Skip to main content
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2014 Mar 13.
Published in final edited form as: Public Health Nutr. 2010 Sep 15;14(4):678–687. doi: 10.1017/S1368980010002570

Socio-economic circumstances and food habits in Eastern, Central and Western European populations

Sinéad Boylan 1, Tea Lallukka 2, Eero Lahelma 2, Hynek Pikhart 1, Sofia Malyutina 3, Andrzej Pajak 4, Ruzena Kubinova 5, Oksana Bragina 3, Urszula Stepaniak 4, Aleksandra Gillis-Januszewska 4, Galina Simonova 3, Anne Peasey 1, Martin Bobak 1,*
PMCID: PMC3951866  EMSID: EMS57283  PMID: 20843403

Abstract

Objective

To assess the relationship between several socio-economic indicators and frequency of consumption of seven predefined healthy foods (consumption of fruit, vegetables, wholegrain bread, vegetable-fat spread, vegetable cooking fat, low-fat milk and low-fat cheese) in populations from Eastern, Central and Western Europe.

Design

Analysis of baseline data collected in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS).

Setting

Urban populations in the Czech Republic, Russia, Poland and Finland.

Subjects

In the HAPIEE study, random samples of men and women aged 45–69 years were drawn from population registers and electoral lists of selected cities. In the HHS, men and women aged 40–60 years employed by the City of Helsinki were recruited. Data on 21 326 working subjects from both cohorts were analysed.

Results

Healthy food habits were, in general, positively associated with higher education, occupational position and fewer economic difficulties, but there were differences in the strength of the gradient by food and country. Fruit consumption showed the most consistent gradients, especially in relation to socio-economic status among men (country-specific relative index of inequality (RII) = 2·02–5·17) and women (RII = 2·09–3·57).

Conclusions

The associations between socio-economic indicators and healthy food habits showed heterogeneity between countries. Future studies of dietary behaviours should consider multiple measures of socio-economic position.

Keywords: Nutrition, Diet, Socio-economic, Eastern Europe, International


Socio-economic inequalities in health and health behaviours are evident throughout Europe, particularly so in Eastern European and Baltic countries(1). In Western and Baltic countries, those in higher socio-economic positions have healthier behaviours(24). However, only a few studies have tested the association between socio-economic circumstances and food habits in Eastern European and Baltic countries, with education level being positively associated with both vegetable and cheese consumption(5,6). In addition, most studies have examined the association with food habits using only one or a few socio-economic indicators(7,8). Focusing on only a single domain of socio-economic position provides a limited approach to a multidimensional concept covering many educational, occupational, financial and material circumstances(9) and may lead to overestimation or underestimation of effects(10).

Studies that have adopted a more multidimensional approach have a tendency to use education, occupation and income as key socio-economic indicators. While these three indicators are correlated, they are not directly interchangeable as each may have a unique effect on health(1114). The current study employs similar socio-economic indicators as each has previously been shown to be associated with food habits(3,6,15). Education, often the most consistent indicator, is acquired early in life and may influence how a person understands health-related information and generates long-term beneficial behaviours(16,17). Occupation may determine income and therefore access to healthy food; also, because occupation creates a social network, it can influence health behaviours(16). Current economic difficulty is a third important indicator as lack of money can exist across all income levels and may lead to a reliance on a low-cost, energy-rich diet(1820). The present study investigates the relationship between these indicators and food habits in populations from Eastern, Central and Western Europe – the Czech Republic, Poland, Russia and Finland. These countries represent distinct economic, education and employment structures, and different socio-economic indicators may have different meanings in Central and Eastern Europe compared with the West(21).

However, these indicators may also have different influences in these socially and culturally distinct countries. In addition, food habits may differ between countries due to varying traditions and food access(22). It is important therefore to assess multiple food habits, as the association between socio-economic circumstances and other foods may be overlooked. Despite this, many studies have simply assessed the association between one socio-economic indicator and consumption of one or two foods, particularly fruit and vegetables(5,6,15,23).

The aims of the current study were therefore to assess: (i) the uptake of several predefined healthy food habits in four distinct populations; (ii) the proportion of those with a predefined healthy food habit score; and (iii) the relationship between different socio-economic indicators (education, occupation and current economic difficulty) and these food habits.

Materials and methods

Study populations

The present analyses used data from two cross-sectional cohort studies: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study(24) and the Finnish Helsinki Health Study (HHS)(25). Both cohorts are designed to investigate the relationship between health behaviours and health outcomes. Both studies have published methods elsewhere; therefore only a brief outline is given below(3,2426).

The HAPIEE study examined random samples of men and women aged 45–69 years at baseline in Novosibirsk (Russia), Krakow (Poland) and six Czech urban centres in 2002–2005(24). The 28 947 participants (53% female, overall response rate 59%) were recruited from population registers in Poland and the Czech Republic, and from electoral lists in Russia. The baseline survey involved completion of structured questionnaires and a medical examination in a clinic. In Russia and Poland, questionnaires were administered by a nutritionist and nurse, respectively; however, in the Czech Republic, the participants self-completed questionnaires at home. The questionnaires covered health, medical history, socio-economic circumstances, psychosocial factors and health behaviours including food habits. Data on working participants were used for the current analyses (n 13 417).

The Finnish data came from the HHS baseline survey in 2000–2002. A total of 8960 men and women aged 40–60 years employed by the City of Helsinki (80% female, overall response rate 67 %) were recruited. Data were collected using self-administered questionnaires which assessed health, medical history, socio-economic circumstances and health behaviours, including food habits. Data on occupational class were derived from the City of Helsinki personnel register for those with written consent for this linkage (80 %). For the remaining participants, information on occupational class was completed from the questionnaires.

