Associations between satellite-derived estimates of PM2.5 species concentrations for organic carbon, elemental carbon, nitrate, and sulfate with birth weight and preterm birth in California during 2005-2014.

BACKGROUND: Characterizing the spatial distribution of PM2.5 species concentrations is challenging due to the geographic sparsity of the stationary monitoring network. Recent advances have enabled valid estimation of PM2.5 species concentrations using satellite remote sensing data for use in epidemiologic studies. OBJECTIVE: In this study, we used satellite-based estimates of ambient PM2.5 species concentrations to estimate associations with birth weight and preterm birth in California. METHODS: Daily 24 h averaged ground-level PM2.5 species concentrations of organic carbon, elemental carbon, nitrate, and sulfate were estimated during 2005-2014 in California at 1 km resolution. Birth records were linked to ambient pollutant exposures based on maternal residential zip code. Linear regression and Cox regression were conducted to estimate the effect of 1 µg/m3 increases in PM2.5 species concentrations on birth weight and preterm birth. RESULTS: Analyses included 4.7 million live singleton births having a median 28 days with exposure measurements per pregnancy. In single pollutant models, the observed changes in mean birth weight (per 1 µg/m3 increase in speciated PM2.5 concentrations) were: organic carbon -3.12 g (CI: -4.71, -1.52), elemental carbon -14.20 g (CI: -18.76, -9.63), nitrate -5.51 g (CI: -6.79, -4.23), and sulfate 9.26 g (CI: 7.03, 11.49). Results from multipollutant models were less precise due to high correlation between pollutants. Associations with preterm birth were null, save for a negative association between sulfate and preterm birth (Hazard Ratio per 1 µg/m3 increase: 0.973 CI: 0.958, 0.987).

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.

Effects of air pollution on adverse birth outcomes and pregnancy complications in the U.S. state of Kansas (2000-2015).

Neonatal mortality and morbidity are often caused by preterm birth and lower birth weight. Gestational diabetes mellitus (GDM) and gestational hypertension (GH) are the most prevalent maternal medical complications during pregnancy. However, evidence on effects of air pollution on adverse birth outcomes and pregnancy complications is mixed. Singleton live births conceived between January 1st, 2000, and December 31st, 2015, and reached at least 27 weeks of pregnancy in Kansas were included in the study. Trimester-specific and total pregnancy exposures to nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter less than 2.5 µm (PM2.5), and ozone (O3) were estimated using spatiotemporal ensemble models and assigned to maternal residential census tracts. Logistic regression, discrete-time survival, and linear models were applied to assess the associations. After adjustment for demographics and socio-economic status (SES) factors, we found increases in the second and third trimesters and total pregnancy O3 exposures were significantly linked to preterm birth. Exposure to the second and third trimesters O3 was significantly associated with lower birth weight, and exposure to NO2 during the first trimester was linked to an increased risk of GDM. O3 exposures in the first trimester were connected to an elevated risk of GH. We didn't observe consistent associations between adverse pregnancy and birth outcomes with PM2.5 exposure. Our findings indicate there is a positive link between increased O3 exposure during pregnancy and a higher risk of preterm birth, GH, and decreased birth weight. Our work supports limiting population exposure to air pollution, which may lower the likelihood of adverse birth and pregnancy outcomes.

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.

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.

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.

The role of state breastfeeding laws and programs on exclusive breastfeeding practice among mothers in the special supplemental nutrition program for Women, Infants, and Children (WIC).

