Longitudinal Aging Study in India (LASI): new data resources for addressing aging in India

被引:81
作者
Bloom, David E. [1 ]
Sekher, T. V. [2 ]
Lee, Jinkook [3 ]
机构
[1] Harvard TH Chan Sch Publ Hlth, Boston, MA 02115 USA
[2] Int Inst Populat Sci, Mumbai, India
[3] Univ Southern Calif, Los Angeles, CA USA
来源
NATURE AGING | 2021年 / 1卷 / 12期
基金
美国国家卫生研究院;
关键词
D O I
10.1038/s43587-021-00155-y
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The Longitudinal Aging Study in India (LASI), the largest national health and retirement study in the world, released its wave 1 microdata earlier this year. The principal investigators of LASI introduce the study and explain how it can advance aging research in India and beyond in response to the impending challenges of rapid population aging.
引用
收藏
页码:1070 / 1072
页数:3
相关论文
共 15 条
[1]   Sex Differences in Cognitive Health Among Older Adults in India [J].
Angrisani, Marco ;
Jain, Urvashi ;
Lee, Jinkook .
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY, 2020, 68 :S20-S28
[2]  
[Anonymous], 1994, Health and Retirement Study
[3]  
[Anonymous], 2019, Department of Economic and Social Affairs. World Population Prospects 2019, V141, P1
[4]  
Bloom D., 2021, Addressing Alzheimer's disease and related dementias to realise the promise of the UN's 'Decade of Healthy Ageing', V26
[5]   The Association of Cognitive and Visual Function in a Nationally Representative Study of Older Adults in India [J].
Ehrlicha, Joshua R. ;
Ndukwe, Tochukwu ;
Chien, Sandy ;
Lee, Jinkook .
NEUROEPIDEMIOLOGY, 2021, 55 (02) :126-134
[6]  
Giridhar G, 2014, POPULATION AGEING IN INDIA, pXVII
[7]  
International Institute for Population Sciences (IIPS) NPHCE MoHFW HTHCS of PH (HSPH) and the U of SC (USC), 2020, Longitudinal Ageing Study in India (LASI) Wave 1, 2017-18, India Report
[8]   The cost of Alzheimer's disease in China and re-estimation of costs worldwide [J].
Jia, Jianping ;
Wei, Cuibai ;
Chen, Shuoqi ;
Li, Fangyu ;
Tang, Yi ;
Qin, Wei ;
Zhao, Lina ;
Jin, Hongmei ;
Xu, Hui ;
Wang, Fen ;
Zhou, Aihong ;
Zuo, Xiumei ;
Wu, Liyong ;
Han, Ying ;
Han, Yue ;
Huang, Liyuan ;
Wang, Qi ;
Li, Dan ;
Chu, Changbiao ;
Shi, Lu ;
Gong, Min ;
Du, Yifeng ;
Zhang, Jiewen ;
Zhang, Junjian ;
Zhou, Chunkui ;
Lv, Jihui ;
Lv, Yang ;
Xie, Haiqun ;
Ji, Yong ;
Li, Fang ;
Yu, Enyan ;
Luo, Benyan ;
Wang, Yanjiang ;
Yang, Shanshan ;
Qu, Qiumin ;
Guo, Qihao ;
Liang, Furu ;
Zhang, Jintao ;
Tan, Lan ;
Shen, Lu ;
Zhang, Kunnan ;
Zhang, Jinbiao ;
Peng, Dantao ;
Tang, Muni ;
Lv, Peiyuan ;
Fang, Boyan ;
Chu, Lan ;
Jia, Longfei ;
Gauthier, Serge .
ALZHEIMERS & DEMENTIA, 2018, 14 (04) :483-491
[9]   Learning From Clinical Consensus Diagnosis in India to Facilitate Automatic Classification of Dementia: Machine Learning Study [J].
Jin, Haomiao ;
Chien, Sandy ;
Meijer, Erik ;
Khobragade, Pranali ;
Lee, Jinkook .
JMIR MENTAL HEALTH, 2021, 8 (05)
[10]  
Lee JC., PLoS Med