Post on 27-Jan-2015
description
Disability Transitions and Health Expectancies among Adults 45 Years and Older in Malawi: A Cohort-Based
Model
Collin F Payne, UPenn GGD & PSCJames Mkandawire, IKI MalawiHans-Peter Kohler, UPenn PSC
GHME 2013June 18
Population growth by age group in SSA 2010–2060 (2010 = 100), share of total
population by age groups
Source: authors’ calculations based on United Nations World Population Prospects 2010 population projections.
SSA: Person Years Lived Above Age 25 By Age Group
Source: authors’ calculations based on United Nations World Population Prospects 2010 population projections.
• Evidence about health and disability among older adults in SSA is very limited
• High levels of labor force participation: 98% for age 50–64, 90% for age 65+ based on the 2009 Malawi Welfare Monitoring Survey (WMS)
• Individuals are very poorly served by the existing health infrastructure in SSA—government health clinics are not equipped to deal with the chronic diseases of aging
Focus on Mature Adults (= individuals aged 45+)
Our Research
• Focus on day-to-day activities in domains relevant to the subsistence-agriculture context of rural Malawi. – Analyze patterns of transition between levels of
disability across age– Estimate health expectancies (HEs) in levels of
disability
• Characterize processes of health, aging, and functional limitations in rural Malawi
• Seek to provide insights into the potential gains in well-being and economic productivity which could arise from investments in the health of older adults in SSA.
Malawi Longitudinal Survey of Families and Health (MLSFH)
• Longitudinal household panel conducted by UPenn
• Our analyses use data from 2006, 2008, and 2010 rounds• Parent sample added in 2008, bringing number of individuals
age 45+ to ~1,200
• HIV testing among individuals aged 45+ y in the 2008 MLSFH found an overall HIV prevalence of 3.3%.
• Basic demographic and socioeconomic characteristics are similar between our 2010 study population and the 45+ y rural population in the nationally representative Malawi 2010–2011 Third Integrated Household Survey (IHS3).
• Classification of physical limitations (“disability”) based on 2 questions from SF12 module – limitations in cooking and cleaning, walking to meetings
in the village, or tending to cattle and livestock
– limitations in carrying heavy loads, working on the farm, pounding maize, or digging a pit latrine
• Response categories of “limited a lot”, “limited a little”, or “not limited”
• Disability Status (“lived experience with disability”)– healthy: no limitations in either set of activities
– moderately limited: “limited a little” in either set of activities
– severely limited: “limited a lot” in either set of activities
Disability Status
Self-Reported disability, % working for income, pain interfering with work, and subjective well-
being
Source: Payne CF, Mkandawire J, Kohler H-P (2013) Disability Transitions and Health Expectancies among Adults 45 Years and Older in Malawi: A Cohort-Based Model. PLoS Med 10(5): e1001435. doi:10.1371/journal.pmed.1001435
Analysis Model• Microsimulation-based multistate life table—based on the
Stochastic Population Analysis for Complex Events (SPACE) program.
1) Estimate transition probabilities• Estimate conditional (on age, sex, and health state) annual probabilities of transitioning between health states (healthy, moderately limited, severely limited, dead): 2) Generate health expectancies• Create synthetic cohorts of 100,000 45-, 55-, 65-, and 75-y-old
individuals with the same initial gender and health state distribution as our study population
• Microsimulation: ‘‘Age’’ these individuals forward year by year using conditional transition probabilities and rates of mortality estimated from the data, repeat until death.– Estimate CIs by analyzing 499 bootstrap re-samples of the initial dataset and
taking the central 95% of the resulting distribution
Estimated Annual Transition Probabilities between Health Statuses
Source: Payne CF, Mkandawire J, Kohler H-P (2013) Disability Transitions and Health Expectancies among Adults 45 Years and Older in Malawi: A Cohort-Based Model. PLoS Med 10(5): e1001435. doi:10.1371/journal.pmed.1001435
A) From Healthy B) From Moderately Limited
Estimated Annual Transition Probabilities between Health Statuses
Source: Payne CF, Mkandawire J, Kohler H-P (2013) Disability Transitions and Health Expectancies among Adults 45 Years and Older in Malawi: A Cohort-Based Model. PLoS Med 10(5): e1001435. doi:10.1371/journal.pmed.1001435
C) From Severely Limited D) Mortality Probabilities
Health expectancies: Average remaining life expectancy (LE) at ages 45–75
Source: Payne CF, Mkandawire J, Kohler H-P (2013) Disability Transitions and Health Expectancies among Adults 45 Years and Older in Malawi: A Cohort-Based Model. PLoS Med 10(5): e1001435. doi:10.1371/journal.pmed.1001435
Discussion
• Functional limitations are associated with a lower likelihood of working for income and reduced work efforts in agriculture
• Risks of experiencing an onset of functional limitations are high compared to developed contexts
• Onset of functional limitations happens earlier in life– Proportion of remaining life spent in severe
limitation at age 45 is comparable to 80-year olds in the US
Implications• Older population in SSA has been largely
left out of health-focused interventions and policies, particularly those focusing on MDGs.
• Many policy makers in SSA hesitant to direct money to the elderly population, and see investment in the aging population as “irrelevant to core national development interests”.
• Based on our findings, we believe that sentiment is misguided—the high burden of disability among mature adults is associated with substantial loss of labor output.
Thanks!
• Any post-discussion questions:– collinp@sas.upenn.edu– Paper is available at PLOS Medicine• doi:10.1371/journal.pmed.1001435
• Acknowledgements:– I am supported by the NSF Graduate
Research Fellowship (Grant No. DGE-0822)