The impact of methods to handle missing data on the estimated prevalence of dementia and mild cognitive impairment in a cross-sectional study including non-responders.

Objective: Although several statistical methods for adjusting for missing data have been developed and are widely applied in research, few studies have investigated these methods in adjusting for missingness in datasets that aim to estimate the prevalence of dementia. We attempted to develop a more feasible approach for handling missingness in a cross-sectional study among elderly.

Methods: Five methods of estimating prevalence, including stratified weighting (SW), inverse-probability weighting (IPW), hot deck imputation (HDI), ordinal logistic regression (OLR) and multiple imputation (MI), were applied to handle the missing data yielded by a dataset that include 2231 non-responders.

Awareness Status of Chronic Disabling Neurological Diseases among Elderly Veterans.

Background: The awareness, treatment and prevention of chronic diseases are generally poor among the elderly population of China, whereas the prevention and control of chronic diseases in elderly veteran communities have been ongoing for more than 30 years. Therefore, investigating the awareness status of chronic disabling neurological diseases (CDND) and common chronic diseases (CCD) among elderly veterans may provide references for related programs among the elderly in the general population.

Methods: A cross-sectional survey was conducted among veterans ≥60 years old in veteran communities in Beijing.