Publications by authors named "Allan C Just"

132 Publications

Associations between infant sex and DNA methylation across umbilical cord blood, artery, and placenta samples.

Epigenetics 2021 Sep 25. Epub 2021 Sep 25.

Division of Pulmonary Medicine, Icahn School of Medicine at Mount Sinai, New York, NY.

DNA methylation (DNAm) is vulnerable to dysregulation by environmental exposures during epigenetic reprogramming that occurs in embryogenesis. Sexual dimorphism in environmentally induced DNAm dysregulation has been identified and therefore it is important to understand sex-specific DNAm patterns. DNAm at several autosomal sites has been consistently associated with sex in cord blood and placental fetal tissues. However, there is limited research comparing sex-specific DNAm across tissues, particularly differentially methylated regions (DMRs). This study leverages DNAm data measured using the Illumina HumanMethylation450 BeadChip in cord blood (N = 179), placenta (N = 229), and umbilical artery samples (N = 229) in the PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort to identify autosomal DMRs and differentially methylated positions (DMPs). A replication analyses was conducted in an independent cohort (GEO Accession GSE129841). We identified 183, 257, and 419 DMRs and 2119, 2281, and 3405 DMPs ( < 0.05) in cord blood, placenta, and artery samples, respectively. Thirty-nine DMRs overlapped in all three tissues, overlapping with genes involved in spermatogenesis () and X-inactivation (). In replication analysis, 85% of DMRs overlapped with those identified in PRISM. Overall DMRs and DMPs had higher methylation levels among females in cord blood and artery samples, but higher methylation levels among males in placenta samples. Further research is necessary to understand biological mechanisms that contribute to differences in sex-specific DNAm signatures across tissues, as well as to determine if sexual dimorphism in the epigenome impacts response to environmental stressors.
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http://dx.doi.org/10.1080/15592294.2021.1985300DOI Listing
September 2021

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

Environ Res 2021 Sep 23;204(Pt B):112111. Epub 2021 Sep 23.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

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.
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http://dx.doi.org/10.1016/j.envres.2021.112111DOI Listing
September 2021

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

Environ Res 2021 Sep 16;204(Pt B):112062. Epub 2021 Sep 16.

Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, PA, USA. Electronic address:

Air pollution exposure, especially particulate matter ≤2.5 μm in diameter (PM), 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 PM 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 PM 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 PM exposure). We also tested for sex-specific effects. Average perinatal PM was 22.7 μg/m and ranged 16.4-29.3 μg/m. Early pregnancy PM exposures were associated with higher eGFR in preadolescence. Specifically, we found that PM 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/m increase in PM during the detected prenatal window was associated with a cumulative increase in eGFR of 4.44 mL/min/1.73 (95%CI: 1.37, 7.52), and during the postnatal window we report a cumulative eGFR decrease of -10.36 mL/min/1.73 (95%CI: -17.68, -3.04). We identified perinatal windows of susceptibility to PM exposure with preadolescent kidney function parameters. Follow-up investigating PM exposure with peripubertal kidney function trajectories and risk of kidney disease in adulthood will be critical.
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http://dx.doi.org/10.1016/j.envres.2021.112062DOI Listing
September 2021

A spatiotemporal reconstruction of daily ambient temperature using satellite data in the Megalopolis of Central Mexico from 2003 to 2019.

Int J Climatol 2021 Jun 18;41(8):4095-4111. Epub 2021 Mar 18.

Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA.

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 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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http://dx.doi.org/10.1002/joc.7060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8251982PMC
June 2021

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.

Environ Res 2021 Jul 8;202:111651. Epub 2021 Jul 8.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, 17 East 102nd Street, 3 West, New York, NY, United States; The Institute for Exposomics Research, Icahn School of Medicine at Mount Sinai, 17 East 102nd Street, 3 West, New York, NY, United States. Electronic address:

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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http://dx.doi.org/10.1016/j.envres.2021.111651DOI Listing
July 2021

Neighborhood-level disparities and subway utilization during the COVID-19 pandemic in New York City.

