Skip to main content
SpringerLink
Log in

Quantifying the contributions of behavioral and biological risk factors to socioeconomic disparities in coronary heart disease incidence: the MORGEN study

  • CARDIOVASCULAR DISEASE
  • Published:
European Journal of Epidemiology Aims and scope Submit manuscript

Abstract

Quantifying the impact of different modifiable behavioral and biological risk factors on socioeconomic disparities in coronary heart disease (CHD) may help inform targeted, population-specific strategies to reduce the unequal distribution of the disease. Previous studies have used analytic approaches that limit our ability to disentangle the relative contributions of these risk factors to CHD disparities. The goal of this study was to assess mediation of the effect of low education on incident CHD by multiple risk factors simultaneously. Analyses are based on 15,067 participants of the Dutch Monitoring Project on Risk Factors for Chronic Diseases aged 20–65 years examined 1994–1997 and followed for events until January 1, 2008. Path analysis was used to quantify and test mediation of the low education-CHD association by behavioral (current cigarette smoking, heavy alcohol use, poor diet, and physical inactivity) and biological (obesity, hypertension, diabetes, and hypercholesterolemia) risk factors. Behavioral and biological risk factors accounted for 56.6 % (95 % CI 42.6–70.8 %) of the low education-incident CHD association. Smoking was the strongest mediator, accounting for 27.3 % (95 % CI 17.7–37.4 %) of the association, followed by obesity (10.2 %; 95 % CI 4.5–16.1 %), physical inactivity (6.3 %; 95 % CI 2.7–10.0 %), and hypertension (5.3 %; 95 % CI: 2.8–8.0 %). In summary, in a Dutch cohort, the majority of the relationship between low education and incident CHD was mediated by traditional behavioral and biological risk factors. Addressing barriers to smoking cessation, blood pressure and weight management, and physical activity may be the most effective approaches to eliminating socioeconomic inequalities in CHD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. van der Lucht F, Polder JJ. The Dutch 2010 public health status and forecasts report. Bilthoven: National Institute for Public Health and the Environment; 2010.

    Google Scholar 

  2. Louwman WJ, et al. A 50 % higher prevalence of life-shortening chronic conditions among cancer patients with low socioeconomic status. Br J Cancer. 2010;103(11):1742–8.

    Article  PubMed  CAS  Google Scholar 

  3. Van Lenthe FJ, et al. Material and behavioral factors in the explanation of educational differences in incidence of acute myocardial infarction: the Globe study. Ann Epidemiol. 2002;12(8):535–42.

    Article  PubMed  Google Scholar 

  4. LaVeist TA, Wallace JM Jr. Health risk and inequitable distribution of liquor stores in African American neighborhood. Soc Sci Med. 2000;51(4):613–7.

    Article  PubMed  CAS  Google Scholar 

  5. Wilson DK, et al. Socioeconomic status and perceptions of access and safety for physical activity. Ann Behav Med. 2004;28(1):20–8.

    Article  PubMed  Google Scholar 

  6. Hackbarth DP, Silvestri B, Cosper W. Tobacco and alcohol billboards in 50 Chicago neighborhoods: market segmentation to sell dangerous products to the poor. J Public Health Policy. 1995;16(2):213–30.

    Article  PubMed  CAS  Google Scholar 

  7. Larson NI, Story MT, Nelson MC. Neighborhood environments: disparities in access to healthy foods in the U.S. Am J Prev Med. 2009;36(1):74–81.

    Article  PubMed  Google Scholar 

  8. Moore LV, Diez Roux AV. Associations of neighborhood characteristics with the location and type of food stores. Am J Public Health. 2006;96(2):325–31.

    Article  PubMed  Google Scholar 

  9. Jackson JS, Knight KM. Race and self-regulatory health behaviors: the role of the stress response and the HPA axis in physical and mental health disparities. In: Schaie KW, Cartensen L, editors. Social structures, aging, and self-regulation in the elderly. New York: Springer; 2006. p. 189–207.

    Google Scholar 

  10. Krueger PM, Chang VW. Being poor and coping with stress: health behaviors and the risk of death. Am J Public Health. 2008;98(5):889–96.

    Article  PubMed  Google Scholar 

  11. Ng DM, Jeffery RW. Relationships between perceived stress and health behaviors in a sample of working adults. Health Psychol. 2003;22(6):638–42.

    Article  PubMed  Google Scholar 

  12. Dallman MF, et al. Chronic stress and obesity: a new view of “comfort food”. Proc Natl Acad Sci USA. 2003;100(20):11696–701.

    Article  PubMed  CAS  Google Scholar 

  13. McEwen BS. Protective and damaging effects of stress mediators. N Engl J Med. 1998;338(3):171–9.

    Article  PubMed  CAS  Google Scholar 

  14. Pickering T. Cardiovascular pathways: socioeconomic status and stress effects on hypertension and cardiovascular function. Ann NY Acad Sci. 1999;896:262–77.

