Body fat percentage (BF%) is probably the most evaluated body composition component in sports [
Several methods are available when evaluating BF% [
Conversely, anthropometry, one of the most popular field methods in assessing body composition, is used to estimate BF%, typically with regression equations obtained from other laboratory methods [
Therefore, the purpose of this study was to analyze the accuracy of several anthropometric equations that estimate BF% utilizing DXA as the reference method in professional male soccer players. Since there is a great amount of anthropometric equations [ Anthropometric equations developed in athletic populations (AT) Anthropometric equations developed in nonathletic populations (NAT).
This was a cross-sectional observational study. Participants were evaluated between the years 2009 and 2015 as part of their medical screening.
The sample consisted of 131 professional male soccer players (121 Mexicans, 9 South Americans, and 1 Spaniard) from the 2nd Professional Mexican Soccer League. Their age, body mass, and height ranged from 18 to 37 years, 53.3 to 93.6 kg, and 165.3 to 190.8 cm, respectively.
Participants attended our laboratory at 9:00 am, after a two-hour fasting. They were instructed to avoid any exercise prior to their evaluations. Each participant was evaluated by a whole body DXA scan and a complete anthropometric assessment, both done on the same day. Body fat percentage was estimated for each subject through 14 AT (Table
Analyzed anthropometric equations (developed in athletic populations).
Author | Equation |
---|---|
Forsyth 2SKF [ | BD = 1.103 − (0.00168 |
Forsyth 4SKF [ | BD = 1.10647 − (0.00162 |
Pascale [ | BD = 1.088468 − (0.007123 |
Thorland 3SKF [ | BD = 1.1136 − (0.00154 |
Thorland 7SKF [ | BD = 1.1091 − (0.00052 |
White [ | BD = 1.0958 − (0.00088 |
Withers [ | BD = 1.0988 − (0.0004 |
Zuti [ | BD = 1.0806 − (0.001187 |
Evans 3SKF [ | BF% = 8.997 + (0.24658 |
Evans 7SKF [ | BF% = 10.566 + (0.12077 |
Oliver [ | BF% = 3.53 + (0.132 |
Reilly [ | BF% = 5.174 + (0.124 |
Civar [ | BF% = (0.432 |
Stewart [ | BFM = (331.5 |
BF%: body fat percentage; Ab: abdomen skinfold; Ax: axilla skinfold; B: biceps skinfold; BD: body density; BFM: body fat mass (g); BM: body mass (kg); Ca: calf skinfold; Ch: chest skinfold; IC: iliac crest skinfold; Sb: subscapular skinfold; SKF: skinfolds; Sp: supraspinal skinfold; T: triceps skinfold; Th: thigh skinfold; WC: waist circumference (cm); WD: wrist diameter (cm).
Analyzed anthropometric equations (developed in nonathletic populations).
Author | Equation |
---|---|
Durnin-R [ | BD = 1.161 − (0.0632 |
Durnin-W [ | 18-19 y → BD = 1.162 − (0.063 |
20–29 y → BD = 1.1631 − (0.0632 | |
30–39 y → BD = 1.1422 − (0.0544 | |
Jackson 3SKF [ | BD = 1.10938 − (0.0008267 |
Jackson 7SKF [ | BD = 1.112 − (0.00043499 |
Katch [ | BD = 1.09665 − (0.00103 |
Lean [ | BD = 1.1862 − (0.0684 |
Lohman [ | BD = 1.0982 − (0.000815 |
Nagamine [ | BD = 1.0913 − (0.00116 |
Pollock [ | BD = 1.09716 − (0.00065 |
Sloan [ | BD = 1.1043 − (0.001327 |
Wilmore [ | BD = 1.08543 − (0.000886 |
Ball [ | BF% = 0.465 + (0.18 |
Eston [ | BF% = (0.12 |
Leahy [ | BF% = (Age |
Peterson [ | BF% = 20.94878 + (0.1166 |
Van der Ploeg [ | BF% = (0.183 |
Garcia [ | BFM = (WC |
BF%: body fat percentage; Ab: abdomen skinfold; Ax: axilla skinfold; B: biceps skinfold; BD: body density; BFM: body fat mass (kg); Ca: calf skinfold; Ch: chest skinfold; IC: iliac crest skinfold; Sb: subscapular skinfold; SKF: skinfolds; Sp: supraspinal skinfold; T: triceps skinfold; Th; thigh skinfold; WC: waist circumference (cm); y: years.
