Variable Selection When Estimating Effects in External Target Populations.

External validity is an important part of epidemiologic research. To validly estimate effects in specific external target populations using a chosen effect measure (i.e., "transport"), some methods require that one account for all effect measure modifiers [EMMs]. However, little is known about how including other variables that are not EMMs (i.e., non-EMMs) in adjustment sets impacts estimates. Using simulations, we evaluated how inclusion of non-EMMs affected estimation of the transported risk difference (RD) by assessing impacts of covariates that A) differ (or not) between the trial and the target, B) are associated with the outcome (or not), and C) modify the RD (or not). We assessed variation and bias when covariates with each possible combination of these factors were used to transport RDs using outcome modeling or inverse odds weighting. Including variables that differed in distribution between the populations but were non-EMMs reduced precision, regardless of whether they were associated with the outcome. However, non-EMMs associated with selection did not amplify bias resulting from omitting necessary EMMs. Including all variables associated with the outcome may result in unnecessarily imprecise estimates when estimating treatment effects in external target populations.

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

Prenatal fine particulate matter (PM2.5) and maternal psychological functioning have been associated with child cognitive outcomes, though their independent and joint impacts on earlier behavioral outcomes remains less studied. We used data from 382 mother-child pairs from a prospective birth cohort in Mexico City. Temperament was measured at 24 months using the Carey Toddler Temperament Scale (TTS). Exploratory factor analysis (EFA) was used to update the factor structure of the TTS. During pregnancy, mothers completed the Crisis in Family Systems-Revised, Edinburgh Depression Scale, pregnancy-specific anxiety scale, and the Perceived Stress Scale. Pregnancy PM2.5 was assessed using estimates from a satellite-based exposure model. We assessed the association between prenatal maternal stress and PM2.5 on temperament, in both independent and joint models. Quantile g-computation was used to estimate the joint associations. Models were adjusted for maternal age, SES, education, child sex, and child age. In EFA, we identified three temperament factors related to effortful control, extraversion, and negative affect. Our main results showed that higher levels of PM2.5 and several of the maternal psychological functioning measures were related to both effortful control and negative affect in the child, both individually and as a mixture. For instance, a one quartile increase in the prenatal mixture was associated with higher negative affect scores in the child (0.34, 95% CI: 0.16, 0.53). We observed modification of these associations by maternal SES, with associations seen only among lower SES participants for both effortful control (-0.45, 95% CI: -0.70, -0.20) and negative affect outcomes (0.60, 95% CI: 0.35, 0.85). Prenatal PM2.5 and maternal psychological functioning measures were associated with toddler temperament outcomes, providing evidence for impacts of chemical and non-chemical stressors on early child health.

Personal care product use patterns in association with phthalate and replacement biomarkers across pregnancy.

BACKGROUND: Humans are exposed to phthalates, a class of non-persistent chemicals, through multiple products, including personal care and cosmetics. Associations between specific phthalates and product use have been inconsistent. However, determining these connections could provide avenues for exposure reduction. OBJECTIVE: Examine the association between patterns of personal care product use and associations with phthalate and replacement biomarkers. METHODS: In the Human Placenta and Phthalates Study, 303 women were enrolled in early pregnancy and followed for up to 8 visits across gestation. At each visit, women completed a questionnaire about product use in the prior 24 hours and contributed urine samples, subsequently analyzed for 18 phthalate and replacement metabolites. At early, mid-, and late pregnancy, questionnaire responses were condensed and repeated metabolite concentrations were averaged. Latent class analysis (LCA) was used to determine groups of women with similar use patterns, and weighted associations between group membership and biomarker concentrations were assessed. RESULTS: LCA sorted women into groups which largely corresponded to: (1) low fragranced product use (16-23% of women); (2) fragranced product and low body wash use (22-26%); 3) fragranced product and low bar soap use (26-51%); and (4) low product use (7-34%). Monoethyl phthalate (MEP) urinary concentrations were 7-10% lower and concentrations of summed di(2-ethylhexyl) terephthalate metabolites were 15-21% lower among women in the "low fragranced product use" group compared to the population mean. Few other consistent associations between group and biomarker concentrations were noted. IMPACT STATEMENT: Personal care products and cosmetics are a known exposure source for phthalates and potentially represent one of the most accessible intervention targets for exposure reduction. However, in this analysis accounting for concurrent use and fragranced status of products, we did not find any use patterns that corresponded to universally lower levels.

