Spatial Patterning of Spontaneous and Medically Indicated Preterm Birth in Philadelphia.

Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008-2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities.

Changes in physical activity after joining a bikeshare program: a cohort of new bikeshare users.

BACKGROUND: There are hundreds of bikeshare programs worldwide, yet few health-related evaluations have been conducted. We enrolled a cohort of new bikeshare members in Philadelphia (Pennsylvania, USA) to assess whether within-person moderate and vigorous physical activity (MVPA) increased with higher use of the program and whether effects differed for vulnerable sub-groups. METHODS: During 2015-2018, 1031 new members completed baseline and one-year follow-up online surveys regarding their personal characteristics and past 7-day MVPA minutes per week (minutes per week with- and without walking). Participants were linked to their bikeshare trips to objectively assess program use. Negative binomial (for continuous outcomes) and multinomial (for categorical outcomes) regression adjusted for person characteristics (socio-demographics, health), weather, biking-infrastructure, and baseline biking. RESULTS: Participant median age was 30, 25% were of Black or Latino race/ethnicity, and 30% were socioeconomically disadvantaged. By follow-up, personal bike ownership increased and 75% used bikeshare, although most used it infrequently. Per 10 day change in past year (PY) bikeshare use, non-walking MVPA min/wk increased 3% (roughly 6 min/wk, P < 0.014). More days of bikeshare was also associated with change from inactive to more active (odds ratio for ≥ 15 days in PY vs. no bikeshare use 1.80, CI 1.05-3.09, P < 0.03). Results were consistent across vulnerable sub-groups. In general, impacts on MVPA were similar when exposure was personal bike or bikeshare. CONCLUSIONS: Bikeshare facilitated increases in cycling, slightly increased non-walking MVPA, and showed potential for activating inactive adults; however, for larger program impact, members will need to use it more frequently.

Associations between high ambient temperatures and asthma exacerbation among children in Philadelphia, PA: a time series analysis.

OBJECTIVES: High ambient temperatures may contribute to acute asthma exacerbation, a leading cause of morbidity in children. We quantified associations between hot-season ambient temperatures and asthma exacerbation in children ages 0-18 years in Philadelphia, PA. METHODS: We created a time series of daily counts of clinical encounters for asthma exacerbation at the Children's Hospital of Philadelphia linked with daily meteorological data, June-August of 2011-2016. We estimated associations between mean daily temperature (up to a 5-day lag) and asthma exacerbation using generalised quasi-Poisson distributed models, adjusted for seasonal and long-term trends, day of the week, mean relative humidity,and US holiday. In secondary analyses, we ran models with adjustment for aeroallergens, air pollutants and respiratory virus counts. We quantified overall associations, and estimates stratified by encounter location (outpatient, emergency department, inpatient), sociodemographics and comorbidities. RESULTS: The analysis included 7637 asthma exacerbation events. High mean daily temperatures that occurred 5 days before the index date were associated with higher rates of exacerbation (rate ratio (RR) comparing 33°C-13.1°C days: 1.37, 95% CI 1.04 to 1.82). Associations were most substantial for children ages 2 to <5 years and for Hispanic and non-Hispanic black children. Adjustment for air pollutants, aeroallergens and respiratory virus counts did not substantially change RR estimates. CONCLUSIONS: This research contributes to evidence that ambient heat is associated with higher rates of asthma exacerbation in children. Further work is needed to explore the mechanisms underlying these associations.

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.

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.

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.

Direct and Indirect Associations Between the Built Environment and Leisure and Utilitarian Walking in Older Women.

