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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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Prenatal fine particulate matter (PM2.5) and maternal psychological functioning have been associated with child cognitive outcomes, though their independent and joint impacts on earlier behavioral outcomes remains less studied. We used data from 382 mother-child pairs from a prospective birth cohort in Mexico City. Temperament was measured at 24 months using the Carey Toddler Temperament Scale (TTS). Exploratory factor analysis (EFA) was used to update the factor structure of the TTS. During pregnancy, mothers completed the Crisis in Family Systems-Revised, Edinburgh Depression Scale, pregnancy-specific anxiety scale, and the Perceived Stress Scale. Pregnancy PM2.5 was assessed using estimates from a satellite-based exposure model. We assessed the association between prenatal maternal stress and PM2.5 on temperament, in both independent and joint models. Quantile g-computation was used to estimate the joint associations. Models were adjusted for maternal age, SES, education, child sex, and child age. In EFA, we identified three temperament factors related to effortful control, extraversion, and negative affect. Our main results showed that higher levels of PM2.5 and several of the maternal psychological functioning measures were related to both effortful control and negative affect in the child, both individually and as a mixture. For instance, a one quartile increase in the prenatal mixture was associated with higher negative affect scores in the child (0.34, 95% CI: 0.16, 0.53). We observed modification of these associations by maternal SES, with associations seen only among lower SES participants for both effortful control (-0.45, 95% CI: -0.70, -0.20) and negative affect outcomes (0.60, 95% CI: 0.35, 0.85). Prenatal PM2.5 and maternal psychological functioning measures were associated with toddler temperament outcomes, providing evidence for impacts of chemical and non-chemical stressors on early child health.

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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: Both parental and neighbourhood socio-economic status (SES) are linked to poorer health independently of personal SES measures, but the biological mechanisms are unclear. Our objective was to examine these influences via epigenetic age acceleration (EAA)-the discrepancy between chronological and epigenetic ages. METHODS: We examined three USA-based [Coronary Artery Risk Disease in Adults (CARDIA) study, Fragile Families and Child Wellbeing Study (FFCWS) and Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS)] and one Mexico-based (Project Viva) cohort. DNA methylation was measured using Illumina arrays, personal/parental SES by questionnaire and neighbourhood disadvantage from geocoded address. In CARDIA, we examined the most strongly associated personal, parental and neighbourhood SES measures with EAA (Hannum's method) at study years 15 and 20 separately and combined using a generalized estimating equation (GEE) and compared with other EAA measures (Horvath's EAA, PhenoAge and GrimAge calculators, and DunedinPoAm). RESULTS: EAA was associated with paternal education in CARDIA [GEEs: ßsome college = -1.01 years (-1.91, -0.11) and ß

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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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Exposure to PM2.5 has been associated with the prevalence of obesity. In the Greater Mexico City Area (GMCA), both are ranked among the highest in the world. Our aim was to analyze this association in children, adolescents, and adults in the GMCA. We used data from the 2006 and 2012 Mexican National Surveys of Health and Nutrition (ENSANUT). Participants' past-year exposure to ambient PM2.5 was assessed using land use terms and satellite-derived aerosol optical depth estimates; weight and height were measured. We used survey-adjusted logistic regression models to estimate the odds ratios (ORs) of obesity (vs. normal-overweight) for every 10 µg/m3 increase in annual PM2.5 exposure for children, adolescents, and adults. Using a meta-analysis approach, we estimated the overall odds of obesity. We analyzed data representing 19.3 million and 20.9 million GMCA individuals from ENSANUT 2006 and 2012, respectively. The overall pooled estimate between PM2.5 exposure and obesity was OR = 1.96 (95% CI: 1.21, 3.18). For adolescents, a 10 µg/m3 increase in PM2.5 was associated with an OR of 3.53 (95% CI: 1.45, 8.58) and 3.79 (95% CI: 1.40, 10.24) in 2006 and 2012, respectively. More studies such as this are recommended in Latin American cities with similar air pollution and obesity conditions.

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PURPOSE: Increasingly epidemiological evidence supports that environmental factors are associated with breast cancer (BC) outcomes after a BC diagnosis. Although evidence suggests that air pollution exposure is associated with higher mortality in women with BC, studies investigating potential mechanisms have been lacking. METHODS: We evaluated women with BC (N = 151) attended at the National Cancer Institute-Mexico from 2012 to 2015. We calculated 1-year average exposures to particulate matter < 2.5 µm (PM2.5) at home address before diagnosis. We used linear and logistic regression models to determine the associations between PM2.5 exposure and BC aggressiveness (tumor size, molecular phenotype). RESULTS: Average annual PM2.5 exposure of this population was 23.0 µg/m3 [standard deviation (SD)]: 1.90 µg/m3]. PM2.5 levels were positively correlated with tumor size at diagnosis (r = 0.22; p = 0.007). Multivariable linear models had a similar inference [risk ratio (RR): 1.32; 95% confidence interval (95% CI): 1.04, 1.674]. We did not observe differences in this association by age or menopause status. Further, women with triple-negative BC (TNBC) had significantly higher PM2.5 levels compared with other phenotypes (p = 0.015). Multivariable-adjusted logistic regression models assessing the association between PM2.5 and tumor size had a similar inference (RR 1.41; 95% CI 1.05, 1.89) overall for all ages and also for women who were ≤ 50 years old at diagnosis (RR 1.63; 95% CI 1.036, 2.57). CONCLUSIONS: Our findings suggest a significant association between long-term PM2.5 exposure and BC aggressiveness based on tumor size and phenotype, as well as a worse outcome.

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BACKGROUND: Recent studies have reported that air pollution exposure may have neurotoxic properties. OBJECTIVE: To examine longitudinal associations between prenatal particles less than 2.5 µm in diameter (PM2.5) exposure and neurodevelopment during the first two years of children's life. METHODS: Analysis was conducted in PROGRESS, a longitudinal birth cohort between 2007 and 2013 in Mexico City. We used satellite data to predict daily PM2.5 concentrations at high spatial resolution. Multivariate mixed-effect regression models were adjusted to examine cognitive, language and motor scores in children up to 24 months of age (n = 740) and each trimester-specific and whole pregnancy exposure to PM2.5. RESULTS: Models adjusted by child sex, gestational age, birth weight, smoking and mother's IQ, showed that each increase of 1 µg/m3 of PM2.5 was associated with a decreased language function of -0.38 points (95% CI: -0.77, -0.01). PM2.5 exposure at third trimester of pregnancy contributed most to the observed association. CONCLUSION: Our findings suggest that language development up to 24 months of age may be particularly sensitive to PM2.5 exposure during pregnancy.

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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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RESUMO

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.

Assuntos