or injury are associated with SRH[40] and the diseases under study, but likely not affected by SRH or the diseases. Hence, these variables were included, a priori, as confounders in the models. Age was categorized into age groups; 40-49 years, 50-59 years, and 60-70 years. Smoking status was categorized into never smoked daily, previous daily smoker, and current daily smoker. Alcohol units (AU) were rp Fo defined as number of glasses of wine, beer or liquor. Those reporting to be teetotalers or to have alcohol intake less than four times a month or less than seven AU per two weeks were categorized as low consumers, those reporting drinking five to eight times a month or 8-14 ee AU per two weeks as moderate consumers, and those drinking more often than eight times a month or more than 14 AU as heavy consumers. BMI (kg/m2) was calculated of measured rr height and weight and categorized according to The World Health Organization’s (WHO) definition; underweight (18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0- ev 29.9 kg/m2) and obese (>30.0 kg/m2). People reporting paid- or self-employed work were ie classified as working, otherwise as not working. Educational level was categorized into <10 w years, 10-12 years and >12 years. We chose affirmative answer to the question “Do you suffer from any long-term illness or injury (at least one year) of a physical or psychological nature on that impairs your functioning in your everyday life?” to represent all relevant chronic medical conditions that could confound the results. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 To examine whether the association of the three disease statuses with SRH differed by categories of the other independent variables, we used likelihood ratio-tests with p-value for statistical interaction. We tested for multicollinearity between the independent variables, by linear regression. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 8 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 9 of 43 BMJ Open Page 9 of 22 In an additional analysis, the association between SRH and having had one or more medical consultations during the last year was investigated by logistic regression models, stratified by gender, both in the total study population and after exclusion of persons with diagnoses under study. All analyses were preformed with IBM SPSS Statistics version 20 for windows. rp Fo The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. RESULTS ee In all age categories, a higher proportion of men than women reported good SRH (p<0.001), and in both sexes the proportion reporting good SRH declined by age (p<0.002) (Table 1). rr The proportion reporting good SRH was lower in overweight, obese, and underweight ev women, than in normal weight women (p<0.001). In men the proportion reporting good SRH declined between the normal weight group to overweight-, obese-, and underweight group ie (p<0.001). In previous and current female smokers, a lower proportion reported good SRH w compared to non smokers (p<0.001). In men, the proportion reporting good SRH was higher among non smokers than among previous and current smokers (p<0.001), whereas there was on no difference between previous and current smokers. The proportion reporting good SRH was ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 higher in moderate and heavy alcohol consumers than in low consumers, increased with education and was higher for participants in paid work (p<0.001). Underweight men and persons with “any long-term impairment” had the lowest proportion reporting good SRH of all groups. The proportion reporting good SRH in the overall HUNT 2 study population differed from the proportions reported in persons without thyroid disease and normotensive persons (p<0.01), but not from persons without diabetes mellitus. However, the absolute differences were small. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 10 of 22 There was no multicollinearity between the independent variables. Thyroid function Thyroid dysfunctions, both known and unknown were more often observed among women than among men (p<0.001) (Table 1). Women with known hypothyroidism had lower odds of rp Fo reporting good SRH (OR 0.49 (95% CI 0.41 to 0.59) compared to women without thyroid disease in the adjusted analyses, but women with unknown or subclinical hypothyroidism had 84% and 48% higher odds, respectively, of reporting good SRH compared to the odds of women without thyroid disease (Table 2). The association between thyroid function and SRH ee was basically unchanged after inclusion of confounder variables. Corresponding, but nonsignificant associations were found among men. ev Diabetes mellitus rr The prevalence of unknown, probable, and known diabetes was slightly higher in men than in ie women (p<0.001) (Table 1). Women with known diabetes mellitus had lower odds of good w SRH than those without diabetes in the adjusted analyses; OR 0.53 (95% CI 0.41 to 0.69), whereas in women with unknown or possible diabetes mellitus, the odds of good SRH were on similar to the odds among persons without diabetes, in the adjusted analyses (Table 2). In the adjusted analyses, the association between unknown and probable diabetes mellitus with poor ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 SRH, found in the crude analyses, disappeared when age was included in the model in women and men, but also by inclusion of working status alone in women. In men, the association of diabetes status with SRH differed by levels of education. Among men without higher education (12 years or less), the odds of good SRH were as in the main-effect model (Table 2). However in men with higher education, the ORs of good SRH were barely significantly lower among men with unknown diabetes (OR 0.29 (95% CI 0.09-1.00)) and among men with For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 10 of 43 Page 11 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 11 of 22 possible diabetes (OR 0.79 (95% CI 0.63-1.00)) compared to men without diabetes. Among men with known diabetes in this stratum, the OR of good SRH was 0.31 (95% CI 0.17-0.54) compared to men without diabetes. Blood pressure The prevalence of unknown mild and moderate hypertension was higher in men than in rp Fo women (p<0.001). Unknown severe hypertension and known hypertension were equally distributed between women and men (Table 1). Women with known hypertension had lower odds of reporting good SRH than normotensive women, in the adjusted analyses. The figures were similar in men (Table 2). In contrast; compared to normotensive women, those with ee unknown severe hypertension had 52 % higher odds of reporting good SRH, with similar rr figures in men. Persons with unknown mild and moderate hypertension reported good SRH similar to the normotensive ones. Adjusted for age, the association between unknown mild ev and moderate hypertension and poor SRH disappeared, simultaneously; unknown severe ie hypertension became associated with good SRH in women. In men, age had to be added along with either education- or working status to achieve the latter association. Additional analyses w Women with poor SRH had more than six times the odds of those with good SRH to have had on a medical consultation during the last year; OR 6.29 (95% CI 5.47 to 7.22). For men the ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 corresponding OR was 5.53 (95% CI 4.86 to 6.29). After exclusion of persons with diagnosed thyroid disease, diabetes mellitus, known hypertension, and “any long-term disease”, the corresponding OR was 3.71 (95% CI 2.90 to 4.73), with similar figures in men. DISCUSSION This large population-based study showed that persons with known thyroid dysfunction, diabetes mellitus, and hypertension were less likely to report good SRH than those without For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 12 of 22 such conditions. Less expected, persons with unknown and subclinical hypothyroidism were more likely to report good SRH than those without thyroid disease. Similarly, those with unknown severe hypertension were more likely to report good SRH, compared to persons with normal blood pressure. In general, persons with unknown diabetes and unknown mild/moderate hypertension, reported good health, just like the reference group. rp Fo In general, of the confounders, age seemed to influence the association between disease statuses and SRH most when adjusted for. Age was found to explain the association of poor SRH with unknown and probable diabetes, and with unknown mild and moderate hypertension. In women, age even contributed to an association between unknown severe ee hypertension and good SRH. There seemed to be a linear decrease by age categories in the association with good SRH. The way age is known to be related to both disease and SRH makes these findings reasonable. ev rr Although both a qualitative and quantitative measure of association, the estimated ORs in our ie study will, if interpreted as relative risks, overestimate the case, because the prevalence of good SRH is high in all groups.[41] w The main strengths of this study were the numbers of participants, that the diseases we studied on were high-prevalent, and that we could assume representativeness to the general population ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 regarding the variables included. It is known that individuals with high burden of symptoms are less likely to attend surveys, but so far there has been little evidence that non-participation on this basis introduce substantial bias in associational studies.[42] We studied diseases with generally low symptom-burden, and expect selection bias to be negligible. The main limitation was possibly that we relied on self-reported data on both dependent and independent variables. The validity of self reported measures relevant for this study is For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 12 of 43 Page 13 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 13 of 22 questionable. However, if any, there should be a non-differential misclassification, that only should underestimate the associations found. There is always a possibility of residual confounding in non-randomized study designs, and due to the observational, cross-sectional design we neither can assume a causal relationship. Bias due to differential detection of disease in the study population could lead to a type 1 rp Fo error. Hypothyroidism and diabetes mellitus are often associated with vague symptoms such as tiredness and weakness. These symptoms are strongly associated with reduced SRH.[43] It is likely that presenting such symptoms for the GP would result in measurements of TSH, free T4, and serum glucose, thus reveal any related dysfunction. Low self-perceived health ee increases the probability to visit a GP.[44] The social security covers most costs related to rr clinical measurements and blood sampling in Norway, thus we expect GPs to have a low threshold to measure thyroid function, blood pressure or glucose levels. People who do not ev consult their GP will not have diseases with mild or no symptoms diagnosed, and their ie personality could be characterized by less worrying and more optimistic attitude to health being reflected in better SRH.[45] w On the other hand, the association between known disease and poor SRH could in fact be on explained physiologically due to the pathological effect of disease. Lack of corresponding ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 association between ignored, but prevalent disease and poor SRH is not in line with this hypothesis, rising question of a possible adverse effect of disease labelling. However, confounding by severity of disease cannot be ruled out. Due to low numbers of persons having unknown hypothyroidism and diabetes mellitus, the results should be interpreted with caution. On the other hand, there were high numbers in the For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 14 of 22 subclinical and probable groups, and analyses of these groups did not show any associations with poor SRH, also rising question of a possible disease labelling effect. The fact that the HUNT2 survey was carried out nearly 20 years ago raises a question of generalisability to today’s population. Stability of SRH over time has not been investigated in our study population, although investigated among adolescents.[46] We do not expect the rp Fo association between low burden- or subclinical disease with SRH to be time dependent to the extent that it would change our results considerably. Neither do we expect the changes in prevalence of most explanatory variables to influence the associations found. Consistent findings regarding unknown, subclinical, and probable disease, versus known ee disease, could indicate a potential adverse effect of disease labelling. Although early detection rr of disease is protective on morbidity and mortality for many diseases, low SRH is also shown to be associated morbidity and mortality.[25-27] This is an important aspect in the debate of presymptomatic case-finding. ie ev The BMJ's Too Much Medicine campaign aims to highlight the threat to human health posed w by overdiagnosis and the waste of resources on unnecessary care (http://www.bmj.com/toomuch-medicine). American data have shown that the majority of all health care includes on preference-sensitive and supply-sensitive services. The extent of these services varies greatly ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 without necessarily leading to better health.[47 48] A great deal of activity in such services is based on identifying subclinical disease. The negative health effect this might have, modulated through reduced SRH, can explain why population mortality is not reduced in areas with high frequency of diagnoses. Both public and academic debates are often characterised by the conviction that all medical treatment is efficient. Wennberg showed that a relatively small proportion of all medical For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 14 of 43 Page 15 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 15 of 22 treatment is indisputably good for health.[49] The concern for unrevealed risk factors and subclinical conditions might lead to unnecessary costly health care interventions, increase supply-sensitive services without positive health effect and have a negative influence on people’s general and self-perceived health causing more harm than good.[15] Of ethical reasons, the possible causal effect of disease labelling on SRH is impossible to rp Fo assess in a randomized controlled trial. Our study emphasizes the need for more prospective research to investigate potential health effects of disease labelling and early diagnosis. CONCLUSION ee Our data suggest that early identification of disease may imply a negative effect on SRH, and to the extent that SRH has been associated with greater mortality, this may lead to harm. rr However, as it is also known that diseases such as diabetes and hypertension also lead to ev increased mortality when detected after cardiovascular and metabolic complications have developed, it remains to be seen if an early identification or a late detection strategy would ie provide optimal health for the population. FOOTNOTES w Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 16 of 22 Contributors All authors meet the four criteria for authorship recommended by the International Committee of Medical Journal Editors. SF, AL, and SK have been active supervisors in study conception, design, conduct, interpretation, and reporting. PJ analyzed the data and drafted the manuscript. Critical revisions were done by all supervisors and all authors approved the final version of the manuscript. SF, AL, SK and PJ are joint guarantors. Acknowledgements The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology NTNU), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. The authors would like to thank Bjørn Olav Åsvold for his contribution in planning of the thyroid-part of the study. rp Fo Transparency declaration PJ affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there were no discrepancies from the study as planned. Ethical approval The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. ee Funding No external funding. PJ received a PhD-grant, funded by the Norwegian University of Science and Technology, NTNU. rr Data sharing statement No additional data available. w ie ev ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 16 of 43 Page 17 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 17 of 22 1. Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ 2005;31(4):564-71 doi: 10.1177/0145721705279050[published Online First: Epub Date]|. 2. Borzecki AM, Wong AT, Hickey EC, et al. Hypertension control: how well are we doing? Arch Intern Med 2003;163(22):2705-11 doi: 10.1001/archinte.163.22.2705[published Online First: Epub Date]|. 3. Andros V, Egger A, Dua U. Blood pressure goal attainment according to JNC 7 guidelines and utilization of antihypertensive drug therapy in MCO patients with type 1 or type 2 diabetes. J Manag Care Pharm 2006;12(4):303-9 4. Liddy C, Singh J, Hogg W, et al. Quality of cardiovascular disease care in Ontario, Canada: missed opportunities for prevention - a cross sectional study. BMC Cardiovasc Disord 2012;12:74 doi: 10.1186/1471-2261-12-74[published Online First: Epub Date]|. 5. Huebschmann AG, Mizrahi T, Soenksen A, et al. Reducing clinical inertia in hypertension treatment: a pragmatic randomized controlled trial. J Clin Hypertens (Greenwich) 2012;14(5):322-9 doi: 10.1111/j.1751-7176.2012.00607.x[published Online First: Epub Date]|. 6. Alkerwi Aa, Pagny S, Lair M-L, et al. Level of Unawareness and Management of Diabetes, Hypertension, and Dyslipidemia among Adults in Luxembourg: Findings from ORISCAV-LUX Study. PLoS One 2013;8(3):e57920 doi: 10.1371/journal.pone.0057920[published Online First: Epub Date]|. 7. Khan N, Chockalingam A, Campbell NR. Lack of control of high blood pressure and treatment recommendations in Canada. Can J Cardiol 2002;18(6):657-61 8. Hetlevik I, Holmen J, Kruger O, et al. Fifteen years with clinical guidelines in the treatment of hypertension - still discrepancies between intentions and practice. Scand J Prim Health Care 1997;15(3):134-40 doi: Doi 10.3109/02813439709018503[published Online First: Epub Date]|. 9. Hetlevik I, Holmen J, Midthjell K. Treatment of diabetes mellitus - physicians' adherence to clinical guidelines in Norway. Scand J Prim Health Care 1997;15(4):193-97 doi: Doi 10.3109/02813439709035027[published Online First: Epub Date]|. 10. Petursson H, Getz L, Sigurdsson JA, et al. Current European guidelines for management of arterial hypertension: Are they adequate for use in primary care? Modelling study based on the Norwegian HUNT 2 population. BMC Fam Pract 2009;10 doi: Artn 70 Doi 10.1186/1471-229610-70[published Online First: Epub Date]|. 11. Petursson H, Getz L, Sigurdsson JA, et al. Can individuals with a significant risk for cardiovascular disease be adequately identified by combination of several risk factors? Modelling study based on the Norwegian HUNT 2 population. J Eval Clin Pract 2009;15(1):103-09 doi: DOI 10.1111/j.1365-2753.2008.00962.x[published Online First: Epub Date]|. 12. Getz L, Sigurdsson JA, Hetlevik I, et al. Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. Br Med J 2005;331(7516):551-54A doi: DOI 10.1136/bmj.38555.648623.8F[published Online First: Epub Date]|. 13. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 1999;282(15):1458-65 doi: 10.1001/jama.282.15.1458[published Online First: Epub Date]|. 14. Smith CM. Origin and uses of primum non nocere--above all, do no harm! J Clin Pharmacol 2005;45(4):371-7 doi: 10.1177/0091270004273680[published Online First: Epub Date]|. 15. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. Br Med J 2012;344 doi: Artn E3502 Doi 10.1136/Bmj.E3502[published Online First: Epub Date]|. 16. Miilunpalo S, Vuori I, Oja P, et al. Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 18 of 22 working-age population. J Clin Epidemiol 1997;50(5):517-28 doi: S0895-4356(97)00045-0 [pii][published Online First: Epub Date]|. 17. Meurer LN, Layde PM, Guse CE. Self-rated health status: a new vital sign for primary care? WMJ 2001;100(7):35-9 18. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-5 doi: 59/5/342 [pii] 10.1136/jech.2004.021204[published Online First: Epub Date]|. 19. Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24(3):218-24 20. Bopp M, Braun J, Gutzwiller F, et al. Health risk or resource? Gradual and independent association between self-rated health and mortality persists over 30 years. PLoS One 2012;7(2):e30795 doi: 10.1371/journal.pone.0030795 PONE-D-11-20499[pii][published Online First: Epub Date]|. 21. Moller L, Kristensen TS, Hollnagel H. Self rated health as a predictor of coronary heart disease in Copenhagen, Denmark. J Epidemiol Community Health 1996;50(4):423-8 22. Kaplan GA, Goldberg DE, Everson SA, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol 1996;25(2):259-65 doi: Doi 10.1093/Ije/25.2.259[published Online First: Epub Date]|. 