Cancer vulnerabilities unveiled by genomic loss.

Due to genome instability, most cancers exhibit loss of regions containing tumor suppressor genes and collateral loss of other genes. To identify cancer-specific vulnerabilities that are the result of copy number losses, we performed integrated analyses of genome-wide copy number and RNAi profiles and identified 56 genes for which gene suppression specifically inhibited the proliferation of cells harboring partial copy number loss of that gene. These CYCLOPS (copy number alterations yielding cancer liabilities owing to partial loss) genes are enriched for spliceosome, proteasome, and ribosome components. One CYCLOPS gene, PSMC2, encodes an essential member of the 19S proteasome. Normal cells express excess PSMC2, which resides in a complex with PSMC1, PSMD2, and PSMD5 and acts as a reservoir protecting cells from PSMC2 suppression. Cells harboring partial PSMC2 copy number loss lack this complex and die after PSMC2 suppression. These observations define a distinct class of cancer-specific liabilities resulting from genome instability.

Antimicrobial exposure during infancy in a longitudinal California cohort.

BACKGROUND: To describe temporal and sociodemographic patterns of antimicrobial exposure during the first year of life in a large US cohort. METHODS: Singleton infants born 1998-2014 enrolled in Kaiser Permanente Northern California integrated health system (n = 345,550) were followed longitudinally via comprehensive electronic health records, capturing all systemic antimicrobial inpatient administrations and outpatient dispensings. Antimicrobial exposure was summarized by maternal and infant characteristics, birth year, inpatient/outpatient status, age in months, and drug class. RESULTS: Overall, 44% of infants in this cohort received at least one dose of antimicrobials during infancy. Decreases over time were driven by reduced outpatient dispensings specifically in later infancy, primarily for penicillins. Among infants receiving any antimicrobials the median number of exposure-days was 16. Inpatient dispensings peaked in the first 30 days of life and outpatient dispensings peaked at 10-11 months. Birth characteristics (i.e., NICU admission, gestational age) were strong independent predictors of antimicrobial exposure between 0- < 3 months; sociodemographic factors were modest predictors of exposure for 3-12 months. CONCLUSION: Predictors of antimicrobial exposure in early and late infancy are distinct with early infancy exposures highly correlated to birth characteristics. The cumulative proportion of infants exposed has decreased due to fewer late infancy outpatient dispensings. IMPACT: Comprehensive antimicrobial exposure histories and the maternal and infant characteristics predicting exposure have not been well described in US populations. This analysis provides estimates of cumulative antimicrobial exposures by sociodemographic factors, delivery characteristics, month of life, inpatient/outpatient status, and antibiotic class among one of the largest US HMOs. Predictors of early infancy antimicrobial exposures differ from those in late infancy, with early exposures strongly correlated to birth characteristics and late infancy exposures modestly related to sociodemographic factors. Antimicrobial exposure among infants decreased over the time period primarily due to reduced outpatient dispensings in later infancy.

Gastroesophageal Adenocarcinomas With Defective Mismatch Repair: Current Knowledge and Clinical Management.

Esophageal, gastroesophageal junction, and gastric adenocarcinomas, referred to collectively as gastroesophageal adenocarcinomas (GEAs), are a major cause of global cancer-related mortality. Our increasing molecular understanding has led to the addition of biomarker-directed approaches to defined subgroups and has improved survival in selected patients, such as those with HER2 and Claudin18.2 overexpression. Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of cancer, including GEA, but biomarkers beyond PD-L1 expression are lacking. Mismatch repair deficiency and/or high microsatellite instability (dMMR/MSI-H) is observed in 8% to 22% of nonmetastatic GEA, and 3% to 5% of patients with metastatic disease. dMMR/MSI-H tumors are associated with more favorable prognosis and significant benefit from ICIs, although some heterogeneity exists. The activity of ICIs in advanced dMMR/MSI-H cancer is seen across lines of therapy and should be recommended in the frontline setting. In patients with nonmetastatic dMMR/MSI-H cancer, increasing evidence suggests that perioperative and adjuvant chemotherapy may not provide benefit to the dMMR/MSI-H subgroup. The activity of perioperative chemotherapy-free immune checkpoint regimens in patients with nonmetastatic dMMR/MSI-H cancer is highly promising and underscores the need to identify this unique subgroup. We recommend MMR/MSI testing for all patients with GEA at diagnosis, and review the key rationale and clinical management implications for patient with dMMR/MSI-H tumors across disease stages.

