AUTHOR=Wen Jun , Shi Xiaowen , Liu Yan , Zhuang Rongjuan , Guo Shuliang , Chi Jing 

TITLE=Malnutrition mediates the association between handgrip status and asthma risk: an observational and prospective cohort study from multiple European countries

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1555888

DOI=10.3389/fnut.2025.1555888

ISSN=2296-861X

ABSTRACT=BackgroundEpidemiological investigations on the association of handgrip status and asthma risk still remain understudied. This research aims to investigate the associations of handgrip strength (HGS), relative handgrip strength (RHGS), low HGS, and asthma risk, as well as the mediating role of nutritional status, using data from the Survey of Health, Ageing and Retirement in Europe (SHARE).MethodThis investigation included 27,185 participants for a cross-sectional study and 18,047 participants for a prospective cohort study from SHARE. Four machine learning models, the Shapley Additive Explanations (SHAP) model, restricted cubic spline (RCS), cumulative occurrence curve, logistic regression, and Cox regression were used to comprehensively evaluate the performance of handgrip status in predicting asthma risk. Finally, the mediation effect model was employed to evaluate the role of nutritional status in the relationship between grip strength and asthma risk.ResultThe cross-sectional investigation suggested that both HGS (OR: 0.98, 95% CI: 0.98–0.99) and RHGS (OR: 0.61, 95% CI: 0.51–0.73) were negatively linked to the risk of asthma, and low HGS was a risk factor for asthma (OR: 1.52, 95% CI: 1.24–1.87). And the prospective cohort investigation with a median follow-up time of 30 months further confirmed that both HGS (HR: 0.98, 95% CI: 0.97–1.00) and RHGS (HR: 0.52, 95% CI: 0.37–0.73) were negatively linked to the risk of asthma. Among the four machine learning models used to evaluate handgrip status and the risk of asthma, eXtreme Gradient Boosting (XGBoost) showed better predictive performance. The SHAP model based on XGBoost suggested that the top five crucial indicators for predicting asthma risk were RHGS, HGS, country, age, and chronic lung disease. Finally, the mediation effect model suggested that malnutrition partially mediated the relationship between low HGS and increased risk of asthma, with a mediation proportion of 2.71%.ConclusionThis investigation suggested that lower HGS and RHGS were linked to a higher risk of asthma, and handgrip status could be used as an independent marker of asthma risk in European populations. And malnutrition partially mediated the relationship between low HGS and asthma risk. Improving muscle strength could be a potential preventive strategy against asthma, with implications for public health and clinical practice.