- Email: [email protected]
Adductor pollicis muscle thickness has a low association with lean mass in women
Clinical Nutrition xxx (2017) 1e3
Contents lists available at ScienceDirect
Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Short Communication
Adductor pollicis muscle thickness has a low association with lean mass in women Sara M. Barreiro a, Heitor O. Santos a, Raíla P.F. Cruz a, Paula C. Nahas a, Luana T. Rossato a, bio L. Orsatti b, c, Erick P. de Oliveira a, * Fa a b c
School of Medicine, Federal University of Uberlandia (UFU), Uberlandia, Minas Gerais, Brazil Exercise Biology Research Group (BioEx), Federal University of Triangulo Mineiro (UFTM), Brazil Department of Sport Sciences, Federal University of Triangulo Mineiro, Uberaba, MG, Brazil
a r t i c l e i n f o
s u m m a r y
Article history: Received 14 April 2017 Accepted 11 August 2017
Background & aim: Lean mass (LM) is a functional component of body composition and is an important parameter of nutritional status assessment. The adductor pollicis muscle thickness (APMT) has been used as a predictor of LM, but it is not well known if this method presents a higher prediction of LM than simple anthropometric measurements, such as weight. Thus, we aimed to associate APMT (alone and plus weight) with LM in women. Methods: This cross-sectional study was conducted with 82 young and postmenopausal women. Body weight (Filizola®) and height (Welmy®) was quantified and APMT was measured by Lange® caliper. Body composition (LM and fat percentage) was estimated by dual-energy X-ray absorptiometry. Results: APMT was positively correlated with LM (r ¼ 0.35; p ¼ 0.001), however, weight was strongly correlated with LM (r ¼ 0.81; p < 0.001). APMT showed a prediction of 12% of LM (b ¼ 0.346, R2 ¼ 0.120, p < 0.001), and weight explained the variations of LM by 65% (b ¼ 0.808, R2 ¼ 0.654, p < 0.001). When weight and APMT were evaluated together, there was an increase of only 0.06% in LM prediction (b ¼ 0.820, R2 ¼ 0.655, p < 0.001), compared to weight alone. Conclusion: When compared to weight, APMT showed a low association with LM. These results suggest that a simpler anthropometric measurement, such as weight, can be a better predictor of LM than APMT. © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Keywords: Body composition Nutritional assessment Lean mass Body weight
1. Introduction The lean mass (LM) assessment is an important parameter of nutritional status assessment and can be estimated by several methods, such as dual energy X-ray absorptiometry (DXA), magnetic resonance, and computed tomography. Although these methodologies are reliable, it presents high cost and difficult to access, besides technical complexity [1]. The estimation of LM by anthropometric measurements, using circumferences and skinfolds, would be a possible and feasible methodology since it is simple and less costly. However, predictive equations are necessary for quantifying LM and the anthropometric measurements are susceptible to errors [1]. Thus, new simple alternative tools are needed to predict LM in clinical practice.
In this way, the adductor pollicis muscle thickness (APMT), which is located at the apex of an imaginary angle formed by the extension of the thumb and the index finger, has been used as a possible predictor of muscle mass [2,3] and malnutrition [4] in clinical situations, presenting advantages, such as low-cost, minimally invasive and is a simple measurement, which reduces error [2]. However, it is not well known, in free-living women, if this method presents a higher prediction of LM than simple anthropometric measurements, such as weight, that is correlated with muscle mass [5]. Therefore, we aimed to associate the APMT (alone and plus weight) with the LM in women. 2. Materials and methods 2.1. Subjects
* Corresponding author. Av. Par a, nº1720 Bloco 2U Campus Umuarama, 38400-902, ^ndia, MG, Brazil. Uberla E-mail address: [email protected] (E.P. de Oliveira).
