J Korean Diabetes.  2022 Jun;23(2):106-112. 10.4093/jkd.2022.23.2.106.

Utility of Bioelectrical Impedance Analysis for Body Composition Assessment

• Lim S

• KMID: 2531494
• DOI: http://doi.org/10.4093/jkd.2022.23.2.106

Abstract

People with obesity are at high risk of type 2 diabetes, cardiovascular diseases, and certain types of malignancy. A significant reduction in muscle mass is also associated with increased risk of developing sarcopenia. In general, body composition is affected by several factors, including ethnicity, environment, genetics, and lifestyle patterns. Assessment of body composition is an important tool for maintaining good general health and longevity, and is utilized by physicians and researchers to monitor disease severity and nutritional status. It can also be used to monitor the effectiveness of dietary and drug interventions. Dual energy X-ray absorptiometry is regarded as the gold standard method for analyzing body composition. However, there is an associated risk of a small amount of radiation exposure. In addition, severely obese people are not candidates for this method. Recently, bioelectrical impedance analysis (BIA) has been developed. BIA poses no radiation hazard, is easy applicable and relatively inexpensive. Thus, BIA is widely used in fitness centers as well as in hospitals. Several studies have been conducted to assess the effectiveness of BIA for measuring body composition, but most have focused on subjects of European descent. Of note, body composition differs among ethnic groups: Asians have a greater tendency toward obesity at a lower body mass index than Caucasians. Therefore, an ethnicity-specific approach is required for precise estimation of body composition using BIA. In conclusion, healthcare providers should have a thorough understanding of body composition assessment and the advantages and disadvantages of different measurement methods.

Keyword

Body composition; Fats; Impedance; Muscles; Obesity; Sarcopenia

Figure

• 

  Fig. 1. Various causes of sarcopenia. GH, growth hormone; IGF-1, insulin-like growth factor-1; TFT, tyroid function text.

• 

  Fig. 2. Progress in bioelectrical impedance analysis (BIA) method (upper panel). The BIA technology has progressed from single segmental to multi-segmental assessment. Two BIA machines for body composition assessment in whole body (lower left) and abdomen (lower right).

Reference

1.Gómez-Ambrosi J., Silva C., Galofré JC., Escalada J., Santos S., Gil MJ. Body adiposity and type 2 diabetes: increased risk with a high body fat percentage even having a normal BMI. Obesity (Silver Spring). 2011. 19:1439–44.

2.Freisling H., Arnold M., Soerjomataram I., O'Doherty MG., Ordóñez-Mena JM., Bamia C. Comparison of general obesity and measures of body fat distribution in older adults in relation to cancer risk: meta-analysis of individu-al participant data of seven prospective cohorts in Europe. Br J Cancer. 2017. 116:1486–97.

3.Bigaard J., Frederiksen K., Tj⊘nneland A., Thomsen BL., Overvad K., Heitmann BL. Body fat and fat-free mass and all-cause mortality. Obes Res. 2004. 12:1042–9.

4.Finkelstein EA., Trogdon JG., Cohen JW., Dietz W. Annual medical spending attributable to obesity: payer-and ser-vice-specific estimates. Health Aff (Millwood). 2009. 28:w822–31.

5.Dietz W., Santos-Burgoa C. Obesity and its implications for COVID-19 mortality. Obesity (Silver Spring). 2020. 28:1005.

6.Lim S., Shin SM., Nam GE., Jung CH., Koo BK. Proper man-agement of people with obesity during the COVID-19 pandemic. J Obes Metab Syndr. 2020. 29:84–98.

7.Lim S., Lim H., Després JP. Collateral damage of the COVID-19 pandemic on nutritional quality and physical activity: perspective from South Korea. Obesity (Silver Spring). 2020. 28:1788–90.

8.Lim S., Bae JH., Kwon HS., Nauck MA. COVID-19 and diabetes mellitus: from pathophysiology to clinical man-agement. Nat Rev Endocrinol. 2021. 17:11–30.

9.Andreoli A., Garaci F., Cafarelli FP., Guglielmi G. Body composition in clinical practice. Eur J Radiol. 2016. 85:1461–8.

