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Background: Epidemiological findings regarding the association of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP) are inconsistent; evidence for HDP risk related to PM2.5 components, mixture effects, and windows of susceptibility is limited. We aimed to investigate the relationships between HDP and exposure to PM2.5 during pregnancy. Methods and findings: A large retrospective cohort study was conducted among mothers with singleton pregnancies in Kaiser Permanente Southern California from 2008 to 2017. HDP were defined by International Classification of Diseases-9/10 (ICD-9/10) diagnostic codes and were classified into 2 subcategories based on the severity of HDP: gestational hypertension (GH) and preeclampsia and eclampsia (PE-E). Monthly averages of PM2.5 total mass and its constituents (i.e., sulfate, nitrate, ammonium, organic matter, and black carbon) were estimated using outputs from a fine-resolution geoscience-derived model. Multilevel Cox proportional hazard models were used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of PM2.5 constituents. The distributed lag model was applied to estimate the association between monthly exposure and HDP risk. This study included 386,361 participants (30.3 ± 6.1 years) with 4.8% (17,977/373,905) GH and 5.0% (19,381/386,361) PE-E cases, respectively. In single-pollutant models, we observed increased relative risks for PE-E associated with exposures to PM2.5 total mass [adjusted hazard ratio (HR) per interquartile range: 1.07, 95% confidence interval (CI) [1.04, 1.10] p < 0.001], black carbon [HR = 1.12 (95% CI [1.08, 1.16] p < 0.001)] and organic matter [HR = 1.06 (95% CI [1.03, 1.09] p < 0.001)], but not for GH. The population attributable fraction for PE-E corresponding to the standards of the US Environmental Protection Agency (9 μg/m3) was 6.37%. In multi-pollutant models, the PM2.5 mixture was associated with an increased relative risk of PE-E ([HR = 1.05 (95% CI [1.03, 1.07] p < 0.001)], simultaneous increase in PM2.5 constituents of interest by a quartile) and PM2.5 black carbon gave the greatest contribution of the overall mixture effects (71%) among all individual constituents. The susceptible window is the late first trimester and second trimester. Furthermore, the risks of PE-E associated with PM2.5 exposure were significantly higher among Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods (p < 0.05 for Cochran's Q test). Study limitations include potential exposure misclassification solely based on residential outdoor air pollution, misclassification of disease status defined by ICD codes, the date of diagnosis not reflecting the actual time of onset, and lack of information on potential covariates and unmeasured factors for HDP. Conclusions: Our findings add to the literature on associations between air pollution exposure and HDP. To our knowledge, this is the first study reporting that specific air pollution components, mixture effects, and susceptible windows of PM2.5 may affect GH and PE-E differently. Yi Sun and colleagues investigate the association between hypertensive disorders in pregnancy and particulate air pollution. Author summary: Why was this study done?: Although previous studies have explored the associations of particulate matter ≤2.5 μm (PM2.5) exposure with hypertensive disorders in pregnancy (HDP), earlier findings are inconclusive. Several unaddressed issues remain, such as lack of simultaneous consideration of PM2.5 constituents, mixture effects, windows of susceptibility, and levels of disease severity. What did the researchers do and find?: A retrospective cohort study (N = 386,361) was conducted using electronic health records from Kaiser Permanente Southern California (2008 to 2017) to examine the associations between HDP (mild HDP: gestational hypertension (GH) versus severe HDP: preeclampsia and eclampsia (PE-E)) and exposure to PM2.5, and identify windows of susceptibility to PM2.5 during pregnancy. We found higher risks for PE-E associated with exposures to PM2.5 total mass, organic matter, and black carbon, but not for GH. The main effect of increased PE-E risk was driven by PM2.5 black carbon (71%) and PM2.5 organic matter (26%). The most influential time windows of PM2.5 exposure associated with HDP are the late first trimester and second trimester. Hispanic and African American mothers and mothers who live in low- to middle-income neighborhoods may be more vulnerable to air pollution on HDP risk. What do these findings mean?: Our findings suggest that different PM2.5 chemical constituents and critical exposure windows may affect GH and PE-E differently. Our work highlights the need for further research to investigate different components of air pollutants, levels of disease severity, and various susceptible windows, which is important to better understand the underlying mechanisms between air pollution and HDP and develop corresponding interventions. [ABSTRACT FROM AUTHOR]

