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Early life phthalates exposure has been associated with adverse respiratory outcomes. However, evidence linking prenatal phthalates exposure and childhood lung function has been inconclusive. Additionally, few studies have examined phthalates exposure as a mixture and explored sexually dimorphic associations. We aimed to investigate sex-specific associations of prenatal phthalates mixtures with childhood lung function using the PROGRESS cohort in Mexico (N = 476). Prenatal phthalate concentrations were measured in maternal urine collected during the 2nd and 3rd trimesters. Children's lung function was evaluated at ages 8-13 years. Individual associations were assessed using multivariable linear regression, and mixture associations were modeled using repeated holdout WQS regression and hierarchical BKMR; data was stratified by sex to explore sex-specific associations. We identified significant interactions between 2nd trimester phthalates mixture and sex on FEV1 and FVC z-scores. Higher 2nd trimester phthalate concentrations were associated with higher FEV1 (ß = 0.054, 95 %CI: 0.005, 0.104) and FVC z-scores (ß = 0.074, 95 % CI: 0.024, 0.124) in females and with lower measures in males (FEV1, ß = -0.017, 95 %CI: -0.066, 0.026; FVC, ß = -0.014, 95 %CI: -0.065, 0.030). This study indicates that prenatal exposure to phthalates is related to childhood lung function in a sex-specific manner.

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Introduction: Neurotoxicity resulting from air pollution is of increasing concern. Considering exposure timing effects on neurodevelopmental impairments may be as important as the exposure dose. We used distributed lag regression to determine the sensitive windows of prenatal exposure to fine particulate matter (PM2.5) on children's cognition in a birth cohort in Mexico. Methods: Analysis included 553 full-term (≥37 weeks gestation) children. Prenatal daily PM2.5 exposure was estimated using a validated satellite-based spatiotemporal model. McCarthy Scales of Children's Abilities (MSCA) were used to assess children's cognitive function at 4-5 years old (lower scores indicate poorer performance). To identify susceptibility windows, we used Bayesian distributed lag interaction models to examine associations between prenatal PM2.5 levels and MSCA. This allowed us to estimate vulnerable windows while testing for effect modification. Results: After adjusting for maternal age, socioeconomic status, child age, and sex, Bayesian distributed lag interaction models showed significant associations between increased PM2.5 levels and decreased general cognitive index scores at 31-35 gestation weeks, decreased quantitative scale scores at 30-36 weeks, decreased motor scale scores at 30-36 weeks, and decreased verbal scale scores at 37-38 weeks. Estimated cumulative effects (CE) of PM2.5 across pregnancy showed significant associations with general cognitive index (CE^ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale (CE^ = -0.27, 95% CI = -0.74, -0.02), motor scale (CE^ = -0.25, 95% CI = -0.44, -0.05), and verbal scale (CE^ = -0.2, 95% CI = -0.43, -0.02). No significant sex interactions were observed. Conclusions: Prenatal exposure to PM2.5, particularly late pregnancy, was inversely associated with subscales of MSCA. Using data-driven methods to identify sensitive window may provide insight into the mechanisms of neurodevelopmental impairment due to pollution.

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BACKGROUND: Satellite-based PM2.5 predictions are being used to advance exposure science and air-pollution epidemiology in developed countries; including emerging evidence about the impacts of PM2.5 on acute health outcomes beyond the cardiovascular and respiratory systems, and the potential modifying effects from individual-level factors in these associations. Research on these topics is lacking in low and middle income countries. We aimed to explore the association between short-term exposure to PM2.5 with broad-category and cause-specific mortality outcomes in the Mexico City Metropolitan Area (MCMA), and potential effect modification by age, sex, and SES characteristics in such associations. METHODS: We used a time-stratified case-crossover study design with 1,479,950 non-accidental deaths from the MCMA for the period of 2004-2019. Daily 1 × 1 km PM2.5 (median = 23.4 µg/m3; IQR = 13.6 µg/m3) estimates from our satellite-based regional model were employed for exposure assessment at the sub-municipality level. Associations between PM2.5 with broad-category (organ-system) and cause-specific mortality outcomes were estimated with distributed lag conditional logistic models. We also fit models stratifying by potential individual-level effect modifiers including; age, sex, and individual SES-related characteristics namely: education, health insurance coverage, and job categories. Odds ratios were converted into percent increase for ease of interpretation. RESULTS: PM2.5 exposure was associated with broad-category mortality outcomes, including all non-accidental, cardiovascular, cerebrovascular, respiratory, and digestive mortality. A 10-µg/m3 PM2.5 higher cumulative exposure over one week (lag06) was associated with higher cause-specific mortality outcomes including hypertensive disease [2.28% (95%CI: 0.26%-4.33%)], acute ischemic heart disease [1.61% (95%CI: 0.59%-2.64%)], other forms of heart disease [2.39% (95%CI: -0.35%-5.20%)], hemorrhagic stroke [3.63% (95%CI: 0.79%-6.55%)], influenza and pneumonia [4.91% (95%CI: 2.84%-7.02%)], chronic respiratory disease [2.49% (95%CI: 0.71%-4.31%)], diseases of the liver [1.85% (95%CI: 0.31%-3.41%)], and renal failure [3.48% (95%CI: 0.79%-6.24%)]. No differences in effect size of associations were observed between age, sex and SES strata. CONCLUSIONS: Exposure to PM2.5 was associated with non-accidental, broad-category and cause-specific mortality outcomes beyond the cardiovascular and respiratory systems, including specific death-causes from the digestive and genitourinary systems, with no indication of effect modification by individual-level characteristics.

