Aplicabilidade de equações na avaliação da composição corporal da população brasileira

Rezende, Fabiane Aparecida Canaan; Rosado, Lina Enriqueta Frandsen Paez de Lima; Priore, Sílvia Eloíza; Franceschini, Sylvia do Carmo Castro

doi:10.1590/s1415-52732006000300007

Cited by 18 publications

(13 citation statements)

References 31 publications

(60 reference statements)

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“…These results are particularly important, given that excess adipose tissue and mainly its accumulation in the abdominal region is associated with several undesirable metabolic diseases (34). WC has been pointed as the best anthropometric indicator of visceral fat accumulation.…”

Section: Discussionmentioning

confidence: 99%

Effect of glycemic index on obesity control

Pereira

Costa

Alfenas

2015

Arch. Endocrinol. Metab.

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Objective: Evaluate the effect of glycemic index (GI) on biochemical parameters, food intake, energy metabolism, anthropometric measures and body composition in overweight subjects. Materials and methods: Simple blind study, in which nineteen subjects were randomly assigned to consume in the laboratory two daily low GI (n = 10) or high GI (n = 9) meals, for forty-five consecutive days. Habitual food intake was assessed at baseline. Food intake, anthropometric measures and body composition were assessed at each 15 days. Energy metabolism and biochemical parameters were evaluated at baseline and the end of the study. Results: Low GI meals increased fat oxidation, and reduced waist circumference and HOMA-IR, while high GI meals increased daily dietary fiber and energy intake compared to baseline. There was a higher reduction on waist circumference and body fat, and a higher increase on postprandial fat oxidation in response to the LGI meals than after high GI meals. High GI meals increased fasting respiratory coefficient compared to baseline and low GI meals. Conclusion: The results of the present study showed that the consumption of two daily low GI meals for forty-five consecutive days has a positive effect on obesity control, whereas, the consumption of high GI meals result has the opposite effect. Arch Endocrinol Metab. 2015;59(3):245-51

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Section: Discussionmentioning

confidence: 99%

Effect of glycemic index on obesity control

Pereira

Costa

Alfenas

2015

Arch. Endocrinol. Metab.

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“…However, for being a two-compartment model for assessing body composition, the predictive equations of body fat do not allow a specific measurement of the amount of muscle mass and especially the AMM for diagnosing sarcopenia. Therefore, several models of predictive equations to assess AMM have been developed in samples composed of individuals with specific characteristics [33-35]; therefore for use in a general way or in other populations, these models must be validated [33,36-38]. …”

Section: Introductionmentioning

confidence: 99%

Development and validation of anthropometric equations to estimate appendicular muscle mass in elderly women

Pereira

Silva

Santos

et al. 2013

Nutr J

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ObjectiveThis study aimed to examine the cross validity of two anthropometric equations commonly used and propose simple anthropometric equations to estimate appendicular muscle mass (AMM) in elderly women.MethodsAmong 234 physically active and functionally independent elderly women, 101 (60 to 89 years) were selected through simple drawing to compose the study sample. The paired t test and the Pearson correlation coefficient were used to perform cross-validation and concordance was verified by intraclass correction coefficient (ICC) and by the Bland and Altman technique. To propose predictive models, multiple linear regression analysis, anthropometric measures of body mass (BM), height, girth, skinfolds, body mass index (BMI) were used, and muscle perimeters were included in the analysis as independent variables. Dual-Energy X-ray Absorptiometry (AMMDXA) was used as criterion measurement. The sample power calculations were carried out by Post Hoc Compute Achieved Power. Sample power values from 0.88 to 0.91 were observed.ResultsWhen compared, the two equations tested differed significantly from the AMMDXA (p <0.001 and p = 0.001). Ten population / specific anthropometric equations were developed to estimate AMM, among them, three equations achieved all validation criteria used: AMM (E2) = 4.150 +0.251 [bodymass (BM)] - 0.411 [bodymass index (BMI)] + 0.011 [Right forearm perimeter (PANTd) 2]; AMM (E3) = 4.087 + 0.255 (BM) - 0.371 (BMI) + 0.011 (PANTd) 2 - 0.035 [thigh skinfold (DCCO)]; MMA (E6) = 2.855 + 0.298 (BM) + 0.019 (Age) - 0,082 [hip circumference (PQUAD)] + 0.400 (PANTd) - 0.332 (BMI). The equations estimated the criterion method (p = 0.056 p = 0.158), and explained from 0.69% to 0.74% of variations observed in AMMDXA with low standard errors of the estimate (1.36 to 1.55 kg) and high concordance (ICC between 0,90 and 0.91 and concordance limits from -2,93 to 2,33 kg).ConclusionThe equations tested were not valid for use in physically active and functionally independent elderly women. The simple anthropometric equations developed in this study showed good practical applicability and high validity to estimate AMM in elderly women.