    Article  PubMed  CAS  Google Scholar 

  15. Tamashiro KL. Metabolic syndrome: links to social stress and socioeconomic status. Ann NY Acad Sci. 2011;1231:46–55.

    Article  PubMed  Google Scholar 

  16. Kivimaki M, 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;97(5):874–9.

    Article  PubMed  Google Scholar 

  17. Kuper H, et al. Psychosocial determinants of coronary heart disease in middle-aged women: a prospective study in Sweden. Am J Epidemiol. 2006;164(4):349–57.

    Article  PubMed  Google Scholar 

  18. Lawlor DA, Ebrahim S, Davey Smith G. Adverse socioeconomic position across the lifecourse increases coronary heart disease risk cumulatively: findings from the British women’s heart and health study. J Epidemiol Community Health. 2005;59(9):785–93.

    Article  PubMed  Google Scholar 

  19. Lynch JW, et al. Do cardiovascular risk factors explain the relation between socioeconomic status, risk of all-cause mortality, cardiovascular mortality, and acute myocardial infarction? Am J Epidemiol. 1996;144(10):934–42.

    Article  PubMed  CAS  Google Scholar 

  20. Marmot MG, et al. Biological and behavioural explanations of social inequalities in coronary heart disease: the Whitehall II study. Diabetologia. 2008;51(11):1980–8.

    Article  PubMed  CAS  Google Scholar 

  21. Strand BH, Tverdal A. 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;58(8):705–9.

    Article  PubMed  Google Scholar 

  22. Suadicani P, Hein HO, Gyntelberg F. 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;26(3):516–22.

    Article  PubMed  CAS  Google Scholar 

  23. Woodward M, et al. Contribution of contemporaneous risk factors to social inequality in coronary heart disease and all causes mortality. Prev Med. 2003;36(5):561–8.

    Article  PubMed  Google Scholar 

  24. Yarnell J, et al. Education, socioeconomic and lifestyle factors, and risk of coronary heart disease: the PRIME Study. Int J Epidemiol. 2005;34(2):268–75.

    Article  PubMed  CAS  Google Scholar 

  25. Rosengren A, et al. Education and risk for acute myocardial infarction in 52 high, middle and low-income countries: INTERHEART case-control study. Heart. 2009;95(24):2014–22.

    Article  PubMed  CAS  Google Scholar 

  26. Ramsay SE, et al. Socioeconomic inequalities in coronary heart disease risk in older age: contribution of established and novel coronary risk factors. J Thromb Haemost. 2009;7(11):1779–86.

    Article  PubMed  CAS  Google Scholar 

  27. McFadden E, et al. Occupational social class, risk factors and cardiovascular disease incidence in men and women: a prospective study in the European Prospective Investigation of Cancer and Nutrition in Norfolk (EPIC-Norfolk) cohort. Eur J Epidemiol. 2008;23(7):449–58.

    Article  PubMed  Google Scholar 

  28. Wolfe LM. Sewall Wright on the method of path coefficients: an annotated bibliography. Struct Equ Model. 1999;6:280–91.

    Article  Google Scholar 

  29. Wright S. The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proc Natl Acad Sci USA. 1920;6(6):320–32.

    Article  PubMed  CAS  Google Scholar 

  30. Stringhini S, et al. Health behaviours, socioeconomic status, and mortality: further analyses of the British Whitehall II and the French GAZEL prospective cohorts. PLoS Med. 2011;8(2):e1000419.

    Article  PubMed  Google Scholar 

  31. Beulens JW, et al. Cohort profile: the EPIC-NL study. Int J Epidemiol. 2010;39(5):1170–8.

    Article  PubMed  Google Scholar 

  32. Smit HA, et al. Monitoring van Risicofactoren en Gezondheid in Nederland (MORGEN-project): doelstellingen en werkwijze. Bilthoven: RIVM; 1994.

    Google Scholar 

  33. Van Oers JAM, et al. Alcohol consumption, alcohol-related problems, problem drinking, and socioeconomic status. Alcohol Alcohol. 1999;34(1):78–88.

    Article  PubMed  Google Scholar 

  34. Grittner U, et al. Alcohol consumption and social inequality at the individual and country levels—results from an international study. Eur J Public Health. 2012;23:332−339.

    Google Scholar 

  35. Maclure M. Demonstration of deductive meta-analysis: ethanol intake and risk of myocardial infarction. Epidemiol Rev. 1993;15(2):328–51.

    PubMed  CAS  Google Scholar 

  36. Sesso HD, Gaziano JM. Alcohol intake and cardiovascular morbidity and mortality. Curr Opin Nephrol Hypertens. 1999;8(3):353–7.

