The burden of disease from dementia is a growing global concern as incidence increases exponentially with age and average life expectancy has been increasing around the world. Planning for an aging population requires reliable projections of future dementia prevalence and resource requirements, however, existing population projections are simple and have poor predictive accuracy. The Dementia Population Risk Tool (DemPoRT) will predict incidence of dementia in the population setting using multivariable modeling techniques.~The derivation cohort will consist of elderly Ontario respondents of Canadian Community Health Survey (CCHS) (2001, 2003, 2005, 2007; approximately 19 000 males and 25 000 females). Pre-specified predictors include sociodemographic, general health, behavioral, functional and health condition variables. Incident dementia will be identified through individual linkage of survey respondents to population-level administrative health care databases. Using time of first dementia capture as the primary outcome and death as a competing risk, sex-specific proportional hazards regression models will be estimated. The 2008/2009 CCHS survey be used for validation (approximately 4 600 males and 6 300 females). Overall calibration and discrimination will be assessed as well as calibration within predefined subgroups of importance to clinicians and policy makers.
The purpose of this study is to develop and validate the Dementia Population Risk Tool (DemPoRT) algorithm to predict dementia incidence in the population setting.