Spatial Inequities in Life Expectancy in Small Areas of Buenos Aires, Argentina 2015-2017.

Studies of life expectancy (LE) in small areas of cities are relatively common in high-income countries but rare in Latin American countries. Small-area estimation methods can help to describe and quantify inequities in LE between neighborhoods and their predictors. Our objective was to analyze the distribution and spatial patterning of LE across small areas of Ciudad Autónoma de Buenos Aires (CABA), Argentina, and its association with socioeconomic characteristics. As part of the SALURBAL project, we used georeferenced death certificates in 2015-2017 for CABA, Argentina. We used a spatial Bayesian Poisson model using the TOPALS method to estimate age- and sex-specific mortality rates. We used life tables to estimate LE at birth. We obtained data on neighborhood socioeconomic characteristics from the 2010 census and analyzed their associations. LE at birth was higher for women (median of across neighborhoods = 81.1 years) compared to men (76.7 years). We found a gap in LE of 9.3 (women) and 14.9 years (men) between areas with the highest and the lowest LE. Better socioeconomic characteristics were associated with higher LE. For example, mean differences in LE at birth in areas with highest versus lowest values of composite SES index were 2.79 years (95% CI: 2.30 to 3.28) in women and 5.61 years (95% CI: 4.98 to 6.24) in men. We found large spatial inequities in LE across neighborhoods of a large city in Latin America, highlighting the importance of place-based policies to address this gap.

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.

Patient characteristics and neighborhood attributes associated with hepatitis C screening and positivity in Philadelphia.

Among patients of an urban primary care network in Philadelphia with a universal hepatitis C virus (HCV) screening policy for patients born during 1945-1965, we examined whether being unscreened and HCV positivity were associated with attributes of the census tracts where patients resided, which we considered as proxies for social health determinants. For patients with at least one clinic visit between 2014 and mid-2017, we linked demographic and HCV screening information from electronic health records with metrics that described the census tracts where patients resided. We used generalized estimating equations to estimate adjusted relative risk ratios (aRRs) for being unscreened and HCV positive. Overall, 28% of 6,906 patients were unscreened. Black race, male gender, and residence in census tracts with relatively high levels of violent crime, low levels of educational attainment and household incomes, and evidence of residential segregation by Hispanic ethnicity were associated with lower aRRs for being unscreened. Among screened patients, 9% were HCV positive. Factors associated with lower risks of being unscreened were, in general, associated with higher HCV positivity. Attributes of census tracts where patients reside are probably less apparent to clinicians than patients' gender or race but might reflect unmeasured patient characteristics that affected screening practices, along with preconceptions regarding the likelihood of HCV infection based on prior screening observations or implicit biases. Approaching complete detection of HCV-infected people would be hastened by focusing on residents of census tracts with attributes associated with higher infection levels or, if known, higher infection levels directly.

Association between informal employment and depressive symptoms in 11 cities in Latin America.

Background: Mental health is an important contributor to the global burden of disease, and depression is the most prevalent mental disorder in Latin America and the Caribbean (LAC). Informal jobs, often characterized by precarious working conditions, low wages, and limited employment benefits, are also highly prevalent in LAC and may be associated with poorer mental health. Our study tests the association between informal employment and major depressive symptoms in LAC cities. Methods: We used individual-level data collected by the Development Bank of Latin America via their "Encuesta CAF" (ECAF) 2016, a cross-sectional household survey of 11 LAC cities (N = 5430). Depressive symptoms were measured using the 10-item Center for Epidemiologic Studies Short Depression Scale with possible total score ranging from 0 to 30. Scores were dichotomized, with a score > ‾ 16 indicating the presence of major depressive symptoms. Informal employment was defined based on self-reported lack of contribution to the social security system. We used generalized estimating equation (GEE) log-binomial models to estimate the association between informal employment and depressive symptoms overall and by gender. Models were adjusted for age, education, and household characteristics. Results: Overall, individuals employed in informal jobs had a 27% higher prevalence of major depressive symptoms (Prevalence Ratio [PR]: 1.27; 95% Confidence Interval [CI]: 1.00, 1.62) compared to those in formal jobs. The prevalence of depressive symptoms among individuals with informal jobs was higher compared to those with formal jobs in both women (PR: 1.36, 95% CI: 1.06, 1.74) and men (PR: 1.22; 95% CI: 0.90, 1.65). Conclusions: Informal employment in LAC was associated with a higher prevalence of major depressive symptoms. It is important to develop policies aiming at reducing informal jobs and increasing universal social protection for informal workers.

