Annals of Epidemiology

Community-led urban greening may contribute to neighborhood safety, but its relationship with crime remains uncertain. We examined whether Keep Indianapolis Beautiful Project GreenSpaces in Indianapolis were associated with changes in violence and total crime. We used a matched-pair difference-in-differences design comparing funded sites with matched unfunded applicant sites. The primary analysis included 29 matched pairs with two years of pre- and post-grant follow-up. Monthly Part I violent offenses and total crime within 600-m buffers were modeled using Poisson pseudo-maximum likelihood. In the first post-grant year, the violent-crime estimate was lower but imprecise (IRR, 0.903; 95% CI, 0.805-1.014). In the second post-grant year, the relative rate was lower (IRR, 0.830; 95% CI, 0.718-0.961). Total crime estimates showed no clear post-grant change. Additional analyses indicated some sensitivity to spatial scale, but no sustained divergence in pre-grant crime patterns. Analyses of short-term crime dependence showed clear month-to-month persistence in violent crime within sites but limited evidence of stable spatial dependence across nearby sites. Therefore, within the two-year post-grant period examined, Project GreenSpaces was associated most consistently with lower relative violent-crime rates in the second year, while no corresponding decrease was observed for total recorded crime. Longer follow-up is needed to determine whether these patterns persist or change as projects mature.

This study examines the impact of various maternal factors and continuous labor support on birth outcomes among 124 birthing people in the Baltimore region of Maryland who sought and/or received doula care. The cohort primarily consists of Black birthing people and includes detailed data on maternal age, race, education level, employment status, health insurance status, income level, preexisting health challenges, and pregnancy or delivery-related health challenges. The study also explores whether the pregnancy was the birthing person's first, as well as neonatal outcomes such as NICU admission, low birth weight, and other newborn health concerns. Due dates and delivery dates were compared and analyzed, where available, to provide a comprehensive understanding of the timing of births among the cohort. The findings highlight known correlations between maternal socioeconomic factors, health factors, and adverse birth outcomes, emphasizing the critical role of doula support during the prenatal period and labor and delivery in improving maternal and neonatal health, as well as in providing culturally competent care and positive birth experiences. This research contributes to the growing body of evidence on the benefits of doula care, particularly for marginalized communities, and underscores the need for targeted interventions to address health disparities among Black Birthing persons.

Background: The incidence of early-onset colorectal cancer (EOCRC), defined as CRC diagnosed age <50, is rising in the United States and is the leading cause of cancer death in among those with early-onset cancer. Epigenetic exposure signatures based on methylation risk scores (MRS) offer a novel approach to identify long-term exposures that may contribute to EOCRC risk. We sought to replicate findings from a recent study in a racially and geographically diverse CRC cohort. Methods: We computed weighted MRS across lifestyle, air pollution, and pesticide exposome traits in 146 participants from the Disparities and Cancer Epidemiology (DANCE) cohort, a diverse population-based CRC study, applying the Maas et al. (2026) framework to tumor tissue. Associations between MRS and age at CRC onset (EOCRC, n=29; intermediate-onset (IOCRC) 50-64 years, n=69; late-onset, [&ge;]65 years, n=48) were evaluated using linear and polytomous regression, with adjustment and stratification for race, geography, Area Deprivation Index (ADI), and Multi-Environmental Exposure Index (MEEI). Spearman correlations were calculated between MRSes and observed exposures. Results: EOCRC cases were predominately Black (65.5% vs. 31.3% among LOCRC) and resided in higher-deprivation neighborhoods. We found higher odds of EOCRC associated with epigenetic exposure signatures for 2,4-D herbicide, heptachlor, coarse particulate matter (PM), Mediterranean Diet Score, and smoking, and borderline associations for fine PM and nitrogen dioxide. IOCRC was associated with signatures for 2,4-D, lindane, and obesity. Heterogeneity was observed by race and area-level factors, though associations were largely consistent across strata. ADI and MEEI were correlated with multiple pesticide and pollutant epigenetic signatures. Conclusions: In a diverse US cohort, epigenetic exposure signatures distinguish CRC cohorts, particularly EOCRC from later-onset disease, with associations consistent with but not identical to previous research. EOCRC in DANCE was characterized by higher epigenetic exposure signatures for air pollution, smoking, and distinct pesticide exposure profiles. IOCRC had overlapping characteristics with early- and late-onset and were the only group with a significant obesity signature. These findings support the hypothesis that exposome-driven epigenetic changes contribute to EOCRC risk and highlight the importance of studying diverse populations to characterize the full spectrum of environmental risk factors.

