Background: Epidemiologic studies have reported associations between fine particles (aerodynamic diameter ≤ 2.5 µm; PM₂.₅) and mortality. However, concerns have been raised regarding the sensitivity ...of the results to model specifications, lower exposures, and averaging time. Objective: We addressed these issues using 11 additional years of follow-up of the Harvard Six Cities study, incorporating recent lower exposures. Methods: We replicated the previously applied Cox regression, and examined different time lags, the shape of the concentration—response relationship using penalized splines, and changes in the slope of the relation over time. We then conducted Poisson survival analysis with time-varying effects for smoking, sex, and education. Results: Since 2001, average PM₂.₅ levels, for all six cities, were < 18 µg/m³. Each increase in PM₂.₅ (10 µg/m³) was associated with an adjusted increased risk of all-cause mortality (PM₂.₅ average on previous year) of 14% 95% confidence interval (CI): 7, 22, and with 26% (95% CI: 14, 40) and 37% (95% CI: 7, 75) increases in cardiovascular and lung-cancer mortality (PM₂.₅ average of three previous years), respectively. The concentration-response relationship was linear down to PM₂.₅ concentrations of 8 µg/m³. Mortality rate ratios for PM₂.₅ fluctuated over time, but without clear trends despite a substantial drop in the sulfate fraction. Poisson models produced similar results. Conclusions: These results suggest that further public policy efforts that reduce fine particulate matter air pollution are likely to have continuing public health benefits.
Green, natural environments may ameliorate adverse environmental exposures (e.g., air pollution, noise, and extreme heat), increase physical activity and social engagement, and lower stress.
We aimed ...to examine the prospective association between residential greenness and mortality.
Using data from the U.S.-based Nurses' Health Study prospective cohort, we defined cumulative average time-varying seasonal greenness surrounding each participant's address using satellite imagery Normalized Difference Vegetation Index (NDVI). We followed 108,630 women and observed 8,604 deaths between 2000 and 2008.
In models adjusted for mortality risk factors (age, race/ethnicity, smoking, and individual- and area-level socioeconomic status), women living in the highest quintile of cumulative average greenness (accounting for changes in residence during follow-up) in the 250-m area around their home had a 12% lower rate of all-cause nonaccidental mortality 95% confidence interval (CI); 0.82, 0.94 than those in the lowest quintile. The results were consistent for the 1,250-m area, although the relationship was slightly attenuated. These associations were strongest for respiratory and cancer mortality. The findings from a mediation analysis suggested that the association between greenness and mortality may be at least partly mediated by physical activity, particulate matter < 2.5 μm, social engagement, and depression.
Higher levels of green vegetation were associated with decreased mortality. Policies to increase vegetation may provide opportunities for physical activity, reduce harmful exposures, increase social engagement, and improve mental health. Planting vegetation may mitigate the effects of climate change; in addition, evidence of an association between vegetation and lower mortality rates suggests it also might be used to improve health.
James P, Hart JE, Banay RF, Laden F. 2016. Exposure to greenness and mortality in a nationwide prospective cohort study of women. Environ Health Perspect 124:1344-1352; http://dx.doi.org/10.1289/ehp.1510363.
Exposure to traffic-related air pollutants is an important public health issue. Here, we present a systematic review and meta-analysis of research examining the relationship of measures of nitrogen ...oxides (NOx) and of various measures of traffic-related air pollution exposure with lung cancer.
We conducted random-effects meta-analyses of studies examining exposure to nitrogen dioxide (NO2) and NOx and its association with lung cancer. We identified 20 studies that met inclusion criteria and provided information necessary to estimate the change in lung cancer per 10-μg/m3 increase in exposure to measured NO2. Further, we qualitatively assessed the evidence of association between distance to roadways and traffic volume associated with lung cancer.
