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Journal articles on the topic 'Body lean mass'

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Author: Grafiati
Published: 11 March 2023

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1

Forbes, Gilbert B., Eva Prochaska Sauer, and Lowell R. Weitkamp. "Lean body mass in twins." Metabolism 44, no. 11 (November 1995): 1442–46. http://dx.doi.org/10.1016/0026-0495(95)90144-2.

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2

Colpitts, Benjamin H., Danielle R. Bouchard, Mohammad Keshavarz, Jonathan Boudreau, and Martin Sénéchal. "Does lean body mass equal health despite body mass index?" Scandinavian Journal of Medicine & Science in Sports 30, no. 4 (December 12, 2019): 672–79. http://dx.doi.org/10.1111/sms.13605.

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3

Kim, Soo-Youn. "Relationship between Lean Body Mass and Appetite-Regulating Hormones in Ballet Dancers." Korean Journal of Sports Science 28, no. 1 (February 28, 2019): 1067–75. http://dx.doi.org/10.35159/kjss.2019.02.28.1.1067.

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4

Forbes, Gilbert B. "Lean Body Mass-Body Fat Interrelationships in Humans." Nutrition Reviews 45, no. 10 (April 27, 2009): 225–31. http://dx.doi.org/10.1111/j.1753-4887.1987.tb02684.x.

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5

&NA;. "Lean body mass better dose predictor?" Inpharma Weekly &NA;, no. 939 (May 1994): 20. http://dx.doi.org/10.2165/00128413-199409390-00040.

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6

Sepulveda, Patricio V., Ernest D. Bush, and Keith Baar. "Pharmacology of manipulating lean body mass." Clinical and Experimental Pharmacology and Physiology 42, no. 1 (December 22, 2014): 1–13. http://dx.doi.org/10.1111/1440-1681.12320.

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7

Wedgwood, Ralph J. "INCONSTANCY OF THE LEAN BODY MASS." Annals of the New York Academy of Sciences 110, no. 1 (December 15, 2006): 141–52. http://dx.doi.org/10.1111/j.1749-6632.1963.tb17080.x.

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8

Negri, M., M. Zamboni, and G. Gambaro. "Lean body mass to estimate GFR." Nephrology Dialysis Transplantation 22, no. 4 (January 25, 2007): 1267. http://dx.doi.org/10.1093/ndt/gfm030.

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9

SUZUKI, Jun, Kenichi FURUTOH, and Masaru NISHIKIBE. "A new system using NMR technology for measurement of body composition in experimental animals." Folia Pharmacologica Japonica 123, no. 4 (2004): 281–87. http://dx.doi.org/10.1254/fpj.123.281.

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10

Cosolo, Walter C., Denis J. Morgan, Ego Seeman, Allan S. Zimet, Joe J. McKendrick, and John R. Zalcberg. "Lean body mass, body surface area and epirubicin kinetics." Anti-Cancer Drugs 5, no. 3 (June 1994): 293–97. http://dx.doi.org/10.1097/00001813-199406000-00005.

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11

Swaminathan, R., Phillipa Major, Harold Snieder, and Timothy Spector. "Serum Creatinine and Fat-free Mass (Lean Body Mass)." Clinical Chemistry 46, no. 10 (October 1, 2000): 1695–96. http://dx.doi.org/10.1093/clinchem/46.10.1695.

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12

Keshaviah, P. R., K. D. Nolph, H. L. Moore, B. Prowant, P. F. Emerson, M. Meyer, Z. J. Twardowski, R. Khanna, L. Ponferrada, and A. Collins. "Lean body mass estimation by creatinine kinetics." Journal of the American Society of Nephrology 4, no. 7 (January 1994): 1475–85. http://dx.doi.org/10.1681/asn.v471475.

