Personal and social-built environmental factors of glucose variability among multi ethnic groups of adults with type 2 diabetes

多种族成人 2 型糖尿病患者血糖变异性的个人和社会环境因素

• 批准号: 10418218
• 负责人: Soohyun Nam
• 金额: $ 43.71万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10418218
• 关键词: Address; Adult; Affect; Affective; Alcohol consumption; Behavior; Blinded; Blood Glucose; Body mass index; Cardiovascular Diseases; Characteristics; Clinical; Complications of Diabetes Mellitus; Data; Data Collection; Development; Diabetes Mellitus; Diet; Eating; Ecological momentary assessment; Elderly; Environment; Environmental Risk Factor; Ethnic Origin; Ethnic group; Exercise; Fasting; Frequencies; Future; Glucose; Glycosylated Hemoglobin; Goals; Health Personnel; Hemoglobin concentration result; High Prevalence; Hour; Hyperglycemia; Income; Individual; Insulin-Dependent Diabetes Mellitus; Intake; Intervention; Knowledge; Life Style; Link; Measures; Mediating; Neighborhoods; Non-Insulin-Dependent Diabetes Mellitus; Nutrient; Outcome; Participant; Patients; Persons; Pharmaceutical Preparations; Physical activity; Pilot Projects; Play; Protocols documentation; Provider; Public Health; Publishing; Quality of life; Questionnaires; Race; Research; Risk; Risk Factors; Role; Sleep; Smoking; Social support; Stress; Teenagers; Time; Well in self; actigraphy; adherence rate; base; blood glucose regulation; built environment; clinical application; clinical decision-making; clinical practice; comorbidity; demographics; diabetes distress; diabetes risk; diabetes self-management; dietary; effective therapy; epidemiology study; ethnic minority; experience; food insecurity; glucose metabolism; glucose monitor; glycemic control; high risk; hypothalamic-pituitary-adrenal axis; improved; insight; lifestyle data; lifestyle factors; macrovascular disease; middle age; mortality; multi-ethnic; personalized intervention; prospective; racial and ethnic; racial discrimination; randomized trial; response; sedentary; sex; sleep quality; social; social cohesion; time interval

PROJECT SUMMARY The pivotal goals of diabetes treatment are to minimize diabetes complications and improve quality of life for individuals with diabetes. In-depth analyses from large scale, randomized trials and epidemiological studies have indicated that glycated hemoglobin (HbA1c), the primary metric for assessing glycemic control, alone may not sufficiently predict the risk of diabetes complications. Near-normal HbA1c level did not consistently improve diabetes complications. People with similar HbA1c values can have markedly different glucose profiles with varying frequencies and amplitudes of hypo- and hyper-glycemia. Glucose variability (GV) refers to fluctuations in blood glucose levels throughout the day (intra-day GV) or over days (inter-day GV) and is an emerging predictor of diabetes complications. GV can be measured in real-time through continuous glucose monitoring (CGM). Considerable research in CGM to understand GV has led to the growing use of CGM in clinical practice among individuals with type 1 diabetes. However, few studies address factors that affect GV in type 2 diabetes (T2D), leaving large gaps in knowledge about how to mitigate GV and improve diabetes outcomes in T2D. Roles of individuals’ lifestyle behaviors, emotional well-being and social-built environments in glucose control have been well documented. Also, real-time data on lifestyle such as day-to-day sleep, physical activity and diet are being generated. However, how these factors are associated with GV has yet to be examined. This study will be one of the first to prospectively examine the temporal relationships among sleep, physical activity, diet, emotional well-being, and GV, incorporating between-person associations and within-person variability among adults of diverse race/ethnicity with T2D. We will use a real-time, data capture strategy, ecological momentary assessment to measure lifestyle factors and emotional well-being. Three 24-hr dietary recalls will be conducted to collect nutrient-level data. We will also use actigraphy as objective measures of sleep and physical activity paired with CGM, a real-time, unobtrusive glucose measure that will be blinded from participants during a study period of 14 days. The specific aims of the study are to: (1) identify risk factors associated with high GV among diverse adults with T2D by examining between-person associations among demographics, clinical factors, lifestyle (sleep, physical activity, diet) factors, the variability of each lifestyle factor, emotional well-being, social-built environmental factors and inter-day GV, (2) identify ‘within- person predictors’ of GV to inform the development of personalized diabetes interventions by examining within- person associations among sleep, physical activity, diet, emotional well-being and intra-day GV, and (3) examine which lifestyle factors either mediate or moderate the relationship between emotional well-being and GV among diverse adults with T2D. The findings from the proposed study will guide clinical decision-making for healthcare providers to facilitate effective treatment using CGM and inform the development of personalized interventions to mitigate GV and improve diabetes outcomes.

项目概要 糖尿病治疗的关键目标是尽量减少糖尿病并发症并提高患者的生活质量 来自大规模随机试验和流行病学研究的深入分析。 已经表明，单独评估血糖控制的主要指标——糖化血红蛋白 (HbA1c) 可能无法充分预测糖尿病并发症的风险。接近正常的 HbA1c 水平并不始终如一。 改善糖尿病并发症。具有相似 HbA1c 值的人的血糖曲线可能明显不同。 低血糖和高血糖的频率和幅度不同，是指血糖变异性（GV）。 血糖水平全天（日内 GV）或数天（日间 GV）的波动，是一个 糖尿病并发症的新兴预测指标可以通过连续血糖实时测量。 为了解 GV 而对 CGM 进行的大量研究导致了 CGM 在以下领域的广泛使用： 1 型糖尿病患者的临床实践 然而，很少有研究涉及影响 GV 的因素。 2 型糖尿病 (T2D)，在如何减轻 GV 和改善糖尿病方面的知识存在巨大差距 个人生活方式、情绪健康和社会构建环境的作用。 此外，有关生活方式（例如日常睡眠）的实时数据也得到了充分记录。 体力活动和饮食正在产生然而，这些因素与 GV 之间的关系尚不清楚。 这项研究将是第一个前瞻性研究之间的时间关系的研究。 睡眠、体力活动、饮食、情绪健康和 GV，纳入人与人之间的关联和 我们将使用实时数据采集来了解不同种族/民族的 T2D 成年人之间的个体差异。 策略、生态瞬时评估，衡量生活方式因素和情绪健康 3 个 24 小时。 我们还将进行饮食召回以收集营养水平数据。 睡眠和身体活动的测量与 CGM 相结合，CGM 是一种实时、不引人注目的血糖测量，将 在 14 天的研究期间对参与者进行盲法研究的具体目的是：(1) 识别风险。 通过检查不同的人与人之间的关联，研究与成人 T2D 患者高 GV 相关的因素 在人口统计、临床因素、生活方式（睡眠、体力活动、饮食）因素之间，每个因素的变异性 生活方式因素、情绪健康、社会环境因素和日间 GV，(2) 识别“内部- GV 的个体预测因子通过检查内部情况为个性化糖尿病干预措施的发展提供信息 睡眠、体力活动、饮食、情绪健康和日内 GV 之间的人际关联，以及 (3) 检查哪些生活方式因素可以介导或调节情绪健康与健康之间的关系 不同 T2D 成人的 GV。拟议研究的结果将指导临床决策。 帮助医疗保健提供者利用 CGM 促进有效治疗，并为个性化治疗的发展提供信息 减轻 GV 和改善糖尿病结局的干预措施。