Childhood Air Pollution Exposure Associated with Self-reported Bronchitic Symptoms in Adulthood.

Rationale: Few studies have examined the effects of long-term childhood air pollution exposure on adult respiratory health, including whether childhood respiratory effects underlie this relation. Objectives: To evaluate associations between childhood air pollution exposure and self-reported adult bronchitic symptoms while considering child respiratory health in the Southern California Children's Health Study. Methods: Exposures to nitrogen dioxide (NO2), ozone, and particulate matter <2.5 µm and <10 µm in diameter (PM10) assessed using inverse-distance-squared spatial interpolation based on childhood (birth to age 17 yr) residential histories. Bronchitic symptoms (bronchitis, cough, or phlegm in the past 12 mo) were ascertained via a questionnaire in adulthood. Associations between mean air pollution exposure across childhood and self-reported adult bronchitic symptoms were estimated using logistic regression. We further adjusted for childhood bronchitic symptoms and asthma to understand whether associations operated beyond childhood respiratory health impacts. Effect modification was assessed for family history of asthma, childhood asthma, and adult allergies. Measurements and Main Results: A total of 1,308 participants were included (mostly non-Hispanic White [56%] or Hispanic [32%]). At adult assessment (mean age, 32.0 yr; standard deviation [SD], 4.7), 25% reported bronchitic symptoms. Adult bronchitic symptoms were associated with NO2 and PM10 childhood exposures. Odds ratios per 1-SD increase were 1.69 (95% confidence interval, 1.14-2.49) for NO2 (SD, 11.1 ppb) and 1.51 (95% confidence interval, 1.00-2.27) for PM10 (SD, 14.2 µg/m3). Adjusting for childhood bronchitic symptoms or asthma produced similar results. NO2 and PM10 associations were modified by childhood asthma, with greater associations among asthmatic individuals. Conclusions: Childhood NO2 and PM10 exposures were associated with adult bronchitic symptoms. Associations were not explained by childhood respiratory health impacts; however, participants with childhood asthma had stronger associations.

Prenatal Exposure to Source-Specific Fine Particulate Matter and Autism Spectrum Disorder.

In this study, associations between prenatal exposure to fine particulate matter (PM2.5) from 9 sources and development of autism spectrum disorder (ASD) were assessed in a population-based retrospective pregnancy cohort in southern California. The cohort included 318,750 mother-child singleton pairs. ASD cases (N = 4559) were identified by ICD codes. Source-specific PM2.5 concentrations were estimated from a chemical transport model with a 4 × 4 km2 resolution and assigned to maternal pregnancy residential addresses. Cox proportional hazard models were used to estimate the hazard ratios (HR) of ASD development for each individual source. We also adjusted for total PM2.5 mass and in a separate model for all other sources simultaneously. Increased ASD risk was observed with on-road gasoline (HR [CI]: 1.18 [1.13, 1.24]), off-road gasoline (1.15 [1.12, 1.19]), off-road diesel (1.08 [1.05, 1.10]), food cooking (1.05 [1.02, 1.08]), aircraft (1.04 [1.01, 1.06]), and natural gas combustion (1.09 [1.06, 1.11]), each scaled to standard deviation increases in concentration. On-road gasoline and off-road gasoline were robust for other pollutant groups. PM2.5 emitted from different sources may have different impacts on ASD. The results also identify PM source mixtures for toxicological investigations that may provide evidence for future public health policies.

Impact of childhood exposure to traffic related air pollution on adult cardiometabolic health: Exploring the role of perceived stress.

BACKGROUND: Little is known about how childhood exposure to traffic-related air pollution (TRAP) and stress interact to affect adults' cardiometabolic health. We examined this interaction and assessed the impact of over 10 years of childhood TRAP exposure on cardiometabolic health. METHODS: From 2018 to 2023, 313 young adults from the Southern California Children's Health Study were enrolled in a follow-up assessment. Using CALINE4 line source dispersion model, average childhood TRAP exposures (from pregnancy to age 13) were estimated for nitrogen oxides (NOx) from all roads. Traffic density was calculated within a 300-m residential buffer. Cardiometabolic health was assessed in adulthood (mean age 24 ± 1.7) based on blood lipids (total cholesterol, high- and low-density lipoprotein [HDL, LDL], triglycerides), glucose metabolism (fasting glucose, fasting insulin, HbA1c), body composition (BMI, android/gynoid ratio [AG ratio], percent body fat), and blood pressure. A PDAY (Pathobiologic Determinants of Atherosclerosis in Youth) score was generated to evaluate overall cardiometabolic health. Participants' perceived stress was assessed in childhood and adulthood (ages 13 and 24 years, respectively). RESULTS: Results of mixed effects linear models, adjusted for demographics and smoking status, suggested that each standard deviation increase in childhood exposure to traffic-related total NOx was associated with 0.62 increase in PDAY score (95% Confidence Interval [CI]:0.10,1.14), 0.09% increase in HbA1c (95%CI: 0.04, 0.15), 1.19% increase in percent body fat (95%CI: 0.18, 2.20), and 0.96 kg/m2 increase in BMI (0.11, 1.80) in adulthood. Among participants with higher childhood stress levels, we observed significant associations of traffic-related total NOx with total cholesterol, HDL, LDL, HbA1c, insulin, and BMI. None of these associations were significant among people with lower stress levels. We observed similar statistically significant associations of traffic density. CONCLUSION: Long-term childhood exposure to TRAP in childhood may have lasting adverse impacts on cardiometabolic health, especially for children with higher stress levels.