Background Timely overdose response depends not only on surveillance systems that detect overdose clusters, but also on communication pathways that deliver actionable information to the professionals positioned to respond. Understanding which overdose-related communications are received, perceived as useful, and translated into action is essential for improving overdose prevention and response infrastructure. Objective We assessed which overdose-related communication channels professionals reported receiving, which they perceived as most helpful, how organizations reported responding to overdoses or overdose clusters, and whether these patterns differed by professional role, county, and funding source. Methods We conducted an exploratory descriptive survey in 2024 using a convenience sample of professionals across Connecticut whose jobs involved overdose prevention or response (N=149). Using this survey data, we summarized reported receipt and perceived utility of overdose-related communication channels, organizational response actions, and internal receipt of Connecticut Department of Public Health overdose alerts. Results were stratified descriptively by professional role, county, and funding source. We interpreted findings using a public health communication-to-action cascade focused on signal detection, communication receipt, internal dissemination, perceived utility, and response action. Results Reported communication receipt and perceived utility differed most clearly by professional role. Peer information sharing was the most commonly reported communication source and was frequently perceived as helpful, but respondents who reported receiving formal channels such as state alerts, local alerts, or platform-based information often identified those channels as most helpful. Internal receipt of Connecticut Department of Public Health overdose alerts also varied by role. SSPs/substance use treatment programs and first responders more often reported outreach to people who use drugs, whereas government and health district respondents reported a more even mix of public communication and outreach activities. Conclusions Overdose-related communication in Connecticut appears role-dependent and unevenly distributed. Informal peer networks are widely used and perceived as helpful, while formal alert systems may require improvements to reach and actionability. Practical improvements include opt-in communication pathways tailored to professional roles, clearer access points for state and local alerts, internal dissemination protocols that specify who should receive which alerts, and alert-to-action playbooks that connect specific alert types to recommended response steps.

OBJECTIVE: To describe (1) US emergency department-treated pickleball injury burden and the injury-to-participation measure among total players, with burden among adults aged 60 to 79 years as a descriptive subgroup, and (2) determine whether general internet search interest for 'pickleball' is also associated with total pickleball-related injuries. DESIGN: Ecological time series study, United States, 2014 to 2023. DATA SOURCES: National Electronic Injury Surveillance System (NEISS) emergency department microdata yielded 1,738 adjudicated pickleball cases, 921 of them orthopedic, weighted to an estimated 101,450 injuries nationally. Google Trends, English Wikipedia pageviews, and GDELT news volume served as general pickleball attention signals, with the Trends index for 'sourdough' as a negative control. Sports and Fitness Industry Association (SFIA) participation estimates supplied a total player denominator. MAIN OUTCOME MEASURES: Annual national injury estimates with design-based 95 percent confidence intervals; injury-to-participation measures; and correlations between total pickleball-related injuries and general pickleball attention signals before and after removing trend and seasonality. RESULTS: Estimated emergency department-treated pickleball injuries rose 17.5-fold, from 1,391 in 2014 (highly unstable) to 24,294 in 2023. 70 percent of adjudicated cases involved adults aged 60 to 79. During 2017-2023, injury estimates rose 4.0-fold and participation rose about 4.4-fold. No temporal trend was detected in the injury-to-participation measure (P=0.59). Search interest looked like an excellent proxy: in annual levels it correlated with total pickleball-related injuries at R=0.96, and Pickleball Wikipedia pageviews at R=0.98. However, so did searches for "sourdough", at R=0.76. Removing trend and seasonality left little (monthly residual R=0.084; year-on-year R=0.28 over 96 months, 2015-2023), and the seasons ran opposite, with injuries peaking in February and searches in July, such that, on 12-month mean profiles, the sourdough negative control fitted the injury season (R=0.96) while pickleball ran against it (R=-0.40). General pickleball search interest and pickleball news coverage remained correlated in year-on-year changes in 2017-2023 (R=0.64), whereas their corresponding correlations with total pickleball-related injuries in 2017-2023 were 0.25 and 0.20. CONCLUSIONS: The absolute burden of emergency department-treated pickleball injury has grown substantially, but the available surveillance data cannot resolve whether the sport has become more hazardous per participant. The observed rise is consistent with growth in exposure alone. The strong correlation between search interest and injury counts was not specific, the association was substantially attenuated after detrending, and the seasonal patterns were opposed. These descriptive results do not establish that search interest can substitute for injury surveillance, and series that rise together should not be assumed to be related.

