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Public Health Nutrition logoLink to Public Health Nutrition
. 2012 Jun 12;16(3):487–498. doi: 10.1017/S136898001200290X

Parental education and frequency of food consumption in European children: the IDEFICS study

Juan Miguel Fernández-Alvira 1,*, Theodora Mouratidou 1, Karin Bammann 2, Antje Hebestreit 2, Gianvincenzo Barba 3, Sabina Sieri 4, Lucia Reisch 5, Gabriele Eiben 6, Charalampos Hadjigeorgiou 7, Eva Kovacs 8, Inge Huybrechts 9, Luis A Moreno 1, on behalf of the IDEFICS Consortium
PMCID: PMC10271421  PMID: 22687743

Abstract

Objective

To assess the relationship between parental education level and the consumption frequency of obesity-related foods in European children.

Design

The analysis was based on data from the cross-sectional baseline survey of a prospective cohort study. The effects of parental education on food consumption were explored using analysis of covariance and logistic regression.

Setting

Primary schools and pre-schools of selected regions in Italy, Estonia, Cyprus, Belgium, Sweden, Hungary, Germany and Spain.

Subjects

Participants (n 14 426) of the IDEFICS baseline cohort study aged 2 to 9 years.

Results

Parental education level affected the intake of obesity-related foods in children. Children in the low and medium parental education level groups had lower odds of more frequently eating low-sugar and low-fat foods (vegetables, fruits, pasta/noodles/rice and wholemeal bread) and higher odds of more frequently eating high-sugar and high-fat foods (fried potatoes, fruits with sugar and nuts, snacks/desserts and sugared beverages; P < 0·001). The largest odds ratio differences were found in the low category (reference category: high) for vegetables (OR = 0·56; 95 % CI 0·47, 0·65), fruits (OR = 0·56; 95 % CI 0·48, 0·65), fruits with sugar and nuts (OR = 2·23; 95 % CI 1·92, 2·59) and sugared beverages (OR = 2·01; 95 % CI 1·77, 2·37).

Conclusions

Low parental education level was associated with intakes of sugar-rich and fatty foods among children, while high parental education level was associated with intakes of low-sugar and low-fat foods. These findings should be taken into account in public health interventions, with more targeted policies aiming at an improvement of children's diet.

Keywords: Parental education, Children, IDEFICS study, Food consumption


Social inequalities in health determine the risk of morbidity and mortality from childhood through to adult life( 1 ). Consistent evidence indicates that people of low socio-economic status (SES) have a heavier burden of disease than their better-off counterparts( 2 ). SES refers to an individual's relative position in the social hierarchy and can be operationalized through diverse indicators including educational attainment, occupation and/or income. It is possible that such indicators affect food consumption in different ways due to different underlying social and psychological processes involving factors like nutritional knowledge, budget constraints or peer group behaviour( 3 , 4 ). Diet quality has been shown to follow a socio-economic gradient( 5 ). Studies examining the impact of SES on adolescents' and children's food intake have suggested high consumption of high-fat and high-sugar foods, and low consumption of fruits and vegetables, in individuals from disadvantaged groups( 6 10 ).

Family structure and support is one of the most influential aspects of the social environment of children. Parental influences on children's food choices and intake have an effect on individual and family practices, and operate among other mechanisms via availability and accessibility of foods or parental eating behaviour as food modelling( 11 , 12 ). Through this link, parental educational level is associated with children's food intake and frequency of consumption, and subsequently with childhood overweight and obesity( 13 15 ). However, the stability and repeatability of these relationships between countries have been scarcely investigated.

The present study aimed to assess the association between parental education levels and the consumption frequency of obesity-related food groups (e.g. foods that are shown by consistent evidence to be related, either positively or negatively, to overweight and obesity in children) among children aged 2 to 9 years from eight European countries.

Methods

The ‘Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS’ (IDEFICS) study is a population-based multicentre study of children aged 2 to 9 years from eight European countries. The two main aims were: (i) to investigate the aetiology of obesity and related disorders; and (ii) to implement a community-based intervention to prevent obesity and related diseases. For the present analysis, children recruited during the cross-sectional baseline survey were considered. Between September 2007 and May 2008, 31 543 children from primary schools and pre-schools of selected regions in Italy (Avellino), Estonia (Tartumaa, Harjumaa), Cyprus (Nicosia District, Paphos), Belgium (East-Flanders), Sweden (Västra Götaland), Hungary (Baranya, Zala), Germany (Lower Saxony) and Spain (Zaragoza, Huesca) were invited to participate in the baseline survey (T0) with a response rate of 53·4 % (n 16 864). The lowest response rates were reached in Spain (41 %) and Hungary (44 %), and the highest in Italy (60 %) and Sweden (66 %). In total 16 224 children (51·4 %) fulfilled the study's inclusion criteria (complete information on age, sex, height and weight). Sample size ranged from 1507 in Spain to 2567 in Hungary. An in-depth description of the complete IDEFICS study population is given by Ahrens et al.( 16 ). Of the total sample, 14 426 children (88·9 %) had valid data on SES and food intake, and were included in the current analysis. Further information on the study procedures is available in previous papers( 17 , 18 ). Each participating centre obtained ethical approval for the study from its respective responsible authority. All children provided oral consent and their parents provided written informed consent for all examinations and the collection, analysis and storage of personal data and collected samples.

Measurements

Data on personal, social, environmental and behavioural factors were collected by means of two standardized self-administered questionnaires that were filled in by the parents or guardians of the child. Education level of parents taken from the core parental questionnaire was used as a proxy indicator of SES, using categories according to the International Standard Classification of Education (ISCED)( 19 ). Three levels of education (low, medium, high) were created out of the six ISCED levels of the parental questionnaire: ISCED level 0, 1 or 2 adding up to low education; level 3 or 4 adding up to medium education; and level 5 or 6 adding up to high education. For the purposes of the present analysis, the highest education level of parents (either mother or father) was considered.

Dietary data were obtained by the food frequency section of the Children's Eating Habits Questionnaire–Food Frequency Questionnaire (CEHQ-FFQ)( 20 ) in which the frequency of the child's consumption of selected food items during the preceding four weeks was reported. In order to assess meals under parental control, recall referred to meals outside the school canteen or childcare meal provision settings only( 20 , 21 ). The CEHQ-FFQ consisted of forty-three food items clustered into fourteen food groups. It was applied as a screening instrument to investigate the consumption of foods shown to be related, either positively or negatively, to overweight and obesity in children. The CEHQ-FFQ was not designed to provide an estimate of total energy intake or total food intake, but rather to investigate the consumption frequency of obesity-related foods. Those foods less likely to be associated with obesity were not included. Response options displayed were as follows: ‘never/less than once a week’, ‘1–3 times a week’, ‘4–6 times a week’, ‘1 time per day’, ‘2 times per day’, ‘3 times per day’, ‘4 or more times per day’ and ‘I have no idea’. For the analysis, a conversion factor was used to transform the questionnaire answers into actual weekly consumption frequencies. When the proxy reported having ‘no idea’, consumption frequency could not be calculated and the data were not used in the analysis of the respective food item. No information on portion sizes was obtained.

