Residential food environment and dietary antioxidant consumption among pregnant women: Modifying effects of socioeconomic factors and ethnic identity.

BACKGROUND: Residential food environment influences dietary patterns, however the impact of individuals' perceived social identity on the antioxidant intake, an indicator of healthy dietary patterns, remains underexplored. OBJECTIVE: We conducted a cross-sectional analysis using data collected in a longitudinal cohort. In the study, we aim to investigate the interactions between the food environment and two indicators of social identity, specifically a subjective ladder measure of socioeconomic status (SES) and the Multigroup Ethnic Identity Measure (MEIM) score, in relation to dietary antioxidant intake (DAI) among n = 512 Boston and NYC-resident pregnant women. METHODS: The modified Retail Food Environment Index (mRFEI) was calculated using the Centers for Disease Control and Prevention's equation, with higher scores indicating a healthier food environment. DAI was estimated by summing standardized data from six micronutrients (magnesium, selenium, zinc, and vitamins A, C, and E) obtained through the Block98 Food Frequency Questionnaires administered during pregnancy, with higher scores indicating increased intake. The mRFEI and DAI were dichotomized based on a median split. Multivariable-adjusted logistic regressions were used to analyze associations, both with and without considering women's subjective SES or MEIM levels as effect modifiers. RESULTS: Women were racially/ethnically mixed (19.2 % White, 42.7 % Black, and 33.1 % Hispanic) with 32.2 % reporting more than high school education. In the main effect models, no significant association was observed between mRFEI and DAI. Women with higher MEIM scores exhibited higher DAI [Odds ratio (OR) =1.85, 95 % Confidence interval (CI) = 1.26-2.73]. Exploratory interaction models showed that subjective SES significantly modified the association (p-value for interaction = 0.03), women perceiving themselves to have a lower SES compared to their community (n = 45) exhibited a significantly positive association between mRFEI and DAI. CONCLUSION: These findings suggest that women perceiving their SES to be lower than their neighborhoods may benefit from better access to healthy food.

Ambient temperature exposure and rapid infant weight gain.

BACKGROUND: Childhood obesity is a major public health concern, and the global rate is rising. Rapid infant weight gain is a risk factor for later overweight. Studies have linked prenatal ambient temperature exposure to fetal growth, and preliminary evidence suggests postnatal exposure may be associated with infant weight gain. METHODS: Using a population-based historical cohort study including 1 100 576 infants born 2011-2019, we assessed the relationship between prenatal and one-month postnatal ambient temperature exposure and rapid infant weight gain. We used a hybrid spatiotemporal model to assess temperatures at the family's recorded residence at birth. Repeated weight measurements between birth and 15 months were used to model the outcome using the SuperImposition by Translation and Rotation (SITAR) method. We employed generalized linear models and distributed lag models to estimate the association between prenatal and postnatal exposure and rapid infant weight gain, defined as the upper tertile of the SITAR growth velocity. RESULTS: Overall, higher ambient temperatures were associated with rapid infant weight gain. The cumulative adjusted relative risk for the highest exposure quintile during pregnancy compared with the lowest quintile was 1.33 [95% confidence interval (CI): 1.25, 1.40], and the corresponding association for the first postnatal month was 1.19 (95% CI: 1.15, 1.23). Exposure to high ambient temperature during early and mid-pregnancy, as well as the first postnatal month, was associated with rapid weight gain, while during late pregnancy, exposure to low temperatures was associated with this outcome. CONCLUSIONS: Prenatal and postnatal ambient temperatures are associated with rapid infant weight gain.

Metabolism-Disrupting Chemical Mixtures during Pregnancy, Folic Acid Supplementation, and Liver Injury in Mother-Child Pairs.