Features of urbanicity have been linked to poor psychiatric health in adulthood, but little is known about their relationship with biological age and cognition earlier in life. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we tested associations between the built environment and epigenetic ages (EpiAgeAltum, EpiAgeHorvath, EpiAgePACE) (n=2,452), brain age (n=751), and cognition (n=12,199). Analyses were replicated in Generation R and triangulated in the Millennium Cohort Study. The built environment was not associated with epigenetic ages ({beta}Altum range = 0.013-0.015, p range = .466-.689; {beta}Horvath range = -0.011-0.023, p range = .182-.728; {beta}PACE range = -0.045-0.013, p range = .131-.524) or brain age ({beta} range = 0.022-0.028, p range = .337-.429). A negative association with cognition was observed in Generation R. We provide no consistent evidence that childhood built environment exposure relates to biological age and cognition in adolescence, suggesting these relationships may emerge in later life.

PurposeTo examine the association between BMI-for-age z-score (BAZ) and BMI status with refractive error prevalence, incidence, subtypes, and quantitative refraction in Vietnamese schoolchildren. MethodsWe retrospectively analyzed body mass index and refractive error data from annual school health checks in three Vietnamese cities, 2022 to 2024. The main analysis set was restricted to children age 6 and older (49,415 examinations, 31,522 children). Refractive error subtypes and quantitative refraction came from a Hanoi autorefractor sub-cohort (13,059 examinations). We used sex-stratified Poisson models with generalized estimating equations, adjusted for age, city, and year, plus linear mixed models for quantitative outcomes. ResultsAny refractive error followed a U shaped curve across BAZ in both sexes, significant in girls (prevalence ratio 1.01 per 1-SD BAZ, p = 0.027) but not boys (p = 0.099). Obesity was associated with higher any refractive error prevalence in girls (adjusted prevalence ratio 1.05, p = 0.017). Astigmatism was associated with BAZ in both sexes (p < 0.001), anisometropia in boys only (p < 0.001), with no association for myopia or hyperopia. Spherical equivalent shifted slightly toward hyperopia, not myopia, with higher BAZ. A supplementary check over 1 to 2 years found no evidence that prior BAZ predicted new refractive error onset (prevalence ratio 1.02, p > 0.6 in both sexes), and the nonlinear pattern did not reappear. ConclusionsAdiposity relates cross-sectionally to refractive error in a nonlinear, sex specific way concentrated in astigmatism and anisometropia rather than myopia, though this did not hold up short term.

