Faculty Bibliography

BACKGROUND:Results from blood pressure (BP) control interventional trials can inform clinicians and health systems pursuing better BP control, but they must be interpreted cautiously. OBJECTIVE:Deconstruct the observed drop in systolic BP (SBP) into components attributable to increased adherence to previously prescribed medications, regression to the mean, and initiation of new medications. DESIGN/METHODS:Secondary analysis of BP Home, a pragmatic randomized controlled trial. PARTICIPANTS/METHODS:Patients owning a smartphone who reported uncontrolled BP at their last clinic visit (> 145 mmHg) and a desire to lower their BP by > 10 mmHg. INTERVENTIONS/METHODS:In BP Home, participants were randomly assigned to receive one of two devices for self-measurement of BP and followed for up to 24 months via electronic health records (EHR). APPROACH/METHODS:The primary outcome was EHR-recorded office SBP. We fit SBP trajectories for each participant using linear mixed models, and estimated the contributions of medication adjustments, and increased adherence to pre-existing BP medications due to their enrollment in a research study (i.e., a Hawthorne effect). Regression to the mean was calculated for each participant as the difference between their last measured pre-enrollment SBP and their modeled SBP trajectory at enrollment. KEY RESULTS/RESULTS:Among participants taking BP medications at enrollment, we estimated an average immediate drop in SBP of -4.2 mmHg (95% CI, -5.1 to -3.3; p < 0.001) at enrollment, explainable by increased medication adherence following study enrollment. Starting a new medication class post-enrollment resulted in an SBP drop of -4.1 mmHg (95% CI, -5.3 to -2.8; p < 0.001). The average expected regression to the mean was -3.9 (95% CI, -4.4 to -3.3; p < 0.001). CONCLUSIONS:A significant portion of BP reductions in trials may stem from increased adherence to pre-existing medications arising from enrollment in a research study and enhanced awareness of their elevated BP. NIH TRIAL REGISTRY NUMBER/UNASSIGNED:NCT03796689 (registered on 2019-01-04).

INTRODUCTION/BACKGROUND:Parenting self-efficacy (PSE) is correlated with positive parenting and child outcomes, but may be reduced in stressful settings. Community factors affecting PSE are not well understood. The community of Flint, Michigan, endured significant stressors, including the Flint Water Crisis (FWC), and disproportionate effects of the COVID-19 pandemic. This study examines how these superimposed stressors affect PSE in families in Flint. METHODS:This study was a secondary, cross-sectional analysis of 291 infants and caregivers. Baseline surveys included sociodemographics, stress, and PSE. Primary predictors were FWC and COVID-19 distress. Primary outcome was PSE. Bivariate analyses were used to examine the association between FWC and COVID-19 distress with PSE, and multiple linear regression to control for sociodemographics. RESULTS:Both increased COVID-19 distress and FWC distress had significant inverse association with PSE in bivariate analyses, and predicted PSE (COVID-19 distress, β -.18, p <.01, and FWC distress, β -.18, p <.05) in multiple linear regression. A significant interaction was found between FWC distress and COVID-19 distress. Simple slope analyses indicated that COVID-19 distress predicted reduced PSE only for high FWC-distress group (β -.22, p <.01). DISCUSSION/CONCLUSIONS:Results show COVID-19 distress and FWC distress both had independent negative associations with PSE, but FWC distress moderated the effect of COVID-19 distress on PSE, indicating that families more affected by previous stressors were more vulnerable to the effects of COVID-19 distress, while those less affected were resilient to subsequent stressors. Future interventions should target disinvestment, prevent community stressors, and support exposed families.

OBJECTIVE:We discuss implications of potential ascertainment biases for studies examining diabetes risk following SARS-CoV-2 infection using electronic health records (EHRs). We quantitatively explore sensitivity of results to misclassification of COVID-19 status using data from the U.S.-based Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network on children (≤17 years) and young adults (18-44 years). MATERIALS AND METHODS/METHODS:In our retrospective case study from the DiCAYA Network, SARS-CoV-2 was identified using labs and diagnoses from June 1, 2020 to December 31, 2021. Patients were followed through December 31, 2022 for new diabetes diagnoses. Sites examined incident diabetes by COVID-19 status using Cox proportional hazards models. Results were pooled in meta-analyses. A bias analysis examined potential impact of COVID-19 misclassification scenarios on results, guided by hypotheses that sensitivity would be <50% and would be higher among those who developed diabetes. RESULTS:Prevalence of documented COVID-19 was low overall and variable across sites (children: 4.4%-7.7%, young adults: 6.2%-22.7%). Individuals with documented COVID-19 were at higher risk of incident diabetes compared to those with no documented infection, but results were heterogeneous across sites. Findings were highly sensitive to COVID-19 misclassification assumptions. Observed results could be biased away from the null under several differential misclassification scenarios. DISCUSSION/CONCLUSIONS:Although EHR-based documentation of COVID-19 was associated with incident diabetes, COVID-19 phenotypes likely had low sensitivity, with considerable variation across sites. Misclassification assumptions strongly impacted interpretation of results. CONCLUSION/CONCLUSIONS:Given the potential for low phenotype sensitivity and misclassification, caution is warranted when interpreting analyses of COVID-19 and incident diabetes using clinical or administrative databases.

