title: Projection of young-old and old-old with functional disability: does accounting for the changing educational composition of the elderly population make a difference?
abstract: This study compares projections, up to year 2040, of young-old (aged 60-79) and old-old (aged 80+) with functional disability in Singapore with and without accounting for the changing educational composition of the Singaporean elderly. Two multi-state population models, with and without accounting for educational composition respectively, were developed, parameterized with age-gender-(education)-specific transition probabilities (between active, functional disability and death states) estimated from two waves (2009 and 2011) of a nationally representative survey of community-dwelling Singaporeans aged ≥ 60 years (N=4,990). Probabilistic sensitivity analysis with the bootstrap method was used to obtain the 95% confidence interval of the transition probabilities. Not accounting for educational composition overestimated the young-old with functional disability by 65 percent and underestimated the old-old by 20 percent in 2040. Accounting for educational composition, the proportion of old-old with functional disability increased from 40.8 percent in 2000 to 64.4 percent by 2040; not accounting for educational composition, the proportion in 2040 was 49.4 percent. Since the health profiles, and hence care needs, of the old-old differ from those of the young-old, health care service utilization and expenditure and the demand for formal and informal caregiving will be affected, impacting health and long-term care policy.
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors.forename: John P
authors.initials: JP
authors.lastname: Ansah
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors.forename: Rahul
authors.initials: R
authors.lastname: Malhotra
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors.forename: Nicola
authors.initials: N
authors.lastname: Lew
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors.forename: Chi-Tsun
authors.initials: CT
authors.lastname: Chiu
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore; Department of Sociology, National University of Singapore, Singapore, Singapore.
authors.forename: Angelique
authors.initials: A
authors.lastname: Chan
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore.
authors.forename: Steffen
authors.initials: S
authors.lastname: Bayer
authors.affiliation: Signature Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore, Singapore; Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America.
authors.forename: David B
authors.initials: DB
authors.lastname: Matchar
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D004185:Disability Evaluation; D004522:Educational Status; D005260:Female; D005544:Forecasting / Q000379:methods; D005102:Health Expenditures; D006301:Health Services Needs and Demand / Q000191:economics; D006306:Health Surveys; D006801:Humans; D008134:Long-Term Care / Q000191:economics; D008297:Male; D008875:Middle Aged; D012846:Singapore