Comparing the Health Effects of Ambient Particulate Matter Estimated Using Ground-Based versus Remote Sensing Exposure Estimates

BACKGROUND: Remote sensing (RS) is increasingly used for exposure assessment in epidemiological and burden of disease studies, including those investigating whether chronic exposure to ambient fine particulate matter (PM2.5) is associated with mortality. OBJECTIVES: To compare relative risk estimates of mortality from diseases of the circulatory system for PM2.5 modeled from RS with that for PM2.5 modeled using ground-level information. METHODS: We geocoded the baseline residence of 668,629 American Cancer Society Cancer Prevention Study II (CPS-II) cohort participants followed from 1982 to 2004 and assigned PM2.5 levels to all participants using seven different exposure models. Most of the exposure models were averaged for the years 2002-2004, while one RS estimate was for a longer, contemporaneous period. We used Cox proportional hazards regression to estimate relative risks (RR) for the association of PM2.5 with circulatory mortality and ischemic heart disease. RESULTS: Estimates of mortality risk differed among exposure models. The smallest relative risk was observed for the RS estimates that excluded ground-based monitors for circulatory deaths (RR = 1.02 (95% confidence interval (CI): 1.00-1.04 per 10 microg/m3 increment in PM2.5). The largest relative risk was observed for the land use regression model that included traffic information (RR = 1.14, 95% CI: 1.11-1.17 per 10 microg/m3 increment in PM2.5). CONCLUSIONS: We found significant associations between PM2.5 and mortality in every model; however, relative risks estimated from exposure models using ground-based information were generally larger than those estimated with RS alone

Temporal aspects of air pollutant measures in epidemiologic analysis: a simulation study.

Numerous observational studies have assessed the association between ambient air pollution and chronic disease incidence, but there is no uniform approach to create an exposure metric that captures the variability in air pollution through time and determines the most relevant exposure window. The purpose of the present study was to assess ways of modeling exposure to air pollution in relation to incident hypertension. We simulated data on incident hypertension to assess the performance of six air pollution exposure metrics, using characteristics from the Black Women's Health Study. Each metric made different assumptions about how to incorporate time trends in pollutant data, and the most relevant window of exposure. We use observed values for particulate matter ≤ 2.5 microns (PM2.5) for this cohort to create the six exposure metrics and fit Cox proportional hazards models to the simulated data using the six metrics. The optimal exposure metric depends on the underlying association between PM2.5 and disease, which is unknown. Metrics that incorporate exposure information from multiple years tend to be more robust and suffer from less bias. This study provides insight into factors that influence the metric used to quantifying exposure to PM2.5 and suggests the need for careful sensitivity analyses

Ambient Air Pollution and 16-Year Weight Change in African-American Women

IntroductionSubstantial research has been dedicated to understanding the reasons for the dramatic rise in obesity rates in the U.S. in the last 2 decades. Animal studies and epidemiologic studies in children have suggested that air pollution might contribute to weight gain. This study investigates the association between ambient air pollution and weight gain over 16 years of follow-up (1995-2011) in a large cohort of African-American women in the U.S.MethodsThis study assessed associations of fine particulate matter, ozone, and nitrogen dioxide with weight gain using a linear random effects model. All analyses were conducted in 2015.ResultsThere was no statistically significant association between weight change and fine particulate matter (mean weight change over 16 years per interquartile range [2.9 μg/m(3)], 0.12 kg; 95% CI=-0.10, 0.35) and ozone (0.16 kg per interquartile range [6.7 ppb]; 95% CI=-0.11, 0.43). There was a small decrease in weight associated with nitrogen dioxide (-0.50 per interquartile range [9.7 ppb]; 95% CI=-0.77, -0.23).ConclusionsThe results do not provide support for an association of air pollution with weight gain in African-American adult women

Assessment of traffic-related noise in three cities in the United States

BackgroundTraffic-related noise is a growing public health concern in developing and developed countries due to increasing vehicle traffic. Epidemiological studies have reported associations between noise exposure and high blood pressure, increased risk of hypertension and heart disease, and stress induced by sleep disturbance and annoyance. These findings motivate the need for regular noise assessments within urban areas. This paper assesses the relationships between traffic and noise in three US cities.MethodsNoise measurements were conducted in downtown areas in three cities in the United States: Atlanta, Los Angeles, and New York City. For each city, we measured ambient noise levels, and assessed their correlation with simultaneously measured vehicle counts, and with traffic data provided by local Metropolitan Planning Organizations (MPO). Additionally, measured noise levels were compared to noise levels predicted by the Federal Highway Administration's Traffic Noise Model using (1) simultaneously measured traffic counts or (2) MPO traffic data sources as model input.ResultsWe found substantial variations in traffic and noise within and between cities. Total number of vehicle counts explained a substantial amount of variation in measured ambient noise in Atlanta (78%), Los Angeles (58%), and New York City (62%). Modeled noise levels were moderately correlated with measured noise levels when observed traffic counts were used as model input. Weaker correlations were found when MPO traffic data was used as model input.ConclusionsAmbient noise levels measured in all three cities were correlated with traffic data, highlighting the importance of traffic planning in mitigating noise-related health effects. Model performance was sensitive to the traffic data used as input. Future noise studies that use modeled noise estimates should evaluate traffic data quality and should ideally include other factors, such as local roadway, building, and meteorological characteristics

Obesity and weight gain in relation to incidence of sarcoidosis in US black women: Data from the Black Women\u27s Health Study

BACKGROUND: Sarcoidosis, a systemic disorder characterized by chronic granulomatous infl ammation, occurs more frequently among US black women, as do overweight and obesity. Little is known about the relation of overweight and obesity, which induce chronic infl ammation, to incidence of sarcoidosis. METHODS: We assessed the relation of obesity and weight gain to the incidence of sarcoidosis in the Black Women\u27s Health Study, a follow-up study of 59,000 US black women aged 21 to 69 years at baseline in 1995. Information on weight at age 18 years, height, current weight, incident sarcoidosis, and covariates was collected at baseline and on biennial follow-up questionnaires. Cox regression models adjusted for age, education, geographic region, smoking, alcohol consumption, and physical activity were used to estimate incidence rate ratios (IRRs) and 95% CIs. RESULTS: From 1995 through 2011, 454 incident cases of sarcoidosis occurred during 707,557 person-years of follow-up. The incidence of sarcoidosis increased with increasing BMI and weight gain. The IRR was 1.40 (95% CI, 0.88-2.25) for BMI ≥ 30 kg/m 2 at age 18 years relative to 20 to 24 kg/m2 (P trend =.18), 1.42 (95% CI, 1.07-1.89) for BMI ≥ 35 kg/m2 at baseline relative to 20 to 24 kg/m2 (P trend =.01), and 1.47 (95% CI, 1.10-1.97) for a weight gain between age 18 years and baseline of ≥ 30 kg relative to 0 to 9 kg (P trend =.16). In stratified analyses, there were significant trends of sarcoidosis incidence with increasing BMI and weight gain in women aged ≥ 45 years and ever smokers. CONCLUSIONS: The present study provides evidence that weight gain and obesity during adulthood are associated with increased sarcoidosis incidence