The Association of Air Pollution Exposure With Glucose and Lipid Levels: The Role of an Extreme Air Pollution Event Alongside 2 Decades of Moderate Exposure.

Extreme air pollution events and moderate exposure to fine particulate matter (PM2.5) are associated with increased cardiometabolic risk. The World Trade Center (WTC) Health Program general responder cohort includes responders to the WTC disaster. We investigated whether their exposure to this extreme air pollution event (2001) was associated with long-term metabolic outcomes, independently from the associations of intermediate-term PM2.5 exposure later in life (2004-2019). We included 22,447 cohort members with cholesterol (n = 96,155) and glucose (n = 81,599) laboratory results. Self-reported WTC exposure was derived from a questionnaire. PM2.5 exposure was derived from a satellite-based model. We observed an increase of 0.78 mg/dL (95% confidence interval (CI): 0.30, 1.26) in glucose and 0.67 mg/dL (95% CI: 1.00, 2.35) in cholesterol levels associated with an interquartile range increase in PM2.5 averaged 6 months before the study visit. Higher WTC-exposure categories were also associated with higher cholesterol (0.99 mg/dL, 95% CI: 0.30, 1.67, for intermediate exposure) and glucose (0.82 mg/dL, 95% CI: 0.22, 1.43, for high exposure) levels. Most associations were larger among people with diabetes. Extreme air pollution events and intermediate PM2.5 exposure have independent metabolic consequences. These exposures contributed to higher glucose and lipids levels among WTC responders, which may be translated into increased cardiovascular risk.

Impact of exposure to air pollution on cervicovaginal microbial communities.

PURPOSE: Vaginal microbial communities can be dominated by anaerobic (community state type IV, CST IV) or Lactobacillus (other CSTs) species. CST IV is a risk factor for spontaneous preterm birth (sPTB) and is more common among Black than White populations. In the US, average air pollution exposures are higher among Black compared to White people and exert systemic health effects. We sought to (1) quantify associations of air pollution, specifically particulate matter <2.5 µm in diameter (PM2.5), with CST IV and (2) explore the extent to which racial disparities in PM2.5 exposure might explain racial differences in the prevalence of CST IV. DESIGN: Methods: We performed a secondary analysis of 566 participants of the Motherhood & Microbiome study. PM2.5 exposures were derived from a machine learning model integrating NASA satellite and EPA ground monitor data. Previously, cervicovaginal swabs from 15 to 20 weeks' gestation were analyzed using 16 S rRNA sequencing and hierarchical clustering assigned CSTs. Multivariable logistic regression models calculated adjusted odds ratios of CST IV (vs. other CSTs) per interquartile range (IQR) increment of PM2.5. Race-stratified and mediation analyses were performed. RESULTS: Higher PM2.5 exposure was associated with CST IV (aOR 1.39, 95% CI 1.02-1.91). Further adjustment for race/ethnicity attenuated the association (aOR 1.34, 95% CI: 0.97-1.83). Black participants (vs. White) had higher median PM2.5 exposure (10.6 vs. 9.6 µg/m3, P < 0.001) and higher prevalence of CST IV (47% vs. 11%, P < 0.001). Mediation analysis revealed that higher PM2.5 exposure may explain 3.9% (P = 0.038) and 3.3% (P = 0.15) of the Black-White disparity in CST IV in unadjusted and adjusted models, respectively. CONCLUSION: PM2.5 was associated with CST IV, a risk factor for sPTB. Additionally, PM2.5 exposure may partially explain racial differences in the prevalence of CST IV. Further research is warranted to discover how environmental exposures affect microbial composition and perpetuate racial health disparities.

Short-term exposure to PM2.5 and 1.5 million deaths: a time-stratified case-crossover analysis in the Mexico City Metropolitan Area.

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.

Ambient PM2.5 exposure and salivary cortisol output during pregnancy in a multi-ethnic urban sample.

