[Epidemiological characteristics of falls in the elderly in Jiangsu from 2006 to 2021]

Objective: To understand the epidemiological characteristics and influencing factors of elderly unintentional fall-related injuries (EUFI) in Jiangsu from 2006 to 2021 and provide a scientific basis for the prevention of falls in the elderly and the formulation of related policies. Methods: Data on EUFI was collected from the first diagnosed cases in the injury surveillance hospitals in Jiangsu from 2006 to 2021, and epidemiological characteristics of injuries were analyzed. logistic regression was performed to identify the risk factors for EUFI. Results: The number of EUFI increased from 2006 to 2021, ranked as the first cause of elderly unintentional injuries during these years. The proportion of EUFI among elderly unintentional injuries increased in the same period. The male-to-female ratio is 1∶1.4. Falls mainly occurred during 8:00-10:00 am (32.7%). The most common place where falls occurred was at home (63.6%). From 2006 to 2014, leisure activities (62.1%), housework/study (23.1%), and work (5.2%) were the top three activities when injuries occurred. During 2015-2021, leisure activities (41.7%), housework/study (22.6%) and walking (20.5%) were the top three activities when injuries occurred. The major fall-related injuries were fractures (39.9%), with the injured parts at low limbs (32.5%), of which most were mild injuries (60.3%), and the primary outcome was hospitalization after treatment (74.1%). logistic regression showed that the risk factors of EUFI were female, old age, immigrants, winter, public residence, housework/study, and leisure activities. Higher education, occupation of household and production and transportation equipment operators were protective factors (all P<0.05). Conclusions: Fall is the leading cause of unintentional injuries in the elderly in Jiangsu, especially the elderly female population. Corresponding measures should be taken to prevent and intervene in falls in the elderly in the community according to the distribution characteristics.