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A new technique for estimating lean body mass (LBM) from creatinine kinetics has been developed. It is based on the principle that creatinine production is proportional to LBM and that, in the steady state, creatinine production is equal to the sum of creatinine excretion (urinary and dialytic) and metabolic degradation. This technique was applied to 17 normal subjects, 26 stable, chronic hemodialysis (HD) patients, and 71 stable, chronic peritoneal dialysis (PD) patients. In the HD group, LBM was also determined by bioimpedance in 11 patients and calculated from total body water, measured as the volume of urea distribution of a sterile urea infusion, in 15 patients. In normal subjects and in the PD group, LBM was assessed by creatinine kinetics as well as by bioimpedance, near infrared, and anthropometric techniques. In the HD patients, LBM by creatinine kinetics correlated significantly with LBM from total body water and the bioimpedance technique. There was no statistical difference between the total body water and creatinine kinetics techniques, but the bioimpedance values were systematically higher than those obtained by the kinetic technique. In the PD group and in normal volunteers, LBM values by creatinine kinetics correlated significantly with the other methods but were lower. Forty-seven percent of the HD patients and 66% of the PD patients had significantly lower LBM by creatinine kinetics than expected for their sex and age. Estimation of LBM by creatinine kinetics is proposed as a simple and convenient technique for the routine nutritional assessment of dialysis patients.
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13

Peters, A. M., H. L. R. Snelling, D. M. Glass, and N. J. Bird. "Estimation of lean body mass in children." British Journal of Anaesthesia 106, no. 5 (May 2011): 719–23. http://dx.doi.org/10.1093/bja/aer057.

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14

Mongelli, Max. "Maternal Lean Body Mass and Birth-Weight." Australian and New Zealand Journal of Obstetrics and Gynaecology 36, no. 2 (May 1996): 133–35. http://dx.doi.org/10.1111/j.1479-828x.1996.tb03268.x.

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15

Forbes, Gilbert B. "Lean body mass on low calorie diets." American Journal of Clinical Nutrition 43, no. 1 (January 1, 1986): 173. http://dx.doi.org/10.1093/ajcn/43.1.173.

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16

Forbes, G. B. "Lean body mass on low calorie diets." American Journal of Clinical Nutrition 43, no. 1 (January 1, 1986): 173. http://dx.doi.org/10.1093/ajcn/43.1.173b.

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17

Peters, A. M., H. L. R. Snelling, D. M. Glass, and N. J. Bird. "Estimation of Lean Body Mass in Children." Survey of Anesthesiology 56, no. 1 (February 2012): 26–27. http://dx.doi.org/10.1097/01.sa.0000410700.55371.0f.

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18

Antonio, Jose. "Protein Bars May Enhance Lean Body Mass." Strength and Conditioning Journal 27, no. 4 (August 2005): 32–33. http://dx.doi.org/10.1519/00126548-200508000-00004.

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19

Crowder, Todd A., Daniel A. Jaffe, Jennifer K. Hewit, Matthew D. Magennis, Jenna M. Morogiello, and Guy D. Leahy. "Gender, Body Mass And Lean Body Mass Relationships On A Robust Fitness Challenge." Medicine & Science in Sports & Exercise 53, no. 8S (August 2021): 357–58. http://dx.doi.org/10.1249/01.mss.0000763404.43186.66.

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20

Shea, James R., Melissa H. Henshaw, Janet Carter, and Shahryar M. Chowdhury. "Lean body mass is the strongest anthropometric predictor of left ventricular mass in the obese paediatric population." Cardiology in the Young 30, no. 4 (March 16, 2020): 476–81. http://dx.doi.org/10.1017/s1047951120000311.

