LASI Pilot /
LASI FINANCIAL SPONSORS /
Technical Advisory Committee
Although adult health and ageing is a subject that is
increasingly being investigated, there are currently no
comprehensive and internationally comparable survey data
in India that cover and connect the full range of topics
necessary to understand the economic, social,
psychological, and health aspects of adults and the
ageing process. Longitudinal Ageing Study in India
(LASI) is designed to fill this gap.
focuses on the health, economic, and social well-being
of India's elderly population. LASI is conceptually
comparable to the Health and Retirement Study (HRS) in
the United States and is appropriately harmonized with
other health and retirement studies, including its
sister surveys in Asia – such as the Chinese Health and
Retirement Longitudinal Study (CHARLS) and the Korean
Longitudinal Study of Aging (KLOSA) – thereby allowing
for cross-country comparison. LASI also takes account of
features unique to India, including its institutional
and cultural characteristics.
will be a national landmark in scientific research that
will allow a better understanding of India’s adult
health problems and population ageing processes and will
inform the design of appropriate evidence-based policies
for adults and older people. We will build on the
success of the LASI pilot survey and implement the first
two waves of a large-scale, national and state
representative panel survey on the health, economic
status, and social behaviors of older people in India,
with sufficient statistical power to test hypotheses in
subpopulations of interest. LASI data will advance
scientific knowledge and inform policymakers in India
and elsewhere. Our public, internationally harmonized
data will allow for cross-national comparative research
studies on ageing.
The full-scale national LASI survey (Main wave 1) is launched in 2016.
The survey instrument is carefully designed to collect information compatible with other worldwide Longitudinal Ageing Surveys, as well as incorporating to culture and societies of India.
The LASI team in IIPS in collaboration with Harvard School of Public Health and University of Southern California successfully conducted the 2010 LASI pilot survey in the four states of Karnataka, Kerala, Punjab, and Rajasthan to test survey tools, protocols and to learn lessons for the main wave.
The analysis of LASI pilot data revealed insightful evidence on reported and measured health status, social network characteristics, income and consumption, retirement, and pensions of ageing population.
Scientific Goals of LASI
The main goal of LASI is to collect credible scientific data on burden of disease, mental health, functional health, health care social and economic wellbeing of elderly population.
LASI data is being collected based on internationally comparable research design, tools and adopts state of the art scientific methods to provide the foundation for credible and acceptable data – for national and state level policy making and long-term scientific research.
The main objective of LASI is to provide comprehensive longitudinal evidence base on health, social and economic wellbeing of elderly population in India.
LASI will provide data on demographics, household economic status, health and biomarkers, health insurance and health care utilization, family and social network, social welfare schemes, work and employment, retirement and pension, life satisfaction and expectations.
LASI is designed to cover scientific data on five major subject and policy domains of adult and older population of India namely:
1. Health: Disease burden & risk factors (reported and measured)
2. Health care and health care financing
3. Social: Family and social network
4. Economic: Income, wealth, expenditure, employment, retirement and pension
5. Welfare programs for Elderly
Geographic Coverage and Sampling Design
LASI main wave’s covers 30 states and 6 union territories of India covering a panel sample size of 60,250 elderly persons aged 45 years and above.
The long-term goal of LASI is to continue this survey for the next 25 years with the first wave planned in the year 2016-17 and second wave in 2018-19.
LASI aims to obtain all the indicators for each of the 30 states and 6 union territories.
In addition, LASI aims at obtaining indicators for each of the four metropolitan cities of Delhi, Kolkata, Mumbai and Chennai.
Sample design: The target sample for LASI is non-institutionalized Indian residents aged 45 and older and their spouses (irrespective of age).
LASI adopts multistage clustering sampling design; three-stage sample design in rural areas and a four-stage sample design in urban areas.
In each state, at first stage, involved selection of Primary Sampling Units (PSUs), i.e., sub-districts (Tehsils/Talukas); the second stage involved the selection of Secondary Sampling Units (SSUs) i.e. villages from rural areas and ward from urban areas of the selected PSUs.
In rural areas, at the third stage, households are selected from selected villages. However, sampling in urban areas involved one more stage. From each selected urban ward, one Census Enumeration Block (CEB) was randomly selected in the third stage.
At the fourth stage, households from this CEB will be selected.
The main reason for adopting a four-stage sample design in urban areas is that urban wards are quite large, making it difficult to list all the households in a ward and select households directly from the resulting list.