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.

Neighborhood Effects on Missed Appointments in a Large Urban Academic Multispecialty Practice.

BACKGROUND: Missed appointments diminish the continuity and quality of care. OBJECTIVE: To determine whether missing scheduled appointments is associated with characteristics of the populations in places where patients reside. DESIGN: Retrospective cross-sectional study using data extracted from electronic health records linked to population descriptors for each patient's census tract of residence. PATIENTS: A total of 58,981 patients ≥18 years of age with 275,682 scheduled appointments during 2014-2015 at a multispecialty outpatient practice. MAIN MEASURES: We used multinomial generalized linear mixed models to examine associations between the outcomes of scheduled appointments (arrived, canceled, or missed) and selected characteristics of the populations in patients' census tracts of residence (racial/ethnic segregation based on population composition, levels of poverty, violent crime, and perceived safety and social capital), controlling for patients' age, gender, type of insurance, and type of clinic service. KEY RESULTS: Overall, 17.5% of appointments were missed. For appointments among patients residing in census tracts in the highest versus lowest quartile for each population metric, adjusted odds ratios (aORs) for missed appointments were 1.27 (CI 1.19, 1.35) for the rate of violent crime, 1.27 (CI 1.20, 1.34) for the proportion Hispanic, 1.19 (CI 1.12, 1.27) for the proportion living in poverty, 1.13 (CI 1.05, 1.20) for the proportion of the census tract population that was Black, and 1.06 (CI 1.01, 1.11 for perceived neighborhood safety. CONCLUSIONS: Characteristics of the places where patients reside are associated with missing scheduled appointments, including high levels of racial/ethnic segregation, poverty, and violent crime and low levels of perceived neighborhood safety. As such, targeting efforts to improve access for patients living in such neighborhoods will be particularly important to address underlying social determinants of access to health care.

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.

Physical Disorders and Poor Self-Rated Health in Adults Living in Four Latin American Cities: A Multilevel Approach.

Considering that urban environments may affect self-rated health through behavioral and psychosocial mechanisms, the aim of this study was to investigate the association between self-rated health and perceived urban environment characteristics among adults living in four Latin American cities. Data is from a population-based survey by Development Bank of Latin America, encompassing adults between 20 and 60 years old in Buenos Aires, Lima, Mexico City, and Panama City. Self-rated health was measured using a single question and the response options were categorized as poor and good. The explanatory variables were empirical Bayes estimates of self-reported area physical disorder, social disorder, access to services, and access to leisure spaces derived from the survey. The covariates were: individual age, sex, education, wealth index, and length of residency in the neighborhood; and an area social environment index. Multilevel logistic regressions with two levels (individual and sub-city areas) were fitted. Poor self-rated health was reported by 34.73% (95% CI: 33.17 to 36.29) of the participants and was associated with physical disorder (OR = 1.16 per SD; 95% CI: 1.02 to 1.32). Our findings suggest that public policies to promote population health should consider area urban environment factors, especially those associated with disorder.

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.

Identifying neighborhood characteristics associated with diabetes and hypertension control in an urban African-American population using geo-linked electronic health records.