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AbstractBackground:Indexing left ventricular mass to body surface area or height2.7 leads to inaccuracies in diagnosing left ventricular hypertrophy in obese children. Lean body mass predictive equations provide the opportunity to determine the utility of lean body mass in indexing left ventricular mass. Our objectives were to compare the diagnostic accuracy of predicted lean body mass, body surface area, and height in detecting abnormal left ventricle mass in obese children.Methods:Obese non-hypertensive patients aged 4–21 years were recruited prospectively. Dual-energy X-ray absorptiometry was used to measure lean body mass. Height, weight, sex, race, and body mass index z-score were used to calculate predicted lean body mass.Results:We enrolled 328 patients. Average age was 12.6 ± 3.8 years. Measured lean body mass had the strongest relationship with left ventricular mass (R2 = 0.84, p < 0.01) compared to predicted lean body mass (R2 = 0.82, p < 0.01), body surface area (R2 = 0.80, p < 0.01), and height2.7 (R2 = 0.65, p < 0.01). Of the clinically derived variables, predicted lean body mass was the only measure to have an independent association with left ventricular mass (β = 0.90, p < 0.01). Predicted lean body mass was the most accurate scaling variable in detecting left ventricular hypertrophy (positive predictive value = 88%, negative predictive value = 99%).Conclusions:Lean body mass is the strongest predictor of left ventricular mass in obese children. Predicted lean body mass is the most accurate anthropometric scaling variable for left ventricular mass in left ventricular hypertrophy detection. Predicted lean body mass should be considered for clinical use as the body size correcting variable for left ventricular mass in obese children.
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21

Vanderburgh, P., and F. Katch. "VO2MAX PER BODY MASS PENALIZES THOSE WITH LARGER PERCENT BODY FAT, NOT LARGER LEAN BODY MASS." Medicine & Science in Sports & Exercise 27, Supplement (May 1995): S97. http://dx.doi.org/10.1249/00005768-199505001-00552.

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22

&NA;. "Somatropin increases lean body mass in elderly adults." Inpharma Weekly &NA;, no. 1365 (November 2002): 18. http://dx.doi.org/10.2165/00128413-200213650-00045.

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23

Nelson, Merlin V. "Estimation of lean body mass by bioelectrical impedance." American Journal of Clinical Nutrition 49, no. 1 (January 1, 1989): 184–85. http://dx.doi.org/10.1093/ajcn/49.1.184-a.

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24

Fowler, Sandra L., Philip Khoury, and Steven R. Daniels. "Lean Body Mass in Pediatric HIV Infection † 836." Pediatric Research 43 (April 1998): 145. http://dx.doi.org/10.1203/00006450-199804001-00857.

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25

Sood, M. "Lean body mass in children with cystic fibrosis." Archives of Disease in Childhood 88, no. 9 (September 1, 2003): 836—a—836. http://dx.doi.org/10.1136/adc.88.9.836-a.

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26

Roubenoff, Ronenn, and Joseph J. Kehayias. "The Meaning and Measurement of Lean Body Mass." Nutrition Reviews 49, no. 6 (April 27, 2009): 163–75. http://dx.doi.org/10.1111/j.1753-4887.1991.tb03013.x.

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27

Scott Petosa, P., and Michael F. Zupan. "Aerobic Training, Lean Body Mass, and Athletic Performance." STRENGTH AND CONDITIONING JOURNAL 17, no. 3 (1995): 11. http://dx.doi.org/10.1519/1073-6840(1995)017<0011:atlbma>2.3.co;2.

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28

WENDLING, PATRICE. "Drug Boosts Function, Lean Body Mass in Elderly." Internal Medicine News 39, no. 15 (August 2006): 36. http://dx.doi.org/10.1016/s1097-8690(06)73962-2.

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29

Manninen, Anssi H. "Very-low-carbohydrate diets and lean body mass." Obesity Reviews 7, no. 3 (August 2006): 297. http://dx.doi.org/10.1111/j.1467-789x.2006.00271.x.

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30

Campanozzi, Angelo, Myriam Dabbas, Jean Charles Ruiz, Claude Ricour, and Olivier Goulet. "Evaluation of lean body mass in obese children." European Journal of Pediatrics 167, no. 5 (July 6, 2007): 533–40. http://dx.doi.org/10.1007/s00431-007-0546-4.

