Systemic immunity-inflammation index and body mass index: A cross-sectional study
Abstract
Background and aim The Systemic Immunity-inflammation Index (SII) is an emerging metric for assessing an individual’s immunological and inflammatory condition. Studies examining the relationship between SII and body mass index (BMI) are limited. This study aims to clarify the correlation between SII and BMI. Methods The current study investigated the association between SII and BMI using data from the National Health and Nutrition Examination Survey (NHANES). Information on SII and BMI was obtained from laboratory and demographic data. The analytical approach included techniques such as linear univariate analysis, linear multivariate analysis, and subgroup analysis to explore the intricate relationship between SII and BMI comprehensively. Results A total of 1568 participants who met the inclusion criteria were included in the study; their average age was 53.6 ± 16.7 years, and they were 40.8% female and 59.2% male. Several baseline indicators showed statistically significant differences across SII groups. Curve fitting revealed an inverted L-shape, non-linear relationship between SII and BMI. Multivariate linear regression analysis revealed that adjusted β values were 1.7 (95% CI: 0.87–2.54, p < 0.001) for T3 and 0.46 (95% CI: −0.36–1.28, p = 0.271) for T2 in comparison to T1. Threshold analysis indicated that SII < 677.842 was associated with a BMI increase β of 0.005 (95% CI: 0.002–0.007, p < 0.001). The stratified analysis demonstrated the positive association between SII and BMI was not influenced by gender, diabetes, or smoking (all p > 0.05). Conclusions In summary, these findings reveal a robust association between SII and BMI within the examined American population.
Article Details
Authors (6)
Wei Guo
Chongheng Zhang
Fang Cao
Jiangsu Key Laborartory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Joint International Research Laboratory of Climate and Environment Change, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology
Xinxin Sun
Jian Li
Wenfeng Zhang