Food habits

In the HAPIEE study, food habits were assessed using an FFQ based on the Whitehall II Study FFQ(27) which in turn was adapted from the original instrument developed by Willett(28). The Czech, Russian and Polish FFQ consisted of 136, 147 and 148 food and drink items, respectively; the different numbers of questions are due to country-specific dishes. A country-specific portion size for each food was specified, and participants were asked how often, on average, they had consumed that amount of the item during the last three months, with nine responses ranging from ‘never or less than once per month’ to ‘six or more times per day’. Dietary information was available for 13 417 working participants.

The HSS assessment of food habits consisted of a questionnaire querying twenty-two food and drink items; participants were asked how often they consumed these foods and drinks, on average, in the last month, with seven responses ranging from ‘not at all’ to ‘at least twice per day’(3). The HHS did not assess portion sizes. Dietary data were available on 8960 participants in the HHS.

Healthy food habit score

Similar food groups, measured similarly in both cohorts, were identified, and seven healthy food habits were created based on the frequency of consumption, as recommended by WHO dietary guidelines(29): fresh fruit at least twice daily; fresh vegetables at least twice daily; wholegrain bread rather than white bread; skimmed or semi-skimmed milk (low fat) rather than whole milk; vegetable-fat spreads rather than animal-fat spreads; vegetable cooking fats rather than lard or butter; and low-fat cheese rather than high-fat cheese. For example, consumption of white bread only, or a combined consumption of white and wholegrain bread, was not considered as a healthy food habit. Also, for participants who did not report consuming any bread, milk, cheese, spreads or cooking fat such habit was classified as unhealthy because consumption of these foods is recommended in current dietary guidelines(29). The rationale for inclusion was that these foods were included in both studies and in the WHO guidelines.

Participants received one point for meeting each recommended food habit and summation of these points resulted in a healthy food habit score (range 0 to 7), i.e. high scores indicated healthier food habits. The score was arbitrarily dichotomised with participants classified as having healthy food habits if they met at least four of the recommendations (score ≥4). A similar index has been used in previous studies(3,30).

Socio-economic circumstances

The methodological differences and differing education systems, occupational structures and economic situations between these communities limit the comparability of results, but construction of hierarchical classes allows us to examine socio-economic patterning of food habits within communities. In both cohorts, education was divided into three hierarchical categories – basic (incomplete, primary, vocational in HAPIEE cohort; primary, secondary, vocational in HHS cohort), intermediate (secondary in HAPIEE; matriculation in HHS cohort) and higher (university). Occupational class was hierarchically categorised as manual worker, other non-manual worker, semi-professional, professional and managerial. Current economic difficulties were measured in the HAPIEE study using three questions related to the participant’s problems buying food, buying clothes and paying bills; and in the HHS using two questions: problems buying food or clothes and problems paying bills. For these questions, response alternatives indicating the level of difficulties were scored and an overall score was constructed. This was then divided into four categories of economic difficulty: frequently; occasionally; rarely; and never.

Statistical analysis

Of the 22 377 working participants who completed the questionnaire in both cohorts, 21 326 had no more than two of the seven food habits missing (97% of these participants had no missing food habits) and had valid data (non-missing) on education, occupational class and economic difficulties. The analyses were carried out separately for men and women in each cohort using the STATA statistical software package version 10·1 (StataCorp, College Station, TX, USA).

Using logistic regression, the association between each recommended food habit and socio-economic indicator was examined. Subsequently, the association between each socio-economic indicator and healthy food habit score (score ≥4) was examined. Each logistic regression model included one socio-economic indicator and was adjusted for age only.

The association between socio-economic indicators and food habits was examined using a summary index, the relative index of inequality (RII), for each cohort(31). RII is a total effect measure, as it considers both the strength of the differences between the social classes and the distribution of the population across the classes. Before the RII could be calculated, each category of our three socio-economic indicators was represented by a country-specific cumulative midpoint centile. The RII for healthy food habits was then calculated based on a continuous logistic regression coefficient for each socio-economic indicator adjusted for age and compared those at the bottom of the hierarchy with those at the top of the hierarchy (i.e. RII values above 1·00 suggest that those in higher socio-economic positions have healthier food habits)(31). As interpretation of the RII assumes linearity of the association between socio-economic indicators and healthy food habits, departures from linearity were tested for, but were not found.

Results

Socio-economic circumstances

The proportion of non-manual workers and those with high education differed between cohorts and the sexes (Table 1). Economic difficulty was reported more frequently among females; particularly so among the Russian sample.

Table 1.

Distribution of socio-economic circumstances by sex and country; data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS)

Males
Females
Czech
Republic
(n 1947)
Russia
(n 2559)
Poland
(n 2194)
Finland
(n 1729)
Czech
Republic
(n 1846)
Russia
(n 2330)
Poland
(n 1856)
Finland
(n 6865)
n % n % n % n % n % n % n % n %
Education
 Basic 851 44 739 29 560 26 694 40 674 36 861 37 286 15 2918 42
 Intermediate 645 33 890 35 683 31 476 28 898 49 679 29 764 41 2249 33
 High 451 23 930 36 951 43 559 32 274 15 790 34 806 44 1698 25
Occupational class
 Manual workers 509 26 977 38 370 17 472 27 325 18 449 19 212 11 810 12
 Other non-manual workers 408 21 459 18 412 19 175 10 878 48 867 37 585 32 2896 42
 Semi-professionals 329 17 123 5 298 13 336 20 188 10 107 5 177 9 1284 19
 Professionals 526 27 744 29 801 37 453 26 394 21 781 34 755 41 1432 21
 Managers 175 9 256 10 313 14 293 17 61 3 126 5 127 7 443 6
Economic difficulties
 Frequently 58 3 294 12 129 6 67 4 99 6 485 21 168 9 341 5
 Occasionally 215 11 447 17 297 13 275 16 227 12 609 26 329 18 985 14
 Rarely 560 29 669 26 494 23 486 28 648 35 653 28 463 25 2031 14
 Never 1114 57 1149 45 1274 58 901 52 872 47 583 25 896 48 3508 51

Recommended food habits

Compared with the males, a much higher proportion of females met the dietary recommendations for fruit and wholegrain bread consumption, and, in the Finnish sample, vegetable consumption (Table 2). Still, apart from the Finnish sample, few participants reported the consumption of wholegrain bread rather than white, or the use of vegetable-fat spreads. On the contrary, the use of vegetable cooking fats was reported by the majority of participants (overall 78 %). Fewer (8 %) reported consumption of low-fat rather than high-fat cheese; therefore these results are not presented in Table 2. Low-fat milk was less commonly consumed in Russia than in other countries.

