Cumulative Experience of Neighborhood Walkability and Change in Weight and Waist Circumference in REGARDS.

Neighborhood walkability-features of the built environment that promote pedestrian activity-has been associated with greater physical activity and lower body mass index (BMI; calculated as weight (kg)/height (m)2) among neighborhood residents. However, much of the literature has been cross-sectional and only a few cohort studies have assessed neighborhood features throughout follow-up. Using data from the Reasons for Geographic and Racial Differences in Stroke Study (2003-2016) and a neighborhood walkability index (NWI) measured annually during follow-up, we assessed whether the cumulative experience of neighborhood walkability (NWI-years) predicted BMI and waist circumference after approximately 10 years of follow-up, controlling for these anthropometric measures at enrollment. Analyses were adjusted for individual-level sociodemographic covariates and the cumulative experience of neighborhood poverty rate and neighborhood greenspace coverage. Almost a third (29%) of participants changed address at least once during follow-up. The first change of residence, on average, brought the participants to neighborhoods with higher home values and lower NWI scores than their originating neighborhoods. Compared with those having experienced the lowest quartile of cumulative NWI-years, those who experienced the highest quartile had 0.83 lower BMI (95% confidence interval, -1.5, -0.16) and 1.07-cm smaller waist circumference (95% confidence interval, -1.96, -0.19) at follow-up. These analyses provide additional longitudinal evidence that residential neighborhood features that support pedestrian activity are associated with lower adiposity.

National trends and disparities in retail food environments in the USA between 1990 and 2014.

OBJECTIVE: To describe national disparities in retail food environments by neighbourhood composition (race/ethnicity and socio-economic status) across time and space. DESIGN: We examined built food environments (retail outlets) between 1990 and 2014 for census tracts in the contiguous USA (n 71 547). We measured retail food environment as counts of all food stores, all unhealthy food sources (including fast food, convenience stores, bakeries and ice cream) and healthy food stores (including supermarkets, fruit and vegetable markets) from National Establishment Time Series business data. Changes in food environment were mapped to display spatial patterns. Multi-level Poisson models, clustered by tract, estimated time trends in counts of food stores with a land area offset and independent variables population density, racial composition (categorised as predominantly one race/ethnicity (>60 %) or mixed), and inflation-adjusted income tertile. SETTING: The contiguous USA between 1990 and 2014. PARTICIPANTS: All census tracts (n 71 547). RESULTS: All food stores and unhealthy food sources increased, while the subcategory healthy food remained relatively stable. In models adjusting for population density, predominantly non-Hispanic Black, Hispanic, Asian and mixed tracts had significantly more destinations of all food categories than predominantly non-Hispanic White tracts. This disparity increased over time, predominantly driven by larger increases in unhealthy food sources for tracts which were not predominantly non-Hispanic White. Income and food store access were inversely related, although disparities narrowed over time. CONCLUSIONS: Our findings illustrate a national food landscape with both persistent and shifting spatial patterns in the availability of establishments across neighbourhoods with different racial/ethnic and socio-economic compositions.