Prenatal exposure to ambient air pollution is associated with neurodevelopmental outcomes at 2 years of age.

BACKGROUND: Higher prenatal ambient air pollution exposure has been associated with impaired neurodevelopment in preschoolers and school-aged children. The purpose of this study was to explore the relationships between prenatal ambient air pollution exposure and neurodevelopment during infancy. METHODS: This study examined 161 Latino mother-infant pairs from the Southern California Mother's Milk Study. Exposure assessments included prenatal nitrogen dioxide (NO2) and particulate matter smaller than 2.5 and 10 microns in diameter (PM2.5 and PM10, respectively). The pregnancy period was also examined as three windows, early, mid, and late, which describe the first, middle, and last three months of pregnancy. Infant neurodevelopmental outcomes at 2 years of age were measured using the Bayley-III Scales of Infant and Toddler Development. Multivariable linear models and distributed lag linear models (DLM) were used to examine relationships between prenatal exposures and neurodevelopmental scores, adjusting for socioeconomic status, breastfeeding frequency, time of delivery, pre-pregnancy body mass index, and infant birthweight and sex. RESULTS: Higher prenatal exposure to PM10 and PM2.5 was negatively associated with composite cognitive score (ß = -2.01 [-3.89, -0.13] and ß = -1.97 [-3.83, -0.10], respectively). In addition, higher average prenatal exposure to PM10 was negatively associated with composite motor (ß = -2.35 [-3.95, -0.74]), scaled motor (ß = -0.77 [-1.30, -0.24]), gross motor (ß = -0.37 [-0.70, -0.04]), fine motor (ß = -0.40 [-0.71, -0.09]), composite language (ß = -1.87 [-3.52, -0.22]), scaled language (ß = -0.61 [-1.18, -0.05]) and expressive communication scaled scores (ß = -0.36 [-0.66, -0.05]). DLMs showed that higher prenatal air pollution exposure during mid and late pregnancy was inversely associated with motor, cognitive, and communication language scores. CONCLUSIONS: Higher exposure to air pollutants during pregnancy, particularly in the mid and late prenatal periods, was inversely associated with scaled and composite motor, cognitive, and language scores at 2 years. These results indicate that prenatal ambient air pollution may negatively impact neurodevelopment in early life.

The Effects of Coexposure to Extremes of Heat and Particulate Air Pollution on Mortality in California: Implications for Climate Change.

Rationale: Extremes of heat and particulate air pollution threaten human health and are becoming more frequent because of climate change. Understanding the health impacts of coexposure to extreme heat and air pollution is urgent. Objectives: To estimate the association of acute coexposure to extreme heat and ambient fine particulate matter (PM2.5) with all-cause, cardiovascular, and respiratory mortality in California from 2014 to 2019. Methods: We used a case-crossover study design with time-stratified matching using conditional logistic regression to estimate mortality associations with acute coexposures to extreme heat and PM2.5. For each case day (date of death) and its control days, daily average PM2.5 and maximum and minimum temperatures were assigned (0- to 3-day lag) on the basis of the decedent's residence census tract. Measurements and Main Results: All-cause mortality risk increased 6.1% (95% confidence interval [CI], 4.1-8.1) on extreme maximum temperature-only days and 5.0% (95% CI, 3.0-8.0) on extreme PM2.5-only days, compared with nonextreme days. Risk increased by 21.0% (95% CI, 6.6-37.3) on days with exposure to both extreme maximum temperature and PM2.5. Increased risk of cardiovascular and respiratory mortality on extreme coexposure days was 29.9% (95% CI, 3.3-63.3) and 38.0% (95% CI, -12.5 to 117.7), respectively, and were more than the sum of individual effects of extreme temperature and PM2.5 only. A similar pattern was observed for coexposure to extreme PM2.5 and minimum temperature. Effect estimates were larger over age 75 years. Conclusions: Short-term exposure to extreme heat and air pollution alone were individually associated with increased risk of mortality, but their coexposure had larger effects beyond the sum of their individual effects.