Environmental Inequality in Estimated Cancer Risk from Airborne Toxic Exposure across United States Communities from 2011 to 2019.

US Census Bureau data were matched to U.S. Environmental Protection Agency estimated cancer risks from airborne toxics from 2011 to 2019 to explore environmental inequality with nationwide census tract resolution. Spearman correlations showed modest associations between various socioeconomic status factors and estimated cancer risk. Multiple linear regression analyses show positive associations with increased estimated cancer risk (p < 0.05) for high proportions of Blacks in suburban and rural areas. A positive relationship with estimated cancer risk was found for increasing proportions of Asians and Hispanics in nonurban areas. Urban tracts that suffer from the highest estimated cancer risks were concentrated among the communities with a population of higher proportion of minorities. While environmental inequality seems to have improved across the examined years for certain demographics with respect to estimated cancer risk from air toxics, equity is far from achieved, and future work in identifying the sources of environmental inequality could help in achieving a more just environment.

Confounding by Conception Seasonality in Studies of Temperature and Preterm Birth: A Simulation Study.

BACKGROUND: Seasonal patterns of conception may confound acute associations between birth outcomes and seasonally varying exposures. We aim to evaluate four epidemiologic designs (time-stratified case-crossover, time-series, pair-matched case-control, and time-to-event) commonly used to study acute associations between ambient temperature and preterm births. METHODS: We conducted simulations assuming no effect of temperature on preterm birth. We generated pseudo-birth data from the observed seasonal patterns of birth in the United States and analyzed them in relation to observed temperatures using design-specific seasonality adjustments. RESULTS: Using the case-crossover approach (time-stratified by calendar month), we observed a bias (among 1,000 replicates) = 0.016 (Monte-Carlo standard error 95% CI: 0.015-0.018) in the regression coefficient for every 10°C increase in mean temperature in the warm season (May-September). Unbiased estimates obtained using the time-series approach required accounting for both the pregnancies-at-risk and their weighted probability of birth. Notably, adding the daily weighted probability of birth from the time-series models to the case-crossover models corrected the bias in the case-crossover approach. In the pair-matched case-control design, where the exposure period was matched on gestational window, we observed no bias. The time-to-event approach was also unbiased but was more computationally intensive than others. CONCLUSIONS: Most designs can be implemented in a way that yields estimates unbiased by conception seasonality. The time-stratified case-crossover design exhibited a small positive bias, which could contribute to, but not fully explain, previously reported associations.

Prepregnancy body mass index and risk of childhood asthma.

