Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Clinical Trial
. 2005 Aug;20(7):685-92.
doi: 10.1016/j.clinbiomech.2005.03.003.

Prediction of back strength using anthropometric and strength measurements in healthy females

M Wang  1 , A B Leger, G A Dumas
Affiliations
Clinical Trial

Prediction of back strength using anthropometric and strength measurements in healthy females

M Wang et al. Clin Biomech (Bristol). 2005 Aug.

Abstract

Objectives: The purpose of this study was to develop a regression equation to predict back extensor maximal voluntary contraction (back strength) for females based on several anthropometric and strength measurements using a multiple regression technique.

Background: Back strength is an important parameter in low back pain studies. However, the measurement of back strength is problematic in certain populations such as low back pain patients and pregnant women.

Methods: Back strength was measured as both moment at L4/L5 and force. Ten anthropometric or strength measurements were chosen to develop the prediction equation. The data used for developing the models were from eighty non-pregnant female subjects, age 18-42 and with no history of back pain in the past year. Backwards stepwise analysis was performed in order to choose the best fit predictors. The predictive ability of each of the models was checked using the cross-validation technique on 20 other subjects.

Findings: Two prediction models were developed for moment and force, respectively. The models explained 46.9% and 48.2% of the variance in back strength. No multicollinearity problem was found. The validation study showed that the observed back strength was highly correlated with the predicted back strength.

Interpretation: Mass, height, trunk length, grip strength and quadriceps strength are the best predictors of back strength in this study. The models developed in this study can be used for both general female low back pain patients and the pregnancy population.

PubMed Disclaimer