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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01353-6.

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.

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.

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.

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 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 (β: 0.18, 95% confidence interval (CI): 0.11, 0.26) and in median household income (β: 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.

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.

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.

Long-term PM2.5 Exposure and Neurological Hospital Admissions in the Northeastern United States

BACKGROUND

Long-term exposure to fine particles (particulate matter ≤ 2.5 μm; PM2.5) has been consistently linked to heart and lung disease. Recently, there has been increased interest in examining the effects of air pollution on the nervous system, with evidence showing potentially harmful effects on neurodegeneration.

OBJECTIVE

Our objective was to assess the potential impact of long-term PM2.5 exposure on event time, defined as time to first admission for dementia, Alzheimer's (AD), or Parkinson's (PD) diseases in an elderly population across the northeastern United States.

METHODS

We estimated the effects of PM2.5 on first hospital admission for dementia, AD, and PD among all Medicare enrollees ≥ 65 years in 50 northeastern U.S. cities (1999-2010). For each outcome, we first ran a Cox proportional hazards model for each city, adjusting for prior cardiopulmonary-related hospitalizations and year, and stratified by follow-up time, age, sex, and race. We then pooled the city-specific estimates by employing a random effects meta-regression.

RESULTS

We followed approximately 9.8 million subjects and observed significant associations of long-term PM2.5 city-wide exposure with all three outcomes. Specifically, we estimated a hazard ratio (HR) of 1.08 (95% CI: 1.05, 1.11) for dementia, an HR of 1.15 (95% CI: 1.11, 1.19) for AD, and an HR of 1.08 (95% CI: 1.04, 1.12) for PD admissions per 1-μg/m3 increase in annual PM2.5 concentrations.

CONCLUSIONS

To our knowledge, this is the first study to examine the relationship between long-term exposure to PM2.5 and time to first hospitalization for common neurodegenerative diseases. We found strong evidence of association for all three outcomes. Our findings provide the basis for further studies, as the implications of such exposures could be crucial to public health.

CITATION

Kioumourtzoglou MA, Schwartz JD, Weisskopf MG, Melly SJ, Wang Y, Dominici F, Zanobetti A. 2016. Long-term PM2.5 exposure and neurological hospital admissions in the northeastern United States. Environ Health Perspect 124:23-29; http://dx.doi.org/10.1289/ehp.1408973.

Low-Concentration PM2.5 and Mortality: Estimating Acute and Chronic Effects in a Population-Based Study

BACKGROUND

Both short- and long-term exposures to fine particulate matter (≤ 2.5 μm; PM2.5) are associated with mortality. However, whether the associations exist at levels below the new U.S. Environmental Protection Agency (EPA) standards (12 μg/m3 of annual average PM2.5, 35 μg/m3 daily) is unclear. In addition, it is not clear whether results from previous time series studies (fit in larger cities) and cohort studies (fit in convenience samples) are generalizable.

OBJECTIVES

We estimated the effects of low-concentration PM2.5 on mortality.

METHODS

High resolution (1 km × 1 km) daily PM2.5 predictions, derived from satellite aerosol optical depth retrievals, were used. Poisson regressions were applied to a Medicare population (≥ 65 years of age) in New England to simultaneously estimate the acute and chronic effects of exposure to PM2.5, with mutual adjustment for short- and long-term exposure, as well as for area-based confounders. Models were also restricted to annual concentrations < 10 μg/m3 or daily concentrations < 30 μg/m3.

RESULTS

PM2.5 was associated with increased mortality. In the study cohort, 2.14% (95% CI: 1.38, 2.89%) and 7.52% (95% CI: 1.95, 13.40%) increases were estimated for each 10-μg/m3 increase in short- (2 day) and long-term (1 year) exposure, respectively. The associations held for analyses restricted to low-concentration PM2.5 exposure, and the corresponding estimates were 2.14% (95% CI: 1.34, 2.95%) and 9.28% (95% CI: 0.76, 18.52%). Penalized spline models of long-term exposure indicated a larger effect for mortality in association with exposures ≥ 6 μg/m3 versus those < 6 μg/m3. In contrast, the association between short-term exposure and mortality appeared to be linear across the entire exposure distribution.

