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 痴呆症的全球负担正在大大增长，因为低收入国家（LMIC）经历了 人口转变导致人口迅速老化。了解影响痴呆症的因素 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，痴呆症和认知能力下降是重要的公共卫生和政策优先事项。 几项研究的证据表明，糖尿病会增加患认知障碍和 痴呆 糖尿病率。此外，试图改变饮食并通过靶向降低糖尿病风险的干预措施 相比之下，政策级别 解决方案，例如糖粉的卧室税或粮食供应调节（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。至关重要的是确定减少LMIC中糖尿病和痴呆症的大规模政策解决方案。 该项目将使用印度痴呆症的人群代表数据来实现三个目标。首先，我们会的 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 糖尿病患病率。我们还将通过饮食实践和性别研究这种关系中的异质性。 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： 通过印度政府的公共分销制度提供小米的大米，该系统大致提供 该国总谷物消耗的三分之一。为了实现这一目标，我们将利用有关的详细数据 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和血糖，包括对 印度（Lasi-dad）纵向老化研究的痴呆症。最后，我们将利用准随机 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。