These measurements consisted of body mass to nearest 0.1 kg (TBF-410, Tanita, Tokyo, Japan), height to nearest 0.1 cm (Seca 213, Seca, Hamburg, Germany), 10 skinfolds (triceps, subscapular, biceps, chest, axilla, iliac crest, supraspinal, abdomen, thigh, and calf) to nearest 0.1 mm (Harpenden, Baty International, United Kingdom), waist circumference with a metallic tape (to nearest 0.1 cm), and elbow diameter (Campbell 10, Rosscraft, Canada) to nearest 0.05 cm. All measurements were evaluated by trained personnel following standardized procedures. All measurements were evaluated following the ISAK protocol [
A whole body scan was performed for each subject with a DXA fan beam equipment (Hologic QDR4500 Explorer, Massachusetts, USA). The equipment was calibrated daily following the manufacturers indications. All scans were analyzed with the software for Windows® Hologic QDR v 12.1 (1986–2002©, Hologic Inc.). The zone of head was excluded from the scan in order to calculate the body fat percentage. The difference between DXA whole body mass and body mass on scale was on average −
Body fat percentage was estimated with 14 AT anthropometric equations for each participant. These equations estimate body density [
Body fat percentage was estimated with 17 NAT anthropometric equations for each participant. These equations estimate body density [
Siri’s equation [
In order to determine which equations estimated the BF% different than the one obtained with DXA, all anthropometrical BF% estimations were tested with the Kruskal-Wallis and Dunn’s post hoc test, considering a significance level of
The age of participants was 23.2 (20.5–26.8 y), body mass
Subjects’ skinfold thicknesses (
Median (25th–75th percentile) | |
---|---|
Triceps | 7.5 (6.0–9.6) |
Subscapular | 9.6 (7.8–11.5) |
Biceps | 3.8 (3.1–4.5) |
Chest | 7.2 (5.7–9.4) |
Axilla | 8.0 (6.1–10.3) |
Iliac Crest | 13.9 (9.9–20.0) |
Supraspinal | 7.8 (6.3–11.0) |
Abdomen | 15.8 (10.8–21.3) |
Thigh | 8.7 (7.0–10.8) |
Calf | 5.1 (4.3–6.5) |
From the 14 anthropometric equations analyzed, five showed no significant differences compared with DXA (Table
Body fat percentage measured with DXA and estimated with anthropometric equations developed in athletic populations.
Author equation | Median (25th–75th percentile) |
---|---|
DXA | 14.0 (11.9–16.4) |
Thorland (3SKF) | 9.2 (6.3–12.0) |
White | 9.4 (7.4–11.3) |
Stewart | 10.2 (7.2–13.3) |
Withers | 10.5 (8.6–13.1) |
Evans (3SKF) | 10.5 (8.9–12.7) |
Pascale | 10.5 (9.3–12.2) |
Reilly | 10.7 (9.6–12.2) |
Thorland (7SKF) | 10.8 (7.8–14.4) |
Evans (7SKF) | 11.2 (9.4–13.5) |
Civar | 12.6 (10.5–14.5) |
Forsyth (4SKF) | 13.0 (9.6–17.9) |
Oliver | 13.1 (11.0–15.5) |
Forsyth (2SKF) | 13.7 (10.1–18.4) |
Zuti | 14.3 (12.5–17.6) |
2SKF, two skinfolds; 3SKF, three skinfolds; 4SKF, four skinfolds; 7SKF, seven skinfolds; DXA, dual-energy X-ray absorptiometry. Different compared with DXA.
Body fat percentage differences (equation − DXA) from anthropometric equations (developed in athletic populations) statistically similar to DXA.
Author equation | Mean | 95% limits of agreement | |
---|---|---|---|
Oliver | | (−3.9 to 2.3) | |
Civar | | (−4.8 to 1.8) | |
Zuti | | (−4.8 to 6.3) | |
Forsyth (4SKF) | | (−6.2 to 5.7) | |
Forsyth (2SKF) | | (−5.8 to 6.5) | |
Equations are listed from the narrowest to the widest limits of agreement. 2SKF, two skinfolds; 4SKF, four skinfolds; DXA, dual-energy X-ray absorptiometry.