23. Krokstad S, Johnsen R, Westin S. Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol 2002;31(6):1183-91 doi: 10.1093/ije/31.6.1183[published Online First: Epub Date]|. 24. Halford C, Wallman T, Welin L, et al. Effects of self-rated health on sick leave, disability pension, hospital admissions and mortality. A population-based longitudinal study of nearly 15,000 observations among Swedish women and men. BMC Public Health 2012;12:1103 doi: 10.1186/1471-2458-12-1103[published Online First: Epub Date]|. 25. Latham K, Peek CW. Self-Rated Health and Morbidity Onset Among Late Midlife US Adults. J Gerontol B-Psychol 2013;68(1):107-16 doi: DOI 10.1093/geronb/gbs104[published Online First: Epub Date]|. 26. Benyamini Y, Idler EL. Community studies reporting association between self-rated health and mortality - Additional studies, 1995 to 1998. Res Aging 1999;21(3):392-401 doi: Doi 10.1177/0164027599213002[published Online First: Epub Date]|. 27. Nielsen AB, Siersma V, Hiort LC, et al. Self-rated general health among 40-year-old Danes and its association with all-cause mortality at 10-, 20-, and 29 years' follow-up. Scand J Public Health 2008;36(1):3-11 doi: 10.1177/1403494807085242[published Online First: Epub Date]|. 28. Schou MB, Krokstad S, Westin S. How is self-rated health associated with mortality? Tidsskr Nor Laegeforen 2006;126(20):2644-7 29. Barger SD, Muldoon MF. Hypertension labelling was associated with poorer self-rated health in the Third US National Health and Nutrition Examination Survey. J Hum Hypertens 2006;20(2):117-23 doi: 10.1038/sj.jhh.1001950[published Online First: Epub Date]|. 30. Bloom JR, Monterossa S. Hypertension Labeling and Sense of Well-Being. Am J Public Health 1981;71(11):1228-32 doi: Doi 10.2105/Ajph.71.11.1228[published Online First: Epub Date]|. 31. Moum T, Naess S, Sorensen T, et al. Hypertension Labeling, Life Events and Psychological WellBeing. Psychol Med 1990;20(3):635-46 32. Macdonald LA, Sackett DL, Haynes RB, et al. Labelling in hypertension: A review of the behavioural and psychological consequences. J Chronic Dis 1984;37(12):933-42 doi: http://dx.doi.org/10.1016/0021-9681(84)90070-5[published Online First: Epub Date]|. 33. Bianchi GP, Zaccheroni V, Solaroli E, et al. Health-related quality of life in patients with thyroid disorders - A study based on Short-Form 36 and Nottingham Health Profile Questionnaires. Qual Life Res 2004;13(1):45-54 doi: Doi 10.1023/B:Qure.0000015315.35184.66[published Online First: Epub Date]|. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 18 of 43 Page 19 of 43 BMJ Open Study population Page 19 of 22 Men (n=16,220) Women (n=17,514) 34. Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag Health Study 1995-97 (HUNT 2): objectives, methods, and participation. Norsk Epidemiol 2003 13 (1 ):19-32 35. Krokstad S, Langhammer A, Hveem K, et al. Cohort Profile: The HUNT Study, Norway. Int J Epidemiol 2012 doi: dys095 [pii] 10.1093/ije/dys095[published Online First: Epub Date]|. 36. Schnittker J, Bacak V. The Increasing Predictive Validity of Self-Rated Health. PLoS One 2014;9(1):e84933 doi: 10.1371/journal.pone.0084933[published Online First: Epub Date]|. 37. Idler EL, Benyamini Y. Self-rated health and mortality: A review of twenty-seven community studies. J Health Soc Behav 1997;38(1):21-37 doi: Doi 10.2307/2955359[published Online First: Epub Date]|. 38. Manor O, Matthews S, Power C. Dichotomous or categorical response? Analysing self-rated health and lifetime social class. Int J Epidemiol 2000;29(1):149-57 doi: Doi 10.1093/Ije/29.1.149[published Online First: Epub Date]|. 39. Bjoro T, Holmen J, Kruger O, et al. Prevalence of thyroid disease, thyroid dysfunction and thyroid peroxidase antibodies in a large, unselected population. The Health Study of Nord-Trondelag (HUNT). Eur J Endocrinol 2000;143(5):639-47 doi: 1430639 [pii][published Online First: Epub Date]|. 40. Giron P. Determinants of self-rated health in Spain: differences by age groups for adults. Eur J Public Health 2012;22(1):36-40 doi: 10.1093/eurpub/ckq133[published Online First: Epub Date]|. 41. Davies HTO, Crombie IK, Tavakoli M. When can odds ratios mislead? Br Med J 1998;316(7136):989-91 42. Langhammer A, Krokstad S, Romundstad P, et al. The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms. BMC Med Res Methodol 2012;12:143 doi: 10.1186/1471-2288-12-143[published Online First: Epub Date]|. 43. Molarius A, Janson S. Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol 2002;55(4):364-70 doi: http://dx.doi.org/10.1016/S0895-4356(01)00491-7[published Online First: Epub Date]|. 44. Hansen AH, Halvorsen PA, Ringberg U, et al. Socio-economic inequalities in health care utilisation in Norway: a population based cross-sectional survey. BMC Health Serv Res 2012;12:336 doi: 10.1186/1472-6963-12-336[published Online First: Epub Date]|. 45. Vingilis E, Wade T, Seeley J. Predictors of adolescent health care utilization. J Adolesc 2007;30(5):773-800 doi: http://dx.doi.org/10.1016/j.adolescence.2006.10.001[published Online First: Epub Date]|. 46. Breidablik H-J, Meland E, Lydersen S. Self-rated health during adolescence: stability and predictors of change (Young-HUNT study, Norway). The European Journal of Public Health 2009;19(1):73-78 doi: 10.1093/eurpub/ckn111[published Online First: Epub Date]|. 47. Welch HG, Sharp SM, Gottlieb DJ, et al. Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries. JAMA 2011;305(11):1113-8 doi: 10.1001/jama.2011.307[published Online First: Epub Date]|. 48. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138(4):288-98 49. Wennberg JE. Tracking medicine. A researcher’s quest to understand health care. Oxford: Oxford University Press, 2010. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 20 of 43 Page 20 of 22 n % SRH good (%) n % SRH good (%) 40-50 years 7058 40.3 77.6 6517 40.2 81.7 51-60 years 5709 32.6 64.4 5328 32.8 72.1 61-70 years 4747 27.1 56.6 4375 27.0 59.6 6821 0.6 58.4 4804 0.2 42.9 7026 39.1 72.8 8694 29.7 75.3 3489 40.3 68.5 2635 53.8 73.6 104 20.0 56.5 35 16.3 64.8 6973 40.1 70.3 4849 30.1 80.0 4651 26.7 68.0 6105 37.9 69.8 5763 33.1 64.3 5172 32.0 69.1 14888 88.7 11488 73.2 71.0 1471 8.8 76.8 2839 18.1 78.7 430 2.6 76.3 1375 8.8 78.3 < 10 years 8133 48.5 60.5 5711 36.5 63.1 10 – 12 years 5682 33.9 72.8 6615 42.2 76.0 > 12 years 2962 17.7 80.0 3339 21.3 84.7 Yes 11539 67.2 77.1 12309 77.1 79.9 No 5627 32.8 49.0 3665 22.9 49.2 Age group BMI (kg/m2) <18,5 18,5-24,9 25,0-29,9 >30 (0.4% missing) Smoking status Previous daily smoker (0.7% missing) None to low intake High intake 66.7 w Moderate intake ie Alcohol use ev Daily smoker rr Never smoked daily ee rp Fo (3.7% missing) Educational level ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 (3.8% missing) Employed (1.8% missing) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 21 of 43 BMJ Open Page 21 of 22 Any long-term impairment No 10348 59.1 85.9 9912 63.0 88.7 Yes 6275 35.8 39.8 5829 37.0 46.0 14373 86.2 68.7 7804 94.3 72.1 Unknown hypothyroidism 107 0.6 78.5 16 0.2 68.8 Subclinical hypothyroidism 466 2.8 75.0 150 1.8 66.4 Known hypothyroidism 858 5.1 48.9 124 1.5 58.1 Other thyroid dysfunction 872 5.2 61.4 180 2.2 56.2 64.6 69.4 9196 56.9 74.6 (4.1% missing) Thyroid function No thyroid disease rp Fo (1.3% missing) Diabetes mellitus No diabetes ee 11279 rr 0.3 395 2.3 Normotensive 9135 52.6 ie 6858 Unknown mild/moderate hypertension 4473 25.8 5343 403 2.4 70.7 349 2.2 73.8 3327 19.2 54.0 3498 21.8 59.6 34332 97.3 70.3 Unknown diabetes Probable diabetes Known diabetes (0.4% missing) 46 52.2 88 0.5 67.8 5728 32.8 65.9 6392 39.6 71.5 43.1 482 3.0 49.5 72.4 42.7 77.5 67.9 33.3 74.7 ev Blood pressure status Known hypertension Overall study population, HUNT2 ly (0.9% missing) on Unknown severe hypertension w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 30378 98.4 Table 1. Good self-rated health (SRH) by sex and characteristics of the study population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml 74.9 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 22 of 43 Page 22 of 22 Table 2. The association between self-rated health and thyroid function, diabetes mellitus and blood pressure. Odds ratio (OR) of good self-rated health and 95% confidence intervals (95% CI), crude, age adjusted, and adjusted for age, other long-term illness or injury that impairs function in everyday life, smoking habits, alcohol use, educational level, work status and body mass index. Cases with missing data were excluded from the analyses. Women OR (95% CI) Crude n Age adjusted Men Multiple adjusted n OR (95% CI) Crude Age adjusted Multiple adjusted Thyroid function rp Fo No thyroid dysfunction Unknown hypothyroidism Subclinical hypothyroidism 1247 6 92 394 718 Known hypothyroidism 729 Other thyroid dysfunction 704 1.00 1.00 1.00 5 0.85 (0.30- 0.92 (0.31- 1.28 (0.351.66 (1.05- 2.00 (1.25- 1.84 (1.024.65) 14 2.45) 3.19) 3.33) 2.64) 2.72) 9946 39 Known diabetes 318 1.00 1.00 0.85 (0.80- 0.94 (0.88- 1.01 (0.92- 575 0.86 (0.80- 0.94 (0.88- 0.99 (0.919 0.92) 1.08) 1.01) 0.91) 1.10) 1.01) w 4797 846 1.00 1.00 1.00 4 0.72 (0.46- 0.88 (0.55- 1.03 (0.590.48 (0.27- 0.61 (0.34- 0.66 (0.3282 1.13) 1.10) 1.81) 0.86) 1.37) 1.39) 1.00 ie Probable diabetes ev rr Unknown diabetes 1.00 1.13 (0.721.37 (1.10- 1.49 (1.20- 1.48 (1.13- 128 0.77 (0.540.88 (0.62- 1.76) 1.08) 1.85) 1.94) 1.69) 1.24) 107 0.69 (0.440.54 (0.370.44 (0.38- 0.48 (0.41- 0.49 (0.410.63 (0.43- 1.09) 163 0.77) 0.55) 0.59) 0.50) 0.91) 0.58 (0.410.50 (0.370.72 (0.63- 0.77 (0.67- 0.77 (0.650.52 (0.38- 0.84) 0.67) 0.89) 0.93) 0.83) 0.71) Diabetes mellitus No diabetes 1.00 1.00 ee 0.33 (0.27- 0.42 (0.34- 0.53 (0.41- 395 0.33 (0.28- 0.42 (0.35- 0.55 (0.430.70) 0.40) 0.41) 0.51) 0.69) 0.51) Blood pressure 8180 Unknown mild/moderate hypertension 3787 Unknown severe hypertension 2745 Known hypertension 325 637 1.00 8 0.81 (0.75- 1.01 (0.93- 1.10 (0.990.86 (0.79483 0.93) 1.09) 0.87) 1.22) 7 0.92 (0.74- 1.34 (1.08- 1.52 (1.140.85 (0.77308 1.08) 1.15) 1.68) 2.02) 1.00 1.00 1.00 1.00 1.00 ly No hypertension on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1.01 (0.92- 1.01 (0.921.10) 1.12) 1.27 (0.99- 1.48 (1.091.62) 2.02) 0.45 (0.41- 0.59 (0.54- 0.69 (0.61- 311 0.43 (0.39- 0.54 (0.50- 0.64 (0.570.49) 0.60) 0.72) 8 0.47) 0.65) 0.77) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 23 of 43 BMJ Open Page 1 of 19 Disease ignorance and self-rated health, any relationship? The HUNT Study, a cross-sectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad, Siri Forsmo Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway Pål Jørgensen PhD Candidate HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Arnulf Langhammer Professor, Head of HUNT Databank HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Steinar Krokstad Professor, Head of HUNT Research Center Department of Public Health and General Practice, Norwegian University of Science and Technology, Siri Forsmo Professor, Head of Department rr ee rp Fo Correspondence to: P Jørgensen pal_jorgensen@ntnu.no Field Code Changed ev Keywords: Self-rated health, awareness, hypothyroidism, diabetes, hypertension. Word count: 2995 3359 w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 2 of 19 ABSTRACT Objective To explore if awareness versus unawareness of thyroid dysfunction, diabetes mellitus or hypertension is associated with self-rated health. Design Large-scale, cross sectional population based study. The association between thyroid rp Fo function, diabetes mellitus, and blood pressure and self-rated health was explored by multiple logistic regression analysis. Setting The second survey of the Nord-Trøndelag Health Study, HUNT2, 1995-97. Participants 33,734 persons aged 40-70 years. ee Primary outcome measures Logistic regression was used to estimate odds ratios for good rr self-rated health as a function of thyroid status, diabetes mellitus status and blood pressure status. ev Results Persons aware of their hypothyroidism, diabetes mellitus, or hypertension reported ie poorer self-rated health than individuals without such conditions. Women with unknown and subclinical hypothyroidism reported better self-rated health than women with normal thyroid w status. Both in women and men, unknown and probable diabetes, as well as unknown mild/moderate hypertension was not associated with poorer health. Further, persons with on unknown severe hypertension reported better health than normotensive persons. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Conclusions People with undiagnosed, but prevalent hypothyroidism, diabetes mellitus, and hypertension often have good self-rated health, whilst when aware of their diagnoses, they report reduced self-rated health. Use of screening, more sensitive tests, and widened diagnostic criteria might have a negative effect on perceived health in the population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 24 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 25 of 43 Page 3 of 19 STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths • Sample from a large-scale, general population • High-prevalent diseases under study; ensuring statistical power in subgroup analyses rp Fo Limitations • Study mainly based on self-reported data • Cross-sectional study; susceptibility to confounding and impossibility to assume causal relationships ev rr INTRODUCTION ee Guidelines for prevention and treatment have been developed for most high prevalent diseases in western countries aiming for reduction of morbidity and mortality by interventions mainly in primary health care (PHC). w ie In the society there seems to be an increasing conviction of achievable zero-vision regarding risks and diseases. Part of the strategy is to detect risk factors and pre-diseases in even earlier on stages. From a secondary or tertiary health care level, this might seem reasonable since intervention on many individuals with specific risk factors presumably can prevent or delay ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BMJ Open disease or progression of disease. Further, health authorities and hospital clinicians regularly raise concern of the lack of detection of risk factors, of subclinical conditions and of achieving treatment goals.[1-7] Norwegian studies have shown that guidelines are often difficult to implement and adhere to in PHC.[8 9] According to guidelines, most individuals would be defined as at risk and resources needed to handle this appropriately could destabilize the entire health care system.[10-12] An American review pointed out knowledge, attitude, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 4 of 19 and behaviour as barriers of physician’s adherence to clinical guidelines.[13] In an already complex and busy PHC-setting, one might expect that resources used for disease prevention and case finding have to compete with resources for handling acknowledged disease. Also, physicians might want to avoid increasing disease related burden for patients, in line with the old wisdom; “primum non nocere”.[14] Thus the risk and disease zero-visions in society and rp Fo among politicians are seldom shared by PHC professionals. When guidelines, mainly based on research from high risk hospital populations, are applied on low risk populations in PHC, more healthy individuals are identified as being at risk or are ee given diagnoses. Also the widened inclusion criteria for diagnoses in general and use of more sensitive tests contribute to define more individuals at risk or as unhealthy.[15] Possible rr undesirable outcomes of such strategies remain unclear. Self-rated health (SRH) is a valid and widely used measure of general health in epidemiologic ev research.[16-19] It is associated with several clinical conditions often seen in PHC, with recovery [20-23] and is found to predict morbidity, sick leave, and disability pension,[24 25] ie as well as mortality.[26-28] The majority of studies describing association between labelling w of disease per se and SRH have focused on arterial hypertension.[29-32] However, one study has indicated reduced SRH among individuals labelled with thyroid dysfunctions.[33] on The aim of this study was to investigate whether persons’ awareness versus unawareness of ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 thyroid dysfunction, diabetes mellitus, or hypertension was associated with their SRH, as reported in a population-based health study in Norway. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 26 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 27 of 43 Page 5 of 19 METHODS Study population The data sample in this study stem from the second wave of the Nord-Trøndelag Health Study (HUNT2) conducted in 1995-97 in the county of Nord-Trøndelag, Norway. All individuals rp Fo aged 20 years and older, living in the county, were invited (94,194 individuals). In all, 66.7% of men (n=30,860) and 75.5% of women (n=35,280) participated. The survey consisted of both questionnaires and measurements, and is described previously in detail.[34 35] In our study we included answers from the main questionnaire and the baseline measurements for ee persons aged 40-70 years. The age span was chosen because thyroid stimulating hormone (TSH) was analysed in all women and in 50% of men at this age, of a rather low disease rr burden in people younger than 40 years, and of a lower attendance rate under and above this age span. A total of 24,950 individuals had TSH measurements and answered thyroid ev questions, thus were eligible for analysis on thyroid dysfunction, whilst in the analysis of diabetes mellitus and blood pressure, 33,734 individuals were included in all. w Self-rated health ie The first question in the main questionnaire in HUNT2, answered before attending the on examination stations, was “How is your health at the moment?”, with answer alternatives; “very good”, “good”, “not so good”, and “poor”. This short version of SRH measure is shown ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BMJ Open to be a valid predictor of mortality. [18 28 36 37] We dichotomized the answers into “good” (very good, good) and “poor” (not so good, poor). Dichotomization of multinomial SRH is commonly performed, and has been validated by Manor et. al.[38] Thyroid function For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 6 of 19 The participants answered questions on history of hypo- and hyperthyroidism, goitre, other thyroid diseases, and treatment with thyroxin, radio-iodine, surgery, or thyreostatic medication. Serum TSH and free T4 were analysed at the Hormone laboratory, Aker University Hospital, rp Fo Norway. The laboratory reference value for TSH, as defined prior to the survey, was 0.2-4.5 mU/L and for free T4 8.0-20.0 pmol/L. If TSH was <0.2 mU/L or >4.0 mU/L, and/or if the participant reported any thyroid disease, serum free T4 was also measured.[39] Individuals reporting no previous thyroid disease and having TSH within reference range ee were categorized as “no thyroid disease” and chosen as reference category. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 <8.0 pmol/L was defined as rr unknown hypothyroidism. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 8.0 – 20.0 pmol/L was defined as subclinical hypothyroidism. Individuals reporting ev hypothyroidism and use of thyroxin were classified as having known hypothyroidism, regardless of the TSH and T4 levels. Affirmative answers to other thyroid related questions or ie measures outside reference range in the remainders were classified as other thyroid dysfunction. on Diabetes mellitus w Diabetes mellitus was assessed through self-report and blood samples. Serum glucose was analysed at Levanger Hospital, Norway. Those reporting no diabetes and having normal ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 glucose levels (<5.5 mmol/L) were classified as “no diabetes” and were chosen as reference category. No self-reported diabetes and non-fasting glucose >11.0 mmol/L was categorized as unknown diabetes, whereas no diabetes and non-fasting glucose 5.5-11.0 mmol/L was For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 28 of 43 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 29 of 43 Page 7 of 19 categorized as probable diabetes. Self-reported diabetes was classified as known diabetes regardless of the glucose level. Blood pressure In the questionnaire participants were asked about the doctor’s advice after the latest blood rp Fo pressure measurement prior to participation in HUNT. The answer categories were: “no follow-up and no medication necessary”, “recommended follow-up examination but not to take medicine”, “start or continue taking medicine for high blood pressure”, or “never measured”. At HUNT2, mean systolic and mean diastolic arterial blood pressure (BP) of ee measurement 2 and 3 was categorized into normal (systolic (s) BP < 140 mmHg and diastolic (d) BP < 90 mmHg), mild hypertension (sBP 140-159 mmHg and dBP <100 mmHg or sBP rr <160 mmHg and dBP 90-99 mmHg), moderate hypertension (sBP 160-179 mmHg and dBP <109 mmHg or sBP <180 mmHg and dBP 100-109 mmHg), and severe hypertension ev (sBP>180 mmHg or dBP>110 mmHg). We constructed a new variable to define normotensive (reference), unknown mild- and moderate hypertensive, unknown severe ie hypertensive, and known hypertensive persons on the basis of self-report and measures. Statistical analysis w on The descriptive analyses of the study population were stratified by gender, and we used chisquare tests to examine any difference in proportions of SRH between the independent ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BMJ Open variables. Gender-stratified multiple logistic regression were used to estimate odds ratio (OR) with 95% confidence intervals (CI) for good SRH, as a function of thyroid status, diabetes mellitus status and blood pressure status, in separate unadjusted, age adjusted, and multi adjusted analyses for each condition. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 8 of 19 Age, smoking, alcohol consumption, body mass index (BMI), working- and educational status, and self-reported limiting long-term illness or injury are associated with SRH[40] and the diseases under study, but likely not affected by SRH or the diseases. Hence, these variables were included, a priori, as confounders in the models. Age was categorized into age groups; 40-49 years, 50-59 years, and 60-70 years. Smoking status was categorized into never rp Fo smoked daily, previous daily smoker, and current daily smoker. Alcohol units (AU) were defined as number of glasses of wine, beer or liquor. Those reporting to be teetotalers or to have alcohol intake less than four times a month or less than seven AU per two weeks were categorized as low consumers, those reporting drinking five to eight times a month or 8-14 ee AU per two weeks as moderate consumers, and those drinking more often than eight times a month or more than 14 AU as heavy consumers. BMI (kg/m2) was calculated of measured rr height and weight and categorized according to The World Health Organization’s (WHO) ev definition; underweight (18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.029.9 kg/m2) and obese (>30.0 kg/m2). People reporting paid- or self-employed work were ie classified as working, otherwise as not working. Educational level was categorized into <10 years, 10-12 years and >12 years. We chose affirmative answer to the question “Do you suffer w from any long-term illness or injury (at least one year) of a physical or psychological nature on that impairs your functioning in your everyday life?” to represent all relevant chronic medical conditions that could confound the results. To examine whether the association of the three disease statuses with SRH differed by ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 categories of the other independent variables, we used likelihood ratio-tests with p-value for statistical interaction. We tested for multicollinearity between the independent variables, by linear regression. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 30 of 43 Page 31 of 43 BMJ Open Page 9 of 19 In an additional analysis, the association between SRH and having had one or more medical consultations during the last year was investigated by logistic regression models, stratified by gender, both in the total study population and after exclusion of persons with diagnoses under study. rp Fo All analyses were preformed with IBM SPSS Statistics version 20 for windows. The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. RESULTS ee In all age categories, a higher proportion of men than women reported good SRH (p<0.001), and in both sexes the proportion reporting good SRH declined by age (p<0.002) (Table 1). rr The proportion reporting good SRH was lower in overweight, obese, and underweight ev women, than in normal weight women (p<0.001). In men the proportion reporting good SRH declined between the normal weight group to overweight-, obese-, and underweight group ie (p<0.001). In previous and current female smokers, a lower proportion reported good SRH compared to non smokers (p<0.001). In men, the proportion reporting good SRH was higher w among non smokers than among previous and current smokers (p<0.001), whereas there was on no difference between previous and current smokers. The proportion reporting good SRH was higher in moderate and heavy alcohol consumers than in low consumers, increased with education and was higher for participants in paid work (p<0.001). Underweight men and ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com persons with “any long-term impairment” had the lowest proportion reporting good SRH of all groups. The proportion reporting good SRH in the overall HUNT 2 study population differed from the proportions reported in persons without thyroid disease and normotensive persons (p<0.01), but not from persons without diabetes mellitus. However, the absolute differences were small. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 10 of 19 There was no multicollinearity between the independent variables. Thyroid function Thyroid dysfunctions, both known and unknown were more often observed among women rp Fo than among men (p<0.001) (Table 1). Women with known hypothyroidism had lower odds of reporting good SRH (OR 0.49 (95% CI 0.41 to 0.59) compared to women without thyroid disease in the adjusted analyses, but women with unknown or subclinical hypothyroidism had 84% and 48% higher odds, respectively, of reporting good SRH compared to the odds of women without thyroid disease (Table 2). The association between thyroid function and SRH ee was basically unchanged after inclusion of confounder variables. A cCorresponding, but non- rr significant associations pattern wereas found among men. Diabetes mellitus ev The prevalence of unknown, probable, and known diabetes was slightly higher in men than in ie women (p<0.001) (Table 1). Women with known diabetes mellitus had lower odds of good SRH than those without diabetes in the adjusted analyses; OR 0.53 (95% CI 0.41 to 0.69), w whereas in women with unknown or possible diabetes mellitus, the odds of good SRH were on similar to the odds among persons without diabetes, in the adjusted analyses (Table 2). In the adjusted analyses, the association between unknown and probable diabetes mellitus with poor ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 SRH, found in the crude analyses, disappeared when age was included in the model in women and men, but also by inclusion of working status alone in women. In men, the association of diabetes status with SRH differed by levels of education. Among men without higher education (12 years or less), the odds of good SRH were as in the main-effect model (Table 2). However in men with higher education, the ORs of good SRH were barely significantly lower among men with unknown diabetes (OR 0.29 (95% CI 0.09-1.00)) and among men with For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 32 of 43 Page 33 of 43 BMJ Open Page 11 of 19 possible diabetes (OR 0.79 (95% CI 0.63-1.00)) compared to men without diabetes. Among men with known diabetes in this stratum, the OR of good SRH was 0.31 (95% CI 0.17-0.54) compared to men without diabetes. Blood pressure rp Fo The prevalence of unknown mild and moderate hypertension was higher in men than in women (p<0.001). Unknown severe hypertension and known hypertension were equally distributed between women and men (Table 1). Women with known hypertension had lower odds of reporting good SRH than normotensive women, in the adjusted analyses. The figures ee were similar in men (Table 2). In contrast; compared to normotensive women, those with unknown severe hypertension had 52 % higher odds of reporting good SRH, with similar rr figures in men. Persons with unknown mild and moderate hypertension reported good SRH similar to the normotensive ones. Adjusted for age, the association between unknown mild ev and moderate hypertension and poor SRH disappeared, simultaneously; unknown severe hypertension became associated with good SRH in women. In men, age had to be added along ie with either education- or working status to achieve the latter association. Additional analyses w on Women with poor SRH had more than six times the odds of those with good SRH to have had a medical consultation during the last year; OR 6.29 (95% CI 5.47 to 7.22). For men the ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com corresponding OR was 5.53 (95% CI 4.86 to 6.29). After exclusion of persons with diagnosed thyroid disease, diabetes mellitus, known hypertension, and “any long-term disease”, the corresponding OR was 3.71 (95% CI 2.90 to 4.73), with similar figures in men. DISCUSSION For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 12 of 19 This large population-based study showed that persons with known thyroid dysfunction, diabetes mellitus, and hypertension were less likely to report good SRH than those without such conditions. Less expected, persons with unknown and subclinical hypothyroidism were more likely to report good SRH than those without thyroid disease. Similarly, those with unknown severe hypertension were more likely to report good SRH, compared to persons rp Fo with normal blood pressure. In general, persons with unknown diabetes and unknown mild/moderate hypertension, reported good health, just like the reference group. In general, of the confounders, age seemed to influence the association between disease ee statuses and SRH most when adjusted for. Age was found to explain the association of poor SRH with unknown and probable diabetes, and with unknown mild and moderate rr hypertension. In women, age even contributed to an association between unknown severe hypertension and good SRH. There seemed to be a linear decrease by age categories in the ev association with good SRH. The way age is known to be related to both disease and SRH makes these findings reasonable. ie Although both a qualitative and quantitative measure of association, the estimated ORs in our w study will, if interpreted as relative risks, overestimate the case, because the prevalence of good SRH is high in all groups.[41] on The main strengths of this study were the numbers of participants, that the diseases we studied ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 were high-prevalent, and that we could assume representativeness to the general population regarding the variables included. It is known that individuals with high burden of symptoms are less likely to attend surveys, but so far there has been little evidence that non-participation on this basis introduce substantial bias in associational studies.[42] We studied diseases with generally low symptom-burden, and expect selection bias to be negligible. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 34 of 43 Page 35 of 43 BMJ Open Page 13 of 19 The main limitation was possibly that we relied on self-reported data on both dependent and independent variables. The validity of self reported measures relevant for this study is questionable. However, if any, there should be a non-differential misclassification, that only should underestimate the associations found. rp Fo There is always a possibility of residual confounding in non-randomized study designs, and due to the observational, cross-sectional design we neither can assume a causal relationship. Bias due to differential detection of disease in the study population could lead to a type 1 error. Hypothyroidism and diabetes mellitus are often associated with vague symptoms such ee as tiredness and weakness. These symptoms are strongly associated with reduced SRH.[43] It is likely that presenting such symptoms for the GP would result in measurements of TSH, free rr T4, and serum glucose, thus reveal any related dysfunction. Low self-perceived health increases the probability to visit a GP.[44] The social security covers most costs related to ev clinical measurements and blood sampling in Norway, thus we expect GPs to have a low threshold to measure thyroid function, blood pressure or glucose levels. People who do not ie consult their GP will not have diseases with mild or no symptoms diagnosed, and their w personality could be characterized by less worrying and more optimistic attitude to health being reflected in better SRH.[45] on On the other hand, the association between known disease and poor SRH could in fact be ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com explained physiologically due to the pathological effect of disease. Lack of corresponding association between ignored, but prevalent disease and poor SRH is not in line with this hypothesis, rising question of a possible adverse effect of disease labelling. However, confounding by severity of disease cannot be ruled out. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 14 of 19 Due to low numbers of persons having unknown hypothyroidism and diabetes mellitus, the results should be interpreted with caution. On the other hand, there were high numbers in the subclinical and probable groups, and analyses of these groups did not show any associations with poor SRH, also rising question of a possible disease labelling effect. rp Fo The fact that the HUNT2 survey was carried out nearly 20 years ago raises a question of generalisability to today’s population. Stability of SRH over time has not been investigated in our study population, although investigated among adolescents.[46] We do not expect the association between low burden- or subclinical disease with SRH to be time dependent to the ee extent that it would change our results considerably. Neither do we expect the changes in prevalence of most explanatory variables to influence the associations found. rr Consistent findings regarding unknown, subclinical, and probable disease, versus known disease, could indicate a potential adverse effect of disease labelling. Although early detection ev of disease is protective on morbidity and mortality for many diseases, low SRH is also shown to be associated morbidity and mortality.[25-27] This is an important aspect in the debate of w presymptomatic case-finding. ie The BMJ's Too Much Medicine campaign aims to highlight the threat to human health posed on by overdiagnosis and the waste of resources on unnecessary care (http://www.bmj.com/toomuch-medicine). American data have shown that the majority of all health care includes ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 preference-sensitive and supply-sensitive services. The extent of these services varies greatly without necessarily leading to better health.[47 48] A great deal of activity in such services is based on identifying subclinical disease. The negative health effect this might have, modulated through reduced SRH, can explain why population mortality is not reduced in areas with high frequency of diagnoses. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 36 of 43 Page 37 of 43 BMJ Open Page 15 of 19 Both public and academic debates are often characterised by the conviction that all medical treatment is efficient. Wennberg showed that a relatively small proportion of all medical treatment is indisputably good for health.[49] The concern for unrevealed risk factors and subclinical conditions might lead to unnecessary costly health care interventions, increase supply-sensitive services without positive health effect and have a negative influence on rp Fo people’s general and self-perceived health causing more harm than good.[15] Of ethical reasons, the possible causal effect of disease labelling on SRH is impossible to assess in a randomized controlled trial. Our study emphasizes the need for more prospective ee research to investigate potential health effects of disease labelling and early diagnosis. CONCLUSION rr Our data suggest that early identification of disease may imply a negative effect on SRH, and ev to the extent that SRH has been associated with greater mortality, this may lead to harm. However, as it is also known that diseases such as diabetes and hypertension also lead to ie increased mortality when detected after cardiovascular and metabolic complications have developed, it remains to be seen if an early identification or a late detection strategy would w provide optimal health for the population. early identification of disease may imply a negative on effect on SRH and thereby eventually cause more harm than good. On a population level, such efforts might increase the costs in health care and the proportion of supply-sensitive ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com services without any documented positive health effect. More research is needed concerning the possible adverse effects of disease labelling on SRH and mortality. FOOTNOTES Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) Field Code Changed For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 16 of 19 publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. rp Fo Field Code Changed Contributors All authors meet the four criteria for authorship recommended by the International Committee of Medical Journal Editors. SF, AL, and SK have been active supervisors in study conception, design, conduct, interpretation, and reporting. PJ analyzed the data and drafted the manuscript. Critical revisions were done by all supervisors and all authors approved the final version of the manuscript. SF, AL, SK and PJ are joint guarantors. ee Acknowledgements The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology NTNU), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. The authors would like to thank Bjørn Olav Åsvold for his contribution in planning of the thyroid-part of the study. ev rr Transparency declaration PJ affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there were no discrepancies from the study as planned. ie Ethical approval The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. w Funding No external funding. PJ received a PhD-grant, funded by the Norwegian University of Science and Technology, NTNU. Data sharing statement No additional data available. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 38 of 43 Page 39 of 43 BMJ Open Page 17 of 19 1. Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ 2005;31(4):564-71 doi: 10.1177/0145721705279050[published Online First: Epub Date]|. 2. Borzecki AM, Wong AT, Hickey EC, et al. Hypertension control: how well are we doing? Arch Intern Med 2003;163(22):2705-11 doi: 10.1001/archinte.163.22.2705[published Online First: Epub Date]|. 3. Andros V, Egger A, Dua U. Blood pressure goal attainment according to JNC 7 guidelines and utilization of antihypertensive drug therapy in MCO patients with type 1 or type 2 diabetes. J Manag Care Pharm 2006;12(4):303-9 4. Liddy C, Singh J, Hogg W, et al. Quality of cardiovascular disease care in Ontario, Canada: missed opportunities for prevention - a cross sectional study. BMC Cardiovasc Disord 2012;12:74 doi: 10.1186/1471-2261-12-74[published Online First: Epub Date]|. 5. Huebschmann AG, Mizrahi T, Soenksen A, et al. Reducing clinical inertia in hypertension treatment: a pragmatic randomized controlled trial. J Clin Hypertens (Greenwich) 2012;14(5):322-9 doi: 10.1111/j.1751-7176.2012.00607.x[published Online First: Epub Date]|. 6. Alkerwi Aa, Pagny S, Lair M-L, et al. Level of Unawareness and Management of Diabetes, Hypertension, and Dyslipidemia among Adults in Luxembourg: Findings from ORISCAV-LUX Study. PLoS One 2013;8(3):e57920 doi: 10.1371/journal.pone.0057920[published Online First: Epub Date]|. 7. Khan N, Chockalingam A, Campbell NR. Lack of control of high blood pressure and treatment recommendations in Canada. Can J Cardiol 2002;18(6):657-61 8. Hetlevik I, Holmen J, Kruger O, et al. Fifteen years with clinical guidelines in the treatment of hypertension - still discrepancies between intentions and practice. Scand J Prim Health Care 1997;15(3):134-40 doi: Doi 10.3109/02813439709018503[published Online First: Epub Date]|. 9. Hetlevik I, Holmen J, Midthjell K. Treatment of diabetes mellitus - physicians' adherence to clinical guidelines in Norway. Scand J Prim Health Care 1997;15(4):193-97 doi: Doi 10.3109/02813439709035027[published Online First: Epub Date]|. 10. Petursson H, Getz L, Sigurdsson JA, et al. Current European guidelines for management of arterial hypertension: Are they adequate for use in primary care? Modelling study based on the Norwegian HUNT 2 population. BMC Fam Pract 2009;10 doi: Artn 70 Doi 10.1186/1471-229610-70[published Online First: Epub Date]|. 11. Petursson H, Getz L, Sigurdsson JA, et al. Can individuals with a significant risk for cardiovascular disease be adequately identified by combination of several risk factors? Modelling study based on the Norwegian HUNT 2 population. J Eval Clin Pract 2009;15(1):103-09 doi: DOI 10.1111/j.1365-2753.2008.00962.x[published Online First: Epub Date]|. 12. Getz L, Sigurdsson JA, Hetlevik I, et al. Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. Br Med J 2005;331(7516):551-54A doi: DOI 10.1136/bmj.38555.648623.8F[published Online First: Epub Date]|. 13. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 1999;282(15):1458-65 doi: 10.1001/jama.282.15.1458[published Online First: Epub Date]|. 14. Smith CM. Origin and uses of primum non nocere--above all, do no harm! J Clin Pharmacol 2005;45(4):371-7 doi: 10.1177/0091270004273680[published Online First: Epub Date]|. 15. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. Br Med J 2012;344 doi: Artn E3502 Doi 10.1136/Bmj.E3502[published Online First: Epub Date]|. 16. Miilunpalo S, Vuori I, Oja P, et al. Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the Formatted: English (U.S.) Formatted: English (U.S.) w ie ev rr ee rp Fo Formatted: English (U.S.) Formatted: English (U.S.) Formatted: English (U.S.) ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Formatted: English (U.S.) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 18 of 19 working-age population. J Clin Epidemiol 1997;50(5):517-28 doi: S0895-4356(97)00045-0 [pii][published Online First: Epub Date]|. 17. Meurer LN, Layde PM, Guse CE. Self-rated health status: a new vital sign for primary care? WMJ 2001;100(7):35-9 18. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-5 doi: 59/5/342 [pii] 10.1136/jech.2004.021204[published Online First: Epub Date]|. 19. Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24(3):218-24 20. Bopp M, Braun J, Gutzwiller F, et al. Health risk or resource? Gradual and independent association between self-rated health and mortality persists over 30 years. PLoS One 2012;7(2):e30795 doi: 10.1371/journal.pone.0030795 PONE-D-11-20499[pii][published Online First: Epub Date]|. 21. Moller L, Kristensen TS, Hollnagel H. Self rated health as a predictor of coronary heart disease in Copenhagen, Denmark. J Epidemiol Community Health 1996;50(4):423-8 22. Kaplan GA, Goldberg DE, Everson SA, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol 1996;25(2):259-65 doi: Doi 10.1093/Ije/25.2.259[published Online First: Epub Date]|. 23. Krokstad S, Johnsen R, Westin S. Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol 2002;31(6):1183-91 doi: 10.1093/ije/31.6.1183[published Online First: Epub Date]|. 24. Halford C, Wallman T, Welin L, et al. Effects of self-rated health on sick leave, disability pension, hospital admissions and mortality. A population-based longitudinal study of nearly 15,000 observations among Swedish women and men. BMC Public Health 2012;12:1103 doi: 10.1186/1471-2458-12-1103[published Online First: Epub Date]|. 25. Latham K, Peek CW. Self-Rated Health and Morbidity Onset Among Late Midlife US Adults. J Gerontol B-Psychol 2013;68(1):107-16 doi: DOI 10.1093/geronb/gbs104[published Online First: Epub Date]|. 26. Benyamini Y, Idler EL. Community studies reporting association between self-rated health and mortality - Additional studies, 1995 to 1998. Res Aging 1999;21(3):392-401 doi: Doi 10.1177/0164027599213002[published Online First: Epub Date]|. 27. Nielsen AB, Siersma V, Hiort LC, et al. Self-rated general health among 40-year-old Danes and its association with all-cause mortality at 10-, 20-, and 29 years' follow-up. Scand J Public Health 2008;36(1):3-11 doi: 10.1177/1403494807085242[published Online First: Epub Date]|. 28. Schou MB, Krokstad S, Westin S. How is self-rated health associated with mortality? Tidsskr Nor Laegeforen 2006;126(20):2644-7 29. Barger SD, Muldoon MF. Hypertension labelling was associated with poorer self-rated health in the Third US National Health and Nutrition Examination Survey. J Hum Hypertens 2006;20(2):117-23 doi: 10.1038/sj.jhh.1001950[published Online First: Epub Date]|. 30. Bloom JR, Monterossa S. Hypertension Labeling and Sense of Well-Being. Am J Public Health 1981;71(11):1228-32 doi: Doi 10.2105/Ajph.71.11.1228[published Online First: Epub Date]|. 31. Moum T, Naess S, Sorensen T, et al. Hypertension Labeling, Life Events and Psychological WellBeing. Psychol Med 1990;20(3):635-46 32. Macdonald LA, Sackett DL, Haynes RB, et al. Labelling in hypertension: A review of the behavioural and psychological consequences. J Chronic Dis 1984;37(12):933-42 doi: http://dx.doi.org/10.1016/0021-9681(84)90070-5[published Online First: Epub Date]|. 33. Bianchi GP, Zaccheroni V, Solaroli E, et al. Health-related quality of life in patients with thyroid disorders - A study based on Short-Form 36 and Nottingham Health Profile Questionnaires. Qual Life Res 2004;13(1):45-54 doi: Doi 10.1023/B:Qure.0000015315.35184.66[published Online First: Epub Date]|. Formatted: English (U.S.) w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Formatted: English (U.S.) Formatted: English (U.S.) Field Code Changed Formatted: English (U.S.) Formatted: English (U.S.) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 40 of 43 Page 41 of 43 BMJ Open Page 19 of 19 34. Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag Health Study 1995-97 (HUNT 2): objectives, methods, and participation. Norsk Epidemiol 2003 13 (1 ):19-32 35. Krokstad S, Langhammer A, Hveem K, et al. Cohort Profile: The HUNT Study, Norway. Int J Epidemiol 2012 doi: dys095 [pii] 10.1093/ije/dys095[published Online First: Epub Date]|. 36. Schnittker J, Bacak V. The Increasing Predictive Validity of Self-Rated Health. PLoS One 2014;9(1):e84933 doi: 10.1371/journal.pone.0084933[published Online First: Epub Date]|. 37. Idler EL, Benyamini Y. Self-rated health and mortality: A review of twenty-seven community studies. J Health Soc Behav 1997;38(1):21-37 doi: Doi 10.2307/2955359[published Online First: Epub Date]|. 38. Manor O, Matthews S, Power C. Dichotomous or categorical response? Analysing self-rated health and lifetime social class. Int J Epidemiol 2000;29(1):149-57 doi: Doi 10.1093/Ije/29.1.149[published Online First: Epub Date]|. 39. Bjoro T, Holmen J, Kruger O, et al. Prevalence of thyroid disease, thyroid dysfunction and thyroid peroxidase antibodies in a large, unselected population. The Health Study of Nord-Trondelag (HUNT). Eur J Endocrinol 2000;143(5):639-47 doi: 1430639 [pii][published Online First: Epub Date]|. 40. Giron P. Determinants of self-rated health in Spain: differences by age groups for adults. Eur J Public Health 2012;22(1):36-40 doi: 10.1093/eurpub/ckq133[published Online First: Epub Date]|. 41. Davies HTO, Crombie IK, Tavakoli M. When can odds ratios mislead? Br Med J 1998;316(7136):989-91 42. Langhammer A, Krokstad S, Romundstad P, et al. The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms. BMC Med Res Methodol 2012;12:143 doi: 10.1186/1471-2288-12-143[published Online First: Epub Date]|. 43. Molarius A, Janson S. Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol 2002;55(4):364-70 doi: http://dx.doi.org/10.1016/S0895-4356(01)00491-7[published Online First: Epub Date]|. 44. Hansen AH, Halvorsen PA, Ringberg U, et al. Socio-economic inequalities in health care utilisation in Norway: a population based cross-sectional survey. BMC Health Serv Res 2012;12:336 doi: 10.1186/1472-6963-12-336[published Online First: Epub Date]|. 45. Vingilis E, Wade T, Seeley J. Predictors of adolescent health care utilization. J Adolesc 2007;30(5):773-800 doi: http://dx.doi.org/10.1016/j.adolescence.2006.10.001[published Online First: Epub Date]|. 46. Breidablik H-J, Meland E, Lydersen S. Self-rated health during adolescence: stability and predictors of change (Young-HUNT study, Norway). The European Journal of Public Health 2009;19(1):73-78 doi: 10.1093/eurpub/ckn111[published Online First: Epub Date]|. 47. Welch HG, Sharp SM, Gottlieb DJ, et al. Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries. JAMA 2011;305(11):1113-8 doi: 10.1001/jama.2011.307[published Online First: Epub Date]|. 48. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138(4):288-98 49. Wennberg JE. Tracking medicine. A researcher’s quest to understand health care. Oxford: Oxford University Press, 2010. Formatted: English (U.S.) Formatted: English (U.S.) Formatted: English (U.S.) w ie ev rr ee rp Fo Formatted: English (U.S.) Field Code Changed Formatted: English (U.S.) Formatted: English (U.S.) Field Code Changed Formatted: English (U.S.) Formatted: English (U.S.) ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml BMJ Open STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cross-sectional studies Section/Topic Title and abstract Item # 1 Introduction Recommendation Reported on page # Fo (a) Indicate the study’s design with a commonly used term in the title or the abstract 2 (b) Provide in the abstract an informative and balanced summary of what was done and what was found 2 rp Background/rationale 2 Explain the scientific background and rationale for the investigation being reported Objectives 3 State specific objectives, including any prespecified hypotheses Study design 4 Present key elements of study design early in the paper Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 5 Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants 5 Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if Data sources/ 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe Bias 9 Describe any efforts to address potential sources of bias Study size 10 Explain how the study size was arrived at Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and ee Methods rr 4 2-3 ev applicable measurement iew comparability of assessment methods if there is more than one group on why Statistical methods 12 3-4 (a) Describe all statistical methods, including those used to control for confounding ly (b) Describe any methods used to examine subgroups and interactions (c) Explain how missing data were addressed 5-8 5-8 7-8 5 5-8 7-8 8 Table 2 (d) If applicable, describe analytical methods taking account of sampling strategy - (e) Describe any sensitivity analyses - Results For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Page 42 of 43 Page 43 of 43 Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, 5 confirmed eligible, included in the study, completing follow-up, and analysed Descriptive data 14* (b) Give reasons for non-participation at each stage 5 (c) Consider use of a flow diagram - Fo (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders rp Table 1 (b) Indicate number of participants with missing data for each variable of interest Table 1 Outcome data 15* Report numbers of outcome events or summary measures Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included Table 1 ee Table 2 Page 9-11 (b) Report category boundaries when continuous variables were categorized rr 5-7 (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses ev Discussion - 10-11 Key results 18 Summarise key results with reference to study objectives Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias 11-13 Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence 13-14 Generalisability 21 Discuss the generalisability (external validity) of the study results 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on Other information Funding which the present article is based iew 11 on 11 ly 15 *Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies. Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 BMJ Open Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Is there an association between disease ignorance and selfrated health? The HUNT Study, a cross-sectional survey Journal: BMJ Open rp Fo Manuscript ID: Article Type: Date Submitted by the Author: Complete List of Authors: bmjopen-2014-004962.R2 Research 08-May-2014 Secondary Subject Heading: Epidemiology, Public health, Diabetes and endocrinology Hypertension < CARDIOLOGY, General diabetes < DIABETES & ENDOCRINOLOGY, Thyroid disease < DIABETES & ENDOCRINOLOGY, PRIMARY CARE w ie Keywords: General practice / Family practice ev <b>Primary Subject Heading</b>: rr ee Jørgensen, Pål; Norwegian University of Science and Technology, Department of Public Health and General Practice Langhammer, Arnulf; Norwegian University of Science and Technology, HUNT Research Centre Krokstad, Steinar; Norwegian University of Science and Technology, HUNT Research Centre Forsmo, Siri; Norwegian University of Science and Technology, Department of Public Health and General Practice ly on For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 1 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 1 of 24 Is there an association between disease ignorance and self-rated health? The HUNT Study, a crosssectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad, Siri Forsmo Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway Pål Jørgensen PhD Candidate HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Arnulf Langhammer Professor, Head of HUNT Databank HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Steinar Krokstad Professor, Head of HUNT Research Center Department of Public Health and General Practice, Norwegian University of Science and Technology, Siri Forsmo Professor, Head of Department rr ee rp Fo Correspondence to: P Jørgensen pal_jorgensen@ntnu.no ev Keywords: Self-rated health, awareness, hypothyroidism, diabetes, hypertension. Word count: 3380 w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 2 of 24 ABSTRACT Objective To explore if awareness versus unawareness of thyroid dysfunction, diabetes mellitus or hypertension is associated with self-rated health. Design Large-scale, cross sectional population based study. The association between thyroid function, diabetes mellitus, and blood pressure and self-rated health was explored by multiple rp Fo logistic regression analysis. Setting The second survey of the Nord-Trøndelag Health Study, HUNT2, 1995-97. Participants 33,734 persons aged 40-70 years. ee Primary outcome measures Logistic regression was used to estimate odds ratios for good rr self-rated health as a function of thyroid status, diabetes mellitus status and blood pressure status. ev Results Persons aware of their hypothyroidism, diabetes mellitus, or hypertension reported ie poorer self-rated health than individuals without such conditions. Women with unknown and w subclinical hypothyroidism reported better self-rated health than women with normal thyroid status. Both in women and men, unknown and probable diabetes, as well as unknown on mild/moderate hypertension was not associated with poorer health. Further, persons with unknown severe hypertension reported better health than normotensive persons. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Conclusions People with undiagnosed, but prevalent hypothyroidism, diabetes mellitus, and hypertension often have good self-rated health, whilst when aware of their diagnoses, they report reduced self-rated health. Use of screening, more sensitive tests, and widened diagnostic criteria might have a negative effect on perceived health in the population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 2 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 3 of 48 BMJ Open Page 3 of 24 STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths • Sample from a large-scale, general population • High-prevalent diseases under study; ensuring statistical power in subgroup analyses Limitations rp Fo • Study mainly based on self-reported data • Cross-sectional study; susceptibility to confounding and impossibility to assume causal relationships w ie ev rr ee ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 4 of 24 INTRODUCTION Guidelines for prevention and treatment have been developed for most high prevalent diseases in western countries aiming for reduction of morbidity and mortality by interventions mainly in primary health care (PHC). In the society there seems to be an increasing conviction of achievable zero-vision regarding rp Fo risks and diseases. Part of the strategy is to detect risk factors and pre-diseases in even earlier stages. From a secondary or tertiary health care level, this might seem reasonable since intervention on many individuals with specific risk factors presumably can prevent or delay disease or progression of disease. Further, health authorities and hospital clinicians regularly ee raise concern of the lack of detection of risk factors, of subclinical conditions and of rr achieving treatment goals.[1-7] Norwegian studies have shown that guidelines are often difficult to implement and adhere to in PHC.[8 9] According to guidelines, most individuals ev would be defined as at risk and resources needed to handle this appropriately could destabilize ie the entire health care system.[10-12] An American review pointed out knowledge, attitude, and behaviour as barriers of physician’s adherence to clinical guidelines.[13] In an already w complex and busy PHC-setting, one might expect that resources used for disease prevention on and case finding have to compete with resources for handling acknowledged disease. Also, physicians might want to avoid increasing disease related burden for patients, in line with the ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 old wisdom; “primum non nocere”.[14] Thus the risk and disease zero-visions in society and among politicians are seldom shared by PHC professionals. When guidelines, mainly based on research from high risk hospital populations, are applied on low risk populations in PHC, more healthy individuals are identified as being at risk or are given diagnoses. Also the widened inclusion criteria for diagnoses in general and use of more For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 4 of 48 Page 5 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 5 of 24 sensitive tests contribute to define more individuals at risk or as unhealthy.[15] Possible undesirable outcomes of such strategies remain unclear. Self-rated health (SRH) is a valid and widely used measure of general health in epidemiologic research.[16-19] It is associated with several clinical conditions often seen in PHC, with recovery [20-23] and is found to predict morbidity, sick leave, and disability pension,[24 25] rp Fo as well as mortality.[26-28] The majority of studies describing association between labelling of disease per se and SRH have focused on arterial hypertension.[29-32] However, one study has indicated reduced SRH among individuals labelled with thyroid dysfunctions.[33] The aim of this study was to investigate whether persons’ awareness versus unawareness of ee thyroid dysfunction, diabetes mellitus, or hypertension was associated with their SRH, as rr reported in a population-based health study in Norway. w ie ev ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 6 of 24 METHODS Study population The data sample in this study stem from the second wave of the Nord-Trøndelag Health Study (HUNT2) conducted in 1995-97 in the county of Nord-Trøndelag, Norway. All individuals aged 20 years and older, living in the county, were invited (94,194 individuals). In all, 66.7% rp Fo of men (n=30,860) and 75.5% of women (n=35,280) participated. The survey consisted of both questionnaires and measurements, and is described previously in detail.[34 35] In our study we included answers from the main questionnaire and the baseline measurements for persons aged 40-70 years. The age span was chosen because thyroid stimulating hormone ee (TSH) was analysed in all women and in 50% of men at this age, of a rather low disease rr burden in people younger than 40 years, and of a lower attendance rate under and above this age span. A total of 24,950 individuals had TSH measurements and answered thyroid ev questions, thus were eligible for analysis on thyroid dysfunction, whilst in the analysis of ie diabetes mellitus and blood pressure, 33,734 individuals were included in all. Self-rated health w on The first question in the main questionnaire in HUNT2, answered before attending the examination stations, was “How is your health at the moment?”, with answer alternatives; ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 “very good”, “good”, “not so good”, and “poor”. This short version of SRH measure is shown to be a valid predictor of mortality. [18 28 36 37] We dichotomized the answers into “good” (very good, good) and “poor” (not so good, poor). Dichotomization of multinomial SRH is commonly performed, and has been validated by Manor et. al.[38] Thyroid function For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 6 of 48 Page 7 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 7 of 24 The participants answered questions on history of hypo- and hyperthyroidism, goitre, other thyroid diseases, and treatment with thyroxin, radio-iodine, surgery, or thyreostatic medication. Serum TSH and free T4 were analysed at the Hormone laboratory, Aker University Hospital, Norway. The laboratory reference value for TSH, as defined prior to the survey, was 0.2-4.5 rp Fo mU/L and for free T4 8.0-20.0 pmol/L. If TSH was <0.2 mU/L or >4.0 mU/L, and/or if the participant reported any thyroid disease, serum free T4 was also measured.[39] Individuals reporting no previous thyroid disease and having TSH within reference range were categorized as “no thyroid disease” and chosen as reference category. No previous ee thyroid disease combined with TSH >4.5 mU/L and free T4 <8.0 pmol/L was defined as rr unknown hypothyroidism. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 8.0 – 20.0 pmol/L was defined as subclinical hypothyroidism. Individuals reporting ev hypothyroidism and use of thyroxin were classified as having known hypothyroidism, ie regardless of the TSH and T4 levels. Affirmative answers to other thyroid related questions or measures outside reference range in the remainders were classified as other thyroid dysfunction. ly on Diabetes mellitus w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Diabetes mellitus was assessed through self-report and blood samples. Serum glucose was analysed at Levanger Hospital, Norway. Those reporting no diabetes and having normal glucose levels (<5.5 mmol/L) were classified as “no diabetes” and were chosen as reference category. No self-reported diabetes and non-fasting glucose >11.0 mmol/L was categorized as unknown diabetes, whereas no diabetes and non-fasting glucose 5.5-11.0 mmol/L was For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 8 of 24 categorized as probable diabetes. Self-reported diabetes was classified as known diabetes regardless of the glucose level. Blood pressure In the questionnaire participants were asked about the doctor’s advice after the latest blood pressure measurement prior to participation in HUNT. The answer categories were: “no rp Fo follow-up and no medication necessary”, “recommended follow-up examination but not to take medicine”, “start or continue taking medicine for high blood pressure”, or “never measured”. At HUNT2, mean systolic and mean diastolic arterial blood pressure (BP) of measurement 2 and 3 was categorized into normal (systolic (s) BP < 140 mmHg and diastolic ee (d) BP < 90 mmHg), mild hypertension (sBP 140-159 mmHg and dBP <100 mmHg or sBP rr <160 mmHg and dBP 90-99 mmHg), moderate hypertension (sBP 160-179 mmHg and dBP <109 mmHg or sBP <180 mmHg and dBP 100-109 mmHg), and severe hypertension ev (sBP>180 mmHg or dBP>110 mmHg). We constructed a new variable to define ie normotensive (reference), unknown mild- and moderate hypertensive, unknown severe hypertensive, and known hypertensive persons on the basis of self-report and measures. w Statistical analysis on The descriptive analyses of the study population were stratified by gender, and we used chi- ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 square tests to examine any difference in proportions of SRH between the independent variables. Gender-stratified multiple logistic regression were used to estimate odds ratio (OR) with 95% confidence intervals (CI) for good SRH, as a function of thyroid status, diabetes mellitus status and blood pressure status, in separate unadjusted, age adjusted, and multi adjusted analyses for each condition. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 8 of 48 Page 9 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 9 of 24 Age, smoking, alcohol consumption, body mass index (BMI), working- and educational status, and self-reported limiting long-term illness or injury are associated with SRH[40] and the diseases under study, but likely not affected by SRH or the diseases. Hence, these variables were included, a priori, as confounders in the models. Age was categorized into age groups; 40-49 years, 50-59 years, and 60-70 years. Smoking status was categorized into never smoked daily, previous daily smoker, and current daily smoker. Alcohol units (AU) were rp Fo defined as number of glasses of wine, beer or liquor. Those reporting to be teetotalers or to have alcohol intake less than four times a month or less than seven AU per two weeks were categorized as low consumers, those reporting drinking five to eight times a month or 8-14 ee AU per two weeks as moderate consumers, and those drinking more often than eight times a month or more than 14 AU as heavy consumers. BMI (kg/m2) was calculated of measured rr height and weight and categorized according to The World Health Organization’s (WHO) definition; underweight (18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0- ev 29.9 kg/m2) and obese (>30.0 kg/m2). People reporting paid- or self-employed work were ie classified as working, otherwise as not working. Educational level was categorized into <10 w years, 10-12 years and >12 years. We chose affirmative answer to the question “Do you suffer from any long-term illness or injury (at least one year) of a physical or psychological nature on that impairs your functioning in your everyday life?” to represent all relevant chronic medical conditions that could confound the results. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 To examine whether the association of the three disease statuses with SRH differed by categories of the other independent variables, we used likelihood ratio-tests with p-value for statistical interaction. We tested for multicollinearity between the independent variables, by linear regression. Areas under the receiver operating characteristic curves (AUC) were calculated to evaluate the performance of the logistic regression models. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 10 of 24 In an additional analysis, the association between SRH and having had one or more medical consultations during the last year was investigated by logistic regression models, stratified by gender, both in the total study population and after exclusion of persons with diagnoses under study. All analyses were preformed with IBM SPSS Statistics version 20 for windows. rp Fo The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. RESULTS ee In all age categories, a higher proportion of men than women reported good SRH (p<0.001), and in both sexes the proportion reporting good SRH declined by age (p<0.002) (Table 1). rr The proportion reporting good SRH was lower in overweight, obese, and underweight ev women, than in normal weight women (p<0.001). In men the proportion reporting good SRH declined between the normal weight group to overweight-, obese-, and underweight group ie (p<0.001). In previous and current female smokers, a lower proportion reported good SRH w compared to non smokers (p<0.001). In men, the proportion reporting good SRH was higher among non smokers than among previous and current smokers (p<0.001), whereas there was on no difference between previous and current smokers. The proportion reporting good SRH was ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 higher in moderate and heavy alcohol consumers than in low consumers, increased with education and was higher for participants in paid work (p<0.001). Underweight men and persons with “any long-term impairment” had the lowest proportion reporting good SRH of all groups. The proportion reporting good SRH in the overall HUNT 2 study population differed from the proportions reported in persons without thyroid disease and normotensive persons (p<0.01), but not from persons without diabetes mellitus. However, the absolute differences were small. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 10 of 48 Page 11 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 11 of 24 In all fully adjusted regression models, the AUC was 0.80. Unadjusted, the AUC ranged from 0.61 to 0.63. There was no multicollinearity between the independent variables. Thyroid function rp Fo Thyroid dysfunctions, both known and unknown were more often observed among women than among men (p<0.001) (Table 1). Women with known hypothyroidism had lower odds of reporting good SRH than women without thyroid disease in the adjusted analyses.However, women with unknown or subclinical hypothyroidism had 84% and 48% higher odds, ee respectively, of reporting good SRH compared to the odds of women without thyroid disease rr (Table 2). The association between thyroid function and SRH was basically unchanged after inclusion of confounder variables. Corresponding, but non-significant associations were found among men. w ie Diabetes mellitus ev The prevalence of unknown, probable, and known diabetes was slightly higher in men than in on women (p<0.001) (Table 1). Women with known diabetes mellitus had lower odds of good SRH than those without diabetes in the adjusted analyses, whereas in women with unknown ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 or possible diabetes mellitus, the odds of good SRH were similar to the odds among persons without diabetes, in the adjusted analyses (Table 2). In the adjusted analyses, the association between unknown and probable diabetes mellitus with poor SRH, found in the crude analyses, disappeared when age was included in the model in women and men, but also by inclusion of working status alone in women. In men, the association of diabetes status with SRH differed by levels of education. Among men without higher education (12 years or less), the odds of good SRH were as in the main-effect model (Table 2). However in men with higher For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 12 of 24 education, the ORs of good SRH were barely significantly lower among men with unknown diabetes (OR 0.29 (95% CI 0.09-1.00)) and among men with possible diabetes (OR 0.79 (95% CI 0.63-1.00)) compared to men without diabetes. Among men with known diabetes in this stratum, the OR of good SRH was 0.31 (95% CI 0.17-0.54) compared to men without diabetes. rp Fo Blood pressure The prevalence of unknown mild and moderate hypertension was higher in men than in women (p<0.001). Unknown severe hypertension and known hypertension were equally distributed between women and men (Table 1). Women with known hypertension had lower ee odds of reporting good SRH than normotensive women, in the adjusted analyses. The figures rr were similar in men (Table 2). In contrast; compared to normotensive women, those with unknown severe hypertension had 52 % higher odds of reporting good SRH, with similar ev figures in men. Persons with unknown mild and moderate hypertension reported good SRH ie similar to the normotensive ones. Adjusted for age, the association between unknown mild and moderate hypertension and poor SRH disappeared, simultaneously; unknown severe w hypertension became associated with good SRH in women. In men, age had to be added along on with either education- or working status to achieve the latter association. Additional analyses ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Women with poor SRH had more than six times the odds of those with good SRH to have had a medical consultation during the last year; OR 6.29 (95% CI 5.47 to 7.22). For men the corresponding OR was 5.53 (95% CI 4.86 to 6.29). After exclusion of persons with diagnosed thyroid disease, diabetes mellitus, known hypertension, and “any long-term disease”, the corresponding OR was 3.71 (95% CI 2.90 to 4.73), with similar figures in men. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 12 of 48 Page 13 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 13 of 24 DISCUSSION This large population-based study showed that persons with known thyroid dysfunction, diabetes mellitus, and hypertension were less likely to report good SRH than those without such conditions. Less expected, persons with unknown and subclinical hypothyroidism were more likely to report good SRH than those without thyroid disease. Similarly, those with rp Fo unknown severe hypertension were more likely to report good SRH, compared to persons with normal blood pressure. In general, persons with unknown diabetes and unknown mild/moderate hypertension, reported good health, just like the reference group. In general, of the confounders, age seemed to influence the association between disease ee statuses and SRH most when adjusted for. Age was found to explain the association of poor rr SRH with unknown and probable diabetes, and with unknown mild and moderate hypertension. In women, age even contributed to an association between unknown severe ev hypertension and good SRH. There seemed to be a linear decrease by age categories in the ie association with good SRH. The way age is known to be related to both disease and SRH makes these findings reasonable. w Although both a qualitative and quantitative measure of association, the estimated ORs in our on study will, if interpreted as relative risks, overestimate the case, because the prevalence of good SRH is high in all groups.[41] ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The main strengths of this study were the numbers of participants, that the diseases we studied were high-prevalent, and that we could assume representativeness to the general population regarding the variables included. It is known that individuals with high burden of symptoms are less likely to attend surveys, but so far there has been little evidence that non-participation For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 14 of 24 on this basis introduce substantial bias in associational studies.[42] We studied diseases with generally low symptom-burden, and expect selection bias to be negligible. The main limitation was possibly that we relied on self-reported data on both dependent and independent variables. The validity of self reported measures relevant for this study is questionable. However, if any, there should be a non-differential misclassification, that only rp Fo should underestimate the associations found. There is always a possibility of residual confounding in non-randomized study designs, and due to the observational, cross-sectional design we neither can assume a causal relationship. ee Bias due to differential detection of disease in the study population could lead to a type 1 error. Hypothyroidism and diabetes mellitus are often associated with vague symptoms such rr as tiredness and weakness. These symptoms are strongly associated with reduced SRH.[43] It ev is likely that presenting such symptoms for the GP would result in measurements of TSH, free T4, and serum glucose, thus reveal any related dysfunction. Low self-perceived health ie increases the probability to visit a GP.[44] The social security covers most costs related to w clinical measurements and blood sampling in Norway, thus we expect GPs to have a low threshold to measure thyroid function, blood pressure or glucose levels. People who do not on consult their GP will not have diseases with mild or no symptoms diagnosed, and their ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 personality could be characterized by less worrying and more optimistic attitude to health being reflected in better SRH.[45] On the other hand, the association between known disease and poor SRH could in fact be explained physiologically due to the pathological effect of disease. Lack of corresponding association between ignored, but prevalent disease and poor SRH is not in line with this For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 14 of 48 Page 15 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 15 of 24 hypothesis, rising question of a possible adverse effect of disease labelling. However, confounding by severity of disease cannot be ruled out. Due to low numbers of persons having unknown hypothyroidism and diabetes mellitus, the results should be interpreted with caution. On the other hand, there were high numbers in the subclinical and probable groups, and analyses of these groups did not show any associations rp Fo with poor SRH, also rising question of a possible disease labelling effect. The fact that the HUNT2 survey was carried out nearly 20 years ago raises a question of generalisability to today’s population. Stability of SRH over time has not been investigated in our study population, although investigated among adolescents.[46] We do not expect the ee association between low burden- or subclinical disease with SRH to be time dependent to the rr extent that it would change our results considerably. Neither do we expect the changes in prevalence of most explanatory variables to influence the associations found. ev Consistent findings regarding unknown, subclinical, and probable disease, versus known ie disease, could indicate a potential adverse effect of disease labelling. Although early detection w of disease is protective on morbidity and mortality for many diseases, low SRH is also shown to be associated morbidity and mortality.[25-27] This is an important aspect in the debate of presymptomatic case-finding. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The BMJ's Too Much Medicine campaign aims to highlight the threat to human health posed by overdiagnosis and the waste of resources on unnecessary care (http://www.bmj.com/toomuch-medicine). American data have shown that the majority of all health care includes preference-sensitive and supply-sensitive services. The extent of these services varies greatly without necessarily leading to better health.[47 48] A great deal of activity in such services is based on identifying subclinical disease. The negative health effect this might have, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 16 of 24 modulated through reduced SRH, can explain why population mortality is not reduced in areas with high frequency of diagnoses. Both public and academic debates are often characterised by the conviction that all medical treatment is efficient. Wennberg showed that a relatively small proportion of all medical treatment is indisputably good for health.[49] The concern for unrevealed risk factors and rp Fo subclinical conditions might lead to unnecessary costly health care interventions, increase supply-sensitive services without positive health effect and have a negative influence on people’s general and self-perceived health causing more harm than good.[15] Of ethical reasons, the possible causal effect of disease labelling on SRH is impossible to ee assess in a randomized controlled trial. Our study emphasizes the need for more prospective rr research to investigate potential health effects of disease labelling and early diagnosis. CONCLUSION ev Our data suggest that early identification of disease may imply a negative effect on SRH, and ie to the extent that SRH has been associated with greater mortality, this may lead to harm. w However, as it is also known that diseases such as diabetes and hypertension also lead to on increased mortality when detected after cardiovascular and metabolic complications have developed, it remains to be seen if an early identification or a late detection strategy would provide optimal health for the population. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 16 of 48 Page 17 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 17 of 24 FOOTNOTES Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. rp Fo Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. ee Contributors All authors meet the four criteria for authorship recommended by the International Committee of Medical Journal Editors. SF, AL, and SK have been active supervisors in study conception, design, conduct, interpretation, and reporting. PJ analyzed the data and drafted the manuscript. Critical revisions were done by all supervisors and all authors approved the final version of the manuscript. SF, AL, SK and PJ are joint guarantors. ev rr Acknowledgements The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology NTNU), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. The authors would like to thank Bjørn Olav Åsvold for his contribution in planning of the thyroid-part of the study. w ie Transparency declaration PJ affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there were no discrepancies from the study as planned. on Ethical approval The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Funding No external funding. PJ received a PhD-grant, funded by the Norwegian University of Science and Technology, NTNU. Data sharing statement No additional data available. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 18 of 24 1. Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ 2005;31(4):564-71 doi: 10.1177/0145721705279050[published Online First: Epub Date]|. 2. Borzecki AM, Wong AT, Hickey EC, et al. Hypertension control: how well are we doing? Arch Intern Med 2003;163(22):2705-11 doi: 10.1001/archinte.163.22.2705[published Online First: Epub Date]|. 3. Andros V, Egger A, Dua U. Blood pressure goal attainment according to JNC 7 guidelines and utilization of antihypertensive drug therapy in MCO patients with type 1 or type 2 diabetes. J Manag Care Pharm 2006;12(4):303-9 4. Liddy C, Singh J, Hogg W, et al. Quality of cardiovascular disease care in Ontario, Canada: missed opportunities for prevention - a cross sectional study. BMC Cardiovasc Disord 2012;12:74 doi: 10.1186/1471-2261-12-74[published Online First: Epub Date]|. 5. Huebschmann AG, Mizrahi T, Soenksen A, et al. Reducing clinical inertia in hypertension treatment: a pragmatic randomized controlled trial. J Clin Hypertens (Greenwich) 2012;14(5):322-9 doi: 10.1111/j.1751-7176.2012.00607.x[published Online First: Epub Date]|. 