1.Predictive model of fecal or urinary incontinence among older adults in China
Lin LI ; Feilong CHEN ; Xiaoyan LI ; Yiyuan GAO ; Silin ZHU ; Xiyezi DIAO ; Ning WANG ; Tao XU
Chinese Journal of Geriatrics 2023;42(6):726-732
Objective:To construct and validate a predictive model of fecal/urinary incontinence among older adults in China.Methods:Data was obtained from the Seventh Chinese Longitudinal Healthy Longevity Survey in 2018.In the questionnaire, "Are you able to control your bowel and urine" , was regarded as the main effect indicator.Receiver operating curves(ROC)were used to find the best cut-off values of calf circumference for predicting fecal/urinary incontinence, and univariate Logistic model method was used to explore the potential factors associated with fecal/urinary incontinence among community-living older adults in China.A random sampling method was used to extract 70% of the survey data as the training set, and the remaining 30% of the survey data as the test set.A multivariate Logistic regression analysis was conducted in the training set to build a prediction model that encompassed all predictors, and a nomogram was plotted.Results:Logistic regression analysis showed that age, small calf circumference(male <28.5 cm, female <26.5 cm), inability to walk 1 km continuously, inability to lift 5 kg items, inability to do three consecutive squats, limited daily activities, and a history of urinary system disorders, nervous system disorders, and cerebrovascular disorders were all risk factors for fecal/urinary incontinence for older adults in China.Female, better socioeconomic status, and normal body mass index were protective factors for fecal/urinary incontinence.The Logistic regression model for predicting fecal/urinary incontinence among Chinese older adults was constructed using the above twelve factors.The consistency index(C-index)value of the model was 0.907, indicating that the model had good predictive ability.The area under the ROC curve(AUC)of the overall sample, training set and test set were 0.906(95% CI: 0.896-0.917), 0.907(95 % CI: 0.894-0.921)and 0.910(95% CI: 0.892-0.928), respectively, indicating that the model had high prediction ability and good discrimination. Conclusions:Age, sex, calf circumference, ability to walk 1 km continuously, ability to lift 5 kg items, ability to do three consecutive squats, daily activities, history of urinary system disorders, nervous system disorders and cerebrovascular disorders, socioeconomic status, and body mass index were independent predictors for fecal/urinary incontinence among older adults in China.The nomogram based on the above indicators has a good predictive effect on fecal/urinary incontinence for older adults.