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.
Citation: Duncan DT, Sharifi M, Melly SJ, Marshall R, Sequist TD, Rifas-Shiman SL, Taveras EM. 2014. Characteristics of walkable built environments and BMI z-scores in children: evidence from a large electronic health record database. Environ Health Perspect 122:1359–1365; http://dx.doi.org/10.1289/ehp.1307704
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 years; 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.
built environment; geographic information systems; neighborhood; walking; overweight; obesity; older adults; women
While several studies have examined associations between temperature and cardiovascular-disease-related mortality, fewer have investigated the association between temperature and the development of acute myocardial infarction (MI). Moreover, little is known about who is most susceptible to the effects of temperature.
We analyzed data from the Worcester Heart Attack Study, a community-wide investigation of acute MI in residents of the Worcester (MA) metropolitan area. We used a case-crossover approach to examine the association of apparent temperature with acute MI occurrence and with all-cause in-hospital and post-discharge mortality. We examined effect modification by sociodemographic characteristics, medical history, clinical complications, and physical environment.
A decrease in an interquartile range (IQR) in apparent temperature was associated with an increased risk of acute MI on the same day (hazard ratio=1.15 [95% confidence interval= 1.01–1.31]). Extreme cold during the 2 days prior was associated with an increased risk of acute MI (1.36 [1.07–1.74]). Extreme heat during the two days prior was also associated with an increased risk of mortality (1.44 [1.06–1.96]). Persons living in areas with greater poverty were more susceptible to heat.
Exposure to cold increased the risk of acute MI, and exposure to heat increased the risk of dying after an acute MI. Local area vulnerability should be accounted for as cities prepare to adapt to weather fluctuations as a result of climate change.
Background: Exposure to fine particulate matter (PM with diameter ≤ 2.5 μm; PM2.5) has been linked to type 2 diabetes mellitus, but associations with hyperglycemia in pregnancy have not been well studied.
Methods: We studied Boston, Massachusetts–area pregnant women without known diabetes. We identified impaired glucose tolerance (IGT) and gestational diabetes mellitus (GDM) during pregnancy from clinical glucose tolerance tests at median 28.1 weeks gestation. We used residential addresses to estimate second-trimester PM2.5 and black carbon exposure via a central monitoring site and spatiotemporal models. We estimated residential traffic density and roadway proximity as surrogates for exposure to traffic-related air pollution. We performed multinomial logistic regression analyses adjusted for sociodemographic covariates, and used multiple imputation to account for missing data.
Results: Of 2,093 women, 65 (3%) had IGT and 118 (6%) had GDM. Second-trimester spatiotemporal exposures ranged from 8.5 to 15.9 μg/m3 for PM2.5 and from 0.1 to 1.7 μg/m3 for black carbon. Traffic density was 0–30,860 vehicles/day × length of road (kilometers) within 100 m; 281 (13%) women lived ≤ 200 m from a major road. The prevalence of IGT was elevated in the highest (vs. lowest) quartile of exposure to spatiotemporal PM2.5 [odds ratio (OR) = 2.63; 95% CI: 1.15, 6.01] and traffic density (OR = 2.66; 95% CI: 1.24, 5.71). IGT also was positively associated with other exposure measures, although associations were not statistically significant. No pollutant exposures were positively associated with GDM.
Conclusions: Greater exposure to PM2.5 and other traffic-related pollutants during pregnancy was associated with IGT but not GDM. Air pollution may contribute to abnormal glycemia in pregnancy.
Citation: Fleisch AF, Gold DR, Rifas-Shiman SL, Koutrakis P, Schwartz JD, Kloog I, Melly S, Coull BA, Zanobetti A, Gillman MW, Oken E. 2014. Air pollution exposure and abnormal glucose tolerance during pregnancy: the Project Viva Cohort. Environ Health Perspect 122:378–383; http://dx.doi.org/10.1289/ehp.1307065
The objective of this study is to examine associations of proximity to food establishments with body mass index (BMI) among preschool-age children.
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.
Children’s mean (SD) BMI was 19.2 (2.4) kg/m2; 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/m2 higher. Adjustment for socioeconomic characteristics and distance to fast-food restaurants attenuated this estimate to 0.77 kg/m2. Living in any other distance category from a large supermarket and proximity to other food establishments were not associated with child BMI.
Living closer to a large supermarket was associated with higher BMI among preschool-age children who were overweight or obese.
supermarkets; food establishments; children; body mass index; obesity
Objective To investigate whether exposure to aircraft noise increases the risk of hospitalization for cardiovascular diseases in older people (≥65 years) residing near airports.
