Adherence Rates to the Mediterranean Diet Children and Adolescents

The Journal of Nutrition
Nutritional Epidemiology
Adherence Rates to the Mediterranean Diet
Are Low in a Representative Sample of Greek
Children and Adolescents1,2
Meropi D. Kontogianni,3 Nikoletta Vidra,3 Anastasia-Eleni Farmaki,3 Stella Koinaki,3
Katerina Belogianni,3 Stavroula Sofrona,4 Flora Magkanari,4 and Mary Yannakoulia3*
3
Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece and 4‘‘Aristeides Daskalopoulos’’
Foundation, 15125 Athens, Greece
Abstract
Data from studies in pediatric samples exploring adherence to the Mediterranean diet are scarce. The aim of the present
work was to explore adherence to a Mediterranean diet pattern in a representative sample of Greek children and
age. Information on participants’ sociodemographic, anthropometric, and lifestyle characteristics were collected through
telephone interviews. Adherence to the Mediterranean diet guidelines for adults and to the general dietary guidelines for
children was evaluated using KIDMED scores: the higher the score, the more favorable the dietary pattern. The Goldberg
cut-off limits for the ratio of energy intake:basal metabolic rate were used to evaluate dietary underreporting and children
were accordingly classified as low energy reporters (LER) or non-LER. Only 11.3% of children and 8.3% of adolescents had
an optimal KIDMED score ($8). In adolescents, partial correlation analysis revealed a negative weak association between
KIDMED and BMI (r ¼ 20.092; P ¼ 0.031), which remained significant in the non-LER subgroup (r ¼ 20.137, P ¼ 0.011).
Multiple regression analysis revealed that higher KIDMED scores were associated, in non-LER children, with less time spent
on sedentary activities (P ¼ 0.002) and higher paternal education (P ¼ 0.050), whereas in adolescents, with younger age
(P ¼ 0.001), less time spent on sedentary activities (P ¼ 0.015), higher maternal education (P ¼ 0.014), and higher eating
frequency (P ¼ 0.041). In conclusion, low adherence rates to the Mediterranean diet were observed in Greek children and
adolescents; this evidence needs to be further explored regarding its impact on health and disease. J. Nutr. 138: 1951–1956, 2008.
Introduction
The term Mediterranean diet has been widely used to describe
the traditional dietary habits of people in Crete, South Italy, and
other Mediterranean countries during the decade of the 1960s
(1). The diet is characterized by abundant plant foods (fruits,
mainly as typical daily desserts, vegetables, bread, other forms of
cereals, beans, nuts, and seeds). It also includes olive oil as the
principal source of fat, moderate amounts of dairy products
(principally cheese and yogurt), low to moderate amounts of fish
and poultry, red meat in low amounts, and wine consumed in
low to moderate quantities, normally with meals (2,3). The
Mediterranean dietary pattern is characterized as rich in monounsaturated fatty acids, a balanced ratio of (n-6):(n-3) essential
fatty acids, and high amounts of fiber and antioxidants, such as
vitamins E and C, resveratrol, polyphenols, selenium, and
glutathione (1). Greater adherence to the traditional Mediterranean diet has been associated with a significant reduction in total
mortality and improvement in longevity (4) as well as lower
1
Supported by the ‘‘Aristeides Daskalopoulos’’ Foundation.
Author disclosures: M. D. Kontogianni, N. Vidra, A.-E. Farmaki, S. Koinaki,
K. Belogianni, S. Sofrona, F. Magkanari, and M. Yannakoulia, no conflicts of interest.
* To whom correspondence should be addressed. E-mail: myiannak@hua.gr.
2
incidence of atherosclerosis, coronary heart disease, metabolic
syndrome, and biochemical indicators of insulin resistance, inflammation, or cardiovascular disease risk (5–8).
During the past few decades, there has been a gradual
abandonment of this dietary pattern by the inhabitants of the
Mediterranean basin (9), especially by the younger generations
(10,11). Traditional food choices are also changing due to the
increasing affluence and the progressive globalization of food
supply (12). In Spain, for example, energy-dense foods high in
saturated fat and low in micronutrients have replaced traditional
foods and they now constitute a large part of young people’s
diet, thus contributing to obesity and increasing cholesterol
concentrations (13).
Studies in children and adolescents exploring potential associations between either adherence to the Mediterranean diet or
intake of some of its beneficial compounds and biochemical
indices or clinical problems, such as obesity, are scarce (14–17).
Recently, a group of investigators from Spain developed an index
(KIDMED index) to assess compliance with the Mediterranean
diet by young people (2–24 y old) (11) and found that greater
values of this index, suggesting greater adherence to the Mediterranean diet, were associated with greater nutritional adequacy,
especially in terms of vitamins and minerals (18).
0022-3166/08 $8.00 ª 2008 American Society for Nutrition.
Manuscript received 28 January 2008. Initial review completed 4 March 2008. Revision accepted 26 July 2008.
