Zhang Jian, Wang Jiating, Huang Fang, Campos Vanessa Caroline, Huang Hao, Rytz Andreas, Li Yumeng, Hu Wei, Darimont Christian, Yu Kai, Chen Yu-Ming
Nestlé Institute of Health Sciences, Nestlé Research, Beijing, China.
Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.
PLoS One. 2025 Jul 7;20(7):e0326914. doi: 10.1371/journal.pone.0326914. eCollection 2025.
China has the largest population with diabetes globally, with over half of the cases going undiagnosed, highlighting the need for improved screening efforts. This study aimed to adapt the Finnish Diabetes Risk Score (FINDRSC), a widely used tool for assessing diabetes risk without relying on clinical indicators, for screening undiagnosed hyperglycemia and diabetes among Chinese adults.
Data from the China Health and Nutrition Survey (CHNS), collected in the 2009 wave, were utilized as the training data (n = 7277), and data from the Guangzhou Nutrition and Health Study (GNHS, n = 2970), conducted in the years 2011-2014, were used for validation. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L and/or glycated hemoglobin A1c (HbA1c) ≥ 6.5%. Hyperglycemia was defined as FPG ≥ 5.6 mmol/L and/or HbA1c ≥ 5.7%. Predictors in the original FINDRISC model were adjusted according to local standards and guidelines to develop the Modified Chinese screening model (ModChinese). Coefficients and scores of the ModChinese model were estimated using logistic regression. Area under the receiver operating characteristic curve (AUC) was calculated to evaluate model performance.
The prevalence of undiagnosed diabetes and prediabetes was 8.6% and 40.1% in CHNS, and 3.1% and 27.9% in GNHS, respectively. The ModChinese demonstrated superior performance compared to the original FINDRISC, with higher AUC values for detecting both diabetes (0.707 vs. 0.681, p = 0.001) and hyperglycemia (0.680 vs. 0.661, p < 0.001) in the CHNS. Similar improvements were observed in the GNHS, where the ModChinese achieved AUC values of 0.663 for diabetes and 0.606 for hyperglycemia, compared to FINDRISC's 0.622 and 0.593, respectively. Compared with the original FINDRISC, the ModChinese model showed improved sensitivity and specificity for screening undiagnosed diabetes and enhanced sensitivity for hyperglycemia screening in both training and validation datasets.
The ModChinese model is a simple and effective screening tool for identifying undiagnosed diabetes and hyperglycemia in Chinese adults.
中国是全球糖尿病患者人数最多的国家，超过半数的病例未被诊断出来，这凸显了加强筛查工作的必要性。本研究旨在调整芬兰糖尿病风险评分（FINDRSC），这是一种广泛用于评估糖尿病风险且不依赖临床指标的工具，用于筛查中国成年人中未被诊断出的高血糖和糖尿病。
将2009年中国健康与营养调查（CHNS）收集的数据用作训练数据（n = 7277），并将2011 - 2014年进行的广州营养与健康研究（GNHS，n = 2970）的数据用于验证。糖尿病定义为空腹血糖（FPG）≥7.0 mmol/L和/或糖化血红蛋白A1c（HbA1c）≥6.5%。高血糖定义为FPG≥5.6 mmol/L和/或HbA1c≥5.7%。根据当地标准和指南对原始FINDRSC模型中的预测因素进行调整，以开发改良的中国筛查模型（ModChinese）。使用逻辑回归估计ModChinese模型的系数和分数。计算受试者工作特征曲线下面积（AUC）以评估模型性能。
在CHNS中，未被诊断出的糖尿病和糖尿病前期的患病率分别为8.6%和40.1%，在GNHS中分别为3.1%和27.9%。与原始FINDRSC相比，ModChinese表现出更优的性能，在CHNS中检测糖尿病（0.707对0.681，p = 0.001）和高血糖（0.680对0.661，p < 0.001）时具有更高的AUC值。在GNHS中也观察到了类似的改善，ModChinese在糖尿病检测中的AUC值为0.663，在高血糖检测中的AUC值为0.606，而FINDRISC分别为0.622和0.593。与原始FINDRSC相比，ModChinese模型在训练和验证数据集中对筛查未被诊断出的糖尿病表现出更高的敏感性和特异性，对高血糖筛查表现出更高的敏感性。
ModChinese模型是一种用于识别中国成年人中未被诊断出的糖尿病和高血糖的简单有效的筛查工具。
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