BACKGROUND: Growing evidence suggests that maternal obesity may affect the intrauterine environment and increase a child's risk of developing asthma. We aim to investigate the relationship between prepregnancy obesity and childhood asthma risk. METHODS: Cohorts of children enrolled in Kaiser Permanente Northern California integrated healthcare system were followed from birth (2005-2014) to age 4 (n = 104,467), 6 (n = 63,084), or 8 (n = 31,006) using electronic medical records. Child's asthma was defined using ICD codes and asthma-related prescription medication dispensing. Risk ratios (RR) and 95% confidence intervals (95% CIs) for child's asthma were estimated using Poisson regression with robust error variance for (1) prepregnancy BMI categories (underweight [<18.5], normal [18.5-24.9], overweight [25-29.9], obese 1 [30-34.9], and obese 2/3 [≥35]) and (2) continuous prepregnancy BMI modeled using cubic splines with knots at BMI category boundaries. Models were adjusted for maternal age, education, race, asthma, allergies, smoking, gestational weight gain, child's birth year, parity, infant sex, gestational age, and child's BMI. RESULTS: Relative to normal BMI, RRs (95%CIs) for asthma at ages 4, 6, and 8 were 0.91 (0.75, 1.11), 0.95 (0.78, 1.16), and 0.97 (0.75, 1.27) for underweight, 1.06 (0.99, 1.14), 1.08 (1.01, 1.16), and 1.03 (0.94, 1.14) for overweight, 1.09 (1.00, 1.19), 1.12 (1.03, 1.23), 1.03 (0.91, 1.17) for obese 1, and 1.10 (0.99, 1.21), 1.13 (1.02, 1.25), 1.14 (0.99, 1.31) for obese 2/3. When continuous prepregnancy BMI was modeled with splines, child's asthma risk generally increased linearly with increasing prepregnancy BMI. CONCLUSIONS: Higher prepregnancy BMI is associated with modestly increased childhood asthma risk.

Maternal obesity and childhood asthma risk: Exploring mediating pathways.

BACKGROUND: Growing evidence for the effect of maternal obesity on childhood asthma motivates investigation of mediating pathways. OBJECTIVE: To investigate if childhood body mass index (BMI), gestational weight gain (GWG) and preterm birth mediate the association of maternal obesity on childhood asthma risk. METHODS: We used electronic medical records from mother-child pairs enrolled in Kaiser Permanente Northern California integrated healthcare system. Children were followed from their birth (2005-2014) until at least age 4 (n = 95,723), age 6 (n = 59,230) or age 8 (n = 25,261). Childhood asthma diagnosis at each age was determined using ICD-9/10 codes and medication dispensings. Prepregnancy BMI (underweight [<18.5], normal [18.5-24.9], overweight [25-29.9], obese [≥30] kg/m2 ) were defined using height and weight measurements close to the last menstrual period date. Child's BMI (Centers for Disease Control and Prevention BMI-for-age percentiles: underweight [<5th], normal [5th-85th], overweight [85th-95th], obese [>95th]) were obtained using anthropometric measurements taken the year preceding each follow-up age. GWG (delivery weight-prepregnancy weight) was categorised based on Institutes of Medicine recommendations (inadequate, adequate, excessive). Implementing first causal inference test (CIT) then causal mediator models (to decompose the natural direct and indirect effects), we examined the potential mediating effect of childhood BMI, GWG, and preterm birth on the association between prepregnancy BMI (continuous and categorical) and childhood asthma. RESULTS: Overall, risk of childhood asthma increased as prepregnancy BMI increased (age 4 risk ratio: 1.07, 95% confidence interval: 1.04, 1.09, per 5 kg/m2 increase in BMI; similar for age 6 and 8). CIT identified childhood BMI and preterm birth, but not GWG as potential mediators. Causal mediation models confirmed childhood BMI, but not preterm birth, as having a partial mediating effect. Results were similar for age 6 and 8, and when continuous mediators (instead of binary) were assessed. CONCLUSIONS: Childhood overweight/obesity has a modest mediating effect on the association between prepregnancy BMI and childhood asthma.

Gestational Weight Gain and Birth Outcome: A Comparison of Methods of Accounting for Gestational Age.