1951
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adolescents. The study sample (n ¼ 1305, 3–18 y) was representative of the Greek pediatric population in terms of sex and
The aim of the present work was to explore adherence to the
Mediterranean diet based on the KIDMED index in a representative sample of Greek children and adolescents and to evaluate
potential associations with sociodemographic, anthropometric,
and lifestyle characteristics.
Methods
Assessment of sociodemographic characteristics. Parents or adolescents provided information regarding the subject’s age and nationality,
weight, height, family status, as well as parental occupation and education level. Parental educational level was divided into 3 groups (1): low
[illiteracy, primary, junior middle school (#9 y)] (2); medium [senior
middle school (10–12 y)]; and (3) high [university or higher education
($13 y)]. From each participant’s reported weight and height, BMI was
calculated (kg/m2) and participants were then categorized as underweight, normal weight, overweight, or obese, according to the International Obesity Task Force BMI cut-off points (26,27).
Assessment of dietary intake and eating behavior. Dietary intake
was assessed through the KIDMED questionnaire and a 24-h recall of the
previous day’s dietary intake. The KIDMED index was developed in an
attempt to combine the Mediterranean diet guidelines for adults as well
as the general dietary guidelines for children (such as breakfast skipping)
in a single index. It was based on the principles sustaining the Mediterranean dietary pattern as well as on those that undermine it. The index
comprises 16 yes or no questions (11). Questions denoting a negative
connotation with respect to the Mediterranean diet were assigned a value
of 21 and those with a positive aspect 11. The total score ranged from
24 to 12 and was classified into 3 levels: $8, optimal Mediterranean
diet; 4–7, improvement needed to adjust intake to the Mediterranean
diet; and #3, very low diet quality.
The 24-h recall procedure has been used in several pediatric nutrition
surveys (28,29). In children, as well as in adults, there is no perfect
method of assessing dietary intake. On a group basis and given that the
group size is adequate, the 24-h reported intake can provide a reasonably
accurate estimate of mean energy and macronutrient intake, because
1952
Kontogianni et al.
Physical activity assessment. Leisure-time physical activity was
estimated through a recall of the time children spent on specific activities
the previous day, namely 1) walking (e.g. to school/tuition centers, etc.);
2) games or sports with friends/schoolmates (e.g. basketball, volleyball,
soccer, chasing, hide-and-seek, skipping rope, etc.); and 3) organized
physical exercise (e.g. basketball, volleyball, soccer, etc.). Moreover, the
time spent on sedentary activities (e.g. TV viewing, computer or video
games) during the previous day was also recorded. Both physical and
sedentary activities were expressed in min/d.
Statistical analysis. Continuous variables are presented as means 6 SD
and categorical variables as absolute frequencies. The chi-square test evaluated associations between the categorical variables (such as KIDMED
groups and parental education levels) and the Student’s t test and the
ANOVA were applied to evaluate differences in mean values of normally
distributed data between boys and girls or the KIDMED groups. Furthermore, to compare high and medium to low KIDMED groups, post hoc
analyses were performed. The Bonferroni rule was used to account for
the inflation of type-I error. Associations between the KIDMED score
and other variables were evaluated by Spearman correlation coefficients.
Partial correlations between the KIDMED and the BMI, after controlling
for age, sex, and time spent in sedentary and physical activities, were also
performed. Multiple linear regression analyses were applied to evaluate
5
Abbreviations used: BMR, basal metabolic rate; EF, eating frequency; EI,
energy intake; LER, low energy reporters.
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Study population. Data were collected through telephone interviews
from May to July 2007. Multistage, stratified, and proportional random
sampling was applied: multistage and stratified per geographical region
and age group (3–12 y old, 13–18 y old), proportional to children’s and
adolescents’ population aged 3–18 y per region (for urban and rural
areas according to 2001 census) (19), random with regard to the household selection in each stratum, as well as the selection of the child/
adolescent in question within each household (a random-digit dialing
procedure was used). At the beginning of the telephone call, potential
participants were informed about the objectives and methods of the
study, understood that their participation was voluntary, were assured
about the confidentiality of the data, and provided their oral consent. Of
the total potential participants contacted, 10,192 were ineligible (i.e. no
children in the household, mismatching with age, sex, and geographical
distribution required, etc.); 3545 participants refused to participate at
any stage (including those who refused before being informed that were
eligible for this study). The total sample consisted of 1305 participants,
3–18 y old (52% girls), 751 children (mean age: 7.6 6 2.9 y, 51% boys)
and 554 adolescents (mean age: 15.5 6 1.6 y, 43.7% male). The sample
was representative of the Greek pediatric population in terms of sex and
age and covered all the geographical areas of Greece except the Ionian
and Aegean islands. The study was approved by the Ethics Committee of
Harokopio University.