The meta-estimate for the change in lung cancer associated with a 10-μg/m3 increase in exposure to NO2 was 4% (95% CI: 1%, 8%). The meta-estimate for change in lung cancer associated with a 10-μg/m3 increase in NOx was similar and slightly more precise, 3% (95% CI: 1%, 5%). The NO2 meta-estimate was robust to different confounding adjustment sets as well as the exposure assessment techniques used. Trim-and-fill analyses suggest that if publication bias exists, the overall meta-estimate is biased away from the null. Forest plots for measures of traffic volume and distance to roadways largely suggest a modest increase in lung cancer risk.
We found consistent evidence of a relationship between NO2, as a proxy for traffic-sourced air pollution exposure, with lung cancer. Studies of lung cancer related to residential proximity to roadways and NOx also suggest increased risk, which may be attributable partly to air pollution exposure. The International Agency for Research on Cancer recently classified outdoor air pollution and particulate matter as carcinogenic (Group 1). These meta-analyses support this conclusion, drawing particular attention to traffic-sourced air pollution.
Hamra GB, Laden F, Cohen AJ, Raaschou-Nielsen O, Brauer M, Loomis D. 2015. Lung cancer and exposure to nitrogen dioxide and traffic: a systematic review and meta-analysis. Environ Health Perspect 123:1107-1112; http://dx.doi.org/10.1289/ehp.1408882.
Particulate matter (PM) in outdoor air pollution was recently designated a Group I carcinogen by the International Agency for Research on Cancer (IARC). This determination was based on the evidence ...regarding the relationship of PM2.5 and PM10 to lung cancer risk; however, the IARC evaluation did not include a quantitative summary of the evidence.
Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between PM and lung cancer.
We conducted meta-analyses of studies examining the relationship of exposure to PM2.5 and PM10 with lung cancer incidence and mortality. In total, 18 studies met our inclusion criteria and provided the information necessary to estimate the change in lung cancer risk per 10-μg/m3 increase in exposure to PM. We used random-effects analyses to allow between-study variability to contribute to meta-estimates.
The meta-relative risk for lung cancer associated with PM2.5 was 1.09 (95% CI: 1.04, 1.14). The meta-relative risk of lung cancer associated with PM10 was similar, but less precise: 1.08 (95% CI: 1.00, 1.17). Estimates were robust to restriction to studies that considered potential confounders, as well as subanalyses by exposure assessment method. Analyses by smoking status showed that lung cancer risk associated with PM2.5 was greatest for former smokers 1.44 (95% CI: 1.04, 1.22), followed by never-smokers 1.18 (95% CI: 1.00, 1.39), and then current smokers 1.06 (95% CI: 0.97, 1.15). In addition, meta-estimates for adenocarcinoma associated with PM2.5 and PM10 were 1.40 (95% CI: 1.07, 1.83) and 1.29 (95% CI: 1.02, 1.63), respectively.
The results of these analyses, and the decision of the IARC Working Group to classify PM and outdoor air pollution as carcinogenic (Group 1), further justify efforts to reduce exposures to air pollutants that can arise from many sources.
