Abstract
It is unclear how temporal trends in dementia incidence, alongside fast-changing demography, will influence China's future dementia burden. We developed a Markov model that combines population trends in dementia, mortality, and dementia-related comorbidities, to forecast and decompose the burden of dementia in China to2050. Population-based Chinese ageing cohorts provided input data for a 10-health-state Markov macrosimulation model, IMPACT-China Ageing Model (CAM), to predict sex- and age-specific dementia prevalence among people aged 50+ by year to 2050. We assumed three potential future scenarios representing the range of likely dementia incidence trends: upward (+2.9%), flat (0%) or downward (-1.0%). Sensitivity analyses were conducted to examine uncertainty associated with trends in mortality rates and CVD incidence. The projected dementia burden was decomposed into population growth, population ageing, and changing dementia prevalence corresponding to the three incidence trend scenarios. Under the upward trend scenario, the estimated number of people living with dementia is projected to rise to 66.3 million (95% uncertainty interval (UI) 64.7-68.0 million), accounting for 10.4% of the Chinese population aged 50+ by 2050. This large burden will be lower, 43.9 (95% UI 42.9-45.0) million and 37.5 (95% UI 36.5-38.4) million, if dementia incidence remains constant or decreases. Robustness of the projection is confirmed by sensitivity analyses. Decomposition of the change in projected dementia cases indicates dominate effects of increasing dementia prevalence and population ageing, and a relatively minor contribution from negative population growth. Our findings highlight an impending surge in dementia cases in China in the forthcoming decades if the upward trend in dementia incidence continues. Public health interventions geared towards dementia prevention could play a pivotal role in alleviating this burgeoning disease issue. National Science Foundation of China/UK Economic and Social Research Council.
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