Socioeconomic status and cell aging in children

Transcription

Socioeconomic status and cell aging in children
Social Science & Medicine xxx (2012) 1e4
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Social Science & Medicine
journal homepage: www.elsevier.com/locate/socscimed
Short report
Socioeconomic status and cell aging in children
Belinda L. Needham a, *, Jose R. Fernandez b, Jue Lin c, Elissa S. Epel d, Elizabeth H. Blackburn c
a
Department of Sociology, University of Alabama at Birmingham, 1530 3rd Ave. S., HHB 460C, Birmingham, AL 35294, United States
Department of Nutrition Science, University of Alabama at Birmingham, USA
c
Department of Biochemistry and Biophysics, University of California, San Francisco, USA
d
Department of Psychiatry, University of California, San Francisco, USA
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Available online xxx
Theory suggests that chronic stress associated with disadvantaged social status may lead to acceleration in
the rate of decline in physiological functioning. The purpose of this study is to examine the association
between parental socioeconomic status (SES) and leukocyte telomere length (LTL), a marker of cell aging, in
children. We examined SES and LTL in 70 white and black US children aged 7e13 who participated in the
community-based AMERICO (Admixture Mapping for Ethnic and Racial Insulin Complex Outcomes) study.
LTL was assessed using the polymerase chain reaction (PCR) method. Parental education was positively
associated with child LTL, net of controls for sex, age, race/ethnicity, and family income. Compared to
children with at least one college-educated parent, children whose parents never attended college had
telomeres shorter by 1,178 base pairs, which is roughly equivalent to 6 years of additional aging. Socioeconomic disparities in cell aging are evident in early life, long before the onset of age-related diseases.
Ó 2012 Elsevier Ltd. All rights reserved.
Keywords:
Telomere length
Socioeconomic status
Children
USA
Introduction
A large body of research has demonstrated an association
between socioeconomic status (SES) and morbidity and mortality
(Adler & Rehkopf, 2008). Several theoretical models share the
assumption that chronic stress associated with low social status
leads to wear and tear on the body that accelerates the rate of
decline in physiological functioning (Adams & White, 2004;
Geronimus, Hicken, Keene, & Bound, 2006; McEwen, 1998; Pearlin,
1989). Leukocyte telomere length (LTL), a marker of cell aging, may
provide a link between the stress associated with low SES and the
risk of disease (Bauer, Jeckel, & Luz, 2009). The purpose of this study
is to determine whether socioeconomic disparities in cell aging are
evident early in life, before the onset of age-related diseases, such
as cardiovascular disease, diabetes, stroke, and cancer.
Telomeres are repeat sequences of DNA that, together with
associated protein factors, cap the ends of chromosomes and
promote chromosomal stability. Telomeric DNA shortening tends to
occur with advancing chronological age (Frenck, Blackburn, &
Shannon, 1998; Iwama et al., 1998; Lee, Nam, Terao, & Yoshikawa,
2002) and leads to cellular senescence in vitro (Blasco, 2005).
Several studies have demonstrated that shorter LTL is associated
with morbidity (Brouilette, Singh, Thompson, Goodall, & Samani,
* Corresponding author. Tel.: þ205 934 0565; fax: þ205 975 5614.
E-mail address: bneedham@uab.edu (B.L. Needham).
2003; Samani, Boultby, Butler, Thompson, & Goodall, 2001) and
mortality, independent of chronological age (Bakaysa et al., 2007;
Cawthon, Smith, O’Brien, Sivatchenko, & Kerber, 2003; Kimura
et al., 2008). Although previous research has demonstrated an
association between LTL and stressful life circumstances (Drury
et al., 2011; Entringer et al., 2011; Epel et al., 2004), studies
examining the association between SES and LTL in adults have
produced conflicting results. While Cherkas et al. (2006) found that
LTL was significantly shorter in women of lower SES, several other
studies have found little association of SES with cell aging, as
measured by LTL (Adams et al., 2007; Batty et al., 2009). This is the
first study to examine the association between SES and LTL in
a sample of children.