Table 2.

Age-standardised proportion of participants following each dietary recommendation by sex and country; data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS)

Males
Females
Czech Republic
Russia
Poland
Finland
Czech Republic
Russia
Poland
Finland
% 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI
Dietary recommendation*
 Fruit ≥2/d 47 45, 48 19 18, 21 48 46, 50 8 7, 10 64 63, 66 30 28, 32 60 58, 61 25 24, 26
 Vegetables ≥2/d 57 56, 59 79 78, 80 67 65, 68 19 17, 21 65 64, 67 79 78, 80 68 66, 69 38 37, 39
 Wholegrain bread 4 3, 5 6 5, 7 5 4, 6 36 34, 38 7 6, 8 11 9, 12 10 9, 11 53 52, 54
 Low-fat milk 52 50, 54 19 18, 21 45 43, 46 46 44, 48 52 51, 54 21 20, 23 49 47, 51 49 48, 50
 Vegetable-fat spread§ 13 12, 14 3 2, 4 12 11, 13 57 55, 60 20 18, 21 4 3, 4 11 9, 12 55 54, 56
 Vegetable cooking fat 74 73, 75 80 80, 81 76 75, 77 70 68, 72 75 74, 76 82 82, 83 78 77, 79 67 66, 68
*

Results for low-fat cheese are presented in main text.

Compared with no wholegrain bread, no bread, white, or a combination of white and wholegrain bread.

Compared with no low-fat milk, no milk, whole milk, or a combination of low-fat and whole milk.

§

Compared with no vegetable-fat spread, no spread, butter, butter–vegetable spreads, or a combination of spreads.

Compared with no vegetable cooking fat, no cooking fat, butter, lard, or a combination of cooking fats.

Healthy food habit scores

Figures 1 and 2 present the distribution of the healthy food habit scores by country and sex. Mean healthy food habit scores in ascending order were: 2·5 (sd 0.8) for Russian males; 2·7 (sd 0·8) for Russian females; 2·7 (sd 1·2) for Finnish males; 3·0 (sd 1·1) for Czech males; 3·1 (sd 1·1) for Polish males; 3·3 (sd 1·0) for Polish females; 3·4 (sd 1·4) for Finnish females; and 3·4 (sd 1·0) for Czech females. The highest proportion with healthy food habits (score ≥4) existed among the Czech (52 %), Polish (46 %) and Finnish females (45 %). Fewer males (Czech and Polish 36 %, Finnish 27 %, Russian 10 %) and Russian females (19 %) were defined as having healthy food habits.

Fig. 1.

Fig. 1

Distribution of healthy food habit score among males by country (Inline graphic, Czech Republic; Inline graphic, Russia; Inline graphic, Poland; Inline graphic, Finland); data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS). Vertical line denotes cut-off for healthy food habits, i.e. score ≥4

Fig. 2.

Fig. 2

Distribution of healthy food habit score among females by country (Inline graphic, Czech Republic; Inline graphic, Russia; Inline graphic, Poland; Inline graphic, Finland); data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS). Vertical line denotes cut-off for healthy food habits, i.e. score ≥4

Socio-economic circumstances and recommended food habits

Fruit and vegetables

After adjusting for age, men and women with high educational qualifications, high occupational class and no economic difficulties were significantly more likely to consume fruit at least twice daily than those with basic education, low occupational class and frequent economic difficulties (Tables 3 and 4). Among Finnish participants, similar gradients were seen for vegetable consumption.

Table 3.

Socio-economic circumstances and food habits among males by country; data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS)

Czech Republic
Russia
Poland
Finland
Model* RII 95% CI RII 95% CI RII 95% CI RII 95% CI
Fruit
 Education 1·83 1·19, 2·79 3·16 2·08, 4·81 1·31 0·89, 1·93 1·20 0·73, 1·96
 Occupation 1·40 1·07, 1·83 2·94 2·29, 3·78 1·34 1·04, 1·73 1·04 0·66, 1·64
 Economics 2·16 1·26, 3·70 5·17 3·31, 8·07 2·09 1·38, 3·17 2·02 0·81, 5·05
Vegetables
 Education 0·75 0·48, 1·19 0·80 0·36, 1·78 0·66 0·41, 1·07 2·20 1·52, 3·18
 Occupation 1·10 0·82, 1·47 1·02 0·61, 1·68 0·98 0·71, 1·35 2·19 1·57, 3·05
 Economics 1·00 0·56, 1·79 1·67 0·83, 3·35 1·69 1·03, 2·77 2·20 1·15, 4·17
Wholegrain bread
 Education 0·22 0·08, 0·62 2·88 1·45, 5·71 6·50 2·63, 16·07 0·83 0·62, 1·10
 Occupation 0·78 0·42, 1·48 1·41 0·95, 2·12 2·77 1·59, 4·84 0·92 0·70, 1·19
 Economics 1·45 0·38, 5·65 1·29 0·69, 2·41 5·76 1·87, 17·67 1·68 1·02, 2·77
Low-fat milk
 Education 1·16 0·75, 1·79 1·09 0·74, 1·62 0·71 0·48, 1·05 1·80 1·36, 2·38
 Occupation 0·86 0·66, 1·13 1·16 0·90, 1·49 0·85 0·66, 1·09 1·84 1·41, 2·39
 Economics 0·86 0·49, 1·50 0·96 0·66, 1·39 0·71 0·47, 1·08 2·27 1·40, 3·69
Vegetable-fat spread
 Education 1·60 0·90, 2·84 0·82 0·36, 1·89 0·27 0·16, 0·46 0·69 0·52, 0·93
 Occupation 1·27 0·88, 1·83 0·78 0·45, 1·35 0·52 0·37, 0·75 0·88 0·67, 1·15
 Economics 1·71 0·78, 3·72 0·92 0·41, 2·04 0·86 0·49, 1·53 0·76 0·46, 1·25
Vegetable cooking fat
 Education 1·09 0·56, 2·12 3·69 1·66, 8·19 1·52 0·79, 2·93 2·31 1·66, 3·19
 Occupation 0·97 0·64, 1·48 3·48 1·83, 6·58 1·20 0·77, 1·88 2·13 1·55, 2·92
 Economics 0·66 0·27, 1·62 2·52 1·21, 5·26 1·42 0·70, 2·86 0·97 0·54, 1·74
Healthy food habits
 Education 1·27 0·82, 1·97 2·81 1·56, 5·07 0·73 0·49, 1·08 1·32 0·96, 1·81
 Occupation 1·10 0·84, 1·46 1·77 1·25, 2·51 0·91 0·69, 1·18 1·43 1·06, 1·92
 Economics 1·97 1·10, 3·53 3·02 1·65, 5·53 1·50 0·94, 2·28 1·96 1·11, 3·46

