Relevant bibliographies by topics / Analysis body compositon

Academic literature on the topic 'Analysis body compositon'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Analysis body compositon"

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KARAK, KALIDAS, SK MITHUN SK MITHUN, and DR SAKTI RANJAN MISHRA. "A Comparative Analysis on the Level of Body Composition Among Active and Inactive Girls." Indian Journal of Applied Research 3, no. 12 (October 1, 2011): 493–94. http://dx.doi.org/10.15373/2249555x/dec2013/151.

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PIÑEDA GERALDO, ALDO, YULIANA GONZÁLEZ RINCÓN, PATRICIA ÁLVAREZ VEGA, and CARLOS VILLAREAL PEÑA. "SELECCIÓN Y ANÁLISIS DE ECUACIONES ANTROPOMÉTRICAS PARA EL CÁLCULO DE LA COMPOSICIÓN CORPORAL EN ADULTOS." Revista, Ingeniería, Matemáticas y Ciencias de la Información 4, no. 7 (January 10, 2017): 47–56. http://dx.doi.org/10.21017/rimci.2017.v4.n7.a21.

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Tutal, Emre, Mehtap Erkmen Uyar, Siren Sezer, Zeynep Bal, Tugba Bozkurt, Nurhan Özdemir Acar, and Mehmet Haberal. "The Relationship between Body Composition Analysis, Erythropoietin Requirements and Hemoglobin Variability in Hemodialysis Patients." Turkish Nephrology Dialysis Transplantation 24, no. 01 (January 26, 2015): 17–22. http://dx.doi.org/10.5262/tndt.2015.1001.03.

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Feher, Piroska, Dorina Annar, Annamaria Zsakai, and Eva Bodzsar. "The body composition analysis as a complementary tool in the screening of bone structural abnormalities." Anthropologischer Anzeiger 77, no. 2 (April 30, 2020): 161–71. http://dx.doi.org/10.1127/anthranz/2020/1136.

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Brewer, Gabrielle J., Malia N. M. Blue, Katie R. Hirsch, Austin M. Peterjohn, and Abbie E. Smith-Ryan. "Appendicular Body Composition Analysis." Journal of Strength and Conditioning Research 33, no. 11 (November 2019): 2920–25. http://dx.doi.org/10.1519/jsc.0000000000003374.

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NAKADOMO, FUMIO, KIYOJI TANAKA, HITOSHI WATANABE, KANJI WATANABE, and KAZUYA MAEDA. "ASSESSMENT OF BODY COMPOSITION BY BIOELECTRICAL IMPEDANCE ANALYSIS." Japanese Journal of Physical Fitness and Sports Medicine 40, no. 1 (1991): 93–101. http://dx.doi.org/10.7600/jspfsm1949.40.93.

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Borga, Magnus, Janne West, Jimmy D. Bell, Nicholas C. Harvey, Thobias Romu, Steven B. Heymsfield, and Olof Dahlqvist Leinhard. "Advanced body composition assessment: from body mass index to body composition profiling." Journal of Investigative Medicine 66, no. 5 (March 25, 2018): 1.10–9. http://dx.doi.org/10.1136/jim-2018-000722.

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This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy X-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat, in combination with rapid scanning protocols and efficient image analysis tools, makes quantitative MRI a powerful tool for advanced body composition assessment.
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Higgins, Michelle I., J. Peter Marquardt, Viraj A. Master, Florian J. Fintelmann, and Sarah P. Psutka. "Machine Learning in Body Composition Analysis." European Urology Focus 7, no. 4 (July 2021): 713–16. http://dx.doi.org/10.1016/j.euf.2021.03.013.

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SAMOYLOV, A. S., A. V. ZHOLINSKIY, N. V. RYLOVA, M. N. VELICHKO, I. V. BOLSHAKOV, A. V. BODROV, R. A. SIMONOV, and P. D. CHIZHIKOV. "Modern methods of body composition analysis." Practical medicine 20, no. 1 (2022): 21–26. http://dx.doi.org/10.32000/2072-1757-2022-1-21-26.

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The article provides an overview of the Russian and foreign literature on modern methods for analyzing body composition. Much attention is paid to the description of such common methods as the measurement of anthropometric parameters and bioimpedance analysis. Despite low accuracy, anthropometry is still one of the most popular methods for an approximate assessment of nutritional status. We also discuss in detail the most commonly used laboratory methods, such as dual-energy X-ray absorptiometry, computed tomography and magnetic resonance imaging, which can provide accurate and comprehensive information about the human body composition. The need for body composition analysis exists in such areas of clinical medicine as dietetics, nephrology, combustiology, surgery, cardiology, anesthesiology and resuscitation, etc. It was concluded that, depending on the goals and objectives in a particular clinical situation, various research methods and their combinations can be used.
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KAWAKATSU, MITSURU, and KAZUHISA SHIMOGAKI. "108. Body Composition Analysis by DEXA." Japanese Journal of Radiological Technology 47, no. 2 (1991): 219. http://dx.doi.org/10.6009/jjrt.kj00003322894.

