Predicting muscular strength using demographics, skeletal dimensions, and body composition measures

Abstract

The purpose of this study was to develop an equation to predict strength for seven common resistance training exercises using anthropometric and demographic measures. One-hundred forty-seven healthy adults (74 males, 73 females, 35 ± 12 yr, 174 ± 10 cm, 88 ± 19 kg) volunteered to participate. Body composition values (regional/total) and body dimensions were assessed using dual-energy x-ray absorptiometry (DEXA). Subjects underwent the following maximal strength assessments: Leg Press, Chest Press, Leg Curl, Lat Pulldown, Leg Extension, Triceps Pushdown, and Biceps Curl. Multiple linear regression with stepwise removal was used to determine the best model to predict maximal strength for each exercise. Independent predictor variables identified (p < 0.05) were height (cm); weight (kg); BMI; age; sex (0 = F,1 = M); regional lean masses (LM,kg); fat mass (FM,kg); fat free mass (FFM,kg); percent fat (%BF); arm, leg, and trunk lengths (AL, LL, TL; cm); and shoulder width (SW,cm). Analyses were performed with and without regional measures to accommodate scenarios where DEXA is unavailable. All models presented were significant (p < 0.05, R² = 0.68-0.83), with regional models producing the greatest accuracy. Results indicate that maximal strength for individual resistance exercises can be reasonably estimated in adults.

Keywords

Strength training / Exercise testing / Regression equation / DEXA

Authors’ contributions

Sean T. Stanelle wrote the Primary manuscript, and reviewed literature. Sean T. Stanelle, Tyler R. Heimdal, Alexandra L. Remy and Bradley S. Lambert collected and analyzed the data. Stephen F. Crouse and Steven E. Riechman were responsible for the project, designed the study, and supported laboratory facility and equipment. Stephen F. Crouse, Tyler R. Heimdal and Bradley S. Lambert developed the manuscript. Sean T. Stanelle and Bradley S. Lambert generated the manuscript tables and figures. Bradley S. Lambert was the project director and responsible for statistics.

Funding

This research was funded in part by HydroWorx International (Middletown, PA), the Sydney and J. L. Huffines Institute for Sports Medicine and Human Performance (Texas A&M University, College Station, TX), and the National Strength and Conditioning Association (Colorado Springs, CO). Funding sources had no involvement in study design, data collection, data analysis, interpretation of data, manuscript development, or in the decision to submit the paper for publication.

Ethical approval statement

The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The procedures were approved by the institutional review board for research involving human subjects (IRB2008-039), and all volunteers signed a written informed consent prior to participating in the experimental procedures. The manuscript has not been published and is not under consideration for publication elsewhere.

Submission statement

The manuscript has not been published and is not under consideration for publication elsewhere.

Conflict of interest

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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The authors have no conflicts of interest to disclose. This research was funded in part by HydroWorx International (Middletown, PA), the Sydney and J. L. Huffines Institute for Sports Medicine and Human Performance (Texas A&M University, College Station, TX), and The National Strength and Conditioning Association (Colorado Springs, CO). Bradley Lambert, Ph.D (Corresponding Author), [e-mail].