OBJECTIVES: Evidence from murine research supports that fine particulate matter (PM2.5) may stimulate the hypothalamic-pituitary-adrenal axis, leading to elevated circulating glucocorticoid levels. Epidemiologic research examining parallel associations document similar associations. We examined these associations among a diverse sample of pregnant individuals exposed to lower levels of ambient PM2.5. MATERIALS AND METHODS: Participants included pregnant individuals enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) pre-birth cohort. Daily residential PM2.5 exposure was estimated using a satellite-based spatial-temporal hybrid model. Maternal 3rd trimester salivary cortisol levels were used to calculate several features of the diurnal cortisol rhythm. We used multivariable linear regression to examine PM2.5 during the pre-conception period and during each trimester in relation to cortisol awakening rise (CAR), slope, and area under the curve relative to ground (AUCG). RESULTS AND DISCUSSION: The average PM2.5 exposure level across pregnancy was 8.13 µg/m3. PM2.5 in each exposure period was positively associated with AUCG, a measure of total cortisol output across the day. We also observed an inverse association between PM2.5 in the 3rd trimester and diurnal slope, indicating a steeper decline in cortisol throughout the day with increasing exposure. We did not detect strong associations between PM2.5 and slope for the other exposure periods or between PM2.5 and CAR for any exposure period. CONCLUSIONS: In this sample, PM2.5 exposure across the preconception and pregnancy periods was associated with increased cortisol output, even at levels below the U.S. National Ambient Air Quality Annual Standard for PM2.5 of 12.0 µg/m3.

Can weather help explain 'why now?': The potential role of hourly temperature as a stroke trigger.

BACKGROUND: While evidence suggests that daily ambient temperature exposure influences stroke risk, little is known about the potential triggering role of ultra short-term temperature. METHODS: We examined the association between hourly temperature and ischemic and hemorrhagic stroke, separately, and identified any relevant lags of exposure among adult New York State residents from 2000 to 2015. Cases were identified via ICD-9 codes from the New York Department of Health Statewide Planning and Reearch Cooperative System. We estimated ambient temperature up to 36 h prior to estimated stroke onset based on patient residential ZIP Code. We applied a time-stratified case-crossover study design; control periods were matched to case periods by year, month, day of week, and hour of day. Additionally, we assessed effect modification by leading stroke risk factors hypertension and atrial fibrillation. RESULTS: We observed 578,181 ischemic and 164,755 hemorrhagic strokes. Among ischemic and hemorrhagic strokes respectively, the mean (standard deviation; SD) patient age was 71.8 (14.6) and 66.8 (17.4) years, with 55% and 49% female. Temperature ranged from -29.5 °C to 39.2 °C, with mean (SD) 10.9 °C (10.3 °C). We found linear relationships for both stroke types. Higher temperature was associated with ischemic stroke over the 7 h following exposure; a 10 °C increase over 7 h was associated with 5.1% (95% Confidence Interval [CI]: 3.8, 6.4%) increase in hourly stroke rate. In contrast, temperature was negatively associated with hemorrhagic stroke over 5 h, with a 5-h cumulative association of -6.2% (95% CI: 8.6, -3.7%). We observed suggestive evidence of a larger association with hemorrhagic stroke among patients with hypertension and a smaller association with ischemic stroke among those with atrial fibrillation. CONCLUSION: Hourly temperature was positively associated with ischemic stroke and negatively associated with hemorrhagic stroke. Our results suggest that ultra short-term weather influences stroke risk and hypertension may confer vulnerability.

Street-view greenspace exposure and objective sleep characteristics among children.