6. Alkerwi Aa, Pagny S, Lair M-L, et al. Level of Unawareness and Management of Diabetes, Hypertension, and Dyslipidemia among Adults in Luxembourg: Findings from ORISCAV-LUX Study. PLoS One 2013;8(3):e57920 doi: 10.1371/journal.pone.0057920[published Online First: Epub Date]|. 7. Khan N, Chockalingam A, Campbell NR. Lack of control of high blood pressure and treatment recommendations in Canada. Can J Cardiol 2002;18(6):657-61 8. Hetlevik I, Holmen J, Kruger O, et al. Fifteen years with clinical guidelines in the treatment of hypertension - still discrepancies between intentions and practice. Scand J Prim Health Care 1997;15(3):134-40 doi: Doi 10.3109/02813439709018503[published Online First: Epub Date]|. 9. Hetlevik I, Holmen J, Midthjell K. Treatment of diabetes mellitus - physicians' adherence to clinical guidelines in Norway. Scand J Prim Health Care 1997;15(4):193-97 doi: Doi 10.3109/02813439709035027[published Online First: Epub Date]|. 10. Petursson H, Getz L, Sigurdsson JA, et al. Current European guidelines for management of arterial hypertension: Are they adequate for use in primary care? Modelling study based on the Norwegian HUNT 2 population. BMC Fam Pract 2009;10 doi: Artn 70 Doi 10.1186/1471-229610-70[published Online First: Epub Date]|. 11. Petursson H, Getz L, Sigurdsson JA, et al. Can individuals with a significant risk for cardiovascular disease be adequately identified by combination of several risk factors? Modelling study based on the Norwegian HUNT 2 population. J Eval Clin Pract 2009;15(1):103-09 doi: DOI 10.1111/j.1365-2753.2008.00962.x[published Online First: Epub Date]|. 12. Getz L, Sigurdsson JA, Hetlevik I, et al. Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. Br Med J 2005;331(7516):551-54A doi: DOI 10.1136/bmj.38555.648623.8F[published Online First: Epub Date]|. 13. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 1999;282(15):1458-65 doi: 10.1001/jama.282.15.1458[published Online First: Epub Date]|. 14. Smith CM. Origin and uses of primum non nocere--above all, do no harm! J Clin Pharmacol 2005;45(4):371-7 doi: 10.1177/0091270004273680[published Online First: Epub Date]|. 15. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. Br Med J 2012;344 doi: Artn E3502 Doi 10.1136/Bmj.E3502[published Online First: Epub Date]|. 16. Miilunpalo S, Vuori I, Oja P, et al. Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 18 of 48 Page 19 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 19 of 24 working-age population. J Clin Epidemiol 1997;50(5):517-28 doi: S0895-4356(97)00045-0 [pii][published Online First: Epub Date]|. 17. Meurer LN, Layde PM, Guse CE. Self-rated health status: a new vital sign for primary care? WMJ 2001;100(7):35-9 18. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-5 doi: 59/5/342 [pii] 10.1136/jech.2004.021204[published Online First: Epub Date]|. 19. Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24(3):218-24 20. Bopp M, Braun J, Gutzwiller F, et al. Health risk or resource? Gradual and independent association between self-rated health and mortality persists over 30 years. PLoS One 2012;7(2):e30795 doi: 10.1371/journal.pone.0030795 PONE-D-11-20499[pii][published Online First: Epub Date]|. 21. Moller L, Kristensen TS, Hollnagel H. Self rated health as a predictor of coronary heart disease in Copenhagen, Denmark. J Epidemiol Community Health 1996;50(4):423-8 22. Kaplan GA, Goldberg DE, Everson SA, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol 1996;25(2):259-65 doi: Doi 10.1093/Ije/25.2.259[published Online First: Epub Date]|. 23. Krokstad S, Johnsen R, Westin S. Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol 2002;31(6):1183-91 doi: 10.1093/ije/31.6.1183[published Online First: Epub Date]|. 24. Halford C, Wallman T, Welin L, et al. Effects of self-rated health on sick leave, disability pension, hospital admissions and mortality. A population-based longitudinal study of nearly 15,000 observations among Swedish women and men. BMC Public Health 2012;12:1103 doi: 10.1186/1471-2458-12-1103[published Online First: Epub Date]|. 25. Latham K, Peek CW. Self-Rated Health and Morbidity Onset Among Late Midlife US Adults. J Gerontol B-Psychol 2013;68(1):107-16 doi: DOI 10.1093/geronb/gbs104[published Online First: Epub Date]|. 26. Benyamini Y, Idler EL. Community studies reporting association between self-rated health and mortality - Additional studies, 1995 to 1998. Res Aging 1999;21(3):392-401 doi: Doi 10.1177/0164027599213002[published Online First: Epub Date]|. 27. Nielsen AB, Siersma V, Hiort LC, et al. Self-rated general health among 40-year-old Danes and its association with all-cause mortality at 10-, 20-, and 29 years' follow-up. Scand J Public Health 2008;36(1):3-11 doi: 10.1177/1403494807085242[published Online First: Epub Date]|. 28. Schou MB, Krokstad S, Westin S. How is self-rated health associated with mortality? Tidsskr Nor Laegeforen 2006;126(20):2644-7 29. Barger SD, Muldoon MF. Hypertension labelling was associated with poorer self-rated health in the Third US National Health and Nutrition Examination Survey. J Hum Hypertens 2006;20(2):117-23 doi: 10.1038/sj.jhh.1001950[published Online First: Epub Date]|. 30. Bloom JR, Monterossa S. Hypertension Labeling and Sense of Well-Being. Am J Public Health 1981;71(11):1228-32 doi: Doi 10.2105/Ajph.71.11.1228[published Online First: Epub Date]|. 31. Moum T, Naess S, Sorensen T, et al. Hypertension Labeling, Life Events and Psychological WellBeing. Psychol Med 1990;20(3):635-46 32. Macdonald LA, Sackett DL, Haynes RB, et al. Labelling in hypertension: A review of the behavioural and psychological consequences. J Chronic Dis 1984;37(12):933-42 doi: http://dx.doi.org/10.1016/0021-9681(84)90070-5[published Online First: Epub Date]|. 33. Bianchi GP, Zaccheroni V, Solaroli E, et al. Health-related quality of life in patients with thyroid disorders - A study based on Short-Form 36 and Nottingham Health Profile Questionnaires. Qual Life Res 2004;13(1):45-54 doi: Doi 10.1023/B:Qure.0000015315.35184.66[published Online First: Epub Date]|. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 20 of 24 34. Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag Health Study 1995-97 (HUNT 2): objectives, methods, and participation. Norsk Epidemiol 2003 13 (1 ):19-32 35. Krokstad S, Langhammer A, Hveem K, et al. Cohort Profile: The HUNT Study, Norway. Int J Epidemiol 2012 doi: dys095 [pii] 10.1093/ije/dys095[published Online First: Epub Date]|. 36. Schnittker J, Bacak V. The Increasing Predictive Validity of Self-Rated Health. PLoS One 2014;9(1):e84933 doi: 10.1371/journal.pone.0084933[published Online First: Epub Date]|. 37. Idler EL, Benyamini Y. Self-rated health and mortality: A review of twenty-seven community studies. J Health Soc Behav 1997;38(1):21-37 doi: Doi 10.2307/2955359[published Online First: Epub Date]|. 38. Manor O, Matthews S, Power C. Dichotomous or categorical response? Analysing self-rated health and lifetime social class. Int J Epidemiol 2000;29(1):149-57 doi: Doi 10.1093/Ije/29.1.149[published Online First: Epub Date]|. 39. Bjoro T, Holmen J, Kruger O, et al. Prevalence of thyroid disease, thyroid dysfunction and thyroid peroxidase antibodies in a large, unselected population. The Health Study of Nord-Trondelag (HUNT). Eur J Endocrinol 2000;143(5):639-47 doi: 1430639 [pii][published Online First: Epub Date]|. 40. Giron P. Determinants of self-rated health in Spain: differences by age groups for adults. Eur J Public Health 2012;22(1):36-40 doi: 10.1093/eurpub/ckq133[published Online First: Epub Date]|. 41. Davies HTO, Crombie IK, Tavakoli M. When can odds ratios mislead? Br Med J 1998;316(7136):989-91 42. Langhammer A, Krokstad S, Romundstad P, et al. The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms. BMC Med Res Methodol 2012;12:143 doi: 10.1186/1471-2288-12-143[published Online First: Epub Date]|. 43. Molarius A, Janson S. Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol 2002;55(4):364-70 doi: http://dx.doi.org/10.1016/S0895-4356(01)00491-7[published Online First: Epub Date]|. 44. Hansen AH, Halvorsen PA, Ringberg U, et al. Socio-economic inequalities in health care utilisation in Norway: a population based cross-sectional survey. BMC Health Serv Res 2012;12:336 doi: 10.1186/1472-6963-12-336[published Online First: Epub Date]|. 45. Vingilis E, Wade T, Seeley J. Predictors of adolescent health care utilization. J Adolesc 2007;30(5):773-800 doi: http://dx.doi.org/10.1016/j.adolescence.2006.10.001[published Online First: Epub Date]|. 46. Breidablik H-J, Meland E, Lydersen S. Self-rated health during adolescence: stability and predictors of change (Young-HUNT study, Norway). The European Journal of Public Health 2009;19(1):73-78 doi: 10.1093/eurpub/ckn111[published Online First: Epub Date]|. 47. Welch HG, Sharp SM, Gottlieb DJ, et al. Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries. JAMA 2011;305(11):1113-8 doi: 10.1001/jama.2011.307[published Online First: Epub Date]|. 48. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138(4):288-98 49. Wennberg JE. Tracking medicine. A researcher’s quest to understand health care. Oxford: Oxford University Press, 2010. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 20 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 21 of 48 BMJ Open Page 21 of 24 Study population Men (n=16,220) Women (n=17,514) n % SRH good (%) n % SRH good (%) 40-50 years 7058 40.3 77.6 6517 40.2 81.7 51-60 years 5709 32.6 64.4 5328 32.8 72.1 61-70 years 4747 27.1 56.6 4375 27.0 59.6 0.6 58.4 4804 0.2 42.9 7026 39.1 72.8 8694 29.7 75.3 3489 40.3 68.5 2635 53.8 73.6 56.5 35 16.3 64.8 70.3 30.1 80.0 68.0 37.9 69.8 5172 32.0 69.1 (n= 33,734) Age group BMI (kg/m2) <18,5 25,0-29,9 6821 20.0 Never smoked daily 6973 40.1 4849 Previous daily smoker 4651 26.7 6105 Daily smoker 5763 33.1 64.3 14888 88.7 66.7 1471 8.8 430 < 10 years >30 (0.4% missing) Smoking status Alcohol use ly on (0.7% missing) w 104 ie ev rr 18,5-24,9 ee rp Fo 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 11488 73.2 71.0 76.8 2839 18.1 78.7 2.6 76.3 1375 8.8 78.3 8133 48.5 60.5 5711 36.5 63.1 10 – 12 years 5682 33.9 72.8 6615 42.2 76.0 > 12 years 2962 17.7 80.0 3339 21.3 84.7 None to low intake Moderate intake High intake (3.7% missing) Educational level (3.8% missing) EmployedFor peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Yes 11539 67.2 77.1 12309 77.1 79.9 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 22 of 48 Page 22 of 24 5627 32.8 49.0 3665 22.9 49.2 No 10348 59.1 85.9 9912 63.0 88.7 Yes 6275 35.8 39.8 5829 37.0 46.0 14373 86.2 68.7 7804 94.3 72.1 Unknown hypothyroidism 107 0.6 78.5 16 0.2 68.8 Subclinical hypothyroidism 466 2.8 75.0 150 1.8 66.4 Known hypothyroidism 858 5.1 48.9 124 1.5 58.1 5.2 61.4 180 2.2 56.2 64.6 69.4 9196 56.9 74.6 No (1.8% missing) Any long-term impairment (4.1% missing) Thyroid function rp Fo No thyroid disease Other thyroid dysfunction (1.3% missing) ee Diabetes mellitus No diabetes 872 rr 11279 ev 46 0.3 52.2 88 0.5 67.8 Probable diabetes 5728 32.8 65.9 6392 39.6 71.5 Known diabetes 395 482 3.0 49.5 Unknown diabetes 2.3 43.1 w (0.4% missing) ie Blood pressure status Normotensive 9135 52.6 72.4 6858 42.7 77.5 Unknown mild/moderate hypertension 4473 25.8 67.9 5343 33.3 74.7 403 2.4 70.7 349 2.2 73.8 3327 19.2 54.0 3498 21.8 59.6 34332 97.3 70.3 30378 98.4 74.9 Known hypertension ly Unknown severe hypertension on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 (0.9% missing) Overall study population, HUNT2 Table 1. Good self-rated health (SRH) by sex and characteristics of the study population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 23 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 23 of 24 Table 2. The association between self-rated health and thyroid function, diabetes mellitus and blood pressure. Odds ratio (OR) of good self-rated health and 95% confidence intervals (95% CI), crude, age adjusted, and adjusted for age, other long-term illness or injury that impairs function in everyday life, smoking habits, alcohol use, educational level, work status and body mass index. Cases with missing data were excluded from the analyses. Women OR (95% CI) Crude n rp Fo Age adjusted Men Multiple adjusted n OR (95% CI) Crude Age adjusted Multiple adjusted Thyroid function No thyroid dysfunction Unknown hypothyroidism Subclinical hypothyroidism 1247 6 92 394 718 Known hypothyroidism 729 1.13 (0.721.37 (1.10- 1.49 (1.20- 1.48 (1.13- 128 0.77 (0.540.88 (0.62- 1.76) 1.08) 1.85) 1.94) 1.69) 1.24) 107 0.69 (0.440.54 (0.370.44 (0.38- 0.48 (0.41- 0.49 (0.410.63 (0.43- 1.09) 163 0.77) 0.55) 0.59) 0.50) 0.91) 0.58 (0.410.50 (0.370.72 (0.63- 0.77 (0.67- 0.77 (0.650.52 (0.38- 0.84) 0.67) 0.89) 0.93) 0.83) 0.71) 39 4797 Known diabetes 318 1.00 1.00 w Probable diabetes 846 1.00 1.00 1.00 4 0.72 (0.46- 0.88 (0.55- 1.03 (0.590.48 (0.27- 0.61 (0.34- 0.66 (0.3282 1.13) 1.10) 1.81) 0.86) 1.37) 1.39) 1.00 ie Unknown diabetes 9946 ev Diabetes mellitus No diabetes 1.00 rr Other thyroid dysfunction 704 1.00 1.00 1.00 5 0.85 (0.30- 0.92 (0.31- 1.28 (0.351.66 (1.05- 2.00 (1.25- 1.84 (1.024.65) 14 2.45) 3.19) 3.33) 2.64) 2.72) 1.00 1.00 ee 0.85 (0.80- 0.94 (0.88- 1.01 (0.92- 575 0.86 (0.80- 0.94 (0.88- 0.99 (0.919 0.92) 1.08) 1.01) 0.91) 1.10) 1.01) on 0.33 (0.27- 0.42 (0.34- 0.53 (0.41- 395 0.33 (0.28- 0.42 (0.35- 0.55 (0.430.70) 0.40) 0.41) 0.51) 0.69) 0.51) Blood pressure No hypertension 8180 Unknown mild/moderate hypertension 3787 Unknown severe hypertension 2745 Known hypertension 325 ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 637 1.00 8 0.81 (0.75- 1.01 (0.93- 1.10 (0.990.86 (0.79483 0.93) 1.09) 0.87) 1.22) 7 0.92 (0.74- 1.34 (1.08- 1.52 (1.140.85 (0.77308 1.08) 1.68) 1.15) 2.02) 1.00 1.00 1.00 1.00 1.00 1.01 (0.92- 1.01 (0.921.10) 1.12) 1.27 (0.99- 1.48 (1.091.62) 2.02) 0.45 (0.41- 0.59 (0.54- 0.69 (0.61- 311 0.43 (0.39- 0.54 (0.50- 0.64 (0.570.49) 0.60) 0.72) 8 0.47) 0.65) 0.77) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 24 of 24 What is already known on this topic Awareness of thyroid dysfunction, diabetes mellitus, and hypertension is associated with reduced self-rated health Screening, increasingly sensitive diagnostic tests, and widened diagnostic criteria will define more healthy people as sick rp Fo What this study adds Unawareness of hypothyroidism, diabetes mellitus, or hypertension is not associated with reduced self-rated health w ie ev rr ee ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 24 of 48 Page 25 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 1 of 22 Is there an association between disease ignorance and self-rated health? The HUNT Study, a crosssectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad, Siri Forsmo Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway Pål Jørgensen PhD Candidate HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, 7600 Levanger, Norway Arnulf Langhammer Professor, Head of HUNT Databank HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Steinar Krokstad Professor, Head of HUNT Research Center Department of Public Health and General Practice, Norwegian University of Science and Technology, Siri Forsmo Professor, Head of Department rr ee rp Fo Correspondence to: P Jørgensen pal_jorgensen@ntnu.no ev Keywords: Self-rated health, awareness, hypothyroidism, diabetes, hypertension. Word count: 33593380 w ie ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 2 of 22 ABSTRACT Objective To explore if awareness versus unawareness of thyroid dysfunction, diabetes mellitus or hypertension is associated with self-rated health. Design Large-scale, cross sectional population based study. The association between thyroid function, diabetes mellitus, and blood pressure and self-rated health was explored by multiple rp Fo logistic regression analysis. Setting The second survey of the Nord-Trøndelag Health Study, HUNT2, 1995-97. Participants 33,734 persons aged 40-70 years. ee Primary outcome measures Logistic regression was used to estimate odds ratios for good rr self-rated health as a function of thyroid status, diabetes mellitus status and blood pressure status. ev Results Persons aware of their hypothyroidism, diabetes mellitus, or hypertension reported ie poorer self-rated health than individuals without such conditions. Women with unknown and w subclinical hypothyroidism reported better self-rated health than women with normal thyroid status. Both in women and men, unknown and probable diabetes, as well as unknown on mild/moderate hypertension was not associated with poorer health. Further, persons with unknown severe hypertension reported better health than normotensive persons. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Conclusions People with undiagnosed, but prevalent hypothyroidism, diabetes mellitus, and hypertension often have good self-rated health, whilst when aware of their diagnoses, they report reduced self-rated health. Use of screening, more sensitive tests, and widened diagnostic criteria might have a negative effect on perceived health in the population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 26 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 27 of 48 BMJ Open Page 3 of 22 STRENGTHS AND LIMITATIONS OF THIS STUDY Strengths • Sample from a large-scale, general population • High-prevalent diseases under study; ensuring statistical power in subgroup analyses Limitations rp Fo • Study mainly based on self-reported data • Cross-sectional study; susceptibility to confounding and impossibility to assume causal relationships INTRODUCTION ev rr ee Guidelines for prevention and treatment have been developed for most high prevalent diseases in western countries aiming for reduction of morbidity and mortality by interventions mainly in primary health care (PHC). w ie In the society there seems to be an increasing conviction of achievable zero-vision regarding on risks and diseases. Part of the strategy is to detect risk factors and pre-diseases in even earlier stages. From a secondary or tertiary health care level, this might seem reasonable since ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 intervention on many individuals with specific risk factors presumably can prevent or delay disease or progression of disease. Further, health authorities and hospital clinicians regularly raise concern of the lack of detection of risk factors, of subclinical conditions and of achieving treatment goals.[1-7] Norwegian studies have shown that guidelines are often difficult to implement and adhere to in PHC.[8 9] According to guidelines, most individuals would be defined as at risk and resources needed to handle this appropriately could destabilize the entire health care system.[10-12] An American review pointed out knowledge, attitude, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 4 of 22 and behaviour as barriers of physician’s adherence to clinical guidelines.[13] In an already complex and busy PHC-setting, one might expect that resources used for disease prevention and case finding have to compete with resources for handling acknowledged disease. Also, physicians might want to avoid increasing disease related burden for patients, in line with the old wisdom; “primum non nocere”.[14] Thus the risk and disease zero-visions in society and among politicians are seldom shared by PHC professionals. rp Fo When guidelines, mainly based on research from high risk hospital populations, are applied on low risk populations in PHC, more healthy individuals are identified as being at risk or are given diagnoses. Also the widened inclusion criteria for diagnoses in general and use of more ee sensitive tests contribute to define more individuals at risk or as unhealthy.[15] Possible undesirable outcomes of such strategies remain unclear. rr Self-rated health (SRH) is a valid and widely used measure of general health in epidemiologic ev research.[16-19] It is associated with several clinical conditions often seen in PHC, with ie recovery [20-23] and is found to predict morbidity, sick leave, and disability pension,[24 25] as well as mortality.[26-28] The majority of studies describing association between labelling w of disease per se and SRH have focused on arterial hypertension.[29-32] However, one study on has indicated reduced SRH among individuals labelled with thyroid dysfunctions.[33] ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The aim of this study was to investigate whether persons’ awareness versus unawareness of thyroid dysfunction, diabetes mellitus, or hypertension was associated with their SRH, as reported in a population-based health study in Norway. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 28 of 48 Page 29 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 5 of 22 METHODS Study population The data sample in this study stem from the second wave of the Nord-Trøndelag Health Study (HUNT2) conducted in 1995-97 in the county of Nord-Trøndelag, Norway. All individuals aged 20 years and older, living in the county, were invited (94,194 individuals). In all, 66.7% rp Fo of men (n=30,860) and 75.5% of women (n=35,280) participated. The survey consisted of both questionnaires and measurements, and is described previously in detail.