Faculty Bibliography

OBJECTIVES/OBJECTIVE:Edentulism and diabetes mellitus (DM) are frequently seen among older adults. However, the joint effect of edentulism and DM on mortality was understudied. We aim to examine the joint effect of edentulism and DM on all-cause mortality and to what extent the joint effect varies by race/ethnicity. METHODS:Analysis of US Health and Retirement Study (HRS) data (2006-2018) included 11,813 non-Hispanic Whites, 2216 non-Hispanic Blacks, and 1337 Hispanics aged ≥ 50 years old. Mortality data came from the National Death Index or HRS surveys. Edentulism was self-reported and DM was determined by self-reported diagnosis, medication use, or glycosylated hemoglobin. Cox proportional-hazard models with inverse probability treatment weighting were applied. RESULTS:During mean follow-up of 9.6 years, 2874 Whites, 703 Blacks, and 441 Hispanics died. DM was associated with higher mortality across all groups (Whites: HR = 1.43, 95% CI = 1.25-1.64; Blacks: HR = 1.62, 95% CI = 1.28-2.04; Hispanics: HR = 1.46, 95% CI = 1.07-1.99). However, edentulism predicted higher mortality only in Whites (HR = 1.65, 95% CI = 1.51-1.80). Having both conditions showed highest mortality risk in all groups (Whites: HR = 2.31, 95% CI = 1.56-3.42; Blacks: HR = 1.94, 95% CI = 1.45-2.59; Hispanics: HR = 1.77, 95% CI = 1.16-2.70), with a significant additive interaction observed only in Whites (relative excess risk due to interaction = 0.22, p < 0.05). CONCLUSIONS:DM and edentulism pose an additive risk for mortality in Whites, and there are racial/ethnic differences in edentulism-related mortality.

OBJECTIVE:This study examined associations between access to leisure-time physical activity (LTPA) facilities and parks and repeated measures of glycated hemoglobin (A1C) over time, using follow-up tests among United States Veterans with newly diagnosed type-2 diabetes (T2D). METHODS:Data were analyzed from 274,463 patients in the Veterans Administration Diabetes Risk cohort who were newly diagnosed with T2D between 2008 and 2018 and followed through 2023. Generalized estimating equations with a logit link function and binomial logistic regression were used to examine associations. RESULTS:Patients were on average 60.5 years of age, predominantly male (95.0 %) and white (66.9 %), and had an average of 11.7 A1C tests during the study follow-up period. In high- and low-density urban communities, a one-unit higher LTPA facility density score was associated with 1 % and 3 % greater likelihood of in-range A1C tests during follow-up, respectively, but no association was observed among patients living in suburban/small town and rural communities. Across community types, closer park distance was not associated with subsequent greater odds of in-range A1C tests. Unexpectedly, in low-density urban areas, the likelihood of in-range A1C tests was 1 % lower at farther park distances. CONCLUSIONS:These results suggest that broader access to LTPA facilities, but not park proximity, may contribute in small ways to maintaining glycemic control after T2D diagnosis in urban communities. Tailored interventions may be needed to promote patients' effective use of LTPA facilities and parks.

OBJECTIVE:Racial/ethnic disparities in glycemic control among non-Hispanic Black (NHB) and non-Hispanic White (NHW) veterans with type 2 diabetes (T2D) have been reported. This study examined trends in early glycemic control by race/ethnicity to understand how disparities soon after T2D diagnosis have changed between 2008 and 2019 among cohorts of U.S. veterans with newly diagnosed T2D. RESEARCH DESIGN AND METHODS/METHODS:We estimated the annual percentage of early glycemic control (average A1C <7%) in the first 5 years after diagnosis among 837,023 veterans (95% male) with newly diagnosed T2D in primary care. We compared early glycemic control by racial/ethnic group among cohorts defined by diagnosis year (2008-2010, 2011-2013, 2014-2016, and 2017-2018) using mixed-effects models with random intercepts. We estimated odds ratios of early glycemic control comparing racial/ethnic groups with NHW, adjusting for age, sex, and years since diagnosis. RESULTS:The average annual percentage of veterans who achieved early glycemic control during follow-up was 73%, 72%, 72%, and 76% across the four cohorts, respectively. All racial/ethnic groups were less likely to achieve early glycemic control compared with NHW veterans in the 2008-2010 cohort. In later cohorts, NHB and Hispanic veterans were more likely to achieve early glycemic control; however, Hispanic veterans were also more likely to have an A1C ≥9% within 5 years in all cohorts. Early glycemic control disparities for non-Hispanic Asian, Native Hawaiian/Pacific Islander, and American Indian/Alaska Native veterans persisted in cohorts until the 2017-2018 cohort. CONCLUSIONS:Overall early glycemic control trends among veterans with newly diagnosed T2D have been stable since 2008, but trends differed by racial/ethnic groups and disparities in very poor glycemic control were still observed. Efforts should continue to minimize disparities among racial/ethnic groups.