Background: Retirement is a major life transition that may influence cognitive aging. Retirement pathways are becoming increasingly diversified, yet evidence on how heterogeneous retirement trajectories relate to dementia risk remains limited. This study used sequence and cluster analysis to characterize thousands of transition-to-retirement trajectories, including retirement timing and work intensity, to estimate associations with dementia risk. Methods: We used data from 13,879 participants in the U.S. Health and Retirement Study. Our exposure was transition-to-retirement trajectories between ages 51 and 75 identified using sequence and cluster analysis. Our outcome was a validated algorithmically derived dementia probability measure. We estimated associations between trajectory clusters and dementia risk beginning at age 76 using generalized estimating equations, adjusting for sociodemographic characteristics. Inverse probability weights were used to account for attrition. Results: We identified ten distinct transition-to-retirement trajectories characterized by differences in timing of retirement, part-time work, disability, and labor force attachment. Compared with individuals retiring after full-time work in their early-to-mid 60s, dementia risk was similar among those retiring earlier or later from full-time work. In contrast, individuals with sustained part-time employment between ages 51 and 75 had lower odds of dementia (OR: 0.62, 95% CI: 0.48, 0.80), while trajectories characterized by prolonged disability were associated with higher odds of dementia (OR: 1.53, 95% CI: 1.22, 1.91). Conclusions: Retirement timing alone showed limited association with later-life dementia risk, whereas sustained part-time employment and disability-related trajectories were more strongly associated with dementia risk. These findings suggest that employment intensity and health-related exit from the labor force may be more relevant for dementia risk than retirement timing, and that gradual and flexible work-to-retirement transitions may benefit brain health. Background: Retirement is a major life transition that may influence cognitive aging. Retirement pathways are becoming increasingly diversified, yet evidence on how heterogeneous retirement trajectories relate to dementia risk remains limited. This study used sequence and cluster analysis to characterize thousands of transition-to-retirement trajectories, including retirement timing and work intensity, to estimate associations with dementia risk. Methods: We used data from 13,879 participants in the U.S. Health and Retirement Study. Our exposure was transition-to-retirement trajectories between ages 51 and 75 identified using sequence and cluster analysis. Our outcome was a validated algorithmically derived dementia probability measure. We estimated associations between trajectory clusters and dementia risk beginning at age 76 using generalized estimating equations, adjusting for sociodemographic characteristics. Inverse probability weights were used to account for attrition. Results: We identified ten distinct transition-to-retirement trajectories characterized by differences in timing of retirement, part-time work, disability, and labor force attachment. Compared with individuals retiring after full-time work in their early-to-mid 60s, dementia risk was similar among those retiring earlier or later from full-time work. In contrast, individuals with sustained part-time employment between ages 51 and 75 had lower odds of dementia (OR: 0.62, 95% CI: 0.48, 0.80), while trajectories characterized by prolonged disability were associated with higher odds of dementia (OR: 1.53, 95% CI: 1.22, 1.91). Conclusions: Retirement timing alone showed limited association with later-life dementia risk, whereas sustained part-time employment and disability-related trajectories were more strongly associated with dementia risk. These findings suggest that employment intensity and health-related exit from the labor force may be more relevant for dementia risk than retirement timing, and that gradual and flexible work-to-retirement transitions may benefit brain health.

Nitrogen dioxide (NO2) is a widespread air pollutant associated with the risk and prevalence of various respiratory infectious diseases. Epidemiological studies have reported associations between NO2 exposure and COVID-19 incidence, and biological evidence indicates that NO2 exposure increases vulnerability to infection. Motivated by these findings and by the scarcity of mechanistic epidemic models that incorporate air pollutant data, here we introduce an NO2- and mobility-informed metapopulation model and study the first COVID-19 wave in Oklahoma. County-level NO2 concentrations enter the infection rates through a first-order parameterization, alongside high-resolution mobility patterns capturing heterogeneous inter-county connectivity. Using numerical simulations, we demonstrate that higher environmental sensitivity produces earlier and more synchronized outbreaks across counties, while lower sensitivity yields delayed, asynchronous trajectories. When fitted to county-level COVID-19 incidence data, our model outperformed the classic SIR model (fitted independently in each county) in over 75% of counties in Oklahoma across all standard error metrics. The improvements were even more pronounced in forecasting tasks across epidemic stages, with county-level win rates against the SIR model of 59.74% (surge), 87.01% (peak), 80.52% (post-peak), and 88.31% (decline) by nRMSE. To isolate the contribution of NO2, we compared our model against a mobility-only model with NO2 removed and homogeneous infection rates across counties. The NO2 term improved county-level forecasts during the surge (94.81% of counties by nRMSE), post-peak (88.31%), and peak (62.34%) stages, though not during the early and decline stages, suggesting that NO2 information can generate better forecasts than mobility alone during periods of high incidence. Our results demonstrate that environmental exposure can enter the transmission structure of a mechanistic epidemic model directly and that doing so yields measurable forecasting gains.