Greenspace may benefit sleep by enhancing physical activity, reducing stress or air pollution exposure. Studies on greenspace and children's sleep are limited, and most use satellite-derived measures that do not capture ground-level exposures that may be important for sleep. We examined associations of street view imagery (SVI)-based greenspace with sleep in Project Viva, a Massachusetts pre-birth cohort. We used deep learning algorithms to derive novel metrics of greenspace (e.g., %trees, %grass) from SVI within 250m of participant residential addresses during 2007-2010 (mid-childhood, mean age 7.9 years) and 2012-2016 (early adolescence, 13.2y) (N = 533). In early adolescence, participants completed >5 days of wrist actigraphy. Sleep duration, efficiency, and time awake after sleep onset (WASO) were derived from actigraph data. We used linear regression to examine cross-sectional and prospective associations of mid-childhood and early adolescence greenspace exposure with early adolescence sleep, adjusting for confounders. We compared associations with satellite-based greenspace (Normalized Difference Vegetation Index, NDVI). In unadjusted models, mid-childhood SVI-based total greenspace and %trees (per interquartile range) were associated with longer sleep duration at early adolescence (9.4 min/day; 95%CI:3.2,15.7; 8.1; 95%CI:1.7,14.6 respectively). However, in fully adjusted models, only the association between %grass at mid-childhood and WASO was observed (4.1; 95%CI:0.2,7.9). No associations were observed between greenspace and sleep efficiency, nor in cross-sectional early adolescence models. The association between greenspace and sleep differed by racial and socioeconomic subgroups. For example, among Black participants, higher NDVI was associated with better sleep, in neighborhoods with low socio-economic status (SES), higher %grass was associated with worse sleep, and in neighborhoods with high SES, higher total greenspace and %grass were associated with better sleep time. SVI metrics may have the potential to identify specific features of greenspace that affect sleep.

Prenatal lead exposure, telomere length in cord blood, and DNA methylation age in the PROGRESS prenatal cohort.

BACKGROUND: Lead is a ubiquitous pollutant with deleterious effects on human health and remains a major current public health concern in developing countries. This heavy metal may interfere with nucleic acids via oxidative stress or epigenetic changes that affect biological markers of aging, e.g., telomere length and DNA methylation (DNAm). Telomere shortening associates with biological age in newborns, and DNA methylation at specific CpG sites can be used to calculate "epigenetic clocks". OBJECTIVE: The aim of this study was to examine the associations of prenatal lead exposures with telomere length and DNA-methylation-based predictors of age in cord blood. DESIGN: The study included 507 mother-child pairs from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study, a birth cohort in Mexico City. Maternal blood (second trimester, third trimester and at delivery) and bone lead levels (one month postpartum) were measured using inductively coupled plasma-mass spectrometry and X-ray fluorescence, respectively. Cord blood leukocyte telomere length was measured using quantitative PCR and apparent age by DNA methylation biomarkers, i.e., Horvath's DNA methylation age and the Knight's predictor of gestational age. RESULTS: Average maternal age was 28.5 ± 5.5 years, and 51.5% reported low socioeconomic status. Children's mean telomere length was 1.2 ± 1.3 relative units, and mean DNA methylation ages using the Horvath's and Knight's clocks were -2.6 ± 0.1 years and 37.9 ± 1.4 weeks (mean ± SD), respectively. No significant associations were found between maternal blood and bone lead concentrations with telomere length and DNAm age in newborns. CONCLUSION: We found no associations of prenatal lead exposure with telomere length and DNA methylation age biomarkers.

Prenatal PM2.5 exposure and infant temperament at age 6 months: Sensitive windows and sex-specific associations.

BACKGROUND: Prenatal exposure to fine particulate matter with a diameter of ≤2.5 µm (PM2.5) has been linked to adverse neurodevelopmental outcomes in later childhood, while research on early infant behavior remains sparse. OBJECTIVES: We examined associations between prenatal PM2.5 exposure and infant negative affectivity, a stable temperamental trait associated with longer-term behavioral and mental health outcomes. We also examined sex-specific effects. METHODS: Analyses included 559 mother-infant pairs enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort. Daily PM2.5 exposure based on geocoded residential address during pregnancy was estimated using a satellite-based spatiotemporal model. Domains of negative affectivity (Sadness, Distress to Limitations, Fear, Falling Reactivity) were assessed using the Infant Behavior Questionnaire-Revised (IBQ-R) when infants were 6 months old. Subscale scores were calculated as the mean of item-specific responses; the global Negative Affectivity (NA) score was derived by averaging the mean of the four subscale scores. Bayesian distributed lag interaction models (BDLIMs) were used to identify sensitive windows for prenatal PM2.5 exposure on global NA and its subscales, and to examine effect modification by sex. RESULTS: Mothers were primarily racial/ethnic minorities (38% Black, 37% Hispanic), 40% had ≤12 years of education; most did not smoke during pregnancy (87%). In the overall sample, BDLIMs revealed that increased PM2.5 at mid-pregnancy was associated with higher global NA, Sadness, and Fear scores, after adjusting for covariates (maternal age, education, race/ethnicity, sex). Among boys, increased PM2.5 at early pregnancy was associated with decreased Fear scores, while exposure during late pregnancy was associated with increased Fear scores (cumulative effect estimate = 0.57, 95% CI: 0.03-1.41). Among girls, increased PM2.5 during mid-pregnancy was associated with higher Fear scores (cumulative effect estimate = 0.82, 95% CI: 0.05-1.91). CONCLUSIONS: Prenatal PM2.5 exposure was associated with negative affectivity at age 6 months, and the sensitive windows may vary by subdomains and infant sex.

