Phase angle and vector analysis from multifrequency segmental bioelectrical impedance analysis: New reference data for older adults - Reljic, Dejan; Zarafat, Daniel; Jensen, B.; Herrmann, H. J.; Neurath, Markus; Konturek, P. C.; Zopf, Yurdagül (Journal of Physiology and Pharmacology, 2020)
Phase angle (PA) and bioelectrical impedance vector analysis (BIVA) have been recommended as useful prognostic markers in various clinical settings. However, reference data for older adults measured by the novel segmental multifrequency bioelectrical impedance analysis (SMF-BIA) technique are currently lacking. This study examined 567 (286 men, 281 women) healthy older adults (65 – 97 years) and new SMF-BIA-based PA and BIVA reference values were generated stratified according to gender and 3 age groups (65 – 75 years, 76 – 85 years, > 85 years). Mean PA-values (women: 4.30 ± 0.6°, men: 4.77 ± 0.7°) were significantly lower than those previously reported for a younger reference population. Age and gender were significant determinants of PA and BIVA. PA showed a significant decrease with increasing age in both genders. The greatest changes occurred in the age group > 85 years. Men had higher PAs compared to women (except for the oldest age group), but showed a substantially steeper decline in PA, possibly due to a more pronounced reduction of muscle mass. Compared to published reference data for younger adults, there was a clear downward migration of the BIVA vector points in older adults, indicating an age-related reduction of body cell mass. Accordingly, the equation for the BIVA chart generation was modified by adding the factor age. In conclusion, this is the first study to present SMF-BIA-determined PA and BIVA reference data for healthy subjects aged ³ 65 years. These data can be used for clinical purposes to identify individuals at increased risk for adverse health events or to monitor treatment responses.
CRIS-Team Scopus Importer:2020-11-20
Keywords: Age and gender stratification; Bioimpedance analysis; Body composition; Geriatric medicine; Health risk diagnostic and prediction; Nutrition status monitoring