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31

Dewi, Ni Putu Puspita Adhytiarini, Hardhono Susanto, and Ali Rosidi. "Hubungan tingkat kecukupan zat gizi, lean body mass, dan aktivitas fisik dengan kepadatan tulang pada mahasiswa Universitas Udayana Denpasar." Jurnal Gizi Indonesia (The Indonesian Journal of Nutrition) 4, no. 2 (December 30, 2016): 96–101. http://dx.doi.org/10.14710/jgi.4.2.96-101.

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Background: Bone formation and peak bone mass determine with bone density in adulthood related with osteopenia or osteoporosis. It could be influenced by nutrition intakes, lean body mass, and physical activity.Objective: to analyze the correlation between nutritional adequacy, lean body mass, physical activity and bone mineral density in Udayana University Economic’s students, Denpasar. Methods: Cross-sectional study design was done to female students of Faculty of Economic and Business, Udayana University, Denpasar. Seventy five subjects were choosen by simple random sampling. Results: Research subjects were aged 20-25 years old. The mean t-score of bone mineral density is -0,363 ± 1,057. Research subjects were classified as low bone density (osteopenia) 26,7% and 73,3% are normal. Intakes of animal protein (p = 0,042) and lean body mass (p = 0,011) are related with bone mineral density protein (p = 0,955) but not on intakes of vitamin A (p = 0,249), vitamin C (p = 0,632), vitamin D (p = 0,864), calcium (p = 0,724), iron (p = 0,768), magnesium (p = 0,689), phosphorus (p = 0,716), and physical activity (p = 0,254). There were a positive trend on the level of protein, vitamin A, vitamin C, vitamin D, calcium, iron, magnesium and phosphorus sufficiency.Conclusions: Intakes of Animal protein, lean body mass and physical activity related with bone mineral density but not on protein, vitamin A, vitamin C, vitamin D, calcium, iron, magnesium, and phosphorus intake.
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32

HATTORI, Komei. "Body Composition and Lean Body Mass Index for Japanese College Students." Journal of Anthropological Society of Nippon 99, no. 2 (1991): 141–48. http://dx.doi.org/10.1537/ase1911.99.141.

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33

De Graaf, Siebold S. N., Wilma P Meeuwsen-Van Der Roest, Heimen Schraffordt Koops, and Willem G. Zijlstra. "Dissociation of body weight and lean body mass during cancer chemotherapy." European Journal of Cancer and Clinical Oncology 23, no. 6 (June 1987): 731–37. http://dx.doi.org/10.1016/0277-5379(87)90270-7.

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34

Kerr, Deborah Anne, Shona Papalia, Alan Morton, Ian Dick, Satvinder Dhaliwal, and Richard L. Prince. "Bone Mass in Young Women Is Dependent on Lean Body Mass." Journal of Clinical Densitometry 10, no. 3 (July 2007): 319–26. http://dx.doi.org/10.1016/j.jocd.2007.05.001.

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35

Willoughby, Darryn, Susan Hewlings, and Douglas Kalman. "Body Composition Changes in Weight Loss: Strategies and Supplementation for Maintaining Lean Body Mass, a Brief Review." Nutrients 10, no. 12 (December 3, 2018): 1876. http://dx.doi.org/10.3390/nu10121876.