Parental SES and child health
Research on parental SES and child health indicates that
numerous health disparities are evident during childhood,
including disparities in premature birth, injuries, respiratory
illnesses, dental caries, hospitalization, and self-rated health (for
a review, see Bradley & Corwyn, 2002). Compared to high SES
children, those who live in low SES families may have worse health
because (1) they are exposed to more negative life events, (2) they
are more likely to experience psychological distress, (3) they are
more likely to develop health-damaging personality traits, such as
hostility and pessimism, and (4) they are less likely to engage in
healthy behaviors, such as exercise (Chen, 2004). In addition,
0277-9536/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved.
doi:10.1016/j.socscimed.2012.02.019
Please cite this article in press as: Needham, B. L., et al., Socioeconomic status and cell aging in children, Social Science & Medicine (2012),
doi:10.1016/j.socscimed.2012.02.019
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B.L. Needham et al. / Social Science & Medicine xxx (2012) 1e4
childhood may represent a “critical” or “sensitive” period in
development, whereby exposure to conditions associated with low
SES may have long-term consequences for health and well-being,
even among individuals who experience improvement in socioeconomic conditions over time (Cohen, Janicki-Deverts, Chen, &
Matthews, 2010; Hertzman & Wiens, 1996; Shonkoff, Boyce, &
McEwen, 2009).
Despite evidence of socioeconomic disparities in child health,
overall rates of morbidity and mortality are low during this stage of
the life course. Furthermore, the types of health problems that are
observable during childhood, such as accidental injuries, are not
leading causes of adult morbidity and mortality. In order to
demonstrate the link between childhood social conditions and
adult health, it would be useful to identify an indicator of childhood
health status that is related to the onset of diseases, such as cancer
and cardiovascular disease, later in life. Leukocyte telomere length,
a marker of cell aging that is associated with adult morbidity
(Brouilette et al., 2003; Samani et al., 2001) and mortality, independent of chronological age (Bakaysa et al., 2007; Cawthon et al.,
2003; Kimura et al., 2008), may be such a measure.
Hypotheses
Given the evidence of socioeconomic health disparities during
childhood (Bradley & Corwyn, 2002), we expected to find a positive
association between parental SES and child telomere length. As
proposed by Chen (2004), we also expected to find that the association between SES and LTL is partially mediated by health
behavior. Based on previous research examining the association
between telomere length and health behavior in adults, we
examined fruit and vegetable consumption (Paul, 2011), physical
activity (Cherkas et al., 2008), and body mass index (Valdes et al.,
2005) as potential mediators.
Methods
Sample and procedures
The study sample includes 35 white and 35 black children
selected at random from the full sample of 120 white, 120 black,
and 120 Latino children who participated in the community-based
AMERICO (Admixture Mapping for Ethnic and Racial Insulin
Complex Outcomes) study. Data were collected in Birmingham,
Alabama, between 2005 and 2008. Subjects were recruited through
newspaper postings and fliers and recruitment activities at
churches, schools, and community centers. The blood draw took
place at 7:00 am, after a 12 h fast. Children were healthy and
without observable illnesses at the time of the blood draw,
according to parental report. Written, informed consent was
obtained from each child’s parent or legal guardian. Human
subjects approval for this study was granted by the Institutional
Review Board at University of Alabama at Birmingham.
SES measurement
The SES measures included parental education (for the most
highly educated parent) and total household income. The data set
included a measure of educational attainment that ranged from 1 to
7 (1 ¼ less than 8th grade, 2 ¼ 9the10th grade, 3 ¼ 10the11th
grade, 4 ¼ high school, 5 ¼ partial college or special training,
6 ¼ college, 7 ¼ graduate or professional school). Because responses
were not normally distributed, we constructed a three-category
measure of educational attainment: high school graduate (13%),
some college (17%), and college graduate (70%). We then constructed dummy variables for high school graduate and some
college, with college graduate as the reference category in all
analyses. The original income variable ranged from 1 to 9 (in
$10,000 increments from 1 ¼ 0e9999 to 9 ¼ 80,000þ). Given that
responses were not normally distributed, we constructed a threecategory measure of income: <$40,000 per year (20%),
$40,000e$69,000 per year (64%), and $70,000þ per year (16%). We
then constructed dummy variables for income <$40,000 per year
and $40,000e$69,000 per year with income of $70,000 or more per
year as the reference category in all analyses.
