A prediction model for stroke risk among middle-aged and elderly populations
CHU Chu1, XU Hong2, CAI Bo1, HAN Yingying1, MU Haixiang3, ZHENG Huiyan3, LIN Ling1
1. Nantong Center for Disease Control and Prevention, Nantong, Jiangsu 226001, China; 2. Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210000, China; 3. Chongchuan District Center for Disease Control and Prevention, Nantong, Jiangsu 226001, China
Abstract：Objective To create a prediction model for stroke risk among middle-aged and elderly populations, so as to provide a basis for early identification of high-risk population for stroke. Methods From October to December 2023, residents aged ≥45 years in Chongchuan District, Nantong City, Jiangsu Province were selected using a multi-stage stratified random sampling method. The demographic information, life behavior, and chronic disease data were collected through a questionnaire survey. The standardized prevalence of stroke was calculated using data from the seventh National Population Census. The subjects were randomly divided into the training set and the internal validation set according to the ratio of 8∶2. The basic demographic information, life behavior, and chronic diseases of residents aged ≥45 years in Rugao City were collected from July to August 2023 as the external validation set. Predictive factors were selected using multivariable logistic regression model, and a nomogram for stroke among residents aged ≥45 years was established. The prediction effect was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curve, and Hosmer-Lemeshow goodness of fit test. Results A total of 6 290 residents aged ≥45 years were included, including 2 975 males (47.30%) and 3 315 females (52.70%). The average age was (61.90±10.20) years. The prevalence of stroke was 3.80%, and the standardized prevalence was 3.36%. The multivariable logistic regression showed that age, smoking, hypertension, and hyperlipidemia were predictors of stroke risk among residents aged ≥45 years, and the prediction model was ln[p/(1-p)]=-4.619+0.046×age+0.383×smoking+0.887×hypertension+0.678×hyperlipidemia. The AUC values of the training set, internal validation set, and external validation set were 0.748, 0.755, and 0.738, respectively. The consistency indexes were 0.748, 0.755, and 0.738, respectively. The Hosmer-Lemeshow goodness of fit test showed a good fitting effect (P>0.05). Conclusion The prediction model based on age, smoking, hypertension, and hyperlipidemia has good discrimination and calibration, and can be used to predict the risk of stroke among middle-aged and elderly populations aged ≥45 years.
楚楚, 徐红, 蔡波, 韩颖颖, 穆海祥, 郑会燕, 林玲. 中老年人群脑卒中风险预测模型研究[J]. 预防医学, 2025, 37(7): 649-653.
CHU Chu, XU Hong, CAI Bo, HAN Yingying, MU Haixiang, ZHENG Huiyan, LIN Ling. A prediction model for stroke risk among middle-aged and elderly populations. Preventive Medicine, 2025, 37(7): 649-653.
[1] 李季,王梅,张丽丽,等.2015—2022年济宁市脑卒中发病趋势[J].预防医学,2024,36(11):984-987. LI J,WANG M,ZHANG L L,et al.Trend in incidence of stroke in Jining City from 2015 to 2022[J].China Prev Med J,2024,36(11):984-987.(in Chinese) [2] 《中国脑卒中防治报告2021》编写组.《中国脑卒中防治报告2021》概要[J].中国脑血管病杂志,2023,20(11):783-793. Report on Stroke Prevention Treatment in China Writing Group.Brief report on Stroke Prevention and Treatment in China,2021[J].Chin J Cerebrovasc Dis,2023,20(11):783-793.