Background and Aims: Scarce knowledge about the impact of metabolism-disrupting chemicals (MDCs) on liver injury limits opportunities for intervention. We evaluated pregnancy MDC-mixture associations with liver injury and effect modification by folic acid (FA) supplementation in mother-child pairs. Methods: We studied ∼200 mother-child pairs from the Mexican PROGRESS cohort, with measured 43 MDCs during pregnancy (estimated air pollutants, blood/urine metals or metalloids, urine high- and low-molecular-weight phthalate [HMWPs, LMWPs] and organophosphate-pesticide [OP] metabolites), and serum liver enzymes (ALT, AST) at ∼9 years post-parturition. We defined liver injury as elevated liver enzymes in children, and using established clinical scores for steatosis and fibrosis in mothers (i.e., AST:ALT, FLI, HSI, FIB-4). Bayesian Weighted Quantile Sum regression assessed MDC-mixture associations with liver injury outcomes. We further examined chemical-chemical interactions and effect modification by self-reported FA supplementation. Results: In children, many MDC-mixtures were associated with liver injury outcomes. Per quartile HMWP-mixture increase, ALT increased by 10.1% (95%CI: 1.67%, 19.4%) and AST by 5.27% (95% CI: 0.80%, 10.1%). LMWP-mixtures and air pollutant-mixtures were associated with higher AST and ALT, respectively. Air pollutant and non-essential metal/element associations with liver enzymes were attenuated by maternal cobalt blood concentrations ( p -interactions<0.05). In mothers, only the LMWP-mixture was associated with liver injury [OR=1.53 (95%CI: 1.01, 2.28) for HSI>36, and OR=1.62 (95%CI: 1.05, 2.49) for AST:ALT<1]. In mothers and children, most associations were attenuated (null) at FA supplementation≥600mcg/day ( p -interactions<0.05). Conclusions: Pregnancy MDC exposures may increase liver injury risk, particularly in children. These associations may be attenuated by higher FA supplementation and maternal cobalt levels.

Ambient air pollution and daily mortality in ten cities of India: a causal modelling study.

BACKGROUND: The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution. METHODS: We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 µg/m3. To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 µg/m3). FINDINGS: We observed that a 10 µg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 µg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines. INTERPRETATION: Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link. FUNDING: Swedish Research Council for Sustainable Development.

Beyond lung cancer: air pollution and bladder, breast and prostate cancer incidence.

BACKGROUND: The carcinogenicity of air pollution and its impact on the risk of lung cancer is well known; however, there are still knowledge gaps and mixed results for other sites of cancer. METHODS: The current study aimed to evaluate the associations between ambient air pollution [fine particulate matter (PM2.5) and nitrogen oxides (NOx)] and cancer incidence. Exposure assessment was based on historical addresses of >900 000 participants. Cancer incidence included primary cancer cases diagnosed from 2007 to 2015 (n = 30 979). Cox regression was used to evaluate the associations between ambient air pollution and cancer incidence [hazard ratio (HR), 95% CI]. RESULTS: In the single-pollutant models, an increase of one interquartile range (IQR) (2.11 µg/m3) of PM2.5 was associated with an increased risk of all cancer sites (HR = 1.51, 95% CI: 1.47-1.54), lung cancer (HR = 1.73, 95% CI: 1.60-1.87), bladder cancer (HR = 1.50, 95% CI: 1.37-1.65), breast cancer (HR = 1.50, 95% CI: 1.42-1.58) and prostate cancer (HR = 1.41, 95% CI: 1.31-1.52). In the single-pollutant and the co-pollutant models, the estimates for PM2.5 were stronger compared with NOx for all the investigated cancer sites. CONCLUSIONS: Our findings confirm the carcinogenicity of ambient air pollution on lung cancer and provide additional evidence for bladder, breast and prostate cancers. Further studies are needed to confirm our observation regarding prostate cancer. However, the need for more research should not be a barrier to implementing policies to limit the population's exposure to air pollution.

The use of time-dynamic patterns of temperature and flexible generalized models to clarify the relations between temperature and semen quality.