Anthropometric measurements were carried out by trained staff following a standardized procedure in all centres. Body height (cm) was measured without shoes and all braids undone using a portable stadiometer (SECA 225). Weight (kg) was measured by means of a child-adapted version of an electronic scale (TANITA BC 420 SMA) with the children in a fasting status and wearing only underwear( 22 ). BMI was calculated and categorized following cut-off points according to the criteria of the International Obesity Taskforce( 23 , 24 ). The sample was classified into thinness, normal weight, overweight and obese categories.

Statistical analysis

Descriptive data are shown as proportions, means and standard deviations. Differences in frequency of food consumption (times/week) by classified parental education (low, medium and high) were assessed by analysis of covariance models. Logistic regression analysis was used to examine the effect of parental education on frequency of food consumption. For this purpose, frequencies of food consumption were divided into tertiles (lowest, middle and highest consumption), based on country-specific variable distributions and for each food item separately. Finally, dichotomous variables were created, comparing the highest consumption (high consumers) against the rest of the sample, namely the lowest and middle tertiles (average consumers). High parental education level was set as the reference category. Prevalence of high consumers by parental education was also calculated. Both analyses (analysis of covariance and logistic regression) were adjusted for the following covariates: sex, age, BMI category and country. Statistical significance was set at P ≤ 0·05. All analyses were conducted using the Predictive Analytic Software (PASW) version 18·0 (SPSS Inc., Chicago, IL, USA).

Results

Study participants excluded from the present study did not differ from those included in terms of sex, age, BMI category or parental education level. Based on the statistically significant interaction between educational level and country (all P < 0·001), results are provided for the whole sample and by country. Table 1 describes the sociodemographic and anthropometric characteristics of the participating children (n 14 426). Mean age was 6·0 (1·8) years, with 46·6 % being of pre-school age (<6 years old) and 50·9 % being girls. Of the children, 69·8 % had normal weight for their height and age, while 12·4 % were classified as overweight and 6·8 % as obese. Some 41·2 % of the participants’ parents had a high education level, 50·1 % a medium education and 8·7 % a low education. Sample size as a proportion of the total population varied among countries from 8·8 % in Spain to 17·2 % in Hungary. The following results refer to meals consumed outside the school canteen or childcare meal provision settings. The percentage of meals under parental control differed between countries (Italy 88 %, Estonia 69 %, Cyprus 84 %, Belgium 77 %, Sweden 65 %, Germany 90 %, Hungary 69 % and Spain 84 %).

Table 1.

Characteristics of the study sample: children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

n % Mean sd
Age (years)
Total 14 426 5·99 1·8
Pre-school 6631 46·6 4·28 0·9
School 7795 54·0 7·44 0·8
Sex
Girls 7338 50·9
Boys 7088 49·1
Parental education level
Low 1258 8·7
Medium 7227 50·1
High 5941 41·2
BMI category
Thinness 1592 11·0
Normal weight 10 068 69·8
Overweight 1790 12·4
Obese 976 6·8
Country
Belgium 1765 12·2
Cyprus 1462 10·1
Estonia 1599 11·1
Germany 1922 13·3
Hungary 2480 17·2
Italy 2189 15·2
Spain 1272 8·8
Sweden 1737 12·0

Table 2 shows the weekly consumption frequencies and odds ratios (95 % confidence intervals) for consumption of low-sugar and low-fat foods by parental education level for the total sample. Significant differences in mean frequency of consumption of the chosen foods between parental education groups were observed. The highest mean frequency of weekly consumption for vegetables, fruits, pasta/noodles/rice, wholemeal bread and water was observed in the highest education level category. The largest differences were found for water (21·6 (se 0·1) times/week in the high category v. 19·5 (se 0·3) times/week in the low category) and vegetables (9·0 (se 0·1) times/week in the high category v. 7·7 (se 0·2) times/week in the low category). No significant trend was found for plain unsweetened milk. Taking into account the odds ratio results, children with parents in the low and medium parental education level groups had lower odds of more frequently eating vegetables, fruits, pasta/noodles/rice and wholemeal bread (P < 0·001). Children with parents from the low parental education level group had also lower odds of more frequently drinking water (P < 0·05) and plain unsweetened milk (P < 0·001). The largest odds ratio differences were found in the low category (reference category: high) for vegetables (OR = 0·56; 95 % CI 0·47, 0·65) and fruits (OR = 0·56; 95 % CI 0·48, 0·65).

Table 2.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of low-sugar and low-fat foods by classified parental education level; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Food group/Parental education n Mean se p† OR 95 % CI
Vegetables (raw and cooked)
Low 1049 7·7a,b 0·19 33 0·56*** 0·47, 0·65
Medium 6685 8·1a,c 0·07 36 0·76*** 0·70, 0·82
High 5696 9·0b,c 0·08 38
Fruits
Low 1021 7·0a,b 0·19 27 0·56*** 0·48, 0·65
Medium 6598 7·6a,c 0·07 35 0·74*** 0·69, 0·80
High 5660 8·2b,c 0·08 41
Fresh meat and fish
Low 1046 3·9a,b 0·10 41 1·02 0·88, 1·19
Medium 6685 3·6a,c 0·04 36 1·02 0·95, 1·11
High 5726 3·3b,c 0·04 35
Pasta, noodles and rice
Low 1021 2·8a,b 0·08 31 0·61*** 0·52, 0·72
Medium 6606 3·0a,c 0·03 30 0·85*** 0·77, 0·93
High 5669 3·2b,c 0·04 32
Wholemeal bread
Low 993 3·4b 0·15 28 0·76*** 0·64, 0·90
Medium 6479 3·5c 0·06 32 0·79*** 0·72, 0·86
High 5602 3·9b,c 0·06 36
Water
Low 1001 19·5a,b 0·32 60 0·83* 0·71, 0·99
Medium 6563 20·8a,c 0·12 51 0·97 0·89, 1·06
High 5637 21·6b,c 0·14 50
Plain unsweetened milk
Low 973 7·3 0·23 31 0·68*** 0·59, 0·80
Medium 6394 7·5 0·09 36 0·92 0·85, 1·00
High 5511 7·4 0·10 33

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0·05, ***P < 0·001.

†p refers to the proportion of participants assigned to the highest consumption category.

Table 3 shows the weekly consumption frequencies and odds ratios (95 % confidence intervals) for consumption of high-sugar, refined and high-fat foods by parental education level for the total sample. Significant differences in mean frequency of consumption of the chosen foods between parental education groups were observed. The highest mean frequency of weekly consumption for fried potatoes, fruits with sugar and nuts, fried meat and fish, cold cuts, fast food, white bread, sugared beverages, snacks/desserts and chocolate/nut-based spread was observed in the low educational level category. Marked differences were observed for sugared beverages (17·5 (se 0·4) times/week in the low category v. 11·4 (se 0·2) times/week in the high category), snacks/desserts (9·3 (se 0·2) times/week in the low category v. 6·9 (se 0·1) times/week in the high category) and fruits with sugar and nuts (4·7 (se 0·2) times/week in the low category v. 2·5 (se 0·1) times/week in the high category). Odds ratio results show that participants in the low and medium parental education level categories had higher odds of more frequently consuming fried potatoes, fruits with sugar and nuts, fried meat and fish, sugared beverages and snacks/desserts (P < 0·001). Participants in the low parental education category had also higher odds of more frequently consuming fast food and chocolate/nut-based spread (P < 0·001). The largest odds ratio differences were found in the low category (reference category: high) for fruits with sugar and nuts (OR = 2·23; 95 % CI 1·92, 2·59), fried potatoes (OR = 2·00; 95 % CI 1·72, 2·31) and sugared beverages (OR = 2·01; 95 % CI 1·77, 2·37).