Visualizing External Validity: Graphical Displays to Inform the Extension of Treatment Effects from Trials to Clinical Practice.

BACKGROUND: In the presence of effect measure modification, estimates of treatment effects from randomized controlled trials may not be valid in clinical practice settings. The development and application of quantitative approaches for extending treatment effects from trials to clinical practice settings is an active area of research. METHODS: In this article, we provide researchers with a practical roadmap and four visualizations to assist in variable selection for models to extend treatment effects observed in trials to clinical practice settings and to assess model specification and performance. We apply this roadmap and visualizations to an example extending the effects of adjuvant chemotherapy (5-fluorouracil vs. plus oxaliplatin) for colon cancer from a trial population to a population of individuals treated in community oncology practices in the United States. RESULTS: The first visualization screens for potential effect measure modifiers to include in models extending trial treatment effects to clinical practice populations. The second visualization displays a measure of covariate overlap between the clinical practice populations and the trial population. The third and fourth visualizations highlight considerations for model specification and influential observations. The conceptual roadmap describes how the output from the visualizations helps interrogate the assumptions required to extend treatment effects from trials to target populations. CONCLUSIONS: The roadmap and visualizations can inform practical decisions required for quantitatively extending treatment effects from trials to clinical practice settings.

Exposure to indoor light at night in relation to multiple dimensions of sleep health: findings from the Sister Study.

STUDY OBJECTIVE: To examine the association between light at night (LAN) and multiple sleep health dimensions. METHODS: Among 47 765 Sister Study participants, indoor LAN (TV on in the room, light(s) on in room, light from outside the room, nightlight, no light) and sleep dimensions were self-reported at baseline (2003-2009). We used Poisson regression with robust variance to estimate adjusted prevalence ratios (PR) and 95% confidence intervals (CI) for the cross-sectional associations between LAN and short sleep duration (<7 hours/night), insomnia symptoms (difficulty falling or staying asleep), frequent napping (≥3 naps/week), inconsistent sleep/wake time (differed day-to-day and week-to-week), sleep debt (≥2 hours between longest and shortest duration), recent sleep medication use, and a cumulative poor sleep score (≥3 poor sleep dimensions). Population-attributable risks (PARs) were determined for any light exposure vs. none by race/ethnicity. RESULTS: Compared to sleeping with no light in the bedroom, sleeping with a TV on was associated with a higher prevalence of most dimensions of poor sleep (e.g. short sleep duration: PR = 1.38, 95% CI: 1.32 to 1.45; inconsistent sleep/wake time: PR = 1.55, 95% CI: 1.44 to 1.66; sleep debt: PR = 1.36, 95% CI: 1.29 to 1.44; poor sleep score: PR = 1.58, 95% CI: 1.48-1.68). PARs tended to be higher for non-Hispanic black women compared to non-Hispanic white women. CONCLUSIONS: Sleeping with a TV on was associated with poor sleep health among US women, and non-Hispanic black women may be disproportionately burdened.

Use of personal care product mixtures and incident hormone-sensitive cancers in the Sister Study: A U.S.-wide prospective cohort.

