The association of personal and neighborhood socioeconomic indicators with subclinical cardiovascular disease in an elderly cohort. The Cardiovascular Health Study

Department of Epidemiology, School of Public Health, University of Michigan, 1214 S. 2nd Floor, Ann Arbor, MI 48104-2548, USA.
Social Science & Medicine (Impact Factor: 2.89). 12/2004; 59(10):2139-47. DOI: 10.1016/j.socscimed.2004.03.017
Source: PubMed


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.

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Available from: Julius Gardin, Nov 04, 2015
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    • "The lack of effect for neighborhood SEP on any fluid cognitive ability (memory, reasoning, speed, and everyday cognition) or on cognitive plasticity (i.e., response to training) is somewhat surprising given the extensive research documenting neighborhood effects on factors affecting brain health, such as cardiovascular fitness and chronic diseases (e.g., [43, 44]). It would be reasonable to hypothesize that neighborhood could indirectly affect fluid cognitive abilities and training gains, which are more sensitive to compromised brain health than vocabulary [45], through differences in access to health care, nutrition, and opportunities for exercise; however, results suggest that if these indirect effects are present they may be relatively weak. "
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    ABSTRACT: Low neighborhood-level socioeconomic status has been associated with poorer health, reduced physical activity, increased psychological stress, and less neighborhood-based social support. These outcomes are correlates of late life cognition, but few studies have specifically investigated the neighborhood as a unique source of explanatory variance in cognitive aging. This study supplemented baseline cognitive data from the ACTIVE (Advanced Cognitive Training for Independent and Vital Elderly) study with neighborhood-level data to investigate (1) whether neighborhood socioeconomic position (SEP) predicts cognitive level, and if so, whether it differentially predicts performance in general and specific domains of cognition and (2) whether neighborhood SEP predicts differences in response to short-term cognitive intervention for memory, reasoning, or processing speed. Neighborhood SEP positively predicted vocabulary, but did not predict other general or specific measures of cognitive level, and did not predict individual differences in response to cognitive intervention.
    Journal of aging research 08/2012; 2012(2090-2204):435826. DOI:10.1155/2012/435826
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    • "Our study also raises the question of why macro-level socioeconomic conditions should matter to the health of healthy women. Previous studies of area-level contributors to inflammation address this question with a focus on neighborhood environments, and suggest that contextual differences are due to neighborhood conditions that promote psychosocial stress, influence social norms, or fail to facilitate healthy behaviors due to a lack of health-promoting resources [9,37,38]. In contrast, state-level socioeconomic conditions could potentially relate to health status among women through differences in state-level public health outlays, state investments in safety-net insurance that influence early health care seeking behavior, or by influencing the ability for states to contribute resources to local agencies that foster health promotion efforts [39-41]. "
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    ABSTRACT: Cardiovascular inflammation is a key contributor to the development of atherosclerosis and the prediction of cardiovascular events among healthy women. An emerging literature suggests biomarkers of inflammation vary by geography of residence at the state-level, and are associated with individual-level socioeconomic status. Associations between cardiovascular inflammation and state-level socioeconomic conditions have not been evaluated. The study objective is to estimate whether there are independent associations between state-level socioeconomic conditions and individual-level biomarkers of inflammation, in excess of individual-level income and clinical covariates among healthy women. The authors examined cross-sectional multilevel associations among state-level socioeconomic conditions, individual-level income, and biomarkers of inflammation among women (n = 26,029) in the Women's Health Study, a nation-wide cohort of healthy women free of cardiovascular diseases at enrollment. High sensitivity C-reactive protein (hsCRP), soluble intercellular adhesion molecule-1 (sICAM-1) and fibrinogen were measured between 1993 and 1996. Biomarker levels were examined among women within quartiles of state-level socioeconomic conditions and within categories of individual-level income. The authors found that favorable state-level socioeconomic conditions were correlated with lower hsCRP, in excess of individual-level income (e.g. state-level real per capital gross domestic product fixed effect standardized Βeta coefficient [Std B] -0.03, 95% CI -0.05, -0.004). Individual-level income was more closely associated with sICAM-1 (Std B -0.04, 95% CI -0.06, -0.03) and fibrinogen (Std B -0.05, 95% CI -0.06, -0.03) than state-level conditions. We found associations between state-level socioeconomic conditions and hsCRP among healthy women. Personal household income was more closely associated with sICAM-1 and fibrinogen than state-level socioeconomic conditions. Additional research should examine these associations in other cohorts, and investigate what more-advantaged states do differently than less-advantaged states that may influence levels of cardiovascular inflammation among healthy women.
    BMC Public Health 03/2012; 12(1):211. DOI:10.1186/1471-2458-12-211 · 2.26 Impact Factor
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    • "It has been widely observed that SES is associated with frequency of cardiovascular disease. Both men and women of low socioeconomic position have increased risk of CVD morbidity and premature death (Nordstrom et al., 2004; Pollitt et al., 2005). In the past, an explanation of this effect was sought in interactions between genetic predisposition to the disease and unhealthy behavioural factors such as tobacco smoking, poor diet, lack of physical activity and obesity (Acton et al., 2004). "
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    ABSTRACT: It has been widely observed that socioeconomic status (SES) is associated with frequency of cardiovascular disease. Both men and women of low socioeconomic position have increased risk of cardiovascular disease morbidity and premature death. In this study the relationship between SES in childhood, and health status at the age of 50 years was examined. Socioeconomic status in childhood was measured using objective (father's educational level and number of children in the family) and subjective (self-assessed SES in childhood declared in early adulthood) indicators. Data from the Wroclaw Growth Study were completed when subjects were 50 years old, and information concerning health status was added. The results indicated that the objective, universally used measures of SES in childhood such as father's educational level and size of family did not show any essential relationships with health outcomes in adulthood, both for men and women. By contrast, retrospective, self-assessed SES (as better, average or worse as compared with peers) in childhood was significantly associated with the appearance of cardiovascular disease among women aged 50 years. Women who at the beginning of their adult life declared better socioeconomic condition in childhood were significantly healthier at the age of 50 years (OR=3.43; p=0.02). Moreover, this appeared to be independent of BMI, SES and life-style in adulthood. For men, retrospective self-assessed SES showed no relation to health status at the age of 50 years. The gender differences in the relationships between self-assessed SES in childhood and health status in adulthood are explained by possible selective premature mortality among men from lower childhood SES and/or sex differences in cognitive abilities.
    Journal of Biosocial Science 08/2007; 39(4):481-91. DOI:10.1017/S0021932006001799 · 0.98 Impact Factor
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