Table 3.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of high-sugar, refined and high-fat foods by classified parental education level; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Food group/Parental education n Mean se P† OR 95 % CI
Fried potatoes
Low 1035 1·6a,b 0·06 47 2·00*** 1·72, 2·31
Medium 6618 1·2a,c 0·02 41 1·34*** 1·24, 1·45
High 5674 0·9b,c 0·02 33
Fruits with sugar and nuts
Low 1045 4·7a,b 0·15 46 2·23*** 1·92, 2·59
Medium 6691 3·2a,c 0·06 35 1·23*** 1·14, 1·33
High 5742 2·5b,c 0·06 36
Fried meat and fish
Low 1048 3·9a,b 0·09 48 1·36*** 1·17, 1·58
Medium 6683 3·4a,c 0·04 42 1·10* 1·01, 1·20
High 5717 3·0b,c 0·04 41
Cold cuts
Low 1025 4·4a,b 0·12 36 1·18* 1·00, 1·39
Medium 6574 4·0a 0·05 32 1·00 0·92, 1·08
High 5638 3·9b 0·05 36
Fast food
Low 1015 2·4a,b 0·09 30 1·55*** 1·30, 1·85
Medium 6622 1·8a 0·03 25 0·99 0·89, 1·10
High 5700 1·8b 0·04 25
White bread
Low 1030 7·8a,b 0·19 40 1·14 0·99, 1·33
Medium 6609 7·1a,c 0·08 36 1·09* 1·01, 1·18
High 5662 6·6b,c 0·09 37
Sugared beverages‡
Low 1049 17·5a,b 0·35 47 2·01*** 1·77, 2·37
Medium 6710 13·5a,c 0·14 37 1·27*** 1·17, 1·38
High 5744 11·4b,c 0·15 33
Snacks and desserts
Low 1043 9·3a,b 0·21 43 1·61*** 1·39, 1·87
Medium 6686 7·6a,c 0·08 37 1·22*** 1·12, 1·32
High 5738 6·9b,c 0·09 39
Chocolate- or nut-based spread
Low 1017 2·5a,b 0·08 32 1·39*** 1·17, 1·66
Medium 6551 1·9a,c 0·03 31 1·08 0·96, 1·20
High 5664 1·7b,c 0·04 27

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0.05, ***P < 0.001.

†p refers to the proportion of participants assigned to the highest consumption category.

‡Includes soft drinks, fruit juices and sugared milk.

Tables 4 and 5 show the weekly consumption frequencies and odds ratio (95 % confidence intervals) for consumption of low-sugar and low-fat foods and high-sugar, refined and high-fat foods, respectively, by parental education level and by participating country. The largest differences by parental education category were observed in Hungary for sugared beverages (22·5 (se 2·4) times/week in the low category v. 14·1 (se 0·4) times/week in the high category) and for white bread (13·9 (se 1·4) times/week in the low category v. 8·0 (se 0·2) times/week in the high category); in Belgium for water (9·7 (se 1·9) times/week in the low category v. 17·2 (se 0·3) times/week in the high category); and in Cyprus for snacks/desserts (11·0 (se 4·0) times/week in the low category v. 6·1 (se 0·2) times/week in the high category).

Table 5a.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of high-sugar, refined and high-fat foods by classified parental education and country; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Belgium Estonia Germany Sweden
Food group/Parental education Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI
Fried potatoes
Low 1·2 0·17 58 1·25 0·63, 2·47 1·4 0·42 50 0·94 0·38, 2·36 1·5a,b 0·15 48 2·23*** 1·62, 3·06 1·0 0·26 50 3·45* 1·26, 9·39
Medium 1·3c 0·06 57 1·25* 1·01, 1·55 1·5 0·06 52 1·29 0·96, 1·72 0·9a 0·05 33 1·17 0·90, 1·53 0·5 0·05 21 0·99 0·76, 1·30
High 1·1c 0·04 51 1·2 0·11 46 0·6b 0·06 29 0·5 0·03 21
Fruits with sugar and nuts
Low 1·7 0·45 38 0·78 0·39, 1·55 5·5 1·49 36 1·22 0·48, 3·12 4·2a,b 0·31 37 3·10*** 2·20, 4·78 3·1 0·81 69 3·00* 1·02, 8·84
Medium 2·1c 0·13 51 1·36* 1·10, 1·67 5·0 0·15 33 1·10 0·80, 1·50 2·5a 0·14 22 1·47* 1·09, 1·97 2·1 0·15 47 1·14 0·92, 1·41
High 1·6c 0·09 44 4·5 0·36 31 2·1b 0·21 16 1·7 0·09 44
Fried meat and fish
Low 5·2 0·39 43 1·44 0·73, 2·81 2·3 0·60 32 0·81 0·31, 2·12 3·9b 0·20 54 2·07*** 1·43, 2·99 5·3 0·39 56 1·99 0·73, 5·45
Medium 4·5 0·12 33 0·97 0·78, 1·21 3·0c 0·09 42 1·46* 1·07, 1·99 3·5 0·08 52 1·58* 1·16, 2·16 4·4 0·13 37 0·96 0·77, 1·21
High 4·5 0·08 33 2·4c 0·15 33 3·2b 0·12 50 4·2 0·06 38
Cold cuts
Low 5·3 0·63 36 1·32 0·66, 2·67 7·5a,b 1·51 38 1·94 0·74, 5·09 6·0 0·27 38 0·90 0·66, 1·23 3·6 0·92 38 1·84 0·65, 5·17
Medium 4·4 0·14 27 0·84 0·66, 1·05 4·3a 0·11 23 0·93 0·66, 1·32 6·6 0·13 43 1·11 0·87, 1·41 2·5 0·15 26 1·11 0·87, 1·43
High 4·5 0·10 30 4·1b 0·24 23 5·7 0·21 41 2·2 0·10 23
Fast food
Low 0·5b 0·30 11 3·77* 1·24, 11·5 3·8 0·90 32 0·77 0·29, 2·04 1·0a,b 0·15 22 4·64*** 2·77, 7·78 0·6 0·24 31 1·07 0·37, 3·13
Medium 0·2c 0·04 8 2·51*** 1·56, 4·03 4·5 0·11 29 0·78 0·57, 1·07 0·3a 0·03 9 1·52 0·93, 2·47 0·6 0·05 29 0·73 0·73, 1·18
High 0·1b,c 0·02 3 5·0 0·28 35 0·2b 0·05 6 0·6 0·02 31
White bread
Low 7·3b 0·78 56 3·01* 1·53, 5·92 9·4 1·67 36 2·08 0·79, 5·44 8·0a,b 0·35 53 1·92*** 1·34, 2·76 3·8 0·87 31 0·79 0·27, 2·34
Medium 5·8c 0·21 43 1·80*** 1·45, 2·24 6·8 0·17 23 1·24 0·86, 1·80 6·0a 0·16 42 0·96 0·70, 1·31 3·9c 0·20 42 1·25 0·99, 1·56
High 4·3b,c 0·14 29 6·5 0·40 19 6·2b 0·27 46 3·3c 0·09 37
Sugared beverages‡
Low 15·3b 2·28 34 1·45 0·73, 2·90 12·1 2·11 18 0·47 0·15, 1·48 22·2a,b 0·93 46 2·10*** 1·52, 2·90 7·2 1·26 44 1·51 0·55, 4·18
Medium 14·7c 0·50 38 1·77*** 1·42, 2·20 12·8 0·27 34 1·20 0·82, 1·53 16·2a 0·44 34 1·14 0·87, 1·49 5·7 0·28 36 1·17 0·93, 1·47
High 10·9b,c 0·29 26 12·7 0·63 32 14·3b 0·65 31 5·1 0·14 32
Snacks and desserts
Low 8·3 0·91 32 0·89 0·44, 1·80 9·6 1·74 48 1·96 0·78, 4·95 10·7a,b 0·49 41 1·34 0·98, 1·86 5·0 0·86 56 0·84 0·27, 2·65
Medium 8·7 0·28 31 0·87 0·70, 1·09 7·9 0·20 33 1·04 0·76, 1·42 9·6a 0·20 36 0·96 0·74, 1·24 5·0 0·16 51 0·88 0·69, 1·12
High 9·3 0·20 35 7·5 0·40 33 9·1b 0·27 36 5·3 0·08 56
Chocolate- or nut-based spread
Low 3·0b 0·36 16 0·43 0·18, 1,06 2·1a,b 0·68 43 4·26* 1·56, 11·6 3·7a,b 0·26 41 1·46* 1·06, 2·00 0·3 0·17 12 6·94* 1·41, 34·2
Medium 3·9c 0·13 26 0·79* 0·62, 0·99 0·9a,c 0·05 25 2·41*** 1·56, 3·71 2·8a 0·09 33 1·01 0·78, 1·30 0·1 0·02 4 1·32 0·73, 2·40
High 4·4b,c 0·10 29 0·3b,c 0·06 12 2·8b 0·17 33 0·1 0·02 3