BACKGROUND: Personal care products (PCPs), a source of endocrine-disrupting chemical exposure, may be associated with the risk of hormone-sensitive cancers. Few studies have investigated associations for PCP use with the incidence of hormone-sensitive cancers or considered the joint effect of multiple correlated PCPs. We examined associations between frequently used, or "everyday", PCPs and incident cancers of the breast, ovary, and uterus with a fucus on the joint effect of multiple product exposure. METHODS: Sister Study participants (n=49 899) self-reported frequency of use in the year before enrollment (2003-2009) for 41 PCPs. Using five-level frequency categories based on questionnaire options, hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for the associations between multiple PCP use and incident breast, ovarian, and uterine cancer using quantile-based g-computation with Cox proportional hazards regression as the underlying model. Multiple PCP use was examined using groupings (beauty, hygiene, and skincare products) determined by both a priori knowledge and Spearman correlation coefficients for co-occurring product use. Associations between individual PCPs and the three cancers were also examined using Cox proportional hazards models coupling with Benjamini-Hochberg procedure for multiple comparisons. RESULTS: Over an average of 11.6 years, 4 226 breast, 277 ovarian, and 403 uterine cancer cases were identified. Positive associations were observed between the hygiene mixture and ovarian cancer (HR=1.35, 95%CI=1.00, 1.83) and the beauty mixture with postmenopausal breast cancer (HR=1.08, 95%CI=1.01, 1.16). Additionally, we observed an inverse association between the skincare mixture and breast cancer (HR=0.91, 95%CI=0.83, 0.99). No significant associations were observed for individual products after corrected for multiple comparison. CONCLUSIONS: Findings from this multi-product, joint-effect approach contribute to the growing body of evidence for associations between PCPs and breast cancer and provides novel information on ovarian and uterine cancer.

Racial and Ethnic Disparities in Phthalate Exposure and Preterm Birth: A Pooled Study of Sixteen U.S. Cohorts.

BACKGROUND: Phthalate exposures are ubiquitous during pregnancy and may contribute to racial and ethnic disparities in preterm birth. OBJECTIVES: We investigated race and ethnicity in the relationship between biomarkers of phthalate exposure and preterm birth by examining: a) how hypothetical reductions in racial and ethnic disparities in phthalate metabolites might reduce the probability of preterm birth; and b) exposure-response models stratified by race and ethnicity. METHODS: We pooled individual-level data on 6,045 pregnancies from 16 U.S. cohorts. We investigated covariate-adjusted differences in nine urinary phthalate metabolite concentrations by race and ethnicity [non-Hispanic White (White, 43%), non-Hispanic Black (Black, 13%), Hispanic/Latina (38%), and Asian/Pacific Islander (3%)]. Using g-computation, we estimated changes in the probability of preterm birth under hypothetical interventions to eliminate disparities in levels of urinary phthalate metabolites by proportionally lowering average concentrations in Black and Hispanic/Latina participants to be approximately equal to the averages in White participants. We also used race and ethnicity-stratified logistic regression to characterize associations between phthalate metabolites and preterm birth. RESULTS: In comparison with concentrations among White participants, adjusted mean phthalate metabolite concentrations were consistently higher among Black and Hispanic/Latina participants by 23%-148% and 4%-94%, respectively. Asian/Pacific Islander participants had metabolite levels that were similar to those of White participants. Hypothetical interventions to reduce disparities in metabolite mixtures were associated with lower probabilities of preterm birth for Black [13% relative reduction; 95% confidence interval (CI): -34%, 8.6%] and Hispanic/Latina (9% relative reduction; 95% CI: -19%, 0.8%) participants. Odds ratios for preterm birth in association with phthalate metabolites demonstrated heterogeneity by race and ethnicity for two individual metabolites (mono-n-butyl and monoisobutyl phthalate), with positive associations that were larger in magnitude observed among Black or Hispanic/Latina participants. CONCLUSIONS: Phthalate metabolite concentrations differed substantially by race and ethnicity. Our results show hypothetical interventions to reduce population-level racial and ethnic disparities in biomarkers of phthalate exposure could potentially reduce the probability of preterm birth. https://doi.org/10.1289/EHP12831.

Iterative Causal Forest: A Novel Algorithm for Subgroup Identification.

