ArticlePloS one2026
Association between anthropometric measures and abdominal wall thickness in patients with obesity: A cross-sectional CT study.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAbdominal wall thickness (AWT) is a critical determinant of safe abdominal access in patients with obesity, yet it is not routinely assessed preoperatively. Simple, bedside methods for evaluating factors associated with AWT are lacking. This study aimed to evaluate the association between readily available anthropometric measurements and AWT across multiple surgically relevant abdominal regions.
methodsIn this prospective cross-sectional study, 105 patients with obesity (body mass index [BMI] ≥30 kg/m2) who underwent computed tomography (CT) imaging were included. AWT was measured at nine predefined anatomical points corresponding to commonly used surgical landmarks. Anthropometric parameters, including BMI, neck circumference, mid-upper arm circumference, and waist circumference, were recorded. Correlation analyses were performed to assess the associations between anthropometric measurements and CT-measured AWT.
resultsBMI demonstrated a moderate and consistent positive association with AWT across all anatomical regions (rs = 0.34-0.55, all p < 0.001). Waist circumference and mid-upper arm circumference showed moderate associations, whereas neck circumference demonstrated weak and inconsistent associations. AWT varied across anatomical regions, with greater thickness observed in the lower abdomen. Female patients had significantly greater AWT at several sites. These findings highlight regional variability in AWT and its association with anthropometric measurements.
conclusionsAnthropometric measurements, particularly BMI, were significantly associated with AWT across multiple abdominal regions in patients with obesity. These findings provide additional insight into regional abdominal wall variability and may support future development of bedside assessment tools for abdominal access planning. Further studies are needed to develop and validate predictive models for clinical application.
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