Background: Particulate matter (PM) in outdoor air pollution was recently designated a Group I carcinogen by the International Agency for Research on Cancer (IARC). This determination was based on ...the evidence regarding the relationship of PM2.5 and PM10 to lung cancer risk; however, the IARC evaluation did not include a quantitative summary of the evidence. Objective: Our goal was to provide a systematic review and quantitative summary of the evidence regarding the relationship between PM and lung cancer. Methods: We conducted meta-analyses of studies examining the relationship of exposure to PM2.5 and PM10 with lung cancer incidence and mortality. In total, 18 studies met our inclusion criteria and provided the information necessary to estimate the change in lung cancer risk per 10- mu g/m3 increase in exposure to PM. We used random-effects analyses to allow between-study variability to contribute to meta-estimates. Results: The meta-relative risk for lung cancer associated with PM2.5 was 1.09 (95% CI: 1.04, 1.14). The meta-relative risk of lung cancer associated with PM10 was similar, but less precise: 1.08 (95% CI: 1.00, 1.17). Estimates were robust to restriction to studies that considered potential confounders, as well as subanalyses by exposure assessment method. Analyses by smoking status showed that lung cancer risk associated with PM2.5 was greatest for former smokers 1.44 (95% CI: 1.04, 1.22), followed by never-smokers 1.18 (95% CI: 1.00, 1.39), and then current smokers 1.06 (95% CI: 0.97, 1.15). In addition, meta-estimates for adenocarcinoma associated with PM2.5 and PM10 were 1.40 (95% CI: 1.07, 1.83) and 1.29 (95% CI: 1.02, 1.63), respectively. Conclusion: The results of these analyses, and the decision of the IARC Working Group to classify PM and outdoor air pollution as carcinogenic (Group 1), further justify efforts to reduce exposures to air pollutants that can arise from many sources. Citation: Hamra GB, Guha N, Cohen A, Laden F, Raaschou-Nielsen O, Samet JM, Vineis P, Forastiere F, Saldiva P, Yorifuji T, Loomis D. 2014. Outdoor particulate matter exposure and lung cancer: a systematic review and meta-analysis. Environ Health Perspect 122:906-911; http://dx.doi.org/10.1289/ehp.1408092
Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep ...learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.
Objective To determine whether higher past exposure to particulate air pollution is associated with prevalent high symptoms of anxiety.Design Observational cohort study.Setting Nurses’ Health ...Study.Participants 71 271 women enrolled in the Nurses’ Health Study residing throughout the contiguous United States who had valid estimates on exposure to particulate matter for at least one exposure period of interest and data on anxiety symptoms.Main outcome measures Meaningfully high symptoms of anxiety, defined as a score of 6 points or greater on the phobic anxiety subscale of the Crown-Crisp index, administered in 2004.Results The 71 271 eligible women were aged between 57 and 85 years (mean 70 years) at the time of assessment of anxiety symptoms, with a prevalence of high anxiety symptoms of 15%. Exposure to particulate matter was characterized using estimated average exposure to particulate matter <2.5 μm in diameter (PM2.5) and 2.5 to 10 μm in diameter (PM2.5-10) in the one month, three months, six months, one year, and 15 years prior to assessment of anxiety symptoms, and residential distance to the nearest major road two years prior to assessment. Significantly increased odds of high anxiety symptoms were observed with higher exposure to PM2.5 for multiple averaging periods (for example, odds ratio per 10 µg/m3 increase in prior one month average PM2.5: 1.12, 95% confidence interval 1.06 to 1.19; in prior 12 month average PM2.5: 1.15, 1.06 to 1.26). Models including multiple exposure windows suggested short term averaging periods were more relevant than long term averaging periods. There was no association between anxiety and exposure to PM2.5-10. Residential proximity to major roads was not related to anxiety symptoms in a dose dependent manner.Conclusions Exposure to fine particulate matter (PM2.5) was associated with high symptoms of anxiety, with more recent exposures potentially more relevant than more distant exposures. Research evaluating whether reductions in exposure to ambient PM2.5 would reduce the population level burden of clinically relevant symptoms of anxiety is warranted.
Objectives This study sought to evaluate the association of air pollution with the onset of atrial fibrillation (AF). Background Air pollution in general and more specifically particulate matter has ...been associated with cardiovascular events. Although ventricular arrhythmias are traditionally thought to convey the increased cardiovascular risk, AF may also contribute. Methods Patients with dual chamber implantable cardioverter-defibrillators (ICDs) were enrolled and followed prospectively. The association of AF onset with air quality including ambient particulate matter <2.5 μm aerodynamic diameter (PM2.5 ), black carbon, sulfate, particle number, NO2 , SO2 , and O3 in the 24 h prior to the arrhythmia was examined utilizing a case-crossover analysis. In sensitivity analyses, associations with air pollution between 2 and 48 h prior to the AF were examined. Results Of 176 patients followed for an average of 1.9 years, 49 patients had 328 episodes of AF lasting ≥30 s. Positive but nonsignificant associations were found for PM2.5 in the prior 24 h, but stronger associations were found with shorter exposure windows. The odds of AF increased by 26% (95% confidence interval: 8% to 47%) for each 6.0 μg/m3 increase in PM2.5 in the 2 h prior to the event (p = 0.004). The odds of AF were highest at the upper quartile of mean PM2.5. Conclusions PM was associated with increased odds of AF onset within hours following exposure in patients with known cardiac disease. Air pollution is an acute trigger of AF, likely contributing to the pollution-associated adverse cardiac outcomes observed in epidemiological studies.
