Faculty Bibliography

Social determinants of health (SDoH), health care use, and cardiovascular disease (CVD) risk perception are understudied among men who identify as Black and Hispanic. In this study we sought to describe these factors among a cohort of urban-residing Black men, participants in a community-engaged trial on hypertension prevention. We focused on presenting intermediary SDoH, including material circumstances, health behaviors, and psychosocial factors, which allow for a more robust understanding of health inequities but are underexplored. We analyzed baseline trial data (N=430) and compared subgroups (44% of participants self-identified as having Hispanic ethnicity and a Black racial identity). Average age was 38 years, with mean blood pressure of 129/83 mmHg. Hispanic Black (HB) men reported higher unemployment (21.4% versus 11.1%, P=.02) and more housing instability (28.7% versus 18.6%, P=.01) than did non-Hispanic Black (NHB) men. Overall, HB men reported worse household conditions compared with NHB men. Approximately half of both groups reported high stress, 45% (HB) and 51% (NHB), respectively. Both groups had low perception of personal CVD risk and underutilized health care. Hispanic Black men were less likely to have a primary care provider than were NHB men (17.6% versus 29.3%, P<.001). Non-Hispanic Black men reported lower physical activity than did HB men (median, 2655 vs 2547 metabolic equivalent minutes/week, P=.03). Recognizing heterogeneity among Black populations, including in social drivers of CVD disparities, will allow for more precision in designing CVD health promotion interventions. Findings also suggest that perception of personal CVD risk and health care utilization may be important targets for CVD prevention in Black men.

Although it is known that caregiver dietary behaviors influence child eating patterns, a gap remains in addressing the diet of a caregiver as much as their child in pediatric practice. A dyadic (caregiver-child) dietary approach would enhance the promotion of healthy eating patterns in children (and their caregivers) and achieve the population health goal of healthy eating across demographic groups. This study aimed to understand factors influencing dyadic dietary patterns (concordance, discordance) and contexts. Twenty professionals who provide nutrition-related expertise for families were recruited via maximum variation sampling. Qualitative thematic analysis of semi-structured interviews revealed 3 themes: (1) variable professional perspectives on what constitutes "healthy eating," (2) eating patterns of a child in the setting of variable caregiver eating practices, and (3) challenges to the promotion of a healthy caregiver-child dyadic diet within a social context. The results offer insight for future interventions that promote positive intergenerational transmission of health.

BACKGROUND:Few studies assess the association between county-level incarceration rates and stroke death, and none test mechanisms. We examine the link between county imprisonment rates and stroke death, testing pathways and identifying racial disparities. METHODS:In a cross-sectional design, we regressed stroke death onto imprisonment rates, adjusting for poverty, racial composition, education, unemployment, insurance, and violent crime. Using bootstrap methodology, we tested mediation through sports/recreational facilities and food environment, mental health provider and primary care physician (PCP) access, and community mental distress. Data spanned 4 years (2016-2019) and included 2260 counties. RESULTS:Adjusted models indicated a 0.08 (95% CI, 0.05-0.10) increase in stroke deaths for every 1-unit change in imprisonment rate. This association was mediated by food environment (indirect effect, 0.006 [95% CI, 0.000-0.014]), primary care physician access (indirect effect, 0.002 [95% CI, 0.000-0.006]), and mental distress (indirect effect, 0.014 [95% CI, 0.007-0.022]). Counties in the top versus bottom quintile of imprisonment rates had 86.26% larger Black populations and 23.46% smaller White populations. Counties in the top versus bottom quintile of stroke death had 88.94% larger Black populations and 16.19% smaller White populations. CONCLUSIONS:Our results complement evidence that living in high-jail-incarceration counties contributes to stroke death and associated racial disparities. We provide new evidence on prison incarceration rates and the pathways underpinning this association. County-level imprisonment rates and the identified mechanisms represent avenues for further research into how stroke death and disparities may be mitigated.

IMPORTANCE/UNASSIGNED:Health-related social needs (HRSN) influence health outcomes and health care utilization. Clinicians face challenges addressing HRSN due to limited skills, expertise, and time. Further insight is needed on how patients and clinicians navigate HRSN in clinical encounters. OBJECTIVE/UNASSIGNED:This study examines outpatient primary care encounters predating widespread HRSN screening to identify how discussions on HRSN are initiated and addressed. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This qualitative analysis was conducted on transcripts of 97 audiotaped English-speaking patient encounters from 3 clinics in New York City within a municipal health care system from January 2011 through April 2015. Patients were eligible if they were older than 18 years, self-identified as Black or White, had a diagnosis of hypertension, and had at least one prior encounter with the participating clinician. Codes were developed from social needs domains addressed by the Accountable Health Communities HRSN Screening Tool. Codes were added for further social needs identified, whether a patient or clinician initiated the HRSN discussion, and how a social need was addressed, if at all. Encounters were analyzed between June 2023 and February 2024. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Characterization of the content and nature of HRSN discussions during clinical encounters within safety-net clinics. RESULTS/UNASSIGNED:A total of 97 patients (55 [56.7%] women, 58 [59.8%] Black, mean [SD] age, 59.7 [10.6] years) had audiotaped encounters with 27 clinicians (18 [66.7%] women, 15 [55.6%] White, mean [SD] age, 36 [5.8] years). Physical activity (36% of encounters), financial strain (35%), mental health (34%), and substance use (28%) were the most discussed HRSN domains across the 97 encounters. Patients introduced financial strain most often (70% of the time), while clinicians led substance use (75%), physical activity (51%) and mental health (51%) discussions. Patients initiated conversations on employment (77%), food insecurity (62%), and housing instability (52%). Interventions included prescriptions, forms, counseling, and referrals. Domains frequently intervened on included health care navigation needs (85% of discussions), substance use (33%), and mental health (27%). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this qualitative study of HRSN discussions in primary care encounters, clinicians were more likely to initiate discussions on substance use, physical activity, and mental health, behaviors routinely assessed in primary care, but different from topics introduced by patients. Findings underscore the need for standardized screening to improve identification of domains less frequently addressed by clinicians. Additional interventions are also needed, including clinician training for how to address HRSN in resource-constrained settings and integration of other health care team members, to enhance HRSN identification and intervention.