Interviews were conducted with either the parent (or any other
person responsible for a child’s diet) for children 3–12 y old or the
adolescent for participants older than 12 y. Parents or caregivers provide
accurate and reliable information concerning younger children’s dietary,
lifestyle, and anthropometric information; however, as children grow
older, they appear to be able to recall their own intake (20–24), although
a parental report still remains a better indicator of obesity than an
adolescent report of weight status (25).
means are robust and unaffected by the within-person variation; however, the recall technique is not appropriate for estimating actual intake
on an individual basis (30,31). In our study, the interviewers were
intensively trained to record, in the most detailed way, the type of food
consumed (e.g. in terms of fat content, brand name, constituents of
mixed dishes, etc.) as well as the quantity or volume using common
household or other measures (rulers, pack of playing cards, computer
mouse, etc.). For each food item or food group, specific instructions were
given to the interviewers regarding the information required for the food
description and the possible ways of recording quantity or volume.
Special attention was paid to the day of the recall so that weekdays and
weekends were proportionally represented in the total sample of recalls.
Energy and macronutrient intake, meal patterns, as well as diet energy
density were derived from the 24-h dietary recall. Data from recalls were
analyzed for their macro- and micronutrient content by the Nutritionist
Pro, version 2.2 software (Axxya Systems-Nutritionist Pro) through a
hand coding procedure. The Nutritionist Pro food database was
expanded by adding analyses of traditional Greek foods and recipes
(3,32,33) and nutrient information of local processed food items (mainly
snack foods, sweets, and fast foods) provided by the industry. Energy
density was computed as total energy intake (EI)5 to total food weight
consumed (kJ/g). Particular care was given to include all liquids consumed and reported by the participants, including water, beverages, and
soups. However, the possibility that some beverages (especially tap
water) were not reported cannot be eliminated.
Dietary recalls were used to determine the number of eating episodes
per day, i.e. eating frequency (EF). An eating episode was defined as any
eating occasion when food or drink was consumed. The definition of an
eating episode also included drinks (i.e. soft drinks or coffee) consumed
in the absence of food. Two eating episodes occurring within a 15-min
period or less counted as a single episode. For the assessment of low
energy reporting, the ratio of the reported EI:basal metabolic rate (BMR)
was determined for each subject, as in previous studies (34). The BMR
was estimated using the Schofield predictive equations (35), adopted
by the 2004 FAO/WHO/UNU report (36). Participants with EI:BMR
# 0.89 were classified as low energy reporters (LER) based on the cut-off
limits developed by Goldberg et al. (37) for 1-d recall. Normal energy
reporters or non-LER were participants with EI:BMR $ 0.90.
Furthermore, other aspects of eating behavior were evaluated,
including dietary habits related to food consumption (frequency of at
least 1 family meal per day, eating without watching television, etc.).
Involvement in slimming diets either at the time of the study or in the
past was also recorded.
the explanatory ability of several sociodemographic and lifestyle characteristics in relation to KIDMED score (dependent variable), namely age
(y), sex (female vs. male), leisure-time physical activities (min/d), sedentary
activities (min/d), mother’s and father’s education level (high vs. low/
medium), EF (no. of eating episodes per day), and eating at least 1 daily
family meal (yes vs. no). The results from the regression models are
presented as standardized b coefficients. The level of significance was
defined at P , 0.05. Data were analyzed by using the Statistical Package
for the Social Sciences (SPSS 13.0) software.
Results
TABLE 1
Sociodemographic, dietary, and lifestyle characteristics according to age and KIDMED groups1
Children, 3–12 y
Adolescents, 13–18 y
KIDMED
,3
n (%)
Age, y
Male sex, %
BMI, kg/m2
EI, kJ/d
Carbohydrate intake, % energy
Protein intake, % energy
Fat intake, % energy
Energy density, kJ/g
LER,3%
Sedentary activities, min/d
Leisure-time physical activities, min/d
Father's education level
Low-medium, %
High, %
Mother's education level
Low-medium, %
High, %
1
2
3
4–7
KIDMED
$8
P2
,3
0.05
0.10
0.33
0.95
0.16
0.01
0.63
,0.001
0.27
0.01
0.37
150 (27.0)
15.9 6 1.5
47.7
21.5 6 4.0
7289 6 3479
42.8 6 10.4
15.3 6 4.9
42.7 6 9.1
6.3 6 2.1
36.8
104.0 6 99.3
72.1 6 104.2
358 (68.6)
15.4 6 1.6*
42.5
21.1 6 3.1
7511 6 2897
42.9 6 9.2
15.8 6 3.9
42.2 6 8.2
5.4 6 1.7***
30.7
83.3 6 79.4*
82.8 6 88.9
46 (8.3)
15.2 6 1.8*
41.3
20.5 6 2.7
7637 6 3366
43.3 6 10.3
17.1 6 5.6*
41.0 6 8.4
5.0 6 1.3***
26.7
76.4 6 65.0
101.4 6 92.7
4–7
P2
$8
112 (14.9)
8.2 6 2.7
58.9
18.0 6 3.5
7331 6 2278
43.8 6 8.1
14.9 6 3.4
42.1 6 8.1
6.3 6 1.7
9.1
82.3 6 62.2
111.3 6 107.0
554 (73.8)
7.5 6 2.9*
48.7
18.0 6 4.0
7314 6 2269
42.4 6 9.0
16.3 6 4.0**
42.1 6 7.8
5.4 6 1.3***
6.4
63.9 6 60.3**
108.0 6 99.5
85 (11.3)
7.5 6 3.0
55.3
17.4 6 2.8
7226 6 2918
43.9 6 9.1
16.1 6 4.0
41.3 6 7.3
5.0 6 0.8***
8.5
55.9 6 51.0**
124.5 6 96.5
69.5
30.5
57.0**
43.0**
44.6*
55.4*
0.01
63.5
36.5
66.5
33.5
43.3
56.7
0.05
69.1
30.9
59.1**
40.9**
47.9***
52.1 ***
0.02
68.9
31.1
68.0
32.0
45.2
54.8
0.03
0.01
0.53
0.14
0.71
0.96
0.05
0.49
,0.001
0.29
0.02
0.16
Values are means 6 SD or percentages. Asterisks indicate different from the low KIDMED group (Bonferroni corrected): *P , 0.05, **P , 0.01, ***P , 0.001.