BACKGROUND: The built environment predicts walking in older adults, but the degree to which associations between the objective built environment and walking for different purposes are mediated by environmental perceptions is unknown. PURPOSE: We examined associations between the neighborhood built environment and leisure and utilitarian walking and mediation by the perceived environment among older women. METHODS: Women (N = 2732, M age = 72.8 ± 6.8 years) from Massachusetts, Pennsylvania, and California completed a neighborhood built environment and walking survey. Objective population and intersection density and density of stores and services variables were created within residential buffers. Perceived built environment variables included measures of land use mix, street connectivity, infrastructure for walking, esthetics, traffic safety, and personal safety. Regression and bootstrapping were used to test associations and indirect effects. RESULTS: Objective population, stores/services, and intersection density indirectly predicted leisure and utilitarian walking via perceived land use mix (odds ratios (ORs) = 1.01-1.08, 95 % bias corrected and accelerated confidence intervals do not include 1). Objective density of stores/services directly predicted ≥150 min utilitarian walking (OR = 1.11; 95% CI = 1.02, 1.22). Perceived land use mix (ORs = 1.16-1.44) and esthetics (ORs = 1.24-1.61) significantly predicted leisure and utilitarian walking, CONCLUSIONS: Perceived built environment mediated associations between objective built environment variables and walking for leisure and utilitarian purposes. Interventions for older adults should take into account how objective built environment characteristics may influence environmental perceptions and walking.

Effects of Proximity to Supermarkets on a Randomized Trial Studying Interventions for Obesity.

OBJECTIVES: To determine whether proximity to a supermarket modified the effects of an obesity intervention. METHODS: We examined 498 children aged 6 to 12 years with a body mass index (BMI) at or above the 95th percentile participating in an obesity trial in Massachusetts in 2011 to 2013. The practice-based interventions included computerized clinician decision support plus family self-guided behavior change or health coaching. Outcomes were 1-year change in BMI z-score, sugar-sweetened beverage intake, and fruit and vegetable intake. We examined distance to the closest supermarket as an effect modifier. RESULTS: Distance to supermarkets was an effect modifier of 1-year change in BMI z-score and fruit and vegetable intake but not sugar-sweetened beverage intake. With each 1-mile shorter distance to a supermarket, intervention participants increased their fruit and vegetable intake by 0.29 servings per day and decreased their BMI z-score by -0.04 units relative to controls. CONCLUSIONS: Living closer to a supermarket is associated with greater improvements in fruit and vegetable intake and weight status in an obesity intervention.

The role of neighborhood characteristics and the built environment in understanding racial/ethnic disparities in childhood obesity.

BACKGROUND: Childhood obesity prevalence remains high and racial/ethnic disparities may be widening. Studies have examined the role of health behavioral differences. Less is known regarding neighborhood and built environment mediators of disparities. The objective of this study was to examine the extent to which racial/ethnic disparities in elevated child body mass index (BMI) are explained by neighborhood socioeconomic status (SES) and built environment. METHODS: We collected and analyzed race/ethnicity, BMI, and geocoded address from electronic health records of 44,810 children 4 to 18years-old seen at 14 Massachusetts pediatric practices in 2011-2012. Main outcomes were BMI z-score and BMI z-score change over time. We used multivariable linear regression to examine associations between race/ethnicity and BMI z-score outcomes, sequentially adjusting for neighborhood SES and the food and physical activity environment. RESULTS: Among 44,810 children, 13.3% were black, 5.7% Hispanic, and 65.2% white. Compared to white children, BMI z-scores were higher among black (0.43units [95% CI: 0.40-0.45]) and Hispanic (0.38 [0.34-0.42]) children; black (0.06 [0.04-0.08]), but not Hispanic, children also had greater increases in BMI z-score over time. Adjusting for neighborhood SES substantially attenuated BMI z-score differences among black (0.30 [0.27-0.34]) and Hispanic children (0.28 [0.23-0.32]), while adjustment for food and physical activity environments attenuated the differences but to a lesser extent than neighborhood SES. CONCLUSIONS: Neighborhood SES and the built environment may be important drivers of childhood obesity disparities. To accelerate progress in reducing obesity disparities, interventions must be tailored to the neighborhood contexts in which families live.

Examination of how neighborhood definition influences measurements of youths' access to tobacco retailers: a methodological note on spatial misclassification.