CONCLUSIONS

Using a mutually adjusted model, we estimated significant acute and chronic effects of PM2.5 exposure below the current U.S. EPA standards. These findings suggest that improving air quality with even lower PM2.5 than currently allowed by U.S. EPA standards may benefit public health.

CITATION

Shi L, Zanobetti A, Kloog I, Coull BA, Koutrakis P, Melly SJ, Schwartz JD. 2016. Low-concentration PM2.5 and mortality: estimating acute and chronic effects in a population-based study. Environ Health Perspect 124:46-52; http://dx.doi.org/10.1289/ehp.1409111.

Using Satellite-Based Spatiotemporal Resolved Air Temperature Exposure to Study the Association between Ambient Air Temperature and Birth Outcomes in Massachusetts

BACKGROUND

Studies looking at air temperature (Ta) and birth outcomes are rare.

OBJECTIVES

We investigated the association between birth outcomes and daily Ta during various prenatal exposure periods in Massachusetts (USA) using both traditional Ta stations and modeled addresses.

METHODS

We evaluated birth outcomes and average daily Ta during various prenatal exposure periods in Massachusetts (USA) using both traditional Ta stations and modeled address Ta. We used linear and logistic mixed models and accelerated failure time models to estimate associations between Ta and the following outcomes among live births > 22 weeks: term birth weight (≥ 37 weeks), low birth weight (LBW; < 2,500 g at term), gestational age, and preterm delivery (PT; < 37 weeks). Models were adjusted for individual-level socioeconomic status, traffic density, particulate matter ≤ 2.5 μm (PM2.5), random intercept for census tract, and mother's health.

RESULTS

Predicted Ta during multiple time windows before birth was negatively associated with birth weight: Average birth weight was 16.7 g lower (95% CI: -29.7, -3.7) in association with an interquartile range increase (8.4 °C) in Ta during the last trimester. Ta over the entire pregnancy was positively associated with PT [odds ratio (OR) = 1.02; 95% CI: 1.00, 1.05] and LBW (OR = 1.04; 95% CI: 0.96, 1.13).

CONCLUSIONS

Ta during pregnancy was associated with lower birth weight and shorter gestational age in our study population.

Prenatal and Childhood Traffic-Related Pollution Exposure and Childhood Cognition in the Project Viva Cohort (Massachusetts, USA)

BACKGROUND

Influences of prenatal and early-life exposures to air pollution on cognition are not well understood.

OBJECTIVES

We examined associations of gestational and childhood exposure to traffic-related pollution with childhood cognition.

METHODS

We studied 1,109 mother-child pairs in Project Viva, a prospective birth cohort study in eastern Massachusetts (USA). In mid-childhood (mean age, 8.0 years), we measured verbal and nonverbal intelligence, visual motor abilities, and visual memory. For periods in late pregnancy and childhood, we estimated spatially and temporally resolved black carbon (BC) and fine particulate matter (PM2.5) exposures, residential proximity to major roadways, and near-residence traffic density. We used linear regression models to examine associations of exposures with cognitive assessment scores, adjusted for potential confounders.

RESULTS

Compared with children living ≥ 200 m from a major roadway at birth, those living < 50 m away had lower nonverbal IQ [-7.5 points; 95% confidence interval (CI): -13.1, -1.9], and somewhat lower verbal IQ (-3.8 points; 95% CI: -8.2, 0.6) and visual motor abilities (-5.3 points; 95% CI: -11.0, 0.4). Cross-sectional associations of major roadway proximity and cognition at mid-childhood were weaker. Prenatal and childhood exposure to traffic density and PM2.5 did not appear to be associated with poorer cognitive performance. Third-trimester and childhood BC exposures were associated with lower verbal IQ in minimally adjusted models; but after adjustment for socioeconomic covariates, associations were attenuated or reversed.

CONCLUSIONS

Residential proximity to major roadways during gestation and early life may affect cognitive development. Influences of pollutants and socioeconomic conditions on cognition may be difficult to disentangle.

Food environments and childhood weight status: effects of neighborhood median income

BACKGROUND

A key aspect of any intervention to improve obesity is to better understand the environment in which decisions are being made related to health behaviors, including the food environment.

