Socioeconomic differences in dietary patterns among middle-aged men and women
Introduction
Specific food items and nutritional constituents are related to established risk factors for coronary heart disease, diabetes, and are important factors in the causation of many cancers (World Cancer Research Fund, 1997; Shetty & McPherson, 1997). However, it is difficult to isolate these effects and influence the consumption of single food items as the intakes of different foodstuffs are strongly and complexly interrelated. If we can understand these interrelationships, identify the common dietary patterns that individuals consume and are able to specify some of the broad sociodemographic determinants of these patterns, we may be closer to being able to prevent disease by focussing not on specific nutrients but on unhealthy and healthy dietary patterns.
Earlier evidence shows that common dietary patterns can be identified, and that these dietary patterns are closely related to many micro-nutrient levels and energy intake as well as socioeconomic status; those who consume healthier diets are from higher socioeconomic groups (Whichelow & Prevost, 1996; Wirfält & Jeffery, 1997; Pryer et al., 2001). However, we lack a more detailed assessment of the causes of socioeconomic differences in dietary patterns and the possible contribution of these dietary patterns to socioeconomic differences in risk factors for disease.
The purpose of this study is: (i) to identify common dietary patterns in a cohort of middle-aged men and women, (ii) to describe socioeconomic differences in these dietary patterns, and study the sociodemographic and behavioural predictors of these differences, and (iii) to assess whether these dietary patterns contribute to socioeconomic differences in BMI, waist-to-hip-ratio, HDL and serum triglyceride.
Section snippets
Sample
The data come from the Whitehall II study, a prospective cohort study of men and women aged 35–55 years and working in the London offices of 20 civil-service departments at enrolment. Subjects were invited to participate by letter. The overall response rate was 73 per cent, although the true response rate is likely to be higher because around 4 per cent of those listed as employees were not eligible as they had moved before the study began. Altogether 10,308 participants of which 67 per cent
Description of the dietary clusters
Table 1 presents the six dietary clusters obtained from the cluster analyses of food frequency questionnaire items. Each observation is finally allocated to one cluster. The table shows the proportions consuming selected food items for the six clusters. We have only included the 22 items with the highest R2 value.
Very healthy diet had low consumption of meat and white bread, high consumption of fish and wholemeal bread, low consumption of full cream milk, cream, butter, sugar, biscuits and
Discussion
Self-reported dietary data are often inaccurate indicators of nutrient intake; correlations of blood plasma or urine measures of nutrients and estimates based on dietary information are usually low (Bingham et al., 1997; Bingham & Day, 1997; Brunner et al., 2001). In this paper, we have not set out to measure nutrient levels. Our aim has been to identify common dietary patterns based on food frequency data, and to assess socioeconomic differences in these dietary patterns and their
Summary
These results show that dietary patterns are strongly related to socioeconomic status, and that these dietary patterns may be important determinants of socioeconomic differences in some health related risk factors. The causes of socioeconomic differences in dietary choices are not well understood and our data are not ideal to study this. However, these data indicate that dietary choices are less related to material circumstances, and perceptions of control over health, but that factors related
Acknowledgements
The Whitehall II study has been supported by grants from the Medical Research Council; British Heart Foundation; Health and Safety Executive; Department of Health; National Heart Lung and Blood Institute (RO1-HL36310), US, NIH: National Institute on Aging (RO1-AG13196), US, NIH; Agency for Health Care Policy Research (RO1-HS06516); and the John D. and Catherine T. MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health. PM is supported by
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