From the 17 anthropometric equations analyzed, seven showed no significant differences compared with DXA (Table
Body fat percentage measured with DXA and estimated with anthropometric equations developed in nonathletic populations.
Author equation | Median (25th–75th percentile) |
---|---|
DXA | 14.0 (11.9–16.4) |
Lohman | 8.0 (7.1–8.8) |
Sloan | 8.4 (6.8–10.1) |
Pollock | 8.4 (7.1–10.0) |
Jackson (3SKF) | 8.9 (6.7–12.1) |
Jackson (7SKF) | 9.8 (7.3–12.6) |
Katch | 10.4 (8.7–12.9) |
Eston | 11.0 (9.3–13.0) |
Nagamine | 12.0 (10.4–13.6) |
Wilmore | 13.4 (11.4–15.8) |
Ball | 13.7 (11.5–16.4) |
Lean | 14.5 (11.1–17.3) |
Garcia | 14.9 (11.7–18.2) |
Van der Ploeg | 15.1 (12.5–18.1) |
Durnin-W | 15.3 (12.2–18.1) |
Durnin-R | 15.8 (12.7–18.1) |
Leahy | 16.4 (13.7–19.9) |
Peterson | 17.9 (15.1–20.5) |
3SKF, three skinfolds; 7SKF, seven skinfolds; DXA, dual-energy X-ray absorptiometry. Different compared with DXA.
Body fat percentage differences (equation − DXA) from anthropometric equations (developed in nonathletic populations) statistically similar to DXA.
Author equation | Mean | 95% limits of agreement | |
---|---|---|---|
Ball | | (−3.4 to 3.1) | |
Wilmore | | (−3.9 to 3.0) | |
Durnin-R | 1.4 | (−2.3 to 5.1) | |
Van der Ploeg | 1.3 | (−2.4 to 5.1) | |
Durnin-W | 1.1 | (−3.0 to 5.2) | |
Lean | 0.2 | (−4.5 to 5.0) | |
Garcia | 0.3 | (−4.7 to 5.2) | |
Equations are listed from the narrowest to the widest limits of agreement. DXA, dual-energy X-ray absorptiometry.
The purpose of this study was to analyze the accuracy of BF% obtained through several anthropometric equations and that measured with DXA in professional male soccer players. We only found two other studies that addressed the same issue in soccer players [
Da Fonseca et al. [
Other studies have compared anthropometric equations with hydrostatic weighting in different athletic populations [
Different results between previous studies and ours may be explained by the different population in which they were validated (football players, college age men, etc.) and the reference method used.
From the five AT anthropometric equations that did not differ significantly with DXA, four were validated with hydrostatic weighting [
Oliver’s equation [
Wilmore’s equation was developed in male university students (aged 16 to 37 years) [
In a practical way, Wilmore’s equation may be more useful because it accurately estimated BF% using few variables compared to the other equations. From another perspective, we recommend Oliver’s equation, as it had higher agreement with DXA, and because it employs seven skinfolds it may offer a better whole body perspective.
Some of the limitations of this study were as follows: The results of our reference method (DXA) may differ from other reference methods; however several studies have reported that DXA is a practical and accurate method for assessing BF% [ The protocols from the original studies may differ with the one we followed to evaluate the anthropometric measurements; however we tried to keep the anatomical sites as similar as possible. The instruments we used to evaluate the anthropometric measurements also differed from some of the authors’ original studies.
Some of our strengths were as follows: All our personnel (for anthropometric assessments and DXA scanning) are certified to do this kind of evaluations. This study has a large sample. We included many AT and NAT anthropometric equations.
In this study, we found that Oliver’s (AT), Ball’s (NAT), Civar’s (AT), and Wilmore’s (NAT) equations had the highest agreement with DXA for estimating BF% in professional male soccer players. These equations can be used alternatively to DXA for estimating BF% in a cross-sectional way. It remains to be seen if these equations are useful for monitoring changes in BF% over time. These issues deserve further research.
This work is an extended version of a previous poster presentation.
The authors declare that they have no conflicts of interest.
The authors would like to thank Franklyn López Taylor and Rosalía Reynaga Wilkins for their valuable review and comments on the manuscript.