Associations between fine particulate matter and mortality in the 2001 Canadian Census Health and Environment Cohort.

BACKGROUND: Large cohort studies have been used to characterise the association between long-term exposure to fine particulate matter (PM2.5) air pollution with non-accidental, and cause-specific mortality. However, there has been no consensus as to the shape of the association between concentration and response. METHODS: To examine the shape of this association, we developed a new cohort based on respondents to the 2001 Canadian census long-form. We applied new annual PM2.5 concentration estimates based on remote sensing and ground measurements for Canada at a 1km spatial scale from 1998 to 2011. We followed 2.4 million respondents who were non-immigrants aged 25-90 years and did not reside in an institution over a 10 year period for mortality. Exposures were assigned as a 3-year mean prior to the follow-up year. Income tax files were used to account for residential mobility among respondents using postal codes, with probabilistic imputation used for missing postal codes in the tax data. We used Cox survival models to determine hazard ratios (HRs) for cause-specific mortality. We also estimated Shape Constrained Health Impact Functions (a concentration-response function) for selected causes of death. RESULTS: In models stratified by age, sex, airshed, and population centre size, and adjusted for individual and neighbourhood socioeconomic variables, HR estimates for non-accidental mortality were HR = 1.18 (95% CI: 1.15-1.21) per 10µg/m3 increase in concentration. We observed higher HRs for cardiovascular disease (HR=1.25; 95% CI: 1.19-1.31), cardio-metabolic disease (HR = 1.27; 95% CI: 1.21-1.33), ischemic heart disease (HR = 1.36; 95% CI: 1.28-1.44) and chronic obstructive pulmonary disease (COPD) mortality (HR = 1.24; 95% CI: 1.11-1.39) compared to HR for all non-accidental causes of death. For non-accidental, cardio-metabolic, ischemic heart disease, respiratory and COPD mortality, the shape of the concentration-response curve was supra-linear, with larger differences in relative risk for lower concentrations. For both pneumonia and lung cancer, there was some suggestion that the curves were sub-linear. CONCLUSIONS: Associations between ambient concentrations of fine particulate matter and several causes of death were non-linear for each cause of death examined.

Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data.

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR2: 0.33-0.38). For NO2 CTM improved prediction modestly (adjR2: 0.58) compared to models without SAT and CTM (adjR2: 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies.

Response of global particulate-matter-related mortality to changes in local precursor emissions.

Recent Global Burden of Disease (GBD) assessments estimated that outdoor fine-particulate matter (PM2.5) is a causal factor in over 5% of global premature deaths. PM2.5 is produced by a variety of direct and indirect, natural and anthropogenic processes that complicate PM2.5 management. This study develops a proof-of-concept method to quantify the effects on global premature mortality of changes to PM2.5 precursor emissions. Using the adjoint of the GEOS-Chem chemical transport model, we calculated sensitivities of global PM2.5-related premature mortality to emissions of precursor gases (SO2, NOx, NH3) and carbonaceous aerosols. We used a satellite-derived ground-level PM2.5 data set at approximately 10 × 10 km(2) resolution to better align the exposure with population density. We used exposure-response functions from the GBD project to relate mortality to exposure in the adjoint calculation. The response of global mortality to changes in local anthropogenic emissions varied spatially by several orders of magnitude. The largest reductions in mortality for a 1 kg km(-2) yr(-1) decrease in emissions were for ammonia and carbonaceous aerosols in Eastern Europe. The greatest reductions in mortality for a 10% decrease in emissions were found for secondary inorganic sources in East Asia. In general, a 10% decrease in SO2 emissions was the most effective source to control, but regional exceptions were found.

Ambient Fine Particulate Matter Air Pollution and Risk of Weight Gain and Obesity in United States Veterans: An Observational Cohort Study.

BACKGROUND: Experimental evidence and studies of children and adolescents suggest that ambient fine particulate matter [particulate matter ≤2.5µm in aerodynamic diameter (PM2.5)] air pollution may be obesogenic, but the relationship between PM2.5 and the risk of body weight gain and obesity in adults is uncertain. OBJECTIVES: Our goal was to characterize the association between PM2.5 and the risks of weight gain and obesity. METHODS: We followed 3,902,440 U.S. Veterans from 2010 to 2018 (median 8.1 y, interquartile range: 7.3-8.4) and assigned time-updated PM2.5 exposures by linking geocoded residential street addresses with satellite-based estimates of surface-level PM2.5 mass (at ∼1-km2 resolution). Associations with PM2.5 were estimated using Cox proportional hazards models for incident obesity [body mass index (BMI)≥30 kg/m2] and a 10-lb increase in weight relative to baseline and linear mixed models for associations with intra-individual changes in BMI and weight. RESULTS: A 10-µg/m3 higher average annual PM2.5 concentration was associated with risk of incident obesity [n=2,325,769; hazard ratio (HR)=1.08 (95% CI: 1.06, 1.11)] and the risk of a 10-lb (4.54 kg) increase in weight [HR=1.07 (95% CI: 1.06, 1.08)] and with higher intra-individual changes in BMI [0.140 kg/m2 per year (95% CI: 0.139, 0.142)] and weight [0.968 lb/y (95% CI: 0.955, 0.981)]. Nonlinear exposure-response models indicated associations at PM2.5 concentrations below the national standard of 12 µg/m3. As expected, a negative exposure control (ambient air sodium) was not associated with obesity or weight gain. Associations were consistent in direction and magnitude across sensitivity analyses that included alternative outcomes and exposures assigned at different spatial resolutions. DISCUSSION: PM2.5 air pollution was associated with the risk of obesity and weight gain in a large predominantly male cohort of U.S. Veterans. Discussions about health effects of PM2.5 should include its association with obesity, and deliberations about the epidemiology of obesity should consider its association with PM2.5. Investigation in other cohorts will deepen our understanding of the relationship between PM2.5 and weight gain and obesity. https://doi.org/10.1289/EHP7944.