METHODS

Our aim was to examine the extent to which proximity to six types of food establishments is associated with BMI z-score and explore potential effect modification of this relationship. We used geographical information software to determine proximity from 49,770 pediatric patients' residences to six types of food establishments. BMI z-score obtained from the electronic health record was the primary outcome.

RESULTS

In multivariable analyses, living in closest proximity to large (β, -0.09 units; 95% confidence interval [CI], -0.13, -0.05) and small supermarkets (-0.08 units; 95% CI, -0.11, -0.04) was associated with lower BMI z-score; living in closest proximity to fast food (0.09 units; 95% CI, 0.03, 0.15) and full-service restaurants (0.07 units; 95% CI, 0.01, 0.14) was associated with a higher BMI z-score versus those living farthest away. Neighborhood median income was an effect modifier of the relationships of convenience stores and full-service restaurants with BMI z-score. In both cases, closest proximity to these establishments had more of an adverse effect on BMI z-score in lower-income neighborhoods.

CONCLUSIONS

Living closer to supermarkets and farther from fast food and full-service restaurants was associated with lower BMI z-score. Neighborhood median income was an effect modifier; convenience stores and full-service restaurants had a stronger adverse effect on BMI z-score in lower-income neighborhoods.

Prenatal air pollution exposure and newborn blood pressure

BACKGROUND

Air pollution exposure has been associated with increased blood pressure in adults.

OBJECTIVE

We examined associations of antenatal exposure to ambient air pollution with newborn systolic blood pressure (SBP).

METHODS

We studied 1,131 mother-infant pairs in a Boston, Massachusetts, area pre-birth cohort. We calculated average exposures by trimester and during the 2 to 90 days before birth for temporally resolved fine particulate matter (≤ 2.5 μm; PM2.5), black carbon (BC), nitrogen oxides, nitrogen dioxide, ozone (O3), and carbon monoxide measured at stationary monitoring sites, and for spatiotemporally resolved estimates of PM2.5 and BC at the residence level. We measured SBP at a mean age of 30 ± 18 hr with an automated device. We used mixed-effects models to examine associations between air pollutant exposures and SBP, taking into account measurement circumstances; child's birth weight; mother's age, race/ethnicity, socioeconomic position, and third-trimester BP; and time trend. Estimates represent differences in SBP associated with an interquartile range (IQR) increase in each pollutant.

RESULTS

Higher mean PM2.5 and BC exposures during the third trimester were associated with higher SBP (e.g., 1.0 mmHg; 95% CI: 0.1, 1.8 for a 0.32-μg/m3 increase in mean 90-day residential BC). In contrast, O3 was negatively associated with SBP (e.g., -2.3 mmHg; 95% CI: -4.4, -0.2 for a 13.5-ppb increase during the 90 days before birth).

CONCLUSIONS

Exposures to PM2.5 and BC in late pregnancy were positively associated with newborn SBP, whereas O3 was negatively associated with SBP. Longitudinal follow-up will enable us to assess the implications of these findings for health during later childhood and adulthood.

Exposure to traffic and early life respiratory infection: A cohort study

We examined whether proximity to a major roadway and traffic density around the home during pregnancy are associated with risk of early life respiratory infection in a pre-birth cohort in the Boston area. We geocoded addresses for 1,263 mother-child pairs enrolled during the first trimester of pregnancy in Project Viva during 1999-2002. We calculated distance from home to nearest major roadway and traffic density in a 100 m buffer around the home. We defined respiratory infection as maternal report of ≥1 doctor-diagnosed pneumonia, bronchiolitis, croup, or other respiratory infection from birth until the early childhood visit (median age 3.3). We used relative risk regression models adjusting for potential confounders to estimate associations between traffic exposures and risk of respiratory infection. Distance to roadway during pregnancy was associated with risk of respiratory infection. In fully adjusted models, relative risks (95% CI) for respiratory infection were: 1.30 (1.08, 1.55) for <100 m, 1.15 (0.93, 1.41) for 100 to <200 m, and 0.95 (0.84, 1.07) for 200 to <1,000 m compared with living ≥1,000 m away from a major roadway. Each interquartile range increase in distance to roadway was associated with an 8% (95% CI 0.87, 0.98) lower risk, and each interquartile range increase in traffic density was associated with a 5% (95% CI 0.98, 1.13) higher risk of respiratory infection. Our findings suggest that living close to a major roadway during pregnancy may predispose the developing lung to infection in early life. Pediatr Pulmonol. 2015; 50:252-259. © 2014 Wiley Periodicals, Inc.

