Body Adiposity Index Performance in Estimating Body Fat Percentage in Colombian College Students: Findings from the FUPRECOL-Adults Study

Ability of Anthropometric Measurements to Predict Metabolic Health among Patients in Alberta: A Cross-sectional Study in Primary Care

Purpose: This study compared anthropometric and body fat percent (BF%) equations in relation to measures of metabolic health.Methods: BF% calculations (Bergman, Fels, and Woolcott) and anthropometric measurements were used to determine obesity among a sample of patients attending primary care in Alberta, Canada. Anthropometric variables included body mass index (BMI), waist circumference, waist:hip ratio, waist:height ratio, and calculated BF%. Metabolic Z-score was computed as the average of the individual Z-scores of triglycerides, total cholesterol, and fasting glucose and the number of standard deviations from the sample mean.Results: Five hundred and fourteen individuals were included (41.2% male, age: 53 ± 16y, BMI: 27.4 ± 5.7 kg/m2). BMI ≥ 30 kg/m2 detected the smallest number of participants (n = 137) as having obesity, while Woolcott BF% equation categorized the largest number of participants as having obesity (n = 369). No anthropometric or BF% calculation predicted metabolic Z-score in males (all p ≥ 0.05). In females, age-adjusted waist:height ratio had the highest prediction power (R2 = 0.204, p < 0.001), followed by age-adjusted waist circumference (R2 = 0.200, p < 0.001) and age-adjusted BMI (R2 = 0.178, p < 0.001).Conclusions: This study did not find evidence that BF% equations more strongly predicted metabolic Z-scores than other anthropometric values. In fact, all anthropometric and BF% variables were weakly related to metabolic health parameters, with apparent sex differences.

Evaluation of the body adiposity index against dual-energy X-ray absorptiometry for assessing body composition in children and adolescents

BACKGROUND

It is important to clarify the association of lean and fat mass between children and adolescents considering the rising prevalence of overweight and obesity in this age group. The aim of this study was to verify the association between the body adiposity index (BAI) and dual-energy X-ray absorptiometry (DXA) methods for analyzing body composition, as well as analyzing the validity of BAI to verify the percentage of fat in children and adolescents.

METHODS

The sample was composed of 106 children and adolescents, 44 females (age: 11.5 ± 1.8 years) and 62 evils (13.6 ± 2.6 years). The body fat (%F) was measured using DXA and the doubly indirect BAI body fat estimation technique.

RESULTS

The BAI and DXA estimates of %F were strongly correlated (boys: r = .71, P < .0001; girls: r = .72, P < .0001). The linear regression analyses showed that BAI is significant to estimate the %F in total sample (P < .0001). For boys, the %F analyzes performed by BAI and DXA did not show any differences when compared (P = .2). In addition, BAI pointed out a significant proportion bias for both sexes (P < .0001), which suggests its inefficiency in the analysis of %F.

CONCLUSIONS

BAI and DXA correlate; however, there is low reliability and a high proportion bias for the analysis of %F by BAI.

Muscle strength cut-offs for the detection of metabolic syndrome in a nonrepresentative sample of collegiate students from Colombia

BACKGROUND

Evidence shows an association between grip strength and health; however, grip strength cut-offs for the detection of metabolic syndrome (MetS) in Latin American populations are scarce. The purpose of this study was to determine cut-offs of normalized grip strength (NGS) for the detection of MetS in a large nonrepresentative sample of a collegiate student population from Colombia.

METHODS

A total of 1795 volunteers (61.4% female; age = 20.68 ± 3.10 years, mean ± SD), ranging between 18 and 30 years of age participated in the study. Strength was estimated using a handheld dynamometer and normalized to body mass (handgrip strength (kg)/body mass (kg)). Anthropometrics, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis. MetS was defined as including ≥3 of the 5 metabolic abnormalities according to the International Diabetes Federation definition. A metabolic risk score was computed from the following components: waist circumference, triglycerides, high-density lipoprotein cholesterol, glucose, and systolic and diastolic blood pressure.

RESULTS

Receiver operating curve analysis showed significant discriminatory accuracy of NGS in identifying the thresholds and risk categories. Lower strength was associated with increased prevalence of MetS. In males, weak, intermediate, and strong NGS values at these points were <0.466, 0.466-0.615, >0.615, respectively. In females, these cut-off points were <0.332, 0.332-0.437, >0.437, respectively.

CONCLUSION

Our sex-specific cut-offs of NGS could be incorporated into a clinical setting for identifying college students at cardiometabolic disease risk.

Assessment of adiposity distribution and its association with diabetes and insulin resistance: a population-based study

BACKGROUND

Rational measures in estimating adiposity distribution in diabetic patients has yet to be validated. This study aims to provide insight about the possible links between routinely available body adiposity parameters and the development of both diabetes and insulin resistance.