P between all groups as derived from ANOVA or Chi-square test, respectively.
Individuals with the ratio of EI:BMR #0.89 (37).
Mediterranean diet in children and adolescents
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The BMI of the children was 17.9 6 3.8 kg/m2 with 18.2% of
the subjects being overweight and 12.9% obese, whereas among
adolescents, the BMI was 21.2 6 3.4 kg/m2, with 13.5% of them
overweight and 2.8% obese. Seven percent of the children and
32.1% of the adolescents were classified as LER.
The KIDMED score was 5.4 6 1.8 in children and 4.8 6 2.1
in adolescents; only 11.3% of children and 8.3% of adolescents
had an optimal KIDMED score ($8). In children, KIDMED
scores did not differ between boys (5.4 6 1.9) and girls (5.4 6
1.7), but in adolescents, they tended to be higher in females
(4.9 6 2.1) than in males (4.6 6 2.0) (P ¼ 0.07). Children
scoring low in the KIDMED index spent more time on sedentary
activities compared with those scoring medium or high (Table
1). Additionally, the educational level of their parents was lower
compared with the other 2 groups, but their energy density was
higher. In adolescents, those in the low KIDMED score group
were significantly older and their energy density was higher compared with participants of the other 2 groups. In both children
and adolescents, BMI did not differ among the 3 KIDMED score
groups.
In the total sample of children and adolescents, KIDMED
scores were correlated (Spearman) with intakes of calcium (r ¼
0.187; P , 0.001), vitamin C (r ¼ 0.146; P , 0.001), and fiber
(r ¼ 0.073; P ¼ 0.010), and the associations remained after
adjusting for low energy reporting. Correlation coefficients
between BMI and KIDMED score were not significant among
children, even when the analysis was restricted to non-LER.
Conversely, among adolescents, the KIDMED score was weakly
but significantly negatively associated with BMI (r ¼ 20.136; P ¼
0.001) and this association remained significant when the analysis
was restricted to non-LER (r ¼ 20.190; P , 0.001). Partial correlations between KIDMED and BMI, after taking into account
variables such as age, sex, and time spent on sedentary and leisuretime physical activities, remained among children, whereas among
adolescents, the correlations were reduced but still significant both
in the total sample (r ¼ 20.092; P ¼ 0.031) and in the non-LER
subgroup (r ¼ 20.137; P ¼ 0.011).
Demographic, eating behavior, and physical activity factors,
known for their potential effect on food choices, were then
explored in regard to KIDMED. Time spent in sedentary activities (standardized b ¼ 20.128; P ¼ 0.001), maternal education level (standardized b ¼ 0.090; P ¼ 0.039), and EF
(standardized b ¼ 0.085; P ¼ 0.031) was associated with
KIDMED score in children (Table 2). When analyses were
restricted to the non-LER, EF and maternal education level were
not significant (P ¼ 0.164 and 0.094, respectively), whereas
paternal education was positively associated with KIDMED
score (standardized b ¼ 0.088; P ¼ 0.050).
Among adolescents, variables associated with the KIDMED
score were age (standardized b ¼ 20.117; P ¼ 0.010), female
sex (standardized b ¼ 0.084; P ¼ 0.050), time spent in leisuretime physical activities (standardized b ¼ 0.090; P ¼ 0.045),
time spent in sedentary activities (standardized b ¼ 20.133; P ¼
0.002), and EF (standardized b ¼ 0.200; P , 0.001) (Table 2). In
the non-LER subgroup analysis, age (P ¼ 0.001), time spent on
sedentary activities (P ¼ 0.015), and EF (P ¼ 0.041) remained
significant, whereas mother’s education level (P ¼ 0.014) was
also associated with KIDMED score.
