Faculty Bibliography

OBJECTIVE:To examine the relationships between post-stroke depression and cognition using network analysis. In particular, we identified central depressive symptoms, central cognitive performances, and bridge components that connect these 2 constructs. DESIGN/METHODS:An observational study. We applied network analysis to analyze baseline data to visualize and quantify the relationships between depression and cognition. SETTING/METHODS:Home and Community. PARTICIPANTS/METHODS:202 participants with mild-to-moderate stroke (N=202; mean age: 59.7 years; 55% men; 55% Whites; 90% ischemic stroke). INTERVENTION/METHODS:Not applicable. MAIN OUTCOME MEASURES/METHODS:Patient Health Questionnaire (PHQ-8) for depressive symptoms and the NIH Toolbox Cognitive Battery for cognitive performances. RESULTS:Depressive symptoms were positively intercorrelated with the network, with symptoms from similar domains clustered together. Mood (expected influence=1.58), concentration (expected influence=0.67), and guilt (expected influence=0.63) were the top 3 central depressive symptoms. Cognitive performances also showed similar network patterns, with executive function (expected influence=0.89), expressive language (expected influence=0.68), and processing speed (expected influence=0.48) identified as the top 3 central cognitive performances. Psychomotor functioning (bridge expected influence=2.49) and attention (bridge expected influence=1.10) were the components connecting depression and cognition. CONCLUSIONS:The central and bridge components identified in this study might serve as targets for interventions against these deficits. Future trials are needed to compare the effectiveness of interventions targeting the central and bridge components vs general interventions treating depression and cognitive impairment as a homogenous clinical syndrome.

BACKGROUND:Type 2 diabetes disproportionately affects South Asian subgroups. Lifestyle prevention programs help prevent and manage diabetes; however, there is a need to tailor these programs for mobile health (mHealth). OBJECTIVE:This study examined technology access, current use, and preferences for health communication among South Asian immigrants diagnosed with or at risk for diabetes, overall and by sex. We examined factors associated with interest in receiving diabetes information by (1) text message, (2) online (videos, voice notes, online forums), and (3) none or skipped, adjusting for sociodemographic characteristics and technology access. METHODS:We used baseline data collected in 2019-2021 from two clinical trials among South Asian immigrants in New York City (NYC), with one trial focused on diabetes prevention and the other focused on diabetes management. Descriptive statistics were used to examine overall and sex-stratified impacts of sociodemographics on technology use. Overall logistic regression was used to examine the preference for diabetes information by text message, online (videos, voice notes, or forums), and no interest/skipped response. RESULTS:The overall sample (N=816) had a mean age of 51.8 years (SD 11.0), and was mostly female (462/816, 56.6%), married (756/816, 92.6%), with below high school education (476/816, 58.3%) and limited English proficiency (731/816, 89.6%). Most participants had a smartphone (611/816, 74.9%) and reported interest in receiving diabetes information via text message (609/816, 74.6%). Compared to male participants, female participants were significantly less likely to own smartphones (317/462, 68.6% vs 294/354, 83.1%) or use social media apps (Viber: 102/462, 22.1% vs 111/354, 31.4%; WhatsApp: 279/462, 60.4% vs 255/354, 72.0%; Facebook: Messenger 72/462, 15.6% vs 150/354, 42.4%). A preference for receiving diabetes information via text messaging was associated with male sex (adjusted odds ratio [AOR] 1.63, 95% CI 1.01-2.55; P=.04), current unemployment (AOR 1.62, 95% CI 1.03-2.53; P=.04), above high school education (AOR 2.17, 95% CI 1.41-3.32; P<.001), and owning a smart device (AOR 3.35, 95% CI 2.17-5.18; P<.001). A preference for videos, voice notes, or online forums was associated with male sex (AOR 2.38, 95% CI 1.59-3.57; P<.001) and ownership of a smart device (AOR 5.19, 95% CI 2.83-9.51; P<.001). No interest/skipping the question was associated with female sex (AOR 2.66, 95% CI 1.55-4.56; P<.001), high school education or below (AOR 2.02, 95% CI 1.22-3.36; P=.01), not being married (AOR 2.26, 95% CI 1.13-4.52; P=.02), current employment (AOR 1.96, 95% CI 1.18-3.29; P=.01), and not owning a smart device (AOR 2.06, 95% CI 2.06-5.44; P<.001). CONCLUSIONS:Technology access and social media usage were moderately high in primarily low-income South Asian immigrants in NYC with prediabetes or diabetes. Sex, education, marital status, and employment were associated with interest in mHealth interventions. Additional support to South Asian women may be required when designing and developing mHealth interventions. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03333044; https://classic.clinicaltrials.gov/ct2/show/NCT03333044, ClinicalTrials.gov NCT03188094; https://classic.clinicaltrials.gov/ct2/show/NCT03188094. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:RR2-10.1186/s13063-019-3711-y.