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With over two-thirds (71.6%) of the US adult population either overweight or obese, many strategies have been suggested for weight loss. While many are successful, the weight loss is often accompanied by a loss in lean body mass. This loss in lean body mass has multiple negative health implications. Therefore, weight loss strategies that protect lean body mass are of value. It is challenging to consume a significant caloric deficit while maintaining lean body mass regardless of macronutrient distribution. Therefore, the efficacy of various dietary supplements on body weight and body composition have been a topic of research interest. Chromium picolinate has been shown to improve body composition by maintaining lean body mass. In this paper we review some common weight loss strategies and dietary supplements with a focus on their impact on body composition and compare them to the effect of chromium picolinate.
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36

Kim, Seong Rae, Gyeongsil Lee, Seulggie Choi, Yun Hwan Oh, Joung Sik Son, Minseon Park, and Sang Min Park. "Changes in predicted lean body mass, appendicular skeletal muscle mass, and body fat mass and cardiovascular disease." Journal of Cachexia, Sarcopenia and Muscle 13, no. 2 (February 25, 2022): 1113–23. http://dx.doi.org/10.1002/jcsm.12962.

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37

Aoyama, Toru, Tsutomu Sato, Kenki Segami, Yukio Maezawa, Kazuki Kano, Taiichi Kawabe, Hirohito Fujikawa, et al. "Risk factors for loss of lean body mass after gastrectomy for gastric cancer." Journal of Clinical Oncology 34, no. 4_suppl (February 1, 2016): 79. http://dx.doi.org/10.1200/jco.2016.34.4_suppl.79.

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79 Background: Lean body mass loss after surgery, which decreases compliance of adjuvant chemotherapy, is frequently observed in gastric cancer patients who underwent gastrectomy for gastric cancer. However, the risk factors of lean body mass loss remain unclear. Methods: The present study retrospectively examined the patients who underwent curative gastrectomy for gastric cancer between June 2010 and March 2014 at Kanagawa Cancer Center. All patients received perioperative care of the enhanced recovery after surgery protocol. % Lean body mass loss was calculated by percentile of lean body mass at one month after surgery to preoperative lean body mass. Severe lean body mass loss was defined as % lean body mass loss over 5%. Risk factors for severe lean body mass loss were determined by both univariate and multivariate logistic regression analyses. Results: Four-hundred eighty five patients were examined. Median age was 67 years. Operative procedure was total gastrectomy in 190 patients and distal gastrectomy in 295 patients. Surgical complications of grade 2 or more defined by Clavien-Dindo classification was observed in 78 patients including pancreatic fistula in 19, anastomotic leakage in 11 and abdominal abscess in 7. Mortality was observed in one patient. Both univariate and multivariate logistic analyses demonstrated that surgical complications (odds rate 3.576, p = 0.001), total gastrectomy (odds rate 2.522, p = 0.0001), and gender (odds rate 1.928, p = 0.001) were significant independent risk factors for severe lean body mass loss. Conclusions: Male, surgical complications, and total gastrectomy were significant risk factors for 5% of lean body mass loss at first month after gastrectomy. To maintain lean body mass after gastrectomy, the physician need careful attention for the patients who had these risk factors.
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38

Madsen, O. R., A. Hartkopp, J. Micheelsen, J. Sylvest, and O. H. Sørensen. "Lean body mass, fat mass and bone mass in female long-distance runners." Bone 16, no. 3 (March 1995): 402. http://dx.doi.org/10.1016/8756-3282(95)90461-1.

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39

Wells, J. C. K. "Body composition in childhood: effects of normal growth and disease." Proceedings of the Nutrition Society 62, no. 2 (May 2003): 521–28. http://dx.doi.org/10.1079/pns2003261.

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Body composition in children is of increasing interest within the contexts of childhood obesity, clinical management of patients and nutritional programming as a pathway to adult disease. Energy imbalance appears to be common in many disease states; however, body composition is not routinely measured in patients. Traditionally, clinical interest has focused on growth or nutritional status, whereas more recent studies have quantified fat mass and lean mass. The human body changes in proportions and chemical composition during childhood and adolescence. Most of the weight gain comprises lean mass rather than fat. In general, interest has focused on percentage fat, and less attention has been paid to the way in which lean mass varies within and between individuals. In the general population secular trends in BMI have been widely reported, indicating increasing levels of childhood obesity, which have been linked to reduced physical activity. However, lower activity levels may potentially lead not only to increased fatness, but also to reduced lean mass. This issue merits further investigation. Diseases have multiple effects on body composition and may influence fat-free mass and/or fat mass. In some diseases both components change in the same direction, whereas in other diseases, the changes are contradictory and may be concealed by relatively normal weight. Improved techniques are required for clinical evaluations. Both higher fatness and reduced lean mass may represent pathways to an increased risk of adult disease.
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40

