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Dataset: Canadian Longitudinal Study on Aging (CLSA)

Basic Information
Dataset Full Name Canadian Longitudinal Study on Aging
Dataset Acronym CLSA
Summary CLSA is an ongoing, national, longitudinal study following approximately 50,000 adults 45-85 years old living in Canada and is a strategic initiative of the Canadian Institutes of Health Research (CIHR). Recruitment began at multiple sites from 2010 to 2015 . Participants will be followed for at least 20 years with data being collected every 3 years. The CLSA collects information on biological, medical, psychological, economic, social and lifestyle factors. It is designed to develop a better understanding of how those factors affect health and the development of disease and disability as people age. The CLSA will be linked to health administration databases (94% participants consented) that will provide complimentary information regarding medication use, health service utilization, and mortality.

Key Terms

Aging, Longitudinal, Health,Health care utilization, Disability, Retirement, Income

Study Design Longitudinal
Data Type(s) Clinical
Sponsoring Agency/Entity

Canada Foundation for Innovation

Health Conditions/Disability Measures
Health Condition(s)

ICD-9/10 diagnostic codes, Allergies, Alzheimer's/dementia, Anxiety disorders, Arthritis, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions, Chronic pain, Depression, Diabetes, Epilepsy or seizure disorder, Eye diseases, Infectious diseases, Kidney/renal condition, Migraine or frequent headaches, Multiple sclerosis, Neurological conditions, Osteoporosis, Parkinson's disease, Post Traumatic Stress Disorder (PTSD), Stroke, Thyroid disease

Disability Measures

Chronic conditions, Cognitive decline, Cognitive disability, Depression scale, Functional limitations (ADLs and/or IADLs), Hearing disability, Mental health disability, Pain and discomfort, Physical disability, Psychological distress, Special equipment use/assistive technology, Visual disability, Work limitation

Contains a variety of measurements and tests including bone density, visual acuity, hearing, grip strength, walking, standing, balance, spirometry, etc. See Physical Assessments Summary Table.

Measures/Outcomes of Interest
  • Health risks, Unmet health care needs, Injuries, Falls & causes, Chronic disease, Health attitudes, Oral health, Assistive devices
  • Biomarkers, Nutrition, Medication, Sleep, Physical activity
  • Personality traits, Caregivers/caregiving, Elder abuse, Social networks/support, Participation, Life satisfaction
  • Loneliness, Social inequality, Psychological distress
  • Mobility, Transportation, Migration
Sample Population

Household (Adults aged from 45 to 85 at initial recruitment (2010-2015) residing in Canada.)

Sample Size/Notes

50,000 at baseline (2010-2015)

Unit of Observation


Continent(s) North America


Geographic Coverage


Geographic Specificity

7 Canadian Provinces: Alberta, British Columbia, Manitoba, Newfoundland and Labrador, Nova Scotia, Ontario, and Quebec

Special Population(s)

Aging/Older people

Data Collection
Data Collection Mode
  • 20,000 participants provided data through phone interviews
  • 30,000 participants data collected through in-home interviews and site visits for clinical evaluations/exams
Years Collected

Baseline: 2010-2015 

First follow-up: 2015-2018 (ongoing)

Data Collection Frequency

Planned: Every 3 years

Strengths and Limitations
  • Large sample size. Multi-center project. Ideal for longitudinal analysis on heath risk behaviors for development of chronic diseases, psychological disorders and cognitive deficits.
  • Extensive series of survey items regarding health attitudes, medical history, social support, lifestyle, mental health, cognitive impairment, physical and functioning limitations
  • Data Preview portal useful for identifying available variables & sample sizes
  • First follow-up is ongoing, attrition rates unknown
  • At least 5 more years are required until adequate follow up data are collected and released for longitudinal analysis (Follow up 2)
  • Not all data from each wave are released simultaneously
  • Long review process to access data, 6 months from application to data receipt.  Three application deadlines/year. 
Data Details
Primary Website https://www.clsa-elcv.ca/
Data Access https://www.clsa-elcv.ca/data-access
Data Access Requirements

Data Use agreement, $ Cost 

Note: fee waiver requests available for graduate students (M.Sc. or Ph.D.) enrolled at Canadian universities who wish to obtain the CLSA data for the sole purpose of their thesis and postdoctoral fellows who wish to obtain the CLSA data for the sole purpose of their postdoctoral project.

Summary Tables/Reports

Data Preview Portal:


Data Components
  • COM - Comprehensive Assessment (V1_Baseline)
  • TRM - Tracking Assessment (V3_Baseline)
  • TMCQ - 30-minute telephone interview (V1_Baseline Tracking)
  • CMCQ - 30-minute telephone interview (V1_Baseline Comprehensive)
Similar/Related Dataset(s)

Other longitudinal ageing studies:

Selected Papers
Other Papers

Approved CLSA project summaries:



Data support documentation


Canadian Longitudinal Study on Aging (CLSA) Protocol:


Canadian Longitudinal Study on Aging (CLSA) Follow-Up 1 Renewal Protocol:


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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).

Other CLDR supported resources and collaborative opportunities:

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.

For questions or comments please contact disabilitystatistics@cornell.edu