BACKGROUND: Sperm quality has decreased over the last decades worldwide. It is affected, among others, by season and heat. This study aimed to address the association between ambient temperature and sperm quality by assessing its shape using flexible multivariate models and identifying distinct time-dynamic patterns of temperature change based on unsupervised analysis. MATERIAL AND METHODS: A retrospective population-based study has been conducted, including all samples of males attending the Fertility and In-Vitro-Fertilization unit at a single medical center during 2016-2022. Flexible generalized models were fitted to characterize the relations between sperm quality and temperature while accounting for patients characteristics, and to identify temperature levels that correspond with the optimal sperm quality. This information was then used to estimate adjusted slope coefficients at specified time-windows. RESULTS: In total, 4555 sperm samples were provided by 3229 individuals. Sperm concentration, motility and progressive motility were higher by 8 %, 11 % and 16 %, respectively, during the spring versus the fall season. Furthermore, their quality during early spermatogenesis improved with temperature, until a certain optimum around 23 °C-24 °C. Increasing temperature at later developmental stages was associated with lower sperm concentration and higher motility. Sperm concentration and motility were highest following a period of moderate gradual warming. Motility was higher and sperm concentration was lower, following a period with heatwaves or summer. CONCLUSIONS: This study assessed temperature role in sperm production quality by considering both average and time-dynamic temperatures. It identified several temperature change patterns over time and stratified the analysis by them. The differences in the relations across stages of spermatogenesis were addressed. Several mechanisms may explain the associations found, including heat-induced apoptosis of the sperm cells, and destruction of sperm cells DNA integrity by over-production of reactive oxygen species. The gradual global warming necessitates exploration of individual response to outdoor temperature in relations to genetic predisposition, lifestyle, and other health characteristics.

Relative humidity, temperature, and hypertensive disorders of pregnancy: Findings from the Project Viva cohort.

BACKGROUND: Preeclampsia is a multi-system hypertensive disorder of pregnancy that is a leading cause of maternal and fetal morbidity and mortality. Prior studies disagree on the cause and even the presence of seasonal patterns in its incidence. Using unsuitable time windows for seasonal exposures can bias model results, potentially explaining these inconsistencies. OBJECTIVES: We aimed to investigate humidity and temperature as possible causes for seasonal trends in preeclampsia in Project Viva, a prebirth cohort in Boston, Massachusetts, considering only exposure windows that precede disease onset. METHODS: Using the Parameter-elevation Relationships on Independent Slopes Model (PRISM) Climate Dataset, we estimated daily residential temperature and relative humidity (RH) exposures during pregnancy. Our primary multinomial regression adjusted for person-level covariates and season. Secondary analyses included distributed lag models (DLMs) and adjusted for ambient air pollutants including fine particulates (PM2.5). We used Generalized Additive Mixed Models (GAMMs) for systolic blood pressure (SBP) trajectories across hypertensive disorder statuses to confirm exposure timing. RESULTS: While preeclampsia is typically diagnosed late in pregnancy, GAMM-fitted SBP trajectories for preeclamptic and non-preeclamptic women began to diverge at around 20 weeks' gestation, confirming the need to only consider early exposures. In the primary analysis with 1776 women, RH in the early second trimester, weeks 14-20, was associated with significantly higher odds of preeclampsia (OR per IQR increase: 1.81, 95% CI: 1.10, 2.97). The DLM corroborated this window, finding a positive association from weeks 12-20. There were no other significant associations between RH or temperature and preeclampsia or gestational hypertension in any other time period. DISCUSSION: The association between preeclampsia and RH in the early second trimester was robust to model choice, suggesting that RH may contribute to seasonal trends in preeclampsia incidence. Differences between these results and those of prior studies could be attributable to exposure timing differences.

A multi-resolution ensemble model of three decision-tree-based algorithms to predict daily NO2 concentration in France 2005-2022.

