The long-term effects of Kerala Diabetes Prevention Program on diabetes incidence and cardiometabolic risk: a study protocol.

INTRODUCTION: India currently has more than 74.2 million people with Type 2 Diabetes Mellitus (T2DM). This is predicted to increase to 124.9 million by 2045. In combination with controlling blood glucose levels among those with T2DM, preventing the onset of diabetes among those at high risk of developing it is essential. Although many diabetes prevention interventions have been implemented in resource-limited settings in recent years, there is limited evidence about their long-term effectiveness, cost-effectiveness, and sustainability. Moreover, evidence on the impact of a diabetes prevention program on cardiovascular risk over time is limited. OBJECTIVES: The overall aim of this study is to evaluate the long-term cardiometabolic effects of the Kerala Diabetes Prevention Program (K-DPP). Specific aims are 1) to measure the long-term effectiveness of K-DPP on diabetes incidence and cardiometabolic risk after nine years from participant recruitment; 2) to assess retinal microvasculature, microalbuminuria, and ECG abnormalities and their association with cardiometabolic risk factors over nine years of the intervention; 3) to evaluate the long-term cost-effectiveness and return on investment of the K-DPP; and 4) to assess the sustainability of community engagement, peer-support, and other related community activities after nine years. METHODS: The nine-year follow-up study aims to reach all 1007 study participants (500 intervention and 507 control) from 60 randomized polling areas recruited to the original trial. Data are being collected in two phases. In phase 1 (Survey), we are admintsering a structured questionnaire, undertake physical measurements, and collect blood and urine samples for biochemical analysis. In phase II, we are inviting participants to undergo retinal imaging, body composition measurements, and ECG. All data collection is being conducted by trained Nurses. The primary outcome is the incidence of T2DM. Secondary outcomes include behavioral, psychosocial, clinical, biochemical, and retinal vasculature measures. Data analysis strategies include a comparison of outcome indicators with baseline, and follow-up measurements conducted at 12 and 24 months. Analysis of the long-term cost-effectiveness of the intervention is planned. DISCUSSION: Findings from this follow-up study will contribute to improved policy and practice regarding the long-term effects of lifestyle interventions for diabetes prevention in India and other resource-limited settings. TRIAL REGISTRATION: Australia and New Zealand Clinical Trials Registry-(updated from the original trial)ACTRN12611000262909; India: CTRI/2021/10/037191.

Digital Health Solutions for Community-Based Control of Diabetes During COVID-19 Pandemic: A Scoping Review of Implementation Outcomes.

BACKGROUND: The COVID-19 pandemic has added to the pre-existing challenges of diabetes management in many countries. It has accelerated the wider use of digital health solutions which have tremendous potential to improve health outcomes for people with diabetes. However, little is known about the attributes and the implementation of these solutions. OBJECTIVE: To identify and describe digital health solutions for community-based diabetes management and to highlight their key implementation outcomes. METHODS: We searched Ovid Medline, CINAHL, Embase, PsycINFO, and Web of Science for relevant articles. A purposive search was also used to identify grey literature. Articles that described digital health solutions that aimed to improve community-based diabetes management were included in this review. We applied a thematic synthesis of evidence to describe the characteristics of digital health solutions, and to summarize their key implementation outcomes. RESULTS: We included 15 articles that reported digital health solutions that primarily focused on community-based diabetes management. Nine of the 15 innovations involved were mobile applications and/or web-based platforms, and five were based on social media platforms. The majority of the digital health solutions were used for diabetes education and support. High engagement, utilization, and satisfaction rates with digital health solutions were observed. The use of digital health solutions was also associated with improvement in self-management, taking medication, and reduction in glycated hemoglobin (HbA1c) levels. CONCLUSION: COVID-19 triggered digital health solutions have tremendous potential to improve health outcomes for people with diabetes. Further studies are needed to evaluate the sustainability and scale-up of these solutions.