For health care providers, information on community-level social determinants of health is most valuable when it is specific to the populations and health outcomes for which they are responsible. Diabetes and hypertension are highly prevalent conditions whose management requires an interplay of clinical treatment and behavioral modifications that may be sensitive to community conditions. We used geo-linked electronic health records from 2016 of African American patients of a network of federally qualified health centers in Philadelphia, PA to examine cross-sectional associations between characteristics of patients' residential neighborhoods and hypertension and diabetes control (n = 1061 and n = 2633, respectively). Hypertension and diabetes control were defined to align with the Health Resources and Services Administration (HRSA) Uniform Data System (UDS) reporting requirements for HRSA-funded health centers. We examined associations with nine measures of neighborhood socioeconomic status (poverty, education, deprivation index), social environment (violent crime, perceived safety and social capital, racial segregation), and built environment (land-use mix, intersection density). In demographics-adjusted log-binomial regression models accounting for neighborhood-level clustering, poor diabetes and hypertension control were more common in highly segregated neighborhoods (i.e., high proportion of African American residents relative to the mean for Philadelphia; prevalence ratio = 1.27 [1.02-1.57] for diabetes, 1.22 [1.12-1.33] for hypertension) and less common in more walkable neighborhoods (i.e., higher retail land use). Neighborhood deprivation was also weakly associated with poor hypertension control. An important consideration in making geographic information actionable for providers is understanding how specific community-level determinants affect the patient population beyond individual-level determinants.

Personal and Neighborhood Attributes Associated with Cervical and Colorectal Cancer Screening in an Urban African American Population.

INTRODUCTION: Assessing individual social determinants of health in primary care might be complemented by consideration of population attributes in patients' neighborhoods. We studied associations between cervical and colorectal cancer screening and neighborhood attributes among an African American population in Philadelphia. METHODS: We abstracted demographic and cancer screening information from records of patients seen during 2006 at 3 federally qualified health centers and characterized patients' census tracts of residence by using census, survey, and other data to define population metrics for poverty, racial segregation, educational attainment, social capital, neighborhood safety, and violent crime. We used generalized estimating equations to obtain adjusted relative risks of screening associated with individual and census tract attributes. RESULTS: Among 1,708 patients for whom colorectal cancer screening was recommended, screening was up to date for 41%, and among 4,995 women for whom cervical cancer screening was recommended, screening was up to date for 75%. After controlling for age, sex (for colorectal cancer screening), insurance coverage, and clinic site, people living in the most racially segregated neighborhoods were nearly 10% more likely than others to be unscreened for colorectal cancer. Other census tract population attributes were not associated with differences in screening levels for either cancer. CONCLUSIONS: The association between lower rates of colorectal cancer screening and neighborhood racial segregation is consistent with known barriers to colonoscopy among African Americans combined with effects of segregation on health-related behaviors. Recognition of the association between segregation and lower colorectal cancer screening rates might be useful in informing and targeting community outreach to improve screening.

Spatial accessibility to pediatric primary care in Philadelphia: an area-level cross sectional analysis.

BACKGROUND: Pediatric primary care visits are a foundational element in the health maintenance of children. Differential access may be a driver of racial inequities in health. We hypothesized that pediatric primary care accessibility would be lowest in neighborhoods with higher proportion of non-Hispanic Black residents. METHODS: Annual ratios (2008-2016) of providers to pediatric population were calculated by census tract in Philadelphia, Pennsylvania. Marginal logistic regression was used to estimate the independent association between neighborhood racial composition and access to pediatric primary care controlling for confounders. RESULTS: In general, low access to care was associated with greater neighborhood disadvantage (e.g., SES, % poverty, % public insurance). After controlling for neighborhood indicators of disadvantage, risk of being in the lowest quintile of access significantly increased as the percent of non-Hispanic Black residents increased. CONCLUSION: A new measure of pediatric primary care accessibility demonstrates a persistent disparity in primary care access for predominantly non-Hispanic Black neighborhoods.