Exposure to ambient air pollutants, serum miRNA networks, lipid metabolism, and non-alcoholic fatty liver disease in young adults.

BACKGROUND AND AIM: Ambient air pollution (AAP) exposure has been associated with altered blood lipids and liver fat in young adults. MicroRNAs regulate gene expression and may mediate these relationships. This work investigated associations between AAP exposure, serum microRNA networks, lipid profiles, and non-alcoholic fatty liver disease (NAFLD) risk in young adults. METHODS: Participants were 170 young adults (17-22 years) from the Meta-AIR cohort of the Children's Health Study (CHS). Residential AAP exposure (PM2.5, PM10, NO2, 8-hour maximum O3, redox-weighted oxidative capacity [Oxwt]) was spatially interpolated from monitoring stations via inverse-distance-squared weighting. Fasting serum lipids were assayed. Liver fat was imaged by MRI and NAFLD was defined by ≥ 5.5% hepatic fat fraction. Serum microRNAs were measured via NanoString and microRNA networks were constructed by weighted gene correlation network analysis. The first principal component of each network represented its expression profile. Multivariable mixed effects regression models adjusted for sociodemographic, behavioral, and clinical covariates; baseline CHS town code was a random effect. Effects estimates are scaled to one standard deviation of exposure. Mediation analysis explored microRNA profiles as potential mediators of exposure-outcome associations. DIANA-mirPATH identified overrepresented gene pathways targeted by miRNA networks. RESULTS: Prior-month Oxwt was associated with NAFLD (OR=3.45; p = 0.003) and inversely associated with microRNA Network A (ß = -0.016; p = 0.026). Prior-year NO2 was associated with non-HDL-cholesterol (ß = 7.13; p = 0.01) and inversely associated with miRNA Network A (ß = -0.019; p = 0.022). Network A expression was inversely associated with NAFLD (OR=0.35; p = 0.010) and non-HDL-C (ß = -6.94 mg/dL; p = 0.035). Network A members miR-199a/b-3p and miR-130a, which both target fatty acid synthase, mediated 21% of the association between prior-month Oxwt exposure with NAFLD (p = 0.048) and 23.3% of the association between prior-year NO2 exposure and non-HDL-cholesterol (p = 0.026), respectively. CONCLUSIONS: Exposure to AAP may contribute to adverse lipid profiles and NAFLD risk among young adults via altered expression of microRNA profiles.

The impact of GPS-derived activity spaces on personal PM2.5 exposures in the MADRES cohort.

BACKGROUND: In-utero exposure to particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) is associated with low birth weight and health risks later in life. Pregnant women are mobile and locations they spend time in contribute to their personal PM2.5 exposures. Therefore, it is important to understand how mobility and exposures encountered within activity spaces contribute to personal PM2.5 exposures during pregnancy. METHODS: We collected 48-h integrated personal PM2.5 samples and continuous geolocation (GPS) data for 213 predominantly Hispanic/Latina pregnant women in their 3rd trimester in Los Angeles, CA. We also collected questionnaires and modeled outdoor air pollution and meteorology in their residential neighborhood. We calculated three GPS-derived activity space measures of exposure to road networks, greenness (NDVI), parks, traffic volume, walkability, and outdoor PM2.5 and temperature. We used bivariate analyses to screen variables (GPS-extracted exposures in activity spaces, individual characteristics, and residential neighborhood exposures) based on their relationship with personal, 48-h integrated PM2.5 concentrations. We then built a generalized linear model to explain the variability in personal PM2.5 exposure and identify key contributing factors. RESULTS: Indoor PM2.5 sources, parity, and home ventilation were significantly associated with personal exposure. Activity-space based exposure to roads was associated with significantly higher personal PM2.5 exposure, while greenness was associated with lower personal PM2.5 exposure (ß = -3.09 µg/m3 per SD increase in NDVI, p-value = 0.018). The contribution of outdoor PM2.5 to personal exposure was positive but relatively lower (ß = 2.05 µg/m3 per SD increase, p-value = 0.016) than exposures in activity spaces and the indoor environment. The final model explained 34% of the variability in personal PM2.5 concentrations. CONCLUSIONS: Our findings highlight the importance of activity spaces and the indoor environment on personal PM2.5 exposures of pregnant women living in Los Angeles, CA. This work also showcases the multiple, complex factors that contribute to total personal PM2.5 exposure.

