scholarly journals Trunk Fat Estimation According To Gender In Childhood Through Basic Somatic Readings. An Opportunity for Improving Girl’S Evaluation

2021 ◽  
Author(s):  
Manuel Moya ◽  
Virginia Pérez-Fernández
Keyword(s):  
Waist Circumference ◽  
Pediatric Obesity ◽  
Cardiometabolic Risk ◽  
Ad Hoc ◽  
Normal Weight ◽  
Height Ratio ◽  
Exclusion Criteria ◽  
Waist To Height Ratio ◽  
Total Fat ◽  
Better Than

Abstract Background: Easy appraisal of trunk fat and the eventual cardiometabolic risk of pediatric obesity is a present requirement. Its estimators Waist-to-Height Ratio (WHtR) and Relative Fat Mass pediatric (RFMp, expressed as % of total fat content), can be a complement of widely accepted BMI.Methods: 472 children (39% boys), classified as underweight, normal weight, overweight and obese (Nutritional groups, NG) according to BMI Z-score after their strictly obtained anthropometric initial data, with ad hoc exclusion criteria. Calculation of WHtR and RFMp was done for each nutritional group and sex, as associations through multiple linear regression (MLR) and differences among sexes (medians, IQR).Results: Age (mean (95% CI)), 10.8 y (10.1- 11.1). Estimators values in: All group WHtR 0.5 (0.49 – 0.51), RFMp% 32.3 (31.7 – 33.0); Underweight, WHtR 0.41 (0.40 – 0.41), RFMp (%) 22.8 (21.2 – 24.4); Normal weight, WHtR 0.46 (0.45 – 0.47), RFMp(%) 28.9 (28.1 – 29.7); Overweight, WHtR 0.51 (0.50 – 0.52), RFMp(%) 34.2 (33.3 – 35.1) and Obese WHtR 0.56 (0.55 – 0.57), RFMp(%) 37.8 (36.9 – 38.6). Associations (NG; independent variables): In NG adjusted R² values were between 0.74-0.78. In All group Beta coefficients were for RFMp 3.36 (P< 0.001) for girls; for waist circumference (WC 2.97 (P< 0.001) and for WHtR were respectively -0.01 (p< 0.001) and 0.03 (p< 0.001) Sex differences: BMI were in NG without gender differences (Mann-W’s U). Whereas WHtR (median IQR) differ (M vs F) respectively in: All group 0.49 (0.45 - 0.54) vs 0.52 (0.45 - 0.56), p<0.004; in Overweight 0.51 (0.48 – 0.53) vs 0.54 (0.51 – 0.55), p< 0.001; in Obese 0.55 (0.52 – 0.57) vs 0.57 (0.54 – 0.60), p< 0.004. RFMp (%): in All 29.21 (24.27 – 32.92) vs 36.63 (30.2 – 39.51), p< 0.001; in Overweight 31.24 (28.35 – 32.35) vs 37.95 (35.75 – 38.82), p<0.001 and in Obese 35.89 (32.05 – 36.15) vs 40.63 (38.27 – 42.42), p<0.001.Conclusions: WHtR and RFMp are simple and reliable indexes not requiring centile charts. Their values, including waist circumference, can estimate the different trunk fat component in boys and girls better than BMI, especially if overweight and obese. RFMp proved to be more reliable as it considers gender. Reasonably, both should be included in routine anthropometric readings.

scholarly journals Estimating trunk fat in children according to sex using basic somatic readings: an opportunity for improving evaluation among girls

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Manuel Moya ◽  
Virginia Pérez-Fernandez
Keyword(s):  
Waist Circumference ◽  
Fat Mass ◽  
Ad Hoc ◽  
Total Sample ◽  
Normal Weight ◽  
Obese Group ◽  
Overweight Group ◽  
Beta Coefficient ◽  
Total Fat ◽  
Better Than

Abstract Background The fat mass estimators waist-to-height ratio (WHtR) and relative fat mass—pediatric (RFMp) complement the widely accepted body mass index (BMI) in obesity evaluation. Aims of the Study: Conduct an easy appraisal of trunk fat and the cardiometabolic risk associated with pediatric obesity. Methods A total of 472 children (39% boys in the total sample) were classified as underweight, normal weight, overweight or obese (nutritional groups, NGs) according to BMI Z-score after initial anthropometric data were obtained and ad hoc exclusion criteria were applied. WHtR and RFMp (% of total fat) were calculated for each group, associations were assessed through multiple linear regression (MLR), and differences between sexes were evaluated (medians, IQR). Results The mean age (mean (95% CI)) was 10.8 y (10.1–11.1). The values in the total sample were as follows: WHtR, 0.5 (0.49–0.51) and RFMp%, 32.3 (31.7–33.0). In the overweight group, the values were as follows: WHtR, 0.51 (0.50–0.52) and RFMp(%), 34.2 (33.3–35.1). In the obese group, the values were as follows: WHtR, 0.56 (0.55–0.57) and RFMp(%), 37.8 (36.9–38.6). The associations were as follows (NG; independent variables): In the NG, adjusted R2 values were between 0.74 and 0.78. In the total sample, the beta coefficient was 3.36 (P < 0.001) for RFMp for girls; for waist circumference (WC), the beta coefficient was 2.97 (P < 0.001), and for WHtR the beta coefficients were − 0.01 (p < 0.001) and 0.03 (p < 0.001),for girls and for WC respectively. The sex differences were as follows: BMI exhibited no differences in the NG (Mann-Whitney U). WHtR (median (IQR)) differed (M vs. F) in the total sample (0.49 (0.45–0.54) vs. 0.52 (0.45–0.56), p < 0.004); in the overweight group (0.51 (0.48–0.53) vs. 0.54 (0.51–0.55), p < 0.001); and in the obese group (0.55 (0.52–0.57) vs. 0.57 (0.54–0.60), p < 0.004). RFMp (%) differed in the total group (29.21 (24.27–32.92) vs. 36.63 (30.2–39.51), p < 0.001); in the overweight group (31.24 (28.35–32.35) vs. 37.95 (35.75–38.82), p < 0.001) and in the obese group (35.89 (32.05–36.15) vs. 40.63 (38.27–42.42), p < 0.001). Conclusions WHtR and RFMp are simple and reliable indices that do not require centile charts. Their values, including waist circumference, can be used to estimate the different trunk fat components in boys and girls better than BMI, especially if individuals are overweight or obese. RFMp proved to be more reliable as it considers sex. Both should be included in routine anthropometric readings.

