Liu Xin-Ying, Yao Kai
Endoscopy Center, Jinshan Hospital, Fudan University, Shanghai 201508, China.
Department of Neurology, Jinshan Hospital, Fudan University, Shanghai 201508, China.
Mediators Inflamm. 2025 Jun 24;2025:1989715. doi: 10.1155/mi/1989715. eCollection 2025.
The novel inflammatory biomarkers, including systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and neutrophil-to-lymphocyte ratio (NLR), can contribute to predicting the future risk of various diseases. However, the impact of different physical activity (PA) domains on systemic inflammation remains unclear. The study aims to investigate the relationship between domain-specific moderate-to-vigorous-intensity PA (MVPA) and these inflammatory biomarkers among US adults. Participants from the US National Health and Nutrition Examination Survey (NHANES) (2007-2018) were included in this study. The Global Physical Activity Questionnaire was used to assess self-reported MVPA. MVPA was categorized into three domains, including occupation-related MVPA (O-MVPA), transportation-related MVPA (T-MVPA), and leisure-time-related MVPA (LT-MVPA). SII, SIRI, and NLR were derived from the complete blood count results obtained at the NHANES Mobile Examination Centers (MEC). Weighted multivariable linear regression and propensity score matching (PSM) were used to examine the relationship between domain-specific MVPA and inflammatory biomarkers. Additionally, stratified and mediation analyses were performed to assess potential effect modifications and mediators in this association. The study included a total of 29,072 participants. Following PSM, weighted multivariable linear regression indicated a negative association between LT-MVPA meeting PA guidelines ( ≥ 150 min/week) and circulating inflammatory biomarkers ( = -36, 95% confidence interval [CI]: -47 to -25, < 0.001 for SII; = -0.09, 95% CI: -0.13 to -0.05, < 0.001 for SIRI; = -0.08, 95% CI: -0.11 to -0.05, < 0.001 for NLR, respectively), adjusting for all potential covariates in model 2. Participants engaging in sufficient T-MVPA (≥ 150 min/week) also exhibited lower SII and SIRI levels ( = -17, 95% CI: -32 to -2.4, =0.023; = -0.07, 95% CI: -0.11 to -0.03, =0.002). Conversely, O-MVPA showed no significant correlation with any inflammatory biomarkers (all > 0.05). No significant effect modification was observed in the association between LT-MVPA or T-MVPA and inflammatory biomarkers (SII, SIRI, and NLR). Mediation analysis showed that body mass index (BMI) mediated the relationships between these inflammatory biomarkers and both LT-MVPA and T-MVPA. The impact of different PA domains on systemic inflammation varies significantly. Given the well-established link between chronic inflammation and diseases such as cardiovascular disease (CVD), diabetes, and metabolic disorders, specific recommendations for PA categories should be provided, particularly targeting individuals with high systemic inflammatory responses.
包括全身免疫炎症指数（SII）、全身炎症反应指数（SIRI）和中性粒细胞与淋巴细胞比值（NLR）在内的新型炎症生物标志物有助于预测各种疾病的未来风险。然而，不同身体活动（PA）领域对全身炎症的影响仍不明确。本研究旨在调查美国成年人中特定领域的中等至剧烈强度PA（MVPA）与这些炎症生物标志物之间的关系。本研究纳入了美国国家健康与营养检查调查（NHANES）（2007 - 2018年）的参与者。使用全球身体活动问卷来评估自我报告的MVPA。MVPA被分为三个领域，包括职业相关MVPA（O - MVPA）、交通相关MVPA（T - MVPA）和休闲时间相关MVPA（LT - MVPA）。SII、SIRI和NLR来自于在NHANES移动检查中心（MEC）获得的全血细胞计数结果。采用加权多变量线性回归和倾向得分匹配（PSM）来检验特定领域MVPA与炎症生物标志物之间的关系。此外，进行了分层分析和中介分析，以评估该关联中的潜在效应修饰因素和中介因素。该研究共纳入了29,072名参与者。经过PSM后，加权多变量线性回归表明，达到PA指南（≥150分钟/周）的LT - MVPA与循环炎症生物标志物之间存在负相关（SII：β = -36，95%置信区间[CI]：-47至-25，P < 0.001；SIRI：β = -0.09，95% CI：-0.13至-0.05，P < 0.001；NLR：β = -0.08，95% CI：-0.11至-0.05，P < 0.001），在模型2中对所有潜在协变量进行了调整。进行足够T - MVPA（≥150分钟/周）的参与者也表现出较低的SII和SIRI水平（SII：β = -17，95% CI：-32至-2.4，P = 0.023；SIRI：β = -0.07，95% CI：-0.11至-0.03，P = 0.002）。相反，O - MVPA与任何炎症生物标志物均无显著相关性（所有P > 0.05）。在LT - MVPA或T - MVPA与炎症生物标志物（SII、SIRI和NLR）之间的关联中未观察到显著的效应修饰。中介分析表明，体重指数（BMI）介导了这些炎症生物标志物与LT - MVPA和T - MVPA之间的关系。不同PA领域对全身炎症的影响差异显著。鉴于慢性炎症与心血管疾病（CVD）、糖尿病和代谢紊乱等疾病之间已确立的联系，应提供针对PA类别的具体建议，特别是针对全身炎症反应高的个体。