Measurements of neighborhood exposures likely vary depending on the definition of "neighborhood" selected. This study examined the extent to which neighborhood definition influences findings regarding spatial accessibility to tobacco retailers among youth. We defined spatial accessibility to tobacco retailers (i.e., tobacco retail density, closest tobacco retailer, and average distance to the closest 5 tobacco retailers) on the basis of circular and network buffers of 400 m and 800 m, census block groups, and census tracts by using residential addresses from the 2008 Boston Youth Survey Geospatial Dataset (n = 1,292). Friedman tests (to compare overall differences in neighborhood definitions) were applied. There were differences in measurements of youths' access to tobacco retailers according to the selected neighborhood definitions, and these were marked for the 2 spatial proximity measures (both P < 0.01 for all differences). For example, the median average distance to the closest 5 tobacco retailers was 381.50 m when using specific home addresses, 414.00 m when using census block groups, and 482.50 m when using census tracts, illustrating how neighborhood definition influences the measurement of spatial accessibility to tobacco retailers. These analyses suggest that, whenever possible, egocentric neighborhood definitions should be used. The use of larger administrative neighborhood definitions can bias exposure estimates for proximity measures.

Relationships between the built environment and walking and weight status among older women in three U.S. States.

There are few studies of built environment associations with physical activity and weight status among older women in large geographic areas that use individual residential buffers to define environmental exposures. Among 23,434 women (70.0 ± 6.9 yr; range = 57-85) in 3 states, relationships between objective built environment variables and meeting physical activity recommendations via walking and weight status were examined. Differences in associations by population density and state were explored in stratified models. Population density (odds ratio [OR] =1.04 [1.02, 1.07]), intersection density (ORs = 1.18-1.28), and facility density (ORs = 1.01-1.53) were positively associated with walking. Density of physical activity facilities was inversely associated with overweight/obesity (OR = 0.69 [0.49, 0.96]). The strongest associations between facility density variables and both outcomes were found among women from higher population density areas. There was no clear pattern of differences in associations across states. Among older women, relationships between accessible facilities and walking may be most important in more densely populated settings.

Proximity to supermarkets associated with higher body mass index among overweight and obese preschool-age children.

OBJECTIVE: The objective of this study is to examine associations of proximity to food establishments with body mass index (BMI) among preschool-age children. METHODS: We used baseline data from 438 children ages 2-6.9 years with a BMI ≥ 85th percentile participating in a RCT in Massachusetts from 2006 to 2009. We used a geographic information system to determine proximity to six types of food establishments: 1) convenience stores, 2) bakeries, coffee shops, candy stores, 3) full service restaurants, 4) large supermarkets, 5) small supermarkets, and 6) fast-food restaurants. The main outcome was child's BMI. RESULTS: Children's mean (SD) BMI was 19.2 (2.4)kg/m(2); 35% lived ≤ 1 mile from a large supermarket, 42% lived >1 to 2 miles, and 22% lived >2 miles. Compared to children living >2 miles from a large supermarket, those who lived within 1 mile had a BMI 1.06 kg/m(2) higher. Adjustment for socioeconomic characteristics and distance to fast-food restaurants attenuated this estimate to 0.77 kg/m(2). Living in any other distance category from a large supermarket and proximity to other food establishments were not associated with child BMI. CONCLUSIONS: Living closer to a large supermarket was associated with higher BMI among preschool-age children who were overweight or obese.

Using new satellite based exposure methods to study the association between pregnancy PM2.5 exposure, premature birth and birth weight in Massachusetts.