scholarly journals Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3–7 years

2014 ◽  
Vol 33 (2) ◽  
pp. 311-315 ◽  
Author(s):  
Anna Sijtsma ◽  
Gianni Bocca ◽  
Carianne L'Abée ◽  
Eryn T. Liem ◽  
Pieter J.J. Sauer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Waist Circumference ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Height Ratio ◽  
Waist To Height Ratio

Association between waist circumference and waist-to-height ratio with insulin resistance biomarkers in normal-weight adults working in a private educational institution

2019 ◽  
Vol 13 (3) ◽  
pp. 2041-2047 ◽  
Author(s):  
Diego Urrunaga-Pastor ◽  
Luciana De La Fuente-Carmelino ◽  
Carlos J. Toro-Huamanchumo ◽  
Miriam Pérez-Zavala ◽  
Vicente A. Benites-Zapata
Keyword(s):  
Insulin Resistance ◽  
Waist Circumference ◽  
Educational Institution ◽  
Normal Weight ◽  
Height Ratio ◽  
Waist To Height Ratio

scholarly journals Comparison of the ability to identify cardiometabolic risk factors between two new body indices and waist-to-height ratio among Chinese adults with normal BMI and waist circumference

2016 ◽  
Vol 20 (6) ◽  
pp. 984-991 ◽  
Author(s):  
Peng Ju Liu ◽  
Fang Ma ◽  
Hui Ping Lou ◽  
Yan Ning Zhu
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Waist Circumference ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Chinese Adults ◽  
Height Ratio ◽  
Obese Adults ◽  
Auc Value ◽  
Waist To Height Ratio

AbstractObjectiveWaist-to-height ratio (WHtR) has been reported to be more strongly associated with cardiometabolic risk factors among non-obese individuals than BMI and waist circumference (WC). A body shape index (ABSI) and body roundness index (BRI) have been proposed recently to assess obesity-related disorders or mortalities. Our aim was to compare the ability of ABSI and BRI with that of WHtR to identify cardiometabolic risk factors in Chinese adults with normal BMI and WC.DesignReceiver-operating characteristic curves and areas under the curve (AUC) were employed to evaluate the ability of the indices (WHtR, BRI, ABSI) to identify metabolic risk factors and to determine the indices’ optimal cut-off values. The value of each index that resulted in maximization of the Youden index (sensitivity + specificity – 1) was defined as optimal. Differences in the AUC values between the indices were also evaluated.SettingIndividuals attending a voluntary health check-up in Beijing, China, July–December 2015, were recruited to the study.SubjectsNon-obese adults (n 1596).ResultsAmong both genders, ABSI exhibited the lowest AUC value for identifying each risk factor among the three indices; the AUC value of BRI for identifying each risk factor was very close to that of WHtR, and no significant differences were observed between the AUC values of the two new indices.ConclusionsWhen evaluating cardiometabolic risk factors among non-obese adults, WHtR was a simple and effective index in the assessment of cardiometabolic risk factors, BRI could be used as an alternative body index to WHtR, while ABSI could not.

A considerable proportion of metabolic syndrome-free adults from Bratislava-region, Slovakia, display an increased cardiometabolic burden

2021 ◽  
Author(s):  
Dávid Miláček ◽  
Katarína Volkovová ◽  
Martin Gajdoš ◽  
Katarína Šebeková
Keyword(s):  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Cardiometabolic Risk ◽  
Reference Population ◽  
Considerable Proportion ◽  
Operating Characteristics ◽  
Height Ratio ◽  
Increased Risk ◽  
Waist To Height Ratio

Although the dichotomous classification of metabolic syndrome (MS) enables the classification of individuals as MS-free or presenting MS, it is inconvenient for assessing cardiometabolic risk in MS-free ones. Continuous MS score allows for estimation of cardiometabolic burden even in MS-free subjects. We used the scores to estimate the proportion of MS-free subjects on high cardiometabolic risk. 876 subjects (62% females) of Central European descent, aged 20-81 years, were included. IDF criteria were employed to classify MS. Continuous scores were calculated. We used the receiver operating characteristics (ROC) analysis to estimate the cutoff value to determine the proportion of MS-free subjects on increased risk. Using the waist circumference, 38% of males and 23% of females presented MS. ROC area under the curves (90-98%) showed an acceptable performance of both scores to classify the presence of MS. Up to 18% of MS-free males and up to 10% of females displayed continuous score ≥ the relevant cut-off point. The waist-to-height ratio performed similar results. Both continuous scores were proven credible for assessing cardiometabolic risk in MS-free subjects. Clinically, this is important for earlier intervention. Despite minor differences between waist circumference and waist-to-height ratio, it would be appropriate to objectify it using reference population.

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