The contribution of diet and lifestyle to socioeconomic inequalities in cardiovascular morbidity and mortality

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Abstract

Background

The role of differences in diet on the relationship between socioeconomic factors and cardiovascular diseases remains unclear. We studied the contribution of diet and other lifestyle factors to the explanation of socioeconomic inequalities in cardiovascular diseases.

Methods

We prospectively examined the incidence of coronary heart disease (CHD) and stroke events amongst 33,106 adults of the EPIC-NL cohort. Education and employment status indicated socioeconomic status. We used Cox proportional models to estimate hazard ratios ((HR (95% confidence intervals)) for the association of socioeconomic factors with CHD and stroke and the contribution of diet and lifestyle.

Results

During 12 years of follow-up, 1617 cases of CHD and 531 cases of stroke occurred. The risks of CHD and stroke were higher in lowest (HR = 1.98 (1.67;2.35); HR = 1.55 (1.15;2.10)) and lower (HR = 1.50 (1.29;1.75); HR = 1.42 (1.08;1.86)) educated groups than in the highest. Unemployed and retired subjects more often suffered from CHD (HR = 1.37 (1.19;1.58); HR = 1.20 (1.05;1.37), respectively), but not from stroke, than the employed. Diet and lifestyle, mainly smoking and alcohol, explained more than 70% of the educational differences in CHD and stroke and 65% of employment status variation in CHD. Diet explained more than other lifestyle factors of educational and employment status differences in CHD and stroke (36% to 67% vs. 9% to 27%).

Conclusion

The socioeconomic distribution of diet, smoking and alcohol consumption largely explained the inequalities in CHD and stroke in the Netherlands. These findings need to be considered when developing policies to reduce socioeconomic inequalities in cardiovascular diseases.

Introduction

In many industrialized countries, socioeconomic inequalities in cardiovascular diseases (CVD) have been reported [1], [2]. Cardiovascular morbidity and mortality are higher amongst the lowest socioeconomic groups due to their higher exposure to risk factors, such as low social support, negative life events, unhealthy behaviours, and lower health care utilization [3], [4], [5]. Most studies regarding the mediating role of behaviour on this relationship have focussed on physical inactivity, smoking, alcohol consumption, and obesity [3], [5], [6], [7], [8], [9], [10], [11], [12], [13]. Combinations of these behaviours explained 13% to 60% of the socioeconomic differences in cardiovascular morbidity and 19% to 55% of cardiovascular mortality inequalities.

Evidence is mounting that high socioeconomic position, as defined by high educational level, high income and high occupational class, is consistently associated with healthy dietary patterns such as greater consumption of fruits and vegetables, low-fat dairy products, or whole-grain foods, whereas those with low socioeconomic position tend to consume more meat and fatty foods [14], [15]. Although diet is an important risk factor of CVD [16], little is understood about whether dietary factors, and particularly specific food groups, mediate the impact of socioeconomic status on CVD. The few studies that examined specific dietary intakes showed a relatively small contribution of diet (none to a quarter) to the explanation of socioeconomic inequalities in CVD [4], [17], [18], [19]. This relatively small mediating effect might be the result of not considering overall diet but only some isolated dietary factors, such as frequency of fruit and vegetable consumption, type of bread or milk, and meat, vitamin C, or coffee intake. In addition, most studies, except two [4], [19], focussed on cardiovascular mortality but not morbidity and only one investigated stroke separately [17].

Therefore, the aim of our study was to explore the potential mediating effect of a vast number of dietary factors indicating overall diet and other lifestyle factors on the association between socioeconomic position and coronary heart diseases (CHD) and stroke morbidity and mortality in the Dutch sample of the European Prospective Investigation into Cancer and Nutrition (EPIC-NL), a prospective cohort of 40,011 Dutch men and women.