Understanding and managing the health effects of Nitrogen Dioxide (NO2) requires high resolution spatiotemporal exposure maps. Here, we developed a multi-stage multi-resolution ensemble model that predicts daily NO2 concentration across continental France from 2005 to 2022. Innovations of this work include the computation of daily predictions at a 200 m resolution in large urban areas and the use of a spatio-temporal blocking procedure to avoid data leakage and ensure fair performance estimation. Predictions were obtained after three cascading stages of modeling: (1) predicting NO2 total column density from Ozone Monitoring Instrument satellite; (2) predicting daily NO2 concentrations at a 1 km spatial resolution using a large set of potential predictors such as predictions obtained from stage 1, land-cover and road traffic data; and (3) predicting residuals from stage 2 models at a 200 m resolution in large urban areas. The latter two stages used a generalized additive model to ensemble predictions of three decision-tree algorithms (random forest, extreme gradient boosting and categorical boosting). Cross-validated performances of our ensemble models were overall very good, with a ten-fold cross-validated R2 for the 1 km model of 0.83, and of 0.69 for the 200 m model. All three basis learners participated in the ensemble predictions to various degrees depending on time and space. In sum, our multi-stage approach was able to predict daily NO2 concentrations with a relatively low error. Ensembling the predictions maximizes the chance of obtaining accurate values if one basis learner fails in a specific area or at a particular time, by relying on the other learners. To the best of our knowledge, this is the first study aiming to predict NO2 concentrations in France with such a high spatiotemporal resolution, large spatial extent, and long temporal coverage. Exposure estimates are available to investigate NO2 health effects in epidemiological studies.

Placental DNA methylation signatures of prenatal air pollution exposure and potential effects on birth outcomes: an analysis of three prospective cohorts.

BACKGROUND: Pregnancy air pollution exposure (PAPE) has been linked to a wide range of adverse birth and childhood outcomes, but there is a paucity of data on its influence on the placental epigenome, which can regulate the programming of physiological functions and affect child development. This study aimed to investigate the association between prenatal air pollutant exposure concentrations and changes in placental DNA methylation patterns, and to explore the potential windows of susceptibility and sex-specific alterations. METHODS: This multi-site study used three prospective population-based mother-child cohorts: EDEN, PELAGIE, and SEPAGES, originating from four French geographical regions (Nancy, Poitiers, Brittany, and Grenoble). Pregnant women were included between 2003 and 2006 for EDEN and PELAGIE, and between 2014 and 2017 for SEPAGES. The main eligibility criteria were: being older than 18 years, having a singleton pregnancy, and living and planning to deliver in one of the maternity clinics in one of the study areas. A total of 1539 mother-child pairs were analysed, measuring placental DNA methylation using Illumina BeadChips. We used validated spatiotemporally resolved models to estimate PM2·5, PM10, and NO2 exposure over each trimester of pregnancy at the maternal residential address. We conducted a pooled adjusted epigenome-wide association study to identify differentially methylated 5'-C-phosphate-G-3' (CpG) sites and regions (assessed using the Infinium HumanMethylationEPIC BeadChip array, n=871), including sex-specific and sex-linked alterations, and independently validated our results (assessed using the Infinium HumanMethylation450 BeadChip array, n=668). FINDINGS: We identified four CpGs and 28 regions associated with PAPE in the total population, 469 CpGs and 87 regions in male infants, and 150 CpGs and 66 regions in female infants. We validated 35% of the CpGs available. More than 30% of the identified CpGs were related to one (or more) birth outcome and most significant alterations were enriched for neural development, immunity, and metabolism related genes. The 28 regions identified for both sexes overlapped with imprinted genes (four genes), and were associated with neurodevelopment (nine genes), immune system (seven genes), and metabolism (five genes). Most associations were observed for the third trimester for female infants (134 of 150 CpGs), and throughout pregnancy (281 of 469 CpGs) and the first trimester (237 of 469 CpGs) for male infants. INTERPRETATION: These findings highlight the molecular pathways through which PAPE might affect child health in a widespread and sex-specific manner, identifying the genes involved in the major physiological functions of a developing child. Further studies are needed to elucidate whether these epigenetic changes persist and affect health later in life. FUNDING: French Agency for National Research, Fondation pour la Recherche Médicale, Fondation de France, and the Plan Cancer.

Green Space and Internalizing or Externalizing Symptoms Among Children.

