Table_1_Systematic analysis between inflammation-related index and sex hormones in American adults: cross-sectional research based NHANES 2013-2016.docx

BackgroundA series of novel inflammation-related indexes has been confirmed to be efficient indicators of human immune and inflammatory status, with great potential as predictors for a variety of diseases. However, the association between inflammation-related indexes and sex hormones in the general population remained uncertain.MethodsWe incorporated data from the NHANES 2013-2016 survey of American adults. On the basis of distribution and comparison analysis, we chose to undertake separate analyses of men and women (including premenopausal and postmenopausal groups). Multivariable weighted linear regression models, eXtreme Gradient Boosting (XGBoost) models, generalized linear analysis, stratified models, logistic regression models and sensitivity analysis were utilized to assess the relationships between inflammation-related indexes and sex hormones.ResultsTotal 9372 participants out of 20146 were fitted into our research. We conducted separate gender analysis due to different distribution. Multivariable weighted linear regression indicated every component of the inflammation-related index was negatively correlated with at least one component of the male hormone indexes. However, SII, NLR, PPN, and NC were associated positively with female estradiol. XGBoost identify SII, PLR and NLR were the critical indexes on sex hormones. Inflammation-related indexes was associated with Testosterone deficiency in male and postmenstrual group and associated with Excessive Estradiol in premenstrual group. Finally, the subgroup analysis revealed that the association between sex hormones and inflammatory indicators was prominent in American adults over the age of 60 or those with BMI (>28 kg/m2).ConclusionIn all, inflammation-related indexes act as independent risks associated with sex hormone alterations and metabolic disorder in both genders. Using multiple models, we revealed the relative importance of inflammation-related indexes. Subgroup analysis also identified the high-risk population. More prospective and experimental research should be conducted to validate the results.

背景：一系列新颖的炎症相关指数已被证实为评估人类免疫和炎症状态的高效指标，并在预测多种疾病方面具有巨大潜力。然而，炎症相关指数与普通人群中性别激素之间的关系尚未明确。方法：本研究纳入了2013-2016年美国成年人NHANES调查数据。基于分布和比较分析，我们决定对男性和女性（包括绝经前和绝经后群体）进行单独分析。通过多变量加权线性回归模型、XGBoost模型、广义线性分析、分层模型、逻辑回归模型和敏感性分析等方法，评估炎症相关指数与性别激素之间的关系。结果：在20146名参与者中，共有9372人纳入本研究。由于性别分布差异，我们进行了单独的性别分析。多变量加权线性回归表明，炎症相关指数的每个组成部分均与男性激素指数的至少一个组成部分呈负相关。然而，SII、NLR、PPN和NC与女性雌二醇呈正相关。XGBoost模型确定了SII、PLR和NLR是影响性别激素的关键指标。炎症相关指数与男性及月经后组的睾酮缺乏相关，并与月经前组的雌二醇过量相关。最终，亚组分析显示，在美国60岁以上成年人或BMI（>28 kg/m2）的人群中，性别激素与炎症指标之间的关联性尤为显著。结论：总的来说，炎症相关指数作为与性别激素变化和代谢紊乱相关的独立风险因素，存在于两性之中。通过多种模型，我们揭示了炎症相关指数的相对重要性。亚组分析还确定了高风险人群。为了验证研究结果，应开展更多前瞻性和实验性研究。