IMPORTANCE/UNASSIGNED:Among older adults with ischemic heart disease, participation in traditional ambulatory cardiac rehabilitation (CR) remains low. While mobile health CR (mHealth-CR) provides a novel opportunity to deliver care, age-specific impairments to technology use may limit uptake, and efficacy data are currently lacking. OBJECTIVE/UNASSIGNED:To test whether mHealth-CR improves functional capacity in older adults. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:The RESILIENT phase 2, multicenter, randomized clinical trial recruited patients aged 65 years or older with ischemic heart disease (defined as a hospital visit for myocardial infarction or coronary revascularization) from 5 academic hospitals in New York, Connecticut, and Massachusetts between January 9, 2020, and April 22, 2024. INTERVENTION/UNASSIGNED:Participants were randomized 3:1 to mHealth-CR or usual care. mHealth-CR consisted of commercially available software delivered on a tablet computer, coupled with remote monitoring and weekly exercise therapist telephone calls, delivered over a 3-month duration. As RESILIENT was a trial conducted in a routine care setting to inform decision-making, participants in both arms were also allowed to receive traditional CR at their cardiologist's discretion. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The primary outcome was change from baseline to 3 months in functional capacity, measured by 6-minute walk distance (6MWD). Secondary outcomes were health status (12-Item Short Form Health Survey [SF-12]), residual angina, and impairment in activities of daily living. RESULTS/UNASSIGNED:A total of 400 participants (median age, 71.0 years [range, 65.0-91.0 years]; 291 [72.8%] male) were randomized to mHealth-CR (n = 298) or usual care (n = 102) and included in the intention-to-treat analysis. Of those, 356 participants (89.0%) returned in person for 6MWD assessment at 3 months. For the primary outcome, there was no adjusted difference in 6MWD between participants receiving mHealth-CR vs usual care (15.6 m; 95% CI, -0.3 to 31.5 m; P = .06). Among subgroups, there was an improvement in 6MWD among women (36.6 m; 95% CI, 8.7-64.4 m). There were no differences in any secondary outcomes between groups (eg, adjusted difference in SF-12 physical component scores at 3 months: -1.9 points; 95% CI, -3.9 to 0.2 points). Based on inverse propensity score weighting, there was no effect of mHealth-CR on 6MWD among those who did not attend traditional CR (25.7 m; 95% CI, -8.7 to 60.2 m). CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this randomized clinical trial of mHealth-CR vs usual care, mHealth-CR did not significantly increase 6MWD or result in improvements in secondary outcomes. The findings suggest the older adult population may require more age-tailored mHealth strategies to effectively improve outcomes. TRIAL REGISTRATION/UNASSIGNED:ClinicalTrials.gov Identifier: NCT03978130.

PURPOSE/OBJECTIVE:Hypertension (HTN) is common and represents a major modifiable risk factor for ischemic heart disease in older adults. While home blood pressure monitoring (HBPM) is important in HTN management, patterns of HBPM engagement in older adults undergoing mobile health cardiac rehabilitation (mHealth-CR) are unknown. We aimed to identify patterns of adherence to HBPM in a cohort of older adults undergoing mHealth-CR to optimize HBPM use in the future. METHODS:We used interim data from the ongoing Rehabilitation using Mobile Health for Older Adults with Ischemic Heart Disease in the Home Setting (RESILIENT) randomized trial, in which intervention arm participants (adults ≥ 65 years with ischemic heart disease) were instructed to monitor blood pressure (BP) at least weekly. Engagement groups were determined by latent class analysis and compared using ANOVA or Chi-Square tests. Longitudinal mixed effect modeling determined the associations between weekly HBPM and baseline covariates including uncontrolled HTN, obesity, diabetes, depression, alcohol, and tobacco use. RESULTS:Of the 111 participants, the mean age was 71.9 ± 5.6 years, and 83% had HTN. Over the 12-week study, mean HBPM engagement was 2.3 ± 2.3 d/wk. We observed 3 distinct patterns of engagement: high engagement (22%), gradual decline (10%), and sustained baseline engagement (68%). HBPM adherence decreased in two of the engagement groups over time. Of the covariates tested, only depression was associated with weekly HBPM after adjusting for relevant covariates (OR 9.09, P  = .03). CONCLUSIONS:In this older adult cohort undergoing mHealth-CR, we found three main engagement groups with declining engagement over time in two of the three groups. These patterns can inform future mHealth-CR interventions.