BACKGROUND: It is unclear if state laws supporting breastfeeding are associated with exclusive breastfeeding (EBF) practice among low-income mothers participating in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). The main objectives of our study were to assess the relationship between such laws and EBF among WIC-participating mothers and to assess whether this association varied by employment status. We also assessed how mother's exposure to WIC breastfeeding consultation was associated with EBF. METHODS: A cross-sectional study was conducted across seven WIC program locations (i.e., Georgia, Massachusetts, Nevada, Pennsylvania, Wisconsin, Wyoming, Chickasaw Nation) between July-August 2020. Data were collected using convenient sampling from each program location and surveys were administered electronically or on paper to WIC-participating mothers. We restricted our analysis to data from 1161 WIC-participating mothers with infants aged zero to five months old. Multivariable mixed models were used to estimate the relationship between our exposures of interest (i.e., number of laws supporting breastfeeding, employment-related breastfeeding laws, WIC breastfeeding consultation) and EBF, while controlling for potential confounders and accounting for clustering by program location. Effect modification by employment status was assessed on the additive and multiplicative scales. RESULTS: Among WIC-participating mothers living in program locations with no employment-related breastfeeding laws, EBF was 26% less prevalent for employed mothers compared to unemployed mothers (adjusted prevalence ratios [aPR]: 0.74, 95% CI: 0.67,0.83). Among all mothers, a one-unit increase in laws supporting breastfeeding was not associated with EBF (aPR: 0.88, 95% CI: 0.71,1.10). However, among employed mothers, living in areas with more employment-related laws was associated with a higher prevalence of EBF (aPR: 1.43, 95% CI: 0.83, 2.44). Infants whose mothers received a WIC breastfeeding consultation had 33% higher prevalence of being exclusively breastfed compared to infants whose mothers did not receive a WIC breastfeeding consultation (aPR: 1.33, 95% CI: 1.05,1.70). CONCLUSIONS: Infants whose WIC-participating mothers were employed, were less likely to be exclusively breastfed, but our effect modification analyses showed that laws supporting breastfeeding at the workplace may promote EBF among employed women. EBF was more prevalent among mothers who received a WIC breastfeeding consultation compared to those who did not receive such a consultation.

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.

Estimating Heat-Related Exposures and Urban Heat Island Impacts: A Case Study for the 2012 Chicago Heatwave.

Accelerated urbanization increases both the frequency and intensity of heatwaves (HW) and urban heat islands (UHIs). An extreme HW event occurred in 2012 summer that caused temperatures of more than 40°C in Chicago, Illinois, USA, which is a highly urbanized city impacted by UHIs. In this study, multiple numerical models, including the High Resolution Land Data Assimilation System (HRLDAS) and Weather Research and Forecasting (WRF) model, were used to simulate the HW and UHI, and their performance was evaluated. In addition, sensitivity testing of three different WRF configurations was done to determine the impact of increasing model complexity in simulating urban meteorology. Model performances were evaluated based on the statistical performance metrics, the application of a multi-layer urban canopy model (MLUCM) helps WRF to provide the best performance in this study. HW caused rural temperatures to increase by ∼4°C, whereas urban Chicago had lower magnitude increases from the HW (∼2-3°C increases). Nighttime UHI intensity (UHII) ranged from 1.44 to 2.83°C during the study period. Spatiotemporal temperature fields were used to estimate the potential heat-related exposure and to quantify the Excessive Heat Factor (EHF). The EHF during the HW episode provides a risk map indicating that while urban Chicago had higher heat-related stress during this event, the rural area also had high risk, especially during nighttime in central Illinois. This study provides a reliable method to estimate spatiotemporal exposures for future studies of heat-related health impacts.

CRITICAL WINDOW VARIABLE SELECTION FOR MIXTURES: ESTIMATING THE IMPACT OF MULTIPLE AIR POLLUTANTS ON STILLBIRTH.

Understanding the role of time-varying pollution mixtures on human health is critical as people are simultaneously exposed to multiple pollutants during their lives. For vulnerable subpopulations who have well-defined exposure periods (e.g., pregnant women), questions regarding critical windows of exposure to these mixtures are important for mitigating harm. We extend critical window variable selection (CWVS) to the multipollutant setting by introducing CWVS for mixtures (CWVSmix), a hierarchical Bayesian method that combines smoothed variable selection and temporally correlated weight parameters to: (i) identify critical windows of exposure to mixtures of time-varying pollutants, (ii) estimate the time-varying relative importance of each individual pollutant and their first order interactions within the mixture, and (iii) quantify the impact of the mixtures on health. Through simulation we show that CWVSmix offers the best balance of performance in each of these categories in comparison to competing methods. Using these approaches, we investigate the impact of exposure to multiple ambient air pollutants on the risk of stillbirth in New Jersey, 2005-2014. We find consistent elevated risk in gestational weeks 2, 16-17, and 20 for non-Hispanic Black mothers, with pollution mixtures dominated by ammonium (weeks 2, 17, 20), nitrate (weeks 2, 17), nitrogen oxides (weeks 2, 16), PM2.5 (week 2), and sulfate (week 20). The method is available in the R package CWVSmix.