BACKGROUND: Adverse birth outcomes such as low birth weight and premature birth have been previously linked with exposure to ambient air pollution. Most studies relied on a limited number of monitors in the region of interest, which can introduce exposure error or restrict the analysis to persons living near a monitor, which reduces sample size and generalizability and may create selection bias. METHODS: We evaluated the relationship between premature birth and birth weight with exposure to ambient particulate matter (PM2.5) levels during pregnancy in Massachusetts for a 9-year period (2000-2008). Building on a novel method we developed for predicting daily PM2.5 at the spatial resolution of a 10x10 km grid across New-England, we estimated the average exposure during 30 and 90 days prior to birth as well as the full pregnancy period for each mother. We used linear and logistic mixed models to estimate the association between PM2.5 exposure and birth weight (among full term births) and PM2.5 exposure and preterm birth adjusting for infant sex, maternal age, maternal race, mean income, maternal education level, prenatal care, gestational age, maternal smoking, percent of open space near mothers residence, average traffic density and mothers health. RESULTS: Birth weight was negatively associated with PM2.5 across all tested periods. For example, a 10 µg/m³ increase of PM2.5 exposure during the entire pregnancy was significantly associated with a decrease of 13.80 g [95% confidence interval (CI) = -21.10, -6.05] in birth weight after controlling for other factors, including traffic exposure. The odds ratio for a premature birth was 1.06 (95% confidence interval (CI) = 1.01-1.13) for each 10 µg/m3 increase of PM2.5 exposure during the entire pregnancy period. CONCLUSIONS: The presented study suggests that exposure to PM2.5 during the last month of pregnancy contributes to risks for lower birth weight and preterm birth in infants.

Racial differences in the built environment--body mass index relationship? A geospatial analysis of adolescents in urban neighborhoods.

BACKGROUND: Built environment features of neighborhoods may be related to obesity among adolescents and potentially related to obesity-related health disparities. The purpose of this study was to investigate spatial relationships between various built environment features and body mass index (BMI) z-score among adolescents, and to investigate if race/ethnicity modifies these relationships. A secondary objective was to evaluate the sensitivity of findings to the spatial scale of analysis (i.e. 400- and 800-meter street network buffers). METHODS: Data come from the 2008 Boston Youth Survey, a school-based sample of public high school students in Boston, MA. Analyses include data collected from students who had georeferenced residential information and complete and valid data to compute BMI z-score (n = 1,034). We built a spatial database using GIS with various features related to access to walking destinations and to community design. Spatial autocorrelation in key study variables was calculated with the Global Moran's I statistic. We fit conventional ordinary least squares (OLS) regression and spatial simultaneous autoregressive error models that control for the spatial autocorrelation in the data as appropriate. Models were conducted using the total sample of adolescents as well as including an interaction term for race/ethnicity, adjusting for several potential individual- and neighborhood-level confounders and clustering of students within schools. RESULTS: We found significant positive spatial autocorrelation in the built environment features examined (Global Moran's I most ≥ 0.60; all p = 0.001) but not in BMI z-score (Global Moran's I = 0.07, p = 0.28). Because we found significant spatial autocorrelation in our OLS regression residuals, we fit spatial autoregressive models. Most built environment features were not associated with BMI z-score. Density of bus stops was associated with a higher BMI z-score among Whites (Coefficient: 0.029, p < 0.05). The interaction term for Asians in the association between retail destinations and BMI z-score was statistically significant and indicated an inverse association. Sidewalk completeness was significantly associated with a higher BMI z-score for the total sample (Coefficient: 0.010, p < 0.05). These significant associations were found for the 800-meter buffer. CONCLUSION: Some relationships between the built environment and adolescent BMI z-score were in the unexpected direction. Our findings overall suggest that the built environment does not explain a large proportion of the variation in adolescent BMI z-score or racial disparities in adolescent obesity. However, there are some differences by race/ethnicity that require further research among adolescents.

Alcohol outlets and alcohol consumption in changing environments: prevalence and changes over time.