Santa Ana winds (SAWs) are associated with anomalous temperatures in coastal Southern California (SoCal). As dry air flows over SoCal's coastal ranges on its way from the elevated Great Basin down to sea level, all SAWs warm adiabatically. Many but not all SAWs produce coastal heat events. The strongest regionally averaged SAWs tend to be cold. In fact, some of the hottest and coldest observed temperatures in coastal SoCal are linked to SAWs. We show that hot and cold SAWs are produced by distinct synoptic dynamics. High-amplitude anticyclonic flow around a blocking high pressure aloft anchored at the California coast produces hot SAWs. Cold SAWs result from anticyclonic Rossby wave breaking over the northwestern U.S. Hot SAWs are preceded by warming in the Great Basin and dry conditions across the Southwestern U.S. Precipitation over the Southwest, including SoCal, and snow accumulation in the Great Basin usually precede cold SAWs. Both SAW flavors, but especially the hot SAWs, yield low relative humidity at the coast. Although cold SAWs tend to be associated with the strongest winds, hot SAWs tend to last longer and preferentially favor wildfire growth. Historically, out of large (> 100 acres) SAW-spread wildfires, 90% were associated with hot SAWs, accounting for 95% of burned area. As health impacts of SAW-driven coastal fall, winter and spring heat waves and impacts of smoke from wildfires have been recently identified, our results have implications for designing early warning systems. The long-term warming trend in coastal temperatures associated with SAWs is focused on January–March, when hot and cold SAW frequency and temperature intensity have been increasing and decreasing, respectively, over our 71-year record. [ABSTRACT FROM AUTHOR]

Wildfires are becoming more frequent and destructive in a changing climate. Fine particulate matter, PM2.5, in wildfire smoke adversely impacts human health. Recent toxicological studies suggest that wildfire particulate matter may be more toxic than equal doses of ambient PM2.5. Air quality regulations however assume that the toxicity of PM2.5 does not vary across different sources of emission. Assessing whether PM2.5 from wildfires is more or less harmful than PM2.5 from other sources is a pressing public health concern. Here, we isolate the wildfire-specific PM2.5 using a series of statistical approaches and exposure definitions. We found increases in respiratory hospitalizations ranging from 1.3 to up to 10% with a 10 μg m−3 increase in wildfire-specific PM2.5, compared to 0.67 to 1.3% associated with non-wildfire PM2.5. Our conclusions point to the need for air quality policies to consider the variability in PM2.5 impacts on human health according to the sources of emission. Recent toxicological studies suggest that wildfire particulate matter may be more toxic than equal doses of ambient PM2.5. Here, the authors show that even for similar exposure levels, PM2.5 from wildfires is considerably more dangerous for respiratory health at the population level. [ABSTRACT FROM AUTHOR]

Key Points: Santa Ana winds have a predominant ventilation effect as background PM2.5 is transported offshore from highly polluted areasA polluting effect occurs when SAWs spread smoke PM2.5 from wildfires inland toward the coastal regionStatistical approaches that relate surface wind and PM2.5 over space and time can help in identifying wildfire PM2.5 Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region's most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space‐time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999–2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial‐temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures. [ABSTRACT FROM AUTHOR]

[Display omitted] • PM 2.5 , PM 10 , NO 2 , and PM 2.5 constituents was associated with an increased GDM risk. • NO 2 and black carbon PM 2.5 contributed most to GDM among air pollution mixtures. • GDM associated with air pollution were higher among Hispanic or overweight mothers. Epidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents. To assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents. Detailed clinical data were obtained for 395,927 pregnancies in southern California (2008–2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter < 2.5 μm (PM 2.5), <10 μm (PM 10), nitrogen dioxide (NO 2), and ozone (O 3) were estimated using kriging interpolation of Environmental Protection Agency's routine monitoring station data, while PM 2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon) were estimated using a fine-resolution geoscience-derived model. A multilevel logistic regression was used to fit single-pollutant models; quantile g-computation approach was applied to estimate the joint effect of air pollution and PM component mixtures. Main analyses adjusted for maternal age, race/ethnicity, education, median family household income, pre-pregnancy BMI, smoking during pregnancy, insurance type, season of conception and year of delivery. The incidence of GDM was 10.9% in the study population. In single-pollutant models, we observed an increased odds for GDM associated with exposures to PM 2.5 , PM 10 , NO 2 and PM 2.5 constituents. The association was strongest for NO 2 [adjusted odds ratio (OR) per interquartile range: 1.176, 95% confidence interval (CI): 1.147–1.205)]. In multi-pollutant models, increased ORs for GDM in association with one quartile increase in air pollution mixtures were found for both kriging-based regional air pollutants (NO 2 , PM 2.5 , and PM 10 , OR = 1.095, 95% CI: 1.082–1.108) and PM 2.5 constituents (i.e., sulfate, nitrate, ammonium, organic matter and black carbon, OR = 1.258, 95% CI: 1.206–1.314); NO 2 (78%) and black carbon (48%) contributed the most to the overall mixture effects among all krigged air pollutants and all PM 2.5 constituents, respectively. The risk of GDM associated with air pollution exposure were significantly higher among Hispanic mothers, and overweight/obese mothers. This study found that exposure to a mixture of ambient PM 2.5 , PM 10 , NO 2 , and PM 2.5 chemical constituents was associated with an increased risk of GDM. NO 2 and black carbon PM 2.5 contributed most to GDM risk. [ABSTRACT FROM AUTHOR]

Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements. Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO 2 , and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time. Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β −0.010, 95%CI -0.025, 0.005; β −0.019, 95%CI -0.034, −0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β −1.001, 95%CI -1.888, −0.131). The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions. • Little is known about the impact of environmental changes on metabolic biomarkers. • Dynamic exposures to environmental conditions were calculated using GPS data. • Baseline environmental conditions can modulate environmental impacts on biomarkers. • Improved environmental exposures may lower fasting glucose concentration and systemic inflammation. [ABSTRACT FROM AUTHOR]

• NO 2 , O 3 , and PM 2.5 exposure can increase premature rupture of membranes (PROM) risk. • Maternal PM 2.5 nitrate, sulfate, and organic matter exposure can increase PROM risk. • The effect of air pollution mixture on PROM may be mainly driven by O 3 exposure. • Underweight mothers can be more vulnerable to PROM associated with air pollution. There is minimal evidence of relationships between maternal air pollution exposure and spontaneous premature rupture of membranes (SPROM), a critical obstetrical problem that can significantly increase maternal and fetal mortality and morbidity. No prior study has explored the PROM risk related to specific components of particulate matter with aerodynamic diameters of ≤ 2.5 µm (PM 2.5). We examined associations between maternal exposure to nitrogen dioxide (NO 2), ozone (O 3), PM 2.5 , PM 10 , and PM 2.5 constituents and SPROM. A large retrospective cohort study was conducted and included 427,870 singleton live births from Kaiser Permanente Southern California during 2008–2018. Monthly averages of NO 2 , O 3 (8-h daily maximum), PM 2.5 , and PM 10 were measured using empirical Bayesian kriging based on measurements from monitoring stations. Data on PM 2.5 sulfate, nitrate, ammonium, organic matter, and black carbon were obtained from a fine-resolution model. A discrete time approach with pooled logistic regressions was used to estimate associations throughout the pregnancy and based on trimesters and gestational months. The quantile-based g-computation models were fitted to examine the effects of 1) the air pollution mixture of four pollutants of interest and 2) the mixture of PM 2.5 components. There were 37,857 SPROM cases (8.8%) in our study population. We observed relationships between SPROM and maternal exposure to NO 2 , O 3 , and PM 2.5. PM 2.5 sulfate, nitrate, ammonium, and organic matter were associated with higher SPROM risks in the single-pollutant model. Mixture analyses demonstrated that the overall effects of the air pollution mixture and PM 2.5 mixture in this study were mainly driven by O 3 and PM 2.5 nitrate, respectively. Underweight mothers had a significantly higher risk of SPROM associated with NO 2. Our findings add to the literature on associations between air pollution exposure and SPROM. This is the first study reporting the impact of PM 2.5 constituents on SPROM. [ABSTRACT FROM AUTHOR]

• Acute heatwave exposure can increase the premature rupture of membranes (PROM) risk. • Younger mothers with lower socioeconomic status have higher heat-related PROM risks. • Air pollution during pregnancy can be a positive effect modifier of heat effects. • More residential green space may mitigate adverse heat effects on PROM. Significant mortality and morbidity in pregnant women and their offspring are linked to premature rupture of membranes (PROM). Epidemiological evidence for heat-related PROM risk is extremely limited. We investigated associations between acute heatwave exposure and spontaneous PROM. We conducted this retrospective cohort study among mothers in Kaiser Permanente Southern California who experienced membrane ruptures during the warm season (May-September) from 2008 to 2018. Twelve definitions of heatwaves with different cut-off percentiles (75th, 90th, 95th, and 98th) and durations (≥ 2, 3, and 4 consecutive days) were developed using the daily maximum heat index, which incorporates both daily maximum temperature and minimum relative humidity in the last gestational week. Cox proportional hazards models were fitted separately for spontaneous PROM, term PROM (TPROM), and preterm PROM (PPROM) with zip codes as the random effect and gestational week as the temporal unit. Effect modification by air pollution (i.e., PM 2.5 and NO 2), climate adaptation measures (i.e., green space and air conditioning [AC] penetration), sociodemographic factors, and smoking behavior was examined. In total, we included 190,767 subjects with 16,490 (8.6%) spontaneous PROMs. We identified a 9–14% increase in PROM risks associated with less intense heatwaves. Similar patterns as PROM were found for TPROM and PPROM. The heat-related PROM risks were greater among mothers exposed to a higher level of PM 2.5 during pregnancy, under 25 years old, with lower education and household income level, and who smoked. Even though climate adaptation factors were not statistically significant effect modifiers, mothers living with lower green space or lower AC penetration were at consistently higher heat-related PROM risks compared to their counterparts. Using a rich and high-quality clinical database, we detected harmful heat exposure for spontaneous PROM in preterm and term deliveries. Some subgroups with specific characteristics were more susceptible to heat-related PROM risk. [ABSTRACT FROM AUTHOR]