TABLE 2
Results of the multiple regression models evaluating
associations between subjects’ characteristics and
KIDMED score1
Non-LER2
Total sample
Variable
Standardized b
n ¼ 727
20.128
0.090
0.074
0.001
0.039
Standardized b
P
n ¼ 620
20.129
0.002
0.077
0.094
0.086
0.088
0.050
0.031
0.164
0.001
0.510
0.297
0.085
n ¼ 521
20.117
0.084
0.090
0.010
0.050
0.045
0.058
n ¼ 331
20.184
0.035
0.057
20.133
0.080
0.002
0.117
20.131
0.156
0.015
0.014
0.200
,0.001
0.112
0.041
1
The table presents the results from the final models. Apart from the variables
presented above, eating at least 1 daily family meal was also included as an
independent variable, but it was not significantly associated with KIDMED score.
2
Individuals with ratio of EI:BMR $0.90 (37).
Discussion
Studies examining adherence to the Mediterranean diet among
young people are scarce. Serra-Majem et al. (11) found that in a
sample of 3850 children and young people aged 2–24 y residing
in Spain, 46.4% had an optimal Mediterranean diet. In the
present study, only 11.3% of children and 8.3% of adolescents
reported eating habits following the principles of the Mediterranean diet. Hence, our findings support previous evidence for
low to moderate adherence to the traditional dietary patterns
among younger generations in Mediterranean countries (10,11).
Unfortunately, estimates of dietary changes from longitudinal
data or results from past studies examining children’s adherence
to the Mediterranean diet are not available. Data from studies in
adults, however, point out that diets of Mediterranean populations are gradually moving away from the traditional and
beneficial patterns (9,38,39). Several factors have contributed to
this nutrition transition, such as the enhanced commercial
availability of food, the urbanization of life, and the overall
improvement in socioeconomic conditions in Europe, which has
increased the food and energy supply and made food (especially
of animal origin) more affordable (40,41). Moreover, a stressful
lifestyle, less time spent on cooking, and the enhanced variety
and availability of household appliances have also been proposed as determinants of nutrition transition (40). Finally, the
increase in migration and tourism observed in the last decades
has allowed cultural and lifestyle interchanges across populations (42).
Parental education level was a significant predictor of the
KIDMED score. Data from large epidemiological studies support a positive independent effect of household education on the
quality of children’s diet (43–45). Higher education level may be
related to higher income and, thus, greater availability of healthy
foods, increased nutrition knowledge, or increased motivation
to follow a healthy lifestyle. In support of the latter, we found
that a less sedentary lifestyle was also related to greater ad1954
Kontogianni et al.
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Children
Sedentary activities, min/d
Mother's education level,
high vs. low/medium
Father's education level, high vs.
low/medium
EF, eating episodes/d
Adolescents
Age, y
Female sex
Leisure-time physical activities,
min/d
Sedentary activities, min/d
Mother's education level,
high vs. low/medium
EF, eating episodes/d
P
herence to the Mediterranean diet, as previously evidenced in
adults (46,47). Consequently, we hypothesize that behaviors
related to healthy lifestyle tend to cluster and offer additional
beneficial protection against degenerative diseases.
Adoption of the Mediterranean diet has been associated with
favorable effects on lipoprotein levels, endothelium function,
insulin resistance, and metabolic syndrome (6–8). For body weight
and obesity status, however, some investigators observed an inverse association between Mediterranean dietary pattern and BMI
(48,49), whereas others found no correlation (50). In our analysis,
the partial correlation coefficients between KIDMED and BMI
were significantly negative only among adolescents.
Our study has both strengths and limitations. The findings
are strengthened by the fact that the sample was representative
of the Greek population in terms of sex and age, covering most
of the geographical areas. Furthermore, in the evaluation of dietary intake, low energy reporting was considered and all multivariate analyses were performed in the total sample as well as
in normal energy reporters. The prevalences of low energy reporting found here are comparable to those evidenced in earlier
studies (51,52) and the lower prevalence of low energy reporting
among children as compared with adolescents may be partly
attributed to the use of parents or caregivers as accurate reporters of children’s EI (53).
The method of data collection, i.e. through telephone
interviews, might be a potential study limitation, because direct
measures of dietary intake, weight, and height were not
available. On the other hand, the use of telephone surveys as a
method for collecting dietary information has several advantages compared with face-to-face interviews, because they are
less expensive and can reach a larger number of individuals, even
in rural areas (54). The increasing need to have access to dietary
information from large samples in an affordable fashion has
expanded the practice of telephone dietary surveys in several
population groups, including children and adolescents (55), and
validation studies have supported the accuracy of the data
collected (56).
Adherence to a Mediterranean dietary pattern was evaluated
through the use of a newly developed dietary quality index.
