Obesity among postmenopausal women: what is the best anthropometric index to assess adiposity and success of weight-loss intervention?

Abstract

Objectives: First, to establish the respective ability of body mass index (BMI), waist circumference (WC), and relative fat mass index (RFM), to estimate body fat (BF%) measured by DXA (DXA-BF%) and correctly identify postmenopausal women living with obesity (BF% > 35). Second, to identify the best indicator of successful weight-loss intervention in postmenopausal women living with obesity. Methods: A total of 277 women (age: 59.8 ± 5.3 y; BF%: 43.4 ± 5.3) from five weight-loss studies with complete data for anthropometric measurements [BMI = weight/height (kg/m2); WC (cm)] and BF% were pooled together. Statistical performance indicators were determined to assess ability of RFM [64−(20 × height/waist circumference) + (12 × sex)], BMI and WC to estimate BF% before and after weight-loss intervention and to correctly identify postmenopausal women living with obesity. Results: Compared with RFM (r = 0.51; r 2 = 0.27; RMSE = 4.4%; Lin's CCC = 0.46) and WC (r = 0.49; r 2 = 0.25; RMSE = 4.8%; Lin's CCC = 0.41), BMI (r = 0.73; r 2 = 0.52; RMSE = 3.7%; Lin's CCC = 0.71) was the best anthropometric index to estimate DXA-BF% and correctly identify postmenopausal women living with obesity (sensitivity + specificity: BMI = 193; RFM = 152; WC = 158), with lower misclassification error, before weight-loss intervention. After weight-loss, the change in BMI was strongly correlated with change in DXA-BF%, indicating that the BMI is the best indicator of success weight-loss intervention. Conclusion: In the absence of more objective measures of adiposity, BMI is a suitable proxy measure for BF% in postmenopausal women, for whom a lifestyle intervention is relevant. Furthermore, BMI can be used as an indicator to assess success of weight-loss intervention in this subpopulation.

Estimation of Absolute and Relative Body Fat Content Using Noninvasive Surrogates: Can DXA Be Bypassed?

“…Analysis required the use of nonlinear functions having the form of Equation 3, with evident asymptotic maximums of FTBF-about 0.48 for men and 0.55 for females-despite very high values of BMI, %IBW, waist circumference, and TBF by DXA. Similar patterns have been described previously 30,33,[49][50][51][52][53][54] and are suggestive of physiologic upper limits on FTBF. Further, the fractions of variance in FTBF explained by the independent variables in univariate analysis were relatively small (R 2 not exceeding 0.72; Table 3).…”

Efficacy of black rice extract on obesity in obese postmenopausal women: a 12-week randomized, double-blind, placebo-controlled preliminary clinical trial

“…The major findings of this study were the significant differences in trunk fat (kg and %), total fat mass (kg and %), and TG, compared to placebo. Since fat mass is linked to a variety of cardiometabolic comorbidities, it is one of the most important outcomes of weight-loss interventions and a measure of their effectiveness 33 . Participants supplementing with BRE observed improved body structure changes by restricting their intake to anthocyanin-rich foods.…”

Threshold values of anthropometric indicators of obesity for screening of low muscle mass in elderly women as a method for early diagnosis of sarcopenia

“…et al (2020) снижение мышечной силы и увеличение висцеральной жировой ткани связаны со снижением продолжительности жизни [7]. Известно, что ожирение является основным модифицируемым фактором риска развития сахарного диабета, сердечно-сосудистых заболеваний, дислипидемии и артериальной гипертензии, а абдоминальное ожирение связано со смертностью [8].…”