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Few studies have described the long-term repeatability of dual-energy X-ray absorptiometry scans. Even fewer studies have been performed with enough participants to identify possible precision covariates such as sex, age, and body mass index (BMI). Our objective was to investigate the long-term repeatability of both total and subregional body composition measurements and their associations with covariates in a large sample. Two valid whole-body dual-energy X-ray absorptiometry scans were available for 609 participants in the National Health and Nutrition Examination Survey 2000–2002. Participants with scan-quality issues were excluded. Participants varied in race and ethnicity, sex, age (mean 38.8 ± 17.5; range 16–69 yr), and BMI (mean, 26.9 ± 5.2; range 14.1–43.5 kg/m 2 ). The length of time between scans ranged from 3 to 51 days (mean, 18.7 ± 8.4). Precision error estimates for total body measures (bone mineral density, bone mineral content, lean mass, total mass, fat mass, and percent body fat) were calculated as root mean square percent coefficients of variation and standard deviations. The average root mean square percent coefficients of variation and root mean square standard deviations of the precision error for total body variables were 1.12 and 0.01 g/cm 2 for bone mineral density, 1.14 and 27.3 g for bone mineral content, 1.97 and 505 g for fat mass, 1.46 and 760 g for lean mass, 1.10 and 858 g for total mass, and 1.80 and 0.59 for percent body fat. In general, only fat and lean masses were impacted by participant and scan qualities (obesity category, sex, the magnitude of the body composition variables, and time between scans). We conclude that long-term precision error values are impacted by BMI, and sex. Our long-term precision error estimates may be more suitable than short-term precision for calculating least significant change and monitoring time intervals.

Aims: Increased visceral adipose tissue (VAT) volume is strongly associated with several serious metabolic diseases including heart disease and diabetes, and also to fracture risk. Accurate measure of this soft tissue compartment is imperative if it is to be included in clinical risk models. Hologic software, version Apex 4.0, now includes a VAT estimate from whole body scans. Although the analysis is automated, the region is visible and allows for manual adjustment if necessary. The aim of our study was to evaluate how often the VAT region needed adjustment and what would be the error if no manual adjustment is made. Methods: We reanalyzed a subset of the NHANES study whole body scans (20112012) to include VAT volume to the study results. These NHANES participants are considered a representative sample of the US population from ages 18 years to 59 years old. All scans were analyzed using Hologic version Apex 4.0 auto-analysis mode and manually reviewed for proper VAT region placement. VAT regions needing correction were manually adjusted. Paired T-tests were used to determine the difference in error between the auto and manual analyses for VAT and subcutaneous adipose tissue volume (SAT). Results: A total 3283 adult whole body scans were reviewed. VAT boundary marker adjustment was required on 247, or approximately 8% of the scans. The average difference between manual and auto analysis for both VAT and SAT were significantly different (p!0.0001) with VAT being -17.9 34.8 cm and SAT higher +18.0 35.5 cm. Absolute differences ranged from -213.7 to 145.8 cm and -145.8 to 213.7 cm for VAT and SAT, respectively. Conclusion: Our results confirm that for VAT and SAT regions, it is imperative to visualize the and check the region demarcations to assure high accuracy. Failure to do this necessary quality control review could lead to clinically inaccurate results in 1 out of 12 patients. Disclosure of Interest: None Declared