Prenatal phthalates, gestational weight gain, and long-term weight changes among Mexican women.

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.

Critical windows of perinatal particulate matter (PM2.5) exposure and preadolescent kidney function.

Air pollution exposure, especially particulate matter ≤2.5 µm in diameter (PM2.5), is associated with poorer kidney function in adults and children. Perinatal exposure may occur during susceptible periods of nephron development. We used distributed lag nonlinear models (DLNMs) to examine time-varying associations between early life daily PM2.5 exposure (periconceptional through age 8 years) and kidney parameters in preadolescent children aged 8-10 years. Participants included 427 mother-child dyads enrolled in the PROGRESS birth cohort study based in Mexico City. Daily PM2.5 exposure was estimated at each participant's residence using a validated satellite-based spatio-temporal model. Kidney function parameters included estimated glomerular filtration rate (eGFR), serum cystatin C, and blood urea nitrogen (BUN). Models were adjusted for child's age, sex and body mass index (BMI) z-score, as well as maternal education, indoor smoking report and seasonality (prenatal models were additionally adjusted for average first year of life PM2.5 exposure). We also tested for sex-specific effects. Average perinatal PM2.5 was 22.7 µg/m3 and ranged 16.4-29.3 µg/m3. Early pregnancy PM2.5 exposures were associated with higher eGFR in preadolescence. Specifically, we found that PM2.5 exposure between weeks 1-18 of gestation was associated with increased preadolescent eGFR, whereas exposure in the first 14 months of life after birth were associated with decreased eGFR. Specifically, a 5 µg/m3 increase in PM2.5 during the detected prenatal window was associated with a cumulative increase in eGFR of 4.44 mL/min/1.732 (95%CI: 1.37, 7.52), and during the postnatal window we report a cumulative eGFR decrease of -10.36 mL/min/1.732 (95%CI: -17.68, -3.04). We identified perinatal windows of susceptibility to PM2.5 exposure with preadolescent kidney function parameters. Follow-up investigating PM2.5 exposure with peripubertal kidney function trajectories and risk of kidney disease in adulthood will be critical.

Prenatal maternal phthalate exposures and trajectories of childhood adiposity from four to twelve years.

