Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, P.R. China.
Sun Yat-sen Global Health Institute, Institute of State Governance, Sun Yat-sen University, Guangzhou, P.R. China.
BMC Public Health. 2024 Jul 26;24(1):1999. doi: 10.1186/s12889-024-19479-6.
As multimorbidity becomes common that imposes a considerable burden to patients, but the extent to which widely-used multimorbidity indexes can be applied to quantify disease burden using primary care data in China is not clear. We applied the Chinese Multimorbidity-Weighted Index (CMWI) to health check-ups data routinely collected among older adults by primary care, to examine its validity in measuring multimorbidity associated risks of disability and mortality in annual follow-ups.
The study utilized data from annual health check-ups of older adults, which included information on individual age, sex, and 14 health conditions at primary care in a district of Guangzhou, Guangdong, China. The risk of CMWI for mortality was analysed in a total sample of 45,009 persons 65 years and older between 2014 and 2020 (average 2.70-year follow-up), and the risk for disability was in a subsample of 18,320 older adults free of physical impairment in 2019 and followed-up in 2020. Risk of death and disability were assessed with Cox proportional hazard regression and binary logistic regression, respectively, with both models adjusted for age and sex variables. The model fit was assessed by the Akaike information criterion (AIC), and C-statistic or the area under the receiver operating characteristic curve (AUC).
One unit increase in baseline-CMWI (Median= 1.70, IQR: 1.30-3.00) was associated with higher risk in subsequent disability (OR = 1.12, 95%CI = 1.05,1.20) and mortality (OR = 1.18, 95%CI = 1.14, 1.22). Participants in the top tertile of CMWI had 99% and 152% increased risks of disability and mortality than their counterparts in the bottom tertile. Model fit was satisfied with adequate AUC (0.84) or C-statistic (0.76) for both outcomes.
CMWI, calculated based on primary care's routine health check-ups data, provides valid estimates of disability and mortality risks in older adults. This validated tool can be used to quantity and monitor older patients' health risks in primary care.
随着多种疾病的发病率不断增加,给患者带来了相当大的负担,但目前尚不清楚广泛使用的多种疾病指数在多大程度上可以应用于中国的初级保健数据来量化疾病负担。我们应用中国多重疾病加权指数(CMWI)对常规收集的老年人健康检查数据进行分析,以检验其在衡量年度随访中多种疾病相关残疾和死亡风险方面的有效性。
本研究利用了中国广东省广州市一个区的老年人年度健康检查数据,其中包括个人年龄、性别以及在初级保健机构中 14 种健康状况的信息。在年龄均为 65 岁及以上的 45009 名个体(平均随访 2.70 年)的总样本中,分析了 CMWI 对死亡率的风险,在 2019 年无身体损伤且在 2020 年进行随访的 18320 名老年人的亚样本中,分析了 CMWI 对残疾的风险。使用 Cox 比例风险回归和二项逻辑回归分别评估死亡和残疾风险,两个模型均调整了年龄和性别变量。通过赤池信息量准则(AIC)评估模型拟合情况,并使用 C 统计量或接受者操作特征曲线下面积(AUC)进行评估。
基线 CMWI(中位数=1.70,IQR:1.30-3.00)每增加一个单位,随后发生残疾(OR=1.12,95%CI=1.05,1.20)和死亡(OR=1.18,95%CI=1.14,1.22)的风险增加。CMWI 最高三分位的参与者发生残疾和死亡的风险比最低三分位的参与者分别增加 99%和 152%。两个结果的 AUC(0.84)或 C 统计量(0.76)均符合适度拟合标准。
基于初级保健常规健康检查数据计算的 CMWI 可以为老年人的残疾和死亡风险提供有效的估计。这种经过验证的工具可用于量化和监测初级保健中老年患者的健康风险。