Tian Xiubiao, Liu Yan, Han Ying, Shi Jieli, Zhu Tiehong
Department of Endocrinology, Tianjin Medical University General Hospital, Tianjin, China (mainland).
Department of Geriatrics, Henghe Hospital, Beijing, China (mainland).
Med Sci Monit. 2017 Jun 11;23:2833-2841. doi: 10.12659/msm.904449.
BACKGROUND Dysglycemia (pre-diabetes or diabetes) in young adults has increased rapidly. However, the risk scores for detecting dysglycemia in oil field staff and workers in China are limited. This study developed a risk score for the early identification of dysglycemia based on epidemiological and health examination data in an oil field working-age population with increased risk of diabetes. MATERIAL AND METHODS Multivariable logistic regression was used to develop the risk score model in a population-based, cross-sectional study. All subjects completed the questionnaires and underwent physical examination and oral glucose tolerance tests. The performance of the risk score models was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS The study population consisted of 1995 participants, 20-64 years old (49.4% males), with undiagnosed diabetes or pre-diabetes who underwent periodic health examinations from March 2014 to June 2015 in Dagang oil field, Tianjin, China. Age, sex, body mass index, history of high blood glucose, smoking, triglyceride, and fasting plasma glucose (FPG) constituted the Dagang dysglycemia risk score (Dagang DRS) model. The performance of Dagang DRS was superior to m-FINDRISC (AUC: 0.791; 95% confidence interval (CI), 0.773-0.809 vs. 0.633; 95% CI, 0.611-0.654). At the cut-off value of 5.6 mmol/L, the Dagang DRS (AUC: 0.616; 95% CI, 0.592-0.641) was better than the FPG value alone (AUC: 0.571; 95% CI, 0.546-0.596) in participants with FPG <6.1 mmol/L (n=1545, P=0.028). CONCLUSIONS Dagang DRS is a valuable tool for detecting dysglycemia, especially when FPG <6.1 mmol/L, in oil field workers in China.
年轻成年人中的血糖异常（糖尿病前期或糖尿病）迅速增加。然而，在中国油田工作人员中检测血糖异常的风险评分有限。本研究基于糖尿病风险增加的油田工作年龄人群的流行病学和健康检查数据，开发了一种用于早期识别血糖异常的风险评分。
在一项基于人群的横断面研究中，采用多变量逻辑回归建立风险评分模型。所有受试者均完成问卷调查，并接受体格检查和口服葡萄糖耐量试验。使用受试者工作特征曲线下面积（AUC）评估风险评分模型的性能。
研究人群包括1995名年龄在20 - 64岁之间（男性占49.4%）的参与者，他们在2014年3月至2015年6月期间在中国天津大港油田接受定期健康检查，患有未诊断的糖尿病或糖尿病前期。年龄、性别、体重指数、高血糖病史、吸烟、甘油三酯和空腹血糖（FPG）构成了大港血糖异常风险评分（Dagang DRS）模型。Dagang DRS的性能优于m - FINDRISC（AUC：0.791；95%置信区间（CI），0.773 - 0.809对比0.633；95% CI，0.611 - 0.654）。在FPG <6.1 mmol/L的参与者中（n = 1545，P = 0.028），当临界值为5.6 mmol/L时，Dagang DRS（AUC：0.616；95% CI，0.592 - 0.641）比单独的FPG值（AUC：0.571；95% CI，0.546 - 0.596）更好。
Dagang DRS是检测中国油田工人血糖异常的有价值工具，尤其是当FPG <6.1 mmol/L时。