Precisely and efficiently identifying subgroups with heterogeneous treatment effects (HTEs) in real-world evidence studies remains a challenge. Based on the causal forest (CF) method, we developed an iterative CF (iCF) algorithm to identify HTEs in subgroups defined by important variables. Our method iteratively grows different depths of the CF with important effect modifiers, performs plurality votes to obtain decision trees (subgroup decisions) for a family of CFs with different depths, then finds the cross-validated subgroup decision that best predicts the treatment effect as a final subgroup decision. We simulated 12 different scenarios and showed that the iCF outperformed other machine learning methods for interaction/subgroup identification in the majority of scenarios assessed. Using a 20% random sample of fee-for-service Medicare beneficiaries initiating sodium-glucose cotransporter-2 inhibitors (SGLT2i) or glucagon-like peptide-1 receptor agonists (GLP1RA), we implemented the iCF to identify subgroups with HTEs for hospitalized heart failure. Consistent with previous studies suggesting patients with heart failure benefit more from SGLT2i, iCF successfully identified such a subpopulation with HTEs and additive interactions. The iCF is a promising method for identifying subgroups with HTEs in real-world data where the potential for unmeasured confounding can be limited by study design.

Toxic metal mixtures in private well water and increased risk for preterm birth in North Carolina.

BACKGROUND: Prenatal exposure to metals in private well water may increase the risk of preterm birth (PTB) (delivery < 37 weeks' gestation). In this study, we estimated associations between arsenic, manganese, lead, cadmium, chromium, copper, and zinc concentrations in private well water and PTB incidence in North Carolina (NC). METHODS: Birth certificates from 2003-2015 (n = 1,329,071) were obtained and pregnancies were assigned exposure using the mean concentration and the percentage of tests above the maximum contaminant level (MCL) for the census tract of each individuals' residence at the time of delivery using the NCWELL database (117,960 well water tests from 1998-2019). We evaluated associations between single metals and PTB using adjusted logistic regression models. Metals mixtures were assessed using quantile-based g-computation. RESULTS: Compared with those in other census tracts, individuals residing in tracts where > 25% of tests exceeded the MCL for lead (aOR 1.10, 95%CI 1.02,1.18) or cadmium (aOR 1.11, 95% CI 1.00,1.23) had an increased odds of PTB. Conversely, those residing in areas with > 25% MCL for zinc (aOR 0.77 (95% CI: 0.56,1.02) and copper (aOR 0.53 (95% CI: 0.13,1.34)) had a reduced odds of PTB. A quartile increase in the concentrations of a mixture of lead, cadmium, and chromium was associated with a small increased odds for PTB (aOR 1.02, 95% CI 1.01, 1.03). This metal mixture effect was most pronounced among American Indian individuals (aOR per quartile increase in all metals: 1.19 (95% CI 1.06,1.34)). CONCLUSIONS: In a large study population of over one million births, lead and cadmium were found to increase the risk of PTB individually and in a mixture, with additional mixtures-related impacts estimated from co-exposure with chromium. This study highlights critical racial and ethnic health disparities in relation to private well water thereby emphasizing the urgent need for improved private well water quality to protect vulnerable populations.

Maternal serum per- and polyfluoroalkyl substances during pregnancy and breastfeeding duration.