Comparing effects of Euclidean buffers and network buffers on associations between built environment and transport walking: the Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Transport walking has drawn growing interest due to its potential to increase levels of physical activities and reduce reliance on vehicles. While existing studies have compared built environment-health associations between Euclidean buffers and network buffers, no studies have systematically quantified the extent of bias in health effect estimates when exposures are measured in different buffers. Further, prior studies have done the comparisons focusing on only one or two geographic regions, limiting generalizability and restricting ability to test whether direction or magnitude of bias are different by context. This study aimed to quantify the degree of bias in associations between built environment exposures and transport walking when exposures were operationalized using Euclidean buffers rather than network buffers in diverse contexts. METHODS: We performed a simulations study to systematically evaluate the degree of bias in associations between built environment exposures in Euclidean buffers and network buffers and transport walking, assuming network buffers more accurately captured true exposures. Additionally, we used empirical data from a multi-ethnic, multi-site cohort to compare associations between built environment amenities and walking for transport where built environment exposures were derived using Euclidean buffers versus network buffers. RESULTS: Simulation results found that the bias induced by using Euclidean buffer models was consistently negative across the six study sites (ranging from -80% to -20%), suggesting built environment exposures measured using Euclidean buffers underestimate health effects on transport walking. Percent bias was uniformly smaller for the larger 5 km scale than the 1 km and 0.25 km spatial scales, independent of site or built environment categories. Empirical findings aligned with the simulation results: built environment-health associations were stronger for built environment exposures operationalized using network buffers than using Euclidean buffers. CONCLUSION: This study is the first to quantify the extent of bias in the magnitude of the associations between built environment exposures and transport walking when the former are measured in Euclidean buffers vs. network buffers, informing future research to carefully conceptualize appropriate distance-based buffer metrics in order to better approximate real geographic contexts. It also helps contextualize existing research in the field that used Euclidean buffers when that were the only option. Further, this study provides an example of the uncertain geographic context problem.

Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology.

Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research.

Constructing Within-City Neighborhood Health Rankings in Philadelphia by Using Data From the 500 Cities Project.

INTRODUCTION: Profound geographic disparities in health exist in many US cities. Most reporting on these disparities is based on predetermined administrative districts that may not reflect true neighborhoods. We undertook a ranking project to describe health at the neighborhood level and used Philadelphia, Pennsylvania, as our case study. METHODS: To create neighborhood health rankings, we first divided the city into neighborhoods according to groups of contiguous census tracts. Modeling our ranking methods and indicators on the Robert Wood Johnson Foundation County Health Rankings, we gathered census tract-level data from the Centers for Disease Control and Prevention's 500 Cities Project and local sources and aggregated these data, as needed, to each neighborhood. We assigned composite scores and rankings for both health outcomes and health factors to each neighborhood. RESULTS: Scores for health outcomes and health factors were highly correlated. We found clusters of neighborhoods with low rankings in Philadelphia's northern, lower northeastern, western, and southwestern regions. We disseminated information on rankings throughout the city, including through a comprehensive webpage, public communication, and a museum exhibit. CONCLUSION: The Philadelphia neighborhood health rankings were designed to be accessible to people unfamiliar with public health, facilitating education on drivers of health in communities. Our methods can be used as a model for other cities to create and communicate data on within-city geographic health disparities.

Determinants of Residential Preferences Related to Built and Social Environments and Concordance between Neighborhood Characteristics and Preferences.

We explored associations between residential preferences and sociodemographic characteristics, the concordance between current neighborhood characteristics and residential preferences, and heterogeneity in concordance by income and race/ethnicity. Data came from a cross-sectional phone and mail survey of 3668 residents of New York City, Baltimore, Chicago, Los Angeles, St. Paul, and Winston Salem in 2011-12. Scales characterized residential preferences and neighborhood characteristics. Stronger preferences were associated with being older, female, non-White/non-Hispanic, and lower education. There was significant positive but weak concordance between current neighborhood characteristics and residential preferences (after controlling sociodemographic characteristics). Concordance was stronger for persons with higher income and for Whites, suggesting that residential self-selection effects are strongest for populations that are more advantaged.

Associations Between the Built Environment and Objective Measures of Sleep: The Multi-Ethnic Study of Atherosclerosis.

