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预测日本队列中的2型糖尿病发病情况:对NAGALA数据库的8年分析

Predicting incident type 2 diabetes in a Japanese cohort: an 8-year analysis of the NAGALA database.

作者信息

Wang Yangchun, Liu Fei, Tong Ruixiang, He Zhonghua, Fang Qin, Feng Jie, An Hongliang, Liu Junjun

机构信息

Department of Endocrinology, Nanjing Meishan Hospital, Nanjing, China.

Department of General Surgery, Nanjing Meishan Hospital, Nanjing, China.

出版信息

Front Endocrinol (Lausanne). 2025 May 15;16:1465032. doi: 10.3389/fendo.2025.1465032. eCollection 2025.

Abstract

OBJECTIVE

Using data from the NAGALA database, this retrospective cohort study set out to identify the predictive markers for incident Type 2 Diabetes Mellitus (T2DM), with a particular focus on the non-diabetic Japanese population.

METHODS

We examined the data from a cohort of 15,464 individuals (with a male representation of 54.5% and an average age of (43.71 ± 8.90 years) sourced from the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) research which was a longitudinal study at Medical Health Checkup Center of Murakami Memorial Hospital. The analysis focused on the incidence of T2DM from 2004 to 2012. Baseline demographic, anthropometric, biochemical, and lifestyle data were collected. All participants were not type 2 diabetic at baseline. The diagnosis of T2DM was confirmed by HbA1c >= 48mmol/mol, fasting plasma glucose >= 126mg/dL, or diabetes reported by oneself. Multivariate analysis was performed after univariate Cox regression analysis was used to find early determinants of T2DM incidence. The ability of individual components and a composite risk score to discriminate was assessed using Receiver Operating Characteristic (ROC) curves.

RESULTS

Over an average follow-up duration of 2207.82 ± 1379.73 days, 262 patients (1.7%) had the onset of T2DM. Following the removal of confounding variables we found that age (=1.03,95% 1.01∼1.04, =0.001), waist circumference(=1.05,95% 1.03∼1.06, <0.001), alanine transaminase(=1.01,95% 1.00∼1.01, =0.045), glycated hemoglobin (HbA1c) (=24.30,95% 15.69∼37.63,<0.001), fasting plasma glucose(=1.10,95% 1.07∼1.12, <0.001), the presence of fatty liver(=1.86,95% 1.37∼2.53, <0.001), current smoking(=1.61,95% 1.16∼2.23, =0.004), and heavy alcohol consumption(=1.79,95% 1.06∼2.99, =0.028) were identified as independent risk factors for T2DM(all < 0.05), while high-density lipoprotein cholesterol (HDL-C) exhibited a protective effect (0.98,95% 0.97∼1.000.010). The area under the Receiver Operating Characteristic (ROC) curve for individual factors ranged from 0.53 to 0.83, with the highest value for HbA1c. A combined risk model incorporating these factors including age, waist circumference, alanine transaminase, HbA1c, fasting plasma glucose, the presence of fatty liver, current smoking, heavy alcohol consumption, 1/HDL-C achieved an AUC of 0.90 (95% 0.88-0.92, < 0.001), signifying robust discriminatory ability. At a predictive probability threshold of >0.017, the model exhibited sensitivity and specificity of 0.863 and 0.828, respectively.

CONCLUSION

Current research has underscored the significance of a multifaceted approach to the prevention of T2DM, which includes early intervention targeting modifiable risk factors such as obesity, unhealthy alcohol use, and smoking, in conjunction with the monitoring of key metabolic markers like HbA1c and liver enzymes.

摘要

目的

本回顾性队列研究利用NAGALA数据库的数据,旨在确定2型糖尿病(T2DM)发病的预测标志物,特别关注非糖尿病日本人群。

方法

我们检查了来自NAGALA(岐阜地区纵向分析中的非酒精性脂肪性肝病)研究的15464名个体的数据(男性占54.5%,平均年龄为(43.71±8.90岁)),该研究是村上纪念医院体检中心的一项纵向研究。分析重点为2004年至2012年T2DM的发病率。收集了基线人口统计学、人体测量学、生化和生活方式数据。所有参与者在基线时均非2型糖尿病患者。T2DM的诊断通过糖化血红蛋白(HbA1c)≥48mmol/mol、空腹血糖≥126mg/dL或自我报告的糖尿病来确认。在单变量Cox回归分析用于寻找T2DM发病率的早期决定因素后,进行了多变量分析。使用受试者工作特征(ROC)曲线评估各个成分和综合风险评分的鉴别能力。

结果

在平均随访时间2207.82±1379.73天内,262例患者(1.7%)发生了T2DM。在去除混杂变量后,我们发现年龄(=1.03,95% 1.01~1.04,P=0.001)、腰围(=1.05,95% 1.03~1.06,P<0.001)、丙氨酸转氨酶(=1.01,95% 1.00~1.01,P=0.045)、糖化血红蛋白(HbA1c)(=24.30,95% 15.69~37.63,P<0.001)、空腹血糖(=1.10,95% 1.07~1.12,P<0.001)、脂肪肝的存在(=1.86,95% 1.37~2.53,P<0.001)、当前吸烟(=1.61,95% 1.16~2.23,P=0.004)和大量饮酒(=1.79,95% 1.06~2.99,P=0.028)被确定为T2DM的独立危险因素(所有P<0.05),而高密度脂蛋白胆固醇(HDL-C)表现出保护作用(0.98,95% 0.97~1.00,P=0.010)。各个因素的受试者工作特征(ROC)曲线下面积范围为0.53至0.83,其中HbA1c的值最高。包含年龄、腰围、丙氨酸转氨酶、HbA1c、空腹血糖、脂肪肝的存在、当前吸烟、大量饮酒、1/HDL-C等这些因素的综合风险模型的曲线下面积(AUC)为0.90(95% 0.88 - 0.92,P<0.001),表明具有强大的鉴别能力。在预测概率阈值>0.017时,该模型的敏感性和特异性分别为0.863和0.828。

结论

当前研究强调了多方面预防T2DM方法的重要性,这包括针对肥胖、不健康饮酒和吸烟等可改变的危险因素进行早期干预,同时监测HbA1c和肝酶等关键代谢标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b213/12119281/3e55e5503a07/fendo-16-1465032-g001.jpg

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