Characteristics of walkable built environments and BMI z-scores in children: evidence from a large electronic health record database

BACKGROUND

Childhood obesity remains a prominent public health problem. Walkable built environments may prevent excess weight gain.

OBJECTIVES

We examined the association of walkable built environment characteristics with body mass index (BMI) z-score among a large sample of children and adolescents.

METHODS

We used geocoded residential address data from electronic health records of 49,770 children and adolescents 4 to < 19 years of age seen at the 14 pediatric practices of Harvard Vanguard Medical Associates from August 2011 through August 2012. We used eight geographic information system (GIS) variables to characterize walkable built environments. Outcomes were BMI z-score at the most recent visit and BMI z-score change from the earliest available (2008-2011) to the most recent (2011-2012) visit. Multivariable models were adjusted for child age, sex, race/ethnicity, and neighborhood median household income.

RESULTS

In multivariable cross-sectional models, living in closer proximity to recreational open space was associated with lower BMI z-score. For example, children who lived in closest proximity (quartile 1) to the nearest recreational open space had a lower BMI z-score (β = -0.06; 95% CI: -0.08, -0.03) compared with those living farthest away (quartile 4; reference). Living in neighborhoods with fewer recreational open spaces and less residential density, traffic density, sidewalk completeness, and intersection density were associated with higher cross-sectional BMI z-score and with an increase in BMI z-score over time.

CONCLUSIONS

Overall, built environment characteristics that may increase walkability were associated with lower BMI z-scores in a large sample of children. Modifying existing built environments to make them more walkable may reduce childhood obesity.

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.

The built environment and depressive symptoms among urban youth: A spatial regression study

This study evaluated spatial relationships between features of the built environment and youth depressive symptoms. Data used in this study came from the 2008 Boston Youth Survey Geospatial Dataset, which includes Boston high school students with complete residential information (n=1170). Features of the built environment (such as access to walking destinations and community design features) were created for 400- and 800-m street network buffers of the youths' residences. We computed standard Ordinary Least Squares (OLS) regression and spatial simultaneous autoregressive models. We found significant positive spatial autocorrelation in all of the built environment features at both spatial scales (all p=0.001), depressive symptoms (p=0.034) as well as in the OLS regression residuals (all p<0.001), and, therefore, fit spatial regression models. Findings from the spatial regression models indicate that the built environment can have depressogenic effects, which can vary by spatial scale, gender and race/ethnicity (though sometimes in unexpected directions, i.e. associations opposite to our expectations). While our results overall suggest that the built environment minimally influences youth depressive symptoms, additional research is needed, including to understand our results in the unexpected direction.

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.

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.

Evaluating efficiency-equality tradeoffs for mobile source control strategies in an urban area

In environmental risk management, there are often interests in maximizing public health benefits (efficiency) and addressing inequality in the distribution of health outcomes. However, both dimensions are not generally considered within a single analytical framework. In this study, we estimate both total population health benefits and changes in quantitative indicators of health inequality for a number of alternative spatial distributions of diesel particulate filter retrofits across half of an urban bus fleet in Boston, Massachusetts. We focus on the impact of emissions controls on primary fine particulate matter (PM(2.5)) emissions, modeling the effect on PM(2.5) concentrations and premature mortality. Given spatial heterogeneity in baseline mortality rates, we apply the Atkinson index and other inequality indicators to quantify changes in the distribution of mortality risk. Across the different spatial distributions of control strategies, the public health benefits varied by more than a factor of two, related to factors such as mileage driven per day, population density near roadways, and baseline mortality rates in exposed populations. Changes in health inequality indicators varied across control strategies, with the subset of optimal strategies considering both efficiency and equality generally robust across different parametric assumptions and inequality indicators. Our analysis demonstrates the viability of formal analytical approaches to jointly address both efficiency and equality in risk assessment, providing a tool for decisionmakers who wish to consider both issues.