Although the Mediterranean diet indices have a number of
limitations and problems in their use, grouping foods to obtain
scores is a very useful method to evaluate overall diet (57). The
KIDMED was inspired by instruments previously developed for
adult populations (11), because there are no specific guidelines
with regards to the Mediterranean diet for non-adult populations. However, the validity of the KIDMED index has not been
determined compared with other measures of dietary patterns
such as FFQ. Our analysis revealed that the KIDMED score was
positively associated with calcium, vitamin C, and fiber intake.
These nutrients are characteristic of the food groups assessed by
the score (dairy products, fruits, vegetables, pulses, nuts, and
cereals) and the findings may provide some support for the
validity of the index. However, the ability of KIDMED to identify
adherence to the Mediterranean diet and associations with
biological outcomes needs to be investigated in further studies.
Finally, the cross-sectional design of the study and the lack of
biological indicators did not allow us to estimate any causal
relationship between lifestyle parameters and disease or potential
health benefits from adherence to this specific dietary pattern.
Although we attempted to account for variables that were
possibly associated with KIDMED, the potential for residual
confounding by uncontrolled covariates may be possible.
In conclusion, low adherence rates to the Mediterranean diet
were observed in a representative sample of Greek children and
adolescents, as these were estimated through the newly developed KIDMED index. This evidence needs to be further
explored, as well as its impact on health and disease.
Literature Cited
1.
2.
3.
4.
5.
6.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Mediterranean diet in children and adolescents
1955
Downloaded from jn.nutrition.org by guest on October 6, 2014
7.
Simopoulos AP. The Mediterranean diets: what is so special about the
diet of Greece? The scientific evidence. J Nutr. 2001; 131 Suppl 11:
S3065–73.
Willett WC, Sacks F, Trichopoulou A, Drescher G, Ferro-Luzzi A,
Helsing E, Trichopoulos D. Mediterranean diet pyramid: a cultural
model for healthy eating. Am J Clin Nutr. 1995; 61 Suppl 6:S1402–6.
Kafatos A, Verhagen H, Moschandreas J, Apostolaki I, Van Westerop JJ.
Mediterranean diet of Crete: foods and nutrient content. J Am Diet
Assoc. 2000;100:1487–93.
Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a
Mediterranean diet and survival in a Greek population. N Engl J Med.
2003;348:2599–608.
Estruch R, Martı´nez-Gonza´lez MA, Corella D, Salas-Salvado´ J,
Ruiz-Gutie´rrez V, Covas MI, Fiol M, Go´mez-Gracia E, Lo´pez-Sabater
MC, et al. PREDIMED Study Investigators. Effects of a Mediterraneanstyle diet on cardiovascular risk factors: a randomized trial. Ann Intern
Med. 2006;145:1–11.
Panagiotakos DB, Tzima N, Pitsavos C, Chrysohoou C, Zampelas A,
Toussoulis D, Stefanadis C. The association between adherence to the
Mediterranean diet and fasting indices of glucose homoeostasis: the
ATTICA Study. J Am Coll Nutr. 2007;26:32–8.
Esposito K, Ciotola M, Giugliano D. Mediterranean diet, endothelial
function and vascular inflammatory markers. Public Health Nutr.
2006;9:1073–6.
Psaltopoulou T, Naska A, Orfanos P, Trichopoulos D, Mountokalakis T,
Trichopoulou A. Olive oil, the Mediterranean diet, and arterial blood
pressure: the Greek European Prospective Investigation into Cancer and
Nutrition (EPIC) study. Am J Clin Nutr. 2004;80:1012–8.
Trichopoulos D, Lagiou P. Mediterranean diet and overall mortality
differences in the European Union. Public Health Nutr. 2004;7:949–51.
Kafatos A, Diacatou A, Voukiklakis G, Nikolakakis N, Vlachonikolis
G, Kounali D, Mamalakis G, Dontas A. Heart disease risk-factor status
and dietary changes in the Cretan population over the past 30 years.
The seven countries study. Am J Clin Nutr. 1997;65:1882–6.
Serra-Majem L, Ribas L, Ngo J, Ortega R, Garcia A, Perez C, Aranceta
J. Food, youth and the Mediterranean Diet in Spain. Development of
KIDMED, Mediterranean Diet Quality Index in children and adolescents. Public Health Nutr. 2004;7:931–5.
Greco L, Musmarra F, Franzese C, Auricchio S. Early childhood feeding
practices in southern Italy: is the Mediterranean diet becoming
obsolete? Study of 450 children aged 6–32 months in Campania, Italy.
Cultural Paediatric Association. Acta Paediatr. 1998;87:250–6.
Ferna´ndez San Juan PM. Dietary habits and nutritional status of school
aged children in Spain. Nutr Hosp. 2006;21:374–8.
Royo-Bordonada MA, Garce´s C, Gorgojo L, Martı´n-Moreno JM,
Lasuncio´n MA, Rodrı´guez-Artalejo F, Ferna´ndez O, de Oya M. Four
Provinces Study. Saturated fat in the diet of Spanish children: relationship with anthropometric, alimentary, nutritional and lipid profiles.