RII, relative index of inequality.

*

Models include each socio-economic indicator independently along with age.

Healthy food habit score ≥4.

Table 4.

Socio-economic circumstances and food habits among females by country; data from participants in two cross-sectional cohort studies between 2000 and 2005: the Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study and the Finnish Helsinki Health Study (HHS)

Czech Republic
Russia
Poland
Finland
Model* RII 95% CI RII 95% CI RII 95% CI RII 95% CI
Fruit
 Education 2·05 1·22, 3·45 2·05 1·41, 2·98 0·95 0·58, 1·55 1·72 1·44, 2·05
 Occupation 1·81 1·20, 2·71 2·46 1·88, 3·23 1·21 0·86, 1·69 1·74 1·44, 2·11
 Economics 2·56 1·50, 4·38 3·57 2·56, 4·99 2·26 1·48, 3·46 2·09 1·57, 2·79
Vegetables
 Education 2·05 1·21, 3·48 1·82 0·76, 4·37 1·14 0·65, 2·02 1·87 1·60, 2·18
 Occupation 1·39 0·92, 2·09 1·12 0·60, 2·10 0·97 0·65, 1·43 1·86 1·57, 2·21
 Economics 1·41 0·80, 2·49 1·76 0·86, 3·58 1·38 0·83, 2·28 1·88 1·47, 2·39
Wholegrain bread
 Education 1·39 0·61, 3·18 1·48 0·86, 2·52 1·73 0·84, 3·55 1·10 0·95, 1·28
 Occupation 1·34 0·73, 2·44 1·59 1·08, 2·33 1·13 0·70, 1·82 1·21 1·02, 1·44
 Economics 1·02 0·41, 2·55 1·09 0·69, 1·71 2·97 1·45, 6·10 1·73 1·37, 2·18
Low-fat milk
 Education 1·07 0·68, 1·69 0·94 0·63, 1·41 0·51 0·33, 0·81 1·94 1·67, 2·26
 Occupation 1·03 0·74, 1·46 0·77 0·57, 1·03 0·57 0·41, 0·78 2·02 1·70, 2·41
 Economics 0·88 0·53, 1·46 0·68 0·48, 0·96 0·79 0·53, 1·19 1·62 1·28, 2·05
Vegetable-fat spread
 Education 1·63 0·96, 2·75 1·09 0·46, 2·56 0·16 0·09, 0·29 0·60 0·52, 0·71
 Occupation 1·37 0·93, 2·02 0·72 0·39, 1·35 0·23 0·14, 0·37 0·54 0·45, 0·64
 Economics 1·90 1·04, 3·47 0·69 0·34, 1·42 0·83 0·47, 1·48 0·76 0·60, 0·97
Vegetable cooking fat
 Education 2·01 0·95, 4·25 0·87 0·14, 5·50 0·65 0·25, 1·66 2·32 1·95, 2·75
 Occupation 1·33 0·74, 2·34 3·99 0·91, 17·43 0·92 0·49, 1·72 2·29 1·86, 2·81
 Economics 0·86 0·37, 2·03 1·52 0·33, 6·91 0·93 0·41, 2·11 1·38 1·05, 1·81
Healthy food habits
 Education 2·56 1·64, 4·01 1·12 0·71, 1·77 0·51 0·32, 0·79 1·76 1·5, 2·0
 Occupation 1·68 1·20, 2·35 1·43 1·02, 1·98 0·59 0·43, 0·80 1·81 1·52, 2·14
 Economics 1·70 1·04, 2·76 1·52 1·02, 2·26 1·43 0·96, 2·13 2·07 1·63, 2·63

RII, relative index of inequality.

*

Models include each socio-economic indicator independently along with age.

Healthy food habit score ≥4.

Wholegrain bread

As for consumption of wholegrain bread, participants with high educational qualifications, high occupational class and without economic difficulty were generally more likely to consume wholegrain bread compared with those at the opposite ends of the scales – these associations were particularly strong for Polish males. On the contrary, Czech and Finnish males with high education or occupational class were less likely to consume wholegrain bread than those with lower education or occupational class.

Low-fat milk

Finnish participants with high education, high occupational class and no economic difficulty were significantly more likely to consume low-fat milk than Finnish participants with basic education, low occupational class and frequent economic difficulties. Regarding education and occupational class in the Polish female sample, these gradients lay in the opposite direction.