Evaluating efficiency-equality tradeoffs for mobile source control strategies in an urban area

In environmental risk management, there are often interests in maximizing public health benefits (efficiency) and addressing inequality in the distribution of health outcomes. However, both dimensions are not generally considered within a single analytical framework. In this study, we estimate both total population health benefits and changes in quantitative indicators of health inequality for a number of alternative spatial distributions of diesel particulate filter retrofits across half of an urban bus fleet in Boston, Massachusetts. We focus on the impact of emissions controls on primary fine particulate matter (PM(2.5)) emissions, modeling the effect on PM(2.5) concentrations and premature mortality. Given spatial heterogeneity in baseline mortality rates, we apply the Atkinson index and other inequality indicators to quantify changes in the distribution of mortality risk. Across the different spatial distributions of control strategies, the public health benefits varied by more than a factor of two, related to factors such as mileage driven per day, population density near roadways, and baseline mortality rates in exposed populations. Changes in health inequality indicators varied across control strategies, with the subset of optimal strategies considering both efficiency and equality generally robust across different parametric assumptions and inequality indicators. Our analysis demonstrates the viability of formal analytical approaches to jointly address both efficiency and equality in risk assessment, providing a tool for decisionmakers who wish to consider both issues.

Characteristics of school campuses and physical activity among youth

BACKGROUND

Previous research suggests that school characteristics may influence physical activity. However, few studies have examined associations between school building and campus characteristics and objective measures of physical activity among middle school students.

METHODS

Students from ten middle schools (n=248, 42% female, mean age 13.7 years) wore TriTrac-R3D accelerometers in 1997 recording measures of minute-by-minute physical movements during the school day that were then averaged over 15-minute intervals (n=16,619) and log-transformed. School characteristics, including school campus area, play area, and building area (per student) were assessed retrospectively in 2004-2005 using land-use parcel data, site visits, ortho-photos, architectural plans, and site maps. In 2006, linear mixed models using SAS PROC MIXED were fit to examine associations between school environmental variables and physical activity, controlling for potentially confounding variables.

RESULTS

Area per enrolled student ranged from 8.8 to 143.7 m2 for school campuses, from 12.1 to 24.7 m2 for buildings, and from 0.4 to 58.9 m2 for play areas. Play area comprised from 3% to 62% of total campus area across schools. In separate regression models, school campus area per student (beta=0.2244, p<0.0001); building area per student (beta=2.1302, p<0.02); and play area per student (beta=0.347, p<0.0001) were each directly associated with log-TriTrac-R3D vector magnitude. Given the range of area density measures in this sample of schools, this translates into an approximate 20% to 30% increase in average vector magnitude, or walking 2 extra miles over the course of a week.

CONCLUSIONS

Larger school campuses, school buildings, and play areas (per enrolled student) are associated with higher levels of physical activity in middle school students.

Clustering of fast-food restaurants around schools: a novel application of spatial statistics to the study of food environments

OBJECTIVES

We examined the concentration of fast food restaurants in areas proximal to schools to characterize school neighborhood food environments.

METHODS

We used geocoded databases of restaurant and school addresses to examine locational patterns of fast-food restaurants and kindergartens and primary and secondary schools in Chicago. We used the bivariate K function statistical method to quantify the degree of clustering (spatial dependence) of fast-food restaurants around school locations.

RESULTS

The median distance from any school in Chicago to the nearest fast-food restaurant was 0.52 km, a distance that an adult can walk in little more than 5 minutes, and 78% of schools had at least 1 fast-food restaurant within 800 m. Fast-food restaurants were statistically significantly clustered in areas within a short walking distance from schools, with an estimated 3 to 4 times as many fast-food restaurants within 1.5 km from schools than would be expected if the restaurants were distributed throughout the city in a way unrelated to school locations.

CONCLUSIONS

Fast-food restaurants are concentrated within a short walking distance from schools, exposing children to poor-quality food environments in their school neighborhoods.

Playground safety and access in Boston neighborhoods

BACKGROUND

Youth physical activity is partly influenced by access to playgrounds and recreational opportunities. Playgrounds in disadvantaged areas may be less safe.

METHODS

Investigators assessed safety at 154 playgrounds in Boston between July 2000 and July 2001. Playgrounds were geocoded and safety scores assigned to census block groups (CBGs). For each of Boston's 591 CBGs, investigators calculated the total number youth and proportions of black residents, adults without a high school degree, and youth living in poverty. Investigators assigned each CBG a safety score, and calculated distance from the CBG centroid to the nearest playground and nearest "safe" playground (top safety quartile). Statistical analyses were completed using SAS PROC GENMOD by October 2002.