Measurement of mediators
Proposed mediators include fruit and vegetable consumption,
physical activity, and body mass index. Respondents were asked to
report the number of fruits and vegetables consumed per day.
Responses ranged from 0 to 8 for fruits and 0e11 for vegetables. We
used the Physical Activity Questionnaire for Older Children (PAQ-C)
to assess physical activity (Crocker, Bailey, Faulkner, Kowalski, &
McGrath, 1997). The PAQ-C is a self-administered questionnaire
that assesses moderate to vigorous physical activity during the past
seven days. Previous studies have established validity and reliability of the PAQ-C (Kowalski, Crocker, & Faulkner, 1997). The
activity composite score ranges from 1 (low physical activity) to 5
(high physical activity). Body mass index (weight (kg)/height (m2))
was calculated using measures of weight and height obtained by
a trained interviewer.
Telomere length assay
Using standardized procedures, DNA was extracted from whole
blood and stored for 2e5 years at 80 . The LTL assay was performed in the laboratory of Dr. Elizabeth Blackburn at the University of California, San Francisco, by Dr. Jue Lin, using the quantitative
polymerase chain reaction (PCR) method to measure telomere
length relative to standard reference DNA (T/S ratio), as described
in detail elsewhere (Cawthon, 2002; Lin et al., 2009). Each sample
was assayed at least twice. T/S ratios that fell into the 7% variability
range were accepted, and the average of the two was taken as the
final value. A third assay was run for samples with greater than 7%
variability, and the average of the two closest T/S values was used.
The conversion from T/S ratio to base pairs (bp) was calculated
based on comparison of telomeric restriction fragment (TRF) length
from Southern blot analysis and T/S ratios using DNA samples from
the human diploid fibroblast cell line IMR90 at different population
doublings. The formula to convert T/S ratio to bp was 3274 þ 2413 *
(T/S). DNA samples were coded and the lab was blinded to all other
measurements in the study.
Data analysis
Because LTL is normally distributed in this sample, we used
ordinary least squares (OLS) regression to examine the association
between parental SES and child telomere length. The model
included controls for sex (1 ¼ female, 0 ¼ male), age (in years), and
race/ethnicity (1 ¼ black, 0 ¼ white). See Table 1 for descriptive
statistics for all study variables.
Results
As shown in Table 2, age was inversely associated with LTL, but
we found no sex or race/ethnic differences in telomere length.
Parental education was associated with child telomere length,
while family income was only significant at the p < .10 level.
Compared to those with the highest family income ($70,000þ per
year), children living in low-income households (<$40,000 per
Please cite this article in press as: Needham, B. L., et al., Socioeconomic status and cell aging in children, Social Science & Medicine (2012),
doi:10.1016/j.socscimed.2012.02.019
B.L. Needham et al. / Social Science & Medicine xxx (2012) 1e4
Table 1
Descriptive statistics for all study variables (n ¼ 70).
Telomere length (average T/S ratio)
Age (in years)
Female
Male
Black
White
Family income
Less than $40,000 per year
$40,000e$69,000 per year
$70,000þ per year
Parent education
High school graduate
Some college
College graduate
Daily fruit servings
Daily vegetable servings
PAQ-C physical activity score
Body mass index
Table 3
OLS regression of telomere length on parental SES and fruit consumption, vegetable
consumption, physical activity, and body mass index controlling for age, sex, and
race/ethnicity (n ¼ 70).
Mean (SD)
Proportion
Range
2.00 (.52)
9.90 (1.59)
e
e
e
e
e
e
.52
.48
.50
.50
.50e3.46
7.00e12.60
e
e
e
e
e
e
e
.20
.64
.16
e
e
e
e
e
e
1.80 (1.64)
1.95 (1.70)
2.82 (.72)
18.00 (4.92)
.13
.17
.70
e
e
e
e
e
e
e
0e8
0e11
1.47e4.30
13.94e28.49
year) had a lower average T/S ratio (b ¼ .38; 95% Confidence
Interval ¼ .82, .06; p ¼ .09). Those living in moderate-income
households ($40,000e$69,999 per year) also had a lower average
T/S ratio (b ¼ .33; 95% Confidence Interval ¼ .68, .03; p ¼ .07)
than children living in high-income households. Compared to
children with at least one college-educated parent, those whose
most highly educated parent never attended college had a lower
average T/S ratio (b ¼ .49; 95% Confidence Interval ¼ .88, .09;
p ¼ .02).
