Multilevel logistic regression analysis on determinants of adult stroke incidence in Indonesia.

Stroke is a disease or functional disorder of the brain due to blockage (ischemic stroke) or bleeding (hemorrhagic stroke) which can cause death and disability of the sufferer. The prevalence of stroke in Indonesia is still relatively high. As a result, we need a preventive action through early detection by understanding the risk factors that can affect the incidence of stroke in Indonesian society. This study aims to identify the most important risk factors for stroke patients in Indonesia between the ages of 41 and 60 years. This study drew on secondary data from the Rand Corporation website, specifically the fifth wave of the Indonesian Family Life Survey (IFLS-5) conducted in 2014-2015. Multilevel logistic regression model is used to model one binary response variable with one or more independent variables for data having a hierarchical structure. A multilevel logistic regression analysis is used to explain the relationship between stroke case (yes/no) and variables of age, sex, activity, hypertension, diabetes, and average age per province. The multilevel logistic regression modeling results revealed that age (p<0.0001), light activity (p = 0.01), moderate activity (p = 0.02), hypertension (p<0.0001), and diabetes (p = 0.01) were significantly associated in level 1 and the average age per province (p = 0.02). [ABSTRACT FROM AUTHOR]