Determination of Body Fat Percentage by Body State Devices and Dual Energy X-Ray Absorptiometry

  • Mostafa R
  • Negm D
  • ElSawy N
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Abstract

Background: Dual energy X-ray absorptiometry (DEXA) is the most accurate technique in determining fat percentage but it is unpotable, expensive, unavailable for general applicability. Objective: This study aimed to find the most accurate and easiest technique as alternative to DEXA for quick determination of body fat%. This study examined the accuracy of three models of Bioelectrical impedance analysis (BIA) technique (Fat Loss Monitor- Body Composition -Body Fat Analyzer) in determining the body fat percentage with using DEXA as a reference standard. Subject and Methods: A cross sectional study was carried out during the period from (28-9-2017) to (5-4-2018) among a random sample of (53) volunteers female student in Umm Al Qura University from Faculty of Applied Medical Science aged between (20-39 years) from different level of education. All subjects were generally healthy, data was collected through a structured questionnaire compose of three section. Demographic data was collected and anthropometric measurements were evaluated as well as body composition (Only body fat%) using DEXA, body composition monitor, fat loss monitor and body fat analyzer. Results: BMI classification of the total 53 subjects was including 8 healthy females, 17 overfat, 25 obese and 3 underweight. The fat% result from DEXA and body fat analyzer was significant difference at (P < 0.05). Fat percent result from DEXA and Body Composition device was non-significant difference at (P>0.05). The fat% result from DEXA and Fat Loss Monitor device was significant at difference (P<0.05). Conclusion: The most accurate of BIA technique was the Body Composition device compering to DEXA.

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Mostafa, R. A., Negm, D. R., & ElSawy, N. A. (2019). Determination of Body Fat Percentage by Body State Devices and Dual Energy X-Ray Absorptiometry. Asian Journal of Medicine and Health, 1–12. https://doi.org/10.9734/ajmah/2019/v17i230163

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