Digital Anthropometry: A Systematic Review on Precision, Reliability and Accuracy of Most Popular Existing Technologies

Digital anthropometry (DA) has been recently developed for body composition evaluation and for postural analysis. The aims of this review are to examine the current state of DA technology, as well as to verify the methods for identifying the best technology to be used in the field of DA by evaluating the reliability and accuracy of the available technologies on the market, and lay the groundwork for future technological developments. A literature search was performed and 28 studies met the inclusion criteria. The reliability and accuracy of DA was high in most studies, especially in the assessment of patients with obesity, although they varied according to the technology used; a good correlation was found between DA and conventional anthropometry (CA) and body composition estimates. DA is less time-consuming and less expensive and could be used as a screening tool before more expensive imaging techniques or as an alternative to other less affordable techniques. At present, DA could be useful in clinical practice, but the heterogeneity of the available studies (different devices used, laser technologies, population examined, etc.) necessitates caution in the interpretation of the obtained results. Furthermore, the need to develop integrated technologies for analyzing body composition according to multi-compartmental models is increasingly evident.

Automated summary

Digital anthropometry (DA) has been developed for body composition evaluation and postural analysis. This review examines the current state of DA technology and evaluates the reliability and accuracy of available technologies on the market. DA shows high reliability and accuracy, especially in assessing obese patients and correlates well with conventional anthropometry and body composition estimates. DA is cost-effective and time-efficient, making it a useful screening tool before more expensive imaging techniques or as an alternative to other less affordable techniques. However, caution is needed in interpreting results due to the heterogeneity of available studies. Furthermore, there is a need for integrated technologies to analyze body composition according to multi-compartmental models.