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Dissertations / Theses on the topic "Analysis body compositon"

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Blakley, Alivia. "Validity of Various Bioelectrical Impedance Analysis Devices vs the Bod Pod for Body Composition." Cleveland State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=csu155934084847866.

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Biver, Deborah J. "Analysis of body composition with use of body impedance analysis and skinfold calipers : a correlation study /." View online, 1988. http://repository.eiu.edu/theses/docs/32211998878708.pdf.

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Aslani, Alireza. "Body composition analysis in the assessment of cancer cachexia treatment outcomes." University of Sydney, 2008. http://hdl.handle.net/2123/5293.

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Doctor of Philosophy
Introduction Cachexia is characterised by a marked weight loss and the presence of anorexia, anaemia, and asthenia. Although cachexia is often associated with the presence and growth of tumour and observed in solid tumours of the upper gastrointestinal tract, its presence is not unique to cancer and is often also present in most chronic, end-stage diseases processes. The loss of body fat, altered lipid metabolism, increase in the resting energy expenditure, and the increased loss of body protein the degree of which is associated with poor survival, are all hallmarks of this detrimental disease. The clinical aspects and consequences of cachexia can simply be summarised as morbidity, debilitating conditions, and mortality. The conditions such as loss of muscle mass, impaired muscle function, fatigue, reduced activity and functional capacity by themselves are enough to severely and significantly affect the patients’ QL. Although different interventional procedures and therapies are available for the treatment of cachexia and its symptoms, effective methods to evaluate their benefits and outcomes have not been tested or investigated. It was, therefore, the aim of this project to use body composition analysis as a clinical tool and evaluate the effectiveness and outcome of interventional and therapeutic procedures in three groups of patients with cancer. Methods Three patient groups were investigated: 1) patients with pancreatic cancer undergoing Whipple’s Procedure, 2) patients with pancreatic cancer undergoing cancer chemotherapy and receiving either EPA or placebo, and 3) patients with malignant mesothelioma undergoing cancer chemotherapy plus thalidomide or thalidomide alone. Body composition analysis techniques were used to assess the changes in TBN, TBF, TBK, and TBW. In addition, the body composition parameters together with clinical measures were also used to determine parameters influencing survival. The malignant mesothelioma patients were randomised into patients who received gemcitabine / cisplatin plus thalidomide and those who received thalidomide alone. The pancreatic cancer patients undergoing chemotherapy were randomised into the group who were receiving EPA and those who were receiving placebo. In addition, these patients were also investigated on the basis of their disease extent where they were separated into two groups of metastatic and locally advanced. Unpaired T-Test and ANOVA were used to determine differences between groups. Kaplan-Meier analysis and Cox’s Regression were used to assess survival in all three patient cohorts. The Whipple’s Procedure patients were separated into those who received a Clear Margin and those who received an Unclear Margin during their resection. Results 1) In the pancreatic cancer patients undergoing Whipple’s Procedure, compared to the base-line, there were highly significant changes in Weight (p=0.006), BMI (p=0.005), and FM (p=0.007) followed by significant changes in %BFat (p=0.016), TBK/Ht (p=0.021), LBM (By TBK) (p=0.023), LBM (Van Loan) (p=0.034), and LBM (Segal) (p=0.038) at the 14 week time-point. At the 26 weeks post-operative time point, the only significant changes were in the FM (p=0.012), %BFat (p=0.003), and BMI (p=0.027) parameters. There was also a deviation between the two groups in their TBN, LBM and TBW content observable in a long-term setting and fat content in the relatively shorter-term. Although the Unclear Margin group had lower body composition values, both groups seem to begin to gradually “equalise” around the 14 weeks post-operative time-point. The survival analysis results for the Whipple’s Procedure patients demonstrated that Margin Status (p=0.001), Fat Mass (p=0.003) and Age (p=0.081) were significant and could influence survival. 2) When the second cohort pancreatic cancer patients undergoing chemotherapy were analysed, they were initially separated according to the extent of their disease The results of the analyses of body composition changes between measurement time-points for the each group separately, suggested that the patients with locally advanced disease maintain their Weight, FM, and TBN but are more likely to have a lower TBW by the end of the four month of chemotherapy. However, the patients with metastatic pancreatic cancer maintain their TBW but are more likely to have a decreased fat compartment and a higher FFM. The QL analysis showed that the metastatic group are performing “worse” than the locally advanced group especially in term of their Dyspnoea, Nausea & Vomiting, and Sexuality. In addition, the Karnofsky score showed that the