Faculty Bibliography

IMPORTANCE/UNASSIGNED:After the initial disruption from the COVID-19 pandemic, it is unclear how patterns of e-cigarette use in the US have changed. OBJECTIVE/UNASSIGNED:To examine recent patterns in current and daily e-cigarette use among US adults in 2021. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cross-sectional study used data from the 2021 Behavioral Risk Factor Surveillance System (BRFSS) database. The BRFSS is the largest national telephone-based survey of randomly sampled adults in the US. Adults aged 18 years or older, residing in 49 US states (all except Florida), the District of Columbia, and 3 US territories (Guam, Puerto Rico, and the US Virgin Islands), were included in the data set. Data analysis was performed in January 2023. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The main outcome was age-adjusted prevalence of current and daily e-cigarette use overall and by participant characteristics, state, and territory. Descriptive statistical analysis was conducted, applying weights to account for population representation. RESULTS/UNASSIGNED:This study included 414 755 BRFSS participants with information on e-cigarette use. More than half of participants were women (51.3%). In terms of race and ethnicity, 0.9% of participants were American Indian or Alaska Native, 5.8% were Asian, 11.5% were Black, 17.3% were Hispanic, 0.2% were Native Hawaiian or Other Pacific Islander, 62.2% were White, 1.4% were of multiple races or ethnicities, and 0.6% were of other race or ethnicity. Individuals aged 18 to 24 years comprised 12.4% of the study population. The age-standardized prevalence of current e-cigarette use was 6.9% (95% CI, 6.7%-7.1%), with almost half of participants using e-cigarettes daily (3.2% [95% CI, 3.1%-3.4%]). Among individuals aged 18 to 24 years, there was a consistently higher prevalence of e-cigarette use, with more than 18.6% reporting current use and more than 9.0% reporting daily use. Overall, among individuals reporting current e-cigarette use, 42.2% (95% CI, 40.7%-43.7%) indicated former combustible cigarette use, 37.1% (95% CI, 35.6%-38.6%) indicated current combustible cigarette use, and 20.7% (95% CI, 19.7%-21.8%) indicated never using combustible cigarettes. Although relatively older adults (aged ≥25 years) who reported current e-cigarette use were more likely to report former or current combustible cigarette use, younger adults (aged 18-24 years) were more likely to report never using combustible cigarettes. Notably, the proportion of individuals who reported current e-cigarette use and never using combustible cigarettes was higher in the group aged 18 to 20 years (71.5% [95% CI, 66.8%-75.7%]) compared with those aged 21 to 24 years (53.0% [95% CI, 49.8%-56.1%]). CONCLUSION AND RELEVANCE/UNASSIGNED:These findings suggest that e-cigarette use remained common during the COVID-19 pandemic, particularly among young adults aged 18 to 24 years (18.3% prevalence). Notably, 71.5% of individuals aged 18 to 20 years who reported current e-cigarette use had never used combustible cigarettes. These results underscore the rationale for the implementation and enforcement of public health policies tailored to young adults.

BACKGROUND:Drinking water is a common source of exposure to inorganic arsenic. In the US, the Safe Drinking Water Act (SDWA) was enacted to protect consumers from exposure to contaminants, including arsenic, in public water systems (PWS). The reproductive effects of preconception and prenatal arsenic exposure in regions with low to moderate arsenic concentrations are not well understood. OBJECTIVES:This study examined associations between preconception and prenatal exposure to arsenic violations in water, measured via residence in a county with an arsenic violation in a regulated PWS during pregnancy, and five birth outcomes: birth weight, gestational age at birth, preterm birth, small for gestational age (SGA), and large for gestational age (LGA). METHODS:Data for arsenic violations in PWS, defined as concentrations exceeding 10 parts per billion, were obtained from the Safe Drinking Water Information System. Participants of the Environmental influences on Child Health Outcomes Cohort Study were matched to arsenic violations by time and location based on residential history data. Multivariable, mixed effects regression models were used to assess the relationship between preconception and prenatal exposure to arsenic violations in drinking water and birth outcomes. RESULTS:Compared to unexposed infants, continuous exposure to arsenic from three months prior to conception through birth was associated with 88.8 g higher mean birth weight (95% CI: 8.2, 169.5), after adjusting for individual-level confounders. No statistically significant associations were observed between any preconception or prenatal violations exposure and gestational age at birth, preterm birth, SGA, or LGA. CONCLUSIONS:Our study did not identify associations between preconception and prenatal arsenic exposure, defined by drinking water exceedances, and adverse birth outcomes. Exposure to arsenic violations in drinking water was associated with higher birth weight. Future studies would benefit from more precise geodata of water system service areas, direct household drinking water measurements, and exposure biomarkers.