Design Multi-airport retrospective study of approximately 6 million older people residing near airports in the United States. We superimposed contours of aircraft noise levels (in decibels, dB) for 89 airports for 2009 provided by the US Federal Aviation Administration on census block resolution population data to construct two exposure metrics applicable to zip code resolution health insurance data: population weighted noise within each zip code, and 90th centile of noise among populated census blocks within each zip code.
Setting 2218 zip codes surrounding 89 airports in the contiguous states.
Participants 6 027 363 people eligible to participate in the national medical insurance (Medicare) program (aged ≥65 years) residing near airports in 2009.
Main outcome measures Percentage increase in the hospitalization admission rate for cardiovascular disease associated with a 10 dB increase in aircraft noise, for each airport and on average across airports adjusted by individual level characteristics (age, sex, race), zip code level socioeconomic status and demographics, zip code level air pollution (fine particulate matter and ozone), and roadway density.
Results Averaged across all airports and using the 90th centile noise exposure metric, a zip code with 10 dB higher noise exposure had a 3.5% higher (95% confidence interval 0.2% to 7.0%) cardiovascular hospital admission rate, after controlling for covariates.
Conclusions Despite limitations related to potential misclassification of exposure, we found a statistically significant association between exposure to aircraft noise and risk of hospitalization for cardiovascular diseases among older people living near airports.
Short sleep duration is associated with multiple adverse child outcomes. We examined associations of the built environment with infant sleep duration among 1226 participants in a pre-birth cohort. From residential addresses, we used a geographic information system to determine urbanicity, population density, and closeness to major roadways. The main outcome was mother’s report of her infant’s average daily sleep duration at 1 year of age. We ranked urbanicity and population density as quintiles, categorized distance to major roads into 8 categories, and used linear regression adjusted for socio-demographic characteristics, smoking during pregnancy, gestational age, fetal growth, and television viewing at 1 year. In this sample, mean (SD) sleep duration at age 1 year was 12.8 (1.6) hours/day. In multivariable adjusted analyses, children living in the highest quintile of urbanicity slept −19.2 minutes/day (95% CI: −37.0, −1.50) less than those living in the lowest quintile. Neither population density nor closeness to major roadways was associated with infant sleep duration after multivariable adjustment. Our findings suggest that living in more urban environments may be associated with reduced infant sleep.
Sleep; urbanicity; population density; infancy; built environment
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.
Spatial epidemiology; Neighborhood effects; Built environment; Neighborhood walkability; Depressive symptoms; Youth
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 (PM2.5) emissions, modeling the effect on PM2.5 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 decision-makers who wish to consider both issues.
diesel particulate filter; environmental justice; fine particulate matter (PM2.5); inequality; mobile source
Studies of the built environment and physical activity have implicitly assumed that a substantial amount of activity occurs near home, but in fact the location is unknown.
Examine associations between built environment variables within home and work buffers and moderate-vigorous physical activity occurring within these locations.
Adults (n= 148) from Massachusetts wore an accelerometer and GPS unit for up to four days. Moderate and vigorous intensity activity was quantified within 50 m and 1 km home and work buffers. Multiple regression models were used to examine associations between five objective built environment variables within 1 km home and work buffers (intersection density, land use mix, population and housing unit density, vegetation index) and moderate-vigorous physical activity within those areas.
The mean daily minutes of moderate-vigorous physical activity accumulated in all locations = 61.1 ± 32.8, while duration within 1 km home buffers = 14.0 ± 16.4 min. Intersection density, land use mix, and population and housing unit density within 1 km home buffers were positively associated with moderate-vigorous physical activity in the buffer, while a vegetation index showed an inverse relationship (all p< 0.05). None of these variables showed associations with total moderate-vigorous activity. Within 1 km of work, only population and housing unit density were significantly associated with moderate-vigorous physical activity within the buffer.
Findings are consistent with studies showing that certain attributes of the built environment around homes are positively related to physical activity, but in this case only when the outcome was “location-based”. Simultaneous accelerometer-GPS monitoring shows promise as a method to improve understanding of how the built environment influences physical activity behaviors by allowing activity to be quantified in a range of physical contexts and thereby provide a more explicit link between physical activity outcomes and built environment exposures.
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.
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 10x10km 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.
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.
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.
Air pollution; Birth weight; Preterm birth; Aerosol optical depth; Epidemiology; PM2.5
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).
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.
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.
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.
Spatial epidemiology; Neighborhood effects; Built environment; BMI; Adolescents; Race effects
Limited availability of desirable destinations within walkable distances and unsuitable weather may adversely affect physical activity among adolescents on weekends.