Near-roadway air pollution, immune cells and adipokines among obese young adults.

BACKGROUND: Air pollution has been associated with metabolic disease and obesity. Adipokines are potential mediators of these effects, but studies of air pollution-adipokine relationships are inconclusive. Macrophage and T cells in adipose tissue (AT) and blood modulate inflammation; however, the role of immune cells in air pollution-induced dysregulation of adipokines has not been studied. We examined the association between air pollution exposure and circulating and AT adipokine concentrations, and whether these relationships were modified by macrophage and T cell numbers in the blood and AT. METHODS: Fasting blood and abdominal subcutaneous AT biopsies were collected from 30 overweight/obese 18-26 year-old volunteers. Flow cytometry was used to quantify T effector (Teff, inflammatory) and regulatory (Treg, anti-inflammatory) lymphocytes and M1 [inflammatory] and M2 [anti-inflammatory]) macrophage cell number. Serum and AT leptin and adiponectin were measured using enzyme-linked immunosorbent assay (ELISA). Exposure to near-roadway air pollution (NRAP) from freeway and non-freeway vehicular sources and to regional particulate matter, nitrogen dioxide and ozone were estimated for the year prior to biopsy, based on participants' residential addresses. Linear regression models were used to examine the association between air pollution exposures and adipokines and to evaluate effect modification by immune cell counts. RESULTS: An interquartile increase in non-freeway NRAP exposure during 1 year prior to biopsy was associated with higher leptin levels in both serum [31.7% (95% CI: 10.4, 52.9%)] and AT [19.4% (2.2, 36.6%)]. Non-freeway NRAP exposure effect estimates were greater among participants with greater than median Teff/Treg ratio and M1/M2 ratio in blood, and with greater M1 counts in AT. No adipokine associations with regional air pollutants were found. DISCUSSION: Our results suggest that NRAP may increase serum leptin levels in obese young adults, and this association may be promoted in a pro-inflammatory immune cell environment in blood and AT.

Childhood traffic-related air pollution and adverse changes in subclinical atherosclerosis measures from childhood to adulthood.

BACKGROUND: Chronic exposure to air pollutants is associated with increased risk of cardiovascular disease (CVD) among adults. However, little is known about how air pollution may affect the development of subclinical atherosclerosis in younger populations. Carotid artery intima-media thickness (CIMT) is a measure of subclinical atherosclerosis that provides insight into early CVD pathogenesis. METHODS: In a pilot study of 70 participants from the Southern California Children's Health Study, we investigated CIMT progression from childhood to adulthood. Using carotid artery ultrasound images obtained at age 10 and follow-up images at age 21-22, we examined associations between childhood ambient and traffic-related air pollutants with changes in CIMT over time and attained adult CIMT using linear mixed-effects models adjusted for potential confounders. Average residential childhood exposures (i.e., birth to time of measurement at 10-11 years) were assigned for regional, ambient pollutants (ozone, nitrogen dioxide, particulate matter, interpolated from regulatory air monitoring data) and traffic-related nitrogen oxides (NOx) by road class (modeled using the CALINE4 line source dispersion model). Traffic density was calculated within a 300-m residential buffer. RESULTS: For each 1 standard deviation (SD) increase in childhood traffic-related total NOx exposure, we observed greater yearly rate of change in CIMT from childhood to adulthood (ß: 2.17 µm/yr, 95% CI: 0.78-3.56). Increases in annual rate of CIMT change from childhood to adulthood also were observed with freeway NOx exposure (ß: 2.24 µm/yr, 95% CI: 0.84-3.63) and traffic density (ß: 2.11 µm/yr, 95% CI: 0.79-3.43). Traffic exposures were also related to increases in attained CIMT in early adulthood. No associations of CIMT change or attained level were observed with ambient pollutants. CONCLUSIONS: Overall, we observed adverse changes in CIMT over time in relation to childhood traffic-related NOx exposure and traffic density in our study population. While these results must be cautiously interpreted given the limited sample size, the observed associations of traffic measures with CIMT suggest a need for future studies to more fully explore this relationship.

Prenatal exposure to ambient air pollutants and early infant growth and adiposity in the Southern California Mother's Milk Study.