Background Under-five mortality remains a major public health challenge in Zambia despite substantial reductions over recent decades. Demographic and Health Survey (DHS) data are commonly analysed using Cox proportional hazards models; however, violations of the proportional hazards assumption and unobserved cluster-level heterogeneity may compromise inference. This study compared advanced survival modelling approaches to determine the most appropriate framework for analysing under-five mortality using pooled Zambia DHS data. Methods We conducted a pooled secondary analysis of the 2018 and 2024 Zambia Demographic and Health Survey child recode datasets. The analysis included 9,982 children, among whom 266 died before their fifth birthday. A survey-weighted Cox proportional hazards model was fitted as the reference model and assessed using Schoenfeld residual diagnostics. To address identified methodological limitations, an extended Cox model, a shared-frailty model, and a Bayesian survival model were subsequently fitted. Model performance, assumptions, and the consistency of adjusted hazard ratio estimates were compared across modelling approaches. Results The global Schoenfeld test indicated violation of the proportional hazards assumption ({chi}2=51.26, p=0.002). In the adjusted extended Cox model, male children had higher mortality risk than females (aHR 1.95, 95% CI 1.40-2.73), while children with gestation [&ge;]9 months had lower mortality risk than those with shorter gestation (aHR 0.21, 95% CI 0.14-0.32). Average and large birth size were associated with lower mortality compared with small birth size (aHR 0.47, 95% CI 0.34-0.66 and aHR 0.57, 95% CI 0.39-0.84, respectively). Newborn health checks before discharge were associated with lower mortality (aHR 0.50, 95% CI 0.38-0.66), as was any antenatal care (aHR 0.25, 95% CI 0.09-0.75). A high-risk fertility pattern involving fourth or higher births with an interval [&ge;]24 months was also associated with lower mortality (aHR 0.57, 95% CI 0.41-0.80). The shared-frailty model produced similar estimates, including increased mortality among male children (aHR 1.39, 95% CI 1.08-1.78) and twins or multiple births (aHR 2.74, 95% CI 1.36-5.53). Bayesian estimates were broadly consistent with the extended Cox model. Conclusions Advanced survival models provided a more robust analytical framework than the conventional Cox model for evaluating under-five mortality in nationally representative DHS data. While the extended Cox model accommodated time-varying effects, the shared-frailty model captured unobserved cluster-level heterogeneity, and the Bayesian model confirmed the stability of parameter estimates. Incorporating these complementary approaches can improve the validity of survival analyses and strengthen evidence for child survival research and policy in low- and middle-income settings.

Background Attentional control declines with normal aging, yet the role of modifiable lifestyle factors in accelerating this decline remains incompletely characterised in large, diverse populations. We examined associations between four modifiable risk factors (smoking intensity, alcohol binge drinking, social satisfaction and blood pressure) and sustained attention performance in 13,866 adults drawn from the All of Us Research Program. Methods Cognitive performance was assessed using the Gradual-Onset Continuous Performance Task (GradCPT). A composite cognitive efficiency score was derived via principal component analysis of four GradCPT metrics: d' (perceptual sensitivity), response criterion, median reaction time and reaction time variability. Associations between cognitive efficiency and each risk factor were examined using multiple linear regression adjusted for age, sex and race/ethnicity. Effect sizes were expressed as age-equivalent years of cognitive aging (age-equivalent years = regression coefficient for the risk factor divided by the regression coefficient for age) to aid clinical interpretation. Results GradCPT performance declined progressively with age (p < 0.001). Social satisfaction emerged as the strongest lifestyle predictor: low social satisfaction was associated with approximately 5.8 additional age-equivalent years of cognitive aging relative to high social satisfaction. Smoking showed a dose-response pattern, with heavy smokers (> 20 cigarettes/day) exhibiting an approximately 5-year age-equivalent deficit versus never-smokers. Stage 2 hypertension showed a modest, non-significant negative association. Binge drinking showed limited significant associations, likely complicated by survivor and abstainer biases. Bootstrapped analyses of combined exposures showed that combinations of risk factors, particularly those involving low social satisfaction, produced larger cognitive deficits than expected under an additive model. Conclusions These findings support an interactive rather than a purely additive model of lifestyle-related cognitive vulnerability and highlight the GradCPT as a subclinical measure of attention-based cognitive risk in non-clinical populations. Keywords Cognitive aging, Sustained attention, GradCPT, Modifiable risk factors, Social isolation, Smoking, Hypertension, All of Us Research Program

Objective: To examine associations of health insurance status, household income, and cost-related healthcare barriers with receipt of a routine medical checkup among U.S. adults. Methods: This cross-sectional study analyzed 2024 Behavioral Risk Factor Surveillance System data. Survey-weighted descriptive estimates and multivariable logistic regression incorporated sampling weights, strata, and primary sampling units. The outcome was a routine medical checkup within the previous 12 months. Results: Among 321,592 complete cases, 78.0% of U.S. adults reported a recent routine checkup. Cost-related barriers (adjusted odds ratio [AOR], 0.56; 95% confidence interval [CI], 0.54-0.57) and uninsurance (AOR, 0.28; 95% CI, 0.27-0.29) were associated with lower checkup utilization. Lower household-income groups generally had lower adjusted odds than adults with incomes of $200,000 or more. Conclusions: Insurance, income, and reported cost barriers were independently associated with routine checkup utilization. Findings are descriptive and do not establish causal effects. Keywords: health insurance; household income; cost-related barriers; routine medical checkup; healthcare utilization; BRFSS