Halsne, Trygve, Ebba Glørsen Müller, Ann-Eli Spiten, Alexander Gul Sherwani, Lars Tore Gyland Mikalsen, Mona-Elisabeth Revheim, and Caroline Stokke. "The Effect of New Formulas for Lean Body Mass on Lean-Body-Mass–Normalized SUV in Oncologic 18F-FDG PET/CT." Journal of Nuclear Medicine Technology 46, no. 3 (March 29, 2018): 253–59. http://dx.doi.org/10.2967/jnmt.117.204586.

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41

Squillante, Antonio, Brady McCormick, Lorena Martin, and E. Todd Schroeder. "POWER OUTPUT AS A FUNCTION OF BODY MASS AND LEAN BODY MASS IN COMPETITIVE WEIGHTLIFTERS." Medicine & Science in Sports & Exercise 53, no. 8S (August 2021): 31. http://dx.doi.org/10.1249/01.mss.0000759416.35085.18.

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42

Davies, Michael J., Gail P. Dalsky, and Paul M. Vanderburgh. "Allornetric Scaling of VO2 Max by Body Mass and Lean Body Mass in Older Men." Journal of Aging and Physical Activity 3, no. 4 (October 1995): 324–31. http://dx.doi.org/10.1123/japa.3.4.324.

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This study employed allometry to scale maximal oxygen uptake (V̇O2max) by body mass (BM) and lean body mass (LBM) in healthy older men. Ratio standards (ml · kg−1· min−1) derived by dividing absolute V̇O2max (L · min−1) by BM or LBM often fail to control for the body size variable. The subjects were 73 older men (mean ±SD:age = 69.7 ± 4.3 yrs, BM = 80.2 ± 9.6 kg, height = 174.1 ± 6.9 cm). V̇O2max was assessed on a treadmill with the modified Balke protocol (V̇O2max = 2.2 ± 0.4 L · min−1). Body fat (27.7 ± 6.4%) was assessed with dual energy x-ray absorptiometry. Allometry applied to BM and V̇O2max determined the BM exponent to be 0.43, suggesting that heavier older men are being penalized when ratio standards are used. Allometric scaling applied to LBM revealed the LBM exponent to be 1.05 (not different from the ratio standard exponent of 1.0). These data suggest that the use of ratio standards to evaluate aerobic fitness in older men penalized fatter older men but not those with higher LBM.
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43

Crowder, T., and P. Vanderburgh. "SCALING OF PULL-UPS BY BODY MASS AND LEAN BODY MASS FOR YOUNG, FIT MEN." Medicine & Science in Sports & Exercise 27, Supplement (May 1995): S41. http://dx.doi.org/10.1249/00005768-199505001-00232.

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44

Liu, Xiaogang, Lan-Juan Zhao, Yong-Jun Liu, Dong-Hai Xiong, Robert R. Recker, and Hong-Wen Deng. "The MTHFR gene polymorphism is associated with lean body mass but not fat body mass." Human Genetics 123, no. 2 (January 8, 2008): 189–96. http://dx.doi.org/10.1007/s00439-007-0463-7.

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45

Bakshi, Anjani, Kalyani Singh, and Anupa Siddhu. "Body Composition of Chronic Kidney Disease Patients." Journal of Renal and Hepatic Disorders 5, no. 1 (June 30, 2021): 54–58. http://dx.doi.org/10.15586/jrenhep.v5i1.102.

