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Hand grip strength should be normalized by weight not height for eliminating the influence of individual differences: Findings from a cross-sectional study of 1,511 healthy undergraduates

BACKGROUND: Hand grip strength (HGS) is a fast, useful, and inexpensive outcome predictor of nutritional status and muscular function assessment. Numerous demographic and anthropometric factors were reported to be associated with HGS, while which one or several factors produce greater variations in...

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Detalles Bibliográficos
Autores principales: Xu, Taojin, Li, Xu, Wang, Dingfang, Zhang, Yi, Zhang, Qinghua, Yan, Jianyin, Jiang, Junhao, Liu, Wenbin, Chen, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9890066/
https://www.ncbi.nlm.nih.gov/pubmed/36741997
http://dx.doi.org/10.3389/fnut.2022.1063939
Descripción
Sumario:BACKGROUND: Hand grip strength (HGS) is a fast, useful, and inexpensive outcome predictor of nutritional status and muscular function assessment. Numerous demographic and anthropometric factors were reported to be associated with HGS, while which one or several factors produce greater variations in HGS has not been discussed in detail. This is important for answering how should HGS be normalized for eliminating the influence of individual differences in clinical practice. AIMS: To compare the contribution of age, sex, height, weight, and forearm circumference (FCF) to variations in HGS based on a large-scale sample. METHODS: We enrolled 1,511 healthy undergraduate students aged 18–23 years. Age, weight, height, and sex were obtained. HGS was measured using a digital hand dynamometer, and FCF was measured at the point of greatest circumference using a soft ruler in both hands. Pearson’s or Spearman’s correlation coefficients were calculated with data of women and men separated and mixed for comparison. Partial correlation analysis and multivariate linear regression were used to compare the effect of variables on HGS. RESULTS: Analysis results confirmed the correlates of higher HGS include higher height, heavier weight, being men and dominant hand, and larger FCF. The correlation between HGS and FCF was the highest, and the bivariate correlation coefficient between weight and HGS was largerata of women and men were mixed, than that between height and HGS. When data of women and men were mixed, there were moderate correlations between HGS and height and weight (r = 0.633∼0.682). However, when data were separated, there were weak correlations (r = 0.246∼0.391). Notably, partial correlation analysis revealed no significant correlation between height and HGS after eliminating the weight effect, while the correlation between weight and HGS was still significant after eliminating the height effect. Multivariate linear regression analyses revealed sex was the most significant contributor to the variation in HGS (Beta = –0.541 and –0.527), followed by weight (Beta = 0.243 and 0.261) and height (Beta = 0.102 and 0.103). CONCLUSION: HGS and FCF reference values of healthy college students were provided. Weight was more correlate with hand grip strength, at least among the healthy undergraduates. CLINICAL TRIAL REGISTRATION: http://www.chictr.org.cn/showproj.aspx?proj=165914, identifier ChiCTR2200058586.