Although dense neighborhood built environments support increased physical activity and lower obesity, these features may also disturb sleep. Therefore, we sought to understand the association between the built environment and objectively measured sleep. From 2010 to 2013, we analyzed data from examination 5 of the Multi-Ethnic Study of Atherosclerosis, a diverse population from 6 US cities. We fit multilevel models that assessed the association between the built environment (Street Smart Walk Score, social engagement destinations, street intersections, and population density) and sleep duration or efficiency from 1-week wrist actigraphy in 1,889 individuals. After adjustment for covariates, a 1-standard-deviation increase in Street Smart Walk Score was associated with 23% higher odds of short sleep duration (≤6 hours; odds ratio = 1.2, 95% confidence interval: 1.0, 1.4), as well as shorter average sleep duration (mean difference = -8.1 minutes, 95% confidence interval: -12.1, -4.2). Results were consistent across other built environment measures. Associations were attenuated after adjustment for survey-based measure of neighborhood noise. Dense neighborhood development may have multiple health consequence. In promoting denser neighborhoods to increase walkability, it is important to also implement strategies that reduce the adverse impacts of this development on sleep, such as noise reductions efforts.

Associations of Neighborhood-Level Social Determinants of Health with Bacterial Infections in Young, Febrile Infants.

OBJECTIVE: To examine the sociodemographic characteristics of one population of young, febrile infants and identify associations between neighborhood-level social determinants of health (SDHs) with bacterial infections. STUDY DESIGN: This was a retrospective cross sectional study of all infants ≤90 days old with a temperature of ≥38°C who presented in 2014 to the emergency department of an urban children's hospital in a large east coast city. The primary outcome was the presence of a bacterial infection, defined as a positive urine, blood, or cerebrospinal fluid culture that was treated clinically as a pathogen. The home address of each infant was geocoded and linked to neighborhood data based on census tract. Neighborhood-level SDHs included deprivation index, median household income, poverty, childhood poverty, social capital, and crowded housing. Associations were estimated using generalized estimating equations and negative binomial regression analysis. Models were adjusted for age, prematurity, and race/ethnicity. RESULTS: Of 232 febrile infants, the median age was 54 days, 58% were male, 49% were Hispanic, and 88% had public health insurance; 31 infants (13.4%) had a bacterial infection. In the adjusted analyses, the risk of bacterial infection among infants from neighborhoods with high rates of childhood poverty was >3 times higher (relative risk, 3.16; 95% CI, 1.04-9.6) compared with infants from neighborhoods with low rates of childhood poverty. CONCLUSIONS: Our findings suggest that SDHs may be associated with bacterial infections in young, febrile infants. If confirmed in subsequent studies, the inclusion of SDHs in predictive tools may improve accuracy in detecting bacterial infections among young, febrile infants.

Neighborhood price of healthier food relative to unhealthy food and its association with type 2 diabetes and insulin resistance: The multi-ethnic study of atherosclerosis.

This study examined the association between the price of healthier food relative to unhealthy food and type 2 diabetes prevalence, incidence and insulin resistance (IR). Data came from the Multi-Ethnic Study of Atherosclerosis exam 5 administered 2010-2012 (exam 4, five years prior, was used only for diabetes incidence) and supermarket food/beverage prices derived from Information Resources Inc. For each individual, average price of a selection of healthier foods, unhealthy foods and their ratio was computed for supermarkets within 3miles of the person's residential address. Diabetes status was confirmed at each exam and IR was assessed via the homeostasis model assessment index. Multivariable-adjusted logistic, modified Poisson and linear regression models were used to model diabetes prevalence, incidence and IR, respectively as a function of price and covariates; 2353 to 3408 participants were included in analyses (depending on the outcome). A higher ratio of healthy-to-unhealthy neighborhood food price was associated with greater IR (4.8% higher HOMA-IR score for each standard deviation higher price ratio [95% CI -0.2% to 10.1%]) after adjusting for region, age, gender, race/ethnicity, family history of diabetes, income/wealth index, education, smoking status, physical activity, and neighborhood socioeconomic status. No association with diabetes incidence (relative risk=1.11, 95% CI 0.85 to 1.44) or prevalence (odds ratio=0.95, 95% CI 0.81 to 1.11) was observed. Higher neighborhood prices of healthier food relative to unhealthy food were positively associated with IR, but not with either diabetes outcome. This study provides new insight into the relationship between food prices with IR and diabetes.

Neighborhood Physical Environment and Changes in Body Mass Index: Results From the Multi-Ethnic Study of Atherosclerosis.