Cross-sectional studies of total gestational weight gain (GWG) and perinatal outcomes have used different approaches to operationalize GWG and adjust for duration of gestation. Using birth records from California (2007-2017), Nevada (2010-2017), and Oregon (2008-2017), we compared 3 commonly used approaches to estimate associations between GWG and cesarean delivery, small-for-gestational-age birth, and low birth weight (LBW): 1) the Institute of Medicine-recommended GWG ranges at a given gestational week, 2) total weight gain categories directly adjusting for gestational age as a covariate, and 3) weight-gain-for-gestational-age z scores derived from an external longitudinal reference population. Among 5,461,130 births, the 3 methods yielded similar conclusions for cesarean delivery and small-for-gestational-age birth. However, for LBW, some associations based on z scores were in the opposite direction of methods 1 and 2, paradoxically suggesting that higher GWG increases risk of LBW. This was due to a greater proportion of preterm births among those with high z scores, and controlling for gestational age in the z score model brought the results in line with the other methods. We conclude that the use of externally derived GWG z scores based on ongoing pregnancies can yield associations confounded by duration of pregnancy when the outcome is strongly associated with gestational age at delivery.

Acute association between heatwaves and stillbirth in six US states.

BACKGROUND: Heatwaves are becoming more frequent and may acutely increase the risk of stillbirth, a rare and severe pregnancy outcome. OBJECTIVES: Examine the association between multiple heatwave metrics and stillbirth in six U.S. states. METHODS: Data were collected from fetal death and birth records in California (1996-2017), Florida (1991-2017), Georgia (1994-2017), Kansas (1991-2017), New Jersey (1991-2015), and Oregon (1991-2017). Cases were matched to controls 1:4 based on maternal race/ethnicity, maternal education, and county, and exposure windows were aligned (gestational week prior to stillbirth). County-level temperature data were obtained from Daymet and linked to cases and controls by residential county and the exposure window. Five heatwave metrics (1 categorical, 3 dichotomous, 1 continuous) were created using different combinations of the duration and intensity of hot days (mean daily temperature exceeding the county-specific 97.5th percentile) during the exposure window, as well as a continuous measure of mean temperature during the exposure window modeled using natural splines to allow for nonlinear associations. State-specific odds ratios (ORs) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. State-specific results were pooled using a fixed-effects meta-analysis. RESULTS: In our data set of 140,428 stillbirths (553,928 live birth controls), three of the five heatwave metrics examined were not associated with stillbirth. However, four consecutive hot days during the previous week was associated with a 3% increase in stillbirth risk (CI: 1.01, 1.06), and a 1 °C average increase over the threshold was associated with a 10% increase in stillbirth risk (CI: 1.04, 1.17). In continuous temperature analyses, there was a slight increased risk of stillbirth associated with extremely hot temperatures (≥ 35 °C). DISCUSSION: Most heat wave definitions examined were not associated with acute changes in stillbirth risk; however, the most extreme heatwave durations and temperatures were associated with a modest increase in stillbirth risk.

Using logic regression to characterize extreme heat exposures and their health associations: a time-series study of emergency department visits in Atlanta.

BACKGROUND: Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations. METHODS: Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area. RESULTS: For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient. CONCLUSION: Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.

Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products.

BACKGROUND: Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error. METHODS: We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1 km spatial resolution. RESULTS: Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center. CONCLUSION: Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.

Acute associations between heatwaves and preterm and early-term birth in 50 US metropolitan areas: a matched case-control study.

BACKGROUND: The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth. METHODS: Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37-38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5th percentile of MSA-specific temperature metrics, or the 85th percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth (or corresponding gestational week for controls) were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed. RESULTS: There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5th percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth (95%CI: 1.014, 1.039). Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers. CONCLUSION: Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study's findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.

Age-Specific Associations of Ozone and Fine Particulate Matter with Respiratory Emergency Department Visits in the United States.

