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. 2024 Nov 21;14(1):28882.
doi: 10.1038/s41598-024-79329-8.

Waist-to-calf circumference ratio as a potential indicator of diabetes risk: results from the Longevity Check-Up (Lookup) 8

Stefano Cacciatore  1   2 , Anna Maria Martone  3   4 , Francesca Ciciarello  3   4 , Vincenzo Galluzzo  3   4 , Giordana Gava  3   4 , Claudia Massaro  3   4 , Riccardo Calvani  3   4 , Matteo Tosato  3   4 , Emanuele Marzetti  3   4 , Francesco Landi  5   6 ; Lookup 8+ Study Group
Collaborators, Affiliations

Waist-to-calf circumference ratio as a potential indicator of diabetes risk: results from the Longevity Check-Up (Lookup) 8

Stefano Cacciatore et al. Sci Rep. .

Abstract

Diabetes is a prevalent metabolic condition with substantial health and economic impacts. Therefore, effective and accessible indicators are essential for early detection and prevention. This study investigates the link between the waist-to-calf circumference ratio (WCR) and diabetes risk in a large cohort from the Longevity Check-Up (Lookup) 8+ Study. The present investigation is a retrospective cross-sectional study. Diabetes was defined either as self-reported diagnosis, or fasting plasma glucose equal to or greater than 126 mg/dL, or random plasma glucose equal to or greater than 200 mg/dL. The WCR was calculated by dividing waist circumference by calf circumference. A total population of 8900 participants (mean age 57.1 ± 14.8 years, 55% women) was included in the study. The prevalence of diabetes was 9.4%. Mean WCR displayed a significant trend (p for trend < 0.001), and the analysis of covariance (ANCOVA) revealed significant differences among the normal, pre-diabetes, diabetes groups. Unadjusted logistic regression showed a positive association between higher WCR and diabetes, which remained significant in the adjusted models. Receiver operating characteristic curve analysis indicated that WCR had a higher area under the curve compared to waist circumference alone, with cut-off values of 2.35 for men and 2.12 for women providing high sensitivity (91% for men, 92% for women) and specificity (74% for men, 75% for women). Our study introduces WCR as a novel, simple, and cost-effective anthropometric measure for identifying individuals at risk of diabetes, suitable for clinical use, especially in resource-limited settings.

Keywords: Anthropometric measures; Body composition; Cardiovascular risk; Lifestyle; Metabolic syndrome; Muscle mass; Obesity; Waist circumference.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Università Cattolica del Sacro Cuore, Rome, Italy (protocol #A.1220/CE/2011). Consent for publication: Informed consent was obtained from all subjects involved in the study.

Figures

Fig. 1
Fig. 1
Flowchart of the study sample selection. CC calf circumference, WC waist circumference.
Fig. 2
Fig. 2
Quartiles of cut-off values for waist circumference, calf circumference and waist-to-calf circumference ratio according to sex. CC calf circumference, WC waist circumference, WCR waist-to-calf circumference ratio.
Fig. 3
Fig. 3
Diabetes prevalence across waist circumference (WC) and calf circumference (CC) quartiles in the total sample (A), men (B), and women (C). The X-axis shows the quartiles of WC (progressing from Q1, the lowest, to Q4, the highest) alongside quartiles of CC (from Q1 to Q4 in increasing order). Each bar represents the percentage of individuals with diabetes within each specific combination of WC and CC quartiles. The direction of progression in diabetes rate can be observed for both WC and CC across the quartiles.
Fig. 4
Fig. 4
Receiver operating characteristic curve analysis for predicting diabetes according to waist circumference and waist-to-calf circumference ratio. Areas under the curve: total sample, WC = 0.59, WCR = 0.70; men, WC = 0.59; WCR = 0.67; women, WC = 0.59; WCR = 0.70.
See this image and copyright information in PMC

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