Students (n=152, 59% male, mean age 13.7 years) from 10 neighborhoods with schools in four communities wore TriTrac-R3D accelerometers recording physical movements on weekends. Minute-by-minute data were summed over 15-minute intervals providing estimates of proportion of time spent in moderate and vigorous physical activity (MVPA) and (log) mean physical activity levels on weekends (n=7506 intervals). Objective measures of neighborhood characteristics were calculated using geographic information systems including average daily traffic, housing density, open space, and density of employees/ km2 in youth destinations. Linear mixed models were fit examining associations between neighborhood environmental variables and accelerometer measures of physical activity, controlling for time, day, age, BMI, sex of respondent, race/ethnicity, precipitation, and temperature deviation.
On weekends, greater densities of employees in neighborhood destinations serving youth (β=3.96, p=0.050) was directly associated with MVPA, independent of student characteristics.
Young people attending schools in neighborhoods characterized by greater densities of employees in destinations for youth are more physically active on weekends. Compared with neighborhoods with lower densities, attending a school in neighborhoods with higher densities of employees in potential destinations for youth may contribute to participation in an additional 30 minutes of MVPA per day on weekends.
Physical Activity; Built Environment; Accelerometer; Neighborhood Characteristics
Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score® for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances (i.e., 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5–11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant’s residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p < 0.05). The magnitude varied by the GIS indicator of neighborhood walkability. Correlations generally became stronger with a larger spatial scale, and there were some geographic differences. Walk Score® is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score® is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.
neighborhood walkability; GIS; Walk Score®; validity; multi-city
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.
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.
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.
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.
Particulate air pollution has been consistently linked to increased risk of arterial cardiovascular disease. Few data on air pollution exposure and risk of venous thrombosis are available. We investigated whether living near major traffic roads increases the risk of deep vein thrombosis (DVT), using distance from roads as a proxy for traffic exposure.
Methods and Results
Between 1995-2005, we examined 663 patients with DVT of the lower limbs and 859 age-matched controls from cities with population>15,000 inhabitants in Lombardia Region, Italy. We assessed distance from residential addresses to the nearest major traffic road using geographic information system methodology. The risk of DVT was estimated from logistic regression models adjusting for multiple clinical and environmental covariates.
The risk of DVT was increased (Odds Ratio [OR]=1.33; 95% CI 1.03-1.71; p=0.03 in age-adjusted models; OR=1.47; 95%CI 1.10-1.96; p=0.008 in models adjusted for multiple covariates) for subjects living near a major traffic road (3 meters, 10th centile of the distance distribution) compared to those living farther away (reference distance of 245 meters, 90th centile). The increase in DVT risk was approximately linear over the observed distance range (from 718 to 0 meters), and was not modified after adjusting for background levels of particulate matter (OR=1.47; 95%CI 1.11-1.96; p=0.008 for 10th vs. 90th distance centile in models adjusting for area levels of particulate matter <10 μm in aerodynamic diameter [PM10] in the year before diagnosis).
Living near major traffic roads is associated with increased risk of DVT.
Deep vein thrombosis; air pollution; risk factors; coagulation
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.
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.
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 (β=0.2244, p<0.0001); building area per student (β=2.1302, p<0.02); and play area per student (β=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.
Larger school campuses, school buildings, and play areas (per enrolled student) are associated with higher levels of physical activity in middle school students.
Although patients with heart failure (HF) have been identified as particularly susceptible to the acute effects of air pollution, the effects of long-term exposure to air pollution on patients with this increasingly prevalent disease are largely unknown.
This study was designed to examine the mortality risk associated with residential exposure to traffic-related air pollution among HF patients.
A total of 1,389 patients hospitalized with acute HF in greater Worcester, Massachusetts, during 2000 were followed for survival through December 2005. We used daily traffic within 100 and 300 m of residence as well as the distance from residence to major roadways and to bus routes as proxies for residential exposure to traffic-related air pollution. We assessed mortality risks for each exposure variable using Cox proportional hazards models adjusted for prognostic factors.
After the 5-year follow-up, only 334 (24%) subjects were still alive. An interquartile range increase in daily traffic within 100 m of home was associated with a mortality hazard ratio (HR) of 1.15 [95% confidence interval (CI), 1.05–1.25], whereas for traffic within 300 m this association was 1.09 (95% CI, 1.01–1.19). The mortality risk decreased with increasing distance to bus routes (HR = 0.88; 95% CI, 0.81–0.96) and was larger for those living within 100 m of a major roadway or 50 m of a bus route (HR = 1.30; 95% CI, 1.13–1.49). Adjustment for area-based income and educational level slightly attenuated these associations.
Residential exposure to traffic-related air pollution increases the mortality risk after hospitalization with acute HF. Reducing exposure to traffic-related emissions may improve the long-term prognosis of HF patients.
air pollution; epidemiology; follow-up studies; heart failure; survival