Background: Long-term mortality data among Brazilian police officers and firefighters are scarce. This study investigated the leading causes of death in Brazilian male military police officers and firefighters over three decades, comparing their mortality and mean age at death with those of the male population. Methods: We retrospectively analyzed death records of male military police officers and firefighters from Espirito Santo (ES), Brazil, from 1988 to 2019. Mortality was analyzed across three decades and the standardized mortality ratios (SMRs) for the three leading causes were calculated using the male populations of ES and Brazil as references. Results: Overall, 2,198 deaths were identified, with a mean age at death of 59 {+/-} 18.5 years, compared with 60.5 {+/-} 23.9 years among men in ES and 63.4 {+/-} 23.7 years among Brazilian men. Mean age at death was 36 {+/-} 9 years among active-duty and 68 {+/-} 13 years among inactive personnel. Across the study population, the leading causes of death were circulatory system diseases (32%), external causes (26%) and neoplasms (15%). Circulatory disease mortality was higher in the second and third decades compared with both reference populations, whereas external-cause mortality shifted from higher, in the first two decades, to lower than expected in the last decade. Neoplasm mortality was higher relative to Brazil only in the last decade. Conclusion: Mortality patterns differed by cause and over time. The younger mean age at death among active-duty personnel, together with cause-specific excess mortality, highlights the importance of long-term occupational health surveillance and preventive strategies.

Background: Cardiovascular disease is an important competing cause of death in men with metastatic prostate cancer, and ambient air pollution may increase cardiovascular vulnerability. We evaluated associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with all-cause, cardiovascular, and prostate cancer-specific mortality, including joint associations with androgen deprivation therapy (ADT). Methods: We analyzed 33,384 men from 11 US state registries diagnosed with metastatic prostate cancer during 2000-2015 and followed through 2018. Residential PM2.5 and NO2 concentrations at diagnosis were assigned using 1-km exposure models. Multivariable Cox models estimated all-cause mortality, and inverse-probability-weighted Cox models assessed cause-specific mortality. Results: Each interquartile-range increase in PM2.5 was associated with higher cardiovascular mortality (HR 1.04, 95% CI 1.02-1.07; p-trend=0.008). Cardiovascular mortality was also higher in the fourth and fifth PM2.5 quintiles versus the first (HR 1.18 and 1.21, respectively). Higher NO2 was associated with prostate cancer-specific mortality in the highest quintile (HR 1.07, 95% CI 1.01-1.13). In joint analyses, ADT-treated men with high versus low PM2.5 exposure had higher cardiovascular mortality (HR 1.19, 95% CI 1.05-1.34), without clear evidence of effect modification (p-interaction=0.051). Conclusions: In men with metastatic prostate cancer, higher PM2.5 exposure was associated with cardiovascular mortality, particularly among ADT-treated patients, supporting further study of environmental exposures and systemic therapy in cardio-oncology.

Abstract: Background: Children born very preterm (VPT) are at elevated risk for adverse neurobehavioral outcomes and are vulnerable to environmental exposures. We used untargeted metabolomics analysis to identify environmentally relevant metabolites associated with childhood behavioral problems and to characterize related endogenous metabolic pathways. Methods: We studied 226 children born <30 weeks gestation in a multi-site cohort study. Urine collected at age 4 was profiled using untargeted ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). Associations between 30 exogenous environmental metabolites and behavioral problems score at age 4 were evaluated cross-sectionally using multivariable linear regression, followed by metabolome-wide association and pathway enrichment analyses. Results: Three exogenous metabolites were nominally associated with child behavior problems. Specifically, 2-(Acetylamino)-3-( henylthiol)propanoic acid was positively associated with overall ({beta}=1.42, p=0.006), externalizing ({beta}=1.50, p=0.006), and internalizing ({beta}=1.34, p=0.021) behavior problems. Diethofencarb was positively associated with overall ({beta}=0.34, p=0.018) and externalizing ({beta}=0.39, p=0.010) behavior problems, while protocatechuic acid was inversely associated with internalizing problems ({beta}=-0.68, p=0.027). No associations remained significant after false discovery rate (FDR) correction. Nevertheless, these metabolites were associated with 151, 131, and 530 endogenous metabolic features, respectively, at FDR<0.05, highlighting perturbations in lipid metabolism, mitochondrial energetics, inflammatory signaling, amino acid metabolism, and neuroactive pathways. Conclusions: Environmental metabolites associated with behavior problems were linked to broad endogenous metabolic differences relevant to neurodevelopment. These findings highlight potentially modifiable environmental influences, including exposures related to combustion-derived pollutants, pesticides, and dietary sources, that may contribute to behavioral vulnerability among children born very preterm

