This mentored patient-oriented research career development award (K23) will support Dr. David Lee?s training and research to use geographically targeted and community-based methods to identify factors associated with micro-level disparities in diabetic outcomes and enhance monitoring of glycemic control among Black men. Though the prevalence of diabetes is increasing nationally, current diabetes surveillance methods are unable to identify hot spots of poor diabetic outcomes at a community level. However, studies based on a novel geographic method of diabetes surveillance have found that the increase in diabetes burden has been focused in specific communities, especially among Black neighborhoods. For Black adults, poor diabetes control has been associated with fewer primary care visits, less frequent HbA1c testing, and higher rates of emergency department use and hospitalizations, especially among diabetic Black men. Given this infrequent interaction with a usual source of healthcare, community-based settings may provide the advantages of pre- existing trust and engagement to optimize health outcomes for high-risk populations living in neighborhoods that are hot spots of diabetic complications. Thus, the specific aims of this proposal are 1) to use geospatial and quantitative methods to identify which micro-contextual factors account for local disparities in diabetic outcomes among Black communities, 2) to use geographically-targeted qualitative interviews to identify neighborhood-level factors that explain poor diabetic outcomes in certain Black communities, and 3) to perform community-based HbA1c testing and diabetes self-care surveys among Black men living in neighborhoods with a high prevalence of diabetic complications. This community-based research will leverage existing partnerships within a network of local Black-owned barbershops in New York City. Barbershops have become increasingly effective sites for promoting health and measuring health outcomes among Black men, a population which has high rates of mortality and morbidity from diabetes. The results of this research will inform future R-series applications to expand this approach to other high-risk subgroups in Black neighborhoods and other racial and ethnic communities with extremely poor diabetic outcomes. Dr. Lee?s training goals closely parallel his research aims and will further enhance his understanding of: 1) advanced quantitative analysis, 2) qualitative and mixed methods, 3) social and behavioral science, and 4) diabetes education and management. The proposed research and training will be conducted at the New York University School of Medicine and leverage resources of the other professional schools at NYU, which offer outstanding opportunities for collaboration, learning, and multidisciplinary research. This environment, in addition to his research and training plan will provide Dr. Lee with a strong foundation from which he can accelerate his career towards his goal of becoming a fully independent clinical investigator dedicated to reducing disparities in diabetes burden and improving health outcomes in communities that are overwhelmed by diabetic complications.
The overall burden of diabetes is increasing nationally, but specific neighborhoods, especially in Black communities, have experienced a disproportionately higher prevalence of diabetes and its complications such as kidney failure and lower extremity amputations. The goal of the proposed research is to use a mix of quantitative and qualitative methods to identify the micro-contextual factors that account for local disparities in diabetic outcomes among Black communities with a high versus low prevalence of diabetic complications and to enhance the monitoring of glycemic control in neighborhoods with especially poor diabetic outcomes. This K23 career development award will foster Dr. David Lee?s transition to becoming a fully-independent investigator capable of conducting high-impact research to enhance our understanding of local disparities in diabetic outcomes among communities with overwhelming diabetes burden.
|Lee, David C; Jiang, Qun; Tabaei, Bahman P et al. (2018) Using Indirect Measures to Identify Geographic Hot Spots of Poor Glycemic Control: Cross-sectional Comparisons With an A1C Registry. Diabetes Care 41:1438-1447|
|Lee, David C; Gallagher, Mary Pat; Gopalan, Anjali et al. (2018) Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data. J Endocr Soc 2:460-470|
|Lee, David C; Yi, Stella S; Athens, Jessica K et al. (2018) Using Geospatial Analysis and Emergency Claims Data to Improve Minority Health Surveillance. J Racial Ethn Health Disparities 5:712-720|
|Lee, David C; Swartz, Jordan L; Koziatek, Christian A et al. (2017) Assessing the Reliability of Performing Citywide Chronic Disease Surveillance Using Emergency Department Data from Sentinel Hospitals. Popul Health Manag 20:427-434|
|Lee, David C; Yi, Stella S; Fong, Hiu-Fai et al. (2017) Identifying Local Hot Spots of Pediatric Chronic Diseases Using Emergency Department Surveillance. Acad Pediatr 17:267-274|