Socio-economic inequalities in health and health behaviours are evident throughout Europe, particularly so in Eastern European and Baltic countries(Reference Mackenbach, Stirbu and Roskam1). In Western and Baltic countries, those in higher socio-economic positions have healthier behaviours(Reference Helasoja, Lahelma and Prattala2–Reference Helasoja, Lahelma and Prattala4). 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(Reference Sanchez-Villegas, Martinez and Prattala5, Reference Prattala, Hakala and Roskam6). In addition, most studies have examined the association with food habits using only one or a few socio-economic indicators(Reference Petkeviciene, Klumbiene and Prattala7, Reference Grabauskas, Petkeviciene and Kriaucioniene8). 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(Reference Bartley, Sacker and Firth9) and may lead to overestimation or underestimation of effects(Reference Turrell, Hewitt and Patterson10).
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(Reference Laaksonen, Martikainen and Head11–Reference Winkleby, Fortmann and Barrett14). The current study employs similar socio-economic indicators as each has previously been shown to be associated with food habits(Reference Lallukka, Laaksonen and Rahkonen3, Reference Prattala, Hakala and Roskam6, Reference Irala-Estevez, Groth and Johansson15). 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(Reference Galobardes, Morabia and Bernstein16, Reference Fuchs17). Occupation may determine income and therefore access to healthy food; also, because occupation creates a social network, it can influence health behaviours(Reference Galobardes, Morabia and Bernstein16). 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(Reference Darmon and Drewnowski18–Reference Pearlin and Schooler20). 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(Reference Illsley and Baker21).
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(Reference Morland, Wing and Diez22). 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(Reference Sanchez-Villegas, Martinez and Prattala5, Reference Prattala, Hakala and Roskam6, Reference Irala-Estevez, Groth and Johansson15, Reference Giskes, Turrell and Patterson23).
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(Reference Peasey, Bobak and Kubinova24) and the Finnish Helsinki Health Study (HHS)(Reference Lahelma, Martikainen and Rahkonen25). 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(Reference Lallukka, Laaksonen and Rahkonen3, Reference Peasey, Bobak and Kubinova24–Reference Lahelma, Lallukka and Laaksonen26).
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(Reference Peasey, Bobak and Kubinova24). 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(Reference Brunner, Stallone and Juneja27) which in turn was adapted from the original instrument developed by Willett(Reference Willett, Sampson and Stampfer28). 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’(Reference Lallukka, Laaksonen and Rahkonen3). 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(Reference Lallukka, Laaksonen and Rahkonen3, Reference Roos, Sarlio-Lahteenkorva and Lallukka30).
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(Reference Mackenbach and Kunst31). 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)(Reference Mackenbach and Kunst31). 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)
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)
*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 Distribution of healthy food habit score among males by country (—▴—, Czech Republic; —●—, Russia; - -○- -, Poland; —▵—, 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 Distribution of healthy food habit score among females by country (—▴—, Czech Republic; —●—, Russia; - -○- -, Poland; —▵—, 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)
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)
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(Reference Brunner, Stallone and Juneja27, Reference Bingham, Welch and McTaggart32). 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(Reference Dynesen, Haraldsdottir and Holm33). Also, although consumption frequencies do not directly translate into quantities, frequencies can give a reasonable indication of actual intake and food habits in general(Reference Dynesen, Haraldsdottir and Holm33).
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 unsupervised. 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(Reference Boylan, Welch and Pikhart34). 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(Reference Macdiarmid and Blundell35).
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(Reference Laaksonen, Aittomaki and Lallukka36). 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(Reference Helakorpi, Laitalainen and Absetz37). 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(Reference Liu, Manson and Stampfer38–Reference Lampe40) while a low intake of dairy products is associated with diseases such as osteoporosis(Reference Heaney41) and hypertension(Reference Wang, Manson and Buring42). 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(Reference Irala-Estevez, Groth and Johansson15, Reference Fagerli and Wandel44, Reference Roos, Lahelma and Virtanen45).
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(Reference Irala-Estevez, Groth and Johansson15). 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(Reference Prattala, Hakala and Roskam6, Reference Lahelma, Lallukka and Laaksonen26, Reference Roos, Talala and Laaksonen46–Reference Lallukka, Lahti-Koski and Ovaskainen48). A positive association between vegetable consumption and occupation has also been reported in Europe(Reference Irala-Estevez, Groth and Johansson15), and in previous HHS analyses(Reference Lallukka, Laaksonen and Rahkonen3). 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(Reference Prattala, Hakala and Roskam6). 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(Reference Prattala, Helasoja and Mykkanen49), while in Poland no significant difference in ‘dark’ bread consumption was found between those of lower and higher education(Reference Stelmach, Kaczmarczyk-Chalas and Bielecki50).
Consumption of high-fat milk has been previously linked with low education in Finland and the Baltic countries(Reference Petkeviciene, Klumbiene and Prattala7). 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(Reference Petkeviciene, Klumbiene and Prattala7), 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(Reference Petkeviciene, Klumbiene and Prattala7).
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(Reference Lallukka, Laaksonen and Rahkonen3). 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(Reference Stelmach, Kaczmarczyk-Chalas and Bielecki52).
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(Reference Roos, Prattala and Lahelma53, Reference Smith and Baghurst54).
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.