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0.05, ***P < 0.001.

†p refers to the proportion of participants assigned to the highest consumption category.

‡Includes soft drinks, fruit juices and sugared milk.

Table 5b.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of high-sugar, refined and high-fat foods by classified parental education and country; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Cyprus Hungary Italy Spain
Food group/Parental education Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI
Fried potatoes
Low 3·6a,b 1·12 24 3·21* 1·22, 8·49 1·8b 0·29 62 2·85*** 1·60, 5·05 1·2a,b 0·10 42 1·39* 1·04, 1·84 1·5 b 0·15 60 1·69* 1·13, 2·53
Medium 2·1a,c 0·13 14 1·69*** 1·20, 2·39 1·4c 0·05 54 1·99*** 1·68, 2·37 0·8a 0·04 33 0·94 0·74, 1·19 1·3 0·08 52 1·21 0·94, 1·55
High 1·5b,c 0·08 9 0·8b,c 0·04 37 0·7b 0·06 34 1·1b 0·05 47
Fruits with sugar and nuts
Low 5·7 2·15 43 1·63 0·77, 3·43 6·3a,b 1·07 46 2·72*** 1·56, 4·74 4·7a,b 0·28 45 3·14*** 2·30, 4·29 4·4 a,b 0·44 46 3·24*** 2·15, 4·89
Medium 4·5 0·27 36 1·23 0·97, 1·56 3·3a,c 0·14 30 1·41*** 1·17, 1·71 3·2a,c 0·14 31 1·73*** 1·32, 2·27 3·2 a,c 0·22 30 1·60*** 1·20, 2·12
High 3·8 0·19 31 2·4b,c 0·11 23 2·0b,c 0·17 21 2·1 b,c 0·11 21
Fried meat and fish
Low 3·2b 1·98 13 1·46 0·70, 3·05 3·7b 0·46 44 1·57 0·90, 2·72 2·8a,b 0·15 36 1·58* 1·18, 2·13 5·3a,b 0·42 39 1·43 0·95, 2·15
Medium 2·1c 0·18 21 1·52*** 1·21, 1·90 3·0 0·08 34 1·04 0·87, 1·24 2·4a,c 0·07 34 1·40* 1·08, 1·80 4·0a 0·15 32 1·05 0·81, 1·37
High 1·2b,c 0·07 14 2·8b 0·07 34 2·0b,c 0·10 27 3·9b 0·10 31
Cold cuts
Low 3·5 0·72 48 1·49 0·69, 3·23 6·8a,b 0·87 43 1·72 0·99, 3·02 2·9a,b 0·15 28 1·75* 1·25, 2·46 3·9 0·40 19 0·90 0·55, 1·49
Medium 3·2 0·17 31 0·76* 0·60, 0·96 5·1a 0·12 34 1·22* 1·02, 1·46 2·4a 0·07 20 1·17 0·87, 1·58 3·8 0·15 20 0·91 0·67, 1.24
High 3·1 0·13 37 4·7b 0·12 30 2·1b 0·11 18 4·0 0·11 22
Fast food
Low 5·3 1·15 44 1·53 0·70, 3·35 7·0a,b 1·04 57 2·22* 1·26, 3·91 1·0a,b 0·10 31 1·39* 1·01, 1·90 0·8 0·11 35 1·10 0·73, 1·68
Medium 4·1 0·19 29 0·78* 0·62, 0·99 3·6a 0·11 36 0·95 0·80, 1·14 0·7a 0·04 26 1·11 0·85, 1·45 0·8 0·07 29 0·90 0·68, 1·18
High 4·4 0·13 35 3·5b 0·10 37 0·6b 0·06 24 0·8 0·06 30
White bread
Low 11·4 2·03 44 1·59 0·71, 3·56 13·9a,b 1·36 59 2·89*** 1·64, 5·10 6·8 0·30 23 0·88 0·64, 1·21 8·8 0·75 34 0·83 0·55, 1·27
Medium 8·9 0·34 34 1·01 0·80, 1·28 9·7a,c 0·21 42 1·50*** 1·26, 1·80 7·2 0·17 26 1·01 0·78, 1·32 7·2 0·36 34 0·81 0·62, 1·06
High 8·8 0·24 34 8·0b,c 0·21 32 7·3 0·31 25 7·0 0·27 39
Sugared beverages‡
Low 15·1 2·18 39 1·74 0·80, 3·77 22·5a,b 2·38 44 2·07* 1·19, 3·60 16·0a,b 0·59 45 2·74*** 2·02, 3·71 18·2a,b 1·26 55 2·38*** 1·60, 3·54
Medium 13·8c 0·54 34 1·20 0·94, 1·52 16·9a,c 0·39 37 1·53*** 1·28, 1·84 12·9a,c 0·29 32 1·52* 1·16, 1·97 14·1a,c 0·47 38 1·24 0·95, 1·60
High 11·8c 0·35 29 14·1b,c 0·37 28 11·2b,c 0·48 23 12·2b,c 0·27 33
Snacks and desserts
Low 11·0a,b 3·99 52 1·34 0·61, 2·95 9·2a,b 0·84 56 3·45*** 1·98, 6·03 11·5a,b 0·51 43 2·28*** 1·69, 3·08 6·3 0·48 34 1·26 0·83, 1·92
Medium 7·2a,c 0·38 38 1·17 0·92, 1·50 6·4a,c 0·18 38 1·65*** 1·38, 1·98 9·3a 0·25 33 1·44* 1·11, 1·85 5·9 0·28 37 1·44* 1·11, 1·88
High 6·1b,c 0·18 38 4·6b,c 0·13 27 8·1b 0·38 25 5·2 0·17 29
Chocolate- or nut-based spread
Low 1·6 0·41 55 3·92* 1·65, 9·32 3·2a,b 0·48 78 4·88*** 2·53, 9·42 3·0a,b 0·20 26 1·39 0·99, 1·94 1·5 0·19 55 1·29 0·66, 2·52
Medium 1·2c 0·13 34 1·62*** 1·26, 2·09 1·8a,c 0·08 53 1·52*** 1·28, 1·81 2·3a 0·08 23 1·20 0·90, 1·59 1·5 0·09 59 1·16 0·74, 1·79
High 0·7c 0·06 24 1·3b,c 0·06 43 1·9b 0·13 20 1·5 0·06 59