Longitudinal associations between neighborhood characteristics and body mass index (BMI; weight (kg)/height (m)2) were assessed from 2000 to 2011 among 5,919 participants in the Multi-Ethnic Study of Atherosclerosis. The perceived availability of healthy food and walking environment were assessed via surveys, and 1-mile (1.6-km) densities of supermarkets, fruit-and-vegetable stores, and recreational facilities were obtained through a commercial database. Econometric fixed-effects models were used to estimate the association between within-person changes in neighborhood characteristics and within-person change in BMI. In fully adjusted models, a 1-standard-deviation increase in the healthy food environment index was associated with a 0.16-kg/m2 decrease in BMI (95% confidence interval (CI): -0.27, -0.06) among participants with obesity at baseline. A 1-standard-deviation increase in the physical activity environment index was associated with 0.13-kg/m2 (95% CI: -0.24, -0.02) and 0.14-kg/m2 (95% CI: -0.27, -0.01) decreases in BMI for participants who were overweight and obese at baseline, respectively. Paradoxically, increases in the physical activity index were associated with BMI increases in persons who were normal-weight at baseline. This study provides preliminary longitudinal evidence that favorable changes in neighborhood physical environments are related to BMI reductions in obese persons, who comprise a substantial proportion of the US population.

Neighborhood Social Resources and Depressive Symptoms: Longitudinal Results from the Multi-Ethnic Study of Atherosclerosis.

The ways in which a neighborhood environment may affect depression and depressive symptoms have not been thoroughly explored. This study used longitudinal data from 5475 adults in the Multi-Ethnic Study of Atherosclerosis to investigate associations of time-varying depressive symptoms between 2000 and 2012 (measured using the 20-item Center for Epidemiologic Studies Depression Scale (CES-D)) with survey-based measures of neighborhood safety and social cohesion (both individual-level perceptions and neighborhood-level aggregates) and densities of social engagement destinations. Linear mixed models were used to examine associations of baseline cross-sectional associations and cumulative exposures with changes over time in CES-D. Econometric fixed effects models were utilized to investigate associations of within-person changes in neighborhood exposures with within-person changes in CES-D. Adjusting for relevant covariates, higher safety and social cohesion and greater density of social engagement destinations were associated with lower CES-D at baseline. Greater cumulative exposure to these features was not associated with progression of CES-D over 10 years. Within-person increases in safety and in social cohesion were associated with decreases in CES-D, although associations with cohesion were not statistically significant. Social elements of neighborhoods should be considered by community planners and public health practitioners to achieve optimal mental health.

Changes in the built environment and changes in the amount of walking over time: longitudinal results from the multi-ethnic study of atherosclerosis.

Lack of longitudinal research hinders causal inference on the association between the built environment and walking. In the present study, we used data from 6,027 adults in the Multi-Ethnic Study of Atherosclerosis who were 45-84 years of age at baseline to investigate the association of neighborhood built environment with trends in the amount of walking between 2000 and 2012. Walking for transportation and walking for leisure were assessed at baseline and at 3 follow-up visits (median follow-up = 9.15 years). Time-varying built environment measures (measures of population density, land use, number of destinations, bus access, and street connectivity) were created using geographic information systems. We used linear mixed models to estimate the associations between baseline levels of and a change in each built environment feature and a change in the frequency of walking. After adjustment for potential confounders, we found that higher baseline levels of population density, area zoned for retail, social destinations, walking destinations, and street connectivity were associated with greater increases in walking for transportation over time. Higher baseline levels of land zoned for residential use and distance to buses were associated with less pronounced increases (or decreases) in walking for transportation over time. Increases in the number of social destinations, the number of walking destinations, and street connectivity over time were associated with greater increases in walking for transportation. Higher baseline levels of both land zoned for retail and walking destinations were associated with greater increases in leisure walking, but no changes in built environment features were associated with leisure walking. The creation of mixed-use, dense developments may encourage adults to incorporate walking for transportation into their everyday lives.