(in Chinese) [3] ZHOU M G,WANG H D,ZENG X Y,et al.Mortality,morbidity,and risk factors in China and its provinces,1990-2017:a systematic analysis for the global burden of disease study 2017[J].Lancet,2019,394(10204):1145-1158. [4] 耿侯跃,崔岚,覃玉,等.2017—2020年江苏省40岁及以上常住居民脑卒中检出情况及危险因素分析[J].现代预防医学,2023,50(21):3860-3865. GENG H Y,CUI L,QIN Y,et al.Analysis of stroke detection and risk factors among permanent residents aged 40 and above in Jiangsu Province from 2017 to 2020[J].Mod Prev Med,2023,50(21):3860-3865.(in Chinese) [5] 聂祖娇,郑聪毅,王馨,等.健康社会决定因素水平与脑卒中发病风险的关系——一项基于全国前瞻性队列的研究[J].中国循环杂志,2024,39(6):599-605. NIE Z J,ZHENG C Y,WANG X,et al.Relationship between social determinants of health and stroke:a national prospective cohort study[J].Chin Circ J,2024,39(6):599-605.(in Chinese) [6] 于宁,张梅,张笑,等.中国中老年居民高血压、糖尿病和血脂异常共病现状及影响因素研究[J].中华流行病学杂志,2023,44(2):196-204. YU N,ZHANG M,ZHANG X,et al.Study on the status and influencing factors of comorbidity of hypertension,diabetes,and dyslipidemia among middle-aged and elderly Chinese adults[J].Chin J Epidemiol,2023,44(2):196-204.(in Chinese) [7] HIRSHKOWITZ M,WHITON K,ALBERT S M,et al.National sleep foundation's updated sleep duration recommendations:final report[J].Sleep Health,2015,1(4):233-243. [8] 任露露,顾嘉昌,闵艺璇,等.2016—2023年宜兴市脑卒中发病趋势分析[J].预防医学,2025,37(5):498-502. REN L L,GU J C,MIN Y X,et al.Trend in incidence of stroke in Yixing City from 2016 to 2023[J].China Prev Med J,2025,37(5):498-502.(in Chinese) [9] 徐金燕,夏聪聪,杨红美.老年脑卒中肺部感染风险预测模型的建立及验证[J].实用老年医学,2024,38(5):452-455,460. XU J Y,XIA C C,YANG H M,et al.Establishment and validation of a Nomogram to predict the risk of pulmonary infection in elderly patients with stroke[J].Pract Geriatr,2024,38(5):452-455,460.(in Chinese) [10] 曹婉婷,胡秀兰,韩荣荣.2014—2023年临平区脑卒中疾病负担趋势[J].预防医学,2024,36(11):988-991,995. CAO W T,HU X L,HAN R R.Trend in disease burden of stroke in Linping District from 2014 to 2023[J].China Prev Med J,2024,36(11):988-991,995.(in Chinese) [11] 李瑾,侯候,王亚新,等.中国中老年人群脑卒中发病的影响因素探索及列线图模型构建[J].中国动脉硬化杂志,2024,32(10):865-871. LI J,HOU H,WANG Y X,et al.Exploring the influencing factors of stroke and construcing a nomogram prediction model in Chinese middle-aged and older population[J].Chin J Anterioscler,2024,32(10):865-871.(in Chinese) [12] SETYOPRANOTO I,BAYUANGGA H F,PANGGABEAN A S,et al.Prevalence of stroke and associated risk factors in Sleman District of Yogyakarta Special Region,Indonesia[J/OL].Stroke Res Treat,2019[2025-05-30].https://doi.org/10.1155/2019/2642458. [13] FAN F F,YUAN Z W,QIN X H,et al.Optimal systolic blood pressure levels for primary prevention of stroke in general hypertensive adults:findings from the CSPPT(China Stroke Primary Prevention Trial)[J].Hypertension,2017,69(4):697-704. [14] XU J,ZHANG X,JIN A,et al.Trends and risk factors associated with stroke recurrence in China,2007-2018[J/OL].JAMA Network Open,2022,5(6)[2025-05-30].https://doi.org/10.1001/jamanetworkopen.2022.16341. [15] KUMRAL E, EVYAPAN D, GÖKÇAY F, et al. Association of baseline dyslipidemia with stroke recurrence within five-years after ischemic stroke[J]. Int J Stroke,2014,9(Suppl.A100):119-126. [16] RUAN H,RAN X,LI S S,et al.Dyslipidemia versus obesity as predictors of ischemic stroke prognosis:a multi-center study in China[J/OL].Lipids Health Dis,2024,23(1)[2025-05-30].https://doi.org/10.1186/s12944-024-02061-9. [17] WANG C,DU Z,YE N,et al.Hyperlipidemia and hypertension have synergistic interaction on ischemic stroke:insights from a general population survey in China[J/OL].BMC Cardiovasc Disord,2022,22(1)[2025-05-30].https://doi.org/10.1186/s12872-022-02491-2.