Nat Commun 2021 06 17;12(1):3692. Epub 2021 Jun 17.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

The COVID-19 pandemic has yielded disproportionate impacts on communities of color in New York City (NYC). Researchers have noted that social disadvantage may result in limited capacity to socially distance, and consequent disparities. We investigate the association between neighborhood social disadvantage and the ability to socially distance, infections, and mortality in Spring 2020. We combine Census Bureau and NYC open data with SARS-CoV-2 testing data using supervised dimensionality-reduction with Bayesian Weighted Quantile Sums regression. The result is a ZIP code-level index with weighted social factors associated with infection risk. We find a positive association between neighborhood social disadvantage and infections, adjusting for the number of tests administered. Neighborhood disadvantage is also associated with a proxy of the capacity to socially isolate, NYC subway usage data. Finally, our index is associated with COVID-19-related mortality.
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http://dx.doi.org/10.1038/s41467-021-24088-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211826PMC
June 2021

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

Environ Res 2021 09 12;200:111477. Epub 2021 Jun 12.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, USA.

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.
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http://dx.doi.org/10.1016/j.envres.2021.111477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8403657PMC
September 2021

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function.

Clin Epigenetics 2021 Jun 2;13(1):121. Epub 2021 Jun 2.

Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

Background: The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies.

Results: We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The "first-generation" clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria.

Conclusion: DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.
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http://dx.doi.org/10.1186/s13148-021-01082-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170969PMC
June 2021

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

Environ Res 2021 10 26;201:111338. Epub 2021 May 26.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States. Electronic address:

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 log-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 (β = 0.57, 95% CI = 0.17, 1.13) and in girls (β = 0.54, 95% CI = 0.16, 1.08), overall behavioral problems in boys (β = 0.58, 95% CI = 0.20, 1.15), and depression scores in boys (β = 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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http://dx.doi.org/10.1016/j.envres.2021.111338DOI Listing
October 2021

The associations of phthalate biomarkers during pregnancy with later glycemia and lipid profiles.

Environ Int 2021 10 6;155:106612. Epub 2021 May 6.

School of Global Public Health, New York University, NY, USA.

Background: Pregnancy induces numerous cardiovascular and metabolic changes. Alterations in these sensitive processes may precipitate long-term post-delivery health consequences. Studies have reported associations between phthalates and metabolic complications of pregnancy, but no study has investigated metabolic outcomes beyond pregnancy.

Objectives: To examine associations of exposure to phthalates during pregnancy with post-delivery metabolic health.

Design: We quantified 15 urinary phthalate biomarker concentrations during the second and third trimesters among 618 pregnant women from Mexico City. Maternal metabolic health biomarkers included fasting blood measures of glycemia [glucose, insulin, Homeostatic Model Assessment of Insulin Resistance [HOMA-IR], % hemoglobin A1c (HbA1c%)] and lipids (total, high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol, triglycerides), at 4-5 and 6-8 years post-delivery. To estimate the influence of the phthalates mixture, we used Bayesian weighted quantile sum regression and Bayesian kernel machine regression; for individual biomarkers, we used linear mixed models.

Results: As a mixture, higher urinary phthalate biomarker concentrations during pregnancy were associated with post-delivery concentrations of plasma glucose (interquartile range [IQR] difference: 0.13 SD, 95%CrI: 0.05, 0.20), plasma insulin (IQR difference: 0.06 SD, 95%CrI: -0.02, 0.14), HOMA-IR (IQR difference: 0.08 SD, 95% CrI: 0.01, 0.16), and HbA1c% (IQR difference: 0.15 SD, 95%CrI: 0.05, 0.24). Associations were primarily driven by mono-2-ethyl-5-carboxypentyl terephthalate (MECPTP) and the sum of dibutyl phthalate biomarkers (∑DBP). The phthalates mixture was associated with lower HDL (IQR difference: -0.08 SD, 95%CrI: -0.16, -0.01), driven by ∑DBP and monoethyl phthalate (MEP), and higher triglyceride levels (IQR difference: 0.15 SD, 95%CrI: 0.08, 0.22), driven by MECPTP and MEP. The overall mixture was not associated with total cholesterol and LDL. However, ∑DBP and MEP were associated with lower and higher total cholesterol, respectively, and MECPTP and ∑DBP were associated with lower LDL.