RATIONALE: Whereas associations between air pollution and respiratory morbidity for adults 65 years and older are well documented in the United States, the evidence for people under 65 is less extensive. To address this gap, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program collected respiratory emergency department (ED) data from 17 states. OBJECTIVES: To estimate age-specific acute effects of ozone and fine particulate matter (particulate matter ≤2.5 mm in aerodynamic diameter [PM2.5]) on respiratory ED visits. METHODS: We conducted time-series analyses in 894 counties by linking daily respiratory ED visits with estimated ozone and PM2.5 concentrations during the week before the date of the visit. Overall effect estimates were obtained with a Bayesian hierarchical model to combine county estimates for each pollutant by age group (children, 0-18; adults, 19-64; adults ≥ 65, and all ages) and by outcome group (acute respiratory infection, asthma, chronic obstructive pulmonary disease, pneumonia, and all respiratory ED visits). MEASUREMENTS AND MAIN RESULTS: Rate ratios (95% credible interval) per 10-µg/m3 increase in PM2.5 and all respiratory ED visits were 1.024 (1.018-1.029) among children, 1.008 (1.004-1.012) among adults younger than 65 years, and 1.002 (0.996-1.007) among adults 65 and older. Per 20-ppb increase in ozone, rate ratios were 1.017 (1.011-1.023) among children, 1.051 (1.046-1.056) among adults younger than 65, and 1.033 (1.026-1.040) among adults 65 and older. Associations varied in magnitude by age group for each outcome group. CONCLUSIONS: These results address a gap in the evidence used to ensure adequate public health protection under national air pollution policies.

Spatiotemporal Error in Rainfall Data: Consequences for Epidemiologic Analysis of Waterborne Diseases.

The relationship between rainfall, especially extreme rainfall, and increases in waterborne infectious diseases is widely reported in the literature. Most of this research, however, has not formally considered the impact of exposure measurement error contributed by the limited spatiotemporal fidelity of precipitation data. Here, we evaluate bias in effect estimates associated with exposure misclassification due to precipitation data fidelity, using extreme rainfall as an example. We accomplished this via a simulation study, followed by analysis of extreme rainfall and incident diarrheal disease in an epidemiologic study in Ecuador. We found that the limited fidelity typical of spatiotemporal rainfall data sets biases effect estimates towards the null. Use of spatial interpolations of rain-gauge data or satellite data biased estimated health effects due to extreme rainfall (occurrence) and wet conditions (accumulated totals) downwards by 35%-45%. Similar biases were evident in the Ecuadorian case study analysis, where spatial incompatibility between exposed populations and rain gauges resulted in the association between extreme rainfall and diarrheal disease incidence being approximately halved. These findings suggest that investigators should pay greater attention to limitations in using spatially heterogeneous environmental data sets to assign exposures in epidemiologic research.

Enrichment of HER2 Amplification in Brain Metastases from Primary Gastrointestinal Malignancies.

BACKGROUND: In nongastric gastrointestinal (GI) cancers, HER2-positive (HER2+) disease is not common. In breast cancer, HER2 status is associated with increased risk of brain metastases and response to HER2-targeted therapy. The purpose of this project was to compare HER2 status in GI cancer brain metastases versus matched prior sites of disease in order to determine if HER2+ disease is more common intracranially. MATERIALS AND METHODS: We identified 28 patients with GI cancer who had craniotomy for brain metastases between 1999 and 2017 with intracranial metastatic tissue available at Massachusetts General Hospital. Twenty-four patients also had tissue from a prior site of disease. Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) for HER2 were performed on all samples. A tumor was defined as HER2+ if it had 3+ staining by IHC or amplification by FISH. RESULTS: A prior site of disease (including intracranial metastases) was HER2+ for 13% of evaluable patients: 3 of 11 patients with colorectal cancer and no patients with esophageal or pancreatic cancer. The most recent brain metastases were HER2+ for 32% of patients: 2 of 3 esophageal squamous cell carcinomas, 3 of 10 esophageal adenocarcinomas (ACs), 3 of 14 colorectal ACs, and 1 of 1 pancreatic AC. Only 37.5% of patients with HER2+ brain metastasis had concordant HER2+ prior tissue (κ = 0.38, p = .017). CONCLUSION: In this cohort of patients with GI cancer with brain metastases, HER2+ status was more common intracranially compared with prior sites of disease. These findings suggest that testing HER2 in patients with GI cancer with brain metastases may lead to additional therapeutic options, regardless of HER2 status in previously examined tissue. IMPLICATIONS FOR PRACTICE: HER2 amplification is a well-known driver of oncogenesis in breast cancer, with associated increased risk of brain metastases and response to HER2-directed therapy. In nongastric gastrointestinal (GI) cancers, HER2 amplification is not common and consequently is infrequently tested. The current study shows that brain metastases in patients with GI primary malignancies have a relatively high likelihood of being HER2 positive despite HER2 amplification or overexpression being less commonly found in matched tissue from prior sites of disease. This suggests that regardless of prior molecular testing, patients with GI cancer with brain metastases who have tissue available are likely to benefit from HER2 assessment to identify potential novel therapeutic options.