BACKGROUND: Prior epidemiological and animal work has linked in utero exposure to ambient air pollutants (AAP) with accelerated postnatal weight gain, which is predictive of increased cardiometabolic risk factors in childhood and adolescence. However, few studies have assessed changes in infant body composition or multiple pollutant exposures. Therefore, the objective of this study was to examine relationships between prenatal residential AAP exposure with infant growth and adiposity. METHODS: Residential exposure to AAP (particulate matter < 2.5 and 10 microns in aerodynamic diameter [PM2.5, PM10]; nitrogen dioxide [NO2]; ozone [O3]; oxidative capacity [Oxwt: redox-weighted oxidative potential of O3 and NO2]) was modeled by spatial interpolation of monitoring stations via an inverse distance-squared weighting (IDW2) algorithm for 123 participants from the longitudinal Mother's Milk Study, an ongoing cohort of Hispanic mother-infant dyads from Southern California. Outcomes included changes in infant growth (weight, length), total subcutaneous fat (TSF; calculated via infant skinfold thickness measures) and fat distribution (umbilical circumference, central to total subcutaneous fat [CTSF]) and were calculated by subtracting 1-month measures from 6-month measures. Multivariable linear regression was performed to examine relationships between prenatal AAP exposure and infant outcomes. Models adjusted for maternal age, pre-pregnancy body mass index, socioeconomic status, infant age, sex, and breastfeeding frequency. Sex interactions were tested, and effects are reported for each standard deviation increase in exposure. RESULTS: NO2 was associated with greater infant weight gain (ß = 0.14, p = 0.02) and TSF (ß = 1.69, p = 0.02). PM10 and PM2.5 were associated with change in umbilical circumference (ß = 0.73, p = 0.003) and TSF (ß = 1.53, p = 0.04), respectively. Associations of Oxwt (pinteractions < 0.10) with infant length change, umbilical circumference, and CTSF were modified by infant sex. Oxwt was associated with attenuated infant length change among males (ß = -0.60, p = 0.01), but not females (ß = 0.16, p = 0.49); umbilical circumference among females (ß = 0.92, p = 0.009), but not males (ß = -0.00, p = 0.99); and CTSF among males (ß = 0.01, p = 0.03), but not females (ß = 0.00, p = 0.51). CONCLUSION: Prenatal AAP exposure was associated with increased weight gain and anthropometric measures from 1-to-6 months of life among Hispanic infants. Sex-specific associations suggest differential consequences of in utero oxidative stress. These results indicate that prenatal AAP exposure may alter infant growth, which has potential to increase childhood obesity risk.

Spatiotemporal Imputation of MAIAC AOD Using Deep Learning with Downscaling.

Aerosols have adverse health effects and play a significant role in the climate as well. The Multiangle Implementation of Atmospheric Correction (MAIAC) provides Aerosol Optical Depth (AOD) at high temporal (daily) and spatial (1 km) resolution, making it particularly useful to infer and characterize spatiotemporal variability of aerosols at a fine spatial scale for exposure assessment and health studies. However, clouds and conditions of high surface reflectance result in a significant proportion of missing MAIAC AOD. To fill these gaps, we present an imputation approach using deep learning with downscaling. Using a baseline autoencoder, we leverage residual connections in deep neural networks to boost learning and parameter sharing to reduce overfitting, and conduct bagging to reduce error variance in the imputations. Downscaled through a similar auto-encoder based deep residual network, Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) GMI Replay Simulation (M2GMI) data were introduced to the network as an important gap-filling feature that varies in space to be used for missingness imputations. Imputing weekly MAIAC AOD from 2000 to 2016 over California, a state with considerable geographic heterogeneity, our full (non-full) residual network achieved mean R2 = 0.94 (0.86) [RMSE = 0.007 (0.01)] in an independent test, showing considerably better performance than a regular neural network or non-linear generalized additive model (mean R2 = 0.78-0.81; mean RMSE = 0.013-0.015). The adjusted imputed as well as combined imputed and observed MAIAC AOD showed strong correlation with Aerosol Robotic Network (AERONET) AOD (R = 0.83; R2 = 0.69, RMSE = 0.04). Our results show that we can generate reliable imputations of missing AOD through a deep learning approach, having important downstream air quality modeling applications.

Exposure to traffic-related air pollution and the composition of the gut microbiota in overweight and obese adolescents.