A cross-sectional study was conducted with 82 individuals (29 young and 53 postmenopausal women) entering in a physical exercise program in Uberaba, MG, Brazil. These individuals were
http://dx.doi.org/10.1016/j.clnu.2017.08.012 0261-5614/© 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012
2
S.M. Barreiro et al. / Clinical Nutrition xxx (2017) 1e3
clinically selected to perform a resistance exercise program and all women were evaluated at baseline. The present study was approved by the Research Ethics Committee of the Federal University of Triangulo Mineiro (protocol 1.090.676), and all participants signed an informed consent from the project. 2.2. Anthropometric assessment Weight was obtained using a portable balance calibrated (Filizola®) and height was assessed with a portable stadiometer (Welmy®). Both measures were performed according to Lohman's protocol [6] and body mass index (BMI) (kg/m2) was calculated [7]. 2.3. Adductor pollicis muscle thickness The APMT was measured with a Lange® caliper, which was used exerting continuous pressure to pinch the adductor pollicis muscle at the apex of an imaginary angle formed by the extension of the thumb and the index finger [8]. The individuals remained in the standing position and the measurement was performed in the dominant hand. The mean of three measurements was considered as the APMT value. 2.4. Body composition Dual energy X-ray absorptiometry was used for the evaluation of LM and fat percentage by the scanner Hologic QDR-2000 densitometer plus (Hologic, Waltham, MA). The assessment was performed manually and the volunteers were instructed to drink 2 L of water during the day before the test and to refrain from physical activity, in order to standardize muscle mass hydration. The analysis was done after 8e10 h of overnight fasting, and the volunteers had to wear light clothes without metallic accessories, as previously described [9]. 2.5. Statistical analysis The normality of data was tested by ShapiroeWilk. Pearson's correlation was performed to correlate APMT and weight with LM. Simple and multiple linear regression were performed to assess the prediction of LM by APMT and/or weight. Three statistical models were performed: model 1: contained only APMT; model 2: only weight; and model 3: weight plus APMT. The data were described as mean ± SD and percentage. The tests were performed using STATISTICA 6.0 software and the significance level of p < 0.05 was adopted.
The APMT was positively correlated with LM (r ¼ 0.35; p ¼ 0.001) (Supplementary Fig. 1) and weight showed a higher correlation with LM (r ¼ 0.81; p < 0.001) (Supplementary Fig. 2). Additionally, after multiple linear regression analysis, APMT showed a prediction of 12% of LM (b ¼ 0.346, R2 ¼ 0.120, p < 0.001), whereas weight explained 65% of the variances in LM (b ¼ 0.808, R2 ¼ 0.654, p < 0.001). When evaluated together, weight plus APMT increased only 0.06% the LM prediction when compared to weight alone (b ¼ 0.820, R2 ¼ 0.655, p < 0.001) (Fig. 1). 4. Discussion The main finding of the present study was that weight showed a higher association with LM than APMT in women. The use of APMT explained 12%, whereas weight explained 65% of the variances of LM. Additionally, when weight plus APMT were assessed together, the addition of APMT increased this prediction by 0.06%. Our results are in agreement with a recent research performed by Bieleman et al. (2016) [10] in which 3485 young adults (1749 women) were evaluated. The authors aimed to evaluate the association of APMT and BMI with LM and it was showed, in women, that APMT explained 26% of the variances in LM, whereas BMI predicted the LM by 41%. Additionally, BMI plus APMT increased the prediction for LM by 4%, when compared to BMI alone. The authors also found a significant correlation between APMT and LM (r ¼ 0.51), which was higher than at present study (r ¼ 0.35), but both correlations were moderate and probably there are no biological differences between the results of the studies. Although at present study a smaller number of women in a wide age range (young and postmenopausal) were evaluated, both studies showed that the use of APMT does not seem to be a good predictor of LM when compared to weight or BMI. We also showed that weight, instead of BMI, may be a better predictor of LM since weight presented a 24% and 32% higher prediction of LM than BMI comparing with Bieleman et al. [10] and our data ((R2 ¼ 0.330, p < 0.001); data not shown), respectively. The results of present study are also in accordance with a recent investigation performed by our research group [11], in which we found that APMT showed a low prediction of muscle mass (37%) when compared to weight, that explained the variations of muscle mass by 70%. It is important to note that this study [11] evaluated hospitalized patients of both sexes with a high age range and anthropometry was used to assess body composition, which presents known limitations. The present study evaluated young and
3. Results The characteristics of the women are described in Table 1. The mean values of APMT, age, weight, BMI, LM, and body fat were 14.0 ± 3.6 mm, 48.4 ± 19.4 years, 66.2 ± 14.2 kg, 27.1 ± 6.2 kg/m2, 36.7 ± 4.6 kg, 39.7 ± 7.6%, respectively. Table 1 Demographic, anthropometric, and body composition measurements of women. Mean ± SD (n ¼ 82) Age (years) Weight (kg) Height (m) Body mass index (kg/m2) APMT (mm) Lean mass (kg) Body fat (%)
48.4 66.2 1.56 27.1 14.0 36.7 39.7
± ± ± ± ± ± ±
19.4 14.2 0.07 6.2 3.6 4.6 7.6
APMT, Adductor pollicis muscle thickness. SD ¼ standard deviation.