Importance: Evidence suggests that living near green space supports mental health, but studies examining the association of green space with early mental health symptoms among children are rare. Objective: To evaluate the association between residential green space and early internalizing (eg, anxiety and depression) and externalizing (eg, aggression and rule-breaking) symptoms. Design, Setting, and Participants: Data for this cohort study were drawn from the Environmental Influences on Child Health Outcomes cohort; analysis was conducted from July to October 2023. Children born between 2007 and 2013 with outcome data in early (aged 2-5 years) and/or middle (aged 6-11 years) childhood who resided in 41 states across the US, drawing from clinic, hospital, and community-based cohorts, were included. Cohort sites were eligible if they recruited general population participants and if at least 30 children had outcome and residential address data to measure green space exposure. Nine cohorts with 13 sites met these criteria. Children diagnosed with autism or developmental delay were excluded, and 1 child per family was included. Exposures: Green space exposure was measured using a biannual (ie, summer and winter) Normalized Difference Vegetation Index, a satellite image-based indicator of vegetation density assigned to monthly residential history from birth to outcome assessment. Main Outcome and Measures: Child internalizing and externalizing symptoms were assessed using the Child Behavior Checklist for Ages 1½ to 5 or 6 to 18. The association between green space and internalizing and externalizing symptoms was modeled with multivariable linear regression using generalized estimating equations, adjusting for birthing parent educational level, age at delivery, child sex, prematurity, and neighborhood socioeconomic vulnerability. Models were estimated separately for early and middle childhood samples. Results: Among 2103 children included, 1061 (50.5%) were male; 606 (29.1%) identified as Black, 1094 (52.5%) as White, 248 (11.9%) as multiple races, and 137 (6.6%) as other races. Outcomes were assessed at mean (SD) ages of 4.2 (0.6) years in 1469 children aged 2 to 5 years and 7.8 (1.6) years in 1173 children aged 6 to 11 years. Greater green space exposure was associated with fewer early childhood internalizing symptoms in fully adjusted models (b = -1.29; 95% CI, -1.62 to -0.97). No associations were observed between residential green space and internalizing or externalizing symptoms in middle childhood. Conclusions and Relevance: In this study of residential green space and children's mental health, the association of green space with fewer internalizing symptoms was observed only in early childhood, suggesting a sensitive period for nature exposure. Policies protecting and promoting access to green space may help alleviate early mental health risk.

Modelling Europe-wide fine resolution daily ambient temperature for 2003-2020 using machine learning.

To improve our understanding of the health impacts of high and low temperatures, epidemiological studies require spatiotemporally resolved ambient temperature (Ta) surfaces. Exposure assessment over various European cities for multi-cohort studies requires high resolution and harmonized exposures over larger spatiotemporal extents. Our aim was to develop daily mean, minimum and maximum ambient temperature surfaces with a 1 × 1 km resolution for Europe for the 2003-2020 period. We used a two-stage random forest modelling approach. Random forest was used to (1) impute missing satellite derived Land Surface Temperature (LST) using vegetation and weather variables and to (2) use the gap-filled LST together with land use and meteorological variables to model spatial and temporal variation in Ta measured at weather stations. To assess performance, we validated these models using random and block validation. In addition to global performance, and to assess model stability, we reported model performance at a higher granularity (local). Globally, our models explained on average more than 81 % and 93 % of the variability in the block validation sets for LST and Ta respectively. Average RMSE was 1.3, 1.9 and 1.7 °C for mean, min and max ambient temperature respectively, indicating a generally good performance. For Ta models, local performance was stable across most of the spatiotemporal extent, but showed lower performance in areas with low observation density. Overall, model stability and performance were lower when using block validation compared to random validation. The presented models will facilitate harmonized high-resolution exposure assignment for multi-cohort studies at a European scale.

Ambient PM2.5 and specific sources increase inflammatory cytokine responses to stimulators and reduce sensitivity to inhibitors.

