Wang Zhi-Long, Li Jiming, Sun Chang-Hao, Yin Xin, Zhi Xiao-Yu, Liu Yi-Tian, Zheng Ying-Ying, Wu Ting-Ting, Xie Xiang
Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830054, P.R. China.
Center of Emergency and Trauma, The First Affiliated Hospital of Xinjiang Medical University, No137, Liyushan Road, Urumqi, 830011, China.
BMC Endocr Disord. 2025 Mar 26;25(1):80. doi: 10.1186/s12902-024-01807-x.
The issue of obesity is becoming more and more prominent. Understanding the metabolic profile of obese young adults and finding possible risk markers for early prediction and intervention is of great importance.
A total of 13,082 college students with an average age of 20 years were enrolled in this cross-sectional study. The lipid composition was measured and novel lipid profiles such as AIP, AI, LCI, Non-HDL-C, TC/HDL-C, LDL-C/HDL-C and TyG were calculated. Participants were then assessed as normal weight, overweight or obese based on their BMI. Pearson correlation analysis, multivariate logistic analysis, and predictive analysis were used to assess the association and discriminative power between lipid profile and obesity.
The prevalence of obesity with dyslipidemia was 61.0% in males and 38.7% in females. Most obese patients were associated with only one dyslipidemia component, with the highest proportion having low HDL-C. We found a positive correlation between all lipid profiles except HDL-C and BMI. Multivariate logistics regression shows, AIP were strongly associated with obesity, which shows the largest OR = 12.86, 95%CI (9.46,17.48).
In the youth population, higher AIP levels were positively and strongly associated with obesity. AIP may be a novel and better risk biomarker for predicting obesity.
肥胖问题日益突出。了解肥胖青年的代谢特征并寻找早期预测和干预的潜在风险标志物至关重要。
本横断面研究共纳入13082名平均年龄为20岁的大学生。测量脂质成分并计算新的脂质谱,如AIP、AI、LCI、非高密度脂蛋白胆固醇、总胆固醇/高密度脂蛋白胆固醇、低密度脂蛋白胆固醇/高密度脂蛋白胆固醇和TyG。然后根据参与者的BMI将其评估为正常体重、超重或肥胖。采用Pearson相关分析、多因素逻辑分析和预测分析来评估脂质谱与肥胖之间的关联和判别能力。
男性肥胖合并血脂异常的患病率为61.0%,女性为38.7%。大多数肥胖患者仅与一种血脂异常成分相关,其中比例最高的是高密度脂蛋白胆固醇降低。我们发现除高密度脂蛋白胆固醇外的所有脂质谱与BMI之间均呈正相关。多因素逻辑回归显示,AIP与肥胖密切相关,其显示最大比值比(OR)=12.86,95%置信区间(9.46,17.48)。
在青年人群中,较高的AIP水平与肥胖呈正相关且密切相关。AIP可能是一种用于预测肥胖的新型且更好的风险生物标志物。