Fig. 1. Coefficients of determination (R2) of adductor pollicis muscle thickness and weight in the prediction of lean mass. APMT, Adductor pollicis muscle thickness.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012
S.M. Barreiro et al. / Clinical Nutrition xxx (2017) 1e3
postmenopausal women; and body composition was estimated by DXA. However, despite the differences in methodology and population, the results found by Barbosa et al. (2016) [11] are in agreement with present data, confirming that APMT does not seem to be a good predictor of LM or muscle mass independently of the body composition method used to estimate these parameters. The present study had some limitations. The sample was formed only by young and postmenopausal women and a study including men is necessary for better understanding of the association between APMT and LM in a general population. Additionally, it is necessary to evaluate these associations in a higher number of individuals to confirm our data. In contrast, the strength of the present study was the use of DXA, that has a good correlation with gold standard methods (e.g. magnetic resonance) for estimating body composition [12]. In conclusion, when compared to weight, APMT showed a low association with LM. These results suggest that a simpler anthropometric measurement, such as weight, can be a better predictor of LM than APMT. Statement of authorship SMB, HOS and RPFC wrote the manuscript; PCN and LTR participated in collection and analysis of data and wrote the manuscript; FLO participated in the interpretation of the data and contributed to the revision of the manuscript; and EPO carried out the conception and design of the study, participated in the interpretation of the data, wrote, and contributed to the revision of the manuscript. Conflict of interest None. Acknowledgement FAPEMIG for financial support.
3
Appenidix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.clnu.2017.08.012. References [1] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European working group on sarcopenia in older people. Age Ageing 2010;39: 412e23. [2] Lameu EB, Gerude MF, Campos AC, Luiz RR. The thickness of the adductor pollicis muscle reflects the muscle compartment and may be used as a new anthropometric parameter for nutritional assessment. Curr Opin Clin Nutr Metab Care 2004;7:293e301. [3] Cortez AF, Tolentino JC, Elarrat RM, Freitas Passos RB. Association between adductor pollicis muscle thickness, anthropometric and immunological parameters in HIV-positive patients. Clin Nutr ESPEN 2017;17: 105e9. [4] Gonzalez MC, Pureza Duarte RR, Orlandi SP, Bielemann RM, Barbosa-Silva TG. Adductor pollicis muscle: a study about its use as a nutritional parameter in surgical patients. Clin Nutr 2015;34:1025e9. [5] Gariballa S, Alessa A. Sarcopenia: prevalence and prognostic significance in hospitalized patients. Clin Nutr 2013;32:772e6. [6] Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. 1988. [7] Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974;32:77e97. [8] Lameu EB, Gerude MF, Correa RC, Lima KA. Adductor pollicis muscle: a new anthropometric parameter. Rev Hosp Clin Fac Med Sao Paulo 2004;59: 57e62. [9] Orsatti FL, Nahas EA, Orsatti CL, de Oliveira EP, Nahas-Neto J, da Mota GR, et al. Muscle mass gain after resistance training is inversely correlated with trunk adiposity gain in postmenopausal women. J Strength Cond Res 2012;26: 2130e9. [10] Bielemann RM, Horta BL, Orlandi SP, Barbosa-Silva TG, Gonzalez MC, Assuncao MC, et al. Is adductor pollicis muscle thickness a good predictor of lean mass in adults? Clin Nutr 2016;35:1073e7. [11] Barbosa CD, Crepaldi BVC, Nahas PC, Rossato LT, de Oliveira EP. Adductor pollicis muscle thickness has a low association with muscle mass in hospitalized patients. J Negat No Posit Results 2017;2:49e55. [12] Carpenter CL, Sarma M, Nagarajan R, Lee CC, Thomas MA, Go VL, et al. Assessment of visceral adipose tissue by dual energy X-ray absorptiometry and magnetic resonance imaging among a young adult obese population. FASEB J 2016;30.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012