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“…This technique is used by health professionals in clinical practice with the objective of recording body measurements such as weight, height, skinfolds and body circumferences 16 . When linked to indexes or predictive equations, these body measurements, also referred to as anthropometric indicators, can provide information on the quantity of the individual's fat mass 17,18 . Several studies have been carried out with the objective of investigating the accuracy of anthropometric measurements in the description of body fat quantity in different populations, justified by the need to gather measurements in a shorter timeframe, with lower cost and greater simplicity [19][20][21][22] .…”

Section: Introductionmentioning

confidence: 99%

Can anthropometry measure the body fat of people living with HIV/AIDS?: A systematic review

Guimarães

Fausto

Kakehasi

et al. 2017

Rev Esp Nutr Hum Diet

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Introduction: Assessment of the quantity and distribution of body fat in people living with HIV/AIDS is of great importance in clinical practice, due to the association of body fat changes with clinical conditions. The aim of this systematic review was to answer the central question: Can anthropometry accurately measure the body fat in people living with HIV/AIDS? Material and Methods: Systematic review carried out using four databases: Medline, LILACS, Scopus and BDTD. Results:Of the 581 studies found, 11 met the eligibility criteria. To assess the validate of anthropometry, only two studies employed regress analysis to development of predictive body fat equations in people living with HIV/AIDS and nine studies employed correlation analysis. This coefficient only measures the strength of the relation between two variables, and there is not concordance between them and therefore, these studies did not accurately evaluate whether or not the anthropometric information showed good concordance with the gold standard. The other two studies developed five equations to evaluate the total fat and limbs (arm, leg and trunk) in people living with HIV/AIDS using antiretrovirals and showed R 2 between 0.50 and 0.83. Conclusions:Further research needs to be conducted to answer the central question of this review, as the small number of articles that applied the correct statistical test and the absence of research on people living with HIV/AIDS without the use of antiretrovirals. Más información: http://creativecommons.org/licenses/by-nc-sa/4.0/ Introducción: La evaluación de la cantidad y distribución de la grasa corporal en personas que viven con el VIH/SIDA es de gran importancia en la práctica clínica, debido a la asociación de los cambios de grasa corporal con condiciones clínicas. El objetivo de esta revisión es responder a la pregunta central: ¿Puede la antropometría medir con precisión la grasa corporal en las personas que viven con el VIH/SIDA? Material y Métodos: Revisión sistemática llevada a cabo por medio de cuatro bases de datos: Medline, LILACS, Scopus y BDTD. ABSTRACT Can anthropometry measure the body fat of people living with HIV/AIDS? A systematic review R E S E A R C H A R T I C L E Resultados:De los 581 estudios encontrados, 11 cumplieron con los criterios de elegibilidad. Para evaluar la validación de la antropometría, sólo dos estudios emplearon análisis de regresión para el desarrollo de las ecuaciones de predicción de grasa corporal en las personas que viven con el VIH/SIDA y nueve estudios emplearon análisis de correlación. Este coeficiente sólo mide la fuerza de la relación entre dos variables, y no hay concordancia entre ellos y, por lo tanto, estos estudios no evaluaron con precisión si la información antropométrica mostró buena concordancia con el estándar de oro. Los otros dos estudios desarrollaron cinco ecuaciones para evaluar la grasa total y en las extremidades (brazos, piernas y tronco) en personas que viven con el VIH/SIDA y usan antirretrovirales y mostraron R 2 entre 0,50 y 0,83. Conclu...

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Aplicabilidade de equações na avaliação da composição corporal da população brasileira

Cited by 18 publications

References 31 publications

Effect of glycemic index on obesity control

Effect of glycemic index on obesity control

Development and validation of anthropometric equations to estimate appendicular muscle mass in elderly women

Can anthropometry measure the body fat of people living with HIV/AIDS?: A systematic review

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