Due to the high prevalence of childhood obesity, it is imperative to assess the relationship children's access to food retailers and obesity. However, the influence of methodological decisions on these associations has been understudied. We examined relationships between different measures of geospatial food environment (using 4 data sources, and 2 data processing methods), and BMI in a sample of low-income children in Baltimore, Maryland. The choice of data sources and data processing methods produced large differences in estimates of children's exposures to certain store types, such as supermarket-like stores, but had less impact on associations with BMI z-scores.

OBJECTIVES/OBJECTIVE:To test the feasibility, acceptability, and potential efficacy of a mHealth intervention tailored for Chinese immigrant families with type 2 diabetes (T2D). METHODS:We conducted a pilot randomized controlled trial (RCT) with baseline, 3-, and 6-month measurements. Participating dyads, T2D patients and families/friends from NYC, were randomized into the intervention group (n = 11) or the wait-list control group (n = 12). Intervention includes 24 videos covering T2D self-management, behavioral techniques, and family-oriented sessions. Feasibility and acceptability were measured respectively by the retention rate and video watch rate, and a satisfaction survey. Patients' HbA1c, weight, and self-management were also assessed to test potential efficacy. RESULTS:Most T2D patients (n = 23; mean age 56.2±9.4 years; 52.2% male) and families/friends (n = 23, mean age 54.6±11.2 years; 52.2% female) had high school education or less (69.6% and 69.6%), annual household income < $25,000 (65.2% and 52.2%), and limited English proficiency (95.7% and 95.7%). The retention rates were not significantly different between the intervention and the control groups for both the patients (90.91% vs 83.3%, p = 0.589); and their families/friends (3-month: 90.9% vs 75%, p = 0.313; 6-month: 90.9% vs 83.3%, p = 0.589). The mean video watch rate was 76.8% (7%). T2D patients and families/friends rated satisfaction as 9.4 and 10 out of 10, respectively. Despite no between-group differences, the intervention group had significantly lower HbA1c (p = 0.014) and better self-management (p = 0.009), and lost 12 lbs. on average at 6 months (p = 0.079), compared to their baseline levels. CONCLUSIONS:A culturally-tailored, family-based mHealth intervention is feasible and acceptable among low-income, limited English-proficient Chinese families with T2D in NYC. Significant changes in HbA1c and self-management within the intervention group indicate this intervention may have potential efficacy. Given the small sample size of this study, a future RCT with adequate power is needed to test efficacy.

PURPOSE/UNASSIGNED:The purpose of this study is to describe diabetes distress and related factors among Chinese Americans with type 2 diabetes in New York City (NYC). METHODS/UNASSIGNED:We conducted a secondary data analysis of the baseline data from three research studies conducted among community-dwelling Chinese American adults with type 2 diabetes. Diabetes Distress Scale (DDS) was used to measure sources of diabetes distress including emotional-, regimen-, interpersonal-, and physician-related distress. A score of 2 or greater indicates moderate diabetes distress or higher. Patient Health Questionnaire-2 (PHQ-2) was used to measure depressive symptoms. Participants' sociodemographic information was also collected. Descriptive statistics were used to describe diabetes distress, and logistic least absolute shrinkage and selection operator (LASSO) regression was used to examine factors associated with diabetes distress level. RESULTS/UNASSIGNED:Data from 178 participants (mean age 63.55±13.56 years) were analyzed. Most participants were married (76.40%), had a high school degree or less (65.73%), had a household annual income < $25,000 (70.25%), and reported limited English proficiency (93.22%). About 25.84% reported moderate or higher overall distress. The most common sources of distress were emotional burden (29.78%), followed by regimen- (28.65%), interpersonal- (18.54%), and physician-related distress (14.04%). Participants who were younger, female, limited English proficient, and had elevated depressive symptoms were more likely to have higher diabetes distress. CONCLUSION/UNASSIGNED:Diabetes distress is prevalent among Chinese immigrants with type 2 diabetes, especially emotional- and regimen-related distress. Given the known link between diabetes distress and poor glycemic control, it is critical to screen for diabetes distress at primary care clinics and incorporate psychological counseling in diabetes care in this underserved population.

PURPOSE/UNASSIGNED:To explore the relationship between activity engagement and dyadic illness perceptions of community-dwelling individuals with stroke and their caregivers. METHODS/UNASSIGNED:We performed a secondary analysis on a cross-sectional study encompassing eight rehabilitation settings. Participants were recruited from June to December 2019 via the distribution of flyers, use of admission databases, and direct onsite interactions. Activity engagement of individuals with stroke was measured by the Assessment of Life Habits. Dyadic illness perceptions were measured using the Stroke-Specific Illness Perceptions Questionnaire-Revised. RESULTS/UNASSIGNED: CONCLUSIONS/UNASSIGNED:Illness perceptions and post-stroke activity engagement with gender differences should be considered at a dyadic level, as the individuals with stroke and their caregivers influence each other's beliefs.