metastatic group are not performing as well as the locally advanced group. Furthermore, for the metastatic group there was an increase in the patients’ pain with a decline in mood and general performance as well as increase in gastrointestinal symptoms. Pain Card scores also showed a general increase for the metastatic group and a general decrease for the locally advanced group. When the pancreatic cancer patients undergoing chemotherapy were separated according to whether they received EPA or placebo, the results demonstrated that firstly, due to the fact that the patients were well randomised, the two groups commenced the trial with similar and statistically non-significantly different body composition parameters. Secondly, the two groups were also found to be statistically not different at their corresponding measurement time-points. And thirdly, the patients receiving placebo compared to those receiving EPA lost more Weight, and FM but less TBW throughout the trial. The TBK/Ht (p=0.044), TBK (p=0.042), and LBM (By TBK) (p=0.042), however, showed statistically significant differences where in all three parameters the EPA showed an increase compared to the base-line (pre-chemotherapy). Results of the survival analysis demonstrated that the use of EPA in this group of pancreatic cancer patients did not provide any benefit. In fact, as it was shown in the Kaplan-Meier plot, the group of patients receiving the EPA had a “worse” survival than the group receiving the placebo. The QL results showed that placebo group improved in their functional scales, but increased their Altered Bowel Habit scores with an increase in the perception of pain and decrease in relief from pain. The EPA group, however, showed a decrease in the Loss of Appetite, Dyspnoea, Pain, Pancreatic Pain, and Fatigue, and improvements in Role Functioning and Sexuality. 3) Results of the malignant mesothelioma patients demonstrated that both study arms show similar weight changes. In addition, body composition measurements indicated that the gemcitabine / cisplatin chemotherapy plus thalidomide group had a greater TBN loss and a greater TBW gain than the thalidomide-alone group. This loss of TBN and gain in TBW looked to be “concealed” in the weight. The results of the survival analysis carried out on the mesothelioma patient group suggested that haemoglobin levels (p=0.001), Age (p=0.007), and NI (p=0.008) are the parameters that can influence the survival of patients with malignant mesothelioma undergoing chemotherapy. Conclusions 1) The trend in body composition changes in the Whipple’s Procedure group showed that, although both groups may start with non-significantly different body composition, they tended to grow closer around the 14 week point indicating that the Clear Margin group may lose more than Unclear Margin group. The implications of these findings, therefore, were that once the most appropriate surgical procedure is performed, an adjuvant therapy regimen (such as chemotherapy) at around 14 weeks may have the most impact on the patient’s overall treatment outcome. 2) When the pancreatic cancer patients were separated by the extent of their disease, the results lead to the conclusion that the patients with locally advanced disease maintain their Weight, FM, and TBN but are more likely to have a lower TBW by the end of the four month of chemotherapy. However, the patients with metastatic pancreatic cancer maintain their TBW but are more likely to have a decreased fat compartment and a higher FFM. The QL analysis concluded that the results may point to a worsening and/or progressing disease which is consistent with classic metastatic disease aetiology. From the results of the pancreatic cancer patients undergoing cancer chemotherapy it was concluded that the use of EPA in this group of pancreatic cancer patients undergoing cancer chemotherapy with gemcitabine results in a non-significant reduction in weight loss, FM loss, and TBW gain with a statistically significant increase in FFM. The results of the survival analysis was, however, contradictory suggesting that patients receiving EPA may have a worse survival than the placebo group. The QL analysis here concluded that that EPA does improve the QL of this group of pancreatic cancer patients. 3) From the malignant mesothelioma group it was concluded that provided that the overall anti-cancer potential of gemcitabine / cisplatin plus thalidomide is comparable with that of thalidomide-alone, then by looking purely from the body composition angle one may be able to suggest the use of thalidomide alone in the treatment of malignant mesothelioma in this group of patients. From the results of the survival analysis, the fact that the Study Arm parameter did not reach statistical significance could indicate that survival in these patients is not affected by the presence or absence of chemotherapy with gemcitabine and cisplatin. The body composition techniques were used here as a tool to monitor changes in various body composition parameters to assess the outcomes, including survival, of the administration of different therapies and interventional procedures in these three groups of cancer patients. For these purposes, these techniques were demonstrated to be an effective and invaluable tool.
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Duncan, Michael Bennett. "The use of bioelectrical impedance analysis for estimating the body composition of various fish species." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/31531.

