Elsevier

Social Science & Medicine

Volume 59, Issue 10, November 2004, Pages 2139-2147
Social Science & Medicine

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

https://doi.org/10.1016/j.socscimed.2004.03.017Get rights and content

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.

Introduction

Socioeconomic status (SES) has been extensively reviewed in relation to the risk of cardiovascular disease (CVD) events (Kaplan & Keil, 1993). Multiple studies have shown inverse associations between socioeconomic position and prevalence and incidence of CVD (Rose & Marmot, 1981; Feldman et al., 1989; Marmot et al., 1991; Diez-Roux, Nieto, Tyroler, Crum, & Szklo, 1995). Recent work has also shown that living in disadvantaged neighborhoods is associated with increased coronary heart disease even after accounting for personal socioeconomic indicators (Diez-Roux et al., 2001b).

There are multiple processes through which personal and neighborhood socioeconomic characteristics could affect CVD risk. For example, those with lower education levels may not be fully aware of the consequences of eating a diet high in saturated fat or trans-fatty acids or may not be able to afford a healthy diet. Those in disadvantaged neighborhoods may not have access to fresh fruits and vegetables, or they may not have access to safe places to walk (physical activity) or otherwise exercise. Those with blue-collar jobs may face social norms at the workplace that support smoking, a CVD risk factor more common in blue-collar job sites. Persons in poverty or facing economic adversity may experience greater stresses associated with not being able to pay bills, not feeling safe in their homes, etc., which may increase catecholamine responses or other hormones that adversely affect CVD profiles.

Personal SES has also been related to carotid intima-media thickness (IMT), an indicator of early, subclinical atherosclerotic disease (Diez-Roux et al., 1995; Lynch, Kaplan, Salonen, Cohen, & Salonen, 1995; Lynch, Kaplan, Salonen, & Salonen, 1997; Lamont et al., 2000; Rosvall et al., 2000). All of these studies found protective effects of high SES on either IMT or its progression. However, findings differed across SES indicators at the individual level (education, income, occupation), or across measures of IMT (mean, maximum, plaque height, carotid stenosis) (Diez-Roux et al., 1995; Lynch et al (1995), Lynch et al (1997); Lamont et al., 2000; Rosvall et al., 2000). Data relating neighborhood SES indicators and carotid IMT have not been published.

The purpose of this study was to investigate the cross-sectional relationships between both personal SES (education, income, job classification) and neighborhood SES (a score for participant's geographic block-group based on area wealth and income) and prevalent subclinical CVD in a cohort of elderly men and women in the Cardiovascular Health Study (CHS). Subclinical disease measures have been shown to be predictive of future clinical events (Salonen & Salonen, 1993; Bots et al., 1997; Chambless et al., 1997; Hodis et al., 1998; O’Leary et al., 1999). Thus, the investigation of factors associated with early disease is of interest from the point of view of disease prevention. The examination of associations between neighborhood characteristics and measures of subclinical disease also avoids biases associated with the migration of clinically ill persons into poorer neighborhoods. In addition, to the extent that neighborhood characteristics are correlated over a person's lifetime, the investigation of associations in an elderly cohort allows quantification of the relationship between neighborhood characteristics and a summary measure of the extent of atherosclerosis developed over the lifecourse. Potential mediators and confounders of these relationships were also examined.

Section snippets

Study population and study variables

The CHS is a population-based longitudinal study of coronary heart disease and stroke in adults aged 65 years and older (Fried et al., 1991). In 1989–1990, 5201 men and women were recruited from Medicare eligibility lists in four communities: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and Pittsburgh, Pennsylvania. In 1992–1993, an additional 687 black participants from three of these four geographic locations (excluding Washington County, MD)

Results

Characteristics of the study sample are presented in Table 1. The mean (SD) age of the sample included in these analyses was 72.4 (5.4) years. Just over 38% were male and 15.9% were Black. Sixty percent had at least one indicator of subclinical disease. Nearly 25% had an average family income less than $12,000 and 25% had an average family income of $35,000 or greater. Over 55% completed high school or less and just over 20% completed college or more. Blue-collar jobs (farming or forestry or

Discussion

The relationship between CHD and personal SES has been established (Kaplan & Keil, 1993). Other data suggest that neighborhood-level SES also impacts CHD risk, independent of personal SES (Diez-Roux et al., 2001b). It is less clear whether socioeconomic conditions are related to subclinical atherosclerosis and CVD in older adults. Our findings show that older persons with subclinical disease had lower education and household income and were more likely to have blue-collar jobs compared with

Acknowledgements

Wake Forest University School of Medicine: Gregory L. Burke M.D. Wake Forest University—ECG Reading Center: Pentti M. Rautaharju M.D., Ph.D. University of California, Davis: John Robbins M.D. M.H.S. The Johns Hopkins University: Linda P. Fried M.D., M.P.H. The Johns Hopkins University—MRI Reading Center: Nick Bryan M.D., Ph.D., Norman J. Beauchamp M.D. University of Pittsburgh: Lewis H. Kuller, M.D., Dr.P.H. University of California, Irvine—Echocardiography Reading Center (baseline): Julius M.

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    The research reported in this article was supported by contracts N01-HC-85079–N01-HC-85086 from the National Heart, Lung, and Blood Institute, and Georgetown Echo RC-HL 35129 JHU MRI RC-HL 15103, and by R29HL59386.

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