Background: Maternal cigarette smoking is associated with adverse birth outcomes, but low birthweight may reflect preterm delivery, restricted fetal growth, or both. Contemporary evidence distinguishing smoking trajectories is limited. Objectives: To examine associations between maternal cigarette-smoking trajectories and low birthweight among U.S.-resident singleton live births in 2023 to 2024. Methods: We analyzed 5,861,166 U.S.-resident singleton live births in the 2023 to 2024 National Vital Statistics System natality files. Low birthweight was defined as birthweight <2,500 g. Trajectories were never smoking, quitting before pregnancy, quitting during pregnancy, persistent smoking, or other/intermittent smoking. Modified Poisson regression estimated adjusted risk ratios (aRRs) and 95% confidence intervals controlling for birth year and maternal, pregnancy, and infant characteristics. Results: Low-birthweight prevalence was 6.4% among never smokers, 7.7% among mothers who quit before pregnancy, 11.2% among those who quit during pregnancy, 14.6% among persistent smokers, and 10.2% among those with other/intermittent smoking. Compared with never smoking, adjusted risks were higher for quitting before pregnancy (aRR 1.06, 95% CI 1.03, 1.09), quitting during pregnancy (aRR 1.46, 95% CI 1.42, 1.51), persistent smoking (aRR 1.95, 95% CI 1.93, 1.98), and other/intermittent smoking (aRR 1.36, 95% CI 1.25, 1.49). Associations varied little by year (joint interaction P = 0.102). Conclusions: Persistent smoking showed the strongest association with low birthweight. Because the outcome combines preterm delivery and impaired fetal growth, the estimates should not be interpreted as associations with fetal growth restriction alone. Keywords Cigarette Smoking; Smoking Cessation; Pregnancy; Low Birthweight; Birthweight; United States

Coal-fired power plants remain a major source of fine particulate matter (PM2.5) exposure and mortality in the United States. Announced retirement dates mark when those burdens are expected to end, but rising electricity demand, partly from data centers supporting cloud computing and artificial intelligence, has led utilities and regulators to revisit them. Of 50 coal plants scheduled in January 2024 to retire before 2035, 20 had later or removed dates by January 2026. Projecting coal PM2.5 and mortality among Medicare beneficiaries from the 20 plants for 2026-2035, we estimate the revised schedule would result in 1,256 additional deaths (1,136 to 1,376), raising mortality to 3.1 times the original burden. Eighteen plants operate in balancing authorities with hyperscale data-center demand, and federal orders and utility filings supporting several plants' operation cited data-center growth. Retirement schedules are revised faster than health consequences are assessed, and those delays carry a measurable mortality cost.

Objective: To identify factors associated with predischarge morbidity and mortality among small for gestational age infants. Study Design: We conducted a retrospective single-center cohort study of small for gestational age infants admitted to a level IV neonatal intensive care unit. We determined the association of clinical characteristics, congenital anomalies, and genetic disorders with the primary outcome of predischarge morbidity or mortality and characterized morbidity and mortality across congenital anomaly subgroups. Results: Among 293 small for gestational age infants, 18 (6.1%) had a genetic disorder and 103 (35.2%) had a major congenital anomaly, with congenital heart disease (CHD) representing the largest subgroup. The primary outcome of morbidity or mortality occurred in 93 infants (31.7%); 74 infants (25.3%) experienced morbidity and 19 (6.5%) died. CHD (adjusted odds ratio [aOR]: 16.5, 95% CI 6.44-45.7) and multiple congenital anomalies (aOR: 17.8, 95% CI 4.64-71.1) were found to be strongly associated with morbidity or mortality, after accounting for sex, maternal race, and intubation > 7 days. Statistically significant associations were also found with the presence of musculoskeletal anomalies as well as genetic disorders in infants without congenital anomalies, though in limited sample sizes. CHD was the largest contributor to morbidity, whereas multiple congenital anomalies accounted for the greatest proportion of mortality. Infants with abdominal wall defects and central nervous system anomalies experienced no morbidity or mortality. Conclusion: Congenital heart disease and multiple congenital anomalies were strongly associated with morbidity and mortality among SGA infants, whereas the degree of SGA alone was not. These findings suggest that risk is not explained by the degree of SGA alone and may be more strongly associated with congenital disease and other underlying factors.

