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The association of personal and neighborhood socioeconomic indicators with subclinical cardiovascular disease in an elderly cohort. The cardiovascular health study

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  • Nordstrom, Cheryl K.
  • Diez Roux, Ana V.
  • Jackson, Sharon A.
  • Gardin, Julius M.

Abstract

There has been recent interest in determining whether neighborhood characteristics are related to the cardiovascular health of residents. However, there are no data regarding the relationship between neighborhood socioeconomic status (SES) and prevalence of subclinical cardiovascular disease (CVD) in the elderly. We related personal SES (education, income, and occupation type) and neighborhood socioeconomic characteristics (a block-group score summing six variables reflecting neighborhood income and wealth, education, and occupation) to the prevalence of subclinical CVD (asymptomatic peripheral vascular disease or carotid atherosclerosis, electrocardiogram or echocardiogram abnormalities, and/or positive responses to Rose Questionnaire claudication or angina pectoris) among 3545 persons aged 65 and over, without prevalent CVD, in the Cardiovascular Health Study. Sixty percent of participants had at least one indicator of subclinical disease. Compared to those without, those with subclinical disease had significantly lower education, income, and neighborhood scores and were more likely to have blue-collar jobs. After adjustment for age, gender, and race, those in the lowest SES groups had increased prevalence of subclinical disease compared with those in the highest SES groups (OR=1.50; 95% CI 1.21, 1.86 for income; OR=1.41; 95% CI 1.18, 1.69 for education; OR=1.39; 95% CI 1.16, 1.67 for block-group score). Those reporting a blue-collar lifetime occupation had greater prevalence of subclinical disease relative to those reporting a white-collar occupation (OR=1.29; 95% CI 1.02-1.59). After adjustment for behavioral and biomedical risk factors, all of these associations were reduced. Neighborhood score tended to remain inversely associated with subclinical disease after adjustment for personal socioeconomic indicators but associations were not statistically significant. Personal income and blue-collar occupation remained significantly associated with subclinical disease after simultaneous adjustment for neighborhood score and education. Personal and neighborhood socioeconomic indicators were associated with subclinical disease prevalence in this elderly cohort. These relationships were reduced after controlling for traditional CVD risk factors.

Suggested Citation

  • Nordstrom, Cheryl K. & Diez Roux, Ana V. & Jackson, Sharon A. & Gardin, Julius M., 2004. "The association of personal and neighborhood socioeconomic indicators with subclinical cardiovascular disease in an elderly cohort. The cardiovascular health study," Social Science & Medicine, Elsevier, vol. 59(10), pages 2139-2147, November.
    • Handle: RePEc:eee:socmed:v:59:y:2004:i:10:p:2139-2147
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    Cited by:

    1. Andrews, Gavin J. & Cutchin, Malcolm & McCracken, Kevin & Phillips, David R. & Wiles, Janine, 2007. "Geographical Gerontology: The constitution of a discipline," Social Science & Medicine, Elsevier, vol. 65(1), pages 151-168, July.
    2. Cláudia Jardim Santos & Inês Paciência & Ana Isabel Ribeiro, 2022. "Neighbourhood Socioeconomic Processes and Dynamics and Healthy Ageing: A Scoping Review," IJERPH, MDPI, vol. 19(11), pages 1-26, May.
    3. Akresh, Ilana Redstone & Do, D. Phuong & Frank, Reanne, 2016. "Segmented assimilation, neighborhood disadvantage, and Hispanic immigrant health," Social Science & Medicine, Elsevier, vol. 149(C), pages 114-121.
    4. Lemelin, Emily T. & Diez Roux, Ana V. & Franklin, Tracy G. & Carnethon, Mercedes & Lutsey, Pamela L. & Ni, Hanyu & O'Meara, Ellen & Shrager, Sandi, 2009. "Life-course socioeconomic positions and subclinical atherosclerosis in the multi-ethnic study of atherosclerosis," Social Science & Medicine, Elsevier, vol. 68(3), pages 444-451, February.
    5. Arline Geronimus & John Bound & Annie Ro, 2014. "Residential Mobility Across Local Areas in the United States and the Geographic Distribution of the Healthy Population," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 777-809, June.
    6. Olivier Grimaud & Annabelle Lapostolle & Claudine Berr & Catherine Helmer & Carole Dufouil & Wahida Kihal & Annick Alpérovitch & Pierre Chauvin, 2013. "Gender Differences in the Association between Socioeconomic Status and Subclinical Atherosclerosis," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-6, November.
    7. Havard, Sabrina & Deguen, Séverine & Bodin, Julie & Louis, Karine & Laurent, Olivier & Bard, Denis, 2008. "A small-area index of socioeconomic deprivation to capture health inequalities in France," Social Science & Medicine, Elsevier, vol. 67(12), pages 2007-2016, December.
    8. Do, D. Phuong & Dubowitz, Tamara & Bird, Chloe E. & Lurie, Nicole & Escarce, Jose J. & Finch, Brian K., 2007. "Neighborhood context and ethnicity differences in body mass index: A multilevel analysis using the NHANES III survey (1988-1994)," Economics & Human Biology, Elsevier, vol. 5(2), pages 179-203, July.
    9. Wight, Richard G. & Cummings, Janet R. & Miller-Martinez, Dana & Karlamangla, Arun S. & Seeman, Teresa E. & Aneshensel, Carol S., 2008. "A multilevel analysis of urban neighborhood socioeconomic disadvantage and health in late life," Social Science & Medicine, Elsevier, vol. 66(4), pages 862-872, February.

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