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.

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.

The interrelationship between water access, exclusive breastfeeding and diarrhea in children: a cross-sectional assessment across 19 African countries.

BACKGROUND: Access to an improved water supply and practicing exclusive breastfeeding are essential for improving maternal and child health outcomes. However, few studies have been equipped to assess the interdependencies between access to improved water, practicing exclusive breastfeeding, and child health. The primary aim of our study was to assess whether access to an improved water supply and water-fetching were associated with mothers' practice of exclusive breastfeeding. METHODS: We analyzed data on 247 090 mothers with children 5 months old or less using Multiple Indicator Cluster Surveys from 19 African countries. Multivariable logistic regression was used to estimate the relationship between our exposures and exclusive breastfeeding practice, while meta-analytic methods were used to pool adjusted estimates across 19 countries. RESULTS: The prevalence of exclusive breastfeeding ranged from 22% in Nigeria to 70% in Malawi. Pooled results showed water-fetching was not associated with exclusive breastfeeding (adjusted prevalence odds ratios (aPOR) = 1.04, 95% confidence interval (CI) = 0.89, 1.21). Access to an improved water source was also not associated with exclusive breastfeeding (aPOR = 1.06, 95% CI = 0.94, 1.21). Across all countries many women were spending a significant amount of time water-fetching each day (mean time varied from 20 minutes in Ghana to 115 minutes in Mauritania). Exclusively breastfed children had 33% lower odds of diarrhea than those who were not exclusively breastfed (aPOR = 0.67, 95% CI = 0.56, 0.78). CONCLUSION: Our study is the first to assess the relationship between access to improved water supply, water-fetching and exclusive breastfeeding. We found that access to water supply and time spent by mothers fetching water were not associated with exclusive breastfeeding practice, even though mothers spent significant time fetching water.

Caesarean delivery and the risk of atopic dermatitis in children.

BACKGROUND: Caesarean delivery (C-section) may disrupt maternal-infant microbial transfer and alter immune system development and subsequent risk for atopic dermatitis. OBJECTIVE: Investigate the association between C-section and atopic dermatitis by age four and examine potential sources of bias in the relationship in a large cohort study. METHODS: Maternal and child information was collected through Kaiser Permanente Northern California's (KPNC) integrated healthcare system. Data sources included electronic medical records, pharmacy databases, state birth records, and prospectively collected breastfeeding surveys. Children were eligible if they were born in a KPNC or contracting hospital between 2005 and 2014 and had continuous enrolment in the KPNC system for at least four years (n = 173 105). Modified Poisson regression with robust variance estimation was used to estimate the association between C-section and atopic dermatitis overall and when stratified by demographic and labour and delivery characteristics. RESULTS: Although unadjusted analyses showed a positive association between C-section and atopic dermatitis [RR(95%CI): 1.06(1.03, 1.10)], this effect was attenuated towards the null after adjustment [aRR(95%CI): 1.02(0.99, 1.05)]. In stratified analyses, there was evidence that C-section increased atopic dermatitis risk among certain subgroups (eg firstborns, overweight/obese pre-pregnancy BMI), but associations were weak. C-section delivery conditions indicative of the least exposure to maternal microbiome (ie no labour, short interval between membrane rupture and delivery) showed no evidence of association with atopic dermatitis. Estimated associations were not strongly influenced by intrapartum antibiotics, breastfeeding, missing data, or familial factors. CONCLUSION: Caesarean delivery was not associated with atopic dermatitis by age four in this large US cohort. This association did not appear to be biased by intrapartum antibiotics, breastfeeding behaviour, C-section indication, missing covariates, or familial factors.

Cesarean delivery and the risk of allergic rhinitis in children.

