印度老龄化纵向研究痴呆症统一诊断评估的设计与方法:第 2 波。

Pranali Y Khobragade, Sarah Petrosyan, Sharmistha Dey, A B Dey, Jinkook Lee
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摘要

痴呆症的发病率不断上升,因此需要有关认知能力下降和痴呆症发病情况的高质量数据。印度纵向老龄化研究统一诊断评估(LASI-DAD)第二波旨在对印度的认知能力和痴呆症进行纵向评估。第一波的所有参与者都被招募参加了后续访谈,复查样本来自印度纵向老龄化研究,这是一个具有全国代表性的 45 岁及以上印度人队列。受访者接受了一系列认知测试、老年评估和静脉采血。他们的健康和认知状况还通过与近亲或朋友的访谈进行了评估。根据临床痴呆症分级®进行临床共识诊断,并收集痴呆症风险因素的综合数据,包括神经退行性生物标志物、感官功能和环境暴露。2022 年至 2024 年期间,共从印度 22 个邦和中央直辖区招募了 4635 名参与者,占印度总人口的 97.9%。响应率为 84.0%,71.5% 的参与者提供了静脉血液标本。LASI-DAD 为纵向研究印度具有全国代表性的老年人认知、痴呆及其风险因素提供了丰富的新数据。纵向认知数据与纵向评估的生物标志物数据以及关于感官功能和环境暴露的新数据一起,为确定风险因素与生物学定义的认知老化表型之间的关联提供了一个独特的机会。
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Design and methodology of the harmonized diagnostic assessment of dementia for the longitudinal aging study in India: Wave 2.

The rising burden of dementia calls for high-quality data on cognitive decline and dementia onset. The second wave of the Harmonized Diagnostic Assessment for the Longitudinal Aging Study in India (LASI-DAD) was designed to provide longitudinal assessments of cognition and dementia in India. All Wave 1 participants were recruited for a follow-up interview, and a refresher sample was drawn from the Longitudinal Aging Study in India, a nationally representative cohort of Indians aged 45 and older. Respondents underwent a battery of cognitive tests, geriatric assessments, and venous blood collection. Their health and cognitive status were also assessed through an interview with a close family member or friend. Clinical consensus diagnosis was made based on the Clinical Dementia Rating®, and comprehensive data on risk factors of dementia were collected, including neurodegenerative biomarkers, sensory function, and environmental exposures. A total of 4635 participants were recruited between 2022 and 2024 from 22 states and union territories of India, accounting for 97.9% of the population in India. The response rate was 84.0%, and 71.5% of the participants provided venous blood specimen. LASI-DAD provides rich new data to study cognition, dementia, and their risk factors longitudinally in a nationally representative sample of older adults in India. Longitudinal cognitive data, together with longitudinally assessed biomarker data and novel data on sensory function and environmental exposures, provide a unique opportunity to establish associations between risk factors and biologically defined cognitive aging phenotypes.

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