BACKGROUND:Sickle cell trait affects approximately 8% of Black individuals in the United States, along with many other individuals with ancestry from malaria-endemic regions worldwide. While traditionally considered a benign condition, recent evidence suggests that sickle cell trait is associated with lower eGFR and higher risk of kidney diseases, including kidney failure. The mechanisms underlying these associations remain poorly understood. We used proteomic profiling to gain insight into the pathobiology of sickle cell trait. METHODS:We measured proteomics ( N =1285 proteins assayed by Olink Explore) using baseline plasma samples from 592 Black participants with sickle cell trait and 1:1 age-matched Black participants without sickle cell trait from the prospective Women's Health Initiative cohort. Age-adjusted linear regression was used to assess the association between protein levels and sickle cell trait. RESULTS:In age-adjusted models, 35 proteins were significantly associated with sickle cell trait after correction for multiple testing. Several of the sickle cell trait-protein associations were replicated in Black participants from two independent cohorts (Atherosclerosis Risk in Communities study and Jackson Heart Study) assayed using an orthogonal aptamer-based proteomic platform (SomaScan). Many of the validated sickle cell trait-associated proteins are known biomarkers of kidney function or injury ( e.g. , hepatitis A virus cellular receptor 1 [HAVCR1]/kidney injury molecule-1 [KIM-1], uromodulin [UMOD], ephrins), related to red cell physiology or hemolysis (erythropoietin [EPO], heme oxygenase 1 [HMOX1], and α -hemoglobin stabilizing protein) and/or inflammation (fractalkine, C-C motif chemokine ligand 2/monocyte chemoattractant protein-1 [MCP-1], and urokinase plasminogen activator surface receptor [PLAUR]). A protein risk score constructed from the top sickle cell trait-associated biomarkers was associated with incident kidney failure among those with sickle cell trait during Women's Health Initiative follow-up (odds ratio, 1.32; 95% confidence interval, 1.10 to 1.58). CONCLUSIONS:We identified and replicated the association of sickle cell trait with a number of plasma proteins related to hemolysis, kidney injury, and inflammation.

The discrete-time Wright-Fisher (DTWF) model and its diffusion limit are central to population genetics. These models can describe the forward-in-time evolution of allele frequencies in a population resulting from genetic drift, mutation, and selection. Computing likelihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large samples or in the presence of strong selection. Existing methods for computing likelihoods under the DTWF model do not scale to current exome sequencing sample sizes in the hundreds of thousands. Here, we present a scalable algorithm that approximates the DTWF model with provably bounded error. Our approach relies on two key observations about the DTWF model. The first is that transition probabilities under the model are approximately sparse. The second is that transition distributions for similar starting allele frequencies are extremely close as distributions. Together, these observations enable approximate matrix-vector multiplication in linear (as opposed to the usual quadratic) time. We prove similar properties for Hypergeometric distributions, enabling fast computation of likelihoods for subsamples of the population. We show theoretically and in practice that this approximation is highly accurate and can scale to population sizes in the tens of millions, paving the way for rigorous biobank-scale inference. Finally, we use our results to estimate the impact of larger samples on estimating selection coefficients for loss-of-function variants. We find that increasing sample sizes beyond existing large exome sequencing cohorts will provide essentially no additional information except for genes with the most extreme fitness effects.