Conclusions: Phthalate exposure during pregnancy is associated with adverse long-term changes in maternal metabolic health. A better understanding of timing of the exact biological changes and their implications on metabolic disease risk is needed.
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http://dx.doi.org/10.1016/j.envint.2021.106612DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292182PMC
October 2021

The effect of prenatal temperature and PM exposure on birthweight: Weekly windows of exposure throughout the pregnancy.

Environ Int 2021 10 30;155:106588. Epub 2021 Apr 30.

Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health, New York, NY, USA.

Background: Birthweight is a strong predictor of normal growth, healthy development, and survival. Several studies have found associations between temperature, fine particulate matter (PM), and birth weight. However, the relevant timing of exposures varies between studies and is yet unclear. Therefore, we assessed the difference in term birthweight (TBW) associated with weekly exposure to temperature and PM throughout 37 weeks of gestation.

Methods: We included all singleton live term births in Massachusetts, U.S between 2004 and 2015 (n = 712,438). Weekly PM and temperature predictions were estimated on a 1 km grid from satellite-based models. We utilized a distributed lag nonlinear model (DLNM) to estimate the difference in TBW associated with weekly exposures from the last menstrual period to 37 weeks of gestation.

Results: We found a nonlinear association with prenatal temperature exposure. Larger effects were observed in warmer temperatures, where higher temperatures were negatively associated with TBW. Temperature effects were larger in the first and final weeks of gestation. We observed a negative difference in TBW associated with PM exposure. Overall, a 1 µg/m increase in prenatal exposure was associated with 3.9 g lower TBW (95% CI -5.0 g; -2.9 g). PM effects were larger in the final weeks of gestation.

Conclusion: We found heat and PM exposure to be related to lower TBW. Our findings suggest that women are more susceptible to both exposures towards the end of pregnancy. Susceptibility to heat was higher in the initial weeks of pregnancy as well. These critical windows of susceptibility can be communicated to pregnant women during routine prenatal visits to increase awareness and target interventions to reduce exposures.
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http://dx.doi.org/10.1016/j.envint.2021.106588DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292186PMC
October 2021

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

Environ Res 2021 06 28;197:111207. Epub 2021 Apr 28.

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

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.
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http://dx.doi.org/10.1016/j.envres.2021.111207DOI Listing
June 2021

Saliva cell type DNA methylation reference panel for epidemiological studies in children.

Epigenetics 2021 Feb 22:1-17. Epub 2021 Feb 22.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA.

Saliva is a widely used biological sample, especially in pediatric research, containing a heterogenous mixture of immune and epithelial cells. Associations of exposure or disease with saliva DNA methylation can be influenced by cell-type proportions. Here, we developed a saliva cell-type DNA methylation reference panel to estimate interindividual cell-type heterogeneity in whole saliva studies. Saliva was collected from 22 children (7-16 years) and sorted into immune and epithelial cells, using size exclusion filtration and magnetic bead sorting. DNA methylation was measured using the Illumina MethylationEPIC BeadChip. We assessed cell-type differences in DNA methylation profiles and tested for enriched biological pathways. Immune and epithelial cells differed at 181,577 (22.8%) DNA methylation sites (t-test p < 6.28 × 10). Immune cell hypomethylated sites are mapped to genes enriched for immune pathways (p < 3.2 × 10). Epithelial cell hypomethylated sites were enriched for cornification (p = 5.2 × 10), a key process for hard palette formation. Saliva immune and epithelial cells have distinct DNA methylation profiles which can drive whole-saliva DNA methylation measures. A primary saliva DNA methylation reference panel, easily implemented with an R package, will allow estimates of cell proportions from whole saliva samples and improve epigenetic epidemiology studies by accounting for measurement heterogeneity by cell-type proportions.
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http://dx.doi.org/10.1080/15592294.2021.1890874DOI Listing
February 2021

Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortium.