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In recent years, there has been growing interest in developing air pollution prediction models to reduce exposure measurement error in epidemiologic studies. However, efforts for localized, fine-scale prediction models have been predominantly focused in the United States and Europe. Furthermore, the availability of new satellite instruments such as the TROPOsopheric Monitoring Instrument (TROPOMI) provides novel opportunities for modeling efforts. We estimated daily ground-level nitrogen dioxide (NO2) concentrations in the Mexico City Metropolitan Area at 1-km2 grids from 2005 to 2019 using a four-stage approach. In stage 1 (imputation stage), we imputed missing satellite NO2 column measurements from the Ozone Monitoring Instrument (OMI) and TROPOMI using the random forest (RF) approach. In stage 2 (calibration stage), we calibrated the association of column NO2 to ground-level NO2 using ground monitors and meteorological features using RF and extreme gradient boosting (XGBoost) models. In stage 3 (prediction stage), we predicted the stage 2 model over each 1-km2 grid in our study area, then ensembled the results using a generalized additive model (GAM). In stage 4 (residual stage), we used XGBoost to model the local component at the 200-m2 scale. The cross-validated R2 of the RF and XGBoost models in stage 2 were 0.75 and 0.86 respectively, and 0.87 for the ensembled GAM. Cross-validated rootmean-squared error (RMSE) of the GAM was 3.95 µg/m3. Using novel approaches and newly available remote sensing data, our multi-stage model presented high cross-validated fits and reconstructs fine-scale NO2 estimates for further epidemiologic studies in Mexico City.

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Background: Satellite-based PM2.5 predictions are being used to advance exposure science and air-pollution epidemiology in developed countries; including emerging evidence about the impacts of PM2.5 on acute health outcomes beyond the cardiovascular and respiratory systems, and the potential modifying effects from individual-level factors in these associations. Research on these topics is lacking in Latin America. Methods: We used a time-stratified case-crossover study design with 1,479,950 non-accidental deaths from Mexico City Metropolitan Area for the period of 2004-2019. Daily 1×1 km PM2.5 (median=23.4 µg/m3; IQR=13.6 µg/m3) estimates from our satellite-based regional model were employed for exposure assessment at the sub-municipality level. Associations between PM2.5 with broad-category (organ-system) and cause-specific mortality outcomes were estimated with distributed lag conditional logistic models. We also fit models stratifying by potential individual-level effect modifiers including; age, sex, and individual SES-related characteristics namely: education, health insurance coverage, and job categories. Results: PM2.5 exposure was associated with higher total non-accidental, cardiovascular, cerebrovascular, respiratory, and digestive mortality. A 10-µg/m3 PM2.5 higher cumulative exposure over one week (lag06) was associated with higher cause-specific mortality outcomes including hypertensive disease [2.28% (95%CI: 0.26%-4.33%)], acute ischemic heart disease [1.61% (95%CI: 0.59%-2.64%)], other forms of heart disease [2.39% (95%CI: -0.35%-5.20%)], hemorrhagic stroke [3.63% (95%CI: 0.79%-6.55%)], influenza and pneumonia [4.91% (95%CI: 2.84%-7.02%)], chronic respiratory disease [2.49% (95%CI: 0.71%-4.31%)], diseases of the liver [1.85% (95%CI: 0.31%-3.41%)], and renal failure [3.48% (95%CI: 0.79%-6.24%)]. No differences in effect size of associations were observed between SES strata. Conclusions: Exposure to PM2.5 was associated with mortality outcomes beyond the cardiovascular and respiratory systems, including specific death-causes from the digestive and genitourinary systems, with no indications of effect modification by individual SES-related characteristics.

