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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Longitudinal Aging Study in India (LASI)

Basic Information
Dataset Full Name	Longitudinal Aging Study in India
Dataset Acronym	LASI
Summary	The LASI is a longitudinal study of a nationally representative sample of adults 45 years and older living in India. Collection for the first wave of data started in 2016 and has not been completed yet (2017). The study is based on a pilot project conducted in 2010. The primary purpose of the study is to collect data on aging health, social support and economic security that will inform future policies. It takes into account features unique to India including institutional and cultural characteristics.
Key Terms	Aging, Longitudinal, Health, Disability Social and family support, Social networks Health risk behaviors, Chronic disease, Health trajectories, Life expectancy, Disease burden, Food security Biomarkers, Physical function , Anthropometric measurements Retirement, Income, Economic security, Expenditures Elderly welfare programs
Study Design	Longitudinal
Data Type(s)	Clinical Survey
Sponsoring Agency/Entity	National Institutes of Health (NIH)
Health Conditions/Disability Measures
Health Condition(s)	Arthritis, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Diabetes, Heart attack, Pulmonary disorders, Stroke
Disability Measures	Ambulatory disability, Cognitive disability, Functional limitations (ADLs and/or IADLs),, Hearing disability, Mental health disability, Visual disability, Work limitation 10-word list for immediate and delayed memory recall, Balance, CES-D, Grip strength, Lung function, MMSE, Self-reported Health, Timed walk, Vision test
Measures/Outcomes of Interest
Topics	Health and disability, Functional and cognitive limitations, Chronic risk factors Health care utilization, Financing and insurance Regional variations in health access and utilization Social support, Social participation, Social welfare Retirement, Income, Economic well-being, Assets and consumption
Sample
Sample Population	Non-institutionalized Indian adults, ages 45 years and older
Sample Size/Notes	Pilot study (2010): 1,683 Full implementation (2016-2017) plans to include 50,000 individuals
Unit of Observation	Individual and household
Continent(s)	North America
Countries	India
Geographic Coverage	Pilot study: Four states in India: Northern India: Punjab and Rajasthan Southern India: Kerala and Karnataka Full implementation will sample across India.
Geographic Specificity	State (in pilot study)
Special Population(s)	Aging/Older people
Data Collection
Data Collection Mode	Computer assisted personal interviews (CAPI) Self-completed questionnaires Biomarkers collected at home visits
Years Collected	Pilot study: 2010 2016-present (ongoing)
Data Collection Frequency	Full implementation scheduled to be every 2 years
Strengths and Limitations
Strengths	Full implementation will be representative sample of the Indian population. Once multiple waves are available, longitudinal analyses on health risk factors will be possible. Objective markers (biomarkers) of health are included. LASI has been harmonized with the HRS study (as well as SAGE, ELSA, KLoSA) allowing cross-national comparisons.
Limitations	Only 2010 pilot study data is available (as of February 2018) Pilot study sample is relatively small and not representative of all regions Information on earlier life medical history is collected retrospectively.
Data Details
Primary Website	https://www.hsph.harvard.edu/pgda/major-projects/lasi-2/ https://lasi.hsph.harvard.edu/lasi-survey
Data Access	LASI pilot data access: https://g2aging.org/?section=download&studyid=36&r=^q^section=study^a^studyid=36
Data Access Requirements	Data use agreement, No cost
Summary Tables/Reports	Harmonized LASI Pilot Data Documentation: https://www.rand.org/content/dam/rand/pubs/working_papers/WR1000/WR1018/RAND_WR1018.pdf (Note may not include all variables available in stand alone dataset)
Data Components	Pilot household micro data Pilot individual micro data Pilot all data Pilot harmonized data
Similar/Related Dataset(s)	Other longitudinal aging studies: Canadian Longitudinal Study on Aging (CLSA) English Longitudinal Study of Ageing (ELSA) Health and Retirement Study (HRS) - U.S. Japanese Study of Aging and Retirement (JSTAR) Korean Longitudinal Study of Ageing (KLoSA) Mexican Health and Aging Study (MHAS) Survey of Health, Ageing and Retirement in Europe (SHARE) World Health Organization Study on global Ageing and adult health (SAGE)
Selected Papers
Other Papers	LASI related publications list (Gateway to Global Aging Data): https://g2aging.org/?section=papers (select Survey=LASI) LASI related publications list (RAND Corporation): https://www.rand.org/search.html?query=LASI&sortby=relevance
Technical	Data and Documentation: https://g2aging.org/?section=download&studyid=36&r=^q^section=study^a^studyid=36 Pilot user guide 2010: https://g2aging.org/startfile.php?f=LASI-Pilot_user_guide.pdf&urid=3697 Pilot codebook: https://g2aging.org/startfile.php?f=LASI-Pilot_fat_file_codebook.pdf&urid=3697 Interactive codebook: https://g2aging.org/?section=survey&surveyid=59&display=codebook Harmonized LASI Pilot Data Documentation: Version A https://www.rand.org/pubs/working_papers/WR1018.html Biomarker data documentation: https://www.rand.org/content/dam/rand/pubs/working_papers/WR1000/WR1043/RAND_WR1043.pdf

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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