Objective To investigate the incidence of hip fracture among the elderly in communities,explore related influencing factors,and develop and validate a risk prediction model.Methods A stratified sampling method was used to collect sociodemographic data,lifestyles and risk factors in hip fracture between January 2023 and January 2024 among the elderly residents in communities in Deyang.With random splitting,479 elderly people(68.00%)were assigned to the model training set,and 221(32.00%)to the model validation set.In the model training set,the participants were divided into a fracture group and a non-fracture group based on hip fracture or not.Data from both groups were compared,and R software(version 4.3.1)was employed to develop and validate the risk prediction model.Results A total of 700 elderly residents in communities were included,62 of them had hip fracture within one year yielding a cumulative incidence rate of 8.86%.The risk prediction model identified six predictors:frequent consumption of preserved foods,daily exercise time,daily sunlight exposure,osteoporosis,times of fall within a year,and with≥20 pieces of natural teeth.In the training set,the model achieved an AUC of 0.945(95%CI:0.908-0.982),with a sensitivity of 88.89%and a specificity of 89.40%.The calibration curve demonstrated a good agreement between predicted and actual values,indicating a strong calibration.Decision curve analysis(DCA)showed a positive net benefit.In the validation set,the AUC was 0.892(95%CI:0.784-0.999),with a sensitivity of 82.35%and a specificity of 93.63%,confirming a good model fit and predictive performance.The calibration curve exhibited a strong consistency,and DCA indicated a positive net benefit.Conclusion The developed risk prediction model for hip fracture in elderly community residents demonstrates a strong predictive value.It provides a practical reference for community workers and healthcare professionals to screen and assess the risk of hip fracture among the elderly residents in communities.

Objective To investigate the incidence of hip fracture among the elderly in communities,explore related influencing factors,and develop and validate a risk prediction model.Methods A stratified sampling method was used to collect sociodemographic data,lifestyles and risk factors in hip fracture between January 2023 and January 2024 among the elderly residents in communities in Deyang.With random splitting,479 elderly people(68.00%)were assigned to the model training set,and 221(32.00%)to the model validation set.In the model training set,the participants were divided into a fracture group and a non-fracture group based on hip fracture or not.Data from both groups were compared,and R software(version 4.3.1)was employed to develop and validate the risk prediction model.Results A total of 700 elderly residents in communities were included,62 of them had hip fracture within one year yielding a cumulative incidence rate of 8.86%.The risk prediction model identified six predictors:frequent consumption of preserved foods,daily exercise time,daily sunlight exposure,osteoporosis,times of fall within a year,and with≥20 pieces of natural teeth.In the training set,the model achieved an AUC of 0.945(95%CI:0.908-0.982),with a sensitivity of 88.89%and a specificity of 89.40%.The calibration curve demonstrated a good agreement between predicted and actual values,indicating a strong calibration.Decision curve analysis(DCA)showed a positive net benefit.In the validation set,the AUC was 0.892(95%CI:0.784-0.999),with a sensitivity of 82.35%and a specificity of 93.63%,confirming a good model fit and predictive performance.The calibration curve exhibited a strong consistency,and DCA indicated a positive net benefit.Conclusion The developed risk prediction model for hip fracture in elderly community residents demonstrates a strong predictive value.It provides a practical reference for community workers and healthcare professionals to screen and assess the risk of hip fracture among the elderly residents in communities.