As shown in Table 3, we found that none of the proposed
mediators was associated with LTL. Therefore, the association
between parental education and income and child telomere length
was not mediated, or explained, by fruit or vegetable consumption,
physical activity, or body mass index (Baron & Kenny, 1986).
Discussion
This preliminary study suggests that socioeconomic disparities
in telomere length, a marker of cell aging, are evident in early life,
long before the onset of age-related diseases. This disparity does
not appear to be attributable to differences in fruit or vegetable
consumption, physical activity, or body mass index. Although
previous research on SES and LTL in adults has produced mixed
results (see Adams et al., 2007; Batty et al., 2009; Cherkas et al.,
2006), the current study suggests that low social status may
contribute to accelerated cell aging during childhood.
Controlling for age, sex, race/ethnicity, and family income, the
average T/S ratio for children whose parent completed no more
Table 2
OLS regression of telomere length on parental income and education, controlling for
age, sex, and race/ethnicity (n ¼ 70).
Parameter
estimate
Age
.10
Female
.06
Black
.14
Family income ($70,000þ per year)
$40,000e$69,000 per year
.33
Less than $40,000 per year
.38
Parent education (College graduate)
Some college
.06
High school graduate
.49
Intercept
3.29
R2 ¼ .24.
95% Confidence
interval
p value
.18, .03
.19, .32
.15, .44
.01
.61
.34
.68, .03
.82, .06
.07
.09
.44, .31
.88, .09
2.41, 4.18
3
.73
.02
<.001
Parameter
estimate
Age
.10
Female
.06
Black
.10
Family income ($70,000þ per year)
$40,000e$69,000 per year
.32
Less than $40,000 per year
.33
Parent education (College graduate)
Some college
.06
High school graduate
.54
Daily fruit servings
.02
Daily vegetable servings
.00
PAQ-C physical activity score
.02
Body mass index
.02
Intercept
2.86
95% Confidence
interval
p value
.18, .02
.22, .33
.21, .41
.01
.69
.53
.69, .05
.79, .13
.09
.16
.44, .33
.96, .12
.08, .12
.09,.09
.16, .21
.03, .06
1.49, 4.23
.76
.01
.69
.97
.79
.42
<.001
R2 ¼ .27.
than a high school education was 1.77 compared to 2.26 for children whose parent completed college. This corresponds to
a difference of 1178 bp. Given the observed cross-sectional rate of
telomere shortening in this study of 196 bp per year, which is
consistent with previous research on children using Southern blot
analysis (Frenck et al., 1998), the difference in bp between low and
high SES respondents of the same chronological age is roughly
equivalent to 6 years of additional aging.
The main strength of this study is the availability of data on SES
and LTL for children. To our knowledge, no previous studies have
examined the association between childhood socioeconomic
conditions and child telomere length, although several retrospective studies have considered whether childhood social
conditions are associated with adult telomere length (Adams et al.,
2007; Kananen et al., 2010; Surtees et al., 2011). Despite the fact
that every child in the sample had at least one parent who
completed high school (indicating that the sample is skewed
toward higher SES), we were still able to detect a significant
association between parental education and child telomere length.
This suggests that childhood socioeconomic conditions may have
lasting consequences for aging and health throughout the life
course. To determine whether this is the case, we will need to
conduct prospective studies that include measures of childhood
and adult SES and LTL.
Despite its strengths, this study has several limitations that
should be addressed in future research. First, since data are from
a convenience sample, the results are not generalizable. Moreover,
the sample size is very small, which limits statistical power. In
addition to examining a larger, more representative sample of
children, future studies should also examine longitudinal associations between social status and LTL. Longitudinal studies will
enable researchers to determine whether social status is related to
the rate of change in cell aging. Finally, because this study used
secondary data, we were limited in the choice of mediators. Future
studies are necessary to elucidate the mechanisms underlying
group differences in LTL and to identify resources that attenuate the
association between low social status and cell aging.