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0.05, ***P < 0.001.

†p refers to the proportion of participants assigned to the highest consumption category.

‡Includes soft drinks, fruit juices and sugared milk.

Table 4a.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of low-sugar and low-fat foods by classified parental education level and country; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Belgium Estonia Germany Sweden
Food group/Parental education Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI
Vegetables (raw and cooked)
Low 7·2 0·42 19 0·26*** 0·11, 0·60 7·1 1·10 27 0·52 0·19, 1·41 8·4a,b 0·32 34 0·32*** 0·23, 0·46 13·6 2·61 44 1·58 0·58, 4·34
Medium 7·7 0·16 41 0·82 0·66, 1·00 8·8 0·17 36 0·75 0·56, 1·00 10·4a 0·20 52 0·80 0·63, 1·02 11·6 0·35 31 0·93 0·73, 1·17
High 7·9 0·11 46 9·6 0·42 44 11·1b 0·33 57 12·0 0·19 33
Fruits
Low 5·4 0·61 9 0·48 0·14, 1·61 7·0 1·44 46 0·85 0·31, 2·33 7·1a,b 0·36 20 0·42*** 0·30, 0·59 11·6 2·11 50 1·89 0·69, 5·16
Medium 5·4c 0·18 10 0·55*** 0·39, 0·76 7·6 0·17 52 0·72* 0·52, 0·99 8·4a,c 0·18 29 0·63*** 0·49, 0·82 9·3 0·28 36 1·03 0·82, 1·29
High 7·0c 0·15 17 8·3 0·39 58 9·6b,c 0·31 39 9·3 0·17 36
Fresh meat and fish
Low 3·1 0·61 38 2·03* 1·02, 4·05 3·8 0·81 33 1·10 0·41, 2·90 4·0a,b 0·23 46 1·94*** 1·41, 2·66 3·0 0·44 31 0·65 0·22, 1·88
Medium 2·6c 0·12 34 1·60*** 1·29, 2·03 4·2 0·09 37 1·09 0·81, 1·48 3·0a,c 0·09 35 1·25 0·96, 1·62 2·8 0·15 35 0·75* 0·60, 0·94
High 2·0c 0·08 24 4·2 0·19 35 2·4b,c 0·12 29 2·8 0·06 42
Pasta, noodles and rice
Low 1·8 0·15 3 0·26 0·03, 1·99 3·0 0·51 27 0·64 0·24, 1·73 3·2 0·20 27 0·94 0·67, 1·32 3·5 0·48 6 0·57 0·07, 4·40
Medium 1·8c 0·05 5 0·62* 0·40, 0·97 2·8c 0·06 25 0·57*** 0·42, 0·78 2·9 0·07 30 0·99 0·76, 1·29 4·1 0·12 10 0·90 0·63, 1·29
High 2·1c 0·04 8 3·2c 0·14 37 2·9 0·09 30 4·2 0·06 11
Wholemeal bread
Low 1·6a,b 0·48 8 0·15* 0·05, 0·50 3·7 0·84 35 0·66 0·25, 1·76 4·6b 0·29 29 0·56*** 0·40, 0·76 4·9 1·22 25 0·81 0·26, 2·56
Medium 3·7a,c 0·18 24 0·53*** 0·42, 0·67 5·5 0·15 42 0·88 0·66, 1·18 5·2 0·15 37 0·79 0·62, 1·02 4·6 0·19 26 0·86 0·67, 1·10
High 5·4b,c 0·15 38 6·3 0·37 45 5·9b 0·27 43 4·8 0·12 29
Water
Low 9·7a,b 1·87 19 0·14*** 0·07, 0·29 21·3 2·36 59 1·18 0·43, 3·25 18·0 0·69 45 0·94 0·68, 1·31 21·1 2·81 56 1·28 0·40, 4·07
Medium 14·3a,c 0·45 24 0·46*** 0·37, 0·58 18·3 0·29 34 1·08 0·79, 1·48 18·5 0·37 44 1·00 0·77, 1·30 18·4c 0·46 34 1·22 0·96, 1·56
High 17·2b,c 0·30 25 17·8 0·71 35 17·9 0·60 38 16·6c 0·28 24
Plain unsweetened milk
Low 4·0b 0·58 5 0·16* 0·04, 0·67 13·2 1·97 50 1·29 0·53, 3·16 7·8 0·40 26 1·06 0·74, 1·50 14·7 2·16 38 3·20* 1·12, 9·10
Medium 5·3c 0·26 18 0·60*** 0·46, 0·78 10·7 0·22 43 0·98 0·74, 1·33 8·2 0·20 30 1·25 0·95, 1·65 11·4 0·37 21 1·27 0·96, 1·67
High 6·7b,c 0·20 27 10·2 0·51 43 7·6 0·30 25 10·6 0·22 17

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0·05, ***P < 0·001.

†p refers to the proportion of participants assigned to the highest consumption category.

Table 4b.

