title: Waist girth normalized to body build in obesity assessment.
abstract: Waist girth (WG) is regarded as the most significant anthropometric parameter associated with cardiovascular risk. The objective of the present study was to strengthen WG as an obesity marker by basing WG assessment not on gender but on individually measured body build characteristics that need not coincide with gender. We formulated a new marker, the Waist Reference Girth (WRG) and two corollaries, the Waist Deviation (WD) and the Percent Waist Deviation (%WD). The present research centered on deriving an equation for WRG from relevant trunk skeletal measurements that closely predicted WG in lean individuals. This equation would determine any individual's WRG and current WD. Trunk skeletal widths and chest depth as well as WG were measured on 507 physically active subjects (247 men and 260 women), predominantly lean young adults. Multiple regression analysis with the skeletal measurements as independent variables was performed on this data to predict WG. The unisex WRG equation WRG = Chest Sum x 1.635 predicted WG of 282 lean subjects (maximum WD of 4 cm) with R(2) of 0.87 (SEE of 3.0 cm). Male and female WG cutoff values for central obesity are usually taken at 94 cm and 80 cm respectively. For the average male and female WRG in this study (79 cm and 67.4 cm), these cutoff values are equivalent to WD of 15 cm and 12.6 cm respectively and to 19%WD for both genders (15/79 and 12.6/67.4). With %WD normalized for WRG, hence unaffected by intra-group or inter-group variations in the Chest Sum, %WD thresholds may better identify health risks linked to abdominal obesity than existing WG thresholds.
authors.affiliation: goguh@aol.com
authors.forename: Grete
authors.initials: G
authors.lastname: Heinz
authors.forename: Gary T C
authors.initials: GT
authors.lastname: Ko
authors.forename: Louis J
authors.initials: LJ
authors.lastname: Peterson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000886:Anthropometry / Q000379:methods*; D015992:Body Mass Index; D001837:Body Weights and Measures / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000175:diagnosis*; D012044:Regression Analysis; D013008:Somatotypes / Q000502:physiology*; D013909:Thorax / Q000033:anatomy & histology