The LASI instrument has three Schedules:
1. Household Schedules (administered one per LASI selected eligible household):
• The household schedules start with the cover screen/Roster, containing questions about the demographic composition of the household and identifying key informants for the following household modules
• Housing and Environment section, consist of questions about the household’s physical dwelling, residential history, and physical and social characteristics of neighbourhood
• Consumption section is designed to collect data on both market-purchased and home-produced consumption at the household level
• Assets and Debts section includes detailed questions about financial and non-financial assets and debts.
• Income section which attempts to capture the complete profile of income of all household members from all sources, as well as remittances from non-household members
• Health Insurance section attempts to gather information on all the government and private health insurance schemes which provide health care facilities at national and state level, policy coverage and benefits offered by policy
2. Individual Schedules (administered to each respondent of aged 45+ and his/her spouses)
The individual schedule covers the following modules:
• Demographics section: includes birth date, sex, religion, caste, language, marital status, literacy, education, and questions designed to approximate age for illiterate respondents
• Family and Social Networks section: covers detailed questions about all immediate family members, including parents, children, and siblings, both alive and deceased, social activities, and psychosocial measures of life satisfaction, emotional proximity, social status, etc.
• Social Welfare Schemes section: This section will gather information on the awareness and utilization of various social security programmes in India.
• Health section: consists of questions about overall health and specific diseases, functional health, Family Medical History, mental health including Cognition and Depression, and health behaviour & Food Security
• Healthcare Access and Utilization section: designed to capture access to and use of different types of health care providers;
• Work, Retirement and Pension section: includes questions about current job (including self-employment and (subsistence) agriculture) and employment history;
• Experimental modules section: addresses topics beyond the scope of the main survey, to test new concepts, questions and surveying techniques. Each individual respondent will be randomly assigned to one of the four modules described below, so that each module is administered to roughly 25% of the total survey sample. It includes the following modules: a) Time utilization by older population – by type of activities, b) Expectations of work, survival, work–limiting health problems and inflation c) Extent of social connectedness of elderly population with family and friends d) Determining health status of elderly through the use of vignettes
• Biomarkers: The survey also includes the biomarkers module, which administers range of physical and functional measures of health and collects dried blood spots.
LASI covers wide range of direct physical examinations: physical tests and markers. The biomarker collection will be done in the field by following the developed standardized protocols and procedures. In LASI, comprehensive biomarkers for measured health risk and morbidity comprises of:
– Anthropometric Measurements: Height, weight, Waist Circumference, Hip Circumference
– Functional Health Markers: Blood Pressure and Pulse rate (CVD), Lung Function Test (Obstructive airway diseases (OAD)/Respiratory Diseases),Vision Test: Near and Distance visual acuity (Near and Distance visual acuity)
– Performance Based Markers: Grip Strength, Timed-walk, Balance test
– Dried Blood Spot (DBS) based Markers: C-reactive Protein (CRP) (CVD), Epstein Bar virus (Immunity), Glycosylated Haemoglobin (HbA1c) (Diabetes), Haemoglobin (Hb) (Anaemia)
3. Community Schedules (administered at community level, village/rural and Urban/ward)
• The key informants for this schedule in Rural areas are village community head (Sarpanch/Pradhan/Up-pradhan/Panchayat chairperson) and village officer/Secretary (administrative person in-charge of the village).
• The key informants for this schedule in Urban areas are Ward any member of the ward (i.e. elected member/ officers/ engineers/ secretary) who knows about the ward area for at least 2 years. Moreover, the health section answered by Chief Medical Officer in the ward office.
The objective of conducting this survey in community(rural/urban) areas are:
– To study the community characteristics, which includes demographic, social, economic and infrastructural features;
– Access to educational institutions, health facilities, transport facilities and other public services for the community and elderly adults;
– Examine the awareness and coverage of government programs related to elderly health, social security and welfare;
– Identify the problems faced by the elderly in rural/urban areas.
LASI is the first dataset in India that will provide a longitudinal database for designing policies and programs for the older population in the broad domains of social, health and economic wellbeing and allow researcher to investigate in sufficient detail in dynamic links among ageing, health, and physical, social and economic environments.
LASI adopts the following state of the art of large-scale survey for survey protocol and field implementation.
Computer-Assisted Personal Interview (CAPI)
LASI employs computer-assisted personal interview (CAPI) technique to record the responses of survey participants.
This method requires field teams to be outfitted with laptop computers, pre-loaded with survey questions asked of respondents in a face-to-face interview.
Field teams input responses directly into a laptop computer, thereby limiting data entry processes as well as minimizing data recording and entry errors.
This also allows real time monitoring of quality of data.
Comprehensive Range of Biomarkers
Another feature of the LASI survey instrument is the collection of extensive range of biomarkers, which can be analyzed to provide researchers with quantitative data on health.
Biomarkers are as an important tool for understanding the association of socioeconomic status with health and mortality.