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With accelerated muscle proteolysis, a decrease in muscle mass is evident in chronic kidney disease (CKD) patients. This eventually leads to nutritional disturbance that for a long has been mostly attributed to malnutrition. This predisposes patients to premature morbidity and mortality. Assessing body composition, thus, becomes vital. In this cross-sectional study, CKD patients (n = 47) of stages 2, 3a, 3b and 4 were assessed for their lean tissue mass, adipose tissue mass and overhydration by body composition monitor. Lean tissue index and fat tissue index were calculated as lean tissue mass and adipose tissue mass in kilogram divided by patients’ height in square meters. Patients were assessed for their handgrip strength (HGS) by Jamar hydraulic hand dynamometer, and also for their 7-day diet history. Mean lean tissue index of CKD patients was 11.73 ± 2.49 kg/m2. About 34 (72.3%) out of 47 patients were below the reference value of lean tissue index. A significant difference in lean tissue index (P = 0.03) was observed at various stages. Patients at stage 4 had the lowest lean tissue index. Lean tissue was significantly (P = 0.03) low in patients consuming protein <0.6 gm/kg/day. All 47 patients had less than normal HGS values. Patients’ mean fat tissue index was 14.86 ± 6.18 kg/m2 and had water retention with a mean overhydration of 1.47 ± 2.12 L. CKD patients were malnourished with a significant low lean tissue index. Dietary protein intake and HGS of these patients were positively associated with lean tissue index.
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46

Ribeiro, Sandra M. L., and Joseph J. Kehayias. "Sarcopenia and the Analysis of Body Composition1,2." Advances in Nutrition 5, no. 3 (May 1, 2014): 260–67. http://dx.doi.org/10.3945/an.113.005256.

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Abstract Reduction of lean mass is a primary body composition change associated with aging. Because many factors contribute to lean mass reduction, the problem has been given various names depending on the proposed cause, such as “age-related sarcopenia,” “dynapenia,” “myopenia,” “sarcopenic obesity,” or simply “sarcopenia.” There is currently no consensus on how to best diagnose the reduction of lean mass and its consequences on health. We propose that simple body composition methods can be used to indirectly evaluate sarcopenia, provided that those techniques are validated against the “quality of lean” criterion that associates muscle mass and metabolic function with the components of fat-free mass. Promising field methods include the use of stable isotopes for the evaluation of water compartments and new approaches to bioelectrical impedance analysis, which is also associated with the monitoring of water homeostasis.
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47

Barjaktarovic, Mirjana, Tim I. M. Korevaar, Romy Gaillard, Yolanda B. de Rijke, Theo J. Visser, Vincent W. V. Jaddoe, and Robin P. Peeters. "Childhood thyroid function, body composition and cardiovascular function." European Journal of Endocrinology 177, no. 4 (October 2017): 319–27. http://dx.doi.org/10.1530/eje-17-0369.

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Objective The cardiovascular system is a known target for thyroid hormone. Early-life cardiovascular alterations may lead to a higher risk of cardiovascular disease in adulthood. Little is known about the effects of thyroid hormone on cardiovascular function during childhood, including the role of body composition in this association. Design Population-based prospective cohort of children (n = 4251, median age 6 years, 95% range: 5.7–8.0 years). Methods Thyroid-stimulating hormone (TSH) and free thyroxine (FT4) concentrations were measured to assess thyroid function. Left ventricular (LV) mass was assessed with echocardiography. Arterial stiffness was assessed with carotid-femoral pulse wave velocity (CFPWV). Systolic and diastolic blood pressure (BP) was measured. Body composition was assessed by dual-energy X-ray absorptiometry scan. Results FT4 was inversely associated with LV mass (P = 0.002), and with lean body mass (P < 0.0001). The association of FT4 with LV mass was partially mediated through variability in lean body mass (55% mediated effect). TSH was inversely associated with LV mass (P = 0.010), predominantly in boys. TSH was positively associated with systolic and diastolic BP (both P < 0.001). FT4 was positively associated with CFPWV and diastolic BP (P < 0.0001, P = 0.008, respectively), and the latter association attenuated after adjustment for CFPWV. Conclusions At the age of 6 years, higher FT4 is associated with lower LV mass (partially through effects on lean body mass) and with higher arterial stiffness, which may lead to higher BP. Our data also suggest different mechanisms via which TSH and FT4 are associated with cardiovascular function during early childhood.
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48