Epigenetics 2021 Jan 11:1-13. Epub 2021 Jan 11.

Department of Immunobiochemistry, National Institute of Perinatology, Mexico City, Mexico.

Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analyzed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 children and 1,962 adolescent whole-blood samples derived from 10 cohorts. DNA methylation was measured using Illumina Infinium Methylation 450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for the association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels.
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http://dx.doi.org/10.1080/15592294.2020.1864171DOI Listing
January 2021

Prenatal lead exposure and cord blood DNA methylation in PROGRESS: an epigenome-wide association study.

Environ Epigenet 2020 8;6(1):dvaa014. Epub 2020 Dec 8.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1057, New York, NY 10029, USA.

The effects of prenatal lead exposure on child development include impaired growth and cognitive function. DNA methylation might be involved in the underlying mechanisms and previous epigenome-wide association studies reported associations between lead exposure during pregnancy and cord blood methylation levels. However, it is unclear during which developmental stage lead exposure is most harmful. Cord blood methylation levels were assayed in 420 children from a Mexican pre-birth cohort using the Illumina Infinium MethylationEPIC microarray. Lead concentrations were measured in umbilical cord blood as well as in blood samples from the mothers collected at 2nd and 3rd trimester and delivery using inductively coupled plasma-mass spectrometry. In addition, maternal bone lead levels were measured in tibia and patella using X-ray fluorescence. Comprehensive quality control and preprocessing of microarray data was followed by an unbiased restriction to methylation sites with substantial variance. Methylation levels at 202 111 cytosine-phosphate-guanine sites were regressed on each exposure adjusting for child sex, leukocyte composition, batch variables, gestational age, birthweight-for-gestational-age, maternal age, maternal education and mode of delivery. We find no association between prenatal lead exposure and cord blood methylation. This null result is strengthened by a sensitivity analysis showing that in the same dataset known biomarkers for birthweight-for-gestational-age can be recovered and the fact that phenotypic associations with lead exposure have been described in the same cohort.
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http://dx.doi.org/10.1093/eep/dvaa014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722799PMC
December 2020

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

Environ Res 2021 01 22;192:110365. Epub 2020 Oct 22.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address:

Background: Exposure to particulate matter <2.5 μm in diameter (PM) 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 PM 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 PM 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 PM 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 PM was associated with higher risk of ever wheeze at age 6-8 years. We also observed a critical window of PM exposure between postnatal weeks 6-39 and higher risk of current wheeze. We found significant associations between higher prenatal and early life PM exposure and higher cumulative risk ratios of ever wheeze (RR:3.76, 95%CI [1.41, 10.0] per 5 μg/m) and current wheeze in the past year (RR:7.91, 95%CI [1.5, 41.6] per 5 μg/m) 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 PM 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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http://dx.doi.org/10.1016/j.envres.2020.110365DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736115PMC
January 2021

Gradient boosting machine learning to improve satellite-derived column water vapor measurement error.

Atmos Meas Tech 2020 2;13(9):4669-4681. Epub 2020 Sep 2.

Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beersheba, Israel.

