Leveraging a natural experiment to estimate the causal impact of blood sugar on dementia and cognition in India

利用自然实验来估计血糖对印度痴呆症和认知的因果影响

• 批准号: 10703989
• 负责人: Jinkook Lee
• 金额: $ 43.93万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10703989
• 关键词: Affect; Age; Aging; Amyloid; Behavior Therapy; Blood Glucose; Carbohydrates; Caring; Cognition; Consumption; Country; Data; Data Collection; Data Sources; Dementia; Demographic Transitions; Deterioration; Diabetes Mellitus; Diabetes prevention; Diagnostic; Diet; Dietary Practices; Digestion; Elderly; Food; Food Supply; Gender; Genetic Predisposition to Disease; Glycemic Index; Glycosylated hemoglobin A; Goals; Government; Grain; Growth; Health; Health Benefit; Heterogeneity; High Prevalence; Hyperglycemia; Impaired cognition; Incidence; India; Individual; Intervention; Knowledge; Life Style; Literature; Low income; Measures; Metabolism; Methods; Natural experiment; Nature; Nutritional; Oxidative Stress; Persons; Policies; Policy Maker; Population; Prevalence; Process; Public Health; Public Policy; Regulation; Research; Research Personnel; Resistance; Resources; Rice; Risk; Risk Factors; Satiation; Starch; System; Taxes; Time; Variant; Work; aged; aging population; cognitive ability; cost; cost effective intervention; data harmonization; dementia risk; demographics; diabetes risk; diabetic; experience; forging; improved; insight; interest; low and middle-income countries; neurotoxicity; novel; primary outcome; public health intervention; response; secondary outcome; sex; success; sugar; sweetened beverage

Project Summary The global burden of dementia is growing substantially as low- and middle-income countries (LMICs) undergo demographic transitions resulting in rapidly aging populations. Understanding the factors that affect dementia prevalence in LMICs such as India and identifying cost-effective interventions that may curb the onset of dementia and cognitive decline is thus an important public health and policy priority. Evidence from several studies indicates that diabetes increases the risk of developing cognitive impairment and dementia, but few studies have used population-representative data from LMICs experiencing rapidly increasing diabetes rates. Furthermore, interventions that seek to change diets and reduce diabetes risk by targeting individuals directly have had mixed success and are costly to implement at scale. In contrast, policy-level solutions such as sugar-sweetened beverage taxes or regulation of food supply (e.g., caps on added sugars) have the potential to influence dietary patterns at scale, especially in low-income settings where resources are scarce. There is a vital need to identify large-scale policy solutions for reducing diabetes and dementia in LMICs. This project will use population-representative data on dementia in India to accomplish three aims. First, we will study the association between dementia and diabetes, a known risk factor, in a low-income setting with a high prevalence of diabetes. We will also study heterogeneity in this relationship by dietary practice and by sex. Second, we will evaluate a scalable public health intervention that may reduce HbA1c levels and diabetes rates: the delivery of parboiled rice through the Indian government’s Public Distribution System, which provides roughly one-third of the total grain consumed in the country. To accomplish this goal, we will leverage detailed data on the quasi-random distribution of parboiled rice in Kerala, a state with high rice consumption, as well as data on HbA1c and blood glucose from three data sources including the Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD). Finally, we will leverage the quasi-random delivery of parboiled rice to study the causal effect of diabetes on dementia and cognitive decline using an instrumental variables approach.

项目摘要 随着中低收入国家（LMIC）的经历，全球痴呆症的负担正在增长 人口统计学的交易导致迅速衰老的流行。 LMIC的患病率（例如印度），并确定可能遏制的具有成本效益的干预措施 因此，痴呆和认知能力下降是一个重要的政策优先事项。 严重性研究的证据增加了发展认知障碍的风险和 痴呆症，但很少有研究使用LMIC的人群代表性数据迅速增加 糖尿病率。 个人取得了不同的成功，相比之下，政策级别的实施成本很高。 诸如糖量饮料税或食品供应调节等解决方案（例如，添加糖的帽子） 有可能按大规模影响饮食模式，尤其是在资源的低收入环境中 稀缺。至关重要的是识别尺度的政策解决方案，以减少LMIC中的糖尿病和痴呆症。 该项目将使用印度痴呆症痴呆症的人口持耐受性数据来实现三个目标。 在低收入环境中研究痴呆症和糖尿病之间的关联，这是一种已知危险因素 糖尿病的患病率。 其次，我们将评估可扩展的公共卫生干预措施，该干预措施可能会降低HBA1C水平和糖尿病率： 印度政府的公共分销系统的交付米饭大致提供了 该国的三分之一是为了实现这一目标。 喀拉拉邦的帕煮大米的准随机分布，喀拉拉邦是一种富含水稻的状态，以及有关的数据 来自三个数据源的HBA1C和血液葡萄糖，包括统一的诊断评估 印度纵向老化研究的痴呆症（Lasi-dad）。 使用少量水稻来研究糖尿病对痴呆和认知能力下降的因果作用 仪器变量方法。