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BACKGROUND: Machine-learning algorithms are becoming popular techniques to predict ambient air PM2.5 concentrations at high spatial resolutions (1 × 1 km) using satellite-based aerosol optical depth (AOD). Most machine-learning models have aimed to predict 24 h-averaged PM2.5 concentrations (mean PM2.5) in high-income regions. Over Mexico, none have been developed to predict subdaily peak levels, such as the maximum daily 1-h concentration (max PM2.5). OBJECTIVE: Our goal was to develop a machine-learning model to predict mean PM2.5 and max PM2.5 concentrations in the Mexico City Metropolitan Area from 2004 through 2019. METHODS: We present a new modeling approach based on extreme gradient boosting (XGBoost) and inverse-distance weighting that uses AOD, meteorology, and land-use variables. We also investigated applications of our mean PM2.5 predictions that can aid local authorities in air-quality management and public-health surveillance, such as the co-occurrence of high PM2.5 and heat, compliance with local air-quality standards, and the relationship of PM2.5 exposure with social marginalization. RESULTS: Our models for mean and max PM2.5 exhibited good performance, with overall cross-validated mean absolute errors (MAE) of 3.68 and 9.20 µg/m3, respectively, compared to mean absolute deviations from the median (MAD) of 8.55 and 15.64 µg/m3. In 2010, everybody in the study region was exposed to unhealthy levels of PM2.5. Hotter days had greater PM2.5 concentrations. Finally, we found similar exposure to PM2.5 across levels of social marginalization. SIGNIFICANCE: Machine learning algorithms can be used to predict highly spatiotemporally resolved PM2.5 concentrations even in regions with sparse monitoring. IMPACT: Our PM2.5 predictions can aid local authorities in air-quality management and public-health surveillance, and they can advance epidemiological research in Central Mexico with state-of-the-art exposure assessment methods.

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BACKGROUND: Phthalates are endocrine disrupting chemicals that may influence weight status; however, few studies have considered weight gain during pregnancy and subsequent long-term weight changes in women. OBJECTIVE: To determine associations of prenatal phthalate exposure with maternal weight during pregnancy and through up to seven years post-delivery. METHODS: We analyzed 15 urinary phthalate biomarker concentrations during the 2nd and 3rd trimesters among 874 pregnant women enrolled in the Programming Research in Obesity, Growth Environment and Social Stress Study in Mexico City. We examined three time-specific maternal weight outcomes: gestational weight gain (between 2nd and 3rd trimesters), short-term weight (between 3rd trimester and 12 months post-delivery), and long-term weight (between 18 months and 6-7 years post-delivery). We used Bayesian Kernel Machine Regression (BKMR) to estimate associations for the total phthalate mixture, as well as multivariable linear mixed models for individual phthalate biomarkers. RESULTS: As a mixture, 2nd trimester urinary phthalate biomarker concentrations were associated with somewhat lower gestational weight gain between the 2nd and 3rd trimesters (interquartile range, IQR, difference: -0.07 standard deviations, SD; 95% credible interval, CrI: -0.20, 0.06); multivariable regression and BKMR models indicated that this inverse association was primarily driven by mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP). Prenatal (2nd and 3rd trimesters) urinary phthalate mixture concentrations were positively associated with maternal weight change through 12 months postpartum (IQR difference: 0.11 SD; 95% CrI: 0.00, 0.23); these associations persisted from 18 months to 6-7 years follow-up (IQR difference: 0.07 SD; 95% CrI: 0.04, 0.10). Postpartum weight changes were associated with mono-3-carboxypropyl phthalate (MCPP) and MECPTP. CONCLUSIONS: Prenatal phthalate exposure was inversely associated with gestational weight gain and positively associated with long-term changes in maternal weight. Further investigation is required to understand how phthalates may influence body composition and whether they contribute to the development of obesity and other cardiometabolic diseases in women.

