Evidence map›Paper›PMID 35127283›Full record

ArticlePeerJ2022

The performance of body mass component indices in detecting risk of musculoskeletal injuries in physically active young men and women.

Jarosław Domaradzki, Dawid Koźlenia

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 20 citations in OpenAlex.

  1. Frequency, Severity and Ergonomic Awareness of Work-Related Musculoskeletal Disorders Among Australian Optometrists: A Cross-Sectional Survey.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026
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  11. Where Muscle Matters: How Regional Differences, Pain, and Gender Define Gamer Health.International journal of environmental research and public health · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jarosław DomaradzkiPhysical Education and Sport, Wroclaw University of Health and Sport Sciences, Wroclaw, Dolnośląskie, Poland.ORCID 0000-0001-8057-3033
Dawid KoźleniaPhysical Education and Sport, Wroclaw University of Health and Sport Sciences, Wroclaw, Dolnośląskie, Poland.
Wroclaw University of Health and Sport Sciences · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBody composition indices can be related to musculoskeletal injuries (MI), particularly in physically active groups. However, little is known about the accuracy of these diagnoses as potential predictors of musculoskeletal injuries. Therefore, this study aims to indicate the cut-off points of relative body mass (BMI), fat mass index (FMI), skeletal muscle mass (SMI), and muscle to fat ratio (MFR) and establish its reliability in injury prediction for physically active men and women.

methodsThe sample included 119 physically active individuals aged 23.72 ± 1.12 (66 men body height 1.79 ± 0.07 (m); body weight 80.51 ± 9.85 (kg) and 53 women body height 1.67 ± 0.08 (m); body weight 62 ± 10.72 (kg)), students at university of physical education in Poland. The participants' physical activity was measured with the International Physical Activity Questionnaire (IPAQ). The relevance of body mass index (BMI), fat mass index (FMI), skeletal muscle mass index (SMI), and muscle to fat ratio (MFR) in detecting injury risk was examined. Musculoskeletal injuries during 1 year before examination were registered using a self-reporting questionnaire. The areas under the curve (AUC) and Youden Index in the receiver operating characteristic curve (ROC) were calculated.

resultsThe cut-off points used to classify the indices among men were BMI = 24.38; FMI = 3.74; SMI = 16.40; MFR = 3.70; and for women BMI = 20.90; FMI = 4.17; SMI = 8.96; MFR = 1.67. Results suggested the greatest reliability in the prediction of musculoskeletal injuries among men had BMI (AUC = 0.623; Youden = 0.30) and SMI (AUC = 0.608; Youden = 0.23) whereas among women, MFR (AUC = 0.628; Youden = 0.29) and FMI (AUC = 0.614; Youden = 0.32).

conclusionBMI and SMI are the most appropriate indices to predict the risk of musculoskeletal injury in physically active men, whereas in women, MFR and FMI are more reliable. These results indicate that the indices with more muscle mass meaning are better in predicting injury among men. In contrast, indices with a higher contribution of fat are better for women. It indicates sex differentiation of injury risk conditions. Men should focus on developing muscle mass, whereas women should reduce body fat to decrease injury risk. However, widespread use seemed to be limited to the specific examined group. Therefore, cut-off points should be used with caution, and calculated values should be verified and confirmed in subsequent studies.

Indexed as

Body CompositionMusculoskeletal DiseasesAdipose TissueBody Mass IndexBody WeightFemaleHumansMaleReproducibility of ResultsBody composition indicesBody mass index (BMI)Fat mass index (FMI)Muscle to body fat ratio (MFR)Musculoskeletal injuriesPhysical activityRelative muscle mass (SMI)Young adults

Identifiers

PMID35127283
PMCPMC8800385
OpenAlexW4210813530

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.