INTRODUCTION:Governments must scale-up evidence-based interventions to reduce the burden of non-communicable diseases (NCDs). Implementation research can help develop contextually appropriate strategies and optimise interventions for scale-up. We aimed to determine the priorities of the Global Alliance for Chronic Diseases (GACD) 2019 funding round for scale-up research targeting NCD interventions. The research questions were: (a) What was the purpose of the call and what were the specific issues considered by funders when supporting the selected projects? (b) How did the selected research projects align with the objectives of GACD scale-up call? METHODS:We undertook a mixed-methods study to examine the projects funded by the GACD in 2019. We completed semistructured interviews with representatives from 5 out of 8 funding agencies and complemented this by reviewing project documents from 21 (78%) of the 27 funded studies. A literature review of scale-up frameworks informed the interview guide and data extraction template. The transcripts were open-coded using thematic analysis to identify critical issues for funders. Data were extracted to identify the common elements considered when planning, implementing and evaluating interventions for scale-up. RESULTS:Interviews with the funders revealed three enabling themes related to scale-up: local research priorities (contextualisation through engagement), capacity building (developing knowledge base) and connections (networking opportunities). We further identified that timelines (more flexibility) and equity (funding low-income and middle-income researchers) could be considered for future funding investments. Multidisciplinary international research teams led the development of diverse studies to address funder's priorities. The detailed plans included a range of implementation frameworks to help develop contextual scale-up strategies. CONCLUSIONS:Fundamental to NCD scale-up research are (1) funding opportunities that reflect the complexity and time necessary to enable contextualisation; (2) investment in building multidisciplinary research capacity and leadership and (3) better networking to encourage cohesive action and align NCD-related scale-up research activities globally.

To assess the public health impact of the COVID-19 pandemic on mental health, investigators from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program developed the Pandemic-Related Traumatic Stress Scale (PTSS). Based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) acute stress disorder symptom criteria, the PTSS is designed for adolescent (13-21 years) and adult self-report and caregiver-report on 3-12-year-olds. To evaluate psychometric properties, we used PTSS data collected between April 2020 and August 2021 from non-pregnant adult caregivers (n = 11,483), pregnant/postpartum individuals (n = 1,656), adolescents (n = 1,795), and caregivers reporting on 3-12-year-olds (n = 2,896). We used Mokken scale analysis to examine unidimensionality and reliability, Pearson correlations to evaluate relationships with other relevant variables, and analyses of variance to identify regional, age, and sex differences. Mokken analysis resulted in a moderately strong, unidimensional scale that retained nine of the original 10 items. We detected small to moderate positive associations with depression, anxiety, and general stress, and negative associations with life satisfaction. Adult caregivers had the highest PTSS scores, followed by adolescents, pregnant/postpartum individuals, and children. Caregivers of younger children, females, and older youth had higher PTSS scores compared to caregivers of older children, males, and younger youth, respectively. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The growing number of people living with dementia (PLWD) requires a coordinated clinical response to deliver pragmatic, evidence-based interventions in frontline care settings. However, infrastructure to support such a response is lacking. Moreover, there are too few researchers conducting rigorous embedded pragmatic clinical trials (ePCTs) to make the vision of high quality, widely accessible dementia care a reality. National Institute on Aging (NIA) Imbedded Pragmatic Alzheimer's disease and Related Dementias Clinical Trials (IMPACT) Collaboratory seeks to improve the pipeline of early career researchers qualified to lead ePCTs by funding career development awards. Even with support from the Collaboratory, awardees face practical and methodological challenges to success, recently exacerbated by the COVID-19 pandemic. We first describe the training opportunities and support network for the IMPACT CDA recipients. This report then describes the unique career development challenges faced by early-career researchers involved in ePCTs for dementia care. Topics addressed include challenges in establishing a laboratory, academic promotion, mentoring and professional development, and work-life balance. Concrete suggestions to address these challenges are offered for early-career investigators, their mentors, and their supporting institutions. While some of these challenges are faced by researchers in other fields, this report seeks to provide a roadmap for expanding the work of the IMPACT Collaboratory and initiating future efforts to recruit, train, and retain talented early-career researchers involved in ePCTs for dementia care.