[34 35] In our study we included answers from the main questionnaire and the baseline measurements for persons aged 40-70 years. The age span was chosen because thyroid stimulating hormone ee (TSH) was analysed in all women and in 50% of men at this age, of a rather low disease rr burden in people younger than 40 years, and of a lower attendance rate under and above this age span. A total of 24,950 individuals had TSH measurements and answered thyroid ev questions, thus were eligible for analysis on thyroid dysfunction, whilst in the analysis of ie diabetes mellitus and blood pressure, 33,734 individuals were included in all. Self-rated health w on The first question in the main questionnaire in HUNT2, answered before attending the examination stations, was “How is your health at the moment?”, with answer alternatives; ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 “very good”, “good”, “not so good”, and “poor”. This short version of SRH measure is shown to be a valid predictor of mortality. [18 28 36 37] We dichotomized the answers into “good” (very good, good) and “poor” (not so good, poor). Dichotomization of multinomial SRH is commonly performed, and has been validated by Manor et. al.[38] Thyroid function For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 6 of 22 The participants answered questions on history of hypo- and hyperthyroidism, goitre, other thyroid diseases, and treatment with thyroxin, radio-iodine, surgery, or thyreostatic medication. Serum TSH and free T4 were analysed at the Hormone laboratory, Aker University Hospital, Norway. The laboratory reference value for TSH, as defined prior to the survey, was 0.2-4.5 rp Fo mU/L and for free T4 8.0-20.0 pmol/L. If TSH was <0.2 mU/L or >4.0 mU/L, and/or if the participant reported any thyroid disease, serum free T4 was also measured.[39] Individuals reporting no previous thyroid disease and having TSH within reference range were categorized as “no thyroid disease” and chosen as reference category. No previous ee thyroid disease combined with TSH >4.5 mU/L and free T4 <8.0 pmol/L was defined as rr unknown hypothyroidism. No previous thyroid disease combined with TSH >4.5 mU/L and free T4 8.0 – 20.0 pmol/L was defined as subclinical hypothyroidism. Individuals reporting ev hypothyroidism and use of thyroxin were classified as having known hypothyroidism, ie regardless of the TSH and T4 levels. Affirmative answers to other thyroid related questions or measures outside reference range in the remainders were classified as other thyroid dysfunction. ly on Diabetes mellitus w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Diabetes mellitus was assessed through self-report and blood samples. Serum glucose was analysed at Levanger Hospital, Norway. Those reporting no diabetes and having normal glucose levels (<5.5 mmol/L) were classified as “no diabetes” and were chosen as reference category. No self-reported diabetes and non-fasting glucose >11.0 mmol/L was categorized as unknown diabetes, whereas no diabetes and non-fasting glucose 5.5-11.0 mmol/L was For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 30 of 48 Page 31 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 7 of 22 categorized as probable diabetes. Self-reported diabetes was classified as known diabetes regardless of the glucose level. Blood pressure In the questionnaire participants were asked about the doctor’s advice after the latest blood pressure measurement prior to participation in HUNT. The answer categories were: “no rp Fo follow-up and no medication necessary”, “recommended follow-up examination but not to take medicine”, “start or continue taking medicine for high blood pressure”, or “never measured”. At HUNT2, mean systolic and mean diastolic arterial blood pressure (BP) of measurement 2 and 3 was categorized into normal (systolic (s) BP < 140 mmHg and diastolic ee (d) BP < 90 mmHg), mild hypertension (sBP 140-159 mmHg and dBP <100 mmHg or sBP rr <160 mmHg and dBP 90-99 mmHg), moderate hypertension (sBP 160-179 mmHg and dBP <109 mmHg or sBP <180 mmHg and dBP 100-109 mmHg), and severe hypertension ev (sBP>180 mmHg or dBP>110 mmHg). We constructed a new variable to define ie normotensive (reference), unknown mild- and moderate hypertensive, unknown severe hypertensive, and known hypertensive persons on the basis of self-report and measures. w Statistical analysis on The descriptive analyses of the study population were stratified by gender, and we used chi- ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 square tests to examine any difference in proportions of SRH between the independent variables. Gender-stratified multiple logistic regression were used to estimate odds ratio (OR) with 95% confidence intervals (CI) for good SRH, as a function of thyroid status, diabetes mellitus status and blood pressure status, in separate unadjusted, age adjusted, and multi adjusted analyses for each condition. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 8 of 22 Age, smoking, alcohol consumption, body mass index (BMI), working- and educational status, and self-reported limiting long-term illness or injury are associated with SRH[40] and the diseases under study, but likely not affected by SRH or the diseases. Hence, these variables were included, a priori, as confounders in the models. Age was categorized into age groups; 40-49 years, 50-59 years, and 60-70 years. Smoking status was categorized into never smoked daily, previous daily smoker, and current daily smoker. Alcohol units (AU) were rp Fo defined as number of glasses of wine, beer or liquor. Those reporting to be teetotalers or to have alcohol intake less than four times a month or less than seven AU per two weeks were categorized as low consumers, those reporting drinking five to eight times a month or 8-14 ee AU per two weeks as moderate consumers, and those drinking more often than eight times a month or more than 14 AU as heavy consumers. BMI (kg/m2) was calculated of measured rr height and weight and categorized according to The World Health Organization’s (WHO) definition; underweight (18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0- ev 29.9 kg/m2) and obese (>30.0 kg/m2). People reporting paid- or self-employed work were ie classified as working, otherwise as not working. Educational level was categorized into <10 w years, 10-12 years and >12 years. We chose affirmative answer to the question “Do you suffer from any long-term illness or injury (at least one year) of a physical or psychological nature on that impairs your functioning in your everyday life?” to represent all relevant chronic medical conditions that could confound the results. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 To examine whether the association of the three disease statuses with SRH differed by categories of the other independent variables, we used likelihood ratio-tests with p-value for statistical interaction. We tested for multicollinearity between the independent variables, by linear regression. Areas under the receiver operating characteristic curves (AUC) were calculated to evaluate the performance of the logistic regression models. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 32 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 33 of 48 BMJ Open Page 9 of 22 In an additional analysis, the association between SRH and having had one or more medical consultations during the last year was investigated by logistic regression models, stratified by gender, both in the total study population and after exclusion of persons with diagnoses under study. All analyses were preformed with IBM SPSS Statistics version 20 for windows. rp Fo The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. RESULTS ee In all age categories, a higher proportion of men than women reported good SRH (p<0.001), and in both sexes the proportion reporting good SRH declined by age (p<0.002) (Table 1). rr The proportion reporting good SRH was lower in overweight, obese, and underweight ev women, than in normal weight women (p<0.001). In men the proportion reporting good SRH declined between the normal weight group to overweight-, obese-, and underweight group ie (p<0.001). In previous and current female smokers, a lower proportion reported good SRH w compared to non smokers (p<0.001). In men, the proportion reporting good SRH was higher among non smokers than among previous and current smokers (p<0.001), whereas there was on no difference between previous and current smokers. The proportion reporting good SRH was ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 higher in moderate and heavy alcohol consumers than in low consumers, increased with education and was higher for participants in paid work (p<0.001). Underweight men and persons with “any long-term impairment” had the lowest proportion reporting good SRH of all groups. The proportion reporting good SRH in the overall HUNT 2 study population differed from the proportions reported in persons without thyroid disease and normotensive persons (p<0.01), but not from persons without diabetes mellitus. However, the absolute differences were small. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 10 of 22 In all fully adjusted regression models, the AUC was 0.80. Unadjusted, the AUC ranged from 0.61 to 0.63. There was no multicollinearity between the independent variables. Thyroid function rp Fo Thyroid dysfunctions, both known and unknown were more often observed among women than among men (p<0.001) (Table 1). Women with known hypothyroidism had lower odds of reporting good SRH (OR 0.49 (95% CI 0.41 to 0.59) compared tothan women without thyroid disease in the adjusted analyses., butHowever, women with unknown or subclinical ee hypothyroidism had 84% and 48% higher odds, respectively, of reporting good SRH rr compared to the odds of women without thyroid disease (Table 2). The association between thyroid function and SRH was basically unchanged after inclusion of confounder variables. ev Corresponding, but non-significant associations were found among men. Diabetes mellitus w ie The prevalence of unknown, probable, and known diabetes was slightly higher in men than in on women (p<0.001) (Table 1). Women with known diabetes mellitus had lower odds of good SRH than those without diabetes in the adjusted analyses; OR 0.53 (95% CI 0.41 to 0.69), ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 whereas in women with unknown or possible diabetes mellitus, the odds of good SRH were similar to the odds among persons without diabetes, in the adjusted analyses (Table 2). In the adjusted analyses, the association between unknown and probable diabetes mellitus with poor SRH, found in the crude analyses, disappeared when age was included in the model in women and men, but also by inclusion of working status alone in women. In men, the association of diabetes status with SRH differed by levels of education. Among men without higher education (12 years or less), the odds of good SRH were as in the main-effect model (Table For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 34 of 48 Page 35 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 11 of 22 2). However in men with higher education, the ORs of good SRH were barely significantly lower among men with unknown diabetes (OR 0.29 (95% CI 0.09-1.00)) and among men with possible diabetes (OR 0.79 (95% CI 0.63-1.00)) compared to men without diabetes. Among men with known diabetes in this stratum, the OR of good SRH was 0.31 (95% CI 0.17-0.54) compared to men without diabetes. rp Fo Blood pressure The prevalence of unknown mild and moderate hypertension was higher in men than in women (p<0.001). Unknown severe hypertension and known hypertension were equally distributed between women and men (Table 1). Women with known hypertension had lower ee odds of reporting good SRH than normotensive women, in the adjusted analyses. The figures rr were similar in men (Table 2). In contrast; compared to normotensive women, those with unknown severe hypertension had 52 % higher odds of reporting good SRH, with similar ev figures in men. Persons with unknown mild and moderate hypertension reported good SRH ie similar to the normotensive ones. Adjusted for age, the association between unknown mild and moderate hypertension and poor SRH disappeared, simultaneously; unknown severe w hypertension became associated with good SRH in women. In men, age had to be added along on with either education- or working status to achieve the latter association. Additional analyses ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Women with poor SRH had more than six times the odds of those with good SRH to have had a medical consultation during the last year; OR 6.29 (95% CI 5.47 to 7.22). For men the corresponding OR was 5.53 (95% CI 4.86 to 6.29). After exclusion of persons with diagnosed thyroid disease, diabetes mellitus, known hypertension, and “any long-term disease”, the corresponding OR was 3.71 (95% CI 2.90 to 4.73), with similar figures in men. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 12 of 22 DISCUSSION This large population-based study showed that persons with known thyroid dysfunction, diabetes mellitus, and hypertension were less likely to report good SRH than those without such conditions. Less expected, persons with unknown and subclinical hypothyroidism were more likely to report good SRH than those without thyroid disease. Similarly, those with rp Fo unknown severe hypertension were more likely to report good SRH, compared to persons with normal blood pressure. In general, persons with unknown diabetes and unknown mild/moderate hypertension, reported good health, just like the reference group. In general, of the confounders, age seemed to influence the association between disease ee statuses and SRH most when adjusted for. Age was found to explain the association of poor rr SRH with unknown and probable diabetes, and with unknown mild and moderate hypertension. In women, age even contributed to an association between unknown severe ev hypertension and good SRH. There seemed to be a linear decrease by age categories in the ie association with good SRH. The way age is known to be related to both disease and SRH makes these findings reasonable. w Although both a qualitative and quantitative measure of association, the estimated ORs in our on study will, if interpreted as relative risks, overestimate the case, because the prevalence of good SRH is high in all groups.[41] ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The main strengths of this study were the numbers of participants, that the diseases we studied were high-prevalent, and that we could assume representativeness to the general population regarding the variables included. It is known that individuals with high burden of symptoms are less likely to attend surveys, but so far there has been little evidence that non-participation For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 36 of 48 Page 37 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 13 of 22 on this basis introduce substantial bias in associational studies.[42] We studied diseases with generally low symptom-burden, and expect selection bias to be negligible. The main limitation was possibly that we relied on self-reported data on both dependent and independent variables. The validity of self reported measures relevant for this study is questionable. However, if any, there should be a non-differential misclassification, that only rp Fo should underestimate the associations found. There is always a possibility of residual confounding in non-randomized study designs, and due to the observational, cross-sectional design we neither can assume a causal relationship. ee Bias due to differential detection of disease in the study population could lead to a type 1 error. Hypothyroidism and diabetes mellitus are often associated with vague symptoms such rr as tiredness and weakness. These symptoms are strongly associated with reduced SRH.[43] It ev is likely that presenting such symptoms for the GP would result in measurements of TSH, free T4, and serum glucose, thus reveal any related dysfunction. Low self-perceived health ie increases the probability to visit a GP.[44] The social security covers most costs related to w clinical measurements and blood sampling in Norway, thus we expect GPs to have a low threshold to measure thyroid function, blood pressure or glucose levels. People who do not on consult their GP will not have diseases with mild or no symptoms diagnosed, and their ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 personality could be characterized by less worrying and more optimistic attitude to health being reflected in better SRH.[45] On the other hand, the association between known disease and poor SRH could in fact be explained physiologically due to the pathological effect of disease. Lack of corresponding association between ignored, but prevalent disease and poor SRH is not in line with this For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 14 of 22 hypothesis, rising question of a possible adverse effect of disease labelling. However, confounding by severity of disease cannot be ruled out. Due to low numbers of persons having unknown hypothyroidism and diabetes mellitus, the results should be interpreted with caution. On the other hand, there were high numbers in the subclinical and probable groups, and analyses of these groups did not show any associations rp Fo with poor SRH, also rising question of a possible disease labelling effect. The fact that the HUNT2 survey was carried out nearly 20 years ago raises a question of generalisability to today’s population. Stability of SRH over time has not been investigated in our study population, although investigated among adolescents.[46] We do not expect the ee association between low burden- or subclinical disease with SRH to be time dependent to the rr extent that it would change our results considerably. Neither do we expect the changes in prevalence of most explanatory variables to influence the associations found. ev Consistent findings regarding unknown, subclinical, and probable disease, versus known ie disease, could indicate a potential adverse effect of disease labelling. Although early detection w of disease is protective on morbidity and mortality for many diseases, low SRH is also shown to be associated morbidity and mortality.[25-27] This is an important aspect in the debate of presymptomatic case-finding. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The BMJ's Too Much Medicine campaign aims to highlight the threat to human health posed by overdiagnosis and the waste of resources on unnecessary care (http://www.bmj.com/toomuch-medicine). American data have shown that the majority of all health care includes preference-sensitive and supply-sensitive services. The extent of these services varies greatly without necessarily leading to better health.[47 48] A great deal of activity in such services is based on identifying subclinical disease. The negative health effect this might have, For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 38 of 48 Page 39 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 15 of 22 modulated through reduced SRH, can explain why population mortality is not reduced in areas with high frequency of diagnoses. Both public and academic debates are often characterised by the conviction that all medical treatment is efficient. Wennberg showed that a relatively small proportion of all medical treatment is indisputably good for health.[49] The concern for unrevealed risk factors and rp Fo subclinical conditions might lead to unnecessary costly health care interventions, increase supply-sensitive services without positive health effect and have a negative influence on people’s general and self-perceived health causing more harm than good.[15] Of ethical reasons, the possible causal effect of disease labelling on SRH is impossible to ee assess in a randomized controlled trial. Our study emphasizes the need for more prospective rr research to investigate potential health effects of disease labelling and early diagnosis. CONCLUSION ev Our data suggest that early identification of disease may imply a negative effect on SRH, and ie to the extent that SRH has been associated with greater mortality, this may lead to harm. w However, as it is also known that diseases such as diabetes and hypertension also lead to on increased mortality when detected after cardiovascular and metabolic complications have developed, it remains to be seen if an early identification or a late detection strategy would provide optimal health for the population. ly 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 FOOTNOTES Copyright The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 16 of 22 work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above. Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Contributors All authors meet the four criteria for authorship recommended by the International Committee of Medical Journal Editors. SF, AL, and SK have been active supervisors in study conception, design, conduct, interpretation, and reporting. PJ analyzed the data and drafted the manuscript. Critical revisions were done by all supervisors and all authors approved the final version of the manuscript. SF, AL, SK and PJ are joint guarantors. rp Fo Acknowledgements The Nord-Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology NTNU), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. The authors would like to thank Bjørn Olav Åsvold for his contribution in planning of the thyroid-part of the study. rr ee Transparency declaration PJ affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that there were no discrepancies from the study as planned. ev Ethical approval The study was approved by the Regional Committee for Medical Research. All participants signed written informed consent. ie Funding No external funding. PJ received a PhD-grant, funded by the Norwegian University of Science and Technology, NTNU. w Data sharing statement No additional data available. ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 40 of 48 Page 41 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 17 of 22 1. Ziemer DC, Miller CD, Rhee MK, et al. Clinical inertia contributes to poor diabetes control in a primary care setting. Diabetes Educ 2005;31(4):564-71 doi: 10.1177/0145721705279050[published Online First: Epub Date]|. 2. Borzecki AM, Wong AT, Hickey EC, et al. Hypertension control: how well are we doing? Arch Intern Med 2003;163(22):2705-11 doi: 10.1001/archinte.163.22.2705[published Online First: Epub Date]|. 3. Andros V, Egger A, Dua U. Blood pressure goal attainment according to JNC 7 guidelines and utilization of antihypertensive drug therapy in MCO patients with type 1 or type 2 diabetes. J Manag Care Pharm 2006;12(4):303-9 4. Liddy C, Singh J, Hogg W, et al. Quality of cardiovascular disease care in Ontario, Canada: missed opportunities for prevention - a cross sectional study. BMC Cardiovasc Disord 2012;12:74 doi: 10.1186/1471-2261-12-74[published Online First: Epub Date]|. 5. Huebschmann AG, Mizrahi T, Soenksen A, et al. Reducing clinical inertia in hypertension treatment: a pragmatic randomized controlled trial. J Clin Hypertens (Greenwich) 2012;14(5):322-9 doi: 10.1111/j.1751-7176.2012.00607.x[published Online First: Epub Date]|. 6. Alkerwi Aa, Pagny S, Lair M-L, et al. Level of Unawareness and Management of Diabetes, Hypertension, and Dyslipidemia among Adults in Luxembourg: Findings from ORISCAV-LUX Study. PLoS One 2013;8(3):e57920 doi: 10.1371/journal.pone.0057920[published Online First: Epub Date]|. 7. Khan N, Chockalingam A, Campbell NR. Lack of control of high blood pressure and treatment recommendations in Canada. Can J Cardiol 2002;18(6):657-61 8. Hetlevik I, Holmen J, Kruger O, et al. Fifteen years with clinical guidelines in the treatment of hypertension - still discrepancies between intentions and practice. Scand J Prim Health Care 1997;15(3):134-40 doi: Doi 10.3109/02813439709018503[published Online First: Epub Date]|. 9. Hetlevik I, Holmen J, Midthjell K. Treatment of diabetes mellitus - physicians' adherence to clinical guidelines in Norway. Scand J Prim Health Care 1997;15(4):193-97 doi: Doi 10.3109/02813439709035027[published Online First: Epub Date]|. 10. Petursson H, Getz L, Sigurdsson JA, et al. Current European guidelines for management of arterial hypertension: Are they adequate for use in primary care? Modelling study based on the Norwegian HUNT 2 population. BMC Fam Pract 2009;10 doi: Artn 70 Doi 10.1186/1471-229610-70[published Online First: Epub Date]|. 11. Petursson H, Getz L, Sigurdsson JA, et al. Can individuals with a significant risk for cardiovascular disease be adequately identified by combination of several risk factors? Modelling study based on the Norwegian HUNT 2 population. J Eval Clin Pract 2009;15(1):103-09 doi: DOI 10.1111/j.1365-2753.2008.00962.x[published Online First: Epub Date]|. 12. Getz L, Sigurdsson JA, Hetlevik I, et al. Estimating the high risk group for cardiovascular disease in the Norwegian HUNT 2 population according to the 2003 European guidelines: modelling study. Br Med J 2005;331(7516):551-54A doi: DOI 10.1136/bmj.38555.648623.8F[published Online First: Epub Date]|. 13. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines?: A framework for improvement. JAMA 1999;282(15):1458-65 doi: 10.1001/jama.282.15.1458[published Online First: Epub Date]|. 14. Smith CM. Origin and uses of primum non nocere--above all, do no harm! J Clin Pharmacol 2005;45(4):371-7 doi: 10.1177/0091270004273680[published Online First: Epub Date]|. 15. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. Br Med J 2012;344 doi: Artn E3502 Doi 10.1136/Bmj.E3502[published Online First: Epub Date]|. 16. Miilunpalo S, Vuori I, Oja P, et al. Self-rated health status as a health measure: the predictive value of self-reported health status on the use of physician services and on mortality in the w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 18 of 22 working-age population. J Clin Epidemiol 1997;50(5):517-28 doi: S0895-4356(97)00045-0 [pii][published Online First: Epub Date]|. 17. Meurer LN, Layde PM, Guse CE. Self-rated health status: a new vital sign for primary care? WMJ 2001;100(7):35-9 18. Bowling A. Just one question: If one question works, why ask several? J Epidemiol Community Health 2005;59(5):342-5 doi: 59/5/342 [pii] 10.1136/jech.2004.021204[published Online First: Epub Date]|. 19. Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24(3):218-24 20. Bopp M, Braun J, Gutzwiller F, et al. Health risk or resource? Gradual and independent association between self-rated health and mortality persists over 30 years. PLoS One 2012;7(2):e30795 doi: 10.1371/journal.pone.0030795 PONE-D-11-20499[pii][published Online First: Epub Date]|. 21. Moller L, Kristensen TS, Hollnagel H. Self rated health as a predictor of coronary heart disease in Copenhagen, Denmark. J Epidemiol Community Health 1996;50(4):423-8 22. Kaplan GA, Goldberg DE, Everson SA, et al. Perceived health status and morbidity and mortality: Evidence from the Kuopio Ischaemic Heart Disease Risk Factor Study. Int J Epidemiol 1996;25(2):259-65 doi: Doi 10.1093/Ije/25.2.259[published Online First: Epub Date]|. 23. Krokstad S, Johnsen R, Westin S. Social determinants of disability pension: a 10-year follow-up of 62 000 people in a Norwegian county population. Int J Epidemiol 2002;31(6):1183-91 doi: 10.1093/ije/31.6.1183[published Online First: Epub Date]|. 24. Halford C, Wallman T, Welin L, et al. Effects of self-rated health on sick leave, disability pension, hospital admissions and mortality. A population-based longitudinal study of nearly 15,000 observations among Swedish women and men. BMC Public Health 2012;12:1103 doi: 10.1186/1471-2458-12-1103[published Online First: Epub Date]|. 25. Latham K, Peek CW. Self-Rated Health and Morbidity Onset Among Late Midlife US Adults. J Gerontol B-Psychol 2013;68(1):107-16 doi: DOI 10.1093/geronb/gbs104[published Online First: Epub Date]|. 26. Benyamini Y, Idler EL. Community studies reporting association between self-rated health and mortality - Additional studies, 1995 to 1998. Res Aging 1999;21(3):392-401 doi: Doi 10.1177/0164027599213002[published Online First: Epub Date]|. 27. Nielsen AB, Siersma V, Hiort LC, et al. Self-rated general health among 40-year-old Danes and its association with all-cause mortality at 10-, 20-, and 29 years' follow-up. Scand J Public Health 2008;36(1):3-11 doi: 10.1177/1403494807085242[published Online First: Epub Date]|. 28. Schou MB, Krokstad S, Westin S. How is self-rated health associated with mortality? Tidsskr Nor Laegeforen 2006;126(20):2644-7 29. Barger SD, Muldoon MF. Hypertension labelling was associated with poorer self-rated health in the Third US National Health and Nutrition Examination Survey. J Hum Hypertens 2006;20(2):117-23 doi: 10.1038/sj.jhh.1001950[published Online First: Epub Date]|. 30. Bloom JR, Monterossa S. Hypertension Labeling and Sense of Well-Being. Am J Public Health 1981;71(11):1228-32 doi: Doi 10.2105/Ajph.71.11.1228[published Online First: Epub Date]|. 31. Moum T, Naess S, Sorensen T, et al. Hypertension Labeling, Life Events and Psychological WellBeing. Psychol Med 1990;20(3):635-46 32. Macdonald LA, Sackett DL, Haynes RB, et al. Labelling in hypertension: A review of the behavioural and psychological consequences. J Chronic Dis 1984;37(12):933-42 doi: http://dx.doi.org/10.1016/0021-9681(84)90070-5[published Online First: Epub Date]|. 33. Bianchi GP, Zaccheroni V, Solaroli E, et al. Health-related quality of life in patients with thyroid disorders - A study based on Short-Form 36 and Nottingham Health Profile Questionnaires. Qual Life Res 2004;13(1):45-54 doi: Doi 10.1023/B:Qure.0000015315.35184.66[published Online First: Epub Date]|. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 42 of 48 Page 43 of 48 BMJ Open Study population Page 19 of 22 Men (n=16,220) Women (n=17,514) 34. Holmen J, Midthjell K, Krüger Ø, et al. The Nord-Trøndelag Health Study 1995-97 (HUNT 2): objectives, methods, and participation. Norsk Epidemiol 2003 13 (1 ):19-32 35. Krokstad S, Langhammer A, Hveem K, et al. Cohort Profile: The HUNT Study, Norway. Int J Epidemiol 2012 doi: dys095 [pii] 10.1093/ije/dys095[published Online First: Epub Date]|. 36. Schnittker J, Bacak V. The Increasing Predictive Validity of Self-Rated Health. PLoS One 2014;9(1):e84933 doi: 10.1371/journal.pone.0084933[published Online First: Epub Date]|. 37. Idler EL, Benyamini Y. Self-rated health and mortality: A review of twenty-seven community studies. J Health Soc Behav 1997;38(1):21-37 doi: Doi 10.2307/2955359[published Online First: Epub Date]|. 38. Manor O, Matthews S, Power C. Dichotomous or categorical response? Analysing self-rated health and lifetime social class. Int J Epidemiol 2000;29(1):149-57 doi: Doi 10.1093/Ije/29.1.149[published Online First: Epub Date]|. 39. Bjoro T, Holmen J, Kruger O, et al. Prevalence of thyroid disease, thyroid dysfunction and thyroid peroxidase antibodies in a large, unselected population. The Health Study of Nord-Trondelag (HUNT). Eur J Endocrinol 2000;143(5):639-47 doi: 1430639 [pii][published Online First: Epub Date]|. 40. Giron P. Determinants of self-rated health in Spain: differences by age groups for adults. Eur J Public Health 2012;22(1):36-40 doi: 10.1093/eurpub/ckq133[published Online First: Epub Date]|. 41. Davies HTO, Crombie IK, Tavakoli M. When can odds ratios mislead? Br Med J 1998;316(7136):989-91 42. Langhammer A, Krokstad S, Romundstad P, et al. The HUNT study: participation is associated with survival and depends on socioeconomic status, diseases and symptoms. BMC Med Res Methodol 2012;12:143 doi: 10.1186/1471-2288-12-143[published Online First: Epub Date]|. 43. Molarius A, Janson S. Self-rated health, chronic diseases, and symptoms among middle-aged and elderly men and women. J Clin Epidemiol 2002;55(4):364-70 doi: http://dx.doi.org/10.1016/S0895-4356(01)00491-7[published Online First: Epub Date]|. 44. Hansen AH, Halvorsen PA, Ringberg U, et al. Socio-economic inequalities in health care utilisation in Norway: a population based cross-sectional survey. BMC Health Serv Res 2012;12:336 doi: 10.1186/1472-6963-12-336[published Online First: Epub Date]|. 45. Vingilis E, Wade T, Seeley J. Predictors of adolescent health care utilization. J Adolesc 2007;30(5):773-800 doi: http://dx.doi.org/10.1016/j.adolescence.2006.10.001[published Online First: Epub Date]|. 46. Breidablik H-J, Meland E, Lydersen S. Self-rated health during adolescence: stability and predictors of change (Young-HUNT study, Norway). The European Journal of Public Health 2009;19(1):73-78 doi: 10.1093/eurpub/ckn111[published Online First: Epub Date]|. 47. Welch HG, Sharp SM, Gottlieb DJ, et al. Geographic variation in diagnosis frequency and risk of death among Medicare beneficiaries. JAMA 2011;305(11):1113-8 doi: 10.1001/jama.2011.307[published Online First: Epub Date]|. 48. Fisher ES, Wennberg DE, Stukel TA, et al. The implications of regional variations in Medicare spending. Part 2: health outcomes and satisfaction with care. Ann Intern Med 2003;138(4):288-98 49. Wennberg JE. Tracking medicine. A researcher’s quest to understand health care. Oxford: Oxford University Press, 2010. w ie ev rr ee rp Fo ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 44 of 48 Page 20 of 22 n % SRH good (%) n % SRH good (%) 40-50 years 7058 40.3 77.6 6517 40.2 81.7 51-60 years 5709 32.6 64.4 5328 32.8 72.1 61-70 years 4747 27.1 56.6 4375 27.0 59.6 6821 0.6 58.4 4804 0.2 42.9 7026 39.1 72.8 8694 29.7 75.3 3489 40.3 68.5 2635 53.8 73.6 104 20.0 56.5 35 16.3 64.8 6973 40.1 70.3 4849 30.1 80.0 4651 26.7 68.0 6105 37.9 69.8 5763 33.1 64.3 5172 32.0 69.1 14888 88.7 11488 73.2 71.0 1471 8.8 76.8 2839 18.1 78.7 430 2.6 76.3 1375 8.8 78.3 < 10 years 8133 48.5 60.5 5711 36.5 63.1 10 – 12 years 5682 33.9 72.8 6615 42.2 76.0 > 12 years 2962 17.7 80.0 3339 21.3 84.7 Yes 11539 67.2 77.1 12309 77.1 79.9 No 5627 32.8 49.0 3665 22.9 49.2 Age group BMI (kg/m2) <18,5 18,5-24,9 25,0-29,9 >30 (0.4% missing) Smoking status Previous daily smoker (0.7% missing) None to low intake High intake 66.7 w Moderate intake ie Alcohol use ev Daily smoker rr Never smoked daily ee rp Fo (3.7% missing) Educational level ly on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 (3.8% missing) Employed (1.8% missing) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Page 45 of 48 BMJ Open Page 21 of 22 Any long-term impairment No 10348 59.1 85.9 9912 63.0 88.7 Yes 6275 35.8 39.8 5829 37.0 46.0 14373 86.2 68.7 7804 94.3 72.1 Unknown hypothyroidism 107 0.6 78.5 16 0.2 68.8 Subclinical hypothyroidism 466 2.8 75.0 150 1.8 66.4 Known hypothyroidism 858 5.1 48.9 124 1.5 58.1 Other thyroid dysfunction 872 5.2 61.4 180 2.2 56.2 64.6 69.4 9196 56.9 74.6 (4.1% missing) Thyroid function No thyroid disease rp Fo (1.3% missing) Diabetes mellitus No diabetes ee 11279 rr 0.3 395 2.3 Normotensive 9135 52.6 ie 6858 Unknown mild/moderate hypertension 4473 25.8 5343 403 2.4 70.7 349 2.2 73.8 3327 19.2 54.0 3498 21.8 59.6 34332 97.3 70.3 Unknown diabetes Probable diabetes Known diabetes (0.4% missing) 46 52.2 88 0.5 67.8 5728 32.8 65.9 6392 39.6 71.5 43.1 482 3.0 49.5 72.4 42.7 77.5 67.9 33.3 74.7 ev Blood pressure status Known hypertension Overall study population, HUNT2 ly (0.9% missing) on Unknown severe hypertension w 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 30378 98.4 Table 1. Good self-rated health (SRH) by sex and characteristics of the study population. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml 74.9 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com BMJ Open Page 46 of 48 Page 22 of 22 Table 2. The association between self-rated health and thyroid function, diabetes mellitus and blood pressure. Odds ratio (OR) of good self-rated health and 95% confidence intervals (95% CI), crude, age adjusted, and adjusted for age, other long-term illness or injury that impairs function in everyday life, smoking habits, alcohol use, educational level, work status and body mass index. Cases with missing data were excluded from the analyses. Women OR (95% CI) Crude n Age adjusted Men Multiple adjusted n OR (95% CI) Crude Age adjusted Multiple adjusted Thyroid function rp Fo No thyroid dysfunction Unknown hypothyroidism Subclinical hypothyroidism 1247 6 92 394 718 Known hypothyroidism 729 Other thyroid dysfunction 704 1.00 1.00 1.00 5 0.85 (0.30- 0.92 (0.31- 1.28 (0.351.66 (1.05- 2.00 (1.25- 1.84 (1.024.65) 14 2.45) 3.19) 3.33) 2.64) 2.72) 9946 39 Known diabetes 318 1.00 1.00 0.85 (0.80- 0.94 (0.88- 1.01 (0.92- 575 0.86 (0.80- 0.94 (0.88- 0.99 (0.919 0.92) 1.08) 1.01) 0.91) 1.10) 1.01) w 4797 846 1.00 1.00 1.00 4 0.72 (0.46- 0.88 (0.55- 1.03 (0.590.48 (0.27- 0.61 (0.34- 0.66 (0.3282 1.13) 1.10) 1.81) 0.86) 1.37) 1.39) 1.00 ie Probable diabetes ev rr Unknown diabetes 1.00 1.13 (0.721.37 (1.10- 1.49 (1.20- 1.48 (1.13- 128 0.77 (0.540.88 (0.62- 1.76) 1.08) 1.85) 1.94) 1.69) 1.24) 107 0.69 (0.440.54 (0.370.44 (0.38- 0.48 (0.41- 0.49 (0.410.63 (0.43- 1.09) 163 0.77) 0.55) 0.59) 0.50) 0.91) 0.58 (0.410.50 (0.370.72 (0.63- 0.77 (0.67- 0.77 (0.650.52 (0.38- 0.84) 0.67) 0.89) 0.93) 0.83) 0.71) Diabetes mellitus No diabetes 1.00 1.00 ee 0.33 (0.27- 0.42 (0.34- 0.53 (0.41- 395 0.33 (0.28- 0.42 (0.35- 0.55 (0.430.70) 0.40) 0.41) 0.51) 0.69) 0.51) Blood pressure 8180 Unknown mild/moderate hypertension 3787 Unknown severe hypertension 2745 Known hypertension 325 637 1.00 8 0.81 (0.75- 1.01 (0.93- 1.10 (0.990.86 (0.79483 0.93) 1.09) 0.87) 1.22) 7 0.92 (0.74- 1.34 (1.08- 1.52 (1.140.85 (0.77308 1.08) 1.15) 1.68) 2.02) 1.00 1.00 1.00 1.00 1.00 ly No hypertension on 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1.01 (0.92- 1.01 (0.921.10) 1.12) 1.27 (0.99- 1.48 (1.091.62) 2.02) 0.45 (0.41- 0.59 (0.54- 0.69 (0.61- 311 0.43 (0.39- 0.54 (0.50- 0.64 (0.570.49) 0.60) 0.72) 8 0.47) 0.65) 0.77) For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Page 47 of 48 STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of cross-sectional studies Section/Topic Title and abstract Item # 1 Introduction Recommendation Reported on page # Fo (a) Indicate the study’s design with a commonly used term in the title or the abstract 2 (b) Provide in the abstract an informative and balanced summary of what was done and what was found 2 rp Background/rationale 2 Explain the scientific background and rationale for the investigation being reported Objectives 3 State specific objectives, including any prespecified hypotheses Study design 4 Present key elements of study design early in the paper Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 5 Participants 6 (a) Give the eligibility criteria, and the sources and methods of selection of participants 5 Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if Data sources/ 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe Bias 9 Describe any efforts to address potential sources of bias Study size 10 Explain how the study size was arrived at Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and ee Methods rr 4 2-3 ev applicable measurement iew comparability of assessment methods if there is more than one group on why Statistical methods 12 3-4 (a) Describe all statistical methods, including those used to control for confounding ly (b) Describe any methods used to examine subgroups and interactions (c) Explain how missing data were addressed 5-8 5-8 7-8 5 5-8 7-8 8 Table 2 (d) If applicable, describe analytical methods taking account of sampling strategy - (e) Describe any sensitivity analyses - Results For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 BMJ Open BMJ Open Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, 5 confirmed eligible, included in the study, completing follow-up, and analysed Descriptive data 14* (b) Give reasons for non-participation at each stage 5 (c) Consider use of a flow diagram - Fo (a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential confounders rp Table 1 (b) Indicate number of participants with missing data for each variable of interest Table 1 Outcome data 15* Report numbers of outcome events or summary measures Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and why they were included Table 1 ee Table 2 Page 9-11 (b) Report category boundaries when continuous variables were categorized rr 5-7 (c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses ev Discussion - 10-11 Key results 18 Summarise key results with reference to study objectives Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias 11-13 Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence 13-14 Generalisability 21 Discuss the generalisability (external validity) of the study results 22 Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on Other information Funding which the present article is based iew 11 on 11 ly 15 *Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies. Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org. For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Page 48 of 48 Downloaded from http://bmjopen.bmj.com/ on October 14, 2016 - Published by group.bmj.com Is there an association between disease ignorance and self-rated health? The HUNT Study, a cross-sectional survey Pål Jørgensen, Arnulf Langhammer, Steinar Krokstad and Siri Forsmo BMJ Open 2014 4: doi: 10.1136/bmjopen-2014-004962 Updated information and services can be found at: http://bmjopen.bmj.com/content/4/5/e004962 These include: References This article cites 48 articles, 16 of which you can access for free at: http://bmjopen.bmj.com/content/4/5/e004962#BIBL Open Access This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) license, which permits others to distribute, remix, adapt, build upon this work for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/3.0/ Email alerting service Receive free email alerts when new articles cite this article. Sign up in the box at the top right corner of the online article. 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