BACKGROUND/AIM: Adiposity trajectories reflect dynamic process of growth and may predict later life health better than individual measures. Prenatal phthalate exposures may program later childhood adiposity, but findings from studies examining these associations are conflicting. We investigated associations between phthalate biomarker concentrations during pregnancy with child adiposity trajectories. METHODS: We followed 514 mother-child pairs from the Mexico City PROGRESS cohort from pregnancy through twelve years. We measured concentrations of nine phthalate biomarkers in 2nd and 3rd trimester maternal urine samples to create a pregnancy average using the geometric mean. We measured child BMI z-score, fat mass index (FMI), and waist-to-height ratio (WHtR) at three study visits between four and 12 years of age. We identified adiposity trajectories using multivariate latent class growth modeling, considering BMI z-score, FMI, and WHtR as joint indicators of latent adiposity. We estimated associations of phthalates biomarkers with class membership using multinomial logistic regression. We used quantile g-computation to estimate the potential effect of the total phthalate mixture and assessed effect modification by sex. RESULTS: We identified three trajectories of child adiposity, a "low-stable", a "low-high", and a "high-high" group. A doubling of the sum of di (2-ethylhexyl) phthalate metabolites (ΣDEHP), was associated with 1.53 (1.08, 2.19) greater odds of being in the "high-high" trajectory in comparison to the "low-stable" group, whereas a doubling in di-isononyl phthalate metabolites (ΣDiNP) was associated with 1.43 (1.02, 2.02) greater odds of being in the "low-high" trajectory and mono (carboxy-isononyl) phthalate (MCNP) was associated with 0.66 (0.45, 97) lower odds of being in the "low-high" trajectory. No sex-specific associations or mixture associations were observed. CONCLUSIONS: Prenatal concentrations of urinary DEHP metabolites, DiNP metabolites, and MCNP, a di-isodecyl phthalate metabolite, were associated with trajectories of child adiposity. The total phthalate mixture was not associated with early life child adiposity.

Prenatal exposure to PM2.5 and childhood cognition: Accounting for between-site heterogeneity in a pooled analysis of ECHO cohorts in the Northeastern United States.

BACKGROUND: Emerging studies have investigated the adverse health effects of PM2.5 using data from multiple cohorts, and results often are not generalizable across cohorts. We aimed to assess associations between prenatal PM2.5 and childhood cognition in two U.S. cohorts while accounting for between-site heterogeneity. METHODS: Analyses included 348 mother-child dyads enrolled in the dual site (New York City and Boston) PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort and in the First Thousand Days of Life (FTDL) study (Northern Virginia) participating in the Environmental influences on Child Health Outcomes (ECHO) national consortium. Residential prenatal PM2.5 exposure was estimated using a validated satellite-based model and childhood cognition was measured using the NIH Toolbox Cognition Battery at three to eight years of age. We used a log-linear model applied to contingency tables formed by cross-classifying covariates by site to examine between-site heterogeneity using 3rd trimester PM2.5 exposure, age-corrected cognition scores, and covariates potentially causing heterogeneities. Multivariable linear regression models informed by the combinability analysis were used to estimate the coefficients and 95% confidence intervals (CIs) for the association between 3rd trimester PM2.5 exposure and age-corrected cognition scores (mean = 100, SD = 15). RESULTS: The log-linear model indicated that inter-study associations were similar between PRISM-NYC and FTDL, which were different from those in PRISM-Boston. Accordingly, we combined the data of PRISM-NYC and FTDL cohorts. We observed associations between 3rd trimester PM2.5 and cognition scores, findings were varying by site, childsex, and test. For example, a 1 µg/m3 increase of 3rd trimester PM2.5 was associated with -4.35 (95% CI = -8.73, -0.25) mean early childhood cognition scores in females in PRISM-Boston. In the pooled NYC + FTDL site, the association between PM2.5 and childhood cognition may be modified by maternal education and urbanicity. CONCLUSIONS: We found associations between prenatal PM2.5 and impaired childhood cognition. Since multi-site analyses are increasingly conducted, our findings suggest the needed awareness of between-site heterogeneity.

AKI in Hospitalized Patients with COVID-19.

BACKGROUND: Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. METHODS: This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. RESULTS: Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. CONCLUSIONS: AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.

A 1-km hourly air-temperature model for 13 northeastern U.S. states using remotely sensed and ground-based measurements.