Vegetable-fat spreads, cooking fats and low-fat cheese

Finnish participants with high education were significantly less likely to use vegetable-fat spreads than those with basic education; similar gradients were evident for occupational class and economic difficulty among Finnish females. Similarly, Polish participants with high education and high occupational class were significantly less likely to use vegetable-fat spreads compared with those in lower classes. On the contrary, Czech females without economic difficulty were almost twice as likely to use a vegetable-fat spread as those who reported frequent economic difficulty. A strong association between socio-economic circumstances and use of vegetable cooking fats was evident among Russian males and the Finnish cohort – those with high education, high occupational class and no economic difficulty (except Finnish males) were more likely to use recommended cooking fats than those in lower levels and those with frequent economic difficulties. As very few participants reported consuming low-fat cheese, the results are not presented in Tables 3 and 4.

Healthy food habit score

In terms of the healthy food habit score shown in the last rows of Tables 3 and 4, the associations with socio-economic circumstances were similar among females and males. Healthy food habits were strongly related to economic difficulty among Czech males, while being associated with all three socio-economic indicators among Czech females. Stronger associations were evident among Russian males compared with females, with economic difficulty having the strongest effect. The associations among the Polish cohort were less consistent, with no consistent associations seen among Polish males and inverse associations with education and occupation among Polish females. Stronger gradients were evident among Finnish females compared with males, but once again, economic difficulty had the strongest association with healthy food habits among both sexes.

Discussion

Main findings

The present study examined socio-economic differences in seven healthy food habits in Eastern, Central and Western European populations. We found that most socio-economic gradients were positive, i.e. higher socio-economic groups had healthier food habits, but the strength of the gradients varied between countries, and it was in the opposite direction among the Polish sample. From the three socio-economic indicators, economic difficulties showed the most consistent associations with food habits.

Limitations

When interpreting the results, a number of limitations should be considered. First, it is important to bear in mind that the aim of the current study was not to directly compare countries, but rather to test the multidimensional socio-economic framework for food habits in four national contexts from Eastern, Central and Western Europe. The study populations may have differing ideas as to what constitutes a healthy diet or have been exposed to different healthy eating campaigns. For example, while food-based guidelines exist in the Czech Republic, Poland and Finland, only nutrient guidelines are present in Russia, which may explain why only a small number of the Russian sample reported healthy food habits.

Second, the main methodological limitation of the study is the method of dietary assessment. HHS only assessed usual intake of twenty-two food and drink items in the preceding month and did not assess portion size. As the HAPIEE FFQ had more items, the prevalence of consumption may appear to be higher among the HAPIEE cohort compared with the HHS cohort. Although the HAPIEE study used a lengthier FFQ and assessed diet over a longer period of time, the FFQ is not without its faults and can underestimate or overestimate dietary intakes(27,32). As energy intake could not be calculated for the HHS cohort, the current results could not be adjusted for energy intake. Despite these caveats, proxy measures using selected indicators of food habits indicate adherence to general dietary guidelines and are therefore useful in large studies of healthy food habits(33). Also, although consumption frequencies do not directly translate into quantities, frequencies can give a reasonable indication of actual intake and food habits in general(33).

Third, differences in reporting may lead to biased estimations of intakes. In Russia and Poland, FFQ were completed under supervision; while in the Czech Republic and Finland, the questionnaires were completed un-supervised. Indeed results from previous HAPIEE analyses indicate that the Russian and Polish samples had higher energy intakes compared with the Czech sample which may reflect differences in FFQ data collection(34). However, this should not affect the validity of within-country analyses, unless socio-economic status is associated with over-reporting of healthy foods among persons with high education similarly in all countries(35).

Fourth, the cohorts may not be entirely representative since non-response is often associated with health status and health behaviours. It is possible that our results show a more favourable picture than if truly representative samples were examined. However, results from the HHS non-response analyses suggest that health inequalities are unlikely to be biased even though the HHS was conducted only among middle-aged employees of the City of Helsinki(36). Also, since only working subjects were included from the HAPIEE cohort, results may not apply to younger or non-working people in this cohort and may not be representative of each country’s respective populations. Similarly, since all centres in the present study were urban, we were not able to examine nationally representative samples. In Finland, clear regional differences in food habits have been found(37). Although the levels of and trends in mortality and health behaviours in HAPIEE study centres are similar to national figures, generalisations to the whole population are not warranted.

Consistencies with previous literature

It is well recognised that the consumption of a diet rich in fruit, vegetables and whole grains is beneficial to health(3840) while a low intake of dairy products is associated with diseases such as osteoporosis(41) and hypertension(42). Low-fat dairy products are recommended based on evidence that high intakes of fat increase the risk of CVD(43). Many of the results were expected: the strong association between fruit consumption and better socio-economic circumstances, females with healthier food habits than males, and the sex differences in the associations between socio-economic circumstances and food habits(15,44,45).

Of all the food habits, fruit consumption had the most consistent association with socio-economic circumstances. A review of socio-economic differences in food habits in seven European countries, including Finland, found that those with higher education and occupational class had a higher intake of fruit than those in lower classes(15). In the current study, the strongest positive association between fruit consumption and socio-economic position was found in the Russian sample. This observation may arise from the fact that in Novosibirsk, due to its location, fresh fruit is less accessible and hence less affordable, making cost a significant determinant in fruit consumption.

Socio-economic inequalities in vegetable consumption were not apparent in the HAPIEE cohort, while strong positive associations between vegetable consumption and socio-economic circumstances were evident among the Finnish sample, as previously reported(6,26,4648). A positive association between vegetable consumption and occupation has also been reported in Europe(15), and in previous HHS analyses(3). Recently, it has been suggested that the positive association seen between vegetable consumption and education is most evident in countries with low availability and high prices, such as in Nordic and Baltic countries, compared with countries having higher availability and affordability(6). However this explanation is inconsistent with the weak gradients in the HAPIEE cohort and may be due to the popularity of home-grown vegetable production in the HAPIEE countries.

Studies on socio-economic circumstances and consumption of bread are few and inconsistent. In Finland, the consumption of rye bread was associated with a low educational level(49), while in Poland no significant difference in ‘dark’ bread consumption was found between those of lower and higher education(50).