BACKGROUND:Pregnant women are widely exposed to organophosphate esters (OPEs). Few studies have examined how gestational OPE exposures may influence child growth rates, which are important predictors of subsequent cardiometabolic health. METHODS:Among 4566 mother-child dyads from 14 sites within the Environmental influences on Child Health Outcomes (ECHO) Cohort, we evaluated associations of gestational urinary concentrations of nine OPE metabolites with early and mid-childhood rates of change in age- and sex-standardized weight (WAZ), height (HAZ), and body mass index (BMIZ). Using linear mixed models, we estimated associations between each OPE metabolite and each growth measure separately in early childhood (2-5 years; n = 4321) and mid-childhood (6-10 years; n = 2504). We evaluated effect modification by child sex and maternal pre-pregnancy BMI. RESULTS:. DISCUSSION/CONCLUSIONS:In this large, diverse sample of U.S. children, gestational exposure to OPEs was associated with child growth rates, but the direction and magnitude differed by OPE biomarker and developmental period (early- or mid-childhood).

We evaluated the effectiveness of a community research partnership focused on improving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing for New York City residents during the pandemic. We employed interviews, a focus group, and a survey to evaluate partnership characteristics, engagement, and future collaboration. Qualitative analysis revealed five core themes: committee identity, collective goals, information sharing, adaptability, and trust. The findings highlight the importance of flexibility, shared goals, diverse representation, open communication, and trust in effective multisector community health partnerships. (Am J Public Health. 2026;116(4):431-436. https://doi.org/10.2105/AJPH.2025.308358).

BACKGROUND:In the US, 40 states and the District of Columbia (DC) have implemented medical cannabis legalization (MCL), while 24 states and DC have enacted some form of recreational cannabis legalization (RCL). We examined the association between cannabis legalization and law enforcement cannabis seizures to understand illegal drug market responses to increasing state cannabis legalization. METHODS:Data on law enforcement cannabis seizures came from the High Intensity Drug Trafficking Areas (HIDTA) program. We tested the association between state-level RCL and MCL adoption and annual changes in cannabis seizures aggregated by state-year from 2010 to 2023 using a series of Poisson regression models that controlled for time-varying state demographic and law enforcement variables in addition to state and year fixed effects. To account for potential lag time between MCL/RCL effective dates and policy impacts on seizures, we conducted additional analyses with 1-year MCL/RCL lags. RESULTS:Over the study period, there were 286,844 cannabis seizures by HIDTA-affiliated agencies, with 686 state-years of observation. In primary adjusted models, RCL adoption was associated with a significant decrease in cannabis seizures in MCL & RCL states versus MCL-only states, both immediately following RCL adoption (exp(β)=0.55, 95% CI: 0.54, 0.56) and one year after RCL went into effect (exp(β) for 1-year lag=0.62, 95% CI: 0.61, 0.64). CONCLUSIONS:The adoption of RCLs in US states, beyond only MCLs, may help to reduce the size of illegal cannabis markets, or there may be shifting law enforcement seizure priorities in those states.

BACKGROUND:Implementation strategies are dynamic and multi-faceted, and may require adaptations to fit implementation contexts, especially in lower-and-middle income countries. We report the adaptations for an ongoing late-stage implementation science trial (R01HL147811) that integrates hypertension management into HIV care in Lagos, Nigeria - a country with a high dual-disease burden - through the Task Strengthening Strategy for Hypertension (TASSH) intervention and Practice Facilitation implementation strategy. METHODS:FRAME (Framework for Reporting Adaptations and Modifications-Enhanced) modules were used to record adaptations to the intervention (i.e., TASSH) respectively, enhance participant recruitment and retention rates, and increase frequency of trainings. Data collection sources included (not limited to) patient records, nurses' logs, and minutes of implementation review meetings. Data across these sources was coded retrospectively by trained research staff and triangulated during virtual meeting discussions. Once consensus was reached, data was mapped onto the relevant framework modules using Microsoft Excel. RESULTS:We modified FRAME to include an additional component on 'what was originally planned' for the context of the adaptations. There were twelve adaptations identified during the implementation of the study. The adaptations characterized by using the frameworks included reordering recruitment start dates of study cohorts, providing patients incentives to attend follow-up visits, adding feeder sites to the study sites, and increasing the frequency of training to account for the high nurse turnover in the primary healthcare centers. Overall, 25% of the adaptations involved expanding the structure of the intervention and implementation strategies, and 33% involved adding new elements to the strategies. All adaptations occurred in the implementation phase of the trial. CONCLUSION/CONCLUSIONS:Based on our experiences, the characterization of the adaptations using FRAME demonstrates their combined applicability to an ongoing trial that can be tailored to fit the local context. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov ( NCT04704336). Registered on 11 January 2021.