The body composition phenotype of Irish adults aged 18–81 years. (May 2016)

• Record Type: Journal Article
• Authors: Toomey, C.; Leahy, S.; McCreesh, K.; Coote, S.; Jakeman, P.
• Is Part Of: Irish journal of medical science. Volume 185:Number 2(2016)
• Page Start: 537
• Page End: 544
• Publication Date: 2016-05
• Subjects: Body composition -- Obesity -- DXA -- Adiposity -- Visceral fat -- Sarcopenia; Medicine -- Periodicals; Medicine -- Periodicals; 610
• DOI: 10.1007/s11845-015-1338-x
• Languages: English
• ISSNs: 0021-1265

Abstract

Abstract Background Regional distribution of adiposity and lean tissue mass are predictors of health risk that cannot be defined by body mass index but can be attained by dual-energy X-ray absorptiometry (DXA). Age and sex-related adult ranges of whole-body and regional adiposity and lean tissue are not available for Irish men and women. Aims The aim of this study was to construct a DXA-based body composition profile of Irish adults, focusing on age- and sex-related difference in total and regional adiposity and lean tissue mass. Methods The study population comprised a convenience sample of 1606 participants, aged 18–81 years participating in the University of Limerick Body Composition study. Data were analysed to construct stature-normalised indices of body fat mass (BFMI), site-specific visceral adiposity, lean tissue mass (LTMI) and appendicular lean tissue mass (ALTMI). Results Compared to the young adult (18–29 years), BFMI was higher in women (p < 0.001) but plateaued in men aged >50 years. For men, age-related difference in LTMI was not evident but ALTMI was significantly lower in those >50 years. For women, there was evidence of significantly lower LTMI with advancing age and, similar to men, significantly lower ALTMI in those >50 years. Conclusions These data provide an insight into the age-related anthropometric phenotype of Irish adults. Centile data have been constructed that provide informative data of the age and sex-specific range of adiposity and lean tissue mass. These data may assist in identification of those at risk of aberrant, body composition-related disease.