BACKGROUND: Cesarean delivery (C-section) may influence the infant microbiome and affect immune system development and subsequent risk for allergic rhinitis (AR). OBJECTIVE: To investigate the association between C-section and AR at ages 6, 8, and 10 years. METHODS: Data were collected prospectively through Kaiser Permanente Northern Californias (KPNC) integrated healthcare system. Children were eligible if they were born in a KPNC hospital and remained in the KPNC system for minimum 6 years (n = 117,768 age 6; n = 75,115 age 8; n = 40,332 age 10). Risk ratios (RR) for C-section and AR were estimated at each follow-up age and adjusted for important covariates, including intrapartum antibiotics, pre-pregnancy body mass index, maternal allergic morbidities, and breastfeeding. Subanalyses considered information on C-section indication, labor, and membrane rupture. RESULTS: After adjusting for confounders, we did not observe an association between C-section and AR at follow-up ages 6, 8, or 10 years (RR [CI]: 6 years, 0.98 [0.91, 1.04]; 8 years, 1.00 [0.95, 1.07]; 10 years, 1.03 [0.96, 1.10]). In stratified analyses, there was limited evidence that C-section increases the risk of AR in certain subgroups (eg, children of non-atopic mothers, second or higher birth order children), but most estimated risk ratios were consistent with no association. Estimated associations were unaffected by participant attrition, missing data, or intrapartum antibiotics. CONCLUSION: C-section delivery was not associated with AR at follow-up ages of 6, 8, or 10 years in a large contemporary US cohort.

Hormonal Profiles of Menstrual Bleeding Patterns During the Luteal-Follicular Transition.

CONTEXT: Menstrual cycle function is determined by a complex endocrine axis that controls the ovaries and endometrium. While the late luteal phase is characterized by declining progesterone and estrogen, how these hormonal profiles relate to menstrual bleeding patterns is not well understood. OBJECTIVE: Characterize associations between luteal phase hormonal profiles and subsequent menstrual bleeding patterns, specifically spotting before bleeding. DESIGN, SETTING, AND PARTICIPANTS: We examined creatinine-adjusted urinary estrone 3-glucuronide (E13G) and pregnanediol 3-glucuronide (Pd3G) levels in relation to spotting in 116 premenopausal women (ages 20-47) who kept daily menstrual diaries and collected first morning urine samples for ≥ 2 consecutive cycles or 1 luteal-follicular transition (n = 283 transitions). We used linear mixed models to estimate associations between luteal phase hormone levels and spotting before bleeding. MAIN OUTCOME MEASURE(S) AND RESULTS: Transitions with ≥ 1 days of spotting before menstrual bleeding (n = 118) had greater luteal phase Pd3G levels vs nonspotting transitions (n = 165). Differences in Pd3G between spotting and nonspotting transitions were largest at menses onset (34.8%, 95% confidence interval, 18.9%, 52.7%). Pd3G levels for spotting transitions dropped to similar levels as nonspotting transitions an average of 1 day later, which aligned with the first day of bleeding for transitions with contiguous spotting. Spotting transitions were preceded by slower rates of Pd3G decline than nonspotting transitions, whereas E13G declines were similar. CONCLUSIONS: Self-reported bleeding patterns may provide insight into luteal phase Pd3G levels. First bleed appears to be the best choice for defining the end of the luteal phase and achieving hormonal consistency across transitions.

Acute associations between PM2.5 and ozone concentrations and asthma exacerbations among patients with and without allergic comorbidities.

Acute effects of outdoor air pollution on asthma exacerbations may vary by asthma phenotype (allergic vs nonallergic). Associations of ambient PM2.5 and ozone concentrations with acute asthma visits (office, urgent, emergency, and hospitalization) were investigated using electronic medical records. International Classification of Disease codes were used to identify asthmatics, and classify them based on the presence or absence of an allergic comorbidity in their medical records. Daily 24-h average PM2.5, 8-h maximum ozone, and mean temperature were obtained from a centralized monitor. Using a time-stratified case-crossover approach, pollutant concentrations were modeled using moving averages and distributed lag nonlinear models (lag 0-6) to examine lag associations and nonlinear concentration-response. The adjusted odds ratios for a 10 µg/m3 increase in 3-day moving average (lag 0-2) PM2.5 in the two-pollutant models among patients with and without allergic comorbidities were 1.10 (95% confidence interval [CI]: 1.07, 1.13) and 1.05 (95% CI: 1.02, 1.09), respectively; and for a 20 ppb increase in 3-day moving average (lag 0-2) ozone were 1.08 (95% CI: 1.02, 1.14) and 1.00 (95% CI: 0.95, 1.05), respectively. Estimated odds ratios among patients with allergic comorbidities were consistently higher across age, sex, and temperature categories. Asthmatics with an allergic comorbidity may be more susceptible to ambient PM2.5 and ozone.