Per- and polyfluoroalkyl substances (PFAS) are endocrine-disrupting chemicals that may affect breastfeeding duration. We examined associations between maternal PFAS concentrations during pregnancy and breastfeeding cessation. We investigated potential effect modification by parity status. Methods: Among 555 women enrolled in the Healthy Start study (2009-2014), we quantified maternal serum concentrations of 5 PFAS during mid- to late-pregnancy (mean 27 weeks of gestation). Participants self-reported their breastfeeding practices through 18-24 months postnatally. Among all participants and stratified by parity, we estimated associations between maternal PFAS concentrations and breastfeeding discontinuation by 3 and 6 months, using Poisson regression, and breastfeeding duration, using Cox regression. Results: Median PFAS concentrations were similar to those in the general US population. Associations between PFAS and breastfeeding duration differed by parity status. After adjusting for covariates, among primiparous women, associations between PFAS and breastfeeding cessation by 3 and 6 months were generally null, with some inverse associations. Among multiparous women, there were positive associations between perfluorohexane sulfonate, perfluorooctane sulfonate, perfluorooctanoate (PFOA), and perfluorononanoate and breastfeeding cessation by 3 and 6 months. For example, per ln-ng/mL increase in PFOA, the risk ratio for breastfeeding discontinuation by 6 months was 1.45 (95% confidence interval, 1.18, 1.78). Hazard ratios reflected similar patterns between PFAS and breastfeeding duration. Conclusions: Among primiparous women, we did not find evidence for associations between PFAS concentrations and breastfeeding duration. In contrast, among multiparous women, PFAS serum concentrations were generally inversely associated with breastfeeding duration, though estimates may be biased due to confounding by unmeasured previous breastfeeding.

Prenatal Exposure to Toxic Metals and Neural Tube Defects: A Systematic Review of the Epidemiologic Evidence.

BACKGROUND: Neural tube defects (NTDs) affect >300,000 pregnancies worldwide annually. Few nongenetic factors, other than folate deficiency, have been identified that may provide intervenable solutions to reduce the burden of NTDs. Prenatal exposure to toxic metals [arsenic (As), cadmium (Cd), mercury (Hg), manganese (Mn) and lead (Pb)] may increase the risk of NTDs. Although a growing epidemiologic literature has examined associations, to our knowledge no systematic review has been conducted to date. OBJECTIVE: Through adaptation of the Navigation Guide systematic review methodology, we aimed to answer the question "does exposure to As, Cd, Hg, Mn, or Pb during gestation increase the risk of NTDs?" and to assess challenges to evaluating this question given the current evidence. METHODS: We selected available evidence on prenatal As, Cd, Hg, Mn, or Pb exposure and risk of specific NTDs (e.g., spina bifida, anencephaly) or all NTDs via a comprehensive search across MEDLINE, Embase, Web of Science, and TOXLINE databases and applied inclusion/exclusion criteria. We rated the quality and strength of the evidence for each metal. We applied a customized risk of bias protocol and evaluated the sufficiency of evidence of an effect of each metal on NTDs. RESULTS: We identified 30 studies that met our criteria. Risk of bias for confounding and selection was high in most studies, but low for missing data. We determined that, although the evidence was limited, the literature supported an association between prenatal exposure to Hg or Mn and increased risk of NTDs. For the remaining metals, the evidence was inadequate to establish or rule out an effect. CONCLUSION: The role of gestational As, Cd, or Pb exposure in the etiology of NTDs remains unclear and warrants further investigation in high-quality studies, with a particular focus on controlling confounding, mitigating selection bias, and improving exposure assessment. https://doi.org/10.1289/EHP11872.

Variability and Longitudinal Trajectories of Phthalate and Replacement Biomarkers across Pregnancy in the Human Placenta and Phthalates Study.

Human exposure to phthalates is widespread, but assessment of variability across pregnancy has been hampered by short half-lives of phthalate biomarkers and a few repeated measures in prior studies. We aimed to characterize the variability and longitudinal profiles of phthalate and replacement biomarkers across pregnancy. Within the Human Placenta and Phthalates Study, 303 pregnant women provided urine samples at up to 8 visits across gestation. Concentrations of 14 metabolites of phthalates and 4 metabolites of replacements were quantified in each sample, and subject-specific averages within each trimester were calculated. We examined variability in individual biomarker concentrations across the 8 visits, within trimesters, and across trimester-specific averages using intraclass correlation coefficients (ICCs). To explore longitudinal exposure biomarker profiles, we applied group-based trajectory modeling to trimester-specific averages over pregnancy. Pooling multiple visits into trimester-specific averages improved the ICCs for all biomarkers. Most biomarkers generally showed stable concentrations across gestation, i.e., high-, medium-, and low-concentration profiles, with small proportions of participants falling into the "high"-exposure groups. Variability over pregnancy is likely attributable to random fluctuations around a baseline exposure rather than true changes in concentrations over time.