Consumption of high-fat milk has been previously linked with low education in Finland and the Baltic countries(7). This pattern was confirmed in our Finnish sample where those of higher socio-economic position were significantly associated with consumption of low-fat milk compared with those in lower positions. In the Polish sample, however, the associations with low-fat milk consumption were significantly negative. There was also a negative association between high-fat milk and socio-economic circumstances among the Polish sample (results not shown), suggesting that the higher classes in our Polish sample may perceive low-fat milk as an unhealthy rather than healthy food item.

Similar to milk consumption, the only significant associations between the use of vegetable-fat spreads and socio-economic circumstances were found among the Polish and Finnish samples – those with higher socio-economic position were less likely to use vegetable-fat spreads than those with lower socio-economic position. It has been suggested that food costs have a stronger influence on food choice among people with basic education compared with those with a higher education(51). Compared with butter, these vegetable-fat spreads are generally cheaper to purchase in all countries studied, so it is unclear as to why we observed inverse gradients in only the Polish and Finnish samples. Although the results in our Finnish sample differ from previous reports(7), a previous Polish study found that use of butter increased with educational level and material situation (A Nastaly, M Porebski, K Przevozniak et al., unpublished results) and similar inverse gradients have been reported in other Baltic populations(7).

The significant positive socio-economic gradient in Finnish participants and Russian males in the use of vegetable cooking fats may be due to campaigns to promote the consumption of vegetable oils in these countries. Similar findings were found in previous HHS analyses(3). In Eastern and Central Europe, there are few studies assessing the association between use of cooking fat and socio-economic position; one Polish study found that men with a high school education were more likely to use vegetable cooking fat than lower or higher educated men(52).

There were differences in low-fat cheese consumption by education level in Czech males and Russian females. Cost may influence choice of cheese, whereby lower educated persons are more likely to purchase the cheaper low-fat cheese. An opposite trend was evident among the Polish males (among occupation) and Finnish females (among economic difficulty). It is unclear whether these participants have chosen these lower-fat versions for health reasons or because they perceive them as ‘modern’ foods. It has been reported that people of higher socio-economic position tend to choose ‘modern’ foods while people of lower socio-economic position choose more traditional foods(53,54).

What the present study adds

The present large-scale study offers insights into inequalities in food habits by several indicators of socio-economic position in four distinct populations. The ability to assess several multiple indicators, along with multiple food habits, contributes to a better understanding of the influence which socio-economic inequalities may have on dietary behaviour. The WHO Commission on Social Determinants of Health aims to ‘close the gap’ in health inequalities between different groups in the course of a generation(55). However in order to do so, the extent to which the inequalities are modifiable must be clearly evident. The current study, which focused on healthy food habits, implies that this task may not be straightforward. Different populations showed different strength, or even different direction, of gradients measured by different dimensions of socio-economic position. Future studies of inequalities in dietary behaviour should therefore include different indicators and consider the relative importance of each socio-economic indicator.

Acknowledgements

The HAPIEE study was funded by a grant from the Wellcome Trust ‘Determinants of Cardiovascular Diseases in Eastern Europe: A multi-centre cohort study’ (reference no. 064947/Z/01/Z); a grant from the National Institute on Aging ‘Health disparities and aging in societies in transition (the HAPIEE study)’ (grant no. 1R01 AG23522-01); and a grant from the MacArthur Foundation ‘Health and Social Upheaval (a research network)’. The HHS was supported by the Academy of Finland and the Finnish Work Environment Fund. There is no conflict of interest. S.B. was involved in the data analysis and writing of the manuscript. T.L., E.L., M.B., H.P. and A.P. offered advice on the methods. All authors commented on drafts and approved the final text. The authors would like to thank local collaborators, interviewers and participants in the HHS and the City of Helsinki, Novosibirsk, Krakow, Havířov/Karviná, Jihlava, Ústí nad Labem, Liberec, Hradec Králové and Kroměříz.