Weekly consumption frequency (means and their standard errors), prevalence of high consumption, and odds ratios (95 % confidence intervals) for intake of low-sugar and low-fat foods by classified parental education level and country; children (n 14 426) aged 2 to 9 years from eight European countries, baseline survey of IDEFICS study, September 2007 to May 2008

Cyprus Hungary Italy Spain
Food group/Parental education Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI Mean se p† OR 95 % CI
Vegetables (raw and cooked)
Low 8·7 1·85 21 0·39* 0·15, 0·96 8·2 0·76 33 1·02 0·57, 1·82 5·5 0·25 33 0·91 0·68, 1·22 7·4 0·74 32 1·07 0·70, 1·63
Medium 7·3 0·30 30 0·62*** 0·49, 0·78 7·9c 0·16 26 0·71*** 0·59, 0·85 5·5 0·15 33 0·92 0·72, 1·17 7·1 0·29 31 1·06 0·81, 1·39
High 8·1 0·23 41 9·0c 0·19 34 5·4 0·24 35 7·3 0·21 31
Fruits
Low 8·9 1·86 26 0·61 0·25, 1·47 5·7 0·81 15 0·71 0·32, 1·54 6·4 0·32 21 0·63* 0·46, 0·88 8·9 0·58 39 1·09 0·73, 1·65
Medium 9·0 0·33 33 0·85 0·67, 1·08 6·4 0·15 20 1·01 0·82, 1·24 6·9 0·16 26 0·84 0·65, 1·09 8·1 0·32 29 0·73 0·55, 0·95
High 9·5 0·24 37 6·7 0·15 20 7·4 0·30 29 9·0 0·23 36
Fresh meat and fish
Low 3·1 0·61 14 0·56 0·19, 1·63 3·8 0·52 33 1·07 0·60, 1·90 4·7 0·18 35 0·89 0·67, 1·19 3·9 0·29 29 0·88 0·57, 1·36
Medium 2·6c 0·12 24 1·10 0·85, 1·43 3·0c 0·09 31 0·98 0·82, 1·18 4·8 0·09 36 0·91 0·72, 1·15 4·4 0·17 31 1·03 0·78, 1·35
High 2·0c 0·08 23 2·7c 0·07 32 4·6 0·13 38 4·2 0·12 31
Pasta, noodles and rice
Low 3·8 1·27 30 1·20 0·51, 2·80 2·8b 0·32 20 2·70* 1·34, 5·45 3·5a,b 0·19 31 0·39*** 0·29, 0·52 3·0 0·18 29 0·93 0·60, 1·43
Medium 2·7 0·14 24 0·80 0·61, 1·04 2·4c 0·06 16 1·91*** 1·46, 2·49 4·3a,c 0·10 39 0·58*** 0·46, 0·73 2·9 0·08 30 0·89 0·68, 1.17
High 2·9 0·10 28 2·0b,c 0·04 9 5·6b,c 0·19 53 3·0 0·07 32
Wholemeal bread
Low 1·6a,b 0·48 53 1·87 0·75, 4·69 4·8a,b 0·98 44 1·82* 1·04, 3·19 2·1 0·21 31 0·87 0·64, 1·18 0·6 0·28 9 0·40* 0·21, 0·78
Medium 3·7a,c 0·18 31 0·78* 0·60, 0·99 3·2a 0·15 28 0·88 0·73, 1·06 1·8 0·11 31 0·91 0·71, 1·16 0·7 0·12 15 0·71* 0·51, 0·99
High 5·4b,c 0·15 37 3·1b 0·12 31 2·0 0·19 33 0·9 0·10 20
Water
Low 9·7a,b 1·87 64 0·51 0·23, 1·13 19·0 1·72 49 0·72 0·40, 1·28 23·4a,b 0·49 67 0·49*** 0·36, 0·68 27·2 0·64 84 1·07 0·63, 1·84
Medium 14·3a,c 0·45 75 0·84 0·64, 1·09 18·8c 0·33 44 0·65*** 0·54, 0·78 26·1a 0·22 78 0·83 0·63, 1·10 27·7 0·31 85 1·26 0·89, 1·77
High 17·2b,c 0·30 78 21·5c 0·33 52 26·9b 0·34 80 27·5 0·22 82
Plain unsweetened milk
Low 4·0b 0·58 23 1·66 0·64, 4·30 6·7 1·18 39 0·93 0·52, 1·65 3·8b 0·29 32 0·51*** 0·37, 0·68 4·3 0·67 32 1·02 0·68, 1·60
Medium 5·3c 0·26 19 1·16 0·86, 1·57 5·3 0·18 39 0·99 0·83, 1·18 4·6 0·17 41 0·75* 0·59, 0·95 4·9 0·36 37 1·22 0·93, 1·60
High 6·7b,c 0·20 17 4·9 0·17 39 5·2b 0·33 48 4·0 0·23 33

Reference group: high education.

Analysis of covariance model adjusted for gender, age and BMI category. Two-sided level of significance (P < 0·05): asignificant difference between low and medium; bsignificant difference between low and high; csignificant difference between medium and high.

OR and 95 % CI determined by logistic regression models. Variables included in the models were parental education, gender, age and BMI category. Two-sided level of significance: *P < 0·05, ***P < 0·001.

†p refers to the proportion of participants assigned to the highest consumption category.

In the Hungarian sample, consumption frequencies for the pasta/noodles/rice and wholemeal bread categories followed the opposite trend to that in the whole sample, i.e. higher means in the low parental education level group. Similarly, in the Belgian sample, consumption of chocolate/nut-based spread followed an inverse direction compared with the whole group, i.e. higher frequency in the Belgian high parental education level group.

The largest odds ratio differences for intake of each food item among education level groups were observed in Germany (fruits, fried meat and fish, fast food), Belgium (vegetables, fresh meat and fish, white bread, wholemeal bread, water, plain unsweetened milk), Sweden (fried potatoes, chocolate/nut-based spread), Hungary (white bread, snacks/desserts), Spain (fruits with sugar and nuts) and Italy (sugared beverages, pasta/noodles/rice). As an exception, Hungarian and Swedish participants in the low parental education group had higher odds of more frequently consuming pasta/noodles/rice, wholemeal bread (Hungarian) and plain unsweetened milk (Swedish).

Discussion

The present study addressed the relationship between parental education level and the consumption frequency of obesity-related foods in their children. Our findings confirm such an association for a number of the investigated food groups. The intakes of vegetables, fruits, pasta/noodles/rice, wholemeal bread and water increased as education level increased; while intakes of fried potatoes, fruits with sugar and nuts, fried meat and fish, fast food, sugared beverages, snacks/desserts and chocolate/nut-based spread increased as educational level decreased. These trends were observed for the total sample and for most of the participating countries. It is noteworthy to mention that the magnitude of educational differences varied across the selected countries and that some of the observed country-specific differences might reflect cultural food specificities. Country-specific cultural norms on what is considered to be ‘healthy eating’ and gastronomic heritage may have a major impact on education-related disparities in food habits( 25 ). For instance, pasta frequency of consumption in Italy was higher in the high parental education group, possibly reflecting the paramount importance of pasta in the traditional Italian gastronomy. The same applies to the case of chocolate in Belgium. Other examples, like bread consumption (e.g. wholemeal bread in the northern countries, white bread in the southern countries) and plain unsweetened milk (e.g. high consumption in Sweden and Estonia), seem also to be affected by traditional consumption.