Background: Cervical cancer (CC), mostly associated with high-risk human papillomaviruses (hrHPV) infection, is the most common cancer that disproportionately affects women in developing countries, including Ethiopia. Early detection of CC and initiation of treatment are key to positive health outcomes. Identifying factors associated with delayed CC diagnosis is essential for effective prevention and control efforts. This study assessed the stage at diagnosis and examined associated clinical and sociodemographic factors. Methods: An institution-based cross-sectional study was conducted among 284 women newly diagnosed with CC who attended Tibebe Ghion Specialized Hospital (TGSH) between 1st January 2021 and 31st December 2022. A structured questionnaire was used to collect data on the participants' demographic, reproductive, and gynaecologic history, and clinical profiles. The CC stage at diagnosis was categorised as early (stage I-IIA) or late (stage IIB-IV). Logistic regression models (unadjusted and adjusted) were used to examine associations of sociodemographic or clinical factors with stage at CC diagnosis. Results: The mean age ({+/-}standard deviation) at presentation was 53.2 {+/-} 11.3 years, with an age range of 18 - 80 years. Most of the patients (73.6%) were from rural areas, and three-fifths (58.1%) had no medical insurance. Among participants, 74.6% (95% CI: 69.4, 79.6%) had late-stage CC. The odds of late-stage CC diagnosis were higher for women from rural areas (AOR: 2.21; 95% CI:1.18, 4.12; p<0.013), and those with anaemia (defined as <12 mg/dl haemoglobin) (AOR: 3.42; 95% CI: 1.88, 6.23; p<0.001). On the other hand, the odds of late-stage CC diagnosis were lower in HIV positive women (AOR:0.41; 95%CI:0.19, 0.88; p<0.021). Conclusion: The proportion of late-stage diagnosis among CC patients was high. Residential area, anaemia status, and HIV serostatus were factors associated with stage at CC diagnosis. These findings can inform screening efforts of CC and call for expanding of the screening services to the rural setting in order to reduce the burden of late-stage CC diagnosis.

Abstract Objective: Examine whether prenatal adversity is associated with Neonatal Opioid Withdrawal Syndrome (NOWS) severity and the need for pharmacological treatment in infants with prenatal opioid exposure. Study Design: Prospective cohort study of 235 infants from a multi-center study of infants with prenatal opioid exposure. Maternal factors were assessed using the electronic medical record and maternal questionnaires. Latent Class Analysis (LCA) was used to derive mutually exclusive prenatal adversity groups. Results: A 3-class LCA solution provided the best fit to the data and showed 3 distinct groups: one low adversity group (Class 3, 38.7%) and 2 high adversity groups. Infants born to mothers with elevated demographic, medical, polysubstance, and mental health risk factors (Class 1, 31.9%) were more likely to require pharmacological treatment for NOWS (OR=7.70, 95% CI: 3.65-17.14) and had higher NOWS severity, as indexed by longer length of stay ({beta} = 6.08, 95% CI: 4.09-8.07), and higher maximum Finnegan scores ({beta} = 2.62, 95% CI: 1.49-3.76). Infants born to mothers with elevated medical and polysubstance risk factors (Class 2, 29.4%) were also more likely to receive pharmacological treatment for NOWS (OR=3.22, 95% CI: 1.56-6.78) and had higher NOWS severity, as indexed by higher likelihood of receiving adjunctive medication (OR=3.62, 95% CI: 1.11-12.99). Conclusion: Maternal sociodemographic, mental health, substance use, and medical adversity may serve as an early marker of NOWS severity and may aid in the prediction of which neonates will require pharmacological treatment for NOWS. Early identification of infants at high risk for NOWS could lead to earlier treatment and the potential to reduce NOWS severity, length of stay, and associated healthcare costs.