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Unequal Exposure or Unequal Vulnerability? Contributions of Neighborhood Conditions and Cardiovascular Risk Factors to Socioeconomic Inequality in Incident Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis.

ABSTRACT: Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

SUBMITTER: Hussein M

PROVIDER: S-EPMC6030985 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe extent to which physical and social attributes of neighborhoods play a role in childhood asthma remains understudied.ObjectiveTo examine associations of neighborhood-level opportunity and social vulnerability measures with childhood asthma incidence.Design, setting, and participantsThis cohort study used data from children in 46 cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) Program between January 1, 1995, and August 31, 2022. Participant inclusion required at least 1 geocoded residential address from birth and parent or caregiver report of a physician's diagnosis of asthma. Participants were followed up to the date of asthma diagnosis, date of last visit or loss to follow-up, or age 20 years.ExposuresCensus tract-level Child Opportunity Index (COI) and Social Vulnerability Index (SVI) at birth, infancy, or early childhood, grouped into very low (<20th percentile), low (20th to <40th percentile), moderate (40th to <60th percentile), high (60th to <80th percentile), or very high (≥80th percentile) COI or SVI.Main outcomes and measuresThe main outcome was parent or caregiver report of a physician's diagnosis of childhood asthma (yes or no). Poisson regression models estimated asthma incidence rate ratios (IRRs) associated with COI and SVI scores at each life stage.ResultsThe study included 10 516 children (median age at follow-up, 9.1 years [IQR, 7.0-11.6 years]; 52.2% male), of whom 20.6% lived in neighborhoods with very high COI and very low SVI. The overall asthma incidence rate was 23.3 cases per 1000 child-years (median age at asthma diagnosis, 6.6 years [IQR, 4.1-9.9 years]). High and very high (vs very low) COI at birth, infancy, or early childhood were associated with lower subsequent asthma incidence independent of sociodemographic characteristics, parental asthma history, and parity. For example, compared with very low COI, the adjusted IRR for asthma was 0.87 (95% CI, 0.75-1.00) for high COI at birth and 0.83 (95% CI, 0.71-0.98) for very high COI at birth. These associations appeared to be attributable to the health and environmental and the social and economic domains of the COI. The SVI during early life was not significantly associated with asthma incidence. For example, compared with a very high SVI, the adjusted IRR for asthma was 0.88 (95% CI, 0.75-1.02) for low SVI at birth and 0.89 (95% CI, 0.76-1.03) for very low SVI at birth.ConclusionsIn this cohort study, high and very high neighborhood opportunity during early life compared with very low neighborhood opportunity were associated with lower childhood asthma incidence. These findings suggest the need for future studies examining whether investing in health and environmental or social and economic resources in early life would promote health equity in pediatric asthma.

