医学
体质指数
调解
内科学
全国健康与营养检查调查
代谢综合征
促炎细胞因子
内分泌学
优势比
逻辑回归
炎症
调解人
肥胖
纵向研究
背景(考古学)
队列研究
脂肪组织
索引(排版)
生理学
食物频率问卷
质量指数
可能性
胆固醇
疾病
作者
Jiajun Sang,Kexin Zhang,Chengxia Kan,Xuan Li,Hongyan Qiu,Zhentao Guo,Xiaodong Sun
标识
DOI:10.1177/15578518261472829
摘要
Aims: Metabolic syndrome (MetS) is a growing public health burden driven by chronic low-grade inflammation and lipid metabolic dysregulation, with diet as a major modifiable determinant. Proinflammatory diets [assessed by the dietary inflammatory index (DII)] are linked to MetS risk, but the underlying metabolic pathways remain unclear. This study investigated the independent and joint associations of DII and the atherogenic index of plasma (AIP) with MetS and evaluated AIP’s mediating role across populations. Methods: We analyzed data from the National Health and Nutrition Examination Survey (NHANES) (2013–2020; n = 7971) and the China Health and Retirement Longitudinal Study (CHARLS) (2011; n = 9240). DII and AIP were calculated; their associations with MetS were assessed using multivariable logistic regression. Mediation analysis quantified AIP’s mediating effect, with subgroup analyses by body mass index (BMI), age, and sex. In CHARLS, a DII-Proxy was derived from standardized food expenditure and C-reactive protein data. Results: MetS prevalence in NHANES was 22.3%. In both cohorts, higher AIP was strongly associated with MetS. In NHANES, each 1-standard deviation increase in AIP corresponded to markedly higher MetS odds (odds ratio = 10.9, P < 0.001). After adjustment, the direct DII–MetS association weakened, but mediation analyses showed a significant indirect effect via AIP. In CHARLS, AIP mediated 62.9% of the association between DII-Proxy and MetS. Dose–response analyses revealed a nonlinear relationship between DII and MetS and an S-shaped association between AIP and MetS. Stronger mediation effects were observed in females and individuals with normal BMI. Conclusions: AIP is a key mediator linking proinflammatory diets to MetS, supporting the diet–inflammation–lipid axis and identifying targets for precision prevention.
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