BACKGROUND: Traffic-related air pollution (TRAP) exposure has been linked to type 2 diabetes and metabolic dysfunction in humans. Animal studies suggest that air pollutants may alter the composition of the gut microbiota, which may negatively impact metabolic health through changes in the composition and/or function of the gut microbiome. OBJECTIVES: The primary aim of this study was to determine whether elevated TRAP exposure was correlated with gut bacterial taxa in overweight and obese adolescents from the Meta-AIR (Metabolic and Asthma Incidence Research) study. The secondary aim was to examine whether gut microbial taxa correlated with TRAP were also correlated with risk factors for type 2 diabetes (e.g., fasting glucose levels). We additionally explored whether correlations between TRAP and these metabolic risk factors could be explained by the relative abundance of these taxa. METHODS: Participants (17-19 years; n=43) were enrolled between 2014 and 2016 from Southern California. The CALINE4 line dispersion model was used to model prior year residential concentrations of nitrogen oxides (NOx) as a marker of traffic emissions. The relative abundance of fecal microbiota was characterized by 16S rRNA sequencing and spearman partial correlations were examined after adjusting for body fat percent. RESULTS: Freeway TRAP was correlated with decreased Bacteroidaceae (r=-0.48; p=0.001) and increased Coriobacteriaceae (r=0.48; p<0.001). These same taxa were correlated with fasting glucose levels, including Bacteroidaceae (r=-0.34; p=0.04) and Coriobacteriaceae (r=0.41; p<0.01). Further, freeway TRAP was positively correlated fasting glucose (r=0.45; p=0.004) and Bacteroidaceae and Coriobacteriaceae explained 24% and 29% of the correlation between TRAP and fasting glucose levels. CONCLUSIONS: Increased TRAP exposure was correlated with gut microbial taxa and fasting glucose levels. Gut microbial taxa that were correlated with TRAP partially explained the correlation between TRAP and fasting glucose levels. These results suggest that exposure to air pollutants may negatively impact metabolic health via alterations in the gut microbiota.

Particulate matter air pollution and liver cancer survival.

Particulate matter (PM) air pollution exposure has been associated with cancer incidence and mortality especially with lung cancer. The liver is another organ possibly affected by PM due to its role in detoxifying xenobiotics absorbed from PM. Various studies have investigated the mechanistic pathways between inhaled pollutants and liver damage, cancer incidence, and tumor progression. However, little is known about the effects of PM on liver cancer survival. Twenty thousand, two hundred and twenty-one California Cancer Registry patients with hepatocellular carcinoma (HCC) diagnosed between 2000 and 2009 were used to examine the effect of exposure to ambient PM with diameter <2.5 µm (PM2.5 ) on HCC survival. Cox proportional hazards models were used to estimate hazard ratios (HRs) relating PM2.5 to all-cause and liver cancer-specific mortality linearly and nonlinearly-overall and stratified by stage at diagnosis (local, regional and distant)-adjusting for potential individual and geospatial confounders.PM2.5 exposure after diagnosis was statistically significantly associated with HCC survival. After adjustment for potential confounders, the all-cause mortality HR associated with a 1 standard deviation (5.0 µg/m3 ) increase in PM2.5 was 1.18 (95% CI: 1.16-1.20); 1.31 (95% CI:1.26-1.35) for local stage, 1.19 (95% CI:1.14-1.23) for regional stage, and 1.05 (95% CI:1.01-1.10) for distant stage. These associations were nonlinear, with substantially larger HRs at higher exposures. The associations between liver cancer-specific mortality and PM2.5 were slightly attenuated compared to all-cause mortality, but with the same patterns.Exposure to elevated PM2.5 after the diagnosis of HCC may shorten survival, with larger effects at higher concentrations.

Air pollution affects lung cancer survival.

RATIONALE: Exposure to ambient air pollutants has been associated with increased lung cancer incidence and mortality, but due to the high case fatality rate, little is known about the impacts of air pollution exposures on survival after diagnosis. This study aimed to determine whether ambient air pollutant exposures are associated with the survival of patients with lung cancer. METHODS: Participants were 352 053 patients with newly diagnosed lung cancer during 1988-2009 in California, ascertained by the California Cancer Registry. Average residential ambient air pollutant concentrations were estimated for each participant's follow-up period. Cox proportional hazards models were used to estimate HRs relating air pollutant exposures to all-cause mortality overall and stratified by stage (localised only, regional and distant site) and histology (squamous cell carcinoma, adenocarcinoma, small cell carcinoma, large cell carcinoma and others) at diagnosis, adjusting for potential individual and area-level confounders. RESULTS: Adjusting for histology and other potential confounders, the HRs associated with 1 SD increases in NO2, O3, PM10, PM2.5 for patients with localised stage at diagnosis were 1.30 (95% CI 1.28 to 1.32), 1.04 (95% CI 1.02 to 1.05), 1.26 (95% CI 1.25 to 1.28) and 1.38 (95% CI 1.35 to 1.41), respectively. Adjusted HRs were smaller in later stages and varied by histological type within stage (p<0.01, except O3). The largest associations were for patients with early-stage non-small cell cancers, particularly adenocarcinomas. CONCLUSIONS: These epidemiological findings support the hypothesis that air pollution exposures after lung cancer diagnosis shorten survival. Future studies should evaluate the impacts of exposure reduction.

