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Dataset: World Health Organization Study on global Ageing and adult health (SAGE)

Basic Information
Dataset Full Name World Health Organization Study on global Ageing and adult health
Dataset Acronym SAGE
Summary

SAGE is a longitudinal study of adults over 50 years and older living in six countries: China, Ghana, India, Mexico, Russian Federation and South Africa.There is also a comparison sample of adults aged 18-49 years from each country.  It is part of an ongoing effort to compile comprehensive longitudinal information on the health and well-being of adult populations and the aging process. Participants are a nationally representative sample for each country. As of 2017 there were 2 waves of data available in addition to the baseline data (collected in 2002-2004).  Training  for Wave 3 data collection began in Feb 2017.

Key Terms
  • Aging, Longitudinal, Health, Disability
  • Health risk factors, Health attitudes, Nutrition, Physical activity
  • Health care utilization, Health care expenditure, Health care quality
  • Social participation, Well being, Quality of life, Caregiving
  • Housing, environmental risk factors
  •  Economic well-being, assets and expenditures
Study Design Longitudinal
Data Type(s) Clinical
Survey
Sponsoring Agency/Entity

National Institutes of Health (NIH)

Health Conditions/Disability Measures
Health Condition(s)

Depression, Eye diseases, Arthritis, Stroke, Cardiovascular conditions, Diabetes, Pulmonary disorders, Body mass index (BMI)/obesity, Chronic pain, Oral health, Injuries, AIDS/HIV

Disability Measures

Ambulatory disability, Special equipment use/assistive technology, Physical disability, Cognitive disability, Functional limitations (ADLs and/or IADLs), Hearing disability, Visual disability,


Other measures: Timed walk, Vision test, Grip strength, Lung function, WHO Disability Assessment Schedule 2.0 (WHODAS 2.0), 10-WORD list for memory recall 

Measures/Outcomes of Interest
Topics
  • Health coverage and utilization trends among countries.
  • Education, occupation and retirement income and their effects on physical and mental health.
  • Impact of HIV and caregiving.
  • Social engagement and health
  • Employment, Retirement, Work history, Occupation
  • Self-care, Independence, Sleep, Functioning assessment
  • Quality of life, Well-being
  • HIV, Caregiving
Sample
Sample Population

Household population: Adults 50 years and older of age residing in one of the participating countries

Sample Size/Notes
  • 63,445 at baseline (Wave 0, 2002-2004) of whom 18,883 were over 50 years old
  • In Wave 1, 34,127 adults were over 50 years old and 8,327 were 18-49 years old and these are followed to subsequent waves.
Unit of Observation

Individual

Continent(s)

Africa, Asia, Central America & Caribbean

Countries

China, Ghana, India, Mexico, Russian Federation, South Africa

Geographic Coverage

Multi-national:

  • China
  • Ghana
  • India
  • Mexico
  • Russian Federation
  • South Africa
Geographic specificity

Area of residence/city

Special Population(s)

Aging/Older people

Data Collection
Data Collection Mode

At home survey interviews, physical examination and blood collection

Years Collected
  • Wave 0: 2002/04
  • Wave 1: 2007/10
  • Wave 2: 2014/15
  • Wave 3: 2017/18

Data Collection Frequency

Frequency varied by wave and country. Between 3-5 years

Strengths and Limitations
Strengths
  • Multinational, representative and longitudinal data ideal for exploring time and cross-national trends in health, disability and aging..
  • Multidisciplinary survey items accompanied with objective measurements (biomarkers, anthropometric measurements, physical exams). 
  • Some outcomes of the SAGE can be harmonized with HRS, ELSA and SHARE studies.
  • Sub-samples have been asked to participate in further surveys; SAGE-HIV and SAGE-INDEPTH and SAGE-Salt and Tobacco, allowing for further research on health and disability determinants. Can also be used for health policy research.
Limitations
  • Not all countries are participating in all waves or sub-studies, limiting longitudinal analyses and comparisons.
  • Misreporting of comorbidities probable in absence of objective measurement. 
  • Only nine common chronic conditions are surveyed; Potential underreporting.
  • SAGE instrument pre-tested in India, Ghana and Tanzania 
  • Response rates varies significantly between countries: highest in China 98%, Mexico: 51% (Individual response rate)

Data Details
Primary Website

http://www.who.int/healthinfo/sage/en/

Data Access

http://apps.who.int/healthinfo/systems/surveydata/index.php/catalog

Data Access Requirements

Public Use Dataset

Summary Tables/reports

Wave 0:

http://www.who.int/healthinfo/sage/SAGE_Wave0_BackgroundCharacteristics.pdf?ua=1


Wave 1:

http://www.who.int/healthinfo/sage/SAGE_Wave1_BackgroundCharacteristics.pdf?ua=1


Data Components

Separate datasets available for each country/wave:

http://apps.who.int/healthinfo/systems/surveydata/index.php/catalog/sage

Similar/Related Dataset(s)

Other longitudinal ageing studies:

Selected papers
Other Papers

http://www.who.int/healthinfo/sage/articles_all/en/

Technical

http://www.who.int/healthinfo/survey/SAGESurveyManualFinal.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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