Public Health Nutr. 2006;9:429–35.
Petridou E, Malamou H, Doxiadis S, Pantelakis S, Kanellopoulou G,
Toupadaki N, Trichopoulou A, Flytzani V, Trichopoulos D. Blood lipids
in Greek adolescents and their relation to diet, obesity, and socioeconomic factors. Ann Epidemiol. 1995;5:286–91.
Aravanis C, Mensink RP, Karalias N, Christodoulou B, Kafatos A,
Katan MB. Serum lipids, apoproteins and nutrient intake in rural
Cretan boys consuming high-olive-oil diets. J Clin Epidemiol. 1988;41:
1117–23.
Hassapidou M, Fotiadou E, Maglara E, Papadopoulou SK. Energy
intake, diet composition, energy expenditure, and body fatness of
adolescents in northern Greece. Obesity (Silver Spring). 2006;14:855–62.
Serra-Majem L, Ribas L, Garcı´a A, Pe´rez-Rodrigo C, Aranceta J.
Nutrient adequacy and Mediterranean Diet in Spanish school children
and adolescents. Eur J Clin Nutr. 2003;57 Suppl 1:S35–9.
General Secretariat of the National Statistical Service of Greece.
Population census 2000–2001 [cited 2001]. Available from: http://
www.statistics.gr/StatMenu.asp
20. Linneman C, Hessler K, Nanney S, Steger-May K, Huynh A, HaireJoshu D. Parents are accurate reporters of their preschoolers’ fruit and
vegetable consumption under limited conditions. J Nutr Educ Behav.
2004;36:305–8.
21. Byers T, Trieber F, Gunter E, Coates R, Sowell A, Leonard S, Mokdad
A, Jewell S, Miller D, et al. The accuracy of parental reports of their
children’s intake of fruits and vegetables: validation of a food frequency
questionnaire with serum levels of carotenoids and vitamins C, A, and
E. Epidemiology. 1993;4:350–5.
22. Klesges RC, Klesges LM, Brown G, Frank GC. Validation of the 24hour dietary recall in preschool children. J Am Diet Assoc. 1987;
87:1383–5.
23. Sekine M, Yamagami T, Hamanishi S, Kagamimori S. Accuracy of the
estimated prevalence of childhood obesity from height and weight
values reported by parents: results of the Toyama Birth Cohort study.
J Epidemiol. 2002;12:9–13.
24. Jackson J, Strauss CC, Lee AA, Hunter K. Parents’ accuracy in
estimating child weight status. Addict Behav. 1990;15:65–8.
25. Goodman E, Hinden BR, Khandelwal S. Accuracy of teen and parental
reports of obesity and body mass index. Pediatrics. 2000;106:52–8.
26. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard
definition for child overweight and obesity worldwide: international
survey. BMJ. 2000;320:1240–3.
27. Cole TJ, Flegal KM, Nicholls D, Jackson AA. Body mass index cut offs
to define thinness in children and adolescents: international survey.
BMJ. 2007;335:194.
28. Dubois L, Farmer AP, Girard M, Peterson K. Preschool children’s eating
behaviors are related to dietary adequacy and body weight. Eur J Clin
Nutr. 2007;61:846–55.
29. Kant AK. Reported consumption of low-nutrient-density foods by American children and adolescents: nutritional and health correlates, NHANES
III, 1988 to 1994. Arch Pediatr Adolesc Med. 2003;157:789–96.
30. Goran MI. Measurement issues related to studies of childhood obesity:
assessment of body composition, body fat distribution, physical activity,
and food intake. Pediatrics. 1998;101:505–18.
31. McPherson RS, Hoelscher DM, Alexander M, Scanlon KS, Serdula MK.
Dietary assessment methods among school-aged children: validity and
reliability. Prev Med. 2000;31:S11–33.
32. Trichopoulou A, Georga K. Composition tables of simple and composite foods. Athens: Parisianos Scientific Publications; 2004.
33. Greek food composition tables. University of Crete, Department of
Medicine and Technological Institute of Thessaloniki, Department of
Nutrition [cited 2001]. Available from: http://nutrition.med.uoc.gr/
GreekTables.
34. Maillard G, Charles MA, Lafay L, Thibult N, Vray M, Borys JM, Basdevant
A, Eschwe`ge E, Romon M. Macronutrient energy intake and adiposity
in non obese prepubertal children aged 5–11 y (the Fleurbaix Laventie
Ville Sante´ Study). Int J Obes Relat Metab Disord. 2000;24:1608–17.
35. Schofield WN. Predicting basal metabolic rate, new standards and
review of previous work. Hum Nutr Clin Nutr. 1985;39:5–41.
36. FAO/WHO/UNU. Human energy requirements. Report of a Joint FAO/
WHO/UNU Expert Consultation. Rome: FAO/WHO/UNU; 2004.
37. Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward
WA, Prentice AM. Critical evaluation of energy intake data using
fundamental principles of energy physiology. 1. Derivation of cut-off
limits to identify under-recording. Eur J Clin Nutr. 1991;45:569–81.
38. Trichopoulou A, Lagiou P, Kuper H, Trichopoulos D. Cancer and
Mediterranean dietary traditions. Cancer Epidemiol Biomarkers Prev.
2000;9:869–73.
39. Serra-Majem L, La Vecchia C, Ribas-Barba L, Prieto-Ramos F, Lucchini
F, Ramon JM. Changes in diet and mortality from selected cancers in
southern Mediterranean countries, 1960–1989. Eur J Clin Nutr. 1993;
47 Suppl 1:S25–34.
40. Moreno LA, Sarrı´a A, Popkin BM. The nutrition transition in Spain: a
European Mediterranean country. Eur J Clin Nutr. 2002;56:992–1003.
41. Popkin BM. An overview on the nutrition transition and its health
implications: the Bellagio meeting. Public Health Nutr. 2002;5:93–103.
42. Tessier S, Gerber M. Factors determining the nutrition transition in two
Mediterranean islands: Sardinia and Malta. Public Health Nutr. 2005;8:
1286–92.
43. Rogers I, Emmett P, ALSPAC Study Team. The effect of maternal
smoking status, educational level and age on food and nutrient intakes
44.
45.
46.
47.
48.
49.
50.
1956
Kontogianni et al.
51. Fletcher ES, Rugg-Gunn AJ, Matthews JN, Hackett A, Moynihan PJ,
Mathers JC, Adamson AJ. Changes over 20 years in macronutrient
intake and body mass index in 11- to 12-year-old adolescents living in
Northumberland. Br J Nutr. 2004;92:321–33.
52. Champagne CM, Baker NB, DeLany JP, Harsha DW, Bray GA.
Assessment of energy intake underreporting by doubly labeled water
and observations on reported nutrient intakes in children. J Am Diet
Assoc. 1998;98:426–33.
53. Davies PS, Coward WA, Gregory J, White A, Mills A. Total energy
expenditure and energy intake in the pre-school child: a comparison. Br
J Nutr. 1994;72:13–20.
54. Fox TA, Heimendinger J, Block G. Telephone surveys as a method for
obtaining dietary information: a review. J Am Diet Assoc. 1992;92:
729–32.
55. Ponza M, Devaney B, Ziegler P, Reidy K, Squatrito C. Nutrient intakes
and food choices of infants and toddlers participating in WIC. J Am
Diet Assoc. 2004;104 Suppl 1:S71–9.
56. Baxter SD. Accuracy of fourth-graders’ dietary recalls of school
breakfast and school lunch validated with observations: in-person
versus telephone interviews. J Nutr Educ Behav. 2003;35:124–34.
57. Bach A, Serra-Majem L, Carrasco JL, Roman B, Ngo J, Bertomeu I,
Obrador B. The use of indexes evaluating the adherence to the
Mediterranean diet in epidemiological studies: a review. Public Health
Nutr. 2006;9:132–46.
Downloaded from jn.nutrition.org by guest on October 6, 2014
in preschool children: results from the Avon Longitudinal Study of
Parents and Children. Eur J Clin Nutr. 2003;57:854–64.
Sausenthaler S, Kompauer I, Mielck A, Borte M, Herbarth O, Schaaf B,
von Berg A, Heinrich J. Impact of parental education and income
inequality on children’s food intake. Public Health Nutr. 2007;10:
24–33.
Riediger ND, Shooshtari S, Moghadasian MH. The influence of
sociodemographic factors on patterns of fruit and vegetable consumption in Canadian adolescents. J Am Diet Assoc. 2007;107:1511–8.
Sa´nchez-Villegas A, Martı´nez JA, De Irala J, Martı´nez-Gonza´lez MA.
Determinants of the adherence to an ‘‘a priori’’ defined Mediterranean
dietary pattern. Eur J Nutr. 2002;41:249–57.
Costacou T, Bamia C, Ferrari P, Riboli E, Trichopoulos D, Trichopoulou
A. Tracing the Mediterranean diet through principal components and
cluster analyses in the Greek population. Eur J Clin Nutr. 2003;57:
1378–85.
Panagiotakos DB, Chrysohoou C, Pitsavos C, Stefanadis C. Association
between the prevalence of obesity and adherence to the Mediterranean
diet: the ATTICA study. Nutrition. 2006;22:449–56.
Schro¨der H, Marrugat J, Vila J, Covas MI, Elosua R. Adherence to the
traditional Mediterranean diet is inversely associated with body mass
index and obesity in a Spanish population. J Nutr. 2004;134:3355–61.
Trichopoulou A, Naska A, Orfanos P, Trichopoulos D. Mediterranean
diet in relation to body mass index and waist-to-hip ratio: the Greek
European Prospective Investigation into Cancer and Nutrition Study.
Am J Clin Nutr. 2005;82:935–40.