Associations Between Ambient Air Pollutant Concentrations and Birth Weight: A Quantile Regression Analysis.

INTRODUCTION: We investigated the extent to which associations of ambient air pollutant concentrations and birth weight varied across birth weight quantiles. METHODS: We analyzed singleton births ≥27 weeks of gestation from 20-county metropolitan Atlanta with conception dates between January 1, 2002 and February 28, 2006 (N = 273,711). Trimester-specific and total pregnancy average concentrations for 10 pollutants, obtained from ground observations that were interpolated using 12-km Community Multiscale Air Quality model outputs, were assigned using maternal residence at delivery. We estimated associations between interquartile range width (IQRw) increases in pollutant concentrations and changes in birth weight using quantile regression. RESULTS: Gestational age-adjusted associations were of greater magnitude at higher percentiles of the birth weight distribution. Pollutants with large vehicle source contributions (carbon monoxide, nitrogen dioxide, PM2.5 elemental carbon, and total PM2.5 mass), as well as PM2.5 sulfate and PM2.5 ammonium, were associated with birth weight decreases for the higher birth weight percentiles. For example, whereas the decrease in mean birthweight per IQRw increase in PM2.5 averaged over pregnancy was -7.8 g (95% confidence interval = -13.6, -2.0 g), the quantile-specific associations were: 10th percentile -2.4 g (-11.5, 6.7 g); 50th percentile -8.9 g (-15.7, -2.0g); and 90th percentile -19.3 g (-30.6, -7.9 g). Associations for the intermediate and high birth weight quantiles were not sensitive to gestational age adjustment. For some pollutants, we saw associations at the lowest quantile (10th percentile) when not adjusting for gestational age. CONCLUSIONS: Associations between air pollution and reduced birth weight were of greater magnitude for newborns at relatively heavy birth weights.

Source-Apportioned PM2.5 and Cardiorespiratory Emergency Department Visits: Accounting for Source Contribution Uncertainty.

BACKGROUND: Despite evidence suggesting that air pollution-related health effects differ by emissions source, epidemiologic studies on fine particulate matter (PM2.5) infrequently differentiate between particles from different sources. Those that do rarely account for the uncertainty of source apportionment methods. METHODS: For each day in a 12-year period (1998-2010) in Atlanta, GA, we estimated daily PM2.5 source contributions from a Bayesian ensemble model that combined four source apportionment methods including chemical transport and receptor-based models. We fit Poisson generalized linear models to estimate associations between source-specific PM2.5 concentrations and cardiorespiratory emergency department visits (n = 1,598,117). We propagated uncertainty in the source contribution estimates through analyses using multiple imputation. RESULTS: Respiratory emergency department visits were positively associated with biomass burning and secondary organic carbon. For a 1 µg/m increase in PM2.5 from biomass burning during the past 3 days, the rate of visits for all respiratory outcomes increased by 0.4% (95% CI 0.0%, 0.7%). There was less evidence for associations between PM2.5 sources and cardiovascular outcomes, with the exception of ischemic stroke, which was positively associated with most PM2.5 sources. Accounting for the uncertainty of source apportionment estimates resulted, on average, in an 18% increase in the standard error for rate ratio estimates for all respiratory and cardiovascular emergency department visits, but inflation varied across specific sources and outcomes, ranging from 2% to 39%. CONCLUSIONS: This study provides evidence of associations between PM2.5 sources and some cardiorespiratory outcomes and quantifies the impact of accounting for variability in source apportionment approaches.