The atmospheric products of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm include column water vapor (CWV) at a 1 km resolution, derived from daily overpasses of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Aqua and Terra satellites. We have recently shown that machine learning using extreme gradient boosting (XGBoost) can improve the estimation of MAIAC aerosol optical depth (AOD). Although MAIAC CWV is generally well validated (Pearson's >0.97 versus CWV from AERONET sun photometers), it has not yet been assessed whether machine-learning approaches can further improve CWV. Using a novel spatiotemporal cross-validation approach to avoid overfitting, our XGBoost model, with nine features derived from land use terms, date, and ancillary variables from the MAIAC retrieval, quantifies and can correct a substantial portion of measurement error relative to collocated measurements at AERONET sites (26.9% and 16.5% decrease in root mean square error (RMSE) for Terra and Aqua datasets, respectively) in the Northeastern USA, 2000-2015. We use machine-learning interpretation tools to illustrate complex patterns of measurement error and describe a positive bias in MAIAC Terra CWV worsening in recent summertime conditions. We validate our predictive model on MAIAC CWV estimates at independent stations from the SuomiNet GPS network where our corrections decrease the RMSE by 19.7% and 9.5% for Terra and Aqua MAIAC CWV. Empirically correcting for measurement error with machine-learning algorithms is a postprocessing opportunity to improve satellite-derived CWV data for Earth science and remote sensing applications.
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http://dx.doi.org/10.5194/amt-13-4669-2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665162PMC
September 2020

A hybrid approach to predict daily NO concentrations at city block scale.

Sci Total Environ 2021 Mar 2;761:143279. Epub 2020 Nov 2.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Division of Neonatology, Department of Pediatrics, Cohen Children's Medical Center at Northwell Health, New Hyde Park, NY, USA.

Estimating the ambient concentration of nitrogen dioxide (NO) is challenging because NO generated by local fossil fuel combustion varies greatly in concentration across space and time. This study demonstrates an integrated hybrid approach combining dispersion modeling and land use regression (LUR) to predict daily NO concentrations at a high spatial resolution (e.g., 50 m) in the New York tri-state area. The daily concentration of traffic-related NO was estimated at the Environmental Protection Agency's NO monitoring sites in the study area for the years 2015-2017, using the Research LINE source (R-LINE) model with inputs of traffic data provided by the Highway Performance and Management System and meteorological data provided by the NOAA Integrated Surface Database. We used the R-LINE-predicted daily concentrations of NO to build mixed-effects regression models, including additional variables representing land use features, geographic characteristics, weather, and other predictors. The mixed model was selected by the Elastic Net method. Each model's performance was evaluated using the out-of-sample coefficient of determination (R) and the square root of mean squared error (RMSE) from ten-fold cross-validation (CV). The mixed model showed a good prediction performance (CV R: 0.75-0.79, RMSE: 3.9-4.0 ppb). R-LINE outputs improved the overall, spatial, and temporal CV R by 10.0%, 18.9% and 7.7% respectively. Given the output of R-LINE is point-based and has a flexible spatial resolution, this hybrid approach allows prediction of daily NO at an extremely high spatial resolution such as city blocks.
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http://dx.doi.org/10.1016/j.scitotenv.2020.143279DOI Listing
March 2021

Association of ambient PM exposure with maternal bone strength in pregnant women from Mexico City: a longitudinal cohort study.

Lancet Planet Health 2020 11;4(11):e530-e537

Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.

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) 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 PM 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 PM concentrations using linear mixed models and distributed lag models.

Findings: Adjusting for multiple exposure windows, each 10 ug/m increase in PM 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/m increase in third trimester PM 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. PM 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 PM exposure during and after pregnancy was associated with diminished trabecular and cortical bone strength. Early pregnancy PM 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 PM pollution could improve public health by reducing bone fracture risk.

Funding: US National Institute of Environmental Health Sciences.
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http://dx.doi.org/10.1016/S2542-5196(20)30220-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664993PMC
November 2020

Associations between daily ambient temperature and sedentary time among children 4-6 years old in Mexico City.

PLoS One 2020 30;15(10):e0241446. Epub 2020 Oct 30.

Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.