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The reliable measurement of growth and condition is vital for effective fisheries assessments. Biologists have long attempted to estimate condition for their assessments, but a reliable method to nonlethally estimate body composition is lacking. Proximate analysis is the most dependable and accurate method for estimating internal composition, but it is lethal, time consuming, and expensive. Recent research has shown bioelectrical impedance analysis (BIA) to be an effective method for estimating proximate composition in some fishes. The technique is quick, inexpensive, and, most importantly, nonlethal, which is vital when examining endangered species or cultured fish. My research focused on developing BIA indices for several new species of fish, using those indices to evaluate the body composition of fish in the field, and determining whether water temperature influenced resistance and reactance measurements. I found that BIA accurately estimated the body composition of bluegill Lepomis macrochirus, redear sunfish Lepomis microlophus, brook trout Salvelinus fontinalis, and northern logperch Percina caprodes (r2 â ¥ 0.71, p < 0.0001). I also determined that bluegill and redear regressions were not significantly different (P â ¥ 0.10) suggesting they can be used interchangeably during future studies. Laboratory studies revealed that water temperature did not significantly influence resistance and reactance measurements of bluegill, redear, and largemouth bass Micropterus salmoides (P â ¥ 0.18). These results, along with previous literature, indicate that BIA may be an accurate and reliable assessment tool for fisheries biologists.
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Radley, Duncan. "Body composition analysis : evaluation of methods in adolescents of varying fatness." Thesis, Leeds Beckett University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485476.

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Introduction The objectives of the present study were twofold: 1) to investigate the cross-sectional and longitudinal accuracy of percentage body fat (%fat) estimates from laboratory methods and field methods in a sample of mainly overweight and obese adolescents; and 2) to examine the use of each method to assess the effectiveness of the Carnegie International Weight Loss Camp (CIC) intervention. ABSTRACT / / Methods The laboratory methods: dual-energy X-ray absorptiometry (OXA), air displacement plethysmography (AOPSiri. AOPLoh), total body water (TBW73, TBWLoh) , threecompartment mineral model (3CMin) and three-compartment total body water model (3CrBw), and the field methods: skinfold thicknesses (SKFs), bie-electrical impedance analysis (BIA) and four-compartment bie-electrical impedance model (4CB1A) were evaluated against a criterion four-compartment model (4CLoh). 76 adolescents participated in the cross-sectional study, age (mean ± SO) 14.0 ± 1.6 y, body mass index 30.0 ±6.7 kg.m-2 and %fat (4C model) 36.9 ± 11.9%. 13 children attending the CIC (campers), 14 overweight comparison group children (OWCG) and 8 normal weight comparison group children (NWCG) participated in the longitudinal and intervention evaluation study. Results Cross-sectional analysis of laboratory methods, in all subjects, revealed mean percentage body fat (%fat) determined by 3CrBW (37.0 ± 11.8%) and 3CMin (36.8 ± 12.9%) were within ± 0.5% of that determined by 4CLoh (36.9 ± 11.9%). %Fat determined by AOPsiri (38.0 ± 12.4%), AOPLoh (36.0 ± 12.8%), TBW73 (35.8 ± 11.7) and TBWLoh (37.6 ± 11.4%) were within between ± 0.7% and ± 1.2% of that determined by 4CLoh, whilst OXA overestimated %fat by 3.6%. Considering individual agreement 3CrBW revealed the lowest 95% limits of agreement (± 1.1%) followed by values between ± 3.6% and ±7.2% for all other methods. Cross-sectional analysis of field methods, in all subjects, revealed mean %fat determined by 4CBIA (36.2 ± 12.8%) and 1 BIA prediction equation were within ± 0.5% of that determined by 4CLoh %fat (35.9 ± 12.5%). %Fat determined by 3 BIA prediction equations were within between ± 0.8% and ± 1.8% of that determined by 4CLoh , whilst all other methods differed by between ± 2.4% and ± 6.0%. Considering individual agreement 4CB1A revealed the lowest 95% limits of agreement (± 3.2%) and SKFs the greatest (± 15.6%). The 95% limits of agreement for all other BIA prediction equations ranged from ± 7.9% to ± 12.8%. Longitudinal analysis of laboratory methods, by group, revealed a less than ± 1% mean difference to 4CLoh %fat delta values in all cases except by 3CMin, TBW73 and TSWLoh in Campers, 3CMin in the OWCG and DXA in the NWCG. Considering individual agreement the lowest 95% limits of agreement were produced by 3CrBW.(± 0.6% to ±1.0%) and the highest by DXA (%fat ±4.2% to ±5.9). Longitudinal analysis of field methods, by group, revealed a less than ± 1% mean difference to 4CLoh %fat delta values in all cases except 2 BIA prediction equations and SKFs in Campers, but a greater than ± 1% mean difference in all cases in the OWCG and NWCG with the exception of SKFs in the NWCG. In all cases the lowest 95% limits of agreement were produced by 4CB1A (%fat ± 1.8% to ± 6.2%). Evaluation of the CIC intervention revealed that 3CrBW was the only method to show agreement with the 4C model findings of a significant difference between each group. Discussionl Conclusion The present study demonstrates that a number of methods were able to provide accurate mean but not individual cross-sectional and longitudinal body composition estimates compared to a criterion 4C 'model. In general laboratory methods provided more accurate estimates than field methods. In addition, the study highlights 3CTBW as an accurate alternative to 4C' model analysis in lean, overweight and obese adolescents when very accurate individual estimates are required. Similarly, when evaluating changes in an intervention compared to control groups using only a small number of participants the 3CrBW model is the most accurate altemative method. Findings from the present study also highlight caution is warranted when interpreting data, both cross-sectionally and longitudinally, without careful attention to and understanding of t~e theoretical underpinnings of the method being used.
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Company, Joe Ball Stephen D. "Body composition comparison bioelectric impedance analysis with DXA in adult athletes /." Diss., Columbia, Mo. : University of Missouri--Columbia, 2008. http://hdl.handle.net/10355/5697.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on September 16, 2009). Thesis advisor: Dr. Steve Ball. Includes bibliographical references.
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Fallah, Shokr. "Application of bioelectrical impedance analysis to detect body composition of athletes." Thesis, Queensland University of Technology, 2003.

