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.

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: 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: 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: 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: 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.

INTRODUCTION:Intensive lifestyle intervention remains an effective modality to reduce diabetes incidence and delay the progression to type 2 diabetes. The primary aim of this study was to pilot-test the feasibility and acceptability of a culturally and linguistically tailored web-based DPP intervention among Chinese Americans with prediabetes living in New York City. METHODS:Thirteen Chinese American participants with prediabetes were recruited to complete a 1-year web-based Diabetes Prevention Program (DPP) lifestyle intervention. Quantitative and qualitative measures such as retention rate and data collected from web-based questionnaires and focus groups were collected and analyzed to assess study feasibility and acceptability. RESULTS AND DISCUSSION:online platform successfully demonstrated feasibility and acceptability among Chinese Americans with prediabetes. Further evaluation of the web-based Chinese Diabetes Prevention Program in a larger trial is warranted.

BACKGROUND:Type 2 diabetes (T2D) in Chinese Americans is a rising public health concern for the US health care system. The majority of Chinese Americans with T2D are foreign-born older immigrants and report limited English proficiency and health literacy. Multiple social determinants of health limit access to evidence-based diabetes interventions for underserved Chinese immigrants. A social media-based diabetes intervention may be feasible to reach this community. OBJECTIVE:The purpose of the Chinese American Research and Education (CARE) study was to examine the potential efficacy of a social media-based intervention on glycemic control in Chinese Americans with T2D. Additionally, the study aimed to explore the potential effects of the intervention on psychosocial and behavioral factors involved in successful T2D management. In this report, we describe the design and protocol of the CARE trial. METHODS:and psychosocial and behavioral outcomes. RESULTS:This pilot RCT study was approved by the Institutional Review Board at NYU Grossman School of Medicine in March 2021. The first participant was enrolled in March 2021, and the recruitment goal (n=60) was met in March 2022. All data collection is expected to conclude by November 2022, with data analysis and study results ready for reporting by December 2023. Findings from this pilot RCT will further guide the team in planning a future large-scale study. CONCLUSIONS:This study will serve as an important first step in exploring scalable interventions to increase access to evidence-based diabetes interventions among underserved, low-income, immigrant populations. This has significant implications for chronic care in other high-risk immigrant groups, such as low-income Hispanic immigrants, who also bear a high T2D burden, face similar barriers to accessing diabetes programs, and report frequent social media use (eg, WhatsApp). TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03557697; https://clinicaltrials.gov/ct2/show/NCT03557697. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/42554.

BACKGROUND:Social determinants of health (SDOH) refer to the social, economic, and psychosocial conditions that influence health. Lower levels of SDOH factors including income, education, and employment are associated with a higher prevalence of diabetes, poorer glycemic control, and increased diabetes-related mortality. Few studies have conducted a comprehensive evaluation of multiple SDOH factors in a population with type 2 diabetes mellitus (T2DM). OBJECTIVE:This study aimed to identify the range of SDOH challenges-including diabetes-related distress-that impact patients with insulin-dependent diabetes at an urban safety-net clinic using the 5-domain SDOH framework developed by the Healthy People 2020 initiative. METHODS:The pilot study used a cross-sectional, mixed methods approach. Participants were recruited from 3 programs within a general internal medicine clinic that provides ambulatory care for patients with uncontrolled T2DM. We administered an investigator-developed SDOH survey based on the Healthy People 2020 framework and the validated Diabetes Distress Scale (DDS), which assesses 4 domains of diabetes-related distress. One-on-one interviews were conducted to gain in-depth information about challenges. RESULTS:level of 11.0% (SD 2.6%). Overall, 92% (52/57) of participants had a barrier in at least one SDOH domain. SDOH challenges were most commonly reported in the domain of Health and Health Care (84%, 48/57), followed by Economic Stability (54%, n=31), Neighborhood and Built Environment (53%, n=30), Education and Health Literacy (47%, n=27), and Social and Community context (37%, n=21). The mean overall DDS score was 2.09 (SD 0.84), where scores of ≥2 indicate distress. Further, 79% (45/57) of participants had at least moderate diabetes-related distress in one of the 4 DDS domains. General themes that emerged from participant interviews included job interference with healthy behaviors, concerns about burdening others, challenges communicating with providers, and difficulty getting appointments in a timely manner. CONCLUSIONS:We found high levels of SDOH barriers across all 5 domains of the Center for Disease Control and Prevention's Healthy People 2020 framework, including significant levels of diabetes-related distress. Future programs to address SDOH barriers in patients with uncontrolled insulin-dependent diabetes should consider screening for and focusing on a wide range of challenges.

Importance:Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that estimates personalized PPGR to specific foods may be more efficacious for weight loss. Objective:To compare a standardized low-fat vs a personalized diet regarding percentage of weight loss in adults with abnormal glucose metabolism and obesity. Design, Setting, and Participants:The Personal Diet Study was a single-center, population-based, 6-month randomized clinical trial with measurements at baseline (0 months) and 3 and 6 months conducted from February 12, 2018, to October 28, 2021. A total of 269 adults aged 18 to 80 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) ranging from 27 to 50 and a hemoglobin A1c level ranging from 5.7% to 8.0% were recruited. Individuals were excluded if receiving medications other than metformin or with evidence of kidney disease, assessed as an estimated glomerular filtration rate of less than 60 mL/min/1.73 m2 using the Chronic Kidney Disease Epidemiology Collaboration equation, to avoid recruiting patients with advanced type 2 diabetes. Interventions:Participants were randomized to either a low-fat diet (<25% of energy intake; standardized group) or a personalized diet that estimates PPGR to foods using a machine learning algorithm (personalized group). Participants in both groups received a total of 14 behavioral counseling sessions and self-monitored dietary intake. In addition, the participants in the personalized group received color-coded meal scores on estimated PPGR delivered via a mobile app. Main Outcomes and Measures:The primary outcome was the percentage of weight loss from baseline to 6 months. Secondary outcomes included changes in body composition (fat mass, fat-free mass, and percentage of body weight), resting energy expenditure, and adaptive thermogenesis. Data were collected at baseline and 3 and 6 months. Analysis was based on intention to treat using linear mixed modeling. Results:Of a total of 204 adults randomized, 199 (102 in the personalized group vs 97 in the standardized group) contributed data (mean [SD] age, 58 [11] years; 133 women [66.8%]; mean [SD] body mass index, 33.9 [4.8]). Weight change at 6 months was -4.31% (95% CI, -5.37% to -3.24%) for the standardized group and -3.26% (95% CI, -4.25% to -2.26%) for the personalized group, which was not significantly different (difference between groups, 1.05% [95% CI, -0.40% to 2.50%]; P = .16). There were no between-group differences in body composition and adaptive thermogenesis; however, the change in resting energy expenditure was significantly greater in the standardized group from 0 to 6 months (difference between groups, 92.3 [95% CI, 0.9-183.8] kcal/d; P = .05). Conclusions and Relevance:A personalized diet targeting a reduction in PPGR did not result in greater weight loss compared with a low-fat diet at 6 months. Future studies should assess methods of increasing dietary self-monitoring adherence and intervention exposure. Trial Registration:ClinicalTrials.gov Identifier: NCT03336411.