Similarly to our findings, higher intakes of fruits and vegetables in children and adolescents with high SES have been reported in previous studies( 26 30 ). Some studies have observed that the impact of SES is particularly strong for healthy foods, such as vegetables and fruits( 31 ). These findings were reported in several countries with different cultural backgrounds, suggesting that fruit and vegetables are commonly considered as healthy. However, some other socio-economic differences in food intake have not been reported consistently (like for wholemeal bread, pasta, fish or fats), suggesting that these are more culturally dependent.

Previous studies have also focused on the socio-economic situation of parents, especially on maternal education, finding again positive associations between parental education and foods reducing the risk of obesity, like fruits and vegetables( 29 ). Education could provide an important socio-economic influence on health-related behaviour as it may increase the use of health-related information( 32 ). Although some other SES indicators, mainly occupational position and income, have been shown to have an impact on food intake( 33 37 ), parental education level, especially maternal education level, has been strongly related to children's dietary habits( 14 , 38 , 39 ) and to childhood overweight and obesity( 13 , 40 , 41 ).

An important strength of the present study is its large sample size and international multicentric nature, which allowed us to investigate the research question in different cultural settings with a wider variety of food consumption patterns. Another important strength of the study is the strict standardized procedures followed during the data collection of the IDEFICS fieldwork( 16 , 17 ) and the high quality control procedures carried out during the project, including plausibility checks implemented in the database and performed during data entry.

One of the major limitations of the study is the response rate. The whole survey programme involved complex logistics for participants and required the active involvement of parents, so that time constraints prevented some parents from participating. In addition, a selection bias cannot be ruled out as individuals without health problems or not having concerns about their children's health may be less motivated to take part in such a study. It is also known that participation is lower both in people with lower levels of education and in high-income groups( 42 ). As we have no systematic information about non-participants, the direction of a possible bias cannot be predicted.

A second limitation of the study design is the fact that the sample selected within the IDEFICS study was not necessarily representative for each specific country and the results obtained by the participating centres cannot be generalized to the whole countries.

Another limitation is related to the use of the frequency of consumption assessment tool, which is based on proxy reports. Proxy reporting might be strongly related to the number of meals under parental control. Subsequently, the accuracy of the consumption frequencies reported by parents could differ between countries, as the number of meals consumed at home did differ between the participating countries. Some previous studies suggest that over-reporting of foods reducing the risk of obesity mainly takes place among individuals with higher levels of education, due to their greater knowledge about healthy diet, and therefore might tend to overstate the actual consumption, the known social desirability bias( 33 , 43 ). Although FFQ are not designed to accurately capture intakes, results of food consumption frequencies derived from the food frequency section of the CEHQ-FFQ gave reproducible estimates of the consumption frequency in the IDEFICS children( 21 ).

Conclusions

The present study showed a strong association of parental education level with the frequency of consumption of high-fat, high-sugar foods and products increasing the risk of obesity. These findings suggest that children of parents with a low educational level may be at higher risk of unhealthy eating. Therefore, the socio-economic determinants of food choice within families need to be addressed. It should be noted that the amount of differences, and not only the size of differences, in relation to disease outcome is of interest, and should be addressed in future research. The results of the present study should lead to more accurate targeting of intervention programmes for healthy eating promotion in childhood, in order to overcome social health inequalities. Special focus should be driven to undereducated parents and their children, in order to minimize this social health burden.

Acknowledgements

The present analysis was conducted as part of the IDEFICS study (http://www.idefics.eu), undertaken with financial support of the European Community within the Sixth RTD Framework Programme Contract No. 016181 (FOOD) and grant support for the IDEFICS study from the European Union. There are no competing interests. The authors’ contributions were as follows: J.M.F.-A., statistical analysis and manuscript writing; T.M., statistical analysis and critical revision of the manuscript; K.B., study design, statistical analysis and critical revision of the manuscript; A.H., critical revision of the manuscript; G.B., critical revision of the manuscript; S.S., critical revision of the manuscript; L.R., critical revision of the manuscript; G.E., critical revision of the manuscript; C.H., critical revision of the manuscript; E.K., critical revision of the manuscript; I.H., statistical analysis and critical revision of the manuscript; L.A.M., study design, statistical analysis and critical revision of the manuscript. The authors are grateful for the support provided by school boards, headmasters and communities, and thank the IDEFICS children and their parents for participating in this extensive examination. The information in this document reflects the authors’ views and is provided as is. No guarantee or warranty is given that the information is fit for any particular purpose.

