STATUS REPORT: INDEPTH Adult Health & Aging - with WHO SAGE – Site scientists, editorial team, mentors engaged funder R Suzman / NIA INDEPTH AGM, October 2009 Pune, India

Goals: INDEPTH Adult Health & Aging -> To establish INDEPTH’s capability to contribute critical insights into the adult health, aging and disease transitions evolving in Africa and Asia; -> To use this understanding to evaluate interventions of potentially high impact

Background October 2003, Johannesburg develop’t of INDEPTH Adult Health & Aging platform 17 African and Asian sites April 2005, Johannesburg collaboration with Evidence, Info & Res for Policy, WHO development of INDEPTH/WHO short module 2006 – 2007: 8 INDEPTH sites Fieldwork: short module (8 sites); full SAGE (3 sites) May 2008, Epidemiol & Global Health, Umeå U, Sweden Data harmonization and analysis workshop  Paper drafting, internal review

INDEPTH-WHO collaboration Aims to: conduct a summary physical & cognitive function module that is integrated into routine surveillance rounds [implement the full version of SAGE in a few DSS sites] Summary function module should: be repeated regularly to allow measurement of health transition in older populations relate health transition to demographic events such as fatal health outcomes (mortality) Large samples will be needed to examine associations with cause-specific mortality.

2008, Umeå workshop

INDEPTH-WHO physical & cognitive function in older adults 2006/7 SiteStudy populationPhysical and cognitive evaluation Site popPop 50+SAGE- INDEPTH summary Full SAGE survey AFRICA Agincourt, South Africa XX Ifakara, Tanzania X Nairobi, Kenya X Navrongo, Ghana XX ASIA Filabavi, Vietnam X Matlab, Bangladesh X Purworejo, Indonesia X Vadu, India XX

SAGE Instruments (Summary Modules) Health state descriptions –Self reported health status –Difficulty with work/household activities –8 health domains: mobility, self-care, pain and discomfort, cognition, interpersonal activities, affect, vision, sleep and energy. –Set of vignettes for the 8 health domains: 5 scenarios for each domain Subjective wellbeing and quality of life All questions are in categorical ordered response

Analyzing the SAGE data Creating composite index –WHO-DAS (Disability Assessment Schedule) –WHO-QOL (Quality of Life) –WHO-Health Score Enriching the data with DSS variables Age at time of interview, sex, education completed, marital status, HH size, number of HH member 50+ in the same household, SES quintile

Health Score: difficulties in conducting activities in eight health domains: affect, cognition, interpersonal activities, mobility, pain, self-care, sleep and energy, and vision. Quality of Life index: respondent’s thoughts about their life and life situation, satisfaction with themselves, health, ability to perform daily living activities, personal relationships, living conditions, and overall life. Disability assessment: difficulties in functional assessment and activities in the last 30 days All questions were posed as five-response scale Results transformed to a continuous cardinal scale from 0 to 100 The composite scores

Study subjects SitesMenWomenTotal Navrongo-GH*1,7892,7954,584 Ifakara-TZ*2,4542,6775,131 Nairobi-KE*1, ,072 Agincourt-SA*1,0123,0734,085 Vadu-ID2,8052,6255,430 Matlab-BD*2,0162,0214,037 Filabavi-VN3,4695,0668,535 Purworejo-ID5,7276,66812,395 Total20,59925,67046,269 Sample of 50+ (*) vs. All of 50+

NavrongoIfakaraNairobiAgincourt Sleep/energy Pain/discomfort Vision Sleep/energy Mobility -3.1 Mobility Pain/discomfort Pain/discomfort Affect Vision Sleep/energy Cognition Pain/discomfort Sleep/energy Affect Affect Cognition Cognition -2.5 Mobility -1.6 Vision Interpersonal Affect Cognition -1.6 Mobility Vision Interpersonal Interpersonal Interpersonal -0.6 Self-care Self-care Self-care Self-care Health score was used as outcome variables, and the regression analyses were adjusted to sex, age, education level, socio-economic quintiles, and marital status in each site.

VaduMatlabFilabaviPurworejo Vision Mobility Mobility Pain/discomfort -2.5 Pain/discomfort Pain/discomfort Sleep/energy Cognition Mobility Affect Pain/discomfort -2.9 Vision Interpersonal Sleep/energy Cognition -2.5 Sleep/energy Affect Vision Affect Affect Cognition Cognition Vision Mobility Self-care Interpersonal Interpersonal Interpersonal Sleep/energy Self-care Self-care 0.8 Self-care Health score was used as outcome variables, and the regression analyses were adjusted to sex, age, education level, socio-economic quintiles, and marital status in each site.

 Predictors of poor health are being women, older age, lived in Matlab, Agincourt and Navrongo, low SES, and reported disability and poor functioning.  A larger difference of health score in men and women than expected.  Post-regression decomposition: 87% of the health score difference was attributable to differences of age, education, socio-economic levels, marital status, living arrangement, disability and functioning, quality of life between men and women. Cross-site highlights

Journal progress update: Global Health Action CONTRIBUTIONSTATUS Foreword Awaited EditorialTo be written once all papers ready Background/methods paper 1 st draft complete Site-specific papers 7 of 8 ready for peer review Online submission to GHA underway Senior reviewer/mentor selected Cross-site comparative paper Analyses in advanced stage CommentariesAuthors to be invited Journal launch 2010 with release Public access dataset

Planning ahead… Further analyses and writing with enriched dataset (contextual variables, longitudinal data) –Data validity: cross-site comparison INDEPTH-Harvard workshop 04/2010 Repeat module Bring together… –NCD risk factor module –Work on demogr / epidem transitions –Work on health systems R&D Program of intervention / health systems R&D