Multidimensional assessment of elderly people’s health for the development of a fall risk index

As life expectancy increases, the likelihood of more falls and fall-related hospitalizations increases with a significant impact on the health system. Given the high incidence of falls in healthy elderly people, in order to prevent them, it is necessary to identify predisposing risk factors, analyze the specific needs of the subjects and use a targeted preventive strategy. This paper investigates the influence of multidimensional health parameters on the fall risk of community-dwelling older people, living in inner areas of Marche Region (Italy). Multidimensional data on the global health of each individual has been collected among several health domains (i.e., mobility, psychological, nutritional, cardiological, social). Statistical analysis has been applied for the assessment of the relationship among the defined health variables and the influence on the fall risk. The binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability. The following features have been proven to be strong predictors of fall: female (OR for Gender, 5.526; 95% CI, 1.49–20.53), limited range of movement (OR 3.278; 95% CI, 1.01-10.68), diabetes (OR 4.487; 95% CI, 1.02-19.80), previous syncope (OR 7.686; 95% CI, 1.01-58.55), and body mass index (OR 1.176; 95% CI, 1.03-1.35). Future work will allow the development of a fall prediction index to have a framework of the elder’s global health status and to define a personalized intervention strategy for any adverse event prevention.