Studies examining mediators and moderators of the association
between parental SES and child LTL may one day be used to develop
interventions to prevent accelerated aging among low SES children.
Given the association between shorter LTL and earlier morbidity
and mortality in adults, reducing disparities in cell aging among
children could lead to a significant reduction in adult health
disparities.
Please cite this article in press as: Needham, B. L., et al., Socioeconomic status and cell aging in children, Social Science & Medicine (2012),
doi:10.1016/j.socscimed.2012.02.019
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B.L. Needham et al. / Social Science & Medicine xxx (2012) 1e4
References
Adams, J., Martin-Ruiz, C., Pearce, M., White, M., Parker, L., & von Zglinicki, T. (2007).
No association between socio-economic status and white blood cell telomere
length. Aging Cell, 6(1), 125e128.
Adams, J. M., & White, M. (2004). Biological ageing: a fundamental biological link
between socio-economic status and health? European Journal of Public Health,
14(3), 331e334.
Adler, N., & Rehkopf, D. (2008). US disparities in health: descriptions, causes, and
mechanisms. Annual Review of Public Health, 29, 235e252.
Bakaysa, S., Mucci, L., Slagbloom, P., Boomsma, D., McClearn, G., Johansson, B., et al.
(2007). Telomere length predicts survival independent of genetic influences.
Aging Cell, 6, 769e774.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality & Social Psychology, 51(6), 1173e1182.
Batty, G. D., Wang, Y., Brouilette, S. W., Shiels, P., Packard, C., Moore, J., et al. (2009).
Socioeconomic status and telomere length: the west of Scotland coronary
prevention study. Journal of Epidemiology and Community Health, 63(10), 839e841.
Bauer, M. E., Jeckel, C. M., & Luz, C. (2009). The role of stress factors during aging of
the immune system. Annals of the New York Academy of Science, 1153, 139e152.
Blasco, M. (2005). Telomeres and human disease: ageing, cancer and beyond. Nature
Reviews Genetics, 6(8), 611e622.
Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development.
Annual Review of Psychology, 53, 371e399.
Brouilette, S., Singh, R., Thompson, J., Goodall, A., & Samani, N. (2003). White cell
telomere length and risk of premature myocardial infarction. Arteriosclerosis,
Thrombosis, and Vascular Biology, 23(5), 842e846.
Cawthon, R. (2002). Telomere measurement by quantitative PCR. Nucleic Acids Res,
30, e47.
Cawthon, R., Smith, K., O’Brien, E., Sivatchenko, A., & Kerber, R. (2003). Association
between telomere length in blood and mortality in people aged 60 years or
older. Lancet, 361, 393e395.
Chen, E. (2004). Why socioeconomic status affects the health of children:
a psychosocial perspective. Current Directions in Psychological Science, 13,
112e115.
Cherkas, L., Aviv, A., Valdes, A., Hunkin, J., Gardner, J., Surdulescu, L., et al. (2006).
The effects of social status on biological aging as measured by white-blood-cell
telomere length. Aging Cell, 5, 361e365.
Cherkas, L., Hunkin, J., Kato, B., et al. (2008). The association between physical
activity in leisure time and leukocyte telomere length. Archives of Internal
Medicine, 68(2), 154e158.
Cohen, S., Janicki-Deverts, D., Chen, E., & Matthews, K. A. (2010). Childhood socioeconomic status and adult health. Annals of the New York Academy of Sciences,
1186(1), 37e55.
Crocker, P. R. E., Bailey, D. A., Faulkner, R. A., Kowalski, K. C., & McGrath, R. (1997).
Measuring general levels of physical activity: preliminary evidence for the
physical activity questionnaire for older children. Medicine and Science in Sports
and Exercise, 29, 1344e1349.
Drury, S., Theall, K., Gleason, M., Smyke, A., De Vivo, I., Wong, J., et al. (2011).
Telomere length and early severe social deprivation: linking early adversity and
cellular aging. Molecular Psychiatry, Epub ahead of print May 17, 2011.
Entringer, S., Epel, E. S., Kumsta, R., Lin, J., Hellhammer, D. H., Blackburn, E. H., et al.