Background: Sedentary behavior is a worldwide public health concern. There is consistent and growing evidence linking sedentary behavior to mortality and morbidity. Early monitoring and assessment of environmental factors associated with sedentary behaviors at a young age are important initial steps for understanding children's sedentary time and identifying pertinent interventions.

Objective: This study examines the association between daily temperature (maximum, mean, minimum, and diurnal variation) and all-day sedentary time among 4-6 year old children in Mexico City (n = 559) from the year 2013 to 2015.

Methods: We developed a spatiotemporally resolved hybrid satellite-based land use regression temperature model and calculated percent daily sedentary time from aggregating 10-second epoch vertical counts captured by accelerometers that participants wore for one week. We modeled generalized additive models (GAMs), one for each temperature type as a covariate (maximum, mean, minimum, and diurnal variation). All GAMs included percent all-day sedentary time as the outcome and participant-level random intercepts to account for repeated measures of sedentary time. Our models were adjusted for demographic factors and environmental exposures.

Results: Daily maximum temperature, mean temperature, and diurnal variation have significant negative linear relationships with all-day sedentary time (p<0.01). There is no significant association between daily minimum temperature and all-day sedentary time. Children have on average 0.26% less daily sedentary time (approximately 2.2 minutes) for each 1°C increase in ambient maximum temperature (range 7.1-30.2°C), 0.27% less daily sedentary time (approximately 2.3 minutes) for each 1°C increase in ambient mean temperature (range 4.3-22.2°C), and 0.23% less daily sedentary time (approximately 2.0 minutes) for each 1°C increase in diurnal variation (range 3.0-21.6°C).

Conclusions: These results are contrary to our hypothesis in which we expected a curvilinear relationship between temperature (maximum, mean, minimum, and diurnal variation) and sedentary time. Our findings suggest that temperature is an important environmental factor that influences children's sedentary behavior.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241446PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598506PMC
January 2021

Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM) using satellite data over large regions.

Atmos Environ (1994) 2020 Oct 17;239. Epub 2020 Jul 17.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Reconstructing the distribution of fine particulate matter (PM) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM on a 1×1 km resolution for a 13 state region in the Northeastern USA for the years 2000-2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.
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http://dx.doi.org/10.1016/j.atmosenv.2020.117649DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591135PMC
October 2020

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

Environ Res 2021 05 22;196:110320. Epub 2020 Oct 22.

Department of Environmental Medicine and Public Health, And Pediatrics, Institute for Exposomics Research, Kravis Children's Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

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.
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http://dx.doi.org/10.1016/j.envres.2020.110320DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060371PMC
May 2021

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

Environ Res 2021 01 14;192:110341. Epub 2020 Oct 14.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

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 (β = -3.7% [-6.5, -0.78] per 1 unit increase in WQS biomarker index) and non-HDL cholesterol (β = -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 (β = 19.4% [1.26, 40.7] per doubling of phthalate) and monobenzyl phthalate (β = -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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http://dx.doi.org/10.1016/j.envres.2020.110341DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736226PMC
January 2021

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

J Med Internet Res 2020 11 6;22(11):e24018. Epub 2020 Nov 6.

Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Background: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking.

Objective: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points.

Methods: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions.

Results: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction.

Conclusions: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.
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http://dx.doi.org/10.2196/24018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652593PMC
November 2020

Predictors of patterns of weight change 1 year after delivery in a cohort of Mexican women.

Public Health Nutr 2021 Sep 1;24(13):4113-4123. Epub 2020 Oct 1.

Center for Population Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico.

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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http://dx.doi.org/10.1017/S1368980020002803DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012395PMC
September 2021

Prenatal PM exposure and behavioral development in children from Mexico City.

Neurotoxicology 2020 12 17;81:109-115. Epub 2020 Sep 17.

Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, United States.

Background: Childhood exposure to air pollution has been linked with maladaptive cognitive development; however, less is known about the association between prenatal fine particulate matter (PM) exposure and childhood behavior.

