JOURNAL ARTICLE
Muscle moves mass: Deconstructing the culture of weight loss in American Olympic Weightlifting.
Published In: International Review for the Sociology of Sport, 2023, v. 58, n. 5. P. 765 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Nelson, Monica; Jette, Shannon 3 of 3
Abstract
This article examines the bodily discourses and weight management practices of American Olympic Weightlifters, a traditionally "non-lean" sport, to understand how athletes conceptualize the relationship between body composition and athletic performance. Based on interviews with sixteen competitive weightlifters, two dominant narratives emerged: "Mass Moves Mass," which accepts a wide range of body fat as functional for strength, and "Muscle Moves Mass," which rejects body fat and emphasizes muscle mass as the sole contributor to strength. Despite physiological evidence supporting the functional role of body fat in strength gain, most athletes adhered to the "Muscle Moves Mass" narrative, leading to a pervasive "culture of weight loss" characterized by chronic weight cutting and avoidance of weight gain, sometimes resulting in negative health outcomes such as Relative Energy Deficiency in Sport (RED-S). The study suggests that this preference for leanness may be influenced by broader dominant cultural discourses condemning body fat and calls for coaches to better address athletes' interpretations of bodily signals to mitigate disordered practices. It also highlights the need for further research on the intersections of sport-specific and dominant bodily discourses in shaping athlete health and performance in non-lean sports.
Additional Information
- Source:International Review for the Sociology of Sport. 2023/08, Vol. 58, Issue 5, p765
- Document Type:Article
- Subject Area:Sports and Leisure
- Publication Date:2023
- ISSN:1012-6902
- DOI:10.1177/10126902221120183
- Accession Number:164871475
- Copyright Statement:Copyright of International Review for the Sociology of Sport is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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