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

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大幅增加 人口结构的转变导致人口迅速老龄化。了解影响痴呆症的因素 在印度等低收入中等收入国家中的流行率，并确定成本效益高的干预措施，可以遏制 因此，痴呆症和认知能力下降是一个重要的公共卫生和政策优先事项。 多项研究的证据表明，糖尿病会增加患认知障碍的风险， 痴呆症，但很少有研究使用具有人口代表性的数据，这些数据来自经历快速增长的LMIC 糖尿病发病率。此外，寻求改变饮食和通过有针对性地降低糖尿病风险的干预措施 个人直接取得了好坏参半的结果，大规模实施成本高昂。相比之下，政策层面 解决方案，如含糖饮料税或食品供应管制(例如，限制添加糖) 有可能大规模影响饮食模式，特别是在低收入环境中，资源 少之又少。迫切需要确定大规模的政策解决方案，以减少低收入国家的糖尿病和痴呆症。 该项目将使用具有人口代表性的印度痴呆症数据来实现三个目标。首先，我们将 在低收入和高收入的环境中，研究痴呆症和糖尿病之间的联系，糖尿病是一个已知的危险因素 糖尿病的流行。我们还将通过饮食实践和性别来研究这种关系中的异质性。 其次，我们将评估一项可扩展的公共卫生干预措施，该干预措施可能会降低HbA1c水平和糖尿病发病率： 通过印度政府的公共配送系统运送煮熟的大米，该系统提供了大约 占全国粮食消费总量的三分之一。为了实现这一目标，我们将利用以下详细数据 大米消耗量大的喀拉拉邦稻谷的准随机分布，以及 来自三个数据来源的HbA1c和血糖，包括协调诊断评估 印度纵向老龄化研究中的痴呆症(LASI-DAD)。最后，我们将利用准随机 送半熟大米研究糖尿病对痴呆症和认知功能下降的因果影响 工具变量法。

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.