Biomarkers can be useful for studying a variety of social behaviors and environments, burden of health risk and chronic disease conditions.
– Anthropometric Measurements
– Functional Health Markers
– Performance Based Markers
– Dried Blood Spot (DBS) based Markers
Use of IT-based Technologies
LASI in addition IT based technologies and including Geographic information system (GPS), will be used for Thematic mapping and community analysis to collect the information at community level. Photographic identification and barcode technology will be used for matching and anonymizing data
For more details, please refer the
In 2010, LASI pilot survey was conducted successfully with targeted sample of 1,600 individuals aged 45 and older along with their spouses, and will inform the design and rollout of a full-scale, nationally representative LASI survey.
The expectation is that LASI will be a biennial survey and will be representative of Indians aged 45 and older, with no upper age limit.
The age of 45 is chosen to (a) harmonize this survey with its sister HRS surveys in Asia; and (b) allow measurement of pre-retirement behavior, as people often begin to change their labor market, health, and consumption behaviors as they age.
1,600 age-qualifying individuals were drawn using stratified, multistage area probability sampling design.
After a series of pre-pilot studies designed to test the instrument and the key ideas behind it was that the pilot data were collected through face-to-face interviews over period of three months.
Descriptive analysis of the data has been performed and lessons drawn will be used to inform the launching of a full-scale LASI survey.
The LASI pilot survey was conducted in four states: Karnataka, Kerala, Punjab, and Rajasthan.
To capture regional variation we have included two northern states (Punjab and Rajasthan) and two southern states (Karnataka and Kerala).
Karnataka and Rajasthan were included in the Study on Global AGEing and Adult Health (SAGE), which will enable us to compare our findings with the SAGE data.
The inclusion of Kerala and Punjab demonstrates our aim to obtain a broader representation of India, where geographic variations accompanied by socioeconomic and cultural differences call for careful study and deliberation.
Punjab is an example of an economically developed state, while Rajasthan is relatively poor, with very low female literacy, high fertility, and persisting gender disparities. Kerala, which is known for its relatively efficient health care system, has undergone rapid social development and is included as a potential harbinger of how other Indian states might evolve.
LASI-Pilot micro data
LASI Pilot Team Members
||Technical Team Staff
||Field Research Officers
| P. Arokiasamy, IIPS (PI)
||Vaidehi Yelamanchili, IIPS
|David E. Bloom, HSPH (PI)
||R.S. Reshmi, IIPS
|Jinkook Lee, RAND (PI)
||Ashok Posture, IIPS
||Heikrujam Amarjit Singh, IIPS
|Sulabha Parasuraman, IIPS
||Namita Sahoo, IIPS
|T.V. Sekher, IIPS
|S.K. Mohanty, IIPS
||Rajan Kumar Gupt, IIPS
|Lisa Berkman, HSPH
||Grant Benson, University of Michigan
|David Canning, HSPH
||Kevin Feeney, RAND Corporation
|Tarun Khanna, HSPH
||Steven Heeringa, University of Michigan
|Ajay Mahal, Monash University
||Heather Lanthorn, HSPH
|Amitabh Chandra, HSPH
|Nicholas Christakis, HSPH
||Jennifer O’Brien, HSPH
|Adeline Delavande, RAND
||Marija Ozolins, HSPH
|Peifeng Hu, University of California, Los Angeles
||Jessica Perkins, HSPH
|Arvind Mathur, IAG
||Teresa Seeman, University of California
|Arun Risbud, NARI
||Zubin Shroff, HSPH
|Kavita Sivaramakrishnan, Columbia University
||Esther Ullman, University of Michigan
|S.V. Subramanian, HSPH
||Sharon Williams, Purdue University
|Bas Weerman, RAND
||Joanne Yoong, RAND Corporation
LASI FINANCIAL SPONSORS
• Ministry of Health and Family Welfare (MoHFW) Govt. of India
• National Institute on Aging (NIA)/ National Institutes of Health (NIH), USA
• The United Nations Population Fund (UNFPA), India
LASI Collaborative Institutions
The longitudinal ageing study is designed in partnership between the following national and international institutions.
International Institute for Population Sciences (IIPS):
The International Institute for Population Sciences (IIPS), an autonomous institution under the MOHFW, Govt. of India Mumbai is the nodal institution for LASI Project implementation.
National Collaborating Institutions
• Regional Geriatric Centers under NCD division, Ministry of Health and Family Welfare, Govt. of India - Collaborating organizations for implementation of Biomarker component of LASI project.
• National AIDS Research Institute (NARI), Pune, collaborating Indian institution for DBS storage and molecular biomarker testing of DBS.