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HOUTKOOPER, LINDA BRAUNSCHMIDT. "VALIDITY OF WHOLE-BODY BIOELECTRICAL IMPEDANCE ANALYSIS FOR BODY COMPOSITION ASSESSMENT IN NONOBESE AND OBESE CHILDREN AND YOUTH." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183914.

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Whole-body bioelectrical impedance analysis (BIA) was evaluated for its reliability and accuracy in estimating body composition in children and youth. The established electrical principle for estimating volume in a geometrical system from conductor-length('2) divided by impedance is the basis for the use of this method in humans. The hypothesis that body-height('2) divided by the resistance component of impedance (resistance index) can be used to estimate total body water (TBW), fat free body (FFB), and percent fat (%FAT) was tested. Validation studies in adults indicate BIA is a reliable and fairly accurate method of estimating TBW, FFB, and %FAT but no testing has been completed on children. The subjects were 103 nonobese and obese anglo males and females from 10 to 14 years old. Within-day reliability of resistance and reactance was assessed by analysis of variance with built-in comparisons. Between-day reliability for all measurements, made four to five weeks apart, was evaluated by test-retest correlation coefficients and paired t-tests. The criterion variables were FFB and %FAT estimated using equations developed for children and youth based on: (1) skinfolds, (2) body density, (3) TBW, (4) density and TBW, (5) density, TBW, and bone mineral content. Regression and multiple regression analyses were used to select the most accurate method of measuring FFB and %FAT and to determine the relationship among criterion variables and the following independent variables: resistance index alone and combined with sex, fatness category, sex x fatness, age, sexual maturation status, weight, anthropometric variables, and reactance. From this study the following conclusions were made: (1) BIA measurements were reliable, (2) resistance index had a linear relationship with FFB estimated from several criterion variables, (3) weight, sex, fatness category, sex x fatness, age, and sexual maturation status were significant variables for predicting criterion variables used in combination with resistance index but were not significant when anthropometric variables were included in the analysis, (4) prediction accuracy for FFB and %FAT from resistance index was fair (SEE 2.58 kg and 4.21%) and from resistance index plus anthropometric variables and reactance was good (SEE 1.88 kg and 3.26%) and similar to that from the best anthropometric variables alone (SEE 2.11 kg and 3.19%).
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Kelley, Edward T. II. "Comparative Analysis of Obesity Classification Methods in Aging Adults." Bowling Green State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1429283749.

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Jensen, Björn [Verfasser], Anja [Akademischer Betreuer] Bosy-Westphal, and Claus-C. [Gutachter] Glüer. "Bioelectrical impedance analysis in the assessment of body composition – methodological considerations / Björn Jensen ; Gutachter: Claus-C. Glüer ; Betreuer: Anja Bosy-Westphal." Kiel : Universitätsbibliothek Kiel, 2020. http://d-nb.info/1211649288/34.

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Books on the topic "Analysis body compositon"

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Gordner, Ronald L. Bioelectric impedance analysis in body composition measurement: January 1989 through December 1994 : 627 citations. Bethesda, Md: U.S. Dept. of Health and Human Services, Public Health Service, National Institutes of Health, National Library of Medicine, Reference Section, 1994.

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Heritage, Ford. Composition and facts about foods and their relationship to the human body. Pomeroy, WA: Health Research, 1993.

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André, Haeberli, ed. Human protein data. Weinheim: Wiley-VCH, 1998.

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service), SpringerLink (Online, ed. SUSHI Food for the eye, the body & the soul. 2nd ed. Boston, MA: Springer-Verlag US, 2009.

