Multivariate Cluster Point Process to Quantify and Explore Multi-Entity Configurations: Application to Biofilm Image Data.

Clusters of similar or dissimilar objects are encountered in many fields. Frequently used approaches treat each cluster's central object as latent. Yet, often objects of one or more types cluster around objects of another type. Such arrangements are common in biomedical images of cells, in which nearby cell types likely interact. Quantifying spatial relationships may elucidate biological mechanisms. Parent-offspring statistical frameworks can be usefully applied even when central objects ("parents") differ from peripheral ones ("offspring"). We propose the novel multivariate cluster point process (MCPP) to quantify multi-object (e.g., multi-cellular) arrangements. Unlike commonly used approaches, the MCPP exploits locations of the central parent object in clusters. It accounts for possibly multilayered, multivariate clustering. The model formulation requires specification of which object types function as cluster centers and which reside peripherally. If such information is unknown, the relative roles of object types may be explored by comparing fit of different models via the deviance information criterion (DIC). In simulated data, we compared a series of models' DIC; the MCPP correctly identified simulated relationships. It also produced more accurate and precise parameter estimates than the classical univariate Neyman-Scott process model. We also used the MCPP to quantify proposed configurations and explore new ones in human dental plaque biofilm image data. MCPP models quantified simultaneous clustering of Streptococcus and Porphyromonas around Corynebacterium and of Pasteurellaceae around Streptococcus and successfully captured hypothesized structures for all taxa. Further exploration suggested the presence of clustering between Fusobacterium and Leptotrichia, a previously unreported relationship.

Signs of Potential Androgen Excess Across the Lifespan in a US-based Digital Cohort Study.

CONTEXT: Androgen excess (AE)-related symptoms can vary widely and may appear across the life course. OBJECTIVE: We assessed the prevalence of signs of potential AE and heterogeneity by demographic/health characteristics. METHODS: We used data of 24 435 participants who consented and enrolled during November 2019 to December 2022 in a US digital cohort to evaluate the prevalence and heterogeneity of self-reported signs of potential AE: possible hirsutism (having thick coarse hair on ≥4 of 8 body locations), hair level on the chin, hair loss on top of the head, and moderate to severe acne. RESULTS: The prevalence of possible hirsutism, having several/a lot of hair on the chin, significantly reduced hair/visible scalp on top of the head, and moderate to severe acne were 6.9%, 12.6%, 1.7%, and 31.8%, respectively. While possible hirsutism and moderate to severe acne decreased with age (range: 18-86 years), hair on the chin and hair loss on the head increased with age. Participants who self-identified as Hispanic or South Asian reported a higher prevalence of possible hirsutism (11.2%, 16.9%, vs 6.3% among non-Hispanic White participants). Participants with higher body mass index had a higher prevalence of possible hirsutism. Moderate to severe acne was more common among those with polycystic ovary syndrome. Possible hirsutism and hair loss were less common among participants using hormones for contraception. CONCLUSION: In this large cohort, signs of potential AE varied by demographic and health factors. These results could provide a new understanding of how potential AE may appear differently in diverse groups, informing future work to develop more inclusive evaluation at a population level.

A BAYESIAN HIERARCHICAL SMALL AREA POPULATION MODEL ACCOUNTING FOR DATA SOURCE SPECIFIC METHODOLOGIES FROM AMERICAN COMMUNITY SURVEY, POPULATION ESTIMATES PROGRAM, AND DECENNIAL CENSUS DATA.