Air Pollution, Neighbourhood Socioeconomic Factors, and Neural Tube Defects in the San Joaquin Valley of California.

BACKGROUND: Environmental pollutants and neighbourhood socioeconomic factors have been associated with neural tube defects, but the potential impact of interaction between ambient air pollution and neighbourhood socioeconomic factors on the risks of neural tube defects is not well understood. METHODS: We used data from the California Center of the National Birth Defects Study and the Children's Health and Air Pollution Study to investigate whether associations between air pollutant exposure in early gestation and neural tube defects were modified by neighbourhood socioeconomic factors in the San Joaquin Valley of California, 1997-2006. There were 5 pollutant exposures, 3 outcomes, and 9 neighbourhood socioeconomic factors included for a total of 135 investigated associations. Estimates were adjusted for maternal race-ethnicity, education, and multivitamin use. RESULTS: We present below odds ratios (ORs) that exclude 1 and a chi-square test of homogeneity P-value of <0.05. We observed increased odds of spina bifida comparing the highest to lowest quartile of particulate matter <10 µm (PM10 ) among those living in a neighbourhood with: (i) median household income of less than $30 000 per year [OR 5.1, 95% confidence interval (CI) 1.7, 15.3]; (ii) more than 20% living below the federal poverty level (OR 2.6, 95% CI 1.1, 6.0); and (iii) more than 30% with less than or equal to a high school education (OR 3.2, 95% CI 1.4, 7.4). The ORs were not statistically significant among those higher socioeconomic status (SES) neighbourhoods. CONCLUSIONS: Our results demonstrate effect modification by neighbourhood socioeconomic factors in the association of particulate matter and neural tube defects in California.

Associations of children's lung function with ambient air pollution: joint effects of regional and near-roadway pollutants.

BACKGROUND: Previous studies have reported adverse effects of either regional or near-roadway air pollution (NRAP) on lung function. However, there has been little study of the joint effects of these exposures. OBJECTIVES: To assess the joint effects of NRAP and regional pollutants on childhood lung function in the Children's Health Study. METHODS: Lung function was measured on 1811 children from eight Southern Californian communities. NRAP exposure was assessed based on (1) residential distance to the nearest freeway or major road and (2) estimated near-roadway contributions to residential nitrogen dioxide (NO2), nitric oxide (NO) and total nitrogen oxides (NOx). Exposure to regional ozone (O3), NO2, particulate matter with aerodynamic diameter <10 µm (PM10) and 2.5 µm (PM2.5) was measured continuously at community monitors. RESULTS: An increase in near-roadway NOx of 17.9 ppb (2 SD) was associated with deficits of 1.6% in forced vital capacity (FVC) (p=0.005) and 1.1% in forced expiratory volume in 1 s (FEV1) (p=0.048). Effects were observed in all communities and were similar for NO2 and NO. Residential proximity to a freeway was associated with a reduction in FVC. Lung function deficits of 2-3% were associated with regional PM10 and PM2.5 (FVC and FEV1) and with O3 (FEV1), but not NO2 across the range of exposure between communities. Associations with regional pollution and NRAP were independent in models adjusted for each. The effects of NRAP were not modified by regional pollutant concentrations. CONCLUSIONS: The results indicate that NRAP and regional air pollution have independent adverse effects on childhood lung function.

Exploring relationships between smoke exposure, housing characteristics, and preterm birth in California.

Pregnant people are vulnerable to air pollution exposure, including risk of preterm birth, low birth weight, and stillbirth. Understanding the infiltration of outdoor wildfire smoke into a residential space is critical for the accurate assessment of wildfire smoke exposure and associated health effects in pregnant people. Relying on ambient measurements of wildfire smoke alone can result in exposure misclassification. In this study, we examine the role of physical housing characteristics in the relationship between smoke exposure and preterm birth. In particular, we examine the effect of home size, year of construction, cooling type, and renovation status, as effect modifiers in the relationship between smoke exposure during pregnancy and preterm birth from 2007 to 2015 in California. To do this, we combined data on home characteristics from the California Tax Assessor, birth outcomes from the California birth records database, and the number of smoke days for each pregnancy from theNOAA (National Oceanic and Atmospheric Administration) Hazard Mapping System (HMS). We estimated the association between smoke day exposures and odds of preterm birth using logistic regression models and stratified by air basin and housing characteristics. Our findings reveal that cooling type and renovation status are key factors modifying the smoke exposure-preterm birth relationship. Notably, we found elevated associations for people living in unrenovated homes, those using evaporative cooling systems, and those using central air conditioning units. While we observed elevated odds of preterm birth associated with increasing smoke day exposure for residents of large and new homes, this effect does not significantly differ across home size and age quartiles. This study highlights the need to further examine the relative roles of housing characteristics as well as factors not measured here including behavioral factors, time spent outdoors, window use, and occupational exposures in driving adverse birth outcomes related to wildfire smoke exposure.