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BACKGROUND: Exposure to air pollution is the main risk factor for morbidity and mortality in the world. Exposure to particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) is associated with cardiovascular and respiratory conditions, as well as with lung cancer, and there is evidence to suggest that it is also associated with type II diabetes (DM). The Mexico City Metropolitan Area (MCMA) is home to more than 20 million people, where PM2.5 levels exceed national and international standards every day. Likewise, DM represents a growing public health problem with prevalence around 12%. In this study, the objective was to evaluate the association between exposure to PM2.5 and DM in adults living in the MCMA. METHODS: Data from the 2006 or 2012 National Health and Nutrition Surveys (ENSANUT) were used to identify subjects with DM and year of diagnosis. We estimated PM2.5 exposure at a residence level, based on information from the air quality monitoring system (monitors), as well as satellite measurements (satellite). We analyzed the relationship through a cross-sectional approach and as a case - control study. RESULTS: For every 10 µg/m3 increase of PM2.5 we found an OR = 3.09 (95% CI 1.17-8.15) in the 2012 sample. These results were not conclusive for the 2006 data or for the case - control approach. CONCLUSIONS: Our results add to the evidence linking PM2.5 exposure to DM in Mexican adults. Studies in low- and middle-income countries, where PM2.5 atmospheric concentrations exceed WHO standards, are required to strengthen the evidence.

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While weather stations generally capture near-surface ambient air temperature (Ta) at a high temporal resolution to calculate daily values (i.e., daily minimum, mean, and maximum Ta), their fixed locations can limit their spatial coverage and resolution even in densely populated urban areas. As a result, data from weather stations alone may be inadequate for Ta-related epidemiology particularly when the stations are not located in the areas of interest for human exposure assessment. To address this limitation in the Megalopolis of Central Mexico (MCM), we developed the first spatiotemporally resolved hybrid satellite-based land use regression Ta model for the region, home to nearly 30 million people and includes Mexico City and seven more metropolitan areas. Our model predicted daily minimum, mean, and maximum Ta for the years 2003-2019. We used data from 120 weather stations and Land Surface Temperature (LST) data from NASA's MODIS instruments on the Aqua and Terra satellites on a 1 × 1 km grid. We generated a satellite-hybrid mixed-effects model for each year, regressing Ta measurements against land use terms, day-specific random intercepts, and fixed and random LST slopes. We assessed model performance using 10-fold cross-validation at withheld stations. Across all years, the root-mean-square error ranged from 0.92 to 1.92 K and the R 2 ranged from .78 to .95. To demonstrate the utility of our model for health research, we evaluated the total number of days in the year 2010 when residents ≥65 years old were exposed to Ta extremes (above 30°C or below 5°C). Our model provides much needed high-quality Ta estimates for epidemiology studies in the MCM region.

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INTRODUCTION: Prenatal exposure to fine particulate matter air pollution (PM2.5) is an important, under-studied risk factor for neurodevelopmental dysfunction. We describe the relationships between prenatal PM2.5 exposure and vigilance and inhibitory control, executive functions related to multiple health outcomes in Mexico City children. METHODS: We studied 320 children enrolled in Programming Research in Obesity, GRowth, Environment and Social Stressors, a longitudinal birth cohort study in Mexico City. We used a spatio-temporal model to estimate daily prenatal PM2.5 exposure at each participant's residential address. At age 9-10 years, children performed three Go/No-Go tasks, which measure vigilance and inhibitory control ability. We used Latent class analysis (LCA) to classify performance into subgroups that reflected neurocognitive performance and applied multivariate regression and distributed lag regression modeling (DLM) to test overall and time-dependent associations between prenatal PM2.5 exposure and Go/No-Go performance. RESULTS: LCA detected two Go/No-Go phenotypes: high performers (Class 1) and low performers (Class 2). Predicting odds of Class 1 vs Class 2 membership based on prenatal PM2.5 exposure timing, logistic regression modeling showed that average prenatal PM2.5 exposure in the second and third trimesters correlated with increased odds of membership in low-performance Class 2 (OR = 1.59 (1.16, 2.17), p = 0.004). Additionally, DLM analysis identified a critical window consisting of gestational days 103-268 (second and third trimesters) in which prenatal PM2.5 exposure predicted poorer Go/No-Go performance. DISCUSSION: Increased prenatal PM2.5 exposure predicted decreased vigilance and inhibitory control at age 9-10 years. These findings highlight the second and third trimesters of gestation as critical windows of PM2.5 exposure for the development of vigilance and inhibitory control in preadolescent children. Because childhood development of vigilance and inhibitory control informs behavior, academic performance, and self-regulation into adulthood, these results may help to describe the relationship of prenatal PM2.5 exposure to long-term health and psychosocial outcomes. The integrative methodology of this study also contributes to a shift towards more holistic analysis.

