Estimating the Lifetime Risk of Dementia in the Canadian Elderly Population Using Cross-Sectional Cohort Survival Data

• Published in: Journal of the American Statistical Association 2014, Vol.109 (505), p.24-35
• Main Authors: Carone, Marco, Asgharian, Masoud, Jewell, Nicholas P.
• Format: Article
• Language: English
• Subjects: Applications and Case Studies; Bias; cohort studies; Cross-sectional sampling; cross-sectional studies; cumulative risk; Dementia; Distribution functions; elderly; Epidemiology; Estimators; Invariance; Left truncation; Loss to follow-up; Older adults; Older people; Participant observation; Point processes; Population estimates; Population recruitment; public health; Sampling; Sampling bias; Simulation; Statistics; Stratified sampling; Survival analysis; Truncation
• ISSN: 1537-274X; 0162-1459; 1537-274X
• DOI: 10.1080/01621459.2013.859076

Dementia is one of the world's major public health challenges. The lifetime risk of dementia is the proportion of individuals who ever develop dementia during their lifetime. Despite its importance to epidemiologists and policy-makers, this measure does not seem to have been estimated in the Canadian population. Data from a birth cohort study of dementia are not available. Instead, we must rely on data from the Canadian Study of Health and Aging, a large cross-sectional study of dementia with follow-up for survival. These data present challenges because they include substantial loss to follow-up and are not representatively drawn from the target population because of structural sampling biases. A first bias is imparted by the cross-sectional sampling scheme, while a second bias is a result of stratified sampling. Estimation of the lifetime risk and related quantities in the presence of these biases has not been previously addressed in the literature. We develop and study nonparametric estimators of the lifetime risk, the remaining lifetime risk, and cumulative risk at specific ages, accounting for these complexities. In particular, we reveal the fact that estimation of the lifetime risk is invariant to stratification by current age at sampling. We present simulation results validating our methodology, and provide novel facts about the epidemiology of dementia in Canada using data from the Canadian Study of Health and Aging. Supplementary materials for this article are available online.