RESULTS

In bivariate analysis, playground safety was inversely associated with total CBG youth population (p =0.001) and proportions of black residents (p <0.001), youth in poverty (p =0.003) and residents with no high school degree (p <0.002). The proportion of black residents in the CBG was inversely associated with safety (p =0.013), independent of CBG educational attainment and numbers of youth. The average distance was 417 meters to the nearest playground and 1133 meters to the nearest "safe" playground. Distance to the nearest playground was inversely associated with the proportion of residents with no high school degree (p <0.0001) after controlling for numbers of youth and proportion of black residents. CBGs with more youth had greater distances to the safest playgrounds (p =0.04).

CONCLUSIONS

In Boston, playground safety and access to playgrounds varied according to indicators of small-area socioeconomic and racial/ethnic composition.

Influence of traffic patterns on particulate matter and polycyclic aromatic hydrocarbon concentrations in Roxbury, Massachusetts

Vehicle emissions have been associated with adverse health effects in multiple epidemiological studies, but the sources or constituents responsible have not been established. Characterization of vehicle-related exposures requires detailed information on spatial and temporal trends of various pollutants and the ability to predict exposures in unmonitored settings. To address these issues, in the summer of 2001 we measured continuously particle-bound polycyclic aromatic hydrocarbons (PAHs), ultrafine particles, and PM(2.5) at a number of sites in Roxbury, a neighborhood of Boston, Massachusetts with significant diesel and gasoline-fueled traffic. We took measurements at the side of the road and at varying distances from the road, with simultaneous collection of traffic counts and meteorological conditions. Across all nine sites, median roadside concentrations were 8 ng/m(3) of particle-bound PAHs (range: 4-57), 16,000 ultrafine particles/cm(3) (range: 11,000-53,000), and 54 microg/m(3) of PM(2.5) as measured with a DustTrak (range: 12-86). Concentrations of all pollutants were lower at greater distances from the road, upwind, and at higher wind speeds, with greater concentration gradients for PAHs and ultrafine particles. In linear mixed effects regression models accounting for temporal autocorrelation, large diesel vehicle counts were significantly associated with roadside concentrations of PAHs (P=0.02), with a moderate association with ultrafine particles and little relation with PM(2.5). Although more comprehensive information would be needed for epidemiological applications, these data demonstrate significant spatial and temporal heterogeneity for traffic-related pollutants during the summer in an urban center, with our monitoring and analytical methodology helping to inform source attribution.

Using GIS and historical records to reconstruct residential exposure to large-scale pesticide application

Investigation of pesticide impacts on human health depends on good measures of exposure. Historical exposure data are needed to study health outcomes, such as cancer, that involve long latency periods, and other outcomes that are a function of the timing of exposure. Environmental or biological samples collected at the time of epidemiologic study may not represent historical exposure levels. To study the relationship between residential exposure to pesticides and breast cancer on Cape Cod, Massachusetts, historical records of pesticide use were integrated into a geographic information system (GIS) to estimate exposures from large-scale pesticide applications between 1948 and 1995. Information on pesticide use for gypsy moth and other tree/vegetative pest control, cranberry bog cultivation, other agriculture, mosquito control, recreational turf management, and rights-of-way maintenance is included in the database. Residents living within or near pesticide use areas may be exposed through inhalation due to drift and volatilization and through dermal contact and ingestion at the time of application or in later years from pesticides that deposit on soil, accumulate in crops, or migrate to groundwater. Procedures were developed to use the GIS to estimate the relative intensity of past exposures at each study subject's Cape Cod addresses over the past 40 years, taking into account local meteorological data, distance and direction from a residence to a pesticide use source area, size of the source area, application by ground-based or aerial methods, and persistent or nonpersistent character of the pesticide applied. The resulting individual-level estimates of relative exposure intensity can be used in conjunction with interview data to obtain more complete exposure assessment in an epidemiologic study. While the database can improve environmental epidemiological studies involving pesticides, it simultaneously illustrates important data gaps that cannot be filled. Studies such as this one have the potential to identify preventable causes of disease and guide public policies.