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

基本信息

批准号：
10838114
负责人：
Soohyun Nam
金额：
$ 54.27万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10838114
关键词：
Address Adult Affect Behavior Behavior Therapy Blinded Blood Glucose Blood flow Cardiac Cardiometabolic Disease Cardiovascular Diseases Caring Censuses Chronic Kidney Failure Climate Clinical Complications of Diabetes Mellitus Connecticut Continuous Glucose Monitor Country Data Data Aggregation Data Collection Decision Making Dehydration Development Diabetes Mellitus Diet Dietary intake Eating Eating Behavior Ecological momentary assessment Environment Environmental Risk Factor Ethnic Population Frequencies Future Gluconeogenesis Glucose Glycosylated Hemoglobin Glycosylated hemoglobin A Goals Green space Health Heat Waves High temperature of physical object Home heating Hospitalization Hour Hyperglycemia Impairment Incidence Individual Infarction Insulin Resistance Intervention Life Style Life Style Modification Link Liver Longevity Machine Learning Measurement Measures Mediating Modeling Myocardial Ischemia Non-Insulin-Dependent Diabetes Mellitus North America Nutrient Osmolar Concentration Outcome Parents Participant Patient Education Persons Physical activity Physiological Plasma Policies Population Public Health Questionnaires Research Resolution Risk Role Seasons Skin Sleep Social support Stroke Surface Sweating Temperature Time Vasodilation Vulnerable Populations actigraphy behavioral response built environment cardiometabolism climate change climate impact climate zone climate-related health cold temperature comorbidity demographics diabetes control dietary epidemiologic data epidemiology study food insecurity glycemic control health equity health equity promotion hepatic gluconeogenesis improved individual patient insight lifestyle data lifestyle factors macrovascular disease meteorological data mortality mortality risk multi-ethnic novel randomized trial regional difference research study response risk prediction sensor social social cohesion social health determinants spatiotemporal time interval vulnerable community weather stations

项目摘要

Project Summary Extreme ambient temperature (Ta), which is becoming more common due to climate change, has been associated with the increased incidence of cardiometabolic disease and mortality. Dehydration induced by high Ta stimulates gluconeogenesis in the liver and promotes insulin resistance. Increased blood flow to the skin during heatwaves increases cardiac demand, resulting in cardiac ischemia, infarction, and stroke in individuals with pre-existing cardiovascular disease (CVD). Thus, individuals with diabetes are particularly vulnerable to heat waves due to impaired physiological responses to heat and CVD comorbidities. Glucose variability (GV), measured by continuous glucose monitoring (CGM), is fluctuations in blood glucose levels over a given interval of time (intra-day or inter-day) and is an important emerging parameter of dynamic glycemic control. Glycated hemoglobin (HbA1c), a marker of the average blood glucose levels over the previous 2 to 3 months, is the primary metric used to predict diabetic complications. However, in-depth analyses from large scale, randomized trials, and epidemiological studies have indicated that HbA1c alone may not sufficiently predict the risk of diabetes complications. To date, climate change and health (CCH) research has been done at the population- level with aggregated data and HbA1c levels. Although the previous studies provided valuable insight into climate change and diabetes care, the mean HbA1c level at the population level with aggregated data in different climate zones makes it difficult to understand the real impact of Ta on individual patients. There is an urgent need to address gaps in CCH research studying lifestyle behavioral responses to Ta under climate change, social-built environment, and diabetes outcomes with high spatiotemporal granularity. We will collect time-stamped lifestyle data using ecological momentary assessment (EMA) and actigraphy and perform 24-hour dietary recalls. CGM, a real-time, unobtrusive glucose measure will be blinded from participants during the 14-day observation period. We will collect hourly and daily Ta from weather stations, daily Ta estimates from the Daily Surface Weather Data on a 1-km Grid for North America, and develop a high resolution (1 km2) spatiotemporally resolved hourly Ta model in Connecticut using satellite data with a machine learning approach. Participants will also be asked to wear a personal Ta sensor. Leveraging data in GV and multi-level personal (demographic, comorbidities), lifestyle, and social-built environmental factors that our parent study provides, and linking them to Ta data, we propose the following specific aims: (1) identify the risk groups who are vulnerable to high or low Ta by examining demographics, comorbidities, lifestyle (physical activity, sleep, eating behaviors/diet), social-built environment and GV among multi-ethnic adults with T2D for 14 days each in 2 seasons, (2) examine the influence of Ta on time-varying lifestyle factors and GV, within-person across 14 days using the hourly Ta estimates at 1 km2 special resolution to inform future personalized behavioral interventions, and (3) evaluate the feasibility and utility of the wearable Ta sensor and compare the data with the model developed hourly Ta and observed hourly Ta data.

项目概要由于气候变化而变得越来越普遍的极端环境温度（Ta）已被与心脏代谢疾病的发病率和死亡率增加有关。高浓度引起的脱水 Ta 刺激肝脏中的糖异生并促进胰岛素抵抗。增加流向皮肤的血液热浪期间增加心脏需求，导致个体心脏缺血、梗塞和中风患有先前存在的心血管疾病（CVD）。因此，糖尿病患者特别容易受到由于对热的生理反应受损和心血管疾病合并症而导致热浪。血糖变异性（GV），通过连续血糖监测 (CGM) 测量，是给定时间间隔内血糖水平的波动时间（日内或日间）的变化，是动态血糖控制的重要新兴参数。糖化血红蛋白 (HbA1c) 是过去 2 至 3 个月平均血糖水平的指标，是用于预测糖尿病并发症的主要指标。然而，大规模、随机的深入分析试验和流行病学研究表明，仅 HbA1c 可能不足以预测罹患糖尿病的风险糖尿病并发症。迄今为止，气候变化与健康（CCH）研究已在人口中进行汇总数据和 HbA1c 水平。尽管之前的研究提供了有关气候的宝贵见解变化和糖尿病护理，人群水平的平均 HbA1c 水平以及不同气候下的汇总数据区域使得很难了解 Ta 对个体患者的真正影响。迫切需要解决 CCH 研究中的空白，研究气候变化、社会构建下对 Ta 的生活方式行为反应环境和具有高时空粒度的糖尿病结果。我们将收集带有时间戳的生活方式使用生态瞬时评估 (EMA) 和体动记录仪获取数据，并进行 24 小时饮食回忆。连续GM，在 14 天的观察期内，实时、不引人注目的血糖测量将对参与者不知情。我们将从气象站收集每小时和每日的 Ta，根据每日地面天气数据估算每日的 Ta 在北美 1 公里网格上，开发高分辨率（1 平方公里）时空解析的每小时 Ta 康涅狄格州的模型使用卫星数据和机器学习方法。参与者还将被要求佩戴个人 Ta 传感器。利用 GV 和多层次个人（人口统计、合并症）数据，我们的父母研究提供了生活方式和社会环境因素，并将它们与 Ta 数据联系起来，我们提出以下具体目标：（1）通过检查确定易受高或低Ta影响的风险人群人口统计、合并症、生活方式（体力活动、睡眠、饮食行为/饮食）、社会构建环境和 GV 在 2 个季节各 14 天的多族裔成人 T2D 中，（2）检查 Ta 对随时间变化的生活方式因素和 GV，在 14 天内使用每小时 Ta 估算的人内特殊情况决议为未来的个性化行为干预提供信息，以及（3）评估该方案的可行性和效用穿戴式 Ta 传感器，并将数据与开发的模型每小时 Ta 和观测到的每小时 Ta 数据进行比较。