BACKGROUND:Over a third of US adults carry a diagnosis of prediabetes, 70% of whom may progress to type 2 diabetes mellitus ("diabetes"). Community health workers (CHWs) can help patients undertake healthy behavior to prevent diabetes. However, there is limited guidance to integrate CHWs in primary care, specifically to address CHWs' dual clinic-based and community-oriented role. OBJECTIVE:Using evidence from CHWs' adaptations of a diabetes-prevention intervention in safety-net hospitals in New York City, we examine the nature, intent, and possible consequences of CHWs' actions on program fidelity. We propose strategies for integrating CHWs in primary care. DESIGN/METHODS:Case study drawing on the Model for Adaptation Design and Impact (MADI) to analyze CHWs' actions during implementation of CHORD (Community Health Outreach to Reduce Diabetes), a cluster-randomized pragmatic trial (2017-2022) at Manhattan VA and Bellevue Hospital. PARTICIPANTS/METHODS:CHWs and clinicians in the CHORD study, with a focus in this analysis on CHWs. APPROACH/METHODS:Semi-structured interviews and focus group discussion with CHWs (n=4); semi-structured interviews with clinicians (n=17). Interpretivist approach to explain CHWs' adaptations using a mix of inductive and deductive analysis. KEY RESULTS/RESULTS:CHWs' adaptations extended the intervention in three ways: by extending social assistance, healthcare access, and operational tasks. The adaptations were intended to improve fit, reach, and retention, but likely had ripple effects on implementation outcomes. CHWs' focus on patients' complex social needs could divert them from judiciously managing their caseload. CONCLUSIONS:CHWs' community knowledge can support patient engagement, but overextension of social assistance may detract from protocolized health-coaching goals. CHW programs in primary care should explicitly delineate CHWs' non-health support to patients, include multiprofessional teams or partnerships with community-based organizations, establish formal communication between CHWs and clinicians, and institute mechanisms to review and iterate CHWs' work to resolve challenges in their community-oriented role.

BACKGROUND:While Type 2 Diabetes Mellitus (T2DM) prevalence is increasing among younger individuals, few studies have examined how age at T2DM diagnosis relates to dementia risk in diabetic populations. We aimed to investigate the association between age at T2DM diagnosis and subsequent dementia risk, and to determine whether obesity moderates this relationship. METHODS:We conducted a prospective cohort study using data from the Health and Retirement Study (2002-2016) matched with its 2003 Diabetes Mail-Out Survey. The study included 1,213 dementia-free adults aged ≥50 with diagnosed T2DM. Primary exposures were age at T2DM diagnosis (categorized as <50, 50-59, 60-69, and ≥70 years) and obesity status (BMI ≥30 kg/m2). The outcome was incident dementia, assessed using the Telephone Interview for Cognitive Status. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for sociodemographic factors, health behaviors, health status, and diabetes medication use. RESULTS:Over a median follow-up of 10 (interquartile range, 6-14) years, 216 (17.8%) participants developed dementia. Compared to participants diagnosed with T2DM at age ≥70 years, those diagnosed at younger ages had increased dementia risk: HR 1.70 (95% CI, 1.03-2.80) for 60-69 years, 1.72 (95% CI, 1.06-2.79) for 50-59 years, and 1.90 (95% CI, 1.14-3.18) for <50 years. Obesity significantly moderated this relationship, with obese individuals diagnosed with T2DM before age 50 showing the highest dementia risk (HR 3.05; 95% CI 1.23-7.56) compared to non-obese individuals diagnosed at ≥50 years. CONCLUSIONS:Younger age at diagnosis of T2DM was significantly associated with a higher risk of dementia, particularly among individuals with obesity. Interventions specifically targeting obesity may be more effective in preventing dementia for adults with a younger onset of T2DM.

