Faculty Bibliography

BACKGROUND:Offering medications for opioid use disorder (MOUD) in carceral settings significantly reduces overdose. However, it is unknown to what extent individuals in jails continue MOUD once they leave incarceration. We aimed to assess the relationship between in-jail MOUD and MOUD continuity in the month following release. METHODS:We conducted a retrospective cohort study of linked NYC jail-based electronic health records and community Medicaid OUD treatment claims for individuals with OUD discharged from jail between 2011 and 2017. We compared receipt of MOUD within 30 days of release, among those with and without MOUD at release from jail. We tested for effect modification based on MOUD receipt prior to incarceration and assessed factors associated with treatment discontinuation. RESULTS:Of 28,298 eligible incarcerations, 52.8 % received MOUD at release. 30 % of incarcerations with MOUD at release received community-based MOUD within 30 days, compared to 7 % of incarcerations without MOUD (Risk Ratio: 2.62 (2.44-2.82)). Most (69 %) with MOUD claims prior to incarceration who received in-jail MOUD continued treatment in the community, compared to 9 % of those without prior MOUD. Those who received methadone (vs. buprenorphine), were younger, Non-Hispanic Black and with no history of MOUD were less likely to continue MOUD following release. CONCLUSIONS:MOUD maintenance in jail is strongly associated with MOUD continuity upon release. Still, findings highlight a gap in treatment continuity upon-reentry, especially among those who initiate MOUD in jail. In the wake of worsening overdose deaths and troubling disparities, improving MOUD continuity among this population remains an urgent priority.

OBJECTIVE:Although some studies have observed an association between birthweight and cardiovascular disease in adulthood, fewer have investigated whether birthweight is linked to cardiovascular health in early childhood. This study assesses the association between birthweight and cardiovascular outcomes in children 6 years of age. STUDY DESIGN/METHODS:Birthweight, blood pressure (BP), and markers of arterial stiffness in children, including brachial artery distensibility and carotid-femoral pulse wave velocity (cfPWV), were obtained from 324 participants in The Infant Development and the Environment Study, a prospective multisite pregnancy cohort. Birthweight was converted into sex-specific birthweight-for-gestational-age (bw/ga) z -scores based on the INTERGROWTH-21st standard. Following 2017 American Academy of Pediatrics guidelines, SBP and DBP were transformed into sex, age, and height-specific z -scores. Associations between birthweight and cardiovascular outcomes were assessed using nested multivariable linear regression models among the overall and sex-stratified samples. RESULTS:Among the overall sample, bw/ga z -score was positively associated with cfPWV [b = 0.11 m/s, 95% confidence interval (CI): 0.01 m/s, 0.21 m/s] in crude and adjusted models. No associations between birthweight and cardiovascular outcomes were detected among the sex-stratified analyses. CONCLUSION/CONCLUSIONS:Overall, birthweight was not related to cardiovascular outcomes in children 6 years old. However, infants born with a higher birthweight may be at risk for higher cfPWV in childhood. Early intervention in pregnant people at risk of delivering high birthweight infants may be warranted if results are replicated.

Studies have recently begun to explore the potential long-term health impacts of homeownership policies implemented in the New Deal era. We investigated the association between assigned grades of lending risk by the Home Owners' Load Corporation (HOLC) maps from the 1930s and present-day prevalence of three cardiovascular risk factors (diabetes and obesity in 2020, and hypertension in 2019), estimated at the census tract level in the United States. To minimize potential confounding, we adjusted for sociodemographic data from the time period when HOLC maps were made. We calculated propensity scores (predicted probability of receiving a HOLC grade) and created a pseudo-population using inverse probability weighting. We then employed marginal structural models to estimate prevalence differences comparing A vs. B, B vs. C, and C vs. D HOLC grades. Adjusting only for regions, a less desirable HOLC grade was associated with higher estimated prevalence rates of present-day cardiovascular risk factors; however, most differences were no longer significant after applying propensity score methods. The one exception was that the prevalence of diabetes, hypertension, and obesity were all higher in C vs. B graded census tracts, while no differences were observed for C and D and A and B comparisons. These results contribute to a small body of evidence that suggests historical "yellowlining" (as C grade was in color yellow) may have had persistent impacts on neighborhood-level cardiovascular risk factors 80 years later.

