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Associations Between Neighborhood Environment, Health Behaviors, and Mortality.

ABSTRACT: INTRODUCTION:Considering the joint association of neighborhood socioeconomic environment and individual-level health behaviors with health outcomes may help officials design effective disease prevention strategies. This study evaluates the joint influences of neighborhood socioeconomic environment and individual health behaviors on mortality in a cohort primarily comprising people with low individual-level SES. METHODS:The prospective Southern Community Cohort Study includes 77,896 white and African American participants recruited in the years 2002-2009; 55% of participants had a household income <$15,000 at baseline interview. Mortality from cancer (n=2,471), cardiovascular diseases (n=3,005), and all-causes (n=10,099) was identified from the National Death Index through December 31, 2013 (median follow-up, 8 years). Data were analyzed in 2016 and 2017. Associations were assessed between mortality, a neighborhood deprivation index composed of 11 census tract-level variables, five health behaviors, and a composite healthy lifestyle score. RESULTS:Living in a neighborhood with the greatest socioeconomic disadvantage was associated with higher all-cause mortality in both men (hazard ratio=1.41, 95% CI=1.27, 1.57) and women (hazard ratio=1.77, 95% CI=1.57, 2.00). Associations were attenuated after adjustment for individual-level SES and major risk factors (hazard ratio for men=1.09, 95% CI=0.98, 1.22, and hazard ratio for women=1.26, 95% CI=1.12, 1.42). The dose-response association between neighborhood disadvantage and mortality was less apparent among smokers. Nevertheless, individuals who lived in disadvantaged neighborhoods and had the unhealthiest lifestyle scores experienced the highest mortality. CONCLUSIONS:Disadvantaged neighborhood socioeconomic environments are associated with increased mortality in a cohort of individuals of low SES. Positive individual-level health behaviors may help negate the adverse effect of disadvantage on mortality.

SUBMITTER: Warren Andersen S

PROVIDER: S-EPMC5739075 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Associations Between Neighborhood Environment, Health Behaviors, and Mortality.

Warren Andersen Shaneda S Blot William J WJ Shu Xiao-Ou XO Sonderman Jennifer S JS Steinwandel Mark M Hargreaves Margaret K MK Zheng Wei W

American journal of preventive medicine 20180101 1

<h4>Introduction</h4>Considering the joint association of neighborhood socioeconomic environment and individual-level health behaviors with health outcomes may help officials design effective disease prevention strategies. This study evaluates the joint influences of neighborhood socioeconomic environment and individual health behaviors on mortality in a cohort primarily comprising people with low individual-level SES.<h4>Methods</h4>The prospective Southern Community Cohort Study includes 77,89 ...[more]

PMID: 29254556

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Project description:BackgroundThe VHA is the largest integrated US health system and is increasingly moving care into the communities where veterans reside. Veterans who utilize the VA for their care have worse health status than the general population. However, there is limited evidence about the association of neighborhood environment and health outcomes among veterans.ObjectivesThe primary aim of this study is to assess the relative contribution of neighborhood environment, health system, and individual characteristics to health status and mortality of veterans.MethodsInformation on personal socio-economic indicators, existing medical conditions and health status were obtained from baseline data from a multi-site, randomized trial of primary care patients (n = 15,889). The physical component scale (PCS) and mental component scale (MCS) summarized health status. Census tracts were used as proxies for neighborhoods. A summary score based on census tract data characterized the neighborhood socio-economic environment and walkability. Data were analyzed with multilevel hierarchical models. Analyses of health status were cross-sectional. Mortality analyses were longitudinal as participants were followed for an average of 722.5 days to ascertain vital status.ResultsNeighborhood SES was associated with PCS and MCS scores, controlling for individual socio-economic status, self-reported co-morbid disease, smoking status, and health care access. In the lowest versus highest quartiles of neighborhood SES, adjusted PCS scores were 34.4 vs. 35.4 (p < 0.05) and adjusted MCS scores were 46.2 versus 47.0 (p < 0.05). PCS score was also significantly associated with neighborhood walkability (p < 0.05). Mortality was lower for veterans living in neighborhoods with the highest decile neighborhood SES (HR 0.78, highest vs. lowest decile 95% CI 0.63, 0.97).ConclusionsVeterans living in lower SES neighborhoods have poorer health status and a higher risk of mortality, independent of individual characteristics and health care access. Neighborhood walkability was associated with higher PCS scores.