Objectives: Our aim was to assess the association between prenatal PM exposure and behavioral development in 4-6 year old children residing in Mexico City.

Methods: We used data from 539 mother-child pairs enrolled in a prospective birth cohort in Mexico City. We estimated daily PM exposure using a 1 km satellite-based exposure model and averaged over each trimester of pregnancy. We assessed childhood behavior at 4-6 years of age using the parent-completed Behavioral Assessment Scale for Children (BASC-2) composite scores and subscales. We used linear regression models to estimate change in BASC-2 T-scores with trimester specific 5-μg/m increases in PM. All models were mutually adjusted for PM exposures during the other trimesters, maternal factors including age, education, socioeconomic status, depression, and IQ, child's age at study visit, and season. We additionally assessed sex-specific effects by including an interaction term between PM and sex.

Results: Higher first trimester PM exposure was associated with reduced Adaptive Skills scores (β: -1.45, 95% CI: -2.60, -0.30). Lower scores on the Adaptive Skills composite score and subscales indicate poorer functioning. For PM exposure during the first trimester, decrements were consistent across adaptive subscale scores including Adaptability (β: -1.51, 95% CI: -2.72, -0.30), Social Skills (β: -1.63, 95% CI: -2.90, -0.36), and Functional Communication (β: -1.21, 95% CI: -2.21, -0.21). The association between 1 trimester PM and depression was stronger in males than females (β for males: 1.52, 95% CI: -0.41, 3.45; β for females: -0.13, 95% CI: -1.99, 1.72; p-int: 0.07).

Conclusions: Exposure to PM during early pregnancy may be associated with impaired behavioral development in children, particularly for measures of adaptive skills. These results suggest that air pollution impacts behavioral domains as well as cognition, and that the timing of exposure may be critical.
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http://dx.doi.org/10.1016/j.neuro.2020.09.036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708408PMC
December 2020

AKI in Hospitalized Patients with COVID-19.

J Am Soc Nephrol 2021 01 3;32(1):151-160. Epub 2020 Sep 3.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.

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.
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http://dx.doi.org/10.1681/ASN.2020050615DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7894657PMC
January 2021

Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19.

J Gen Intern Med 2020 10 19;35(10):2838-2844. Epub 2020 Aug 19.

The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Background: Data on patients with coronavirus disease 2019 (COVID-19) who return to hospital after discharge are scarce. Characterization of these patients may inform post-hospitalization care.

Objective: To describe clinical characteristics of patients with COVID-19 who returned to the emergency department (ED) or required readmission within 14 days of discharge.

Design: Retrospective cohort study of SARS-COV-2-positive patients with index hospitalization between February 27 and April 12, 2020, with ≥ 14-day follow-up. Significance was defined as P < 0.05 after multiplying P by 125 study-wide comparisons.

Participants: Hospitalized patients with confirmed SARS-CoV-2 discharged alive from five New York City hospitals.

Main Measures: Readmission or return to ED following discharge.

Results: Of 2864 discharged patients, 103 (3.6%) returned for emergency care after a median of 4.5 days, with 56 requiring inpatient readmission. The most common reason for return was respiratory distress (50%). Compared with patients who did not return, there were higher proportions of COPD (6.8% vs 2.9%) and hypertension (36% vs 22.1%) among those who returned. Patients who returned also had a shorter median length of stay (LOS) during index hospitalization (4.5 [2.9,9.1] vs 6.7 [3.5, 11.5] days; P = 0.006), and were less likely to have required intensive care on index hospitalization (5.8% vs 19%; P = 0.001). A trend towards association between absence of in-hospital treatment-dose anticoagulation on index admission and return to hospital was also observed (20.9% vs 30.9%, P = 0.06). On readmission, rates of intensive care and death were 5.8% and 3.6%, respectively.

