Association of abnormal-glucose tolerance during pregnancy with exposure to PM2.5 components and sources.

Maternal exposure to PM2.5 has been associated with abnormal glucose tolerance during pregnancy, but little is known about which constituents and sources are most relevant to glycemic effects. We conducted a retrospective cohort study of 1148 pregnant women to investigate associations of PM2.5 chemical components with gestational diabetes mellitus (GDM) and impaired glucose tolerance (IGT) and to identify the most harmful sources in Heshan, China from January 2015 to July 2016. We measured PM2.5 using filter-based method and analyzed them for 28 constituents, including carbonaceous species, water-soluble ions and metal elements. Contributions of PM2.5 sources were assessed by positive matrix factorization (PMF). Logistic regression model was used to estimate composition-specific and source-specific effects on GDM/IGT. Random forest algorithm was applied to evaluate the relative importance of components to GDM and IGT. PM2.5 total mass and several chemical constituents were associated with GDM and IGT across the early to mid-gestation periods, as were the PM2.5 sources fossil fuel/oil combustion, road dust, metal smelting, construction dust, electronic waster, vehicular emissions and industrial emissions. The trimester-specific associations differed among pollutants and sources. The third and highest quartile of elemental carbon, ammonium (NH4+), iron (Fe) and manganese (Mn) across gestation were consistently associated with higher odds of GDM/IGT. Maternal exposures to zinc (Zn), titanium (Ti) and vehicular emissions during the first trimester, and vanadium (V), nickel (Ni), road dust and fossil fuel/oil combustion during the second trimester were more important for GDM/IGT. This study provides important new evidence that maternal exposure to PM2.5 components and sources is significantly related to elevated risk for abnormal glucose tolerance during pregnancy.

Insights into the source-specific health risk of ambient particle-bound metals in the Pearl River Delta region, China.

Quantification of source-specific health risks of PM2.5 plays an essential role in health-oriented air pollution control. However, there is limited evidence supporting the source-based risk apportionment of particle-bound metals. In this study, source-specific cancer and non-cancer risk characterization of 12 particle-bound metals was performed in the Pearl River Delta (PRD) region, China. A combination of health risk assessment model and receptor-based source apportionment modeling with positive matrix factorization (PMF) was applied for characterizing the spatial-temporal patterns for inhalation health risks of particle-bound metals in three main city clusters, inland area and coastal area in the region from December 2014 through July 2016. Results showed that the carcinogenic risk of particle-bound metals for adults (4.13 × 10-5) was higher than that for children (9.53 × 10-6) in the PRD region. The highest and significant non-carcinogenic risk was found in the northwest city cluster. Industrial emission (63.3%) were the dominant contributors to the cancer risk, while the main contributors to the non-cancer risk were the vehicle emission source (33.2%) in the dry season and industrial emission (30.8%) in the wet season. Our results provide important evidence for spatial source-specific health risks with temporal characteristics of particle-bound metals in most densely populated areas in the southern China, and suggest that reduction of industrial and vehicle emissions could facilitate more cost-effective PM2.5 control measures to improve human health.

Association of ambient particle pollution with gestational diabetes mellitus and fasting blood glucose levels in pregnant women from two Chinese birth cohorts.

BACKGROUND: Fasting blood glucose may capture the adverse effects of air pollution on pregnant women better than the incidence of gestational diabetes mellitus (GDM), but evidence on the association between air pollution and maternal glucose concentrations is limited. OBJECTIVE: To investigate the associations between air pollutants, GDM and fasting blood glucose during pregnancy. METHODS: We recruited 2326 pregnant women from two birth cohorts located in Guangzhou and Heshan, the Pearl River Delta region (PRD), China. PM10, PM2.5 and black carbon (BC) exposure concentrations in the first and second trimesters of pregnancy were collected at fixed-site monitoring stations for each cohort. Multiple logistic regressions were employed to estimate the associations between particle pollution and GDM. Mixed-effects models were used to evaluate the associations of air pollutants with blood glucose levels. Restricted cubic spline functions were fitted to visualize the concentration-response relationships. Distributed lag non-linear models were used to estimate week-specific lag effects of particle pollution exposure on GDM and blood glucose. Unconstrained distributed lag models with lags of 0-3 weeks were used to examine potential cumulative effects. RESULTS: We observed positive and significant associations of PM10, PM2.5 and BC exposure with fasting glucose, particularly in the second trimester. PM10, PM2.5 and BC were strongly correlated and displayed similar cumulative (lag 0-3 weeks) associations with fasting blood glucose. Exposure to particle pollution was not associated with 1-h or 2-h blood glucose. Models estimating the association between air pollutants and GDM were consistent with statistical insignificance. CONCLUSIONS: Based on the results of the present study, exposure to air pollution during pregnancy exerts cumulative, adverse effects on fasting glucose levels. This study provides preliminary support for the use of blood glucose levels to explore the potential health impact of air pollution on pregnant women.

Respiratory health effects of residential individual and cumulative risk factors in children living in two cities of the Pearl River Delta Region, China.

BACKGROUND: Indoor environment is complex, with many factors potentially interacting with each other to affect health. However, previous studies have usually focused on effect of a single factor. Assessment of the combined effects of multiple factors can help with understanding the overall health risk. METHODS: A cross-sectional study was conducted among 2,306 school children in Guangzhou and Shenzhen. Questionnaire data on respiratory symptoms and diseases were collected along with sociodemographic and residential environmental information. A subset of children (N=987) were measured for their lung function. A random forest algorithm was applied to screen the top-ranked indoor environmental exposure variables and to form a composite index for cumulative risk of indoor pollution (CRIP). Logistic regressions were conducted to analyze the independent effect of single indoor environmental risk factors and the combined effect of CRIP on children's respiratory health. Multiple linear regressions were used to examine the independent and combined effects of indoor environmental exposure on lung function. RESULTS: We found that home dampness and molds as well as environmental tobacco smoke (ETS) were significantly and independently associated with increased prevalence of children's respiratory symptoms and diseases and with reduced lung function. A higher CRIP level was significantly associated with increased risk of cough with cold (OR =1.37, 95% CI: 1.05-1.79) and wheeze (OR =2.71, 95% CI: 1.16-6.34). A higher CRIP level was also associated with reduced lung function measured as FVC, FEV1, PEF, FEF25%, FEF25-75% and VC. CONCLUSIONS: In children living in the subtropical region of the Pearl River Delta, home dampness and the presence of mold as well as ETS were individual risk factors for children's respiratory health. The composite CRIP index was associated with respiratory symptoms and lung function, suggesting the utility of this index for predicting the combined effects of multiple risk factors.