Project description:BackgroundAs the largest integrated US health system, the Veterans Health Administration (VHA) provides unique national data to expand knowledge about the association between neighborhood socioeconomic status (NSES) and health. Although living in areas of lower NSES has been associated with higher mortality, previous studies have been limited to higher-income, less diverse populations than those who receive VHA care.ObjectiveTo describe the association between NSES and all-cause mortality in a national sample of veterans enrolled in VHA primary care.DesignOne-year observational cohort of veterans who were alive on December 31, 2011. Data on individual veterans (vital status, and clinical and demographic characteristics) were abstracted from the VHA Corporate Data Warehouse. Census tract information was obtained from the US Census Bureau American Community Survey. Logistic regression was used to model the association between NSES deciles and all-cause mortality during 2012, adjusting for individual-level income and demographics, and accounting for spatial autocorrelation.ParticipantsVeterans who had vital status, demographic, and NSES data, and who were both assigned a primary care physician and alive on December 31, 2011 (n = 4,814,631).Main measuresCensus tracts were used as proxies for neighborhoods. A summary score based on census tract data characterized NSES. Veteran addresses were geocoded and linked to census tract NSES scores. Census tracts were divided into NSES deciles.Key resultsIn adjusted analysis, veterans living in the lowest-decile NSES tract were 10 % (OR 1.10, 95 % CI 1.07, 1.14) more likely to die than those living in the highest-decile NSES tract.ConclusionsLower neighborhood SES is associated with all-cause mortality among veterans after adjusting for individual-level socioeconomic characteristics. NSES should be considered in risk adjustment models for veteran mortality, and may need to be incorporated into strategies aimed at improving veteran health.

Project description:PurposeHispanic/Latino adults on the Texas-Mexico border have high rates of chronic disease. Neighborhoods can influence health, though there is a limited research on neighborhood environment and health in Hispanics/Latinos. The purpose of this study was to assess the relation of neighborhood environment with health variables in Hispanic/Latino adults, including physical activity [PA], depression, anxiety, and lab-assessed conditions (type 2 diabetes, metabolic syndrome, and chronic inflammation).MethodsParticipants were randomly-selected from a Hispanic/Latino cohort on the Texas-Mexico border. Neighborhood environment, self-reported PA, anxiety, and depression were assessed through questionnaires. Laboratory values determined Type 2 diabetes, metabolic syndrome, and C-reactive protein (CRP). We conducted multivariable linear and logistic regression analyses to assess the associations of neighborhood environment and health variables, controlling for covariates.ResultsParticipants (n = 495) were mostly females, without insurance. After controlling for covariates, crime (Adjusted Odds Ratio [AOR] = 1.59 (95%CI 1.06-2.38), no streetlights (AOR = 1.65, 95%CI 1.06-2.57), and traffic (AOR = 1.74, 95%CI 1.16-2.62) were all significantly associated with anxiety. Only traffic was significantly associated with depression (AOR = 1.61, 95%CI1.05-2.47). A lack of nearby shops (AOR = 0.57, 95%CI 0.38-0.84) and no one out doing PA (AOR = 0.53, 95% CI 0.34-0.83) were both significantly associated with lower odds of meeting PA guidelines. A lack of nearby shops was associated with a 26% increase in the CRP value (β = 0.26, 95%CI 0.04-0.47).DiscussionSeveral neighborhood environment variables were significantly associated with mental health, PA and CRP, though estimates were small. The neighborhood environment is a meaningful contextual variable to consider for health-related interventions in Hispanic/Latino adults, though more study is needed regarding the magnitude of the estimates.Trial registrationNCT01168765.

Project description:Objective To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI). Methods The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change. Highlights • Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed.• Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change.• There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.

Dataset Information

Associations Between Neighborhood Environment, Health Behaviors, and Mortality.

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Associations Between Neighborhood Environment, Health Behaviors, and Mortality.

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