Autism spectrum disorder (ASD) is a developmental disorder with increasing prevalence worldwide, yet has unclear etiology.
We explored the association between maternal exposure to particulate matter ...(PM) air pollution and odds of ASD in her child.
We conducted a nested case-control study of participants in the Nurses' Health Study II (NHS II), a prospective cohort of 116,430 U.S. female nurses recruited in 1989, followed by biennial mailed questionnaires. Subjects were NHS II participants' children born 1990-2002 with ASD (n = 245), and children without ASD (n = 1,522) randomly selected using frequency matching for birth years. Diagnosis of ASD was based on maternal report, which was validated against the Autism Diagnostic Interview-Revised in a subset. Monthly averages of PM with diameters ≤ 2.5 μm (PM2.5) and 2.5-10 μm (PM10-2.5) were predicted from a spatiotemporal model for the continental United States and linked to residential addresses.
PM2.5 exposure during pregnancy was associated with increased odds of ASD, with an adjusted odds ratio (OR) for ASD per interquartile range (IQR) higher PM2.5 (4.42 μg/m3) of 1.57 (95% CI: 1.22, 2.03) among women with the same address before and after pregnancy (160 cases, 986 controls). Associations with PM2.5 exposure 9 months before or after the pregnancy were weaker in independent models and null when all three time periods were included, whereas the association with the 9 months of pregnancy remained (OR = 1.63; 95% CI: 1.08, 2.47). The association between ASD and PM2.5 was stronger for exposure during the third trimester (OR = 1.42 per IQR increase in PM2.5; 95% CI: 1.09, 1.86) than during the first two trimesters (ORs = 1.06 and 1.00) when mutually adjusted. There was little association between PM10-2.5 and ASD.
Higher maternal exposure to PM2.5 during pregnancy, particularly the third trimester, was associated with greater odds of a child having ASD.
Background Rotating night shift work imposes circadian strain and is linked to the risk of several chronic diseases. Purpose To examine associations between rotating night shift work and all-cause; ...cardiovascular disease (CVD); and cancer mortality in a prospective cohort study of 74,862 registered U.S. nurses from the Nurses’ Health Study. Methods Lifetime rotating night shift work (defined as ≥3 nights/month) information was collected in 1988. During 22 years (1988–2010) of follow-up, 14,181 deaths were documented, including 3,062 CVD and 5,413 cancer deaths. Cox proportional hazards models estimated multivariable-adjusted hazard ratios (HRs) and 95% CIs. Results All-cause and CVD mortality were significantly increased among women with ≥5 years of rotating night shift work, compared to women who never worked night shifts. Specifically, for women with 6–14 and ≥15 years of rotating night shift work, the HRs were 1.11 (95% CI=1.06, 1.17) and 1.11 (95% CI=1.05, 1.18) for all-cause mortality and 1.19 (95% CI=1.07, 1.33) and 1.23 (95% CI=1.09, 1.38) for CVD mortality. There was no significant association between rotating night shift work and all-cancer mortality (HR≥15years =1.08, 95% CI=0.98, 1.19) or mortality of any individual cancer, with the exception of lung cancer (HR≥15years =1.25, 95% CI=1.04, 1.51). Conclusions Women working rotating night shifts for ≥5 years have a modest increase in all-cause and CVD mortality; those working ≥15 years of rotating night shift work have a modest increase in lung cancer mortality. These results add to prior evidence of a potentially detrimental effect of rotating night shift work on health and longevity.
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