International Collaborating Institutions
• Harvard T. H. Chan School of Public Health (HSPH), USA – lead US collaborating institute for implementing the project activities.
• University of Southern California (USC), USA – Collaborating Institution for technical support in designing and developing the IT- CAPI tools and programming of LASI survey instrument.
• University of California, Los Angeles, (UCLA), USA - Collaborating US Institution for technical support on biomarker component of LASI project.
• RAND Corporation, USA - International Technical Advisors committee
LASI Main Wave TEAM
|International Institute of Population of Sciences (IIPS)
||Harvard T. H. Chan School of Public Health (HSPH)
||University of Southern California (USC)
|P. Arokiasamy, IIPS (PI)
||Prof. David Bloom (PI)
||Prof. Jinkook Lee (PI)
||Dr. Peifung Hu
||Mr. Bas Weerman
|Prof. S.K. Mohanty
|Dr. Aparajita Chattopadhyay
| Dr. Dipti Govil
| Dr. Sarang Pedgaonkar
|Dr. Sangeeta Gupta
||Ms. Arunika Agarwal
||Dr. Pranali Khobragade
|Dr. Benson Thomas M.
||Ms. Alyssa Lubet
|| Ms. Urvashi Jain
|Dr. Sanchita Sarang
||Ms. Sandy Chien
|Dr. Dipika Gudekar
|Dr. Snehaprabha Surpam
|Dr. G.V. Shannmugam
|Ms. Shradha S. Gharat
| Mr. Amit Khobragade
|Mr. Ashok Posture
||Ms. Binit Dhume
|Mr. Manoj Patange
|Ms. Madhavi Dhone
|Mr. Abhijit Sangale
| Ms. Devyani Ahire
| Mr. Amar Sapate
| Mr. Ashutosh Jadhav
|Accounts and Administration Team
|Ms. Dhanavanti Lawande
|Mr. Nazrul Haque Ansari
|Mr. Rambachan Vishwakarma
Technical Advisory Committee
National Technical Advisory Committee Members (NAC)
- Joint Secretary, Non-Communicable Diseases (NCD) Division, Ministry of Health and Family Welfare (MOHFW), Government of India (G0I)
- Joint Secretary, Ageing Division, Ministry of social Justice and Empowerment (MOSJE), Government of India (G0I)
- Deputy Director General, NCD Division, Ministry of Health and Family Welfare (MOHFW)
- Director, International Institute for Population Sciences (IIPS), Mumbai
- Director-General, Indian Council of Medical Research (ICMR) & Secretary, Department of Health Research, Ministry of Health and Family Welfare (MOHFW), Government of India (G0I)
- Director-General of Health Services, MOHFW, GOI
- Assistant Director-General, DGHS, MOHFW, GOI
- Chief Director, Statistics, MOHFW, GOI
- Deputy Secretary, NCD Division, MOHFW, GOI
- NCD Division, MOHFW, GOI
- United Nations Population Fund (UNFPA), Country Representative for India
- Head, NCD division ICMR
- P.M. Kulkarni, Chair
- National Institute of Health (NIH) Representative (India)
- M. H. Suryanarayana, Indira Gandhi Institute of Development Research (IGIDR), Mumbai
- Mathew Varghese, The National Institute of Mental Health and Neuroscience (NIMHANS), Bengaluru
- Sonalde Desai, National Council of Applied Economic Research (NCAER), Delhi
- Indira Jaiprakash, Bengaluru
- Moneer Alam, Institute of Economic Growth (IEG), Delhi
- S. lrudaya Rajan, Center for Development Studies (CDS), Kerala
- K. Srinath Reddy, Public Health Foundation of India (PHFI), Delhi
- Gita Sen, Indian Institute of Management (IIM), Bengaluru
- Heads of Regional Geriatric Centers, MOHFW
- Dr. Ashwini Shete, NARI, Pune
- Director, National AIDS Research Institute (NARI), Pune
- LASI PI Team from IIPS, Harvard school of Public Health and University of Southern California.
- Other special invitees
International Technical Advisory Committee Members (IAC)
- James Banks, University College, London
- James Smith, Rand Corporation, USA, Chair
- John Phillips, National Institute on Aging (NIA)
- David Weir, University of Michigan, USA
- David Wise, Harvard University, USA
- Yaohui Zhao, Beijing University, Beijing
- Axel Borsch-Supan, University Mannheim, Germany
- Somnath Chatterji, World Health Organization,
- Geneva Arie Kapteyn, RAND Corporation
- Michael Marmot, University College London
- Teresa Seeman, UCLA School of Medicine, California
- LASI PI Team from IIPS, Harvard school of Public Health and University of Southern California.