Air displacement plethysmography (ADP) is fast, accurate, and reliable. Nevertheless, in about 3% of the cases, standard ADP tests provide rogue results. To spot these outliers and improve precision, repeated trials protocols have been devised, but few works have addressed their reliability. This study was conducted to evaluate the test–retest reliabilities of two known protocols and a new one, proposed here. Ninety-two healthy adults (46 men and 46 women) completed six consecutive ADP tests. To evaluate the reliability of single measurements, we used the results of the first two tests; for multiple measures protocols, we computed the test result from trials 1–3 and the retest result from trials 4–6. Bland–Altman analysis revealed that the bias and the width of the 95% interval of agreement were smaller for multiple trials than for single ones. For percent body fat (%BF)/fat-free mass, the technical error of measurement was 1% BF/0.68 kg for single trials and 0.62% BF/0.46 kg for the new protocol of multiple trials, which proved to be the most reliable. The minimal detectable change (MDC) was 2.77% BF/1.87 kg for single trials and 1.72% BF/1.26 kg for the new protocol.

Air displacement plethysmography (ADP) is a widespread technique for assessing global obesity in both health and disease. The reliability of ADP has been demonstrated by studies focused on duplicate trials. The present study was purported to evaluate learning effects on the reliability of body composition assessment using the BOD POD system, the sole commercially available ADP instrument. To this end, quadruplicate trials were performed on a group of 105 subjects (51 women and 54 men). We estimated measurement error from pairs of consecutive trials—(1,2), (2,3), and (3,4)—to test the hypothesis that early measurements are subject to larger errors. Indeed, statistical analysis revealed that measures of reliability inferred from the first two trials were inferior to those computed for the other pairs of contiguous trials: for percent body fat (%BF), the standard error of measurement (SEM) was 1.04% for pair (1,2), 0.71% for pair (2,3), and 0.66% for pair (3,4); the two-way random effects model intraclass correlation coefficient (ICC) was 0.991 for pair (1,2), and 0.996 for pairs (2,3) and (3,4). Our findings suggest that, at least for novice subjects, the first ADP test should be regarded as a practice trial. When the remaining trials were pooled together, the reliability indices of single ADP tests were the following: ICC = 0.996, SEM = 0.70%, and minimum detectable change (MDC) = 1.93% for %BF, and ICC = 0.999, SEM = 0.49 kg, and MDC = 1.35 kg for fat-free mass (FFM). Thus, the present study pleads for eliminating learning effects to further increase the reliability of ADP.

Background/aims: Prior research identified a significant association between heart disease and metabolic dysfunction-associated liver steatohepatitis (MASLD), but the mechanisms are unclear. This study aims to search predictive biomarkers for grade I left ventricular diastolic dysfunction (LVDD), an early stage of heart failure (HF), in type 2 diabetes mellitus (T2DM) patients. Methods: This single-center, prospective observational study screened 73 T2DM patients for grade 1 LVDD and MASLD using 2D echocardiography, tissue analysis, spectral color Doppler, and Fibromax. Results: The study analyzed 50 patients (mean age 58±11.3 years) with a median diabetes duration of 7 years, abdominal obesity (mean BMI 34.4±5.9 kg/m2), and a mean HbA1c of 7.9±1.5%. The prevalence of grade I LVDD, fibrosis, mild steatosis, moderate to severe liver steatosis, mild MASLD, and moderate MASLD was 54%, 44%, 14%, 80%, 43%, and 34%, respectively. Regression analysis revealed that grade 1 LVDD was positively associated with age, Fibrotest, ɑ2-macroglobulin, epicardiac adipose tissue (EAT), and negatively associated with lateral s`, E wave, E/e`, E/A, medium E`, and septal e` (p< 0.05 for all). ɑ2-macroglobulin > 1.92 g/L (AUROC= 0.782, sensitivity 70.4%, specificity 81.2%) and fibrotest score > 0.11 (AUROC 0.766, sensitivity 92.6%, specificity 56.2%) were significant predictors of grade I LVDD. Conclusion: HF is a multifaceted disorder associated with multisystem organ damage, including nonalcoholic MASLD. Although the underlying mechanisms remain unclear, innovative non-invasive biomarkers, such as ɑ2-macroglobulin or fibrotest, could concurrently indicate liver stiffness and the likelihood of grade I LVDD, an early, asymptomatic HF stage in T2DM patients.

Body composition assessment helps conducting a healthy life or tracking the effectiveness of a weight management therapy. Ultrasound (US)-based body composition research has gained momentum because of the emergence of portable and inexpensive instruments bundled with user-friendly software. Previously, US-based assessment of body fat percentage (% BF) was found precise, but inaccurate in certain populations. Therefore, this study sought to compute % BF from subcutaneous fat thicknesses (SFs) given by US converting an anthropometric formula that involves skinfold thicknesses (SKFs) measured at the same sites. The symmetry of the body with respect to the central sagittal plane is an underlying assumption in both anthropometry and US-based body composition assessment, so measurements were taken on the right side of the body. Relying on experimental data on skinfold compressibility, we adapted 33 SKF formulas for US use and tested their validity against air displacement plethysmography on a study group of 97 women (BMI = 25.4 ± 6.4 kg/m², mean ± SD) and 107 men (BMI = 26.7 ± 5.7 kg/m²). For both sexes, the best proprietary formula had Lin’s concordance correlation coefficient (CCC) between 0.7 and 0.73, standard error of estimate (SEE) < 3% BF and total error (TE) > 6% BF—mainly because of the underestimation of % BF in overweight and obese subjects. For women (men) the best adapted formula had CCC = 0.85 (0.80), SEE = 3.2% (2.4%) BF, and TE = 4.6% (5.4%) BF. Remarkably, certain adapted formulas were more accurate for overweight and obese people than the proprietary equations. In conclusion, anthropometric equations provide useful starting points in the quest for novel formulas to estimate body fat content from ultrasound measurements.