OBJECTIVES:This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS:We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS:We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS:We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

Background A number of studies have shown an association between social determinants of health and the emergence of obesity and diabetes, but whether the relationship is causal is not clear. Objective To test whether social, environmental, and medical determinants directly or indirectly affect population-level diabetes prevalence after controlling for mediator-mediator interactions. Methods Data were obtained from the CDC and supplemented with nine other data sources for 3,109 US counties. The dependent variable was the prevalence of diabetes in 2017. Independent variables were a given county's 30 social, environmental, and medical characteristics in 2015 and 2016. A network multiple mediation analysis was conducted. First, we used Least Absolute Shrinkage and Selection Operator (LASSO) regression to relate the 2017 diabetes rate in each county to 30 predictors measured in 2016, identifying statistically significant and robust predictors as the mediators within the network model and as direct determinants of 2017 diabetes. Second, each of the direct causes of diabetes was taken as a new response variable and LASSO-regressed on the same 30 independent variables measured in 2015, identifying the indirect (mediated) causes of diabetes. Subsequently, these direct and indirect predictors were used to construct a network model. The completed network was then employed to estimate the direct and mediated impact of variables on diabetes. Results For 2017 diabetes rates, 63% of the variation was explained by five variables measured in 2016: the percentage of residents who were (1) obese, (2) African American, (3) physically inactive, (4) in poor health condition, and (5) had a history of diabetes. These five direct predictors, measured in 2016, mediated the effect of indirect variables measured in 2015, including the percentage of residents who were (1) Hispanic, (2) physically distressed, (3) smokers, (4) living with children in poverty, (5) experiencing limited access to healthy foods, and (6) had low income. Conclusion All of the direct predictors of diabetes prevalence, except the percentage of residents who were African American, were medical conditions potentially influenced by lifestyles. Counties characterized by higher levels of obesity, inactivity, and poor health conditions exhibited increased diabetes rates in the following year. The impact of social determinants of illness, such as low income, children in poverty, and limited access to healthy foods, had an indirect effect on the health of residents and, consequently, increased the prevalence of diabetes.

BACKGROUND:It is critical to assess implementation fidelity of evidence-based interventions and factors moderating fidelity, to understand the reasons for their success or failure. However, fidelity and fidelity moderators are seldom systematically reported. The study objective was to conduct a concurrent implementation fidelity evaluation and examine fidelity moderators of CHORD (Community Health Outreach to Reduce Diabetes), a pragmatic, cluster-randomized, controlled trial to test the impact of a Community Health Workers (CHW)-led health coaching intervention to prevent incident type 2 Diabetes Mellitus in New York (NY). METHODS:We applied the Conceptual Framework for Implementation Fidelity to assess implementation fidelity and factors moderating it across the four core intervention components: patient goal setting, education topic coaching, primary care (PC) visits, and referrals to address social determinants of health (SDH), using descriptive statistics and regression models. PC patients with prediabetes receiving care from safety-net patient-centered medical homes (PCMHs) at either, VA NY Harbor or at Bellevue Hospital (BH) were eligible to be randomized into the CHW-led CHORD intervention or usual care. Among 559 patients randomized and enrolled in the intervention group, 79.4% completed the intake survey and were included in the analytic sample for fidelity assessment. Fidelity was measured as coverage, content adherence and frequency of each core component, and the moderators assessed were implementation site and patient activation measure. RESULTS:Content adherence was high for three components with nearly 80.0% of patients setting ≥ 1 goal, having ≥ 1 PC visit and receiving ≥ 1 education session. Only 45.0% patients received ≥ 1 SDH referral. After adjusting for patient gender, language, race, ethnicity, and age, the implementation site moderated adherence to goal setting (77.4% BH vs. 87.7% VA), educational coaching (78.9% BH vs. 88.3% VA), number of successful CHW-patient encounters (6 BH vs 4 VA) and percent of patients receiving all four components (41.1% BH vs. 25.7% VA). CONCLUSIONS:The fidelity to the four CHORD intervention components differed between the two implementation sites, demonstrating the challenges in implementing complex evidence-based interventions in different settings. Our findings underscore the importance of measuring implementation fidelity in contextualizing the outcomes of randomized trials of complex multi-site behavioral interventions. TRIAL REGISTRATION:The trial was registered with ClinicalTrials.gov on 30/12/2016 and the registration number is NCT03006666 .

INTRODUCTION:Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment. RESEARCH DESIGN AND METHODS:We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type. RESULTS:The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger. CONCLUSIONS:PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.