With a renewed focus on health equity in the United States driven by national crises and legislation to improve digital healthcare innovation, there is a need for the designers of digital health tools to take deliberate steps to design for equity in their work. A concrete toolkit of methods to design for health equity is needed to support digital health practitioners in this aim. This narrative review summarizes several health equity frameworks to help digital health practitioners conceptualize the equity dimensions of importance for their work, and then provides design approaches that accommodate an equity focus. Specifically, the Double Diamond Model, the IDEAS framework and toolkit, and community collaboration techniques such as participatory design are explored as mechanisms for practitioners to solicit input from members of underserved groups and better design digital health tools that serve their needs. Each of these design methods requires a deliberate effort by practitioners to infuse health equity into the approach. A series of case studies that use different methods to build in equity considerations are offered to provide examples of how this can be accomplished and demonstrate the range of applications available depending on resources, budget, product maturity, and other factors. We conclude with a call for shared rigor around designing digital health tools that deliver equitable outcomes for members of underserved populations.

Measures of selective constraint on genes have been used for many applications, including clinical interpretation of rare coding variants, disease gene discovery and studies of genome evolution. However, widely used metrics are severely underpowered at detecting constraints for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. Here we developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, s_het. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease and other phenotypes, especially for short genes. Our estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve the estimation of many gene-level properties, such as rare variant burden or gene expression differences.

OBJECTIVE:Colorectal cancer (CRC) is the third leading cause of cancer death among both men and women in the United States. CRC-related events may increase media coverage and public attention, boosting awareness and prevention. This study examined associations between several types of CRC events (including unplanned celebrity cancer deaths and planned events like national CRC awareness months, celebrity screening behavior, and screening guideline changes) and news coverage, Twitter discussions, and Google search trends about CRC and CRC screening. METHODS:We analyzed data from U.S. national news media outlets, posts scraped from Twitter, and Google Trends on CRC and CRC screening during a three-year period from 2020 to 2022. We used burst detection methods to identify temporal spikes in the volume of news, tweets, and search after each CRC-related event. RESULTS:There is a high level of heterogeneity in the impact of celebrity CRC events. Celebrity CRC deaths were more likely to precede spikes in news and tweets about CRC overall than CRC screening. Celebrity screening preceded spikes in news and tweets about screening but not searches. Awareness months and screening guideline changes did precede spikes in news, tweets, and searches about screening, but these spikes were inconsistent, not simultaneous, and not as large as those events concerning most prominent public figures. CONCLUSIONS:CRC events provide opportunities to increase attention to CRC. Media and public health professionals should actively intervene during CRC events to increase emphasis on CRC screening and evidence-based recommendations.

A large body of research has documented racial/ethnic disparities in childhood obesity in the United States (US) but less work has sought to understand differences within racial groups. Longitudinal studies are needed to describe BMI trajectories across development, particularly for Black children from immigrant families who have been underrepresented in childhood obesity research. The current study utilizes BMI data collected longitudinally from ages 5 to 8 years and growth mixture modeling to (1) identify and visualize growth patterns among Black children from primarily Caribbean immigrant families, and (2) to compare these patterns to growth trajectories among Black children from US-born families. First, we identified four classes or trajectories of growth for Black children from immigrant families. The largest trajectory (70% of the sample) maintained non-overweight throughout the study period. A second trajectory developed overweight by age 8 (25%). Two small trajectory groups demonstrated high rates of moderate and severe obesity-i.e., specifically, a trajectory of accelerated weight gain ending in moderate/severe obesity (3%), and a trajectory of early severe obesity with BMI decreasing slightly with age (2%). We identified a very similar four class/trajectory model among Black children from US-born families, and compared the model to the one for children from immigrant families using multi-group growth mixture modeling. We found that the patterns of growth did not differ significantly between the populations, with two notable exceptions. Among Black children from immigrant families, ∼ 5% were classified into the two heavier BMI trajectories, compared to ∼ 11% of children from US-born families. Additionally, among children with an accelerated weight gain trajectory, children from immigrant families had lower BMIs on average at each time point than children from US-born families. These findings describe the multiple trajectories of weight gain among Black children from immigrant families and demonstrate that although these trajectories are largely similar to those of Black children from US-born families, the differences provide some evidence for lower obesity risk among Black children from immigrant families compared to Black children from US-born families. As this study is the first to describe BMI trajectories for Black children from immigrant families across early and middle childhood, future work is needed to replicate these results and to explore differences in heavier weight trajectories between children from immigrant and US-born families.