Long-term exposure to iron and copper in fine particulate air pollution and their combined impact on reactive oxygen species concentration in lung fluid: a population-based cohort study of cardiovascular disease incidence and mortality in Toronto, Canada.

BACKGROUND: Exposure to fine particulate (PM2.5) air pollution is associated with increased cardiovascular disease (CVD), but less is known about its specific components, such as metals originating from non-tailpipe emissions. We investigated the associations of long-term exposure to metal components [iron (Fe) and copper (Cu)] in PM2.5 with CVD incidence. METHODS: We conducted a population-based cohort study in Toronto, Canada. Exposures to Fe and Cu in PM2.5 and their combined impact on the concentration of reactive oxygen species (ROS) in lung fluid were estimated using land use regression models. Incidence of acute myocardial infarction (AMI), congestive heart failure (CHF) and CVD death was ascertained using health administrative datasets. We used mixed-effects Cox regression models to examine the associations between the exposures and health outcomes. A series of sensitivity analyses were conducted, including indirect adjustment for individual-level cardiovascular risk factors (e.g. smoking), and adjustment for PM2.5 and nitrogen dioxide (NO2). RESULTS: In single-pollutant models, we found positive associations between the three exposures and all three outcomes, with the strongest associations detected for the estimated ROS. The associations of AMI and CHF were sensitive to indirect adjustment, but remained robust for CVD death in all sensitivity analyses. In multi-pollutant models, the associations of the three exposures generally remained unaltered. Interestingly, adjustment for ROS did not substantially change the associations between PM2.5 and CVD, but attenuated the associations of NO2. CONCLUSIONS: Long-term exposure to Fe and Cu in PM2.5 and their combined impact on ROS were consistently associated with increased CVD death.

Fine particular matter and its constituents in air pollution and gestational diabetes mellitus.

BACKGROUND: Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM2.5 (particular matter ≤ 2.5 µm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China. METHODS: The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders. RESULTS: A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, [adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01-1.22]. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05-1.23), black carbon (aOR = 1.15; 95%CI: 1.07-1.25) and nitrate (aOR = 1.13; 95%CI: 1.02-1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM2.5 mass and accounting for multi-collinearity. CONCLUSIONS: Exposure to PM2.5 in 2nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.

Evaluation of Maternal Exposure to PM2.5 and Its Components on Maternal and Neonatal Thyroid Function and Birth Weight: A Cohort Study.

Background: Particulate matter (PM) air pollution is an environmental risk to public health. The prevalence of thyroid disease during pregnancy has increased rapidly in recent decades, but the available data on the relationships among air pollution, thyroid function, and birth outcomes in pregnant women, particularly in China, are scarce. We aimed to evaluate the association between maternal exposure to PM2.5 and its components and maternal and neonatal thyroid function and to investigate whether thyroid function acts as a mediator between air pollution and birth weight. Methods: In this prospective birth cohort study, the levels of maternal exposure to PM2.5 and its components during the first trimester were assessed in 433 pregnant women in Nanjing, China, enrolled during 2014-2015. We evaluated the levels of maternal exposure to PM2.5 and its six main constituents-organic matter (OM), black carbon (BC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and soil dust-using the V4.CH.02 product of the Dalhousie University Atmospheric Composition Analysis Group. The maternal serum-free thyroxine (fT4), thyrotropin (TSH), and thyroid peroxidase antibody (TPOAb) levels during the second trimester were measured through electrochemiluminescent microparticle immunoassays. The neonatal TSH levels were detected using an AutoDELFIA Neonatal TSH kit within 72 hours after birth, and the birth weight Z-score of each newborn was estimated. Results: Higher exposure to maternal PM2.5 and some components (BC and NH4+) decreased the maternal fT4 level (p < 0.05), and the birth weight Z-score was decreased (p < 0.05) by higher exposure to maternal PM2.5 and some components (OM, BC, NO3-, and NH4+). A mediation analysis clarified that the maternal fT4 levels explained 15.9%, 18.4%, and 20.9% of the associations of maternal PM2.5, BC, and NH4+ exposure with the birth weight Z-score, respectively (p < 0.05). After additional sensitivity analyses including only nonpreterm participants (n = 418) and non-TPOAb-positive participants (n = 415), the models remained stable. Conclusions: Our results suggest an inverse association between maternal exposure to PM2.5 and its components and the maternal fT4 levels. Maternal fT4 might act as a mediator between exposure to PM2.5 and its components and birth weight.