Ambient exposure to fine particulate matter (PM2.5) is associated with increased morbidity and mortality from multiple diseases. Recent observations suggest the hypothesis that trained immunity contributes to these risks, by demonstrating that ambient PM2.5 sensitizes innate immune cells to mount larger inflammatory response to subsequent bacterial stimuli. However, little is known about how general and durable this sensitization phenomenon is, and whether specific sources of PM2.5 are responsible. Here we consider these issues in a longitudinal study of children. The sample consisted of 277 children (mean age 13.92 years; 63.8% female; 38.4% Black; 32.2% Latinx) who completed baseline visits and were re-assessed two years later. Fasting whole blood was ex vivo incubated with 4 stimulating agents reflecting microbial and sterile triggers of inflammation, and with 2 inhibitory agents, followed by assays for IL-1ß, IL-6, IL-8, and TNF-α. Blood also was assayed for 6 circulating biomarkers of low-grade inflammation: C-reactive protein, interleukin-6, -8, and -10, tumor necrosis factor-α, and soluble urokinase-type plasminogen activator receptor. Using machine learning, levels of 15 p.m.2.5 constituents were estimated for a 50 m grid around children's homes. Models were adjusted for age, sex, race, pubertal status, and household income. In cross-sectional analyses, higher neighborhood PM2.5 was associated with larger cytokine responses to the four stimulating agents. These associations were strongest for constituents released by motor vehicles and soil/crustal dust. In longitudinal analyses, residential PM2.5 was associated with declining sensitivity to inhibitory agents; this pattern was strongest for constituents from fuel/biomass combustion and motor vehicles. By contrast, PM2.5 constituents were not associated with the circulating biomarkers of low-grade inflammation. Overall, these findings suggest the possibility of a trained immunity scenario, where PM2.5 heightens inflammatory cytokine responses to multiple stimulators, and dampens sensitivity to inhibitors which counter-regulate these responses.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 µg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 µg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 µg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 µg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Sensitive development windows of prenatal air pollution and cognitive functioning in preschool age Mexican children.

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.

Association between prenatal and childhood PM2.5 exposure and preadolescent anxiety and depressive symptoms.

Background: Fine particulate matter (PM2.5) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise. Methods: We examined the association between early-life PM2.5 exposure and symptoms of anxiety and depression in a cohort of 8-11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children's Manifest Anxiety Scale and Children's Depression Inventory. Daily PM2.5 was estimated using a satellite-based exposure model and averaged over several early and recent exposure windows. Linear and logistic regression models were used to estimate the change in symptoms with each 5-µg/m3 increase in PM2.5. Models were adjusted for child's age, child's sex, maternal age, maternal socioeconomic status, season of conception, and temperature. Results: Average anxiety and depressive symptom T-scores were 51.0 (range 33-73) and 53.4 (range 44-90), respectively. We observed consistent findings for exposures around the fourth year of life, as this was present for both continuous and dichotomized anxiety symptoms, in both independent exposure models and distributed lag modeling approaches. This window was also observed for elevated depressive symptoms. An additional consistent finding was for PM2.5 exposure during early pregnancy in relation to both clinically elevated anxiety and depressive symptoms, this was seen in both traditional and distributed lag modeling approaches. Conclusion: Both early life and recent PM2.5 exposure were associated with higher mental health symptoms in the child highlighting the role of PM2.5 in the etiology of these conditions.

Individual and joint effects of prenatal PM2.5 and maternal stress on child temperament.

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.

Impact of heatwaves on all-cause mortality in India: A comprehensive multi-city study.