References

  • 1. Mackenbach JP, Stirbu I, Roskam AJ et al. (2008) Socioeconomic inequalities in health in 22 European countries. N Engl J Med 358, 2468–2481. [DOI] [PubMed] [Google Scholar]
  • 2. Mackenbach JP & Kunst AE (1997) Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med 44, 757–771. [DOI] [PubMed] [Google Scholar]
  • 3. Turrell G, Hewitt B, Patterson C et al. (2003) Measuring socio-economic position in dietary research: is choice of socio-economic indicator important? Public Health Nutr 6, 191–200. [DOI] [PubMed] [Google Scholar]
  • 4. Galobardes B, Lynch J & Smith GD (2007) Measuring socioeconomic position in health research. Br Med Bull 81–82, 21–37. [DOI] [PubMed] [Google Scholar]
  • 5. Darmon N & Drewnowski A (2008) Does social class predict diet quality? Am J Clin Nutr 87, 1 107–1117. [DOI] [PubMed] [Google Scholar]
  • 6. Sausenthaler S, Kompauer I, Mielck A et al. (2007) Impact of parental education and income inequality on children's food intake. Public Health Nutr 10, 24–33. [DOI] [PubMed] [Google Scholar]
  • 7. James WP, Nelson M, Ralph A et al. (1997) Socioeconomic determinants of health. The contribution of nutrition to inequalities in health. BMJ 314, 1545–1549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Huh J, Riggs NR, Spruijt-Metz D et al. (2011) Identifying patterns of eating and physical activity in children: a latent class analysis of obesity risk. Obesity (Silver Spring) 19, 652–658. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Cutler GJ, Flood A, Hannan P et al. (2011) Multiple sociodemographic and socioenvironmental characteristics are correlated with major patterns of dietary intake in adolescents. J Am Diet Assoc 111, 230–240. [DOI] [PubMed] [Google Scholar]
  • 10. Eloranta AM, Lindi V, Schwab U et al. (2011) Dietary factors and their associations with socioeconomic background in Finnish girls and boys 6–8 years of age: the PANIC Study. Eur J Cin Nutr 65, 1211–1218. [DOI] [PubMed] [Google Scholar]
  • 11. Vereecken CA, Keukelier E & Maes L (2004) Influence of mother's educational level on food parenting practices and food habits of young children. Appetite 43, 93–103. [DOI] [PubMed] [Google Scholar]
  • 12. Hebestreit A, Keimer K, Hassel H et al. (2010) What do children understand? Communicating health behavior in a European multicenter study. J Public Health 18, 391–401. [Google Scholar]
  • 13. Lamerz A, Kuepper-Nybelen J, Wehle C et al. (2005) Social class, parental education, and obesity prevalence in a study of six-year-old children in Germany. Int J Obes (Lond) 29, 373–380. [DOI] [PubMed] [Google Scholar]
  • 14. Cribb VL, Jones LR, Rogers IS et al. (2011) Is maternal education level associated with diet in 10-year-old children? Public Health Nutr 14, 2037–2048. [DOI] [PubMed] [Google Scholar]
  • 15. Cooke LJ, Wardle J, Gibson EL et al. (2004) Demographic, familial and trait predictors of fruit and vegetable consumption by pre-school children. Public Health Nutr 7, 295–302. [DOI] [PubMed] [Google Scholar]
  • 16. Ahrens W, Bammann K, Siani A et al. (2011) The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obes (Lond) 35, Suppl. 1, S3–S15. [DOI] [PubMed] [Google Scholar]
  • 17. Ahrens W, Bammann K, de Henauw S et al. (2006) Understanding and preventing childhood obesity and related disorders – IDEFICS: a European multilevel epidemiological approach. Nutr Metab Cardiovasc Dis 16, 302–308. [DOI] [PubMed] [Google Scholar]
  • 18. Bammann K, Peplies J, Pigeot I et al. (2007) IDEFICS: a multicenter European project on diet- and lifestyle-related disorders in children. Med Klin 102, 230–235. [DOI] [PubMed] [Google Scholar]
  • 19. United Nations Educational, Scientific and Cutural Organization (2010) ISCED: International Standard Classification for Education. http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx (accessed May 2011).
  • 20. Huybrechts I, Bornhorst C, Pala V et al. (2011) Evaluation of the Children's Eating Habits Questionnaire used in the IDEFICS study by relating urinary calcium and potassium to milk consumption frequencies among European children. Int J Obes (Lond) 35, Suppl. 1, S69–S78. [DOI] [PubMed] [Google Scholar]
  • 21. Lanfer A, Hebestreit A, Ahrens W et al. (2011) Reproducibility of food consumption frequencies derived from the Children's Eating Habits Questionnaire used in the IDEFICS study. Int J Obes (Lond) 35, Suppl. 1, S61–S68. [DOI] [PubMed] [Google Scholar]
  • 22. Stomfai S, Ahrens W, Bammann K et al. (2011) Intra- and inter-observer reliability in anthropometric measurements in children. Int J Obes (Lond) 35, Suppl. 1, S45–S51. [DOI] [PubMed] [Google Scholar]
  • 23. Cole TJ, Bellizzi MC, Flegal KM et al. (2000) Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320, 1240–1243. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Cole TJ, Flegal KM, Nicholls D et al. (2007) Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ 335, 194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Margetts BM, Martinez JA, Saba A et al. (1997) Definitions of ‘healthy’ eating: a pan-EU survey of consumer attitudes to food, nutrition and health. Eur J Clin Nutr 51, Suppl. 2, S23–S29. [PubMed] [Google Scholar]
  • 26. Abudayya AH, Stigum H, Shi Z et al. (2009) Sociodemographic correlates of food habits among school adolescents (12–15 year) in North Gaza Strip. BMC Public Health 9, 185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Sandvik C, Gjestad R, Samdal O et al. (2010) Does socio-economic status moderate the associations between psychosocial predictors and fruit intake in schoolchildren? The Pro Children study. Health Educ Res 25, 121–134. [DOI] [PubMed] [Google Scholar]
  • 28. Suliga E (2010) Parental education and living environmental influence on physical development, nutritional habits as well as level of physical activity in Polish children and adolescents. Anthropol Anz 68, 53–66. [DOI] [PubMed] [Google Scholar]
  • 29. Klocke A (1997) The impact of poverty on nutrition behaviour in young Europeans. In Poverty and Food in Welfare Societies, pp. 224–237 [B Kohler, E Feichtinger, E Barlosius et al., editors]. Berlin: WZB, Edition Sigma. [Google Scholar]
  • 30. Rasmussen M, Krolner R, Klepp KI et al. (2006) Determinants of fruit and vegetable consumption among children and adolescents: a review of the literature. Part I: Quantitative studies. Int J Behav Nutr Phys Act 3, 22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Blake CE, Wethington E, Farrell TJ et al. (2011) Behavioral contexts, food-choice coping strategies, and dietary quality of a multiethnic sample of employed parents. J Am Diet Assoc 111, 401–407. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Laitinen S, Rasanen L, Viikari J et al. (1995) Diet of Finnish children in relation to the family's socio-economic status. Scand J Soc Med 23, 88–94. [DOI] [PubMed] [Google Scholar]
  • 33. Irala-Estevez JD, Groth M, Johansson L et al. (2000) A systematic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables. Eur J Clin Nutr 54, 706–714. [DOI] [PubMed] [Google Scholar]
  • 34. Craig LC, McNeill G, Macdiarmid JI et al. (2010) Dietary patterns of school-age children in Scotland: association with socio-economic indicators, physical activity and obesity. Br J Nutr 103, 319–334. [DOI] [PubMed] [Google Scholar]
  • 35. Shavers VL (2007) Measurement of socioeconomic status in health disparities research. J Natl Med Assoc 99, 1 013–1023. [PMC free article] [PubMed] [Google Scholar]
  • 36. Braveman PA, Cubbin C, Egerter S et al. (2005) Socioeconomic status in health research: one size does not fit all. JAMA 294, 2879–2888. [DOI] [PubMed] [Google Scholar]
  • 37. Wagstaff A & Watanabe N (2003) What difference does the choice of SES make in health inequality measurement? Health Econ 12, 885–890. [DOI] [PubMed] [Google Scholar]
  • 38. Nilsen SM, Krokstad S, Holmen TL et al. (2010) Adolescents’ health-related dietary patterns by parental socio-economic position, the Nord-Trondelag Health Study (HUNT). Eur J Public Health 20, 299–305. [DOI] [PubMed] [Google Scholar]
  • 39. Ebenegger V, Marques-Vidal PM, Nydegger A et al. (2011) Independent contribution of parental migrant status and educational level to adiposity and eating habits in preschool children. Eur J Clin Nutr 65, 210–218. [DOI] [PubMed] [Google Scholar]
  • 40. Ruijsbroek A, Wijga AH, Kerkhof M et al. (2011) The development of socio-economic health differences in childhood: results of the Dutch longitudinal PIAMA birth cohort. BMC Public Health 11, 225. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Moschonis G, Tanagra S, Vandorou A et al. (2010) Social, economic and demographic correlates of overweight and obesity in primary-school children: preliminary data from the Healthy Growth Study. Public Health Nutr 13, 1693–1700. [DOI] [PubMed] [Google Scholar]
  • 42. Groves R (2006) Nonresponse rates and nonresponse bias in household surveys. Public Opin Q 70, 646–675. [Google Scholar]
  • 43. Hulshof KF, Brussaard JH, Kruizinga AG et al. (2003) Socio-economic status, dietary intake and 10 y trends: the Dutch National Food Consumption Survey. Eur J Clin Nutr 57, 1 28–137. [DOI] [PubMed] [Google Scholar]

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