BACKGROUND: Accurate and precise estimates of ambient air temperatures that can capture fine-scale within-day variability are necessary for studies of air temperature and health. METHOD: We developed statistical models to predict temperature at each hour in each cell of a 927-m square grid across the Northeast and Mid-Atlantic United States from 2003 to 2019, across ~4000 meteorological stations from the Integrated Mesonet, using inputs such as elevation, an inverse-distance-weighted interpolation of temperature, and satellite-based vegetation and land surface temperature. We used a rigorous spatial cross-validation scheme and spatially weighted the errors to estimate how well model predictions would generalize to new cell-days. We assess the within-county association of temperature and social vulnerability in a heat wave as an example application. RESULTS: We found that a model based on the XGBoost machine-learning algorithm was fast and accurate, obtaining weighted root mean square errors (RMSEs) around 1.6 K, compared to standard deviations around 11.0 K. We found similar accuracy when validating our model on an external dataset from Weather Underground. Assessing predictions from the North American Land Data Assimilation System-2 (NLDAS-2), another hourly model, in the same way, we found it was much less accurate, with RMSEs around 2.5 K. This is likely due to the NLDAS-2 model's coarser spatial resolution, and the dynamic variability of temperature within its grid cells. Finally, we demonstrated the health relevance of our model by showing that our temperature estimates were associated with social vulnerability across the region during a heat wave, whereas the NLDAS-2 showed a much weaker association. CONCLUSION: Our high spatiotemporal resolution air temperature model provides a strong contribution for future health studies in this region.

The association between ambient temperature variability and myocardial infarction in a New York-State-based case-crossover study: An examination of different variability metrics.

BACKGROUND: Short-term temperature variability has been consistently associated with mortality, with limited evidence for cardiovascular outcomes. Previous studies have used multiple metrics to measure temperature variability; however, those metrics do not capture hour-to-hour changes in temperature. OBJECTIVES: We assessed the correlation between sub-daily temperature-change-over-time metrics and previously-used metrics, and estimated associations with myocardial infarction (MI) hospitalizations. METHODS: Hour-to-hour change-over-time was measured via three metrics: 24-hr mean absolute hourly first difference, 24-hr maximum absolute hourly first difference, and 24-hr mean hourly first difference. We first assessed the Spearman correlations between these metrics and four previously-used metrics (24-hr standard deviation of hourly temperature, 24-hr diurnal temperature range, 48-hr standard deviation of daily minimal and maximal temperatures, and 48-hr difference of daily mean temperature), using hourly data from the North America Land Data Assimilation System-2 Model. Subsequently, we estimated the association between these metrics and primary MI hospitalization in adult residents of New York State for 2000-2015 using a time-stratified case-crossover design. RESULTS: The hour-to-hour change-over-time metrics were correlated, but not synonymous, with previously-used metrics. We observed 809,259 MI, 45% of which were among females and the mean (standard deviation) age was 70 (15). An increase from mean to 90th percentile in mean absolute first difference of temperature was associated with a 2.04% (95% Confidence Interval [CI]: 1.30-2.78%) increase in MI rate. An increase from mean to 90th percentile in mean first difference also yielded a positive association (1.86%; 95%CI: 1.09-2.64%). We observed smaller- or similar-in-magnitude positive associations for previously-used metrics. DISCUSSION: First, short-term hour-to-hour temperature change was positively associated with MI risk. Second, all other variability metrics yielded positive associations with MI, with varying magnitude. In future research on temperature variability, researchers should define their research question, including which aspects of variability they intend to measure, and apply the appropriate metric. ALTERNATIVE: All metrics of temperature variability, including short-term hour-to-hour temperature changes, were positively associated with MI risk, though the magnitude of effect estimates varied by metric.

Prenatal and early life exposure to particulate matter, environmental tobacco smoke and respiratory symptoms in Mexican children.

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.

Prenatal PM2.5 exposure in the second and third trimesters predicts neurocognitive performance at age 9-10 years: A cohort study of Mexico City children.

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.

Prenatal maternal phthalate exposures and child lipid and adipokine levels at age six: A study from the PROGRESS cohort of Mexico City.

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.

Prenatal urinary concentrations of phthalate metabolites and behavioral problems in Mexican children: The Programming Research in Obesity, Growth Environment and Social Stress (PROGRESS) study.

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.

Prenatal air pollution exposure and neurodevelopment: A review and blueprint for a harmonized approach within ECHO.

BACKGROUND: Air pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants. OBJECTIVES: We briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO. METHODS: We review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO. DISCUSSION: While the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research. CONCLUSIONS: In ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.