METHODS

We performed a population-based cross-sectional study in 9496 subjects aged 40 years or older. All of the body adiposity measures including body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR), visceral adiposity index (VAI), body adiposity index (BAI) and lipid accumulation product index (LAP) were separately evaluated according to standard measurement methods. Diabetes was diagnosed according to the American Diabetes Association 2010 criteria.

RESULTS

All tested body adiposity measurements were significantly associated with fasting plasma glucose (FPG), oral glucose tolerance test (OGTT) 2 h glucose, HbA1c and fasting insulin. Compared with other adiposity phenotypes, LAP have shown the relatively strongest while BAI have shown the relatively weakest association with increased odds of both diabetes and insulin resistance across all logistic regression models. Additionally, LAP provided the best discrimination accuracy for diabetes [area under the curve (AUC): 0.658 95% confidence intervals (CI) 0.645-0.671] and insulin resistance (AUC: 0.781 95% CI 0.771-0.792) when compared with other body adiposity parameters.

CONCLUSIONS

The LAP index seems to be a better indicator than other adiposity measures tested in the study to evaluate the association of visceral fat mass with diabetes and insulin resistance, which should be given more consideration in the clinical practice.

Muscle mass to visceral fat ratio is an important predictor of the metabolic syndrome in college students

This study aimed to evaluate the associations between the muscle mass to visceral fat (MVF) ratio and cardiometabolic risk factors in a large population of college students in Colombia and to propose cut-off points of this index for the metabolic syndrome (MetS). A total of 1464 young adults recruited from the FUPRECOL (Asociación de la Fuerza Prensil con Manifestaciones Tempranas de Riesgo Cardiovascular en Jóvenes y Adultos Colombianos) study were categorised into four groups based on their MVF ratio. Muscle mass and visceral fat level of the participants were measured using a bioelectrical impedance analysis. Cardiometabolic risk factors including lifestyle characteristics, anthropometry, blood pressure and biochemical parameters were assessed. The prevalence of moderate to severe obesity, hypertension and the MetS was higher in subjects in quartile (Q)1 (lower MVF ratio) (P <0·001). ANCOVA revealed that the subjects in Q1 had higher cardiometabolic disturbances, including altered anthropometry, blood pressure, muscle strength and biochemical parameters after adjusting for age and sex compared with young adults in higher MVF ratio quartiles (P <0·001). Muscular mass and physical activity levels were significantly lower in subjects with a lower MVF ratio (P <0·001). The receiver operating characteristic curve analyses indicated that in men the best MVF ratio cut-off point for detecting the MetS was 18·0 (AUC 0·83, sensitivity 78 % and specificity 77 %) and for women, the MVF ratio cut-off point was 13·7 (AUC 0·85, sensitivity 76 % and specificity 87 %). A lower MVF ratio is associated with a higher risk cardiometabolic profile in early adulthood, supporting that the MVF ratio could be used as a complementary screening tool that may help clinicians identify young adults at high cardiometabolic risk.

Tri-Ponderal Mass Index vs. Fat Mass/Height³ as a Screening Tool for Metabolic Syndrome Prediction in Colombian Children and Young People

Tri-ponderal mass index (TMI) and fat mass index (FMI) have been proposed as alternative approaches for assessing body fat since BMI does not ensure an accurate screening for obesity and overweight status in children and adolescents. This study proposes thresholds of the TMI and FMI for the prediction of metabolic syndrome (MetS) in children and young people. For this purpose, a cross-sectional study was conducted on 4673 participants (57.1% females), who were 9–25 years of age. As part of the study, measurements of the subjects’ weight, waist circumference, serum lipid indices, blood pressure and fasting plasma glucose were taken. Body composition was measured by bioelectrical impedance analysis (BIA). The TMI and FMI were calculated as weight (kg)/height (m³) and fat mass (kg)/height (m³), respectively. Following the International Diabetes Federation (IDF) definition, MetS is defined as including three or more metabolic abnormalities. Cohort-specific thresholds were established to identify Colombian children and young people at high risk of MetS. The thresholds were applied to the following groups: (i) a cohort of children where the girls’ TMI ≥ 12.13 kg/m³ and the boys’ TMI ≥ 12.10 kg/m³; (ii) a cohort of adolescents where the girls’ TMI ≥ 12.48 kg/m³ and the boys’ TMI ≥ 11.19 kg/m³; (iii) a cohort of young adults where the women’s TMI ≥ 13.21 kg/m³ and the men’s TMI ≥ 12.19 kg/m³. The FMI reference cut-off values used for the different groups were as follows: (i) a cohort of children where the girls’ FMI ≥ 2.59 fat mass/m³ and the boys’ FMI ≥ 1.98 fat mass/m³; (ii) a cohort of adolescents where the girls’ FMI ≥ 3.12 fat mass/m³ and the boys’ FMI ≥ 1.46 fat mass/m³; (iii) a cohort of adults where the women’s FMI ≥ 3.27 kg/m³ and the men’s FMI ≥ 1.65 kg/m³. Our results showed that the FMI and TMI had a moderate discriminatory power to detect MetS in Colombian children, adolescents, and young adults.