Small area population counts are necessary for many epidemiological studies, yet their quality and accuracy are often not assessed. In the United States, small area population counts are published by the United States Census Bureau (USCB) in the form of the decennial census counts, intercensal population projections (PEP), and American Community Survey (ACS) estimates. Although there are significant relationships between these three data sources, there are important contrasts in data collection, data availability, and processing methodologies such that each set of reported population counts may be subject to different sources and magnitudes of error. Additionally, these data sources do not report identical small area population counts due to post-survey adjustments specific to each data source. Consequently, in public health studies, small area disease/mortality rates may differ depending on which data source is used for denominator data. To accurately estimate annual small area population counts and their associated uncertainties, we present a Bayesian population (BPop) model, which fuses information from all three USCB sources, accounting for data source specific methodologies and associated errors. We produce comprehensive small area race-stratified estimates of the true population, and associated uncertainties, given the observed trends in all three USCB population estimates. The main features of our framework are: (1) a single model integrating multiple data sources, (2) accounting for data source specific data generating mechanisms and specifically accounting for data source specific errors, and (3) prediction of population counts for years without USCB reported data. We focus our study on the Black and White only populations for 159 counties of Georgia and produce estimates for years 2006-2023. We compare BPop population estimates to decennial census counts, PEP annual counts, and ACS multi-year estimates. Additionally, we illustrate and explain the different types of data source specific errors. Lastly, we compare model performance using simulations and validation exercises. Our Bayesian population model can be extended to other applications at smaller spatial granularity and for demographic subpopulations defined further by race, age, and sex, and/or for other geographical regions.

Epigenetic Aging and Racialized, Economic, and Environmental Injustice: NIMHD Social Epigenomics Program.

Importance: Epigenetic age acceleration is associated with exposure to social and economic adversity and may increase the risk of premature morbidity and mortality. However, no studies have included measures of structural racism, and few have compared estimates within or across the first and second generation of epigenetic clocks. Objective: To determine whether epigenetic age acceleration is positively associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design, Setting, and Participants: This cross-sectional study used data from the My Body My Story (MBMS) study between August 8, 2008, and December 31, 2010, and examination 5 of the Multi-Ethnic Atherosclerosis Study (MESA) from April 1, 2010, to February 29, 2012. In the MBMS, DNA extraction was performed in 2021; linkage of structural measures to the MBMS and MESA, in 2022. US-born individuals were randomly selected from 4 community health centers in Boston, Massachusetts (MBMS), and 4 field sites in Baltimore, Maryland; Forsyth County, North Carolina; New York City, New York; and St Paul, Minnesota (MESA). Data were analyzed from November 13, 2021, to August 31, 2023. Main Outcomes and Measures: Ten epigenetic clocks (6 first-generation and 4 second-generation), computed using DNA methylation data (DNAm) from blood spots (MBMS) and purified monocytes (MESA). Results: The US-born study population included 293 MBMS participants (109 men [37.2%], 184 women [62.8%]; mean [SD] age, 49.0 [8.0] years) with 224 Black non-Hispanic and 69 White non-Hispanic participants and 975 MESA participants (492 men [50.5%], 483 women [49.5%]; mean [SD] age, 70.0 [9.3] years) with 229 Black non-Hispanic, 191 Hispanic, and 555 White non-Hispanic participants. Of these, 140 (11.0%) exhibited accelerated aging for all 5 clocks whose estimates are interpretable on the age (years) scale. Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 (95% CI, 0.003-0.27) SDs and with birth state conservatism by 0.06 (95% CI, 0.01-0.12) SDs, pooling across all clocks. Low parental educational level was associated with epigenetic age acceleration, pooling across all clocks, for both Black non-Hispanic (0.24 [95% CI, 0.08-0.39] SDs) and White non-Hispanic (0.27 [95% CI, 0.03-0.51] SDs) MBMS participants. Adult impoverishment was positively associated with the pooled second-generation clocks among the MESA participants (Black non-Hispanic, 0.06 [95% CI, 0.01-0.12] SDs; Hispanic, 0.07 [95% CI, 0.01-0.14] SDs; White non-Hispanic, 0.05 [95% CI, 0.01-0.08] SDs). Conclusions and Relevance: The findings of this cross-sectional study of MBMS and MESA participants suggest that epigenetic age acceleration was associated with racialized and economic injustice, potentially contributing to well-documented inequities in premature mortality. Future research should test the hypothesis that epigenetic accelerated aging may be one of the biological mechanisms underlying the well-documented elevated risk of premature morbidity and mortality among social groups subjected to racialized and economic injustice.

Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using PM2.5 in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016).

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between PM2.5 during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily PM2.5 was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM2.5 concentration was relatively stable across pregnancy at ∼7µg/m3. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5)] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

Residential radon decay products are associated with cough and phlegm in patients with COPD.

Radon decay products attach to particulate matter (referred to as particle radioactivity, PR) has been shown to be potential to promote airway damage after inhalation. In this study, we investigated associations between PR with respiratory symptoms and health-related quality of life (HRQL) in patients with COPD. 141 male patients with COPD, former smokers, completed the St. George's Respiratory Questionnaire (SGRQ) after up to four 1-week seasonal assessments (N=474) of indoor (home) and ambient (central site) particulate matter ≤ 2.5 µm in diameter (PM2.5) and black carbon (BC). Indoor PR was measured as α-activity (radiation) on PM2.5 filter samples. The ratio of indoor/ambient sulfur in PM2.5 (a ventilation surrogate) was used to estimate α-PR from indoor radon decay. SGRQ responses assessed frequent cough, phlegm, shortness of breath, wheeze, and chest attacks in the past 3 months. Multivariable linear regression with generalized estimating equations accounting for repeated measures was used to explore associations, adjusting for potential confounders. Median (IQR) indoor α-PR was 1.22 (0.62) mBq/m3. We found that there were positive associations between α-PR with cough and phlegm. The strongest associations were with estimated α-PR of indoor origin for cough (31.1 % increase/IQR, 95 %CI: 8.8 %, 57.8 %), and was suggestive for phlegm (13.0 % increase/IQR, 95 %CI: -2.5 %, 31.0 %), similar adjusting for indoor BC or PM2.5. α-PR of indoor origin was positively associated with an increase in SGRQ Symptoms score [1.2 units/IQR; 95 %CI: -0.3, 2.6] that did not meet conventional levels of statistical significance. Our results suggested that exposure to indoor radon decay products measured as particle radioactivity, a common indoor exposure, is associated with cough, and suggestively associated with phlegm and worse HRQL symptoms score in patients with COPD.

Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution.

Children's health studies support an association between maternal environmental exposures and children's birth outcomes. A common goal is to identify critical windows of susceptibility-periods during gestation with increased association between maternal exposures and a future outcome. The timing of the critical windows and magnitude of the associations are likely heterogeneous across different levels of individual, family, and neighborhood characteristics. Using an administrative Colorado birth cohort we estimate the individualized relationship between weekly exposures to fine particulate matter (PM 2.5) during gestation and birth weight. To achieve this goal, we propose a statistical learning method combining distributed lag models and Bayesian additive regression trees to estimate critical windows at the individual level and identify characteristics that induce heterogeneity from a high-dimensional set of potential modifying factors. We find evidence of heterogeneity in the PM 2.5 -birth weight relationship, with some mother-child dyads showing a 3 times larger decrease in birth weight for an IQR increase in exposure (5.9 to 8.5 PM 2.5 µg/m3) compared to the population average. Specifically, we find increased vulnerabilitity for non-Hispanic mothers who are either younger, have higher body mass index or lower educational attainment. Our case study is the first precision health study of critical windows.

The Legacy of Redlining: Increasing Childhood Asthma Disparities Through Neighborhood Poverty.

