Department of Anesthesiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Department of Pharmacy, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, Shandong, China.
BMC Endocr Disord. 2024 Apr 17;24(1):48. doi: 10.1186/s12902-024-01579-4.
Type 2 diabetes mellitus (T2DM) is known to have obesity as a risk factor. Body mass index cannot distinguish between lean mass and fat mass. We aimed to examine the association between predicted fat mass, predicted lean mass, predicted percent fat and risk of T2DM in Japanese adults. We also explored whether these three new parameters could predict T2DM better than other obesity markers.
This present study is a secondary data analysis. The study enrolled 20,944 Japanese individuals who participated in the NAGALA medical assessment program between 2004 and 2015. 15,453 participants who are eligible and have complete information were included to our analysis. Through the use of Kaplan-Meier curve, restricted cubic spline and univariate and multivariate Cox regression analysis, the relationship between predicted fat mass, predicted lean mass, predicted percent fat and T2DM risk was examined. The area under the curve method was used to assess the differences between these markers of obesity.
A total of 373 cases of T2DM occurred over a median time of 5.4 years. In the male group, we found a U-shaped connection between predicted fat mass, predicted lean mass, and T2DM onset (p value, non-linearity < 0.05). A linear relationship was found between predicted percent fat and T2DM onset. The linear relationship was also found in the female group for predicted fat mass, and predicted percent fat. And for women, predicted lean mass was not an independent predictor. The area under the curve (AUC) for predicted fat mass, predicted lean mass, predicted percent fat in men was 0.673 (95%CI: 0.639 ~ 0.707), 0.598 (95%CI: 0.561 ~ 0.635), 0.715 (95%CI: 0.684 ~ 0.745), respectively. In males, WHtR was the strongest predictor (AUC 0.7151, 95%CI: 0.684 ~ 0.746), followed by predicted percent fat (AUC 0.7150, 95%CI: 0.684 ~ 0.745). In the females, WHtR was also the strongest predictor (AUC 0.758, 95%CI: 0.703 ~ 0.813), followed by body mass index (AUC 0.757, 95%CI: 0.704 ~ 0.811) and predicted percent fat (AUC 0.742, 95%CI: 0.687 ~ 0.798).
Predicted fat mass, predicted lean mass, predicted percent fat were strongly connected with an increased risk for developing T2DM in Japanese, particularly in males. WHtR and predicted percent fat had a slightly better discrimination than other common obesity indicators in males. In the females, predicted fat mass and predicted percent fat were associated with T2DM risk, WHtR and body mass index had the slightly higher predictive power.
2 型糖尿病(T2DM)已知肥胖是其危险因素。体重指数不能区分瘦体重和脂肪量。我们旨在研究预测脂肪量、预测瘦体重、预测体脂百分比与日本成年人 T2DM 风险之间的关系。我们还探讨了这三个新参数是否比其他肥胖标志物能更好地预测 T2DM。
本研究为二次数据分析。研究纳入了 20944 名 2004 年至 2015 年参加 NAGALA 医学评估计划的日本成年人。纳入了 15453 名符合条件且信息完整的参与者进行分析。通过 Kaplan-Meier 曲线、限制立方样条以及单变量和多变量 Cox 回归分析,研究了预测脂肪量、预测瘦体重、预测体脂百分比与 T2DM 风险之间的关系。曲线下面积(AUC)法用于评估这些肥胖标志物之间的差异。
在中位时间为 5.4 年的随访期间,共发生了 373 例 T2DM。在男性组中,我们发现预测脂肪量、预测瘦体重与 T2DM 发病之间呈 U 型关联(p 值,非线性<0.05)。预测体脂百分比与 T2DM 发病之间呈线性关系。在女性组中也发现了预测脂肪量和预测体脂百分比与 T2DM 发病之间的线性关系。对于女性,预测瘦体重不是独立的预测因子。男性组中预测脂肪量、预测瘦体重、预测体脂百分比的 AUC 分别为 0.673(95%CI:0.6390.707)、0.598(95%CI:0.5610.635)和 0.715(95%CI:0.6840.745)。在男性中,WHtR 是最强的预测因子(AUC 0.7151,95%CI:0.6840.746),其次是预测体脂百分比(AUC 0.7150,95%CI:0.6840.745)。在女性中,WHtR 也是最强的预测因子(AUC 0.758,95%CI:0.7030.813),其次是体重指数(AUC 0.757,95%CI:0.7040.811)和预测体脂百分比(AUC 0.742,95%CI:0.6870.798)。
预测脂肪量、预测瘦体重、预测体脂百分比与日本成年人发生 T2DM 的风险增加密切相关,尤其是在男性中。WHtR 和预测体脂百分比在男性中比其他常见肥胖标志物具有稍好的判别能力。在女性中,预测脂肪量和预测体脂百分比与 T2DM 风险相关,WHtR 和体重指数具有稍高的预测能力。