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Age estimation of the human skeleton. Springfield, Ill: Charles C. Thomas Publisher, Ltd., 2010.

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Lawman's Brut, an early Arthurian poem: A study of Middle English formulaic composition. Lewiston [N.Y.]: E. Mellen Press, 1991.

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R, Speakman J., ed. Body composition analysis of animals. Cambridge: Cambridge University Press, 2001.

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Speakman, John R., ed. Body Composition Analysis of Animals. Cambridge University Press, 2001. http://dx.doi.org/10.1017/cbo9780511551741.

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Sherbeeny, Samy Mohamed El. Validation of selected regression equations for predicting body density, body fat percentage, lean body weight, and body fat weight. 1985.

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(Editor), J. G. Kral, and T. B. VanItallie (Editor), eds. Recent Developments in Body Composition Analysis. Smith-Gordon & Co Ltd, 1993.

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Book chapters on the topic "Analysis body compositon"

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Bonnick, Sydney Lou, and Lori Ann Lewis. "Body Composition Analysis." In Bone Densitometry for Technologists, 341–61. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3625-6_14.

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Brunton, Janet A., Henry S. Bayley, and Stephanie A. Atkinson. "Body Composition Analysis by Dual Energy X-Ray Absorptiometry Compared to Chemical Analysis of Fat, Lean and Bone Mass in Small Piglets." In Human Body Composition, 157–60. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_35.

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Mitchell, Alva D., Paul C. Wang, Hua F. Song, and Walter F. Schmidt. "Body Composition Analysis of the Pig by Magnetic Resonance Imaging." In Human Body Composition, 105–8. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_24.

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Gartner, Agnès, Bernard Maire, Francis Delpeuch, Pierre Sarda, Renée Pierre Dupuy, and Daniel Rieu. "The Use of Bioelectrical Impedance Analysis in Newborns. The Need for Standardization." In Human Body Composition, 165–68. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_37.

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Wang, Jack, F. Avraham Dilmanian, John Thornton, Mary Russell, Santiago Burastero, Manolo Mazariegos, Steven B. Heymsfield, and Richard N. Pierson. "In Vivo Neutron Activation Analysis for Body Fat: Comparisons by Seven Methods." In Human Body Composition, 31–34. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_5.

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Wyatt, Ruth M., Simon J. S. Ryde, Andrew J. Williams, Colin J. Evans, Elizabeth A. McNeil, and Wynford D. Morgan. "Development of an in Vivo Neutron Activation Analysis Technique to Measure Bone Aluminum." In Human Body Composition, 319–21. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_71.

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Wilson, David C., Janice M. E. Day, Ann Hamilton, Garth McClure, and Peter S. W. Davies. "Noninvasive Methods of Body Composition Analysis in Preterm Infants:- Comparison with Dilution of 2H2 18O." In Human Body Composition, 133–38. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_30.

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Tzotzas, Themistoklis, Georgios Karanikas, and Gerasimos E. Krassas. "Body Composition Analysis Using Radionuclides." In Handbook of Anthropometry, 185–203. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-1788-1_10.

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Borga, Magnus, André Ahlgren, and Sarah Weston. "MRI-Based Body Composition Analysis." In Basic Protocols in Foods and Nutrition, 307–34. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2345-9_19.

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Cunnane, Stephen C., Tim Allman, Jimmy Bell, Maria J. Barnard, Glynn Coutts, Stephen C. R. Williams, and Richard A. Iles. "In Vivo Fatty Acid Analysis in Humans and Animals Using Carbon-13 Nuclear Magnetic Resonance Spectroscopy." In Human Body Composition, 355–58. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_83.

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Conference papers on the topic "Analysis body compositon"

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Berg, Vanessa S., Dale S. Preece, Jerome H. Stofleth, and Mathew A. Risenmay. "Kevlar and Carbon Composite Body Armor: Analysis and Testing." In ASME 2005 Pressure Vessels and Piping Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pvp2005-71433.