RATIONALE: Identifying the root causes of racial disparities in childhood asthma is critical for health equity. OBJECTIVES: To determine if the 1930's racist policy of redlining led to present-day disparities in childhood asthma by increasing community-level poverty and decreasing neighborhood socioeconomic position (SEP). METHODS: We categorized census tracts at birth of participants from the Children's Respiratory and Environmental Workgroup birth cohort consortium into A, B, C, or D categories as defined by the Home Owners Loan Corporation (HOLC), with D being the highest perceived risk. Surrogates of present-day neighborhood-level SEP were determined for each tract including the percentage of low-income households, the CDC's social vulnerability index (SVI), and other tract-level variables. We performed causal mediation analysis, which, under the assumption of no unmeasured confounding, estimates the direct and mediated pathways by which redlining may cause asthma disparities through census tract-level mediators adjusting for individual-level covariates. MEASUREMENTS AND MAIN RESULTS: Of 4,849 children, the cumulative incidence of asthma through age 11 was 26.6% and 13.2% resided in census tracts with a HOLC grade of D. In mediation analyses, residing in grade D tracts (aOR = 1.03 [95%CI 1.01,1.05]) was significantly associated with childhood asthma, with 79% of this increased risk mediated by percentage of low-income households; results were similar for SVI and other tract-level variables. CONCLUSIONS: The historical structural racist policy of redlining led to present-day asthma disparities in part through decreased neighborhood SEP. Policies aimed at reversing the effects of structural racism should be considered to create more just, equitable, and healthy communities.

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

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

Menarche and Time to Cycle Regularity Among Individuals Born Between 1950 and 2005 in the US.

Importance: Early menarche is associated with adverse health outcomes. Trends toward earlier menarche have been observed in the US, but data remain limited on differences by sociodemographic factors and body mass index (BMI). Time from menarche to cycle regularity is another understudied early-life characteristic with health implications. Objectives: To evaluate the temporal trends and disparities in menarche and time to regularity and explore early-life BMI as a mediator. Design, Setting, and Participants: This ongoing cohort study enrolled participants from an ongoing mobile application-based US cohort from November 14, 2019, to March 20, 2023. Exposures: Birth year (categorized as 1950-1969, 1970-1979, 1980-1989, 1990-1999, and 2000-2005). Main Outcomes and Measures: Main outcomes were age at menarche and time to regularity, which were self-recalled at enrollment. In addition, early (aged <11 years), very early (aged <9 years), and late (aged ≥16 years) age at menarche was assessed. Results: Among the 71 341 female individuals who were analyzed (mean [SD] age at menarche, 12.2 [1.6] years; 2228 [3.1%] Asian, 3665 [5.1%] non-Hispanic Black, 4918 [6.9%] Hispanic, 49 518 [69.4%] non-Hispanic White, and 8461 [11.9%] other or multiple races or ethnicities), 5223 were born in 1950 to 1969, 12 226 in 1970 to 1979, 22 086 in 1980 to 1989, 23 894 in 1990 to 1999, and 7912 in 2000 to 2005. The mean (SD) age at menarche decreased from 12.5 (1.6) years in 1950 to 1969 to 11.9 (1.5) years in 2000 to 2005. The number of individuals experiencing early menarche increased from 449 (8.6%) to 1223 (15.5%), the number of individuals experiencing very early menarche increased from 31 (0.6%) to 110 (1.4%), and the number of individuals experiencing late menarche decreased from 286 (5.5%) to 137 (1.7%). For 61 932 participants with reported time to regularity, the number reaching regularity within 2 years decreased from 3463 (76.3%) to 4075 (56.0%), and the number not yet in regular cycles increased from 153 (3.4%) to 1375 (18.9%). The magnitude of the trend toward earlier menarche was greater among participants who self-identified as Asian, non-Hispanic Black, or other or multiple races (vs non-Hispanic White) (P = .003 for interaction) and among participants self-rated with low (vs high) socioeconomic status (P < .001 for interaction). Within a subset of 9865 participants with data on BMI at menarche, exploratory mediation analysis estimated that 46% (95% CI, 35%-61%) of the temporal trend in age at menarche was explained by BMI. Conclusions and Relevance: In this cohort study of 71 341 individuals in the US, as birth year increased, mean age at menarche decreased and time to regularity increased. The trends were stronger among racial and ethnic minority groups and individuals of low self-rated socioeconomic status. These trends may contribute to the increase in adverse health outcomes and disparities in the US.

Irregular Cycles, Ovulatory Disorders, and Cardiometabolic Conditions in a US-Based Digital Cohort.