    Article  PubMed  CAS  Google Scholar 

  37. Wareham NJ, et al. Validity and repeatability of a simple index derived from the short physical activity questionnaire used in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr. 2003;6(4):407–13.

    Article  PubMed  Google Scholar 

  38. Trichopoulou A, et al. Modified Mediterranean diet and survival: EPIC-elderly prospective cohort study. BMJ. 2005;330(7498):991.

    Article  PubMed  Google Scholar 

  39. Hoevenaar-Blom MP, et al. Mediterranean style diet and 12-year incidence of cardiovascular diseases: the EPIC-NL cohort study. PLoS ONE. 2012;7(9):e45458.

    Article  PubMed  CAS  Google Scholar 

  40. National Cholesterol Education Program (NCEP). Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult treatment panel III). Final report. Circulation, 2002; 106(25):3143–421.

    Google Scholar 

  41. The sixth report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure. Archives Intern Med. 1997; 157(21):2413–46.

  42. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010; 33 Suppl 1: S62–9.

    Google Scholar 

  43. World Health Organization. International classification of diseases, 9th revision (ICD-9). Geneva: World Health Organization; 1977.

    Google Scholar 

  44. World Health Organization. International classification of diseases, 10th revision (ICD-10). Geneva: World Health Organization; 1990.

    Google Scholar 

  45. Tein J-Y, MacKinnon DP. Estimating mediated effects with survival data. In: Yanai H, et al., editors. New developments on psychometrics. Tokyo: Springer; 2003. p. 405–12.

    Chapter  Google Scholar 

  46. VanderWeele TJ. Causal mediation analysis with survival data. Epidemiology. 2011;22(4):582–5.

    Article  PubMed  Google Scholar 

  47. Valeri L, Vanderweele TJ. Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. Psychol Methods. 2013.

  48. Taylor AB, MacKinnon DP, Tein J-Y. Tests of the three-path mediated effect. Organ Res Methods. 2008;11:241–69.

    Article  Google Scholar 

  49. Barker N. A practical introduction to the bootstrap using the SAS system. In: Pharmaceutical users software exchange annual meeting. Heidelberg, Germany. 2005.

  50. Lewis TT, et al. Hostility is associated with visceral, but not subcutaneous, fat in middle-aged African American and white women. Psychosom Med. 2009;71(7):733–40.

    Article  PubMed  Google Scholar 

  51. Lewis TT, et al. Self-reported experiences of discrimination and visceral fat in middle-aged African–American and Caucasian women. Am J Epidemiol. 2011;173(11):1223–31.

    Article  PubMed  Google Scholar 

  52. Shively CA, Register TC, Clarkson TB. Social stress, visceral obesity, and coronary artery atherosclerosis: product of a primate adaptation. Am J Primatol. 2009;71(9):742–51.

    Article  PubMed  Google Scholar 

  53. Stringhini S, et al. Association of socioeconomic position with health behaviors and mortality. JAMA. 2010;303(12):1159–66.

    Article  PubMed  CAS  Google Scholar 

  54. Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods. 2010;15(4):309–34.

    Article  PubMed  Google Scholar 

  55. van Oort FV, van Lenthe FJ, Mackenbach JP. Material, psychosocial, and behavioural factors in the explanation of educational inequalities in mortality in The Netherlands. J Epidemiol Community Health. 2005;59(3):214–20.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

K. N. Kershaw was supported by Grant T32-HL-069771-07. The Monitoring Project on Risk Factors and Chronic Diseases in the Netherlands (MORGEN) Study was supported by the Ministry of Health, Welfare and Sport of the Netherlands, the National Institute of Public Health and the Environment, Bilthoven, the Netherlands and the Europe Against Cancer Program of the European Union. The authors thank the epidemiologists and field workers of the Municipal Health Services in Amsterdam, Doetinchem, and Maastricht for their important contribution to the data collection for this study.

Author information

Authors and Affiliations

  1. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Suite 1400, Chicago, IL, 60611, USA

    Kiarri N. Kershaw, Mercedes R. Carnethon & Martha L. Daviglus

  2. Department of Public Health, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

    Mariël Droomers

  3. Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA

    Whitney R. Robinson

  4. National Institute for Public Health and the Environment, Bilthoven, The Netherlands

    W. M. Monique Verschuren

  5. Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA

    Martha L. Daviglus

Authors
  1. Kiarri N. Kershaw
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mariël Droomers
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Whitney R. Robinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mercedes R. Carnethon
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martha L. Daviglus
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. W. M. Monique Verschuren
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kiarri N. Kershaw.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 64 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kershaw, K.N., Droomers, M., Robinson, W.R. et al. Quantifying the contributions of behavioral and biological risk factors to socioeconomic disparities in coronary heart disease incidence: the MORGEN study. Eur J Epidemiol 28, 807–814 (2013). https://doi.org/10.1007/s10654-013-9847-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10654-013-9847-2

Keywords

Search

Navigation