OBJECTIVE:To assess the criterion validity of a dietary screener questionnaire adapted for Asian Americans (ADSQ) compared to Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA-24) food diary data amongst Chinese American Adults (CHAs). The ADSQ incorporated example ethnic foods from six Asian American groups. Lessons learned with respect to translating the ADSQ from English into Simplified Chinese were also documented. DESIGN/METHODS:Agreement between a two-day food diary (one weekend day and one weekday) and the ADSQ was assessed for vegetable, fruit, dairy, added sugar, fiber, calcium, and whole grain intake using paired t-tests to compare means and Spearman correlations to assess agreement between intake of food components. SETTING/METHODS:Data were collected online and via phone interviews. PARTICIPANTS/METHODS:Thirty-three CHAs aged 19-62 years (63.6% female). RESULTS:Mean differences were small for fruit, dairy, fiber, calcium, and whole grain intake, but were significantly different for vegetables and added sugar intake. Spearman correlations were < 0.5 and non-significant (p > 0.05) for all components. Both the ASA-24 and the ADSQ identified the same categories where CHAs intake is misaligned with dietary recommendations: whole grains, total fruit, and dairy. Difficulties were encountered in translating 13 out of 26 questions. CONCLUSIONS:The ADSQ may be a useful tool to identify intervention targets for improving dietary quality, but caution is warranted when interpreting vegetable and added sugar estimates. Differences in the English and Chinese languages underscore the need to take into account both literal translations and semantics in translating the ADSQ into other languages.

BACKGROUND:Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR. OBJECTIVE:This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study. METHODS:The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions. RESULTS:We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values. CONCLUSIONS:Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

OBJECTIVE/UNASSIGNED:The objective of this study was to evaluate the relative validity of the nine-item Diet Risk Score (DRS) among Chinese American adults using Healthy Eating Index (HEI)-2015 scores. We provide insights into the application of the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) for this population, and report on lessons learned from carrying out participant recruitment during the COVID-19 pandemic. METHODS/UNASSIGNED:Thirty-three Chinese American adults (mean age=40; 36% male) were recruited from the community and through ResearchMatch. Participants completed the DRS and two 24-hour food records, which were entered into the ASA 24-Hour Dietary Assessment Tool (ASA24) by community health workers (CHWs). HEI-2015 scores were calculated from each food record and an average score was obtained for each participant. One-way analysis of variance and Spearman correlations were used to compare total and component scores between the DRS and HEI-2015. RESULTS/UNASSIGNED:Mean HEI-2015 score was 56.7/100 (SD 10.6) and mean DRS score was 11.8/27 (SD 4.7), with higher scores reflecting better and worse diets, respectively. HEI-2015 and DRS scores were inversely correlated (r=-0.43, p<0.05). The strongest correlations were between HEI-2015 Total Vegetables and DRS Vegetables (r=-0.5, p<0.01), HEI-2015 Total Vegetables and Green Vegetables (r=-0.43, p=0.01) and HEI-2015 Seafood/Plant Protein and DRS Fish (r=-0.47, p<0.01). The inability to advertise and recruit for the study in person at community centres due to pandemic restrictions impeded the recruitment of less-acculturated individuals. A lack of cultural food items in the ASA24 database made it difficult to record dietary intake as reported by participants. CONCLUSION/UNASSIGNED:The DRS can be a valuable tool for physicians to identify and reach Chinese Americans at risk of cardiometabolic disease.

OBJECTIVES/OBJECTIVE:Although technology-supported interventions are effective for reducing chronic disease risk, little is known about the relative and combined efficacy of mobile health strategies aimed at multiple lifestyle factors. The purpose of this clinical trial is to evaluate the efficacy of technology-supported behavioral intervention strategies for managing multiple lifestyle-related health outcomes in overweight adults with type 2 diabetes (T2D) and chronic kidney disease (CKD). DESIGN AND METHODS/METHODS:, age ≥40 years), T2D, and CKD stages 2-4 were randomized to an advice control group, or remotely delivered programs consisting of synchronous group-based education (all groups), plus (1) Social Cognitive Theory-based behavioral counseling and/or (2) mobile self-monitoring of diet and physical activity. All programs targeted weight loss, greater physical activity, and lower intakes of sodium and phosphorus-containing food additives. RESULTS:Of 256 randomized participants, 186 (73%) completed 6-month assessments. Compared to the ADVICE group, mHealth interventions did not result in significant changes in weight loss, or urinary sodium and phosphorus excretion. In aggregate analyses, groups receiving mobile self-monitoring had greater weight loss at 3 months (P = .02), but between 3 and 6 months, weight losses plateaued, and by 6 months, the differences were no longer statistically significant. CONCLUSIONS:When engaging patients with T2D and CKD in multiple behavior changes, self-monitoring diet and physical activity demonstrated significantly larger short-term weight losses. Theory-based behavioral counseling alone was no better than baseline advice and demonstrated no interaction effect with self-monitoring.