Importance: Polycystic ovary syndrome (PCOS), characterized by irregular menstrual cycles and hyperandrogenism, is a common ovulatory disorder. Having an irregular cycle is a potential marker for cardiometabolic conditions, but data are limited on whether the associations differ by PCOS status or potential interventions. Objective: To evaluate the association of PCOS, time to regularity since menarche (adolescence), and irregular cycles (adulthood) with cardiometabolic conditions. Design, Setting, and Participants: This cross-sectional study used a large, US-based digital cohort of users of the Apple Research application on their iPhone. Eligibility criteria were having ever menstruated, living in the US, being at age of consent of at least 18 years (or 19 years in Alabama and Nebraska or 21 years in Puerto Rico), and being able to communicate in English. Participants were enrolled between November 14, 2019, and December 13, 2022, and completed relevant surveys. Exposures: Self-reported PCOS diagnosis, prolonged time to regularity (not spontaneously establishing regularity within 5 years of menarche), and irregular cycles. Main Outcomes and Measures: The primary outcome was self-reported cardiometabolic conditions, including obesity, prediabetes, type 1 and 2 diabetes, high cholesterol, hypertension, metabolic syndrome, arrhythmia, congestive heart failure, coronary artery disease, heart attack, heart valve disease, stroke, transient ischemic attack (TIA), deep vein thrombosis, and pulmonary embolism measured using descriptive statistics and logistic regression to estimate prevalence odds ratios (PORs) and 95% CIs. Effect modification by lifestyle factors was also estimated. Results: The study sample (N = 60 789) had a mean (SD) age of 34.5 (11.1) years, with 12.3% having PCOS and 26.3% having prolonged time to regularity. Among a subset of 25 399 participants who completed the hormonal symptoms survey, 25.6% reported irregular cycles. In covariate-adjusted logistic regression models, PCOS was associated with a higher prevalence of all metabolic and several cardiovascular conditions, eg, arrhythmia (POR, 1.37; 95% CI, 1.20-1.55), coronary artery disease (POR, 2.92; 95% CI, 1.95-4.29), heart attack (POR, 1.79; 95% CI, 1.23-2.54), and stroke (POR, 1.66; 95% CI, 1.21-2.24). Among participants without PCOS, prolonged time to regularity was associated with type 2 diabetes (POR, 1.24; 95% CI, 1.05-1.46), hypertension (POR, 1.09; 95% CI, 1.01-1.19), arrhythmia (POR, 1.20; 95% CI, 1.06-1.35), and TIA (POR, 1.33; 95% CI, 1.01-1.73), and having irregular cycles was associated with type 2 diabetes (POR, 1.36; 95% CI, 1.08-1.69), high cholesterol (POR, 1.17; 95% CI, 1.05-1.30), arrhythmia (POR, 1.21; 95% CI, 1.02-1.43), and TIA (POR, 1.56; 95% CI, 1.06-2.26). Some of these associations were modified by high vs low body mass index or low vs high physical activity. Conclusions and Relevance: These findings suggest that PCOS and irregular cycles may be independent markers for cardiometabolic conditions. Early screening and intervention among individuals with irregular menstrual cycles may be beneficial.

Associations between solar and geomagnetic activity and cognitive function in the Normative Aging study.

BACKGROUND: Studies show that changes in solar and geomagnetic activity (SGA) influence melatonin secretion and the autonomic nervous system. We evaluated associations between solar and geomagnetic activity and cognitive function in the Normative Aging Study from 1992 to 2013. METHODS: We used logistic and linear generalized estimating equations and regressions to evaluate the associations between moving averages of sunspot number (SSN) and Kp index (a measure of geomagnetic activity) and a binary measure for Mini-Mental State Examination (MMSE) scores (≤25 or > 25) and six other cognitive tests as continuous measures, combined into one global composite score and considered separately. RESULTS: A one-IQR increase in same-day SSN and Kp index were associated with 17% (95% CI: 3%, 34%) and 19% (95% CI: 4%, 36%) increases in the odds of low MMSE score. We observed small increases in the global cognitive score with increasing SSN, although we observed decreases specifically in relation to the backwards digit span test. CONCLUSIONS: Periods of high SGA were associated with cognitive function. SGA may not equally impact all aspects of cognitive function, as evidenced by differences in associations observed for the MMSE, global cognitive score, and individual cognitive tests. Given that much of the pathology of cognitive decline in the elderly remains unexplained, studies specifically targeting decline and with longer follow-up periods are warranted.

