Huang Chunxia, Ding Yining, Xu Shuling, Chen Rumeng, Jiang Ting, Zeng Bin, Bao Meihua, He Binsheng, Li Sen, Fu Qingming
School of Stomatology, Changsha Medical University, Changsha, China.
School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China.
Medicine (Baltimore). 2025 Mar 14;104(11):e41746. doi: 10.1097/MD.0000000000041746.
Although studies have indicated causality between brisk walking and various diseases, the relationships between walking pace and respiratory diseases lack thorough investigation. The underlying relationships between walking pace and various respiratory diseases were examined through univariable Mendelian randomization (MR) analyses. Furthermore, we performed multivariable MR analyses to observe whether relationships between walking pace and respiratory diseases change after adjustment of body mass index (BMI). The genome-wide association study data of self-reported walking pace, BMI, and 42 respiratory diseases were retrieved from publicly available datasets. We employed the inverse-variance weighted, weighted median, and MR-Egger methods for MR analysis. Using the inverse-variance weighted method in univariable MR, we identified statistically significant negative causal associations between self-reported walking pace and 4 respiratory traits, including chronic lower respiratory diseases (odds ratio [OR], 0.27 [95% confidence interval [CI], 0.18-0.41]), asthma (OR, 0.23 [95% CI, 0.14-0.38]), chronic obstructive pulmonary disease (OR, 0.15 [95% CI, 0.08-0.30]), and diseases of the respiratory system (OR, 0.54 [95% CI, 0.41-0.70]). Similar results were observed with the MR-Egger and weighted median methods. These associations remained significant, though slightly attenuated, after adjusting for BMI. A brisk walking pace may significantly benefit respiratory health and aid in disease prevention and risk stratification.
尽管研究表明快走与各种疾病之间存在因果关系,但步行速度与呼吸系统疾病之间的关系缺乏深入研究。通过单变量孟德尔随机化(MR)分析研究了步行速度与各种呼吸系统疾病之间的潜在关系。此外,我们进行了多变量MR分析,以观察在调整体重指数(BMI)后,步行速度与呼吸系统疾病之间的关系是否发生变化。从公开可用的数据集中检索了自我报告的步行速度、BMI和42种呼吸系统疾病的全基因组关联研究数据。我们采用逆方差加权、加权中位数和MR-Egger方法进行MR分析。在单变量MR中使用逆方差加权方法,我们发现自我报告的步行速度与4种呼吸特征之间存在统计学上显著的负因果关联,包括慢性下呼吸道疾病(优势比[OR],0.27[95%置信区间[CI],0.18-0.41])、哮喘(OR,0.23[95%CI,0.14-0.38])、慢性阻塞性肺疾病(OR,0.15[95%CI,0.08-0.30])和呼吸系统疾病(OR,0.54[95%CI,0.41-0.70])。MR-Egger和加权中位数方法也观察到了类似的结果。在调整BMI后,这些关联仍然显著,尽管略有减弱。快走速度可能对呼吸健康有显著益处,并有助于疾病预防和风险分层。