Conclusions: Return to hospital after admission for COVID-19 was infrequent within 14 days of discharge. The most common cause for return was respiratory distress. Patients who returned more likely had COPD and hypertension, shorter LOS on index-hospitalization, and lower rates of in-hospital treatment-dose anticoagulation. Future studies should focus on whether these comorbid conditions, longer LOS, and anticoagulation are associated with reduced readmissions.
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http://dx.doi.org/10.1007/s11606-020-06120-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437962PMC
October 2020

Accelerated epigenetic aging as a risk factor for chronic obstructive pulmonary disease and decreased lung function in two prospective cohort studies.

Aging (Albany NY) 2020 08 3;12(16):16539-16554. Epub 2020 Aug 3.

Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27709, USA.

Chronic obstructive pulmonary disease (COPD) is a frequent diagnosis in older individuals and contributor to global morbidity and mortality. Given the link between lung disease and aging, we need to understand how molecular indicators of aging relate to lung function and disease. Using data from the population-based KORA (Cooperative Health Research in the Region of Augsburg) surveys, we associated baseline epigenetic (DNA methylation) age acceleration with incident COPD and lung function. Models were adjusted for age, sex, smoking, height, weight, and baseline lung disease as appropriate. Associations were replicated in the Normative Aging Study. Of 770 KORA participants, 131 developed incident COPD over 7 years. Baseline accelerated epigenetic aging was significantly associated with incident COPD. The change in age acceleration (follow-up - baseline) was more strongly associated with COPD than baseline aging alone. The association between the change in age acceleration between baseline and follow-up and incident COPD replicated in the Normative Aging Study. Associations with spirometric lung function parameters were weaker than those with COPD, but a meta-analysis of both cohorts provide suggestive evidence of associations. Accelerated epigenetic aging, both baseline measures and changes over time, may be a risk factor for COPD and reduced lung function.
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http://dx.doi.org/10.18632/aging.103784DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485704PMC
August 2020

Can ultra short-term changes in ambient temperature trigger myocardial infarction?

Environ Int 2020 10 1;143:105910. Epub 2020 Jul 1.

Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, United States.

Background: Climate change is increasing global average temperatures, as well as the frequency of extreme weather events. Both low and high ambient temperatures have been associated with elevated mortality; however, little is known about the cardiovascular impacts of hourly temperature.

Methods: We assessed the association between hourly ambient temperature and risk of myocardial infarction (MI) across adult residents of New York State (NYS). We identified cases across NYS hospitals from 2000 to 2015 in the New York Department of Health Statewide Planning and Research Cooperative System dataset, using ICD codes. Hourly ambient temperature was assessed at each patient's residential ZIP code, up to 48 hours prior to MI. We employed a time-stratified case-crossover study design matching case to control periods on hour of day, day of week, month and year.

Results: Of the 791,695 primary MI hospital admissions, 45% were female, the mean (standard deviation; SD) age was 70 (15) years, and 49% of cases occurred among New York City residents. The observed temperature range was -29 °C to 39 °C, with a mean of 10.8 °C (10.5 °C). Temperature in the 6 h preceding the MI was positively associated with risk of MI, across the range of observed temperatures, with null or nearly null associations for earlier hours. We estimated a cumulative percent increase in hourly myocardial infarction rate of 7.9% (95% confidence interval [CI]: 5.2%, 10.6%) for an 11 °C (median) to 27 °C (95th percentile) temperature increase for lag hours 0-5. Men, Medicare-ineligible individuals (age < 65), and those experiencing their first MI were most sensitive.

Conclusion: Our study provides evidence that increases in hourly ambient temperature can trigger myocardial infarction. Health-based definitions of extreme heat events may better capture the deleterious effects of heat by accounting for hourly temperature. Our findings can inform the design of more effective preparedness strategies for the increasingly frequent extreme heat events.
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http://dx.doi.org/10.1016/j.envint.2020.105910DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708404PMC
October 2020
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