Non-persistent endocrine disrupting chemical mixtures and uterine leiomyomata in the study of environment, lifestyle and fibroids (SELF).

BACKGROUND: Results of studies investigating associations between individual endocrine-disrupting chemicals (EDCs) and incidence of uterine leiomyomata (UL), a hormone-dependent gynecological condition, have been inconsistent. However, few studies have evaluated simultaneous exposure to a mixture of EDCs with UL incidence. METHODS: We conducted a case-cohort analysis (n = 708) of data from the Study of the Environment, Lifestyle and Fibroids (SELF), a prospective cohort study. Participants were aged 23-35 years at enrollment, had an intact uterus, and identified as Black or African American. We measured biomarker concentrations of 21 non-persistent EDCs, including phthalates, phenols, parabens, and triclocarban, in urine collected at baseline, 20-month, and 40-month clinic visits. We ascertained UL incidence and characteristics using ultrasounds at baseline and approximately every 20 months through 60 months. We used probit Bayesian Kernel Machine Regression (BKMR-P) to evaluate joint associations between EDC mixtures with cumulative UL incidence. We estimated the mean difference in the probit of UL incidence over the study period, adjusting for baseline age, education, years since last birth, parity, smoking status and body mass index. We converted probit estimates to odds ratios for ease of interpretation. RESULTS: We observed that urinary concentrations of the overall EDC mixture were inversely associated with UL incidence in the overall mixtures model, with the strongest inverse associations at the 70th percentile of all biomarkers compared with their 50th percentile (odds ratio = 0.59; 95% confidence interval: 0.36, 0.96). Strongest contributors to the joint association for the mixture were bisphenol S (BPS), ethyl paraben (EPB), bisphenol F (BPF) and mono (2-ethyl-5-carboxypentyl) phthalate (MECPP), which each demonstrated inverse associations except for MECPP. There was suggestive evidence of an interaction between MECPP and EPB. CONCLUSION: In this prospective ultrasound study, we observed evidence of an inverse association between the overall mixture of urinary biomarker concentrations of non-persistent EDCs with UL incidence.

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients.

BACKGROUND: Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 µm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described. METHODS: Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker. RESULTS: 144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1. CONCLUSIONS: In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

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

Introduction: Neurotoxicity resulting from air pollution is of increasing concern. Considering exposure timing effects on neurodevelopmental impairments may be as important as the exposure dose. We used distributed lag regression to determine the sensitive windows of prenatal exposure to fine particulate matter (PM2.5) on children's cognition in a birth cohort in Mexico. Methods: Analysis included 553 full-term (≥37 weeks gestation) children. Prenatal daily PM2.5 exposure was estimated using a validated satellite-based spatiotemporal model. McCarthy Scales of Children's Abilities (MSCA) were used to assess children's cognitive function at 4-5 years old (lower scores indicate poorer performance). To identify susceptibility windows, we used Bayesian distributed lag interaction models to examine associations between prenatal PM2.5 levels and MSCA. This allowed us to estimate vulnerable windows while testing for effect modification. Results: After adjusting for maternal age, socioeconomic status, child age, and sex, Bayesian distributed lag interaction models showed significant associations between increased PM2.5 levels and decreased general cognitive index scores at 31-35 gestation weeks, decreased quantitative scale scores at 30-36 weeks, decreased motor scale scores at 30-36 weeks, and decreased verbal scale scores at 37-38 weeks. Estimated cumulative effects (CE) of PM2.5 across pregnancy showed significant associations with general cognitive index (CE^ = -0.35, 95% confidence interval [CI] = -0.68, -0.01), quantitative scale (CE^ = -0.27, 95% CI = -0.74, -0.02), motor scale (CE^ = -0.25, 95% CI = -0.44, -0.05), and verbal scale (CE^ = -0.2, 95% CI = -0.43, -0.02). No significant sex interactions were observed. Conclusions: Prenatal exposure to PM2.5, particularly late pregnancy, was inversely associated with subscales of MSCA. Using data-driven methods to identify sensitive window may provide insight into the mechanisms of neurodevelopmental impairment due to pollution.

Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study.

OBJECTIVE: To estimate exposure-response associations between chronic exposure to fine particulate matter (PM2.5) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes. DESIGN: Population based cohort study. SETTING: Contiguous US. PARTICIPANTS: 59 761 494 Medicare fee-for-service beneficiaries aged ≥65 years during 2000-16. Calibrated PM2.5 predictions were linked to each participant's residential zip code as proxy exposure measurements. MAIN OUTCOME MEASURES: Risk of the first hospital admission during follow-up for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, valvular heart disease, thoracic and abdominal aortic aneurysms, or a composite of these CVD subtypes. A causal framework robust against confounding bias and bias arising from errors in exposure measurements was developed for exposure-response estimations. RESULTS: Three year average PM2.5 exposure was associated with increased relative risks of first hospital admissions for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, and thoracic and abdominal aortic aneurysms. For composite CVD, the exposure-response curve showed monotonically increased risk associated with PM2.5: compared with exposures ≤5 µg/m3 (the World Health Organization air quality guideline), the relative risk at exposures between 9 and 10 µg/m3, which encompassed the US national average of 9.7 µg/m3 during the study period, was 1.29 (95% confidence interval 1.28 to 1.30). On an absolute scale, the risk of hospital admission for composite CVD increased from 2.59% with exposures ≤5 µg/m3 to 3.35% at exposures between 9 and 10 µg/m3. The effects persisted for at least three years after exposure to PM2.5. Age, education, accessibility to healthcare, and neighborhood deprivation level appeared to modify susceptibility to PM2.5. CONCLUSIONS: The findings of this study suggest that no safe threshold exists for the chronic effect of PM2.5 on overall cardiovascular health. Substantial benefits could be attained through adherence to the WHO air quality guideline.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium.

Importance: Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. Objective: To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. Design, Setting, and Participants: This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Exposure: Early-life exposures to PM2.5 and NO2 according to participants' birth address. Main Outcomes and Measures: Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Results: Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 µg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). Conclusions and Relevance: In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Protocol for the air purification for eosinophilic COPD study (APECS): a randomised controlled trial of home air filtration by HEPA.

INTRODUCTION: Exposure to particulate matter (PM) pollution has been associated with lower lung function in adults with chronic obstructive pulmonary disease (COPD). Patients with eosinophilic COPD have been found to have higher levels of airway inflammation, greater responsiveness to anti-inflammatory steroid inhalers and a greater lung function response to PM pollution exposure compared with those with lower eosinophil levels. This study will evaluate if reducing home PM exposure by high-efficiency particulate air (HEPA) air filtration improves respiratory health in eosinophilic COPD. METHODS AND ANALYSIS: The Air Purification for Eosinophilic COPD Study (APECS) is a double-blinded randomised placebo-controlled trial that will enrol 160 participants with eosinophilic COPD living in the area of Boston, Massachusetts. Real and sham air purifiers will be placed in the bedroom and living rooms of the participants in the intervention and control group, respectively, for 12 months. The primary trial outcome will be the change in forced expiratory volume in 1 s (FEV1). Lung function will be assessed twice preintervention and three times during the intervention phase (at 7 days, 6 months and 12 months postrandomisation). Secondary trial outcomes include changes in (1) health status by St. George's Respiratory Questionnaire; (2) respiratory symptoms by Breathlessness, Cough and Sputum Scale (BCSS); and (3) 6-Minute Walk Test (6MWT). Inflammatory mediators were measured in the nasal epithelial lining fluid (NELF). Indoor PM will be measured in the home for the week preceding each study visit. The data will be analysed to contrast changes in outcomes in the intervention and control groups using a repeated measures framework. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Institutional Review Board of Beth Israel Deaconess Medical Centre (protocol #2019P0001129). The results of the APECS trial will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION: NCT04252235. Version: October 2023.

