Risk Factors and Predictive Model of Long-term Bedridden Risk of Falls in Super-aged Population Based on Competing Risk Model Analysis

Abstract

Background With the aging trend intensifying in China, the number of super-aged population (≥80 years old) is also increasing. This demographic faces a notable decline in balance and reaction capabilities, resulting in an elevated risk of falls than that of other age groups of the elderly. Falls leading to long-term bedridden risk of falls often pose a serious disease burden to families and society. Exploring the potential risk factors for falls in the super-aged people may provide reference for the fall prevention in this population. Objective To identify long-term bedridden risk of falls in super-aged population and develop a risk predictive model. Methods A prospective cohort study was conducted to collect relevant information based on the China Health and Retirement Longitudinal Study questionnaire among the super-aged people who regularly participate in annual physical examination in five districts and counties of Shanghai and Hangzhou from March to November 2015, and to follow up and observe long-term bedridden caused by falls (endpoint events) and death (competing events), a competing risk model was constructed to analyze the influencing factors of long-term bedridden caused by falls. Independent risk factors identified by the competing risk model were used to construct a risk predictive model and nomogram of long-term bedridden risk of falls in super-aged population, and receiver operating characteristic (ROC) curve was plotted to evaluate the accuracy of the model. Results A total of 986 super-aged individuals were included in this study, including 431 (43.7%) males and 555 (56.3%) females, with an average age of (89.8±5.2) years. After 8 years of follow-up, 96 people were lost to follow-up, with a loss rate of 9.7%; endpoint events occurred in 165 people with an incidence rate of 16.7%; 134 people had competing events, with an incidence rate of 13.6%. Competing risk model analysis showed an increase in muscle strength (HR=1.071, 95%CI=1.049-1.091), age>85 years (HR=1.954, 95%CI=1.255-3.042), rural household location (HR=1.946, 95%CI=1.385-2.731), poor sleep quality (HR=5.756, 95%CI=3.904-8.491), cataract (HR=1.832, 95%CI=1.201-2.794), diabetes (HR=1.549, 95%CI=1.121-2.143), cognitive impairment (HR=1.717, 95%CI=1.258-2.344) were independent risk factors for long-term bedridden caused by falls in elderly population under the influence of competing events, and the difference was statistically significant (P<0.05). The area under the ROC curve of the predictive model for the risk of falls resulting in long-term bedridden in the super-aged people was 0.798 (95%CI=0.608-0.988), with a sensitivity of 0.841 and a specificity of 0.677. Conclusion The incidence of long-term bedridden caused by falls in elderly population was 16.7%. A nomogram predictive model can be constructed based on factors such as muscle strength, age, household location, sleep quality, cataracts and diabetes status, cognitive function, to regularly assess the risk of falls in super-aged population. It is recommended to strengthen health education and social support, and reduce the incidence of falls and the risk of long-term bedridden caused by falls.

Keywords

• aged, 80 and over|falls|long-term bedridden|risk factors|nomograms|cohort studies|competing risk models