(2011). Stress exposure in intrauterine life is associated with shorter telomere
length in young adulthood. Proceedings of the National Academy of Sciences of
the United States of America, Epub ahead of print August 3, 2011.
Epel, E. S., Blackburn, E. H., Lin, J., Dhabhar, F. S., Adler, N. E., Morrow, J. D., et al.
(2004). Accelerated telomere shortening in response to life stress. Proceedings of
the National Academy of Sciences of the United States of America, 101(49),
17312e17315.
Frenck, R., Blackburn, E., & Shannon, K. (1998). The rate of telomere sequence loss in
human leukocytes varies with age. Proceedings of the National Academy of
Sciences of the United States of America, 95, 5607e5610.
Geronimus, A., Hicken, M., Keene, D., & Bound, J. (2006). “Weathering” and age
patterns of allostatic load scores among blacks and whites in the United States.
American Journal of Public Health, 96(5), 826e833.
Hertzman, C., & Wiens, M. (1996). Child development and long-term outcomes:
a population health perspective and summary of successful interventions. Social
Science & Medicine, 43(7), 1083e1095.
Iwama, H., Ohyashik, K., Ohyashiki, J., et al. (1998). Telomeric length and telomerase
activity vary with age in peripheral blood cells obtained from normal individuals. Human Genetics, 102(4), 397e402.
Kananen, L., Surakka, I., Pirkola, S., Suvisaari, J., Lonnqvist, J., Peltonen, L., et al.
(2010). Childhood adversities are associated with shorter telomere length at
adult age both in individuals with an anxiety disorder and controls. PLoS One,
5(5), e10826.
Kimura, M., Hjelmborg, J., Gardner, J., Bathum, L., Brimacombe, M., Lu, X., et al.
(2008). Short leukocyte telomeres forecast mortality: a study in elderly Danish
twins. American Journal of Epidemiology, 167(7), 799e806.
Kowalski, K. C., Crocker, P. R. E., & Faulkner, R. A. (1997). Validation of the physical
activity questionnaire for older children. Pediatric Exercise Science, 9, 174e186.
Lee, W., Nam, K., Terao, K., & Yoshikawa, Y. (2002). Age-related telomere length
dynamics in peripheral blood mononuclear cells of healthy cynomolgus
monkeys measured by flow FISH. Immunology, 105(4), 458e465.
Lin, J., Epel, E., Cheon, J., Kroenke, C., Sinclair, E., Bigos, M., et al. (2009). Analyses and
comparisons of telomerase activity and telomere length in human T and B cells:
insights for epidemiology of telomere maintenance. Journal of Immunological
Methods, 352(1e2), 71e80.
McEwen, B. (1998). Protective and damaging effects of stress mediators. New
England Journal of Medicine, 338, 171e179.
Paul, L. (2011). Diet, nutrition and telomere length. The Journal of Nutritional
Biochemistry, 22(10), 895e901.
Pearlin, L. I. (1989). The sociological study of stress. Journal of Health & Social
Behavior, 30(3), 241e256.
Samani, N., Boultby, R., Butler, R., Thompson, J., & Goodall, A. (2001). Telomere
shortening in atherosclerosis. Lancet, 358, 472e473.
Shonkoff, J. P., Boyce, W. T., & McEwen, B. S. (2009). Neuroscience, molecular
biology, and the childhood roots of health disparities: building a new framework for health promotion and disease prevention. Journal of the American
Medical Association, 301(21), 2252e2259.
Surtees, P. G., Wainwright, N. W., Pooley, K. A., Luben, R. N., Khaw, K. T., Easton, D. F.,
et al. (2011). Life stress, emotional health, and mean telomere length in the
European Prospective Investigation into Cancer (EPIC)-Norfolk population
study. Journals of Gerontology Series A: Biological Sciences and Medical Sciences,
66(11), 1152e1162.
Valdes, A. M., Andrew, T., Gardner, J. P., Kimura, M., Oelsner, E., Cherkas, L. F., et al.
(2005). Obesity, cigarette smoking, and telomere length in women. Lancet,
366(9486), 662e664.
Please cite this article in press as: Needham, B. L., et al., Socioeconomic status and cell aging in children, Social Science & Medicine (2012),
doi:10.1016/j.socscimed.2012.02.019