农村老年人口腔衰弱现状及风险预测模型的构建

    Current situation and risk prediction model of oral frailty among elderly people in rural areas

    • 摘要: 目的: 调查农村老年人口腔衰弱现状,并建立相应的风险预测模型。方法: 采用便利抽样的方法,2024年7—12月在安徽省蚌埠市选取595名农村老年人作为研究对象,并分为建模集445名和验证集150名,利用一般资料调查表、口腔衰弱指标筛查-8、衰弱量表、进食评估问卷、微型营养评估简表、简版老年抑郁量表、领悟社会支持量表、老年人口腔健康相关自我效能量表进行调查;利用单因素及多因素logistic回归分析,全面筛选影响因素,将筛选出的影响因素使用R软件“rms”程序包绘制动态列线图,通过ROC曲线和校准曲线评估该模型的预测性能。结果: 多因素分析确定年龄≥80岁(OR=3.804,95%CI: 1.275~7.459)、多重用药(OR=7.979,95%CI: 3.766~16.903)、口腔健康相关自我效能(OR=0.460,95%CI: 0.231~0.917)、吞咽功能障碍(OR=2.429,95%CI: 1.168~5.051)、佩戴义齿(OR=19.713,95%CI: 9.982~38.927)和有慢性病史(OR=1.928,95%CI: 1.081~3.441)等6个因素为独立影响因素。建模集的AUC为0.883,验证集的AUC为0.827,建模和验证集的校准曲线趋向于理想曲线,Hosmer-Lemeshow拟合优度结果(χ2=6.31,P=0.61)提示预测模型拟合良好。结论: 本研究所构建的风险预测模型具有良好的预测性能,可为基层医护人员早期预防口腔衰弱的发生及制定相应的措施提供理论依据。

       

      Abstract: Objective: To investigate the current situation of oral frailty in elderly people adults and to establish a corresponding risk prediction model. Methods: Using convenience sampling method, 595 rural elderly people were selected as study subjects in Bengbu City, Anhui Province, from July to December 2024, and divided into the modeling group(n=445) and the validation group(n=150), and were surveyed using the general information questionnaire, oral frailty index screen-8, FRAIL scale, eating assessment tool-10, mini-nutritional assessment short form, geriatric depression scale-5, perceived social support scale, and geriatric self-efficacy scale for oral health were used to conduct the survey.Single- and multivariate logistic regression was used to comprehensively screen the influencing factors, and the screened influencing factors were plotted in dynamic line graphs using the R software ′rms′ package, and the predicton performance of the model was evaluated by ROC curves and calibration curves. Results: Multivarinte analysis determined that age ≥80 years (OR=3.804, 95%CI: 1.275-7.459), polypharmacy (OR=7.979, 95%CI: 3.766-16.903), oral health-related self-efficacy (OR=0.460, 95%CI: 0.231-0.917), swallowing dysfunction (OR=2.429, 95%CI: 1.168-5.051), wearing denture (OR=19.713, 95%CI: 9.982-38.927), and having a history of chronic disease (OR=1.928, 95%CI: 1.081-3.441) were the six factors as independent influences.The AUC value was 0.883 for the modeling set and 0.827 for the validation set, the calibration curves for the modeling and validation sets converged to the ideal curve, and the Hosmer-Lemeshow goodness-of-fit results (χ2=6.31, P=0.61) suggested that the prediction model was well fitted. Conclusions: The risk prediction model constructed in this study has good prediction performance, which can provide a theoretical basis for primary healthcare workers to prevent the occurrence of oral frailty at an early stage and to develop corresponding measures.

       

    /

    返回文章
    返回