Change in walking and body mass index following residential relocation: the multi-ethnic study of atherosclerosis.

OBJECTIVES: We investigated whether moving to neighborhoods with closer proximity of destinations and greater street connectivity was associated with more walking, a greater probability of meeting the "Every Body Walk!" campaign goals (≥ 150 minutes/week of walking), and reductions in body mass index (BMI). METHODS: We linked longitudinal data from 701 participants, who moved between 2 waves of the Multi-Ethnic Study of Atherosclerosis (2004-2012), to a neighborhood walkability measure (Street Smart Walk Score) for each residential location. We used fixed-effects models to estimate if changes in walkability resulting from relocation were associated with simultaneous changes in walking behaviors and BMI. RESULTS: Moving to a location with a 10-point higher Walk Score was associated with a 16.04 minutes per week (95% confidence interval [CI] = 5.13, 29.96) increase in transport walking, 11% higher odds of meeting Every Body Walk! goals through transport walking (adjusted odds ratio = 1.11; 95% CI = 1.02, 1.21), and a 0.06 kilogram per meters squared (95% CI = -0.12, -0.01) reduction in BMI. Change in walkability was not associated with change in leisure walking. CONCLUSIONS: Our findings illustrated the potential for neighborhood infrastructure to support health-enhancing behaviors and overall health of people in the United States.

Exploring the spatial scale effects of built environments on transport walking: Multi-Ethnic Study of Atherosclerosis.

We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations.

Longitudinal neighbourhood determinants with cognitive health and dementia disparities: protocol of the Multi-Ethnic Study of Atherosclerosis Neighborhoods and Aging prospective cohort study.

INTRODUCTION: The burden of Alzheimer's disease (AD) and AD-related dementias (ADRD) is increasing nationally and globally, with disproportionate impacts on lower-income, lower education and systematically marginalised older adults. Presence of inequalities in neighbourhood factors (eg, social context, physical and built environments) may affect risk of cognitive decline and be key for intervening on AD/ADRD disparities at the population level. However, existing studies are limited by a dearth of longitudinal, detailed neighbourhood measures linked to rich, prospective cohort data. Our main objective is to identify patterns of neighbourhood change related to prevalence of-and disparities in-cognitive decline and dementia. METHODS AND ANALYSES: We describe the process of collecting, processing and linking extensive neighbourhood data to the Multi-Ethnic Study of Atherosclerosis (MESA), creating a 25+ years dataset. Within the MESA parent study, the MESA Neighborhoods and Aging cohort study will characterise dynamic, longitudinal neighbourhood social and built environment variables relevant to cognition for residential addresses of MESA participants. This includes administering new surveys, expanding residential address histories, calculating new measures derived from spatial data and implementing novel deep learning algorithms on street-level imagery. Applying novel statistical techniques, we will examine associations of neighbourhood environmental characteristics with cognition and clinically relevant AD/ADRD outcomes. We will investigate determinants of disparities in outcomes by socioeconomic position and race/ethnicity and assess the contribution of neighbourhood environments to these disparities. This project will provide new evidence about pathways between neighbourhood environments and cognitive outcomes, with implications for policies to support healthy ageing. ETHICS AND DISSEMINATION: This project was approved by the University of Washington and Drexel University Institutional Review Boards (protocols #00009029 and #00014523, and #180900605). Data will be distributed through the MESA Coordinating Center. Findings will be disseminated in peer-reviewed scientific journals, briefs, presentations and on the participant website.

Intraurban socioeconomic inequalities in life expectancy: a population-based cross-sectional analysis in the city of Córdoba, Argentina (2015-2018).

