Elsevier

Health & Place

Volume 44, March 2017, Pages 61-69
Health & Place

Neighborhoods and racial/ethnic differences in ideal cardiovascular health (the Multi-Ethnic Study of Atherosclerosis)

https://doi.org/10.1016/j.healthplace.2017.01.005Get rights and content

Highlights

  • Whites were 3 times more likely to have ideal CVH compared to blacks and Hispanics.

  • Neighborhood adjustment resulted in modest reductions in racial/ethnic differences.

  • Study results were generally robust across analytic approach.

Abstract

Using data from the Multi-Ethnic Study of Atherosclerosis baseline sample from 2000 to 2002 (N=5263; mean age=62) we examined cross-sectional racial/ethnic differences in ideal CVH, defined by the American Heart Association 2020 Impact Goals as a summary measure of ideal levels of blood pressure, fasting glucose, cholesterol, body mass index, diet, physical activity, and smoking. Using three different analytical approaches, we examined differences before and after adjustment for neighborhood socioeconomic, physical, and social environments. Significant racial/ethnic differences were present for all indicators of ideal CVH (excluding physical activity). Additional adjustments for neighborhood factors produced modest reductions in racial/ethnic differences. Future research is necessary to better understand the impact of neighborhood context on health disparities using longitudinal study designs.

Introduction

Persistent and pervasive racial/ethnic differences in health are a major public health concern (Institute of Medicine (US) Commitee on the Review and Assessment of the NIH's Strategic Research Plan and Budget to Reduce and Ultimately Eliminate Health Disparities, 2006, Kelley et al., 2005, Smedley et al., 2003). Racial/ethnic differences in the prevalence of cardiovascular disease (CVD) risk factors and incidence of and mortality due to cardiovascular diseases have been well documented, with blacks disproportionately burdened by adverse outcomes (Go et al., 2014, Mensah et al., 2005). Underlying causes of these differences remain poorly understood, but are most likely generated by multifactorial and multilevel causes that occur over the life-course. Much of the extant literature has focused on individual-level risk factors as explanations for racial/ethnic disparities (genetic, biological, socioeconomic, and psychosocial) (Kramer et al., 2004, Mensah and Dunbar, 2006, Safford et al., 2012). However, more attention has recently been placed on contextual factors such as neighborhood environments.

The increased interest in the intersection of race/ethnicity, neighborhood, and health has emerged in part from the increasing interest in the effects of neighborhoods on health generally. Studies have shown that living in socioeconomically disadvantaged neighborhoods is associated with increased morbidity and mortality, independent of individual-level factors (Borrell et al., 2004, Pickett and Pearl, 2001, Truong and Ma, 2006), and some of the most consistent evidence is from the area of cardiovascular disease (CVD) outcomes. (Borrell et al., 2004, Chaix, 2009, Diez Roux, 2003, Morenoff et al., 2007, Mujahid et al., 2011, Pickett and Pearl, 2001). In the area of CVD, studies have also shown that living in neighborhoods with poor physical environments (e.g. more unhealthy foods on average and fewer opportunities for physical activity) and social environments (e.g. less safety and social cohesion) are associated with increased risk of CVD risk factors such as obesity, diabetes, and hypertension, and fatal and non-fatal CVD (Christine et al., 2015, Diez Roux et al., 2016, Kaiser et al., 2016, Kershaw et al., 2015). Studies have also documented that blacks and other racial/ethnic minorities disproportionately reside in neighborhoods that are socioeconomically disadvantaged, and have poor access to health promoting resources. Combined, the aforementioned supports the hypothesis that neighborhood environments may be one underlying cause of racial/ethnic disparities in health. However, there is little empiric investigation explicitly testing this notion (Do et al., 2007, Dubowitz et al., 2008b, Morenoff et al., 2007, Mujahid et al., 2011, Robert and Reither, 2004).

Studies that have empirically investigated the contribution of neighborhood environments to racial/ethnic differences in health have most consistently examined estimates of differences before and after adjustment for neighborhood environments in a multivariable regression model without an explicit discussion of the major challenges and limitations in this approach (Do et al., 2007, Dubowitz et al., 2008b, Mujahid et al., 2011, Robert and Reither, 2004). These challenges include how best to: deal with the non-independence of observations within neighborhoods (Hubbard et al., 2010, Subramanian and O'Malley, 2010), account for the neighborhood context when all relevant factors may not be measured in a given study, and account for insufficient within-neighborhood sample size and variation in exposures and outcomes. A recent review by Schempf et al. (Schempf and Kaufman, 2012) provides an in-depth discussion of these issues, a comparison of analytic approaches that may address these issues, and compares the strengths and limitations of each analytic approach. Studies providing similar comparisons across analytic approaches remain scarce in the literature. (Morenoff et al., 2007, Schempf and Kaufman, 2012).

Given the increased attention to and importance of primordial prevention, as underscored by the recent American Heart Association 2020 Strategic Impact Goals to reduce cardiovascular mortality by 20% and increase ideal cardiovascular health by 20% (Lloyd-Jones et al., 2010), exploring the contribution of neighborhood environments to racial/ethnic differences in CVD risk in a multi-ethnic study is timely (Havranek et al., 2015). Thus, the overall goal of this study was to determine if cross-sectional racial/ethnic differences in ideal cardiovascular health (CVH) indicators were reduced after adjustment for neighborhood environments, and if results were robust to statistical methods of neighborhood adjustment.

Section snippets

Study population

MESA is a prospective study of 6,814 adults of diverse racial/ethnic backgrounds (self-identified race/ethnicity as non-Hispanic white, non-Hispanic black, Hispanic, and non-Hispanic Chinese) from six study sites (Los Angeles County, California; Chicago, Illinois; Baltimore City and County, Maryland; St. Paul, Minnesota; Forsyth County, North Carolina; New York City, New York) (Bild et al., 2002). Study participants were 45–84 years of age and free from clinical cardiovascular disease at

Results

Among the 6191 MESA Neighborhood participants that provided consent to participate in the MESA Neighborhood Study, we excluded 728 Chinese participants for whom sample sizes were too small to examine neighborhood context. Additional exclusions included address errors (N=133) and missing information on study covariates (N=67) for a final analytic sample of N=5,263 representing 1033 neighborhoods with an average of 5 study participants per neighborhood (range 1–250). Among this analytic sample,

Discussion

In a multi-ethnic cohort of middle-aged adults, we found significant black-white and Hispanic-white differences for all ideal health factors (blood pressure, cholesterol, and glucose), three of four ideal health behaviors (diet, body mass index, and smoking) and all ideal CVH summary measures (health factors, health behaviors, and overall ideal cardiovascular health), independent of sociodemographic characteristics. Adjustment for neighborhood context slightly reduced racial/ethnic differences,

Acknowledgements

This research was supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-RR-024156 and UL1-RR-025005 from NCRR and R01 HL071759 from National Heart, Lung, and Blood Institute at the National Institutes of Health. Dr. Mujahid is funded by the National Heart, Lung, and Blood Institute of the National Institutes of Health, grant 5K01HL115494. The findings and conclusions in this report are those of the author(s) and do not

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