Neighborhood Disadvantage and Autism Spectrum Disorder in a Population With Health Insurance.

Importance: Family socioeconomic status has been associated with autism spectrum disorder (ASD) diagnoses. Less is known regarding the role of neighborhood disadvantage in the United States, particularly when children have similar access to health insurance. Objective: To evaluate the association between neighborhood disadvantage and the diagnosis of ASD and potential effect modification by maternal and child demographic characteristics. Design, Setting, and Participants: This cohort study examined a retrospective birth cohort from Kaiser Permanente Southern California (KPSC), an integrated health care system. Children born in 2001 to 2014 at KPSC were followed up through KPSC membership records. Electronic medical records were used to obtain an ASD diagnosis up to December 31, 2019, or the last follow-up. Data were analyzed from February 2022 to September 2023. Exposure: Socioeconomic disadvantage at the neighborhood level, an index derived from 7 US census tract characteristics using principal component analysis. Main Outcomes and Measures: Clinical ASD diagnosis based on electronic medical records. Associations between neighborhood disadvantage and ASD diagnosis were determined by hazard ratios (HRs) from Cox regression models adjusted for birth year, child sex, maternal age at delivery, parity, severe prepregnancy health conditions, maternal race and ethnicity, and maternal education. Effect modification by maternal race and ethnicity, maternal education, and child sex was assessed. Results: Among 318 372 mothers with singleton deliveries during the study period, 6357 children had ASD diagnoses during follow-up; their median age at diagnosis was 3.53 years (IQR, 2.57-5.34 years). Neighborhood disadvantage was associated with a higher likelihood of ASD diagnosis (HR, 1.07; 95% CI, 1.02-1.11, per IQR = 2.70 increase). Children of mothers from minoritized racial and ethnic groups (African American or Black, Asian or Pacific Islander, Hispanic or Latinx groups) had increased likelihood of ASD diagnosis compared with children of White mothers. There was an interaction between maternal race and ethnicity and neighborhood disadvantage (difference in log-likelihood = 21.88; P < .001 for interaction under χ24); neighborhood disadvantage was only associated with ASD among children of White mothers (HR, 1.17; 95% CI, 1.09-1.26, per IQR = 2.00 increase). Maternal education and child sex did not significantly modify the neighborhood-ASD association. Conclusions and Relevance: In this study, children residing in more disadvantaged neighborhoods at birth had higher likelihood of ASD diagnosis among a population with health insurance. Future research is warranted to investigate the mechanisms behind the neighborhood-related disparities in ASD diagnosis, alongside efforts to provide resources for early intervention and family support in communities with a higher likelihood of ASD.

Decomposing the variance: The unique and shared associations of fine and ultrafine particulate matter exposed during pregnancy with child autism spectrum disorder.

While fine particulate matter (PM2.5) has been associated with autism spectrum disorder (ASD), few studies focused on ultrafine particles (PM0.1). Given that fine and ultrafine particles can be highly correlated due to shared emission sources, challenges remain to distinguish their health effects. In a retrospective cohort of 318,371 mother-child pairs (4549 ASD cases before age 5) in Southern California, pregnancy average PM2.5 and PM0.1 were estimated using a California-based chemical transport model and assigned to residential addresses. The correlation between PM2.5 and PM0.1 was 0.87. We applied a two-step variance decomposition approach: first, decomposing PM2.5 and PM0.1 into the shared and unique variances using ordinary least squares linear regression (OLS) and Deming regression considering errors in both exposures; then assessing associations between decomposed PM2.5 and PM0.1 and ASD using Cox proportional hazard models adjusted for covariates. Prenatal PM2.5 and PM0.1 each was associated with increased ASD risk. OLS decomposition showed that associations were driven mainly by their shared variance, not by their unique variance. Results from Deming regression considering assumptions of measurement errors were consistent with those from OLS. This decomposition approach has potential to disentangle health effects of correlated exposures, such as PM2.5 and PM0.1 from common emissions sources.