OBJECTIVES: To evaluate variability in life expectancy at birth in small areas, describe the spatial pattern of life expectancy, and examine associations between small-area socioeconomic characteristics and life expectancy in a mid-sized city of a middle-income country. DESIGN: Cross-sectional, using data from death registries (2015-2018) and socioeconomic characteristics data from the 2010 national population census. PARTICIPANTS/SETTING: 40 898 death records in 99 small areas of the city of Córdoba, Argentina. We summarised variability in life expectancy at birth by using the difference between the 90th and 10th percentile of the distribution of life expectancy across small areas (P90-P10 gap) and evaluated associations with small-area socioeconomic characteristics by calculating a Slope Index of Inequality in linear regression. PRIMARY OUTCOME: Life expectancy at birth. RESULTS: The median life expectancy at birth was 80.3 years in women (P90-P10 gap=3.2 years) and 75.1 years in men (P90-P10 gap=4.6 years). We found higher life expectancies in the core and northwest parts of the city, especially among women. We found positive associations between life expectancy and better small-area socioeconomic characteristics, especially among men. Mean differences in life expectancy between the highest versus the lowest decile of area characteristics in men (women) were 3.03 (2.58), 3.52 (2.56) and 2.97 (2.31) years for % adults with high school education or above, % persons aged 15-17 attending school, and % households with water inside the dwelling, respectively. Lower values of % overcrowded households and unemployment rate were associated with longer life expectancy: mean differences comparing the lowest versus the highest decile were 3.03 and 2.73 in men and 2.57 and 2.34 years in women, respectively. CONCLUSION: Life expectancy is substantially heterogeneous and patterned by socioeconomic characteristics in a mid-sized city of a middle-income country, suggesting that small-area inequities in life expectancy are not limited to large cities or high-income countries.

Healthy food retail availability and cardiovascular mortality in the United States: a cohort study.

OBJECTIVES: We investigated the association of healthy food retail presence and cardiovascular mortality, controlling for sociodemographic characteristics. This association could inform efforts to preserve or increase local supermarkets or produce market availability. DESIGN: Cohort study, combining Mortality Disparities in American Communities (individual-level data from 2008 American Community Survey linked to National Death Index records from 2008 to 2015) and retail establishment data. SETTING: Across the continental US area-based sociodemographic and retail characteristics were linked to residential location by ZIP code tabulation area (ZCTA). Sensitivity analyses used census tracts instead, restricted to urbanicity or county-based strata, or accounted for non-independence using frailty models. PARTICIPANTS: 2 753 000 individuals age 25+ living in households with full kitchen facilities, excluding group quarters. PRIMARY AND SECONDARY OUTCOME MEASURES: Cardiovascular mortality (primary) and all-cause mortality (secondary). RESULTS: 82% had healthy food retail (supermarket, produce market) within their ZCTA. Density of such retail was correlated with density of unhealthy food sources (eg, fast food, convenience store). Healthy food retail presence was not associated with reduced cardiovascular (HR: 1.03; 95% CI 1.00 to 1.07) or all-cause mortality (HR: 1.05; 95% CI 1.04 to 1.06) in fully adjusted models (with adjustment for gender, age, marital status, nativity, Black race, Hispanic ethnicity, educational attainment, income, median household income, population density, walkable destination density). The null finding for cardiovascular mortality was consistent across adjustment strategies including minimally adjusted models (individual demographics only), sensitivity analyses related to setting, and across gender or household type strata. However, unhealthy food retail presence was associated with elevated all-cause mortality (HR: 1.15; 95% CI 1.11 to 1.20). CONCLUSIONS: In this study using food establishment locations within administrative areas across the USA, the hypothesised association of healthy food retail availability with reduced cardiovascular mortality was not supported; an association of unhealthy food retail presence with higher mortality was not specific to cardiovascular causes.