References

  • 1.Mackenbach JP, Stirbu I, Roskam AJ, et al. Socio-economic inequalities in health in 22 European countries. N Engl J Med. 2008;358:2468–2481. doi: 10.1056/NEJMsa0707519. [DOI] [PubMed] [Google Scholar]
  • 2.Helasoja V, Lahelma E, Prattala R, et al. The sociodemographic patterning of drinking and binge drinking in Estonia, Latvia, Lithuania and Finland, 1994–2002. BMC Public Health. 2007;7:241. doi: 10.1186/1471-2458-7-241. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Lallukka T, Laaksonen M, Rahkonen O, et al. Multiple socio-economic circumstances and healthy food habits. Eur J Clin Nutr. 2007;61:701–710. doi: 10.1038/sj.ejcn.1602583. [DOI] [PubMed] [Google Scholar]
  • 4.Helasoja VV, Lahelma E, Prattala RS, et al. Determinants of daily smoking in Estonia, Latvia, Lithuania, and Finland in 1994–2002. Scand J Public Health. 2006;34:353–362. doi: 10.1080/14034940500414766. [DOI] [PubMed] [Google Scholar]
  • 5.Sanchez-Villegas A, Martinez JA, Prattala R, et al. A systematic review of socioeconomic differences in food habits in Europe: consumption of cheese and milk. Eur J Clin Nutr. 2003;57:917–929. doi: 10.1038/sj.ejcn.1601626. [DOI] [PubMed] [Google Scholar]
  • 6.Prattala R, Hakala S, Roskam AJ, et al. Association between educational level and vegetable use in nine European countries. Public Health Nutr. 2009;12:2174–2182. doi: 10.1017/S136898000900559X. [DOI] [PubMed] [Google Scholar]
  • 7.Petkeviciene J, Klumbiene J, Prattala R, et al. Educational variations in the consumption of foods containing fat in Finland and the Baltic countries. Public Health Nutr. 2007;10:518–523. doi: 10.1017/S1368980007246695. [DOI] [PubMed] [Google Scholar]
  • 8.Grabauskas V, Petkeviciene J, Kriaucioniene V, et al. Health inequalities in Lithuania: education and nutrition habits. Medicina (Kaunas) 2004;40:875–883. [PubMed] [Google Scholar]
  • 9.Bartley M, Sacker A, Firth D, et al. Understanding social variation in cardiovascular risk factors in women and men: the advantage of theoretically based measures. Soc Sci Med. 1999;49:831–845. doi: 10.1016/s0277-9536(99)00192-6. [DOI] [PubMed] [Google Scholar]
  • 10.Turrell G, Hewitt B, Patterson C, et al. Measuring socio-economic position in dietary research: is choice of socio-economic indicator important? Public Health Nutr. 2003;6:191–200. doi: 10.1079/PHN2002416. [DOI] [PubMed] [Google Scholar]
  • 11.Laaksonen E, Martikainen P, Head J, et al. Associations of multiple socio-economic circumstances with physical functioning among Finnish and British employees. Eur J Public Health. 2009;19:38–45. doi: 10.1093/eurpub/ckn123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Lahelma E, Martikainen P, Laaksonen M, et al. Pathways between socioeconomic determinants of health. J Epidemiol Community Health. 2004;58:327–332. doi: 10.1136/jech.2003.011148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Geronimus AT, Bound J. Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples. Am J Epidemiol. 1998;148:475–486. doi: 10.1093/oxfordjournals.aje.a009673. [DOI] [PubMed] [Google Scholar]
  • 14.Winkleby MA, Fortmann SP, Barrett DC. Social class disparities in risk factors for disease: eight-year prevalence patterns by level of education. Prev Med. 1990;19:1–12. doi: 10.1016/0091-7435(90)90001-z. [DOI] [PubMed] [Google Scholar]
  • 15.Irala-Estevez JD, Groth M, Johansson L, et al. A systematic review of socio-economic differences in food habits in Europe: consumption of fruit and vegetables. Eur J Clin Nutr. 2000;54:706–714. doi: 10.1038/sj.ejcn.1601080. [DOI] [PubMed] [Google Scholar]
  • 16.Galobardes B, Morabia A, Bernstein MS. Diet and socioeconomic position: does the use of different indicators matter? Int J Epidemiol. 2001;30:334–340. doi: 10.1093/ije/30.2.334. [DOI] [PubMed] [Google Scholar]
  • 17.Fuchs VR. Economics, health, and post-industrial society. Milbank Mem Fund Q Health Soc. 1979;57:153–182. [PubMed] [Google Scholar]
  • 18.Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87:1107–1117. doi: 10.1093/ajcn/87.5.1107. [DOI] [PubMed] [Google Scholar]
  • 19.Drewnowski A, Specter SE. Poverty and obesity: the role of energy density and energy costs. Am J Clin Nutr. 2004;79:6–16. doi: 10.1093/ajcn/79.1.6. [DOI] [PubMed] [Google Scholar]
  • 20.Pearlin LI, Schooler C. The structure of coping. J Health Soc Behav. 1978;19:2–21. [PubMed] [Google Scholar]
  • 21.Illsley R, Baker D. Contextual variations in the meaning of health inequality. Soc Sci Med. 1991;32:359–365. doi: 10.1016/0277-9536(91)90336-b. [DOI] [PubMed] [Google Scholar]
  • 22.Morland K, Wing S, Diez RA. The contextual effect of the local food environment on residents’ diets: the Atherosclerosis Risk in Communities Study. Am J Public Health. 2002;92:1761–1767. doi: 10.2105/ajph.92.11.1761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Giskes K, Turrell G, Patterson C, et al. Socio-economic differences in fruit and vegetable consumption among Australian adolescents and adults. Public Health Nutr. 2002;5:663–669. doi: 10.1079/PHN2002339. [DOI] [PubMed] [Google Scholar]
  • 24.Peasey A, Bobak M, Kubinova R, et al. Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: rationale and design of the HAPIEE study. BMC Public Health. 2006;6:255. doi: 10.1186/1471-2458-6-255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Lahelma E, Martikainen P, Rahkonen O, et al. Occupational class inequalities across key domains of health: results from the Helsinki Health Study. Eur J Public Health. 2005;15:504–510. doi: 10.1093/eurpub/cki022. [DOI] [PubMed] [Google Scholar]
  • 26.Lahelma E, Lallukka T, Laaksonen M, et al. Social class differences in health behaviours among employees from Britain, Finland and Japan: the influence of psychosocial factors. Health Place. 2010;16:61–70. doi: 10.1016/j.healthplace.2009.08.004. [DOI] [PubMed] [Google Scholar]
  • 27.Brunner E, Stallone D, Juneja M, et al. Dietary assessment in Whitehall II: comparison of 7 d diet diary and food-frequency questionnaire and validity against biomarkers. Br J Nutr. 2001;86:405–414. doi: 10.1079/bjn2001414. [DOI] [PubMed] [Google Scholar]