Section snippets

Study population and design

Between 1993 and 1997, we recruited 17,357 women aged 49–70 years old amongst breast cancer screening participants in the PROSPECT cohort and 22,654 men and women aged 20–59 years, through random population sampling in the MORGEN cohort. These are the two Dutch contributions to the EPIC [20]. The cohorts are described in more detail elsewhere [20]. Both cohorts comply with the Declaration of Helsinki. The subjects gave informed consent. Prospect was approved by the Institutional Review Board of

Results

In total, 2148 subjects acquired cardiovascular disease during follow-up, 1617 with CHD and 531 with stroke (Table 1 in the Supplementary data). The lowest and lower educated groups showed significantly higher risks of CHD (HR = 1.98 (1.67;2.35); HR = 1.50 (1.29;1.75)) and stroke (HR = 1.55 (1.15;2.10); HR = 1.42 (1.08;1.86)) compared with the highest educational level. Unemployed and retired subjects suffered more often from CHD compared to those who were employed (HR = 1.37 (1.19;1.58); HR = 1.20

Discussion

Our results show an educational gradient in CHD and stroke whereas difference between employment status categories was only found for CHD risk. Diet and lifestyle contribute substantially to socioeconomic inequalities in CVD and diet was the most important mediating factor of socioeconomic differences in CHD and stroke. These findings suggest the importance to improve dietary and lifestyle behaviours amongst lower socioeconomic groups not only to improve population health but also to reduce

Conclusion

Our findings indicate that diet, smoking and alcohol consumption largely contributed to socioeconomic inequalities in CVD. Diet accounted for approximately 48% and 67% of educational variation in CHD and stroke risks, and 36% of employment status variation in CHD risk. Our findings indicate that public health interventions that aim to reduce the high prevalence of unhealthy dietary and lifestyle behaviours amongst lower socioeconomic groups may be an effective strategy not only for improving

Acknowledgments

We thank Statistics Netherlands and the PHARMO Institute for follow-up data on vital status and the incidence of non-fatal cardiovascular diseases.

References (38)

  • M. Kivimaki et al.

    Socioeconomic position, co-occurrence of behavior-related risk factors, and coronary heart disease: the Finnish Public Sector study

    Am J Public Health

    (2007)
  • A. Steptoe et al.

    The role of psychobiological pathways in socio-economic inequalities in cardiovascular disease risk

    Eur Heart J

    (2002)
  • B.H. Strand et al.

    Can cardiovascular risk factors and lifestyle explain the educational inequalities in mortality from ischaemic heart disease and from other heart diseases? 26 year follow up of 50,000 Norwegian men and women

    J Epidemiol Community Health

    (2004)
  • P. Suadicani et al.

    Strong mediators of social inequalities in risk of ischaemic heart disease: a six-year follow-up in the Copenhagen Male Study

    Int J Epidemiol

    (1997)
  • H. Kuper et al.

    Psychosocial determinants of coronary heart disease in middle-aged women: a prospective study in Sweden

    Am J Epidemiol

    (2006)
  • A. Rosengren et al.

    Education and risk for acute myocardial infarction in 52 high, middle and low-income countries: INTERHEART case–control study

    Heart

    (2009)
  • J. Yarnell et al.

    Education, socioeconomic and lifestyle factors, and risk of coronary heart disease: the PRIME Study

    Int J Epidemiol

    (2005)
  • C.B. Kamphuis et al.

    Socioeconomic inequalities in cardiovascular mortality and the role of childhood socioeconomic conditions and adulthood risk factors: a prospective cohort study with 17-years of follow up

    BMC Public Health

    (2012)
  • E. Dowler

    Inequalities in diet and physical activity in Europe

    Public Health Nutr

    (2001)
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    Source of funding: The EPIC-NL study was supported by the “Europe Against Cancer” Programme of the European Commission; the Dutch Ministry of Public Health, Welfare and Sports; the Dutch Cancer Society; ZonMW the Netherlands Organisation for Health Research and Development; and the World Cancer Research Fund.

    1

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