Midpregnancy Phthalate and Phenol Biomarkers in Relation to Infant Body Composition: The Healthy Start Prospective Cohort.

BACKGROUND: Gestational phthalate and phenol exposure disrupts adipogenesis, contributing to obesity in mice. Whether gestational phthalate or phenol exposure is associated with infant body composition has not been investigated in humans. OBJECTIVE: We examined associations between biomarkers of phthalate and phenol exposure in midpregnancy and infant size and body composition at birth and at 5 months of age. METHODS: Analyses were conducted among 438 infants from the Healthy Start prospective pregnancy cohort. Sixteen phthalate and phenol biomarkers were quantified in spot urine samples collected at 24-28 wk of gestation. Infant outcomes measured at birth and at 5 months of age included size [weight (in grams)] and body composition [fat and lean masses (in grams); percentage fat mass]. Single- (linear) and multipollutant (quantile g-computation) models were used to estimate associations of phthalate and phenol biomarkers with infant outcomes at birth and at 5 months of age. Models were adjusted for sociodemographics, sample collection timing, and lifestyle factors and used to examine for effect modification by infant sex. RESULTS: In single-pollutant models, mono-benzyl phthalate and di-n-butyl phthalate were inversely associated with percentage fat mass [ß: -0.49 (95% CI: -0.91, -0.08) and -0.51 (95% CI: -1.02, 0.01), respectively] in male but not female infants at birth. Similar, but less precise, associations were observed at 5 months of age. In multipollutant models, a 1-quartile increase in the phthalate and phenol biomarker mixture was inversely associated with percentage fat mass at birth [-1.06 (95% CI: -2.21, 0.1)] and at 5 months of age [-2.14 (95% CI: -3.88, -0.39)] among males, but associations were null among females [0.48 (95% CI: -0.78, 1.75) and -0.64 (95% CI: -2.68, 1.41), respectively]. Similar associations were observed with infant weight. CONCLUSION: In this U.S.-based prospective cohort, gestational phthalate and phenol biomarkers were inversely associated with infant weight and fat mass, particularly in males. https://doi.org/10.1289/EHP12500.

Prenatal organophosphate ester exposure and executive function in Norwegian preschoolers.

Organophosphate esters (OPEs) are ubiquitous chemicals, used as flame retardants and plasticizers. OPE usage has increased over time as a substitute for other controlled compounds. This study investigates the impact of prenatal OPE exposure on executive function (EF) in preschoolers. Methods: We selected 340 preschoolers from the Norwegian Mother, Father, and Child Cohort Study. Diphenyl-phosphate (DPhP), di-n-butyl-phosphate (DnBP), bis(2-butoxyethyl) phosphate (BBOEP), and bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) were measured in maternal urine. EF was measured using the Behavior Rating Inventory of Executive Functioning-Preschool (BRIEF-P) and the Stanford-Binet fifth edition (SB-5). EF scores were scaled so a higher score indicated worse performance. We estimated exposure-outcome associations and evaluated modification by child sex using linear regression. Results: Higher DnBP was associated with lower EF scores across multiple rater-based domains. Higher DPhP and BDCIPP were associated with lower SB-5 verbal working memory (ß = 0.49, 95% CI = 0.12, 0.87; ß = 0.53, 95% CI = 0.08, 1.02), and higher BBOEP was associated with lower teacher-rated inhibition (ß = 0.34, 95% CI = 0.01, 0.63). DPhP was associated with lower parent-reported BRIEF-P measures in boys but not girls [inhibition: boys: 0.37 (95% CI = 0.03, 0.93); girls: -0.48 (95% CI = -1.27, 0.19); emotional control: boys: 0.44 (95% CI = -0.13, 1.26); girls: -0.83 (95% CI = -1.73, -0.00); working memory: boys: 0.49 (95% CI = 0.03, 1.08); girls: -0.40 (95% CI = -1.11, 0.36)]. Fewer sex interactions were observed for DnBP, BBOEP, and BDCIPP, with irregular patterns observed across EF domains. Conclusions: We found some evidence prenatal OPE exposure may impact EF in preschoolers and variation in associations by sex.