  • 28.Willett WC, Sampson L, Stampfer MJ, et al. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am J Epidemiol. 1985;122:51–65. doi: 10.1093/oxfordjournals.aje.a114086. [DOI] [PubMed] [Google Scholar]
  • 29.World Health Organization . Food-Based Dietary Guidelines in the WHO European Region. WHO Regional Office for Europe; Copenhagen: 2003. [Google Scholar]
  • 30.Roos E, Sarlio-Lahteenkorva S, Lallukka T, et al. Associations of work–family conflicts with food habits and physical activity. Public Health Nutr. 2007;10:222–229. doi: 10.1017/S1368980007248487. [DOI] [PubMed] [Google Scholar]
  • 31.Mackenbach JP, Kunst AE. Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med. 1997;44:757–771. doi: 10.1016/s0277-9536(96)00073-1. [DOI] [PubMed] [Google Scholar]
  • 32.Bingham SA, Welch AA, McTaggart A, et al. Nutritional methods in the European Prospective Investigation of Cancer in Norfolk. Public Health Nutr. 2001;4:847–858. doi: 10.1079/phn2000102. [DOI] [PubMed] [Google Scholar]
  • 33.Dynesen AW, Haraldsdottir J, Holm L, et al. Socio-demographic differences in dietary habits described by food frequency questions – results from Denmark. Eur J Clin Nutr. 2003;57:1586–1597. doi: 10.1038/sj.ejcn.1601728. [DOI] [PubMed] [Google Scholar]
  • 34.Boylan S, Welch A, Pikhart H, et al. Dietary habits in three Central and Eastern European countries: the HAPIEE study. BMC Public Health. 2009;9:439. doi: 10.1186/1471-2458-9-439. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Macdiarmid J, Blundell J. Assessing dietary intake: who, what and why of under-reporting. Nutr Res Rev. 1998;11:231–253. doi: 10.1079/NRR19980017. [DOI] [PubMed] [Google Scholar]
  • 36.Laaksonen M, Aittomaki A, Lallukka T, et al. Register-based study among employees showed small nonparticipation bias in health surveys and check-ups. J Clin Epidemiol. 2008;61:900–906. doi: 10.1016/j.jclinepi.2007.09.010. [DOI] [PubMed] [Google Scholar]
  • 37.Helakorpi S, Laitalainen E, Absetz P, et al. Health Behaviour and Health Among Finnish Adults in the Finnish Regions. National Public Health Institute; Helsinki: 2007. [Google Scholar]
  • 38.Liu S, Manson JE, Stampfer MJ, et al. A prospective study of whole-grain intake and risk of type 2 diabetes mellitus in US women. Am J Public Health. 2000;90:1409–1415. doi: 10.2105/ajph.90.9.1409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Liu S, Manson JE, Stampfer MJ, et al. Whole grain consumption and risk of ischemic stroke in women: a prospective study. JAMA. 2000;284:1534–1540. doi: 10.1001/jama.284.12.1534. [DOI] [PubMed] [Google Scholar]
  • 40.Lampe JW. Health effects of vegetables and fruit: assessing mechanisms of action in human experimental studies. Am J Clin Nutr. 1999;70(3 Suppl.):475S–490S. doi: 10.1093/ajcn/70.3.475s. [DOI] [PubMed] [Google Scholar]
  • 41.Heaney RP. Calcium, dairy products and osteoporosis. J Am Coll Nutr. 2000;19(2 Suppl.):83S–99S. doi: 10.1080/07315724.2000.10718088. [DOI] [PubMed] [Google Scholar]
  • 42.Wang L, Manson JE, Buring JE, et al. Dietary intake of dairy products, calcium, and vitamin D and the risk of hypertension in middle-aged and older women. Hypertension. 2008;51:1073–1079. doi: 10.1161/HYPERTENSIONAHA.107.107821. [DOI] [PubMed] [Google Scholar]
  • 43.World Health Organization . Diet, Nutrition and the Prevention of Chronic Diseases. WHO; Geneva: 2003. (WHO Technical Report Series no. 916). Joint WHO/FAO Expert Consultation. [PubMed] [Google Scholar]
  • 44.Fagerli RA, Wandel M. Gender differences in opinions and practices with regard to a ‘healthy diet’. Appetite. 1999;32:171–190. doi: 10.1006/appe.1998.0188. [DOI] [PubMed] [Google Scholar]
  • 45.Roos E, Lahelma E, Virtanen M, et al. Gender, socioeconomic status and family status as determinants of food behaviour. Soc Sci Med. 1998;46:1519–1529. doi: 10.1016/s0277-9536(98)00032-x. [DOI] [PubMed] [Google Scholar]
  • 46.Roos E, Talala K, Laaksonen M, et al. Trends of socioeconomic differences in daily vegetable consumption, 1979–2002. Eur J Clin Nutr. 2008;62:823–833. doi: 10.1038/sj.ejcn.1602798. [DOI] [PubMed] [Google Scholar]
  • 47.Prattala R, Paalanen L, Grinberga D, et al. Gender differences in the consumption of meat, fruit and vegetables are similar in Finland and the Baltic countries. Eur J Public Health. 2007;17:520–525. doi: 10.1093/eurpub/ckl265. [DOI] [PubMed] [Google Scholar]
  • 48.Lallukka T, Lahti-Koski M, Ovaskainen M. Vegetable and fruit consumption and its determinants in young Finnish adults. Scand J Nutr. 2001;45:120–126. [Google Scholar]
  • 49.Prattala R, Helasoja V, Mykkanen H. The consumption of rye bread and white bread as dimensions of health lifestyles in Finland. Public Health Nutr. 2001;4:813–819. doi: 10.1079/phn2000120. [DOI] [PubMed] [Google Scholar]
  • 50.Stelmach W, Kaczmarczyk-Chalas K, Bielecki W, et al. How education, income, control over life and life style contribute to risk factors for cardiovascular disease among adults in a post-communist country. Public Health. 2005;119:498–508. doi: 10.1016/j.puhe.2004.09.006. [DOI] [PubMed] [Google Scholar]
  • 51.World Health Organization . Nutrition and Lifestyle in the Baltic Republics: Summary Report. WHO Regional Office for Europe; Copenhagen: 1999. [Google Scholar]
  • 52.Stelmach W, Kaczmarczyk-Chalas K, Bielecki W, et al. The impact of income, education and health on lifestyle in a large urban population of Poland (Cindi programme) Int J Occup Med Environ Health. 2004;17:393–401. [PubMed] [Google Scholar]
  • 53.Roos E, Prattala R, Lahelma E, et al. Modern and healthy?: socioeconomic differences in the quality of diet. Eur J Clin Nutr. 1996;50:753–760. [PubMed] [Google Scholar]
  • 54.Smith AM, Baghurst KI. Public health implications of dietary differences between social status and occupational category groups. J Epidemiol Community Health. 1992;46:409–416. doi: 10.1136/jech.46.4.409. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Commission on Social Determinants of Health . Closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health: Final Report of the Commission on Social Determinants of Health. WHO; Geneva: 2008. [Google Scholar]

RESOURCES