Nonlinear relationship between atherogenic index of plasma and the risk of prediabetes: a retrospective study based on Chinese adults

被引:29
|
作者
Zheng, Xiaodan [1 ]
Zhang, Xin [2 ]
Han, Yong [3 ,5 ]
Hu, Haofei [4 ,6 ]
Cao, Changchun [2 ]
机构
[1] Fourth Peoples Hosp Shenzhen, Shenzhen Samii Med Ctr, Dept Neurol, Shenzhen 518000, Guangdong, Peoples R China
[2] Shenzhen Dapeng New Dist Nanao Peoples Hosp, Dept Rehabil, 6 Renmin Rd, Shenzhen 518000, Guangdong, Peoples R China
[3] Shenzhen Univ, Shenzhen Peoples Hosp 2, Affiliated Hosp 1, Dept Emergency, Shenzhen 518000, Guangdong, Peoples R China
[4] Shenzhen Univ, Shenzhen Peoples Hosp 2, Affiliated Hosp 1, Dept Nephrol, Shenzhen 518000, Guangdong, Peoples R China
[5] Shenzhen Univ, Shenzhen Peoples Hosp 2, Affiliated Hosp 1, Dept Emergency, 3002 Sungang West Rd, Shenzhen 518000, Guangdong, Peoples R China
[6] Shenzhen Univ, Shenzhen Peoples Hosp 2, Affiliated Hosp 1, Dept Nephrol, 3002 Sungang West Rd, Shenzhen 518000, Guangdong, Peoples R China
关键词
Atherogenic index of plasma; Prediabetes; Non-linearity; CHOLESTEROL; PATHOPHYSIOLOGY; INTERVENTIONS; GLUCAGON;
D O I
10.1186/s12933-023-01934-0
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BackgroundThe atherogenic index of plasma (AIP) can reflect the burden of atherosclerosis. Hyperglycemia is one of the leading causes of atherosclerosis. However, the relationship between AIP and prediabetes is rarely studied. Therefore, we aimed to explore the relationship between AIP and prediabetes.MethodsThis retrospective cohort study recruited 100,069 Chinese adults at the Rich Healthcare Group from 2010 to 2016. AIP was calculated according to Log10 (triglyceride/high-density lipoprotein cholesterol) formula. Cox regression method, sensitivity analyses and subgroup analyses were used to examine the relationship between AIP and prediabetes. Cox proportional hazards regression with cubic spline functions and smooth curve fitting was performed to explore the non-linearity between AIP and prediabetes. The two-piece Cox proportional hazards regression model was used to determine the inflection point of AIP on the risk of prediabetes.ResultsAfter adjusting for confounding covariates, AIP was positively associated with prediabetes (HR: 1.41, 95%CI: 1.31-1.52, P < 0.0001). The two-piecewise Cox proportional hazards regression model discovered that the AIP's inflection point was 0.03 (P for log-likelihood ratio test < 0.001). AIP was positively associated with the risk of prediabetes when AIP & LE; 0.03 (HR: 1.90, 95%CI: 1.66-2.16, P < 0.0001). In contrast, When AIP > 0.03, their association was not significant (HR: 1.04, 95%CI: 0.91-1.19, P = 0.5528).ConclusionThis study shows that AIP was positively and non-linearly associated with the risk of prediabetes after adjusting for other confounding factors. When AIP & LE; 0.03, AIP was positively associated with the risk of prediabetes.
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页数:11
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