OBJECTIVES:Few studies have considered how trends in opioid poisonings have changed among older adults. The objective of this study was to examine trends in fatal and nonfatal opioid-related poisonings ("exposures") among older adults. METHODS:National poison center data were used to examine trends in characteristics of reported exposures to commonly prescribed opioids between 2015 and 2021 among adults 60 years or older. We estimated the proportion of opioid exposures by demographic characteristics, the specific opioid(s) involved, exposure type, route of administration, other substances co-used, and medical outcomes for each calendar year. We estimated whether there were linear changes in prevalence by year using logistic regression. RESULTS:Although there was a decrease in the number of opioid exposures within the study population from 7706 in 2015 to 7337 in 2021 (a 4.8% decrease, P = 0.04), exposures increased for adults aged 70 to 79 years (a 14.0% increase, P < 0.001). The proportion classified as "abuse" increased by 63.3% ( P < 0.001). There were significant decreases in the proportion involving hydromorphone (a 23.3% decrease, P < 0.001) and morphine (a 22.0% decrease, P < 0.001), with an increase involving buprenorphine (a 216.0% increase, P < 0.001). The proportion increased for co-use of cocaine (a 488.9% increase, P < 0.001) and methamphetamine (a 220.0% increase, P = 0.02), with a decrease in co-use of benzodiazepines (a 25.5% decrease, P < 0.001). The proportion of major medical outcomes increased by 93.9% ( P < 0.001). CONCLUSIONS:National patterns of opioid-related poisonings are shifting among older adults, including the types of opioids involved and co-use of other drugs. These results can inform prevention and harm reduction efforts aimed at older adults.

Despite higher chronic disease prevalence, minoritized populations live in highly walkable neighborhoods in US cities more frequently than non-minoritized populations. We investigated whether city-level racial residential segregation (RRS) was associated with city-level walkability, stratified by population density, possibly explaining this counterintuitive association. RRS for Black-White and Latino-White segregation in large US cities was calculated using the Index of Dissimilarity (ID), and walkability was measured using WalkScore. Median walkability increased across increasing quartiles of population density, as expected. Higher ID was associated with higher walkability; associations varied in strength across strata of population density. RRS undergirds the observed association between walkability and minoritized populations, especially in higher population density cities.

Proteomic approaches have unique advantages in the identification of biological pathways that influence physical frailty, a multifactorial geriatric syndrome predictive of adverse health outcomes in older adults. To date, proteomic studies of frailty are scarce, and few evaluated prefrailty as a separate state or examined predictors of incident frailty. Using plasma proteins measured by 4955 SOMAmers in the Atherosclerosis Risk in Community study, we identified 134 and 179 proteins cross-sectionally associated with prefrailty and frailty, respectively, after Bonferroni correction (p < 1 × 10^-5 ) among 3838 older adults aged ≥65 years, adjusting for demographic and physiologic factors and chronic diseases. Among them, 23 (17%) and 82 (46%) were replicated in the Cardiovascular Health Study using the same models (FDR p < 0.05). Notably, higher odds of prefrailty and frailty were observed with higher levels of growth differentiation factor 15 (GDF15; p_prefrailty  = 1 × 10^-15 , p_frailty  = 2 × 10^-19 ), transgelin (TAGLN; p_prefrailty  = 2 × 10^-12 , p_frailty  = 6 × 10^-22 ), and insulin-like growth factor-binding protein 2 (IGFBP2; p_prefrailty  = 5 × 10^-15 , p_frailty  = 1 × 10^-15 ) and with a lower level of growth hormone receptor (GHR, p_prefrailty  = 3 × 10^-16 , p_frailty  = 2 × 10^-18 ). Longitudinally, we identified 4 proteins associated with incident frailty (p < 1 × 10^-5 ). Higher levels of triggering receptor expressed on myeloid cells 1 (TREM1), TAGLN, and heart and adipocyte fatty-acid binding proteins predicted incident frailty. Differentially regulated proteins were enriched in pathways and upstream regulators related to lipid metabolism, angiogenesis, inflammation, and cell senescence. Our findings provide a set of plasma proteins and biological mechanisms that were dysregulated in both the prodromal and the clinical stage of frailty, offering new insights into frailty etiology and targets for intervention.