BACKGROUND: To examine whether changes in density of neighborhood alcohol outlets affected changes in alcohol consumption 1-year after regulatory changes increased alcohol availability. METHODS: Person-level data came from a population-based cohort (aged 21-64) residing in/around the Philadelphia, Pennsylvania metropolitan area (2016-2018, N = 772). Fifty-eight percent lived in a state that began implementing new regulations (Pennsylvania) and the remainder lived in states without major regulatory changes (Delaware and New Jersey). Alcohol consumption was assessed as days per week (pw), drinks pw, high consumption (≥8 drinks pw), and binge drinking. Availability of off-premise alcohol outlets was assessed using 1-mile density and distance. Regression models adjusted for age, gender, race/ethnicity, income, education, health status, state and population density. RESULTS: Cross-sectional analyses found that higher outlet density was associated with more alcohol consumption (days, drinks, high consumption; all p < 0.03) and residing farther from an outlet was associated with less alcohol consumption (days and drinks; all p < 0.04). In longitudinal analyses, relative to no change in outlets, exposure to more outlets was associated with 64% higher odds of drinking on more days pw (p < 0.049) and 55% higher odds of consuming more drinks pw (p < 0.081). However, the longitudinal association between changes in outlets and changes in consumption did not differ for residents in Pennsylvania vs. nearby states. In cross-sectional and longitudinal analyses, outlets were not related to binge drinking. CONCLUSION: Off-premise outlets were associated with alcohol consumption consistently in cross-sectional analysis and in some longitudinal analyses. Results can inform future studies that wish to evaluate longer-term changes in increased alcohol availability and effects on consumption.

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.

Associations between Greenspace and Gentrification-Related Sociodemographic and Housing Cost Changes in Major Metropolitan Areas across the United States.

Neighborhood greenspace may attract new residents and lead to sociodemographic or housing cost changes. We estimated relationships between greenspace and gentrification-related changes in the 43 largest metropolitan statistical areas (MSAs) of the United States (US). We used the US National Land Cover and Brown University Longitudinal Tracts databases, as well as spatial lag models, to estimate census tract-level associations between percentage greenspace (years 1990, 2000) and subsequent changes (1990-2000, 2000-2010) in percentage college-educated, percentage working professional jobs, race/ethnic composition, household income, percentage living in poverty, household rent, and home value. We also investigated effect modification by racial/ethnic composition. We ran models for each MSA and time period and used random-effects meta-analyses to derive summary estimates for each period. Estimates were modest in magnitude and heterogeneous across MSAs. After adjusting for census-tract level population density in 1990, compared to tracts with low percentage greenspace in 1992 (defined as ≤50th percentile of the MSA-specific distribution in 1992), those with high percentage greenspace (defined as >75th percentile of the MSA-specific distribution) experienced higher 1990-2000 increases in percentage of the employed civilian aged 16+ population working professional jobs (ß: 0.18, 95% confidence interval (CI): 0.11, 0.26) and in median household income (ß: 0.23, 95% CI: 0.15, 0.31). Adjusted estimates for the 2000-2010 period were near the null. We did not observe evidence of effect modification by race/ethnic composition. We observed evidence of modest associations between greenspace and gentrification trends. Further research is needed to explore reasons for heterogeneity and to quantify health implications.

Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study.

BACKGROUND: There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. METHODS: Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. RESULTS: Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches. CONCLUSION: Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.

Neighborhood Violent Crime and Perceived Stress in Pregnancy.

Stress has been shown to adversely affect pregnancy outcomes. Neighborhood crime rates may serve as one publicly available social determinant of health for pregnancy studies that use registry or electronic health record datasets in which individual-level stress data are not available. We sought to determine whether neighborhood violent crime incidents were associated with measured perceived stress in a largely minority, urban pregnancy cohort. We performed a secondary analysis of the 1309 Philadelphia residents participating in the Motherhood and Microbiome cohort (n = 2000) with both neighborhood violent crime and Cohen's Perceived Stress Scale (PSS-14) data. Generalized linear mixed models accounting for confounding variables and geographic clustering demonstrated that, regardless of race, women with the highest quartile of neighborhood violent crime had significantly elevated odds of high stress compared to women with lower crime. We also found that Black women were more likely to have both the highest quartile of neighborhood violent crime and high stress than non-Black women. Overall, this study demonstrates that neighborhood violent crime is associated with perceived stress in pregnancy. Given disparate exposure to crime and prenatal stress by race, future work is warranted to determine whether urban neighborhood violence and/or stress reduction strategies would improve birth outcome racial disparities.