Sanchez, Tom, Jingmei Wang, Chad Dudzek, George Ekker, and Kathy Dudzek. "Lean Body Mass, Not Total Body Size, is a Stronger Determinant of Total Body Bone Mass in Boys." Bone 46 (March 2010): S80. http://dx.doi.org/10.1016/j.bone.2010.01.196.

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49

Moquin, Paul A., Alexander B. Wetmore, Kevin M. Carroll, Andrew C. Fry, W. Guy Hornsby, and Michael H. Stone. "Lean Body Mass and Muscle Cross-Sectional Area Adaptations Among College Age Males with Different Strength Levels across 11 Weeks of Block Periodized Programmed Resistance Training." International Journal of Environmental Research and Public Health 18, no. 9 (April 29, 2021): 4735. http://dx.doi.org/10.3390/ijerph18094735.

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The block periodization training paradigm has been shown to produce enhanced gains in strength and power. The purpose of this study is to assess resistance training induced alterations in lean body mass and cross-sectional area using a block periodization training model among individuals (n = 15) of three differing strength levels (high, moderate and low) based on one repetition maximum back squat relative to body weight. A 3 × 5 mixed-design ANOVA was used to examine within-and between-subject changes in cross-sectional area (CSA), lean body mass (LBM), lean body mass adjusted (LBMadjusted) and total body water (TBW) over an 11-week resistance training program. LBMadjusted is total body water subtracted from lean body mass. The ANOVA revealed no statistically significant between-group differences in any independent variable (p > 0.05). Within-group effects showed statistically significant increases in cross-sectional area (p < 0.001), lean body mass (p < 0.001), lean body mass adjusted (p ˂ 0.001) and total body water (p < 0.001) from baseline to post intervention: CSA: 32.7 cm2 ± 8.6; 36.3 cm2 ± 7.2, LBM: 68.0 kg ± 9.5; 70.6 kg ± 9.4, LBMadjusted: 20.4 kg ± 3.1; 21.0 kg ± 3.3 and TBW: 49.8 kg ± 6.9; 51.7 kg ± 6.9. In conclusion, the results of this study suggest subjects experienced an increase in both lean body mass and total body water, regardless of strength level, over the course of the 11-week block periodized program. Gains in lean body mass and cross-sectional area may be due to edema at the early onset of training.
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50

Tracy, Richard E., and Gary E. Sander. "Histologically Measured Cardiomyocyte Hypertrophy Correlates with Body Height as Strongly as with Body Mass Index." Cardiology Research and Practice 2011 (2011): 1–9. http://dx.doi.org/10.4061/2011/658958.

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Cardiac myocytes are presumed to enlarge with left ventricular hypertrophy (LVH). This study correlates histologically measured myocytes with lean and fat body mass. Cases of LVH without coronary heart disease and normal controls came from forensic autopsies. The cross-sectional widths of myocytes in H&E-stained paraffin sections followed log normal distributions almost to perfection in all 104 specimens, with constant coefficient of variation across the full range of ventricular weight, as expected if myocytes of all sizes contribute proportionately to hypertrophy. Myocyte sizes increased with height. By regression analysis, height2.7as a proxy for lean body mass and body mass index (BMI) as a proxy for fat body mass, exerted equal effects in the multiple correlation with myocyte volume, and the equation rejected race and sex. In summary, myocyte sizes, as indexes of LVH, suggest that lean and fat body mass may contribute equally.
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