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BACKGROUND: Phthalate exposure has been associated with increased childhood behavioral problems. Existing studies failed to include phthalate replacements and did not account for high correlations among phthalates. Phthalates' exposure is higher in Mexico than in U.S. locations, making it an ideal target population for this study. AIM: To examine associations between 15 maternal prenatal phthalate metabolite concentrations and children's behavioral problems. METHODS: We quantified phthalate metabolites in maternal urine samples from maternal-child dyads (n = 514) enrolled in the Programming Research in Obesity, Growth Environment and Social Stress (PROGRESS) birth cohort in Mexico City. We performed least absolute shrinkage and selection operator (LASSO) regressions to identify associations between specific-gravity adjusted log2-transformed phthalate metabolites and parent-reported 4-6 year old behavior on the Behavior Assessment System for Children (BASC-2), accounting for metabolite correlations. We adjusted for socio-demographic and birth-related factors, and examined associations stratified by sex. RESULTS: Higher prenatal mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP) urinary concentrations were associated with increased hyperactivity scores in the overall sample (ß = 0.57, 95% CI = 0.17, 1.13) and in girls (ß = 0.54, 95% CI = 0.16, 1.08), overall behavioral problems in boys (ß = 0.58, 95% CI = 0.20, 1.15), and depression scores in boys (ß = 0.44, 95% CI = 0.06, 0.88). Higher prenatal monobenzyl phthalate (MBzP) concentrations were associated with reduced hyperactivity scores in girls (ß = -0.54, 95% CI = -1.08, -0.21). DISCUSSION: Our findings suggested that prenatal concentrations of phthalates and their replacements altered child neurodevelopment and those associations may be influenced sex.

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BACKGROUND: Prenatal phthalate exposures may affect processes that underlie offspring cardiometabolic health, but findings from studies examining these associations are conflicting. We examined associations between biomarkers of phthalate exposures during pregnancy with child lipid and adipokine levels. METHODS: Data were from 463 mother-child pairs in the PROGRESS cohort of Mexico City. We quantified 15 phthalate metabolites in 2nd and 3rd trimester maternal urine samples and created an average pregnancy measure using the geometric mean. We evaluated the 15 metabolites as nine biomarkers, including four metabolite molar sums. We measured fasting serum triglycerides, non-HDL cholesterol, leptin, and adiponectin in children at the six-year follow-up visit (mean = 6.8 years). We estimated associations using linear regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) and assessed effect modification by sex. RESULTS: In BKMR and WQS models, higher concentrations of the total mixture of phthalate biomarkers were associated with lower triglycerides (ß = -3.7% [-6.5, -0.78] per 1 unit increase in WQS biomarker index) and non-HDL cholesterol (ß = -2.0 [-3.7, -0.25] ng/ml per increase in WQS biomarker index). Associations between individual biomarkers and child outcomes were largely null. We observed some evidence of effect modification by child sex for mono-3-carboxypropyl phthalate (ß = 19.4% [1.26, 40.7] per doubling of phthalate) and monobenzyl phthalate (ß = -7.6% [-14.4, -0.23]) in girls for adiponectin. CONCLUSIONS: Individual prenatal phthalate biomarkers were not associated with child lipid or adipokine levels. Contrary to our hypothesis, the total phthalate mixture was associated with lower child triglycerides and non-HDL cholesterol.

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OBJECTIVE: To evaluate the associations of pregestational BMI, gestational weight gain (GWG) and breast-feeding at 1 month postpartum with four patterns of weight change during the first year after delivery: postpartum weight retention (PPWR), postpartum weight gain (PPWG), postpartum weight retention + gain (PPWR + WG) and return to pregestational weight. DESIGN: In this secondary analysis of a prospective study, we categorised postpartum weight change into four patterns using pregestational weight and weights at 1, 6 and 12 months postpartum. We evaluated their associations with pregestational BMI, GWG and breast-feeding using multinomial logistic regression. Results are presented as relative risk ratios (RRR) and 95 % CI. SETTING: Mexico City. PARTICIPANTS: Women participating in the Programming Research in Obesity, Growth, Environment and Social Stressors pregnancy cohort. RESULTS: Five hundred women were included (53 % of the cohort). Most women returned to their pregestational weight by 1 year postpartum (57 %); 8 % experienced PPWR, 14 % PPWG and 21 % PPWR + WG. Compared with normal weight, pregestational overweight (RRR 2·5, 95 % CI 1·3, 4·8) and obesity (RRR 2·2, 95 % CI 1·0, 4·7) were associated with a higher risk of PPWG. Exclusive breast-feeding, compared with no breast-feeding, was associated with a lower risk of PPWR (RRR 0·3, 95 % CI 0·1, 0·9). Excessive GWG, compared with adequate, was associated with a higher risk of PPWR (RRR 3·3, 95 % CI 1·6, 6·9) and PPWR + WG (RRR 2·4, 95 % CI 1·4, 4·2). CONCLUSIONS: Targeting women with pregestational overweight or obesity and excessive GWG, as well as promoting breast-feeding, may impact the pattern of weight change after delivery and long-term women's health.