Contents lists available at ScienceDirect
Clinical Nutrition journal homepage: http://www.elsevier.com/locate/clnu
Short Communication
Adductor pollicis muscle thickness has a low association with lean mass in women Sara M. Barreiro a, Heitor O. Santos a, Raíla P.F. Cruz a, Paula C. Nahas a, Luana T. Rossato a, bio L. Orsatti b, c, Erick P. de Oliveira a, * Fa a b c
School of Medicine, Federal University of Uberlandia (UFU), Uberlandia, Minas Gerais, Brazil Exercise Biology Research Group (BioEx), Federal University of Triangulo Mineiro (UFTM), Brazil Department of Sport Sciences, Federal University of Triangulo Mineiro, Uberaba, MG, Brazil
a r t i c l e i n f o
s u m m a r y
Article history: Received 14 April 2017 Accepted 11 August 2017
Background & aim: Lean mass (LM) is a functional component of body composition and is an important parameter of nutritional status assessment. The adductor pollicis muscle thickness (APMT) has been used as a predictor of LM, but it is not well known if this method presents a higher prediction of LM than simple anthropometric measurements, such as weight. Thus, we aimed to associate APMT (alone and plus weight) with LM in women. Methods: This cross-sectional study was conducted with 82 young and postmenopausal women. Body weight (Filizola®) and height (Welmy®) was quantified and APMT was measured by Lange® caliper. Body composition (LM and fat percentage) was estimated by dual-energy X-ray absorptiometry. Results: APMT was positively correlated with LM (r ¼ 0.35; p ¼ 0.001), however, weight was strongly correlated with LM (r ¼ 0.81; p < 0.001). APMT showed a prediction of 12% of LM (b ¼ 0.346, R2 ¼ 0.120, p < 0.001), and weight explained the variations of LM by 65% (b ¼ 0.808, R2 ¼ 0.654, p < 0.001). When weight and APMT were evaluated together, there was an increase of only 0.06% in LM prediction (b ¼ 0.820, R2 ¼ 0.655, p < 0.001), compared to weight alone. Conclusion: When compared to weight, APMT showed a low association with LM. These results suggest that a simpler anthropometric measurement, such as weight, can be a better predictor of LM than APMT. © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Keywords: Body composition Nutritional assessment Lean mass Body weight
1. Introduction The lean mass (LM) assessment is an important parameter of nutritional status assessment and can be estimated by several methods, such as dual energy X-ray absorptiometry (DXA), magnetic resonance, and computed tomography. Although these methodologies are reliable, it presents high cost and difficult to access, besides technical complexity [1]. The estimation of LM by anthropometric measurements, using circumferences and skinfolds, would be a possible and feasible methodology since it is simple and less costly. However, predictive equations are necessary for quantifying LM and the anthropometric measurements are susceptible to errors [1]. Thus, new simple alternative tools are needed to predict LM in clinical practice.
In this way, the adductor pollicis muscle thickness (APMT), which is located at the apex of an imaginary angle formed by the extension of the thumb and the index finger, has been used as a possible predictor of muscle mass [2,3] and malnutrition [4] in clinical situations, presenting advantages, such as low-cost, minimally invasive and is a simple measurement, which reduces error [2]. However, it is not well known, in free-living women, if this method presents a higher prediction of LM than simple anthropometric measurements, such as weight, that is correlated with muscle mass [5]. Therefore, we aimed to associate the APMT (alone and plus weight) with the LM in women. 2. Materials and methods 2.1. Subjects
* Corresponding author. Av. Par a, nº1720 Bloco 2U Campus Umuarama, 38400-902, ^ndia, MG, Brazil. Uberla E-mail address: [email protected] (E.P. de Oliveira).