Project description:IMPORTANCE:Neighborhood environments may influence the risk for developing type 2 diabetes mellitus (T2DM), but, to our knowledge, no longitudinal study has evaluated specific neighborhood exposures. OBJECTIVE:To determine whether long-term exposures to neighborhood physical and social environments, including the availability of healthy food and physical activity resources and levels of social cohesion and safety, are associated with incident T2DM during a 10-year period. DESIGN, SETTING, AND PARTICIPANTS:We used data from the Multi-Ethnic Study of Atherosclerosis, a population-based cohort study of adults aged 45 to 84 years at baseline (July 17, 2000, through August 29, 2002). A total of 5124 participants free of T2DM at baseline underwent 5 clinical follow-up examinations from July 17, 2000, through February 4, 2012. Time-varying measurements of neighborhood healthy food and physical activity resources and social environments were linked to individual participant addresses. Neighborhood environments were measured using geographic information system (GIS)- and survey-based methods and combined into a summary score. We estimated hazard ratios (HRs) of incident T2DM associated with cumulative exposure to neighborhood resources using Cox proportional hazards regression models adjusted for age, sex, income, educational level, race/ethnicity, alcohol use, and cigarette smoking. Data were analyzed from December 15, 2013, through September 22, 2014. MAIN OUTCOMES AND MEASURES:Incident T2DM defined as a fasting glucose level of at least 126 mg/dL or use of insulin or oral antihyperglycemics. RESULTS:During a median follow-up of 8.9 years (37,394 person-years), 616 of 5124 participants (12.0%) developed T2DM (crude incidence rate, 16.47 [95% CI, 15.22-17.83] per 1000 person-years). In adjusted models, a lower risk for developing T2DM was associated with greater cumulative exposure to indicators of neighborhood healthy food (12%; HR per interquartile range [IQR] increase in summary score, 0.88 [95% CI, 0.79-0.98]) and physical activity resources (21%; HR per IQR increase in summary score, 0.79 [95% CI, 0.71-0.88]), with associations driven primarily by the survey exposure measures. Neighborhood social environment was not associated with incident T2DM (HR per IQR increase in summary score, 0.96 [95% CI, 0.88-1.07]). CONCLUSIONS AND RELEVANCE:Long-term exposure to residential environments with greater resources to support physical activity and, to a lesser extent, healthy diets was associated with a lower incidence of T2DM, although results varied by measurement method. Modifying neighborhood environments may represent a complementary, population-based approach to prevention of T2DM, although further intervention studies are needed.

Project description:AimWe assess the improvement in discrimination afforded by the addition of the computed tomography risk markers thoracic aorta calcium (TAC), aortic valve calcification (AVC), mitral annular calcification (MAC), pericardial adipose tissue volume (PAT), and liver attenuation (LA) to the Framingham risk score (FRS) + coronary artery calcium (CAC) for incident coronary heart disease (CHD) and incident cerebrovascular disease (CVD) in a multiethnic cohort.Methods and resultsA total of 5745 participants were enrolled, with 2710 at intermediate Framingham risk, 210 CVD events, and 155 CHD events). Over 9 years of follow up, 251 had adjudicated CHD, 346 had CVD events, and 321 died. The data were analysed using Cox proportional hazard, receiver operator curve (ROC), and net reclassification improvement (NRI) analyses. In the whole cohort and also when the analysis was restricted to only the intermediate-risk participants, CAC, TAC, AVC, and MAC were all significantly associated with incident CVD, incident CHD, and mortality, and CAC had the strongest association. When added to the FRS, CAC had the highest area under the curve (AUC) for the prediction of incident CVD and incident CHD; LA had the least. The addition of TAC, AVC, MAC, PAT, and LA to FRS + CAC all resulted in a significant reduction in AUC for incident CHD (0.712 vs. 0.646, 0.655, 0.652, 0.648, and 0.569; all p < 0.01, respectively) in participants with intermediate FRS. The addition of CAC to FRS resulted in an NRI of 0.547 for incident CHD in the intermediate-risk group. The NRI when TAC, AVC, MAC, PAT, and LA were added to FRS + CAC were 0.024, 0.026, 0.019, 0.012, and 0.012, respectively, for incident CHD in the intermediate-risk group. Similar results were obtained for incident CVD in the intermediate-risk group and also when the whole cohort was used instead of the intermediate FRS group.ConclusionsThe addition of CAC to the FRS provides superior discrimination especially in intermediate-risk individuals compared with the addition of TAC, AVC, MAC, PAT, or LA for incident CVD and incident CHD. Compared with FRS + CAC, the addition of TAC, AVC, MAC, PAT, or LA individually to FRS + CAC worsens the discrimination for incident CVD and incident CHD. These risk markers are unlikely to be useful for improving cardiovascular risk prediction.

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Unequal Exposure or Unequal Vulnerability? Contributions of Neighborhood Conditions and Cardiovascular Risk Factors to Socioeconomic Inequality in Incident Cardiovascular Disease in the Multi-Ethnic Study of Atherosclerosis.

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