Differential Employment Quality and Educational Inequities in Mental Health: A Causal Mediation Analysis.

BACKGROUND: In the United States, inequities in mental distress between those more and less educated have widened over recent years. Employment quality, a multidimensional construct reflecting the relational and contractual features of employer-employee relationships, may mediate this inequity throughout adulthood, yet no study has examined the extent of this mediation in the United States, or how it varies across racialized and gendered populations. METHODS: Using the information on working-age adults from the 2001 to 2019 Panel Study of Income Dynamics, we construct a composite measure of employment quality via principal component analysis. Using this measure and the parametric mediational g-formula, we then estimate randomized interventional analogs for natural direct and indirect effects of low baseline educational attainment (≤high school: no/yes) on the end-of-follow-up prevalence of moderate mental distress (Kessler-6 Score ≥5: no/yes) overall and within subgroups by race and gender. RESULTS: We estimate that low educational attainment would result in a 5.3% greater absolute prevalence of moderate mental distress at the end of follow-up (randomized total effect: 5.3%, 95% CI = 2.2%, 8.4%), with approximately 32% of this effect mediated by differences in employment quality (indirect effect: 1.7%, 95% CI = 1.0%, 2.5%). The results of subgroup analyses across race and gender are consistent with the hypothesis of mediation by employment quality, though not when selecting on full employment (indirect effect: 0.6%, 95% CI = -1.0%, 2.6%). CONCLUSIONS: We estimate that approximately one-third of US educational inequities in mental distress may be mediated by differences in employment quality.

Volatile Hydrocarbon Exposures and Incident Coronary Heart Disease Events: Up to Ten Years of Follow-up among Deepwater Horizon Oil Spill Workers.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, response and cleanup workers were potentially exposed to toxic volatile components of crude oil. However, to our knowledge, no study has examined exposure to individual oil spill-related chemicals in relation to cardiovascular outcomes among oil spill workers. OBJECTIVES: Our aim was to investigate the association of several spill-related chemicals [benzene, toluene, ethylbenzene, xylene, n-hexane (BTEX-H)] and total hydrocarbons (THC) with incident coronary heart disease (CHD) events among workers enrolled in a prospective cohort. METHODS: Cumulative exposures to THC and BTEX-H across the cleanup period were estimated via a job-exposure matrix that linked air measurement data with self-reported DWH spill work histories. We ascertained CHD events following each worker's last day of cleanup work as the first self-reported physician-diagnosed myocardial infarction (MI) or a fatal CHD event. We estimated hazard ratios (HR) and 95% confidence intervals for the associations of exposure quintiles (Q) with risk of CHD. We applied inverse probability weights to account for bias due to confounding and loss to follow-up. We used quantile g-computation to assess the joint effect of the BTEX-H mixture. RESULTS: Among 22,655 workers with no previous MI diagnoses, 509 experienced an incident CHD event through December 2019. Workers in higher quintiles of each exposure agent had increased CHD risks in comparison with the referent group (Q1) of that agent, with the strongest associations observed in Q5 (range of HR=1.14-1.44). However, most associations were nonsignificant, and there was no evidence of exposure-response trends. We observed stronger associations among ever smokers, workers with ≤high school education, and workers with body mass index <30 kg/m2. No apparent positive association was observed for the BTEX-H mixture. CONCLUSIONS: Higher exposures to volatile components of crude oil were associated with modest increases in risk of CHD among oil spill workers, although we did not observe exposure-response trends. https://doi.org/10.1289/EHP11859.

Identifying and estimating effects of sustained interventions under parallel trends assumptions.