10.Kim KM., Jang HC., Lim S. Differences among skeletal muscle mass indices derived from height-, weight-, and body mass index-adjusted models in assessing sarcopenia. Korean J Intern Med. 2016. 31:643–50.

11.Ganapathy A., Nieves JW. Nutrition and sarcopenia-what do we know? Nutrients. 2020. 12:1755.

12.Prado CM., Lieffers JR., McCargar LJ., Reiman T., Sawyer MB., Martin L. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study. Lancet Oncol. 2008. 9:629–35.

13.Hsu KJ., Liao CD., Tsai MW., Chen CN. Effects of exercise and nutritional intervention on body composition, metabolic health, and physical performance in adults with sarcopenic obesity: a meta-analysis. Nutrients. 2019. 11:2163.

14.Lim S., Kim JH., Yoon JW., Kang SM., Choi SH., Park YJ. Sarcopenic obesity: prevalence and association with metabolic syndrome in the Korean Longitudinal Study on Health and Aging (KLoSHA). Diabetes Care. 2010. 33:1652–4.

15.Campa F., Toselli S., Mazzilli M., Gobbo LA., Coratella G. Assessment of body composition in athletes: a narrative review of available methods with special reference to quantitative and qualitative bioimpedance analysis. Nutrients. 2021. 13:1620.

16.Anderson LJ., Erceg DN., Schroeder ET. Utility of mul-tifrequency bioelectrical impedance compared with dual-energy x-ray absorptiometry for assessment of total and regional body composition varies between men and women. Nutr Res. 2012. 32:479–85.

17.Moon JR., Stout JR., Smith-Ryan AE., Kendall KL., Fukuda DH., Cramer JT. Tracking fat-free mass changes in elderly men and women using single-frequency bioimped-ance and dual-energy X-ray absorptiometry: a four-com-partment model comparison. Eur J Clin Nutr. 2013. 67(Suppl 1):S40–6.

18.Neovius M., Hemmingsson E., Freyschuss B., Uddén J. Bioelectrical impedance underestimates total and truncal fatness in abdominally obese women. Obesity (Silver Spring). 2006. 14:1731–8.

19.Gába A., Kapuš O., Cuberek R., Botek M. Comparison of multi- and single-frequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of body composition in post-menopausal women: effects of body mass index and accelerometer-determined physical activity. J Hum Nutr Diet. 2015. 28:390–400.

20.Chen KT., Chen YY., Wang CW., Chuang CL., Chiang LM., Lai CL. Comparison of standing posture bioelectrical impedance analysis with DXA for body composition in a large, healthy Chinese population. PLoS One. 2016. 11:e0160105.

21.Lukaski HC., Siders WA. Validity and accuracy of regional bioelectrical impedance devices to determine whole-body fatness. Nutrition. 2003. 19:851–7.

22.LaForgia J., Gunn S., Withers RT. Body composition: valid-ity of segmental bioelectrical impedance analysis. Asia Pac J Clin Nutr. 2008. 17:586–91.

23.Nickerson BS., Tinsley GM. Utilization of BIA-derived bone mineral estimates exerts minimal impact on body fat estimates via multicompartment models in physically active adults. J Clin Densitom. 2018. 21:541–9.

24.Kyle UG., Bosaeus I., De Lorenzo AD., Deurenberg P., Elia M., Manuel Gómez J. Bioelectrical impedance analy-sis-part II: utilization in clinical practice. Clin Nutr. 2004. 23:1430–53.

25.Lee DH., Park KS., Ahn S., Ku EJ., Jung KY., Kim YJ. Comparison of abdominal visceral adipose tissue area measured by computed tomography with that estimated by bioelectrical impedance analysis method in Korean subjects. Nutrients. 2015. 7:10513–24.

26.Park KS., Lee DH., Lee J., Kim YJ., Jung KY., Kim KM. Comparison between two methods of bioelectrical impedance analyses for accuracy in measuring abdominal visceral fat area. J Diabetes Complications. 2016. 30:343–9.

27.Lee SY., Ahn S., Kim YJ., Ji MJ., Kim KM., Choi SH. Comparison between dual-energy X-ray absorptiometry and bioelectrical impedance analyses for accuracy in measuring whole body muscle mass and appendicular skeletal muscle mass. Nutrients. 2018. 10:738.