糖尿病已成为全球性的公共卫生问题。肥胖已被确定为糖尿病的危险因素。然而,目前尚不清楚哪些肥胖指标(BMI,WC,WhtR,ABSI,BRI,LAP,VAI)更适合监测糖尿病。因此,本研究的目的是比较这些指标与糖尿病之间的相关性,并揭示LAP与糖尿病之间的关系.
■15,252人参加了这项研究。对LAP进行定级分析,应用COX比例风险模型探讨LAP与新发糖尿病的关系。采用平滑曲线拟合研究LAP与糖尿病之间的非线性联系。最后,采用受试者工作特征(ROC)曲线评价上述指标对糖尿病的预测能力.
■调整混杂因素后,多元线性回归分析显示,每增加一个单位的LAP与患糖尿病风险增加76.8%相关(HR=1.768,95%CI:1.139~2.746,P=0.011).此外,LAP预测新发糖尿病优于其他指标,AUC最大[HR:0.713,95%CI:0.6806-0.7454,P<0.001,女性;HR:0.7922,95%CI:0.7396-0.8447;P<0.001,男性]。当LAP用作孤独预测因子时,其AUC面积是最大的男性和女性。然而,在添加经典预测因子(FPG,HbA1c,SBP,锻炼,年龄)到模型,LAP比ABSI更好,但在成对比较时,并不比其他指标好。
■高水平的LAP与糖尿病密切相关,是糖尿病的重要危险因素,尤其是女性,那些患有脂肪肝和目前吸烟者的人。当使用肥胖的单一指标筛查糖尿病易感性时,LAP优于其他指标,无论是男性还是女性。然而,当肥胖指标与经典预测因子一起添加到模型中时,与其他指标相比,LAP没有显示出明显的优势,除了ABSI。
Diabetes has become a global public health problem. Obesity has been established as a risk factor for diabetes. However, it remains unclear which of the obesity indicators (BMI, WC, WhtR, ABSI, BRI, LAP, VAI) is more appropriate for monitoring diabetes. Therefore, the objective of this investigation is to compare the strength of the association of these indicators and diabetes and reveal the relationship between LAP and diabetes.
15,252 people took part in this research. LAP was quartered and COX proportional risk model was applied to explore the relationship between LAP and new-onset diabetes. Smooth curve fitting was employed to investigate the non-linear link between LAP and diabetes mellitus. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the aforementioned indicators for diabetes.
After adjusting for confounding factors, multiple linear regression analysis showed that each unit increase in LAP was associated with a 76.8% increase in the risk of developing diabetes (HR=1.768, 95% CI: 1.139 to 2.746, P=0.011). In addition, LAP predicted new-onset diabetes better than other indicators, and the AUC was the largest [HR: 0.713, 95% CI: 0.6806-0.7454, P<0.001, in women; HR: 0.7922, 95% CI: 0.7396-0.8447; P<0.001, in men]. When LAP was used as a lone predictor, its AUC area was largest both men and women. However, after adding classical predictors (FPG, HbA1c, SBP, exercise, age) to the model, the LAP is better than the ABSI, but not better than the other indicators when compared in pairs.
High levels of LAP correlate very strongly with diabetes and are an important risk factor for diabetes, especially in women, those with fatty liver and current smokers. LAP was superior to other indicators when screening for diabetes susceptibility using a single indicator of obesity, both in men and in women. However, when obesity indicators were added to the model together with classical predictors, LAP did not show a significant advantage over other indicators, except ABSI.