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BACKGROUND: Exposure to particulate matter <2.5 µm in diameter (PM2.5) and environmental tobacco smoke (ETS) are associated with respiratory morbidity starting in utero. However, their potential synergistic effects have not been completely elucidated. Here, we examined the joint effects of prenatal and early life PM2.5 and prenatal ETS exposure on respiratory outcomes in children. MATERIAL AND METHODS: We studied 536 mother-child dyads in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study in Mexico City. Exposure to PM2.5 was estimated using residence in pregnancy and child's first year of life with a satellite-based spatio-temporal model. ETS exposure was assessed by caregiver's report of any smoker in the household during the second or third trimester. Outcomes included report of ever wheeze and wheeze in the past 12 months (current wheeze) assessed when children were 6-8 years old considered in separate models. Associations were modeled using distributed lag models (DLM) with daily PM2.5 averages for pregnancy and the first year of life, adjusting for child's sex, birth weight z-score, mother's age and education at enrollment, maternal asthma, season of conception and stratified by prenatal ETS exposure (yes/no). RESULTS: We identified a sensitive window from gestational week 14 through postnatal week 18 during which PM2.5 was associated with higher risk of ever wheeze at age 6-8 years. We also observed a critical window of PM2.5 exposure between postnatal weeks 6-39 and higher risk of current wheeze. We found significant associations between higher prenatal and early life PM2.5 exposure and higher cumulative risk ratios of ever wheeze (RR:3.76, 95%CI [1.41, 10.0] per 5 µg/m3) and current wheeze in the past year (RR:7.91, 95%CI [1.5, 41.6] per 5 µg/m3) only among children born to mothers exposed to ETS in pregnancy when compared to mothers who were not exposed. CONCLUSIONS: Exposure to prenatal ETS modified the association between prenatal and early life PM2.5 exposure and respiratory outcomes at age 6-8 years. It is important to consider concurrent chemical exposures to more comprehensively characterize children's environmental risk. Interventions aimed at decreasing passive smoking might mitigate the effects of ambient air pollution.

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BACKGROUND: Pregnancy is associated with deteriorations in maternal bone strength and heightened susceptibility to bone fractures. We aimed to investigate whether ambient particulate matter (PM)2·5 concentrations were associated with bone strength during pregnancy. METHODS: In this longitudinal cohort study, we analysed longitudinal data from women participating in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort in Mexico City, Mexico. Eligible women were aged 18 years or older, at less than 20 weeks' gestation at the time of recruitment, planning to stay in Mexico City for the next 3 years, without heart or kidney disease, did not use steroids or anti-epileptic drugs, were not daily consumers of alcohol, and had access to a telephone. Daily ambient PM2·5 concentrations were estimated from a spatio-temporal model that was based on the individual's address. Trabecular bone strength was measured using quantitative ultrasound from the radius of the middle finger and cortical bone strength from the proximal phalanx of the middle finger, during the second trimester, third trimester, and 1 and 6 months post partum. Bone strength T scores were modelled with PM2·5 concentrations using linear mixed models and distributed lag models. FINDINGS: Adjusting for multiple exposure windows, each 10 ug/m3 increase in PM2·5 exposure concentrations in the first trimester was associated with a 0·18 SD decrease (95% CI -0·35 to -0·01; p=0·033) in ultrasound speed-of-sound (SOS) T score of trabecular bone strength from the second trimester until 6 months post partum. Similarly, each 10 µg/m3 increase in third trimester PM2·5 exposure was associated with a 0·18 SD decrease (-0·36 to -0·01; p=0·044) in the SOS T score of trabecular bone strength from the third trimester until 6 months post partum. PM2·5 exposure in the first month post partum was associated with a 0·20 SD decline (-0·39 to -0·01; p=0·043) in cortical bone strength until 6 months post partum. INTERPRETATION: Ambient PM2·5 exposure during and after pregnancy was associated with diminished trabecular and cortical bone strength. Early pregnancy PM2·5 exposure was associated with a greater decline in bone strength later during pregnancy. Late pregnancy and early post-partum exposures adversely affected the post-partum bone strength recovery. Technological and policy solutions to reduce PM2·5 pollution could improve public health by reducing bone fracture risk. FUNDING: US National Institute of Environmental Health Sciences.