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Kevlar materials make excellent body armor due to their fabric-like flexibility and ultra-high tensile strength. Carbon composites are made up from many layers of carbon AS-4 material impregnated with epoxy. Fiber orientation is bidirectional, orientated at 0° and 90°. They also have ultra-high tensile strength but can be made into relatively hard armor pieces. Once many layers are cut and assembled they can be ergonomicically shaped in a mold during the heated curing process. Kevlar and carbon composites can be used together to produce light and effective body armor. This paper will focus on computer analysis and laboratory testing of a Kevlar/carbon composite cross-section proposed for body armor development. The carbon composite is inserted between layers of Kevlar. The computer analysis was performed with a Lagrangian transversely isotropic material model for both the Kevlar and Carbon Composite. The computer code employed is AUTODYN. Both the computer analysis and laboratory testing utilized different fragments sizes of hardened steel impacting on the armor cross-section. The steel fragments are right-circular cylinders. Laboratory testing was undertaken by firing various sizes of hardened steel fragments at square test coupons of Kevlar layers and heat cured carbon composites. The V50 velocity for the various fragment sizes was determined from the testing. This V50 data can be used to compare the body armor design with other previously designed armor systems. AUTODYN [1] computer simulations of the fragment impacts were compared to the experimental results and used to evaluate and guide the overall design process. This paper will include the detailed transversely isotropic computer simulations of the Kevlar/carbon composite cross-section as well as the experimental results and a comparison between the two. Conclusions will be drawn about the design process and the validity of current computer modeling methods for Kevlar and carbon composites.
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Kullberg, Joel. "Whole-body MRI for analysis of body composition." In 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE, 2010. http://dx.doi.org/10.1109/isbi.2010.5490175.

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González-Solís, J. L. "Study of Body Composition by Impedance Analysis." In MEDICAL PHYSICS: Sixth Mexican Symposium on Medical Physics. AIP, 2002. http://dx.doi.org/10.1063/1.1512062.

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González-Solís, J. L., M. Vargas-Luna, M. Sosa-Aquino, J. Bernal-Alvarado, G. Gutiérrez-Juárez, R. Huerta-Franco, A. Sanchis-Sabater, Luis Manuel Montaño Zentina, and Gerardo Herrera Corral. "Study of Body Composition by Impedance Analysis." In MEDICAL PHYSICS: Sixth Mexican Symposium on Medical Physics. AIP, 2011. http://dx.doi.org/10.1063/1.3682870.

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Chetan, Mihai. "Body composition monitoring through bioelectrical impedance analysis." In 2015 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE). IEEE, 2015. http://dx.doi.org/10.1109/atee.2015.7133826.

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Ivanov, Danail, Iva Dimova, Milen Gadjev, and Ivan Stoilov. "BODY COMPOSITION ANALYSIS OF YOUTH FOOTBALL PLAYERS." In INTERNATIONAL SCIENTIFIC CONGRESS “APPLIED SPORTS SCIENCES”. Scientific Publishing House NSA Press, 2022. http://dx.doi.org/10.37393/icass2022/44.

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ABSTRACT Football is the most popular game and is one of the most dynamically developing sport regarding training means, methods, and use of technologies. We are witnessing constant improvement of sport selection, increasing dynamics in both training process and speed of playing, etc. We find a lot of information regarding body composition of elite football players, but such information for adolescents is fragmentary. The aim of the following study is to reveal real data of youth football players using special equipment (In Body 270) measuring in total 13 indexes. Respondents are players from the youth academy of PCS “Levski” Sofia in U13, U14 and U15 teams. All data is subject to statistical and expert analysis. The total number of respondents is 57 divided by three age groups. The fundamental anthropometric indexes height and weight reveal logical increase as follows: average height increases from 159 cm (U13), 167 cm (U14) to reach 175 cm (U15). The corresponding average weight vary between 45,9 kg (U13) to 62,1 kg (U15). One of the easiest to measure index is BMI have average values for studied teams as follows: 17,9 (U13), 19,0 (U14) and 20,3 (U15). All other indexes as body fat, skeletal and muscle weight are analyzed in detail for the three age groups. Based on received data and the development of evaluation tables we can control objectively body composition of youth football players. This way we can improve sport selection and training process. All experimental data must be used applying the individual approach for assessing the anthropometric and sexual development of the player.
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Pawar, Archana A., D. K. Kamat, and P. M. Patil. "Body composition analysis using various anthropometric equations." In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017. http://dx.doi.org/10.1109/icecds.2017.8390040.

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Li, Victor. "Hybrid Wing Body (HWB) Aircraft Design and Optimization using Stitched Composites." In 16th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-2325.

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RAMAKRISHNAN, MONISH URAPAKAM, and PANKAJ K. MALLICK. "CRUSH CHARACTERISTICS OF ADHESIVELY BONDED COMPOSITE-ALUMINUM TUBES." In Thirty-sixth Technical Conference. Destech Publications, Inc., 2021. http://dx.doi.org/10.12783/asc36/35837.

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Tubular members are used in the automotive industry for body, chassis, and powertrain components such as front rails, underbody frames or sub frames, driveshaft structures and space frames. They are also extensively used in buses and other heavy vehicle structures. With focus on light-weighting, there is increasing use of multimaterial structures with aluminum and high-performance composites. Joining a variety of materials with different characteristics and compositions is a major challenge for the design of such structures. Hence, adhesive bonding is emerging as one of the key joining technique for multi-material structures due to their compatibility with commonly used lightweight materials. Since tubular joints in automotive structures may experience crush type load, this study considers the crush characteristics of composite-aluminum tubular adhesive joints using finite element analysis.
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Pradhan, Ligaj, Gao Song, Chengcui Zhang, Barbara Gower, Steven B. Heymsfield, David B. Allison, and Olivia Affuso. "Feature Extraction from 2D Images for Body Composition Analysis." In 2015 IEEE International Symposium on Multimedia (ISM). IEEE, 2015. http://dx.doi.org/10.1109/ism.2015.117.