A cross-sectional study was conducted with 82 individuals (29 young and 53 postmenopausal women) entering in a physical exercise program in Uberaba, MG, Brazil. These individuals were
http://dx.doi.org/10.1016/j.clnu.2017.08.012 0261-5614/© 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012
2
S.M. Barreiro et al. / Clinical Nutrition xxx (2017) 1e3
clinically selected to perform a resistance exercise program and all women were evaluated at baseline. The present study was approved by the Research Ethics Committee of the Federal University of Triangulo Mineiro (protocol 1.090.676), and all participants signed an informed consent from the project. 2.2. Anthropometric assessment Weight was obtained using a portable balance calibrated (Filizola®) and height was assessed with a portable stadiometer (Welmy®). Both measures were performed according to Lohman's protocol [6] and body mass index (BMI) (kg/m2) was calculated [7]. 2.3. Adductor pollicis muscle thickness The APMT was measured with a Lange® caliper, which was used exerting continuous pressure to pinch the adductor pollicis muscle at the apex of an imaginary angle formed by the extension of the thumb and the index finger [8]. The individuals remained in the standing position and the measurement was performed in the dominant hand. The mean of three measurements was considered as the APMT value. 2.4. Body composition Dual energy X-ray absorptiometry was used for the evaluation of LM and fat percentage by the scanner Hologic QDR-2000 densitometer plus (Hologic, Waltham, MA). The assessment was performed manually and the volunteers were instructed to drink 2 L of water during the day before the test and to refrain from physical activity, in order to standardize muscle mass hydration. The analysis was done after 8e10 h of overnight fasting, and the volunteers had to wear light clothes without metallic accessories, as previously described [9]. 2.5. Statistical analysis The normality of data was tested by ShapiroeWilk. Pearson's correlation was performed to correlate APMT and weight with LM. Simple and multiple linear regression were performed to assess the prediction of LM by APMT and/or weight. Three statistical models were performed: model 1: contained only APMT; model 2: only weight; and model 3: weight plus APMT. The data were described as mean ± SD and percentage. The tests were performed using STATISTICA 6.0 software and the significance level of p < 0.05 was adopted.
The APMT was positively correlated with LM (r ¼ 0.35; p ¼ 0.001) (Supplementary Fig. 1) and weight showed a higher correlation with LM (r ¼ 0.81; p < 0.001) (Supplementary Fig. 2). Additionally, after multiple linear regression analysis, APMT showed a prediction of 12% of LM (b ¼ 0.346, R2 ¼ 0.120, p < 0.001), whereas weight explained 65% of the variances in LM (b ¼ 0.808, R2 ¼ 0.654, p < 0.001). When evaluated together, weight plus APMT increased only 0.06% the LM prediction when compared to weight alone (b ¼ 0.820, R2 ¼ 0.655, p < 0.001) (Fig. 1). 4. Discussion The main finding of the present study was that weight showed a higher association with LM than APMT in women. The use of APMT explained 12%, whereas weight explained 65% of the variances of LM. Additionally, when weight plus APMT were assessed together, the addition of APMT increased this prediction by 0.06%. Our results are in agreement with a recent research performed by Bieleman et al. (2016) [10] in which 3485 young adults (1749 women) were evaluated. The authors aimed to evaluate the association of APMT and BMI with LM and it was showed, in women, that APMT explained 26% of the variances in LM, whereas BMI predicted the LM by 41%. Additionally, BMI plus APMT increased the prediction for LM by 4%, when compared to BMI alone. The authors also found a significant correlation between APMT and LM (r ¼ 0.51), which was higher than at present study (r ¼ 0.35), but both correlations were moderate and probably there are no biological differences between the results of the studies. Although at present study a smaller number of women in a wide age range (young and postmenopausal) were evaluated, both studies showed that the use of APMT does not seem to be a good predictor of LM when compared to weight or BMI. We also showed that weight, instead of BMI, may be a better predictor of LM since weight presented a 24% and 32% higher prediction of LM than BMI comparing with Bieleman et al. [10] and our data ((R2 ¼ 0.330, p < 0.001); data not shown), respectively. The results of present study are also in accordance with a recent investigation performed by our research group [11], in which we found that APMT showed a low prediction of muscle mass (37%) when compared to weight, that explained the variations of muscle mass by 70%. It is important to note that this study [11] evaluated hospitalized patients of both sexes with a high age range and anthropometry was used to assess body composition, which presents known limitations. The present study evaluated young and
3. Results The characteristics of the women are described in Table 1. The mean values of APMT, age, weight, BMI, LM, and body fat were 14.0 ± 3.6 mm, 48.4 ± 19.4 years, 66.2 ± 14.2 kg, 27.1 ± 6.2 kg/m2, 36.7 ± 4.6 kg, 39.7 ± 7.6%, respectively. Table 1 Demographic, anthropometric, and body composition measurements of women. Mean ± SD (n ¼ 82) Age (years) Weight (kg) Height (m) Body mass index (kg/m2) APMT (mm) Lean mass (kg) Body fat (%)
48.4 66.2 1.56 27.1 14.0 36.7 39.7
± ± ± ± ± ± ±
19.4 14.2 0.07 6.2 3.6 4.6 7.6
APMT, Adductor pollicis muscle thickness. SD ¼ standard deviation.