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BACKGROUND: Sedentary behavior is a worldwide public health concern. There is consistent and growing evidence linking sedentary behavior to mortality and morbidity. Early monitoring and assessment of environmental factors associated with sedentary behaviors at a young age are important initial steps for understanding children's sedentary time and identifying pertinent interventions. OBJECTIVE: This study examines the association between daily temperature (maximum, mean, minimum, and diurnal variation) and all-day sedentary time among 4-6 year old children in Mexico City (n = 559) from the year 2013 to 2015. METHODS: We developed a spatiotemporally resolved hybrid satellite-based land use regression temperature model and calculated percent daily sedentary time from aggregating 10-second epoch vertical counts captured by accelerometers that participants wore for one week. We modeled generalized additive models (GAMs), one for each temperature type as a covariate (maximum, mean, minimum, and diurnal variation). All GAMs included percent all-day sedentary time as the outcome and participant-level random intercepts to account for repeated measures of sedentary time. Our models were adjusted for demographic factors and environmental exposures. RESULTS: Daily maximum temperature, mean temperature, and diurnal variation have significant negative linear relationships with all-day sedentary time (p<0.01). There is no significant association between daily minimum temperature and all-day sedentary time. Children have on average 0.26% less daily sedentary time (approximately 2.2 minutes) for each 1°C increase in ambient maximum temperature (range 7.1-30.2°C), 0.27% less daily sedentary time (approximately 2.3 minutes) for each 1°C increase in ambient mean temperature (range 4.3-22.2°C), and 0.23% less daily sedentary time (approximately 2.0 minutes) for each 1°C increase in diurnal variation (range 3.0-21.6°C). CONCLUSIONS: These results are contrary to our hypothesis in which we expected a curvilinear relationship between temperature (maximum, mean, minimum, and diurnal variation) and sedentary time. Our findings suggest that temperature is an important environmental factor that influences children's sedentary behavior.

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BACKGROUND: Childhood exposure to air pollution has been linked with maladaptive cognitive development; however, less is known about the association between prenatal fine particulate matter (PM2.5) exposure and childhood behavior. OBJECTIVES: Our aim was to assess the association between prenatal PM2.5 exposure and behavioral development in 4-6 year old children residing in Mexico City. METHODS: We used data from 539 mother-child pairs enrolled in a prospective birth cohort in Mexico City. We estimated daily PM2.5 exposure using a 1 km2 satellite-based exposure model and averaged over each trimester of pregnancy. We assessed childhood behavior at 4-6 years of age using the parent-completed Behavioral Assessment Scale for Children (BASC-2) composite scores and subscales. We used linear regression models to estimate change in BASC-2 T-scores with trimester specific 5-µg/m3 increases in PM2.5. All models were mutually adjusted for PM2.5 exposures during the other trimesters, maternal factors including age, education, socioeconomic status, depression, and IQ, child's age at study visit, and season. We additionally assessed sex-specific effects by including an interaction term between PM2.5 and sex. RESULTS: Higher first trimester PM2.5 exposure was associated with reduced Adaptive Skills scores (ß: -1.45, 95% CI: -2.60, -0.30). Lower scores on the Adaptive Skills composite score and subscales indicate poorer functioning. For PM2.5 exposure during the first trimester, decrements were consistent across adaptive subscale scores including Adaptability (ß: -1.51, 95% CI: -2.72, -0.30), Social Skills (ß: -1.63, 95% CI: -2.90, -0.36), and Functional Communication (ß: -1.21, 95% CI: -2.21, -0.21). The association between 1st trimester PM2.5 and depression was stronger in males than females (ß for males: 1.52, 95% CI: -0.41, 3.45; ß for females: -0.13, 95% CI: -1.99, 1.72; p-int: 0.07). CONCLUSIONS: Exposure to PM2.5 during early pregnancy may be associated with impaired behavioral development in children, particularly for measures of adaptive skills. These results suggest that air pollution impacts behavioral domains as well as cognition, and that the timing of exposure may be critical.