BACKGROUND: Heatwaves are expected to increase with climate change, posing a significant threat to population health. In India, with the world's largest population, heatwaves occur annually but have not been comprehensively studied. Accordingly, we evaluated the association between heatwaves and all-cause mortality and quantifying the attributable mortality fraction in India. METHODS: We obtained all-cause mortality counts for ten cities in India (2008-2019) and estimated daily mean temperatures from satellite data. Our main extreme heatwave was defined as two-consecutive days with an intensity above the 97th annual percentile. We estimated city-specific heatwave associations through generalised additive Poisson regression models, and meta-analysed the associations. We reported effects as the percentage change in daily mortality, with 95% confidence intervals (CI), comparing heatwave vs non-heatwave days. We further evaluated heatwaves using different percentiles (95th, 97th, 99th) for one, two, three and five-consecutive days. We also evaluated the influence of heatwave duration, intensity and timing in the summer season on heatwave mortality, and estimated the number of heatwave-related deaths. FINDINGS: Among âˆ¼ 3.6 million deaths, we observed that temperatures above 97th percentile for 2-consecutive days was associated with a 14.7 % (95 %CI, 10.3; 19.3) increase in daily mortality. Alternative heatwave definitions with higher percentiles and longer duration resulted in stronger relative risks. Furthermore, we observed stronger associations between heatwaves and mortality with higher heatwave intensity. We estimated that around 1116 deaths annually (95 %CI, 861; 1361) were attributed to heatwaves. Shorter and less intense definitions of heatwaves resulted in a higher estimated burden of heatwave-related deaths. CONCLUSIONS: We found strong evidence of heatwave impacts on daily mortality. Longer and more intense heatwaves were linked to an increased mortality risk, however, resulted in a lower burden of heatwave-related deaths. Both definitions and the burden associated with each heatwave definition should be incorporated into planning and decision-making processes for policymakers.

Coarse Particulate Matter and Markers of Inflammation and Coagulation in the Multi-Ethnic Study of Atherosclerosis (MESA) Population: A Repeat Measures Analysis.

BACKGROUND: In contrast to fine particles, less is known of the inflammatory and coagulation impacts of coarse particulate matter (PM10-2.5, particulate matter with aerodynamic diameter ≤10µm and>2.5µm). Toxicological research suggests that these pathways might be important processes by which PM10-2.5 impacts health, but there are relatively few epidemiological studies due to a lack of a national PM10-2.5 monitoring network. OBJECTIVES: We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average PM10-2.5 concentrations with markers of inflammation and coagulation. METHODS: We leveraged data from 7,071 Multi-Ethnic Study of Atherosclerosis and ancillary study participants 45-84 y of age who had repeated plasma measures of inflammatory and coagulation biomarkers. We estimated PM10-2.5 at participant addresses 1 y and 1 month before each of up to four exams (2000-2012) using spatiotemporal models that incorporated satellite, regulatory monitoring, and local geographic data and accounted for spatial correlation. We used random effects models to estimate associations with interleukin-6 (IL-6), C-reactive protein (CRP), fibrinogen, and D-dimer, controlling for potential confounders. RESULTS: Increases in PM10-2.5 were not associated with greater levels of inflammation or coagulation. A 10-µg/m3 increase in annual average PM10-2.5 was associated with a 2.5% decrease in CRP [95% confidence interval (CI): -5.5, 0.6]. We saw no association between annual average PM10-2.5 and the other markers (IL-6: -0.7%, 95% CI: -2.6, 1.2; fibrinogen: -0.3%, 95% CI: -0.9, 0.3; D-dimer: -0.2%, 95% CI: -2.6, 2.4). Associations consistently showed that a 10-µg/m3 increase in 1-month average PM10-2.5 was associated with reduced inflammation and coagulation, though none were distinguishable from no association (IL-6: -1.2%, 95% CI: -3.0 , 0.5; CRP: -2.5%, 95% CI: -5.3, 0.4; fibrinogen: -0.4%, 95% CI: -1.0, 0.1; D-dimer: -2.0%, 95% CI: -4.3, 0.3). DISCUSSION: We found no evidence that PM10-2.5 is associated with higher inflammation or coagulation levels. More research is needed to determine whether the inflammation and coagulation pathways are as important in explaining observed PM10-2.5 health impacts in humans as they have been shown to be in toxicology studies or whether PM10-2.5 might impact human health through alternative biological mechanisms. https://doi.org/10.1289/EHP12972.