Exposure to Mobile Source Air Pollution in Early-life and Childhood Asthma Incidence: The Kaiser Air Pollution and Pediatric Asthma Study.

BACKGROUND: Early-life exposure to traffic-related air pollution exacerbates childhood asthma, but it is unclear what role it plays in asthma development. METHODS: The association between exposure to primary mobile source pollutants during pregnancy and during infancy and asthma incidence by ages 2 through 6 was examined in the Kaiser Air Pollution and Pediatric Asthma Study, a racially diverse birth cohort of 24,608 children born between 2000 and 2010 and insured by Kaiser Permanente Georgia. We estimated concentrations of mobile source fine particulate matter (PM2.5, µg/m), nitrogen oxides (NOX, ppb), and carbon monoxide (CO, ppm) at the maternal and child residence using a Research LINE source dispersion model for near-surface releases. Asthma was defined using diagnoses and medication dispensings from medical records. We used binomial generalized linear regression to model the impact of exposure continuously and by quintiles on asthma risk. RESULTS: Controlling for covariates and modeling log-transformed exposure, a 2.7-fold increase in first year of life PM2.5 was associated with an absolute 4.1% (95% confidence interval, 1.6%, 6.6%) increase in risk of asthma by age 5. Quintile analysis showed an increase in risk from the first to second quintile, but similar risk across quintiles 2-5. Risk differences increased with follow-up age. Results were similar for NOX and CO and for exposure during pregnancy and the first year of life owing to high correlation. CONCLUSIONS: Results provide limited evidence for an association of early-life mobile source air pollution with childhood asthma incidence with a steeper concentration-response relationship observed at lower levels of exposure.

Caesarean delivery, childhood asthma, and effect modification by sex: An observational study and meta-analysis.

BACKGROUND: Numerous studies indicate caesarean delivery is associated with childhood asthma. Sex-specific associations were reported in four of these studies, and in all four studies, the estimated association between caesarean delivery and asthma was of greater magnitude among girls, although most report a lack of evidence of multiplicative interaction. METHODS: We assessed potential effect modification by sex, on the additive and multiplicative scales, of the association between caesarean delivery and asthma by ages 2 through 6 in up to 17 075 racially diverse children from a retrospective birth cohort, the Kaiser Air Pollution and Pediatric Asthma (KAPPA) Study. We also conducted a random-effects meta-analysis, combining our sex-stratified results (using the odds ratio for compatibility with previous studies) with previously published results. RESULTS: Adjusted risk differences for caesarean delivery and asthma in the KAPPA cohort were higher among girls than boys at every follow-up age. By age 5, caesarean delivery was associated with an absolute 3.8% (95% confidence interval [CI] 0.4%, 7.3%) higher asthma risk among girls and a 1.9% (95% CI -1.7, 5.4) higher risk among boys. The summary odds ratio from the meta-analysis for caesarean delivery and asthma among girls was 1.26 (95% CI 1.14, 1.39) and 1.08 (95% CI 0.98, 1.20) among boys (P = 0.036). CONCLUSIONS: Higher, but imprecise, estimates for females across five studies should motivate investigators to estimate sex-specific associations for caesarean delivery and asthma and to explore biological mechanisms or sex-dependent biases that could explain this possible heterogeneity.

Correction to: Early-life exposure to PM2.5 and risk of acute asthma clinical encounters among children in Massachusetts: a case-crossover analysis.

After publication of the article [1], it was brought to our attention that a number in Table 1 is incorrect.