Neighborhood racial/ethnic segregation and BMI: A longitudinal analysis of the Multi-ethnic Study of Atherosclerosis.

BACKGROUND: Current knowledge regarding the relationship between segregation and body weight is derived mainly from cross-sectional data. Longitudinal studies are needed to provide stronger causal inference. METHODS: We use longitudinal data from the Multi-Ethnic Study of Atherosclerosis and apply an econometric fixed-effect strategy, which accounts for all time-invariant confounders, and compare results to conventional cross-sectional analyses. We examine the relationship between neighborhood-level racial/ethnic segregation, neighborhood poverty, and body mass index (BMI) separately for blacks, Hispanics, and whites. Segregation*gender interactions are included in all models. Neighborhood segregation was operationalized by the local Gi* statistic, which assesses the extent to which a neighborhood's racial/ethnic composition is under (Gi* statistic < 0) or over (Gi* statistic > 0) represented, given the composition in the broader (e.g., county) area. For black, Hispanic, and white stratified models, the Gi* statistic reflects the level of black, Hispanic, and white segregation, respectively. The Gi* statistic was scaled such that a unit change represents a 1.96 difference in the score. RESULTS: Cross-sectional models indicated higher segregation to be negatively associated with BMI for white females and positively associated for Hispanic females. No association was found for black females or males in general. In contrast, fixed-effect models adjusting for neighborhood poverty, higher segregation was positively associated with BMI for black females (coeff = 0.25 kg/m2; 95% CI = [0.03, 0.46]; p-value = 0.03) but negatively associated for Hispanic females (coeff = -0.17 kg/m2; 95% CI = [-0.33, -0.01]; p-value = 0.04) and Hispanic males (coeff = -0.20; 95% CI = [-0.39, -0.01]; p-value = 0.04). Further controls for socioeconomic factors fully explained the associations for Hispanics but not for black females. CONCLUSIONS: Fixed-effect results suggest that segregation's impacts might not be universally harmful, with possible null or beneficial impacts, depending on race/ethnicity. The persistent associations after accounting for neighborhood poverty indicate that the segregation-BMI link may operate through different pathways other than neighborhood poverty.

The Great Recession worsened blood pressure and blood glucose levels in American adults.

Longitudinal, individual-specific data from the Multi-Ethnic Study of Atherosclerosis (MESA) provide support for the hypothesis that the 2008 to 2010 Great Recession (GR) negatively impacted the health of US adults. Results further advance understanding of the relationship by (i) illuminating hypothesized greater negative impacts in population subgroups exposed to more severe impacts of the GR and (ii) explicitly controlling for confounding by individual differences in age-related changes in health over time. Analyses overcome limitations of prior work by (i) employing individual-level data that avoid concerns about ecological fallacy associated with prior reliance on group-level data, (ii) using four waves of data before the GR to estimate and control for underlying individual-level age-related trends, (iii) focusing on objective, temporally appropriate health outcomes rather than mortality, and (iv) leveraging a diverse cohort to investigate subgroup differences in the GR's impact. Innovative individual fixed-effects modeling controlling for individual-level age-related trajectories yielded substantively important insights: (i) significant elevations post-GR for blood pressure and fasting glucose, especially among those on medication pre-GR, and (ii) reductions in prevalence and intensity of medication use post-GR. Important differences in the effects of the GR are seen across subgroups, with larger effects among younger adults (who are likely still in the labor force) and older homeowners (whose declining home wealth likely reduced financial security, with less scope for recouping losses during their lifetime); least affected were older adults without a college degree (whose greater reliance on Medicare and Social Security likely provided more protection from the recession).

Reducing Cardiovascular Disparities Through Community-Engaged Implementation Research: A National Heart, Lung, and Blood Institute Workshop Report.