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BACKGROUND: Studies have identified associations between air pollution and lipid levels in adults, suggesting a mechanism by which air pollution contributes to cardiovascular disease. However, little is known about the association between early life air pollution exposure and lipid levels in children. METHODS: Participants included 465 mother-child pairs from a prospective birth cohort in Mexico City. Daily particulate matter <2.5 µm in diameter (PM2.5) predictions were estimated using a satellite-based exposure model and averaged over trimesters, the entire pregnancy, and the first year of life. We assessed associations with several lipid measures at 4-6 years of age, including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Linear regression models were used to estimate change in lipid levels with each interquartile range increase in PM2.5. We additionally assessed if associations between PM2.5 and lipid levels varied across lipid quantiles using quantile regression. Models were adjusted for maternal education, body mass index, and age, child's age at study visit, prenatal environmental tobacco smoke, and season of conception. RESULTS: PM2.5 exposure during the third trimester was associated with increases in childhood total cholesterol, LDL-C, and non-HDL-C, and decreases in HDL-C and triglycerides. There was additionally an increasing trend in the effect estimate across higher quantiles of total cholesterol, LDL-C, and non-HDL-C during the third trimester and entire pregnancy period. There were no consistent associations for first year of life exposures. CONCLUSION: In this longitudinal birth cohort in Mexico City, associations between prenatal PM2.5 and childhood lipid (total cholesterol, LDL-C, non-HDL-C) levels were greater for children at higher lipid quantiles.

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Pregnancy is a contributor to the obesity epidemic in women, probably through postpartum weight retention (PPWR), weight gain (PPWG), or a combination of both (PPWR + WG). The contribution of these patterns of postpartum weight change to long-term maternal health remains understudied. In a secondary analysis of 361 women from the prospective cohort PROGRESS, we evaluated the associations between patterns of weight change one year after delivery and cardiometabolic risk factors at six years postpartum. Using principal component analysis, we grouped cardiometabolic risk factors into: (1) body mass index (BMI), waist circumference (WC), homeostatic model assessment of insulin resistance (HOMA-IR), high-density lipoprotein cholesterol (HDL-c), triglycerides (TG), and glucose; (2) systolic (SBP) and diastolic blood pressure (DBP); and (3) low-density lipoprotein cholesterol and total cholesterol. Using path analysis, we studied direct (patterns of weight change-outcomes) and indirect associations through BMI at six years postpartum. Around 60% of women returned to their pregestational weight (reference) by one year postpartum, 6.6% experienced PPWR, 13.9% PPWG, and 19.9% PPWR + WG. Women with PPWR + WG, vs. the reference, had higher BMI and WC at six years (2.30 kg/m2, 95% CI [1.67, 2.93]; 3.38 cm [1.14, 5.62]). This was also observed in women with PPWR (1.80 kg/m2 [0.80, 2.79]; 3.15 cm [-0.35, 6.65]) and PPWG (1.22 kg/m2 [0.53, 1.92]; 3.32 cm [0.85, 5.78]). PPWR + WG had a direct association with HOMA-IR (0.21 units [0.04, 0.39]). The three patterns of weight change, vs. the reference, had significant indirect associations with HOMA-IR, glucose, TG, HDL-c, SBP, and DBP through BMI at six years. In conclusion, women with PPWR + WG are at high-risk for obesity and insulin resistance. Interventions targeting women during pregnancy and the first year postpartum may have implications for their long-term risk of obesity and cardiovascular disease.

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Phthalates are associated with several adverse health outcomes, but few studies have evaluated phthalate exposures in Mexican populations, particularly pregnant women. Between 2007 and 2011, 948 pregnant women from Mexico City were recruited as part of the PROGRESS cohort. We quantified 17 metabolites of phthalates and phthalate alternatives in urine samples collected during the second and third trimesters and examined temporal trends of metabolite concentrations, within-person reproducibility, and relations of individual metabolites with sociodemographic, lifestyle, and occupational factors. Concentrations of mono-2-ethyl-5-carboxypentyl terephthalate, a metabolite of the alternative phthalate di-2-ethylhexyl terephthalate, increased monotonically from 2007 to 2010 (31% per year; 95% confidence interval = 23 and 39%). We observed moderate to high correlations among metabolites collected at the same visit, but there was high variability between second and third trimester phthalate metabolite concentrations (intraclass correlation coefficients = 0.17-0.35). In general, higher socioeconomic status was associated with higher phthalate concentrations. Some metabolites were associated with maternal age and education, but no consistent patterns were observed. Women working in the home and those who worked in administration had higher concentrations of several phthalate metabolites relative to students, professionals, and those in customer service. Biomonitoring efforts are warranted to investigate present and future exposure trends and patterns.

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