Environmental and social inequities in continental France: an analysis of exposure to heat, air pollution, and lack of vegetation.

BACKGROUND: Cumulative environmental exposures and social deprivation increase health vulnerability and limit the capacity of populations to adapt to climate change. OBJECTIVE: Our study aimed at providing a fine-scale characterization of exposure to heat, air pollution, and lack of vegetation in continental France between 2000 and 2018, describing spatiotemporal trends and environmental hotspots (i.e., areas that cumulate the highest levels of overexposure), and exploring any associations with social deprivation. METHODS: The European (EDI) and French (FDep) social deprivation indices, the normalized difference vegetation index, daily ambient temperatures, particulate matter (PM2.5 and PM10), nitrogen dioxide, and ozone (O3) concentrations were estimated for 48,185 French census districts. Reference values were chosen to characterize (over-)exposure. Hotspots were defined as the areas cumulating the highest overexposure to temperature, air pollution, and lack of vegetation. Associations between heat overexposure or hotspots and social deprivation were assessed using logistic regressions. RESULTS: Overexposure to heat was higher in 2015-2018 compared with 2000-2014. Exposure to all air pollutants except for O3 decreased during the study period. In 2018, more than 79% of the urban census districts exceeded the 2021 WHO air quality guidelines. The evolution of vegetation density between 2000 and 2018 was heterogeneous across continental France. In urban areas, the most deprived census districts were at a higher risk of being hotspots (odds ratio (OR): 10.86, 95% CI: 9.87-11.98 using EDI and OR: 1.07, 95% CI: 1.04-1.11 using FDep). IMPACT STATEMENT: We studied cumulative environmental exposures and social deprivation in French census districts. The 2015-2018 period showed the highest overexposure to heat between 2000 and 2018. In 2018, the air quality did not meet the 2021 WHO guidelines in most census districts and 8.6 million people lived in environmental hotspots. Highly socially deprived urban areas had a higher risk of being in a hotspot. This study proposes for the first time, a methodology to identify hotspots of exposure to heat, air pollution, and lack of vegetation and their associations with social deprivation at a national level.

Prenatal exposure to air pollution and BWGA Z-score: Modifying effects of placenta leukocyte telomere length and infant sex.

BACKGROUND: Air pollutants, such as fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3), have been associated with adverse birth outcomes, including low birth weight, often exhibiting sex-specific effects. However, the modifying effect of placental telomere length (TL), reflecting cumulative lifetime oxidative stress in mothers, remains unexplored. METHOD: Using data from a Northeastern U.S. birth cohort (n = 306), we employed linear regression and weighted quantile sum models to assess trimester-average air pollution exposures and birth weight for gestational age (BWGA) z-scores. Placental TL, categorized by median split, was considered as an effect modifier. Interactions among air pollutants, placental TL, infant sex, and BWGA z-score were evaluated. RESULTS: Without placental TL as a modifier, only 1st trimester O3 was significantly associated with BWGA z-scores (coefficient: 0.33, 95% CI: 0.03, 0.63). In models considering TL interactions, a significant modifying effect was observed between 3rd trimester NO2 and BWGA z-scores (interaction p-value = 0.02). Specifically, a one interquartile range (1-IQR) increase in 3rd trimester NO2 was linked to a 0.28 (95% CI: 0.06, 0.52) change in BWGA z-score among shorter placental TL group, with no significant association among longer TL group. Among male infants, there were significant associations between 3rd trimester PM2.5 exposure and BWGA z-scores in the longer TL group (coefficient: -0.34, 95% CI: -0.61, -0.02), and between 1st trimester O3 exposure and BWGA z-scores among males in the shorter TL group (coefficient: 0.59, 95% CI: 0.06, 1.08). For females, only a negative association in 2nd trimester mixture model was observed within the longer TL group (coefficient: -0.10, 95% CI: -0.21, -0.01). CONCLUSION: These findings highlight the need to consider the complex interactions among prenatal air pollutant exposures, placental TL, and fetal sex to better elucidate those at greatest risk for adverse birth outcomes.