Many research questions in public health and medicine concern sustained interventions in populations defined by substantive priorities. Existing methods to answer such questions typically require a measured covariate set sufficient to control confounding, which can be questionable in observational studies. Differences-in-differences rely instead on the parallel trends assumption, allowing for some types of time-invariant unmeasured confounding. However, most existing difference-in-differences implementations are limited to point treatments in restricted subpopulations. We derive identification results for population effects of sustained treatments under parallel trends assumptions. In particular, in settings where all individuals begin follow-up with exposure status consistent with the treatment plan of interest but may deviate at later times, a version of Robins' g-formula identifies the intervention-specific mean under stable unit treatment value assumption, positivity, and parallel trends. We develop consistent asymptotically normal estimators based on inverse-probability weighting, outcome regression, and a double robust estimator based on targeted maximum likelihood. Simulation studies confirm theoretical results and support the use of the proposed estimators at realistic sample sizes. As an example, the methods are used to estimate the effect of a hypothetical federal stay-at-home order on all-cause mortality during the COVID-19 pandemic in spring 2020 in the United States.

Exploring water, sanitation, and hygiene coverage targets for reaching and sustaining trachoma elimination: G-computation analysis.

BACKGROUND: Trachoma is the leading infectious cause of blindness. To reduce transmission, water, sanitation, and hygiene (WaSH) improvements are promoted through a comprehensive public health strategy. Evidence supporting the role of WaSH in trachoma elimination is mixed and it remains unknown what WaSH coverages are needed to effectively reduce transmission. METHODS/FINDINGS: We used g-computation to estimate the impact on the prevalence of trachomatous inflammation-follicular among children aged 1-9 years (TF1-9) when hypothetical WaSH interventions raised the minimum coverages from 5% to 100% for "nearby" face-washing water (<30 minutes roundtrip collection time) and adult latrine use in an evaluation unit (EU). For each scenario, we estimated the generalized prevalence difference as the TF1-9 prevalence under the intervention scenarios minus the observed prevalence. Data from 574 cross-sectional surveys conducted in 16 African and Eastern Mediterranean countries were included. Surveys were conducted from 2015-2019 with support from the Global Trachoma Mapping Project and Tropical Data. When modeling interventions among EUs that had not yet met the TF1-9 elimination target, increasing nearby face-washing water and latrine use coverages above 30% was generally associated with consistent decreases in TF1-9. For nearby face-washing water, we estimated a ≥25% decrease in TF1-9 at 65% coverage, with a plateau upon reaching 85% coverage. For latrine use, the estimated decrease in TF1-9 accelerated from 80% coverage upward, with a ≥25% decrease in TF1-9 by 85% coverage. Among EUs that had previously met the elimination target, results were inconclusive. CONCLUSIONS: Our results support Sustainable Development Goal 6 and provide insight into potential WaSH-related coverage targets for trachoma elimination. Targets can be tested in future trials to improve evidence-based WaSH guidance for trachoma.

How Choice of Effect Measure Influences Minimally Sufficient Adjustment Sets for External Validity.

Epidemiologic researchers generalizing or transporting effect estimates from a study to a target population must account for effect-measure modifiers (EMMs) on the scale of interest. However, little attention is paid to how the EMMs required may vary depending on the mathematical nuances of each effect measure. We defined 2 types of EMMs: a marginal EMM, where the effect on the scale of interest differs across levels of a variable, and a conditional EMM, where the effect differs conditional on other variables associated with the outcome. These types define 3 classes of variables: class 1 (conditional EMM), class 2 (marginal but not conditional EMM), and class 3 (neither marginal nor conditional EMM). Class 1 variables are necessary to achieve a valid estimate of the RD in a target population, while an RR requires class 1 and class 2 and an OR requires classes 1, 2, and 3 (i.e., all variables associated with the outcome). This does not mean that fewer variables are required for an externally valid RD (because variables may not modify effects on all scales), but it does suggest that researchers should consider the scale of the effect measure when identifying an EMM necessary for an externally valid treatment effect estimate.