Association between gestational exposure to solar activity and pregnancy loss using live births from a Massachusetts-based medical center.

BACKGROUND: Solar activity has been linked to biological mechanisms important to pregnancy, including folate and melatonin levels and inflammatory markers. Thus, we aimed to investigate the association between gestational solar activity and pregnancy loss. METHODS: Our study included 71,963 singleton births conceived in 2002-2016 and delivered at an academic medical center in Eastern Massachusetts. We studied several solar activity metrics, including sunspot number, Kp index, and ultraviolet radiation, with data from the NASA Goddard Space Flight Center and European Centre for Medium-Range Weather Forecasts. We used a novel time series analytic approach to investigate associations between each metric from conception through 24 weeks of gestation and the number of live birth-identified conceptions (LBICs) -the total number of conceptions in each week that result in a live birth. This approach fits distributed lag models to data on LBICs, adjusted for time trends, and allows us to infer associations between pregnancy exposure and pregnancy loss. RESULTS: Overall, the association between solar activity during pregnancy and pregnancy loss varied by exposure metric. For sunspot number, we found that an interquartile range increase in sunspot number (78·7 sunspots) in all of the first 24 weeks of pregnancy was associated with 14·0 (95% CI: 6·5, 21·3) more pregnancy losses out of the average 92 LBICs in a week, and exposure in weeks ten through thirteen was identified as a critical window. Although not statistically significant, higher exposure to Kp index and to UV radiation across all 24 weeks of pregnancy was associated with more and less pregnancy losses, respectively. CONCLUSION: While exposure to certain metrics of solar activity (i.e., sunspot number) throughout the first 24 weeks of pregnancy may be associated with pregnancy losses, exposure to other metrics were not. Solar activity is a complex phenomenon, and more studies are needed to clarify underlying pathways.

Cotinine concentrations in maternal serum and amniotic fluid during pregnancy and risk of testicular germ cell cancer in the offspring: A prospective nested case-control study.

Maternal smoking in pregnancy may increase the risk of testicular germ cell cancer (TGCC) in offspring, but current evidence remains inconclusive. We performed a nested case-control study using cotinine measurements in maternal serum and amniotic fluid as a biomarker for tobacco exposure during pregnancy. A total of 654 males with maternal serum (n = 359, ncases/controls = 71/288) and/or amniotic fluid (n = 295, ncases/controls = 66/229) samples were included. Data on TGCC diagnoses and relevant covariates were derived from nationwide Danish health registries. Cotinine was quantified by liquid chromatography tandem mass spectrometry. An adapted cox regression model estimated the risk of TGCC considering active and inactive tobacco use defined according to cotinine concentrations of <, ≥15 ng/ml. Overall, the concentrations of cotinine were comparable in maternal serum and amniotic fluid (medianserum/amniotic fluid : 2.1/2.6 ng/ml). A strong statistically significant correlation was detected in 14 paired samples (Spearman rho: 0.85). Based on maternal serum cotinine concentrations, exposure to active tobacco use was not associated with risk of TGCC in offspring (HR 0.88, 95% CI 0.51; 1.52). Similarly, based on amniotic fluid cotinine concentrations, exposure to active tobacco use was not associated with risk of TGCC (HR 1.11, 95% CI 0.64; 1.95). However, different risks were observed for seminomas and nonseminomas in both matrices, but none were statistically significant. Our findings did not provide convincing evidence supporting that exposure to tobacco during pregnancy is associated with TGCC.