Longitudinal Associations of Neighborhood Crime and Perceived Safety With Blood Pressure: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: High neighborhood crime and low perceptions of safety may influence blood pressure (BP) through chronic stress. Few studies have examined these associations using longitudinal data. METHODS: We used longitudinal data from 528 participants of the Multi-Ethnic Study of Atherosclerosis (aged 45-84, nonhypertensive at baseline) who lived in Chicago, Illinois. We examined associations of changes in individual-level perceived safety, aggregated neighborhood-level perceived safety, and past-year rates of police-recorded crime in a 1, ½, or » mile buffer per 1,000 population with changes in systolic and diastolic BPs using fixed-effects linear regression. BP was measured five times between 2000 and 2012 and was adjusted for antihypertensive medication use (+10 mm Hg added to systolic and +5 mm Hg added to diastolic BP for participants on medication). Models were adjusted for time-varying sociodemographic and health-related characteristics and neighborhood socioeconomic status. We assessed differences by sex. RESULTS: A standard deviation increase in individual-level perceived safety was associated with a 1.54 mm Hg reduction in systolic BP overall (95% confidence interval [CI]: 0.25, 2.83), and with a 1.24 mm Hg reduction in diastolic BP among women only (95% CI: 0.37, 2.12) in adjusted models. Increased neighborhood-level safety was not associated with BP change. An increase in police-recorded crime was associated with a reduction in systolic and diastolic BPs among women only, but results were sensitive to neighborhood buffer size. CONCLUSIONS: Results suggest individual perception of neighborhood safety may be particularly salient for systolic BP reduction relative to more objective neighborhood exposures.

Cross-sectional and longitudinal associations of neighbourhood social environment and smoking behaviour: the multiethnic study of atherosclerosis.

BACKGROUND: Social features of neighbourhood environments may influence smoking by creating a stressful environment or by buffering stress through social cohesion. However, the association of the overall neighbourhood social environment (NSE) with smoking, and the association of specific neighbourhood social factors with change in smoking behaviour over time, has rarely been examined. METHODS: This study included 5856 adults aged 45-84 years from the Multi-Ethnic Study of Atherosclerosis (2000-2012, average follow-up: 7.8 years). Outcomes included current smoking status and smoking intensity (average number of cigarettes smoked per day among baseline smokers). NSE was assessed as a composite score composed of aesthetic quality, safety and social cohesion scales (derived from neighbourhood surveys). Generalised linear mixed models evaluated the association of baseline NSE (composite score and individual scales) with current smoking (modified Poisson models) and smoking intensity (negative binomial models) cross-sectionally and longitudinally. RESULTS: Each SD increase in baseline NSE composite score was associated with 13% lower prevalence of smoking at baseline (adjusted prevalence ratio (aPR) 0.87 (95% CI 0.78 to 0.98). Neighbourhood safety and aesthetic quality were similarly associated with lower smoking prevalence (aPR 0.87 (0.78 to 0.97) and aPR 0.87 (0.77 to 0.99), respectively) but the association with social cohesion was weaker or null. No significant associations were observed for smoking intensity among baseline smokers. Baseline NSE was not associated with changes in smoking risk or intensity over time. CONCLUSIONS: Results suggest that neighbourhood social context influences whether older adults smoke, but does not promote smoking cessation or reduction over time.

Spatially Modelling the Association Between Access to Recreational Facilities and Exercise: The 'Multi-Ethnic Study of Atherosclerosis'.

Numerous studies have investigated the relationship between the built environment and physical activity. However these studies assume that these relationships are invariant over space. In this study, we introduce a novel method to analyze the association between access to recreational facilities and exercise allowing for spatial heterogeneity. In addition, this association is studied before and after controlling for crime, a variable that could explain spatial heterogeneity of associations. We use data from the Chicago site of the Multi-Ethnic Study of Atherosclerosis of 781 adults aged 46 years and over. A spatially varying coefficient Tobit regression model is implemented in the Bayesian setting to allow for the association of interest to vary over space. The relationship is shown to vary over Chicago, being positive in the south but negative or null in the north. Controlling for crime weakens the association in the south with little change observed in northern Chicago. The results of this study indicate that spatial heterogeneity in associations of environmental factors with health may vary over space and deserve further exploration.