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Reports on the topic "Analysis body compositon"

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Gummin, David D. Body Composition Analysis in U.S. Navy Divers. Fort Belvoir, VA: Defense Technical Information Center, March 2001. http://dx.doi.org/10.21236/ada407354.

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Gummin, D. D. Body Composition Analysis in U.S. Navy Divers. Fort Belvoir, VA: Defense Technical Information Center, June 2000. http://dx.doi.org/10.21236/ada453110.

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Liechti, Melanie, Massimo Menegon, Alexander Schurz, Nathanael Lutz, and Jan Taeymans. Association between pain intensity and body composition in adults with chronic low back pain: A Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2022. http://dx.doi.org/10.37766/inplasy2022.12.0064.

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Review question / Objective: Is there an association between pain intensity and body composition in chronic low back pain patients? Condition being studied: Evaluation of adults with chronic non-specific low back pain and the association between pain intensity and body composition, including measures of body mass index, waist circumference, waist hip ratio, fat mass, fat distribution or adipose tissue. Information sources: Pubmed, CINAHL, Embase, The Cochrane Library and Web of Science. Google Scholar will be used for grey literature. No trail registers will be screened.
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Geisler, Corinna, Mark Hübers, and Manfred Müller. Assessment of adult malnutrition with bioelectrical impedance analysis. Universitatsbibliothek Kiel, September 2018. http://dx.doi.org/10.21941/manueltask13.

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The two aims of this study were to evaluate (i) the prevalence of malnutrition based on age, sex and BMI specific PA and (ii) to determinate what specific body composition characteristics (skeletal muscle mass and adipose tissue) are related to a low PA.
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Rodrigues-Santana, Luiz, Jose Adsuar, Hugo Louro, Jorge Pérez-Gómez, Miguel Hernández-Mocholí, Jorge Carlos-Vivas, Rossana Gomez-Campos, and Luis Castelli Correia de Campos. The Effects of Whole Body Muscle Stimulation on body composition and strength parameters. A protocol for systematic review and meta analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2021. http://dx.doi.org/10.37766/inplasy2021.2.0050.

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Li, Xinyu, Jiaqi Wang, Jinyu Zhang, Nan Zhang, Caiqin Wu, Zhaohui Geng, Jie Zhou, and Lu Dong. Exercise effect on weight and body composition for breast cancer patients undergoing chemotherapy: A Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2021. http://dx.doi.org/10.37766/inplasy2021.5.0016.

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Chang, Yuwen, Tingting Du, Xiangling Zhuang, and Guojie Ma. Time-restricted eating can lead to weight loss due to energy restriction: A systematic review and meta-analysis based on randomized, controlled trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2022. http://dx.doi.org/10.37766/inplasy2022.10.0098.

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Review question / Objective: P: Adults with overweight or obesity; I: Time restricted eating with eating window less than 10 hours and with or without calorie restriction; C: People with eating window more than 12 hours; O: Weight loss, body composition, metabolic risk factors, energy intake and eating window. Condition being studied: Adults with overweight and obesity. Information sources: We search four databases including PubMed, Embase, Scopus and the Cochrane library.
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Joaquim, Ana, Inês Leão, Pedro Antunes, Andreia Capela, Sofia Viamonte, Alberto Alves, Luísa Helguero, and Ana Macedo. Impact of physical exercise programs in breast cancer survivors on health-related quality of life, physical fitness, and body composition: evidence from systematic reviews and meta-analyses. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0053.

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Review question / Objective: In breast cancer survivors, what is the effect of physical exercise interventions compared to control on health-related quality of life, physical fitness, and body composition? Condition being studied: Breast cancer. Eligibility criteria: Inclusion criteria: full-length articles in English with clinical observations of humans, with a clearly defined clinical question, details of inclusion and exclusion criteria, details of searched databases and relevant search strategies, and a summary of results, per group, for at least one of the desired outcomes.
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Chen, HongPeng, and YuQian Zhao. Effects of vitamin D supplementation on body composition, glucose metabolism, and inflammation in obese or overweight patients: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2022. http://dx.doi.org/10.37766/inplasy2022.3.0152.

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Tian, Siyu. The effects of resistance exercise on body composition and physical function in prostate cancer patients undergoing androgen deprivation therapy: An update systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0019.

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