Body composition measurements from DXA have been available since DXA technology was developed 30 years ago, but are historically underutilized. Recently, there have been rapid developments in body composition assessment including the analysis and publication of representative data for the US, official usage guidance from the International Society for Clinical Densitometry, and development of regional body composition measures with clinical utility. DXA body composition is much more than whole body percent fat. In this paper celebrating 30 years of DXA for body composition, we will review the principles of DXA soft tissue analysis, practical clinical and research applications, and what to look for in the future.

Further understanding is needed of the functionalities and efficiency of social media for health intervention research recruitment. Facebook was examined as a mechanism to recruit young adults for a smoking cessation intervention. An ad campaign targeting young adult smokers tested specific messaging based on market theory and successful strategies used to recruit smokers in previous clinical trials (i.e. informative, call to action, scarcity, social norms), previously successful ads, and general messaging. Images were selected to target smokers (e.g., lit cigarette), appeal to the target age, vary demographically, and vary graphically (cartoon, photo, logo). Facebook’s Ads Manager was used over 7 weeks (6/10/13 – 7/29/13), targeted by age (18–25), location (U.S.), and language (English), and employed multiple ad types (newsfeed, standard, promoted posts, sponsored stories) and keywords. Ads linked to the online screening survey or study Facebook page. The 36 different ads generated 3,198,373 impressions, 5,895 unique clicks, at an overall cost of $2,024 ($0.34/click). Images of smoking and newsfeed ads had the greatest reach and clicks at the lowest cost. Of 5,895 unique clicks, 586 (10%) were study eligible and 230 (39%) consented. Advertising costs averaged $8.80 per eligible, consented participant. The final study sample (n=79) was largely Caucasian (77%) and male (69%), averaging 11 cigarettes/day (SD=8.3) and 2.7 years smoking (SD=0.7). Facebook is a useful, cost-effective recruitment source for young adult smokers. Ads posted via newsfeed posts were particularly successful, likely because they were viewable via mobile phone. Efforts to engage more ethnic minorities, young women, and smokers motivated to quit are needed.

Background Three-dimensional optical (3DO) body scanning has been proposed for automatic anthropometry. However, conventional measurements fail to capture detailed body shape. More sophisticated shape features could better indicate health status. Objectives The objectives were to predict DXA total and regional body composition, serum lipid and diabetes markers, and functional strength from 3DO body scans using statistical shape modeling. Methods Healthy adults underwent whole-body 3DO and DXA scans, blood tests, and strength assessments in the Shape Up! Adults cross-sectional observational study. Principal component analysis was performed on registered 3DO scans. Stepwise linear regressions were performed to estimate body composition, serum biomarkers, and strength using 3DO principal components (PCs). 3DO model accuracy was compared with simple anthropometric models and precision was compared with DXA. Results This analysis included 407 subjects. Eleven PCs for each sex captured 95% of body shape variance. 3DO body composition accuracy to DXA was: fat mass R2 = 0.88 male, 0.93 female; visceral fat mass R2 = 0.67 male, 0.75 female. 3DO body fat test-retest precision was: root mean squared error = 0.81 kg male, 0.66 kg female. 3DO visceral fat was as precise (%CV = 7.4 for males, 6.8 for females) as DXA (%CV = 6.8 for males, 7.4 for females). Multiple 3DO PCs were significantly correlated with serum HDL cholesterol, triglycerides, glucose, insulin, and HOMA-IR, independent of simple anthropometrics. 3DO PCs improved prediction of isometric knee strength (combined model R2 = 0.67 male, 0.59 female; anthropometrics-only model R2 = 0.34 male, 0.24 female). Conclusions 3DO body shape PCs predict body composition with good accuracy and precision comparable to existing methods. 3DO PCs improve prediction of serum lipid and diabetes markers, and functional strength measurements. The safety and accessibility of 3DO scanning make it appropriate for monitoring individual body composition, and metabolic health and functional strength in epidemiological settings. This trial was registered at clinicaltrials.gov as NCT03637855.

Anthropometry, Greek for human measurement, is a tool widely used across many scientific disciplines. Clinical nutrition applications include phenotyping subjects across the lifespan for assessing growth, body composition, response to treatments, and predicting health risks. The simple anthropometric tools such as flexible measuring tapes and calipers are now being supplanted by rapidly developing digital technology devices. These systems take many forms, but excitement today surrounds the introduction of relatively low cost three-dimensional optical imaging methods that can be used in research, clinical, and even home settings. This review examines this transformative technology, providing an overview of device operational details, early validation studies, and potential applications. Digital anthropometry is rapidly transforming dormant and static areas of clinical nutrition science with many new applications and research opportunities.

Background Measures of skeletal muscle function decline at a faster rate with ageing than do indices of skeletal muscle mass. These observations have been attributed to age‐related changes in muscle quality, another functional determinant separate from skeletal muscle mass. This study tested the hypothesis that improved predictions of skeletal muscle strength can be accomplished by combining clinically available measures of skeletal muscle mass and quality. Methods The participants included 146 healthy adult (age ≥ 18 years, range 18–77 years; X ± SD 47 ± 17 years and body mass index 16.5–51.8 kg/m 2 ; 27.7 ± 6.2 kg/m 2 ) men ( n = 60) and women ( n = 86) in whom skeletal muscle mass was estimated as appendicular lean soft tissue (LST) measured by dual‐energy X‐ray absorptiometry and skeletal muscle quality as bioimpedance analysis‐derived phase angle and B‐mode‐evaluated echogenicity of mid‐thigh skeletal muscle. Strength of the right leg and both arms was quantified as knee isokinetic extension and handgrip strength using dynamometers. The statistical significance of adding phase angle or echogenicity to strength prediction multiple regression models that included extremity‐specific LST and other covariates (e.g. age and sex) was evaluated to test the study hypothesis. Results Right leg LST mass alone was significantly ( P < 0.0001) correlated with isokinetic right leg strength ( R 2 = 0.57). The addition of segmental phase angle measured in the right leg at 50 kHz increased the R 2 of this model to 0.66 ( P < 0.0001); other phase angle frequencies (5 and 250 kHz) did not contribute significantly to these models. Results were similar for both right and left arm handgrip strength prediction models. Adding age and sex as model covariates increased the R 2 values of these models further (e.g. right leg strength model R 2 increased to 0.71), but phase angle continued to remain a significant (all P < 0.01) predictor of extremity strength. Similarly, when predicting isokinetic right leg strength, mid‐thigh skeletal muscle echogenicity added significantly ( P < 0.0001) to right leg LST, increasing R 2 from 0.57 to 0.64; age was a significant ( P < 0.0001) covariate in this model, increasing R 2 further to 0.68. Conclusions The hypothesis of the current study was confirmed, strongly supporting and extending earlier reports by quantifying the combined independent effects of skeletal muscle mass and quality on lo...