The association between different physical activity (PA) patterns and cardiometabolic index (CMI) in US adult population from NHANES (2007-2016)

Hao Xue; YuChi Zou; QianKun Yang; Zhao Zhang; Jie Zhang; XiaoYu Wei; JiangLing Zhou; Xiao Liang Tao; ChengMin Zhang; YiJu Xia; Fei Luo

doi:10.1016/j.heliyon.2024.e28792

The association between different physical activity (PA) patterns and cardiometabolic index (CMI) in US adult population from NHANES (2007-2016)

Heliyon. 2024 Mar 26;10(7):e28792. doi: 10.1016/j.heliyon.2024.e28792. eCollection 2024 Apr 15.

Authors

Hao Xue¹, YuChi Zou², QianKun Yang¹, Zhao Zhang³, Jie Zhang¹, XiaoYu Wei¹, JiangLing Zhou¹, Xiao Liang Tao¹, ChengMin Zhang¹, YiJu Xia⁴, Fei Luo¹

Affiliations

¹ National & Regional United Engineering Lab of Tissue Engineering, Department of Orthopedics, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
² Department of Spinal Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, Sichuan Province, China.
³ Orthopedics Department, The General Hospital of Western Theater Command PLA, Chengdu, 610083, Sichuan Province, China.
⁴ Department of Gastroenterology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.

Abstract

Background: Physical activity (PA) is widely recommended for preventing and combating obesity, but the most effective PA pattern for treating obesity remains unclear. Cardiometabolic index (CMI), derived from waist height ratio and triglycerides to high-density lipoprotein-cholesterol ratio, is a novel indicator for evaluating obesity. However, the relationship between different PA patterns and CMI remains unelucidated.

Objective: This study aimed to explore the association between different PA patterns and CMI in U.S. adults.

Methods: Participants with complete information in CMI, PA patterns, and other covariates in the National Health and Nutrition Examination Survey database (2007-2016) were included in this study. Multivariate linear regression models were utilized to explore the relationship between PA patterns and CMI. Moreover, stratified analyses, interaction tests and restricted cubic spline (RCS) regression analysis were used to investigate the stability and nonlinearity of the association, respectively.

Results: A total of 16,442 adults were included in this study. After adjusting for all potential covariates, only the regularly active group was significantly associated with CMI reduction (β = -0.13, 95% CI: 0.19 to -0.07, P < 0.0001), while the weekend warriors group did not achieve equivalent CMI reduction (β = -0.09, 95% CI: 0.32 to 0.14, P = 0.4204). Subgroup analyses and interaction tests revealed that the CMI-PA association was more pronounced in the subgroup with age≤45 or >60, with higher education level, and who are current drinkers. Furthermore, RCS analysis indicated that total PA in a week was significantly, nonlinearly associated with CMI in non-inactive adults, and that a total of PA more than 330 min can reap favorable CMI reduction.

Conclusion: Being regularly active is associated with significant CMI reduction, while being weekend warriors and insufficiently active do not achieve equivalent benefits. For non-inactive individuals, engaging in PA for more than 330 min weekly helps to reduce CMI effectively.

Keywords: Cardiometabolic index; Obesity; Physical activity; Regularly active; Weekend warriors.