Differences in metabolic syndrome severity and prevalence across nine waist circumference measurements collected from smartphone digital anthropometrics

Abstract

Background & aims: Given the technological advances in 3D smartphone (SP) anthropometry, this technique presents a unique opportunity to improve metabolic syndrome (MetS) screening through optimal waist circumference (WC) landmarking procedures. Thus, the purpose of this study was to evaluate the associations between individual MetS risk factors and nine independent WC sites collected using tape measurement or SP anthropometrics and to determine the differences in MetS severity and prevalence when using these different WC measurement locations.

Methods: A total of 130 participants (F:74, M:56; age: 27.8 ± 11.1) completed this cross-sectional evaluation. Using traditional tape measurement, WC was measured at the lowest rib (WC_Rib), superior iliac crest (WC_Iliac), and between the WC_Rib and WC_Iliac (WC_Mid). Additionally, WC measurements were automated using a SP application at six sites along the torso. MetS risk factors were used to calculate MetS severity (MetS_index) and prevalence. Associations were evaluated using multiple linear regression, the effect of each WC site on MetS_index was analyzed using mixed-models ANCOVA, and differences in MetS prevalence using WC_Iliac as the current standard were determined using sensitivity, specificity, chi-squared tests, and odds ratios.

Results: The reference SP-WC (SP_Ref) and WC_Rib demonstrated the largest associations (all p < 0.001) with HDL cholesterol (SP_Ref: -0.48; WC_Rib: -0.49), systolic (SP_Ref: 0.32; WC_Rib: 0.30) and diastolic blood pressure (SP_Ref: 0.34; WC_Rib: 0.32), and fasting blood glucose (SP_Ref: 0.38; WC_Rib: 0.37). SP_Ref and WC_Rib were the only WC without significantly different MetS_index; yet demonstrated lower MetS_index and sensitivity (SP_Ref: 77.8 %; WC_Rib: 74.1 %) relative to WC_Iliac, the conventional (or standard) WC measure.

Conclusions: Compared to the current standard, SP_Ref and WC_Rib protocols are more highly associated with individual MetS risk factors and produce different MetS_index and diagnoses; highlighting the need for new MetS WC protocols. Given the surge in remote/mobile healthcare, SP_Ref may be an alternative to traditional methods in this context but requires further investigation before implementation.

Keywords: Artificial intelligence; Body composition; Metabolic syndrome; Mobile applications; Obesity; Waist circumference.