Cardiovascular disparities remain pervasive in the United States. Unequal disease burden is evident among population groups based on sex, race, ethnicity, socioeconomic status, educational attainment, nativity, or geography. Despite the significant declines in cardiovascular disease mortality rates in all demographic groups during the last 50 years, large disparities remain by sex, race, ethnicity, and geography. Recent data from modeling studies, linked micromap plots, and small-area analyses also demonstrate prominent variation in cardiovascular disease mortality rates across states and counties, with an especially high disease burden in the southeastern United States and Appalachia. Despite these continued disparities, few large-scale intervention studies have been conducted in these high-burden populations to examine the feasibility of reducing or eliminating cardiovascular disparities. To address this challenge, on June 22 and 23, 2017, the National Heart, Lung, and Blood Institute convened experts from a broad range of biomedical, behavioral, environmental, implementation, and social science backgrounds to summarize the current state of knowledge of cardiovascular disease disparities and propose intervention strategies aligned with the National Heart, Lung, and Blood Institute mission. This report presents the themes, challenges, opportunities, available resources, and recommended actions discussed at the workshop.

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.

The Impact of Neighborhoods on CV Risk.

Cardiovascular disease (CVD) continues to be the leading cause of death and a major source of health disparities in the Unites States and globally. Efforts to reduce CVD risk and eliminate cardiovascular health disparities have increasingly emphasized the importance of the social determinants of health. Neighborhood environments have emerged as a possible target for prevention and policy efforts. Hence there is a need to better understand the role of neighborhood environments in shaping cardiovascular risk. The MESA (Multi-Ethnic Study of Atherosclerosis) Neighborhood Study provided a unique opportunity to build a comprehensive place-based resource for investigations of associations between specific features of neighborhood physical and social environments and cardiovascular risk factors and outcomes. This review summarizes the approaches used to characterize residential neighborhood environments in the MESA cohort, provides an overview of key findings to date, and discusses challenges and opportunities in neighborhood health effects research. Results to date suggest that neighborhood physical and social environments are related to behavioral and biomedical risk factors for CVD and that cardiovascular prevention efforts may benefit from taking neighborhood context into account.

Associations of neighborhood socioeconomic and racial/ethnic characteristics with changes in survey-based neighborhood quality, 2000-2011.

We investigated the relationships between neighborhood socio-demographic characteristics (socioeconomic status [SES], percentage of Black residents, and percentage of Hispanic residents) and survey-based measures of the social environment (social cohesion, safety) and the physical environment (healthy food environment, walking environment) in six sites from 2000 through 2011. Neighborhood environments were patterned by area SES and racial/ethnic composition, such that higher SES and lower percentage minority neighborhoods had better physical and social environments. Increasing disparities over time were observed for some neighborhood environments. Further research should explore the role of neighborhood environments in maintaining or increasing social disparities in health.

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.

Disparities in physical activity resource availability in six US regions.

OBJECTIVE: We conducted an ecological study to determine physical activity resource availability overall and by sociodemographic groups in parts of six states (CA, IL, MD, MN, NC, NY). METHODS: Data on parks and recreational facilities were collected from 3 sources in 2009-2012. Three measures characterized park and recreational facility availability at the census tract level: presence of ≥1 resource, number of resources, and resource kernel density. Associations between resource availability and census tract characteristics (predominant racial/ethnic group, median income, and proportion of children and older adults) were estimated using linear, binomial, and zero-inflated negative binomial regression in 2014. Pooled and stratified analyses were conducted. RESULTS: The study included 7139 census tracts, comprising 9.5% of the 2010 US population. Overall the availability of parks and recreational facilities was lower in predominantly minority relative to non-Hispanic white census tracts. Low-income census tracts and those with a higher proportion of children had an equal or greater availability of park resources but fewer recreational facilities. Stratification revealed substantial variation in resource availability by site. CONCLUSION: The availability of physical activity resources varied by sociodemographic characteristics and across regions. Improved knowledge of resource distribution can inform strategies to provide equitable access to parks and recreational facilities.