Fall Risk in Low-Income Elderly People in One Urban Area

Abstract

The purpose of this study was to investigate the factors that increase of the risk for falls in low-income elders in urban areas. The participants were elderly people registered in one of public health centers in one city. Data were collected by interviewing the elders, assessing their environmental risk factors, and surveying relevant secondary data from the public health center records. For data analysis, descriptive statistics and multiple logistic regression were performed using SPSS version 14. Stroke, diabetes, visual deficits, frequency of dizziness, use of assistive devices and moderate depression were statistically significant risk factors. The comorbidity of chronic diseases with other factors including depression, visual deficit, dizziness, and use of assistive devices significantly increased the risk of falls. From multiple logistic regression analysis, statistically significant predictors of falls were found to be stroke, total environmental risk scores, comorbidity of diabetes with visual deficits, and with depression. Fall prevention interventions should be multifactorial, especially for the elders with stroke or diabetes, who were identified in this study as the high risk group for falls. A fall risk assessment tool for low-income elders should include both the intrinsic factors like depression, dizziness, and use of assistive devices, and the extrinsic factors.