Fig. 1. Coefficients of determination (R2) of adductor pollicis muscle thickness and weight in the prediction of lean mass. APMT, Adductor pollicis muscle thickness.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012
S.M. Barreiro et al. / Clinical Nutrition xxx (2017) 1e3
postmenopausal women; and body composition was estimated by DXA. However, despite the differences in methodology and population, the results found by Barbosa et al. (2016) [11] are in agreement with present data, confirming that APMT does not seem to be a good predictor of LM or muscle mass independently of the body composition method used to estimate these parameters. The present study had some limitations. The sample was formed only by young and postmenopausal women and a study including men is necessary for better understanding of the association between APMT and LM in a general population. Additionally, it is necessary to evaluate these associations in a higher number of individuals to confirm our data. In contrast, the strength of the present study was the use of DXA, that has a good correlation with gold standard methods (e.g. magnetic resonance) for estimating body composition [12]. In conclusion, when compared to weight, APMT showed a low association with LM. These results suggest that a simpler anthropometric measurement, such as weight, can be a better predictor of LM than APMT. Statement of authorship SMB, HOS and RPFC wrote the manuscript; PCN and LTR participated in collection and analysis of data and wrote the manuscript; FLO participated in the interpretation of the data and contributed to the revision of the manuscript; and EPO carried out the conception and design of the study, participated in the interpretation of the data, wrote, and contributed to the revision of the manuscript. Conflict of interest None. Acknowledgement FAPEMIG for financial support.
3
Appenidix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.clnu.2017.08.012. References [1] Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European working group on sarcopenia in older people. Age Ageing 2010;39: 412e23. [2] Lameu EB, Gerude MF, Campos AC, Luiz RR. The thickness of the adductor pollicis muscle reflects the muscle compartment and may be used as a new anthropometric parameter for nutritional assessment. Curr Opin Clin Nutr Metab Care 2004;7:293e301. [3] Cortez AF, Tolentino JC, Elarrat RM, Freitas Passos RB. Association between adductor pollicis muscle thickness, anthropometric and immunological parameters in HIV-positive patients. Clin Nutr ESPEN 2017;17: 105e9. [4] Gonzalez MC, Pureza Duarte RR, Orlandi SP, Bielemann RM, Barbosa-Silva TG. Adductor pollicis muscle: a study about its use as a nutritional parameter in surgical patients. Clin Nutr 2015;34:1025e9. [5] Gariballa S, Alessa A. Sarcopenia: prevalence and prognostic significance in hospitalized patients. Clin Nutr 2013;32:772e6. [6] Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. 1988. [7] Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974;32:77e97. [8] Lameu EB, Gerude MF, Correa RC, Lima KA. Adductor pollicis muscle: a new anthropometric parameter. Rev Hosp Clin Fac Med Sao Paulo 2004;59: 57e62. [9] Orsatti FL, Nahas EA, Orsatti CL, de Oliveira EP, Nahas-Neto J, da Mota GR, et al. Muscle mass gain after resistance training is inversely correlated with trunk adiposity gain in postmenopausal women. J Strength Cond Res 2012;26: 2130e9. [10] Bielemann RM, Horta BL, Orlandi SP, Barbosa-Silva TG, Gonzalez MC, Assuncao MC, et al. Is adductor pollicis muscle thickness a good predictor of lean mass in adults? Clin Nutr 2016;35:1073e7. [11] Barbosa CD, Crepaldi BVC, Nahas PC, Rossato LT, de Oliveira EP. Adductor pollicis muscle thickness has a low association with muscle mass in hospitalized patients. J Negat No Posit Results 2017;2:49e55. [12] Carpenter CL, Sarma M, Nagarajan R, Lee CC, Thomas MA, Go VL, et al. Assessment of visceral adipose tissue by dual energy X-ray absorptiometry and magnetic resonance imaging among a young adult obese population. FASEB J 2016;30.
Please cite this article in press as: Barreiro SM, et al., Adductor pollicis muscle thickness has a low association with lean mass in women, Clinical Nutrition (2017), http://dx.doi.org/10.1016/j.clnu.2017.08.012