Anthropometric Indicators of Adiposity Related to Body Weight and Body Shape as Cardiometabolic Risk Predictors in British Young Adults: Superiority of Waist-to-Height Ratio

Frequently reported poor dietary habits of young adults increase their risk of metabolic syndrome (MetS). Excess adiposity is the most established predictor of MetS, and numerous anthropometric measures have been proposed as proxy indicators of adiposity. We aimed to assess prevalence of MetS in young adult population and to make comparison between weight- and shape-oriented measures of adiposity to identify the best index in association with measured body fat and as a risk predictor for MetS. Healthy males and females aged 18-25 years from the Northwest of England were recruited using convenience sampling (n=550). As part of the assessment of the overall health of young adults, the biochemical variables and adiposity measures BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), new BMI, Body Adiposity Index (BAI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), and A Body Shape Index (ABSI) were assessed. Linear regression analysis was used to investigate the association between the proxy indices of adiposity and measured percentage body fat. The odds ratio with 95% confidence interval was used to investigate the relationship between cardiometabolic (CM) risk factors and proxy measures of adiposity. The discriminatory power of these measures for diagnosis of MetS was investigated using area under the receiver operating characteristic curve. Body weight-related indicators of adiposity, particularly CUN-BAE, had stronger association with measured body fat compared with body shape-related indices. In relation with MetS, body shape-related indices, particularly elevated WC and WHtR, had stronger associations with CM risk compared with body weight-related measures. Amongst all indices, the best predictor for CM risk was WHtR, while ABSI had the weakest correlation with body fat, MetS, and CM risk. Indices directly associated with WC and specifically WHtR had greater diagnostic power in detection of CM risk in young adults.

The Role of Body Adiposity Index in Determining Body Fat Percentage in Colombian Adults with Overweight or Obesity

The aim of this study is to investigate the accuracy of body adiposity index (BAI) as a convenient tool for assessing body fat percentage (BF%) in a sample of adults with overweight/obesity using bioelectrical impedance analysis (BIA). The study population was composed of 96 volunteers (60% female, mean age 40.6 ± 7.5 years old). Anthropometric characteristics (body mass index, height, waist-to-height ratio, hip and waist circumference), socioeconomic status, and diet were assessed, and BF% was measured by BIA-BF% and by BAI-BF%. Pearson’s correlation coefficient was used to evaluate the correlation between BAI-BF% and BF% assessed by BIA-BF%, while controlling for potential confounders. The concordance between the BF% measured by both methods was obtained with a paired sample t-test, Lin’s concordance correlation coefficient, and Bland-Altman plot analysis. Overall, the correlation between BF% obtained by BIA-BF% and estimated by BAI-BF% was r = 0.885, p < 0.001, after adjusting for potential confounders (age, socioeconomic status, and diet). Lin’s concordance correlation coefficient was moderate in both sexes. In the men, the paired t-test showed a significant mean difference in BF% between the methods (−5.6 (95% CI −6.4 to −4.8); p < 0.001). In the women, these differences were (−3.6 (95% CI −4.7 to −2.5); p < 0.001). Overall, the bias of the BAI-BF% was −4.8 ± 3.2 BF%; p < 0.001), indicating that the BAI-BF% method significantly underestimated the BF% in comparison with the reference method. In adults with overweight/obesity, the BAI presents low agreement with BF% measured by BIA-BF%; therefore, we conclude that BIA-BF% is not accurate in either sex when body fat percentage levels are low or high. Further studies are necessary to confirm our findings in different ethnic groups.

Percentage of Body Fat and Fat Mass Index as a Screening Tool for Metabolic Syndrome Prediction in Colombian University Students

High body fat is related to metabolic syndrome (MetS) in all ethnic groups. Based on the International Diabetes Federation (IDF) definition of MetS, the aim of this study was to explore thresholds of body fat percentage (BF%) and fat mass index (FMI) for the prediction of MetS among Colombian University students. A cross-sectional study was conducted on 1687 volunteers (63.4% women, mean age = 20.6 years). Weight, waist circumference, serum lipids indices, blood pressure, and fasting plasma glucose were measured. Body composition was measured by bioelectrical impedance analysis (BIA) and FMI was calculated. MetS was defined as including more than or equal to three of the metabolic abnormalities according to the IDF definition. Receiver operating curve (ROC) analysis was used to determine optimal cut-off points for BF% and FMI in relation to the area under the curve (AUC), sensitivity, and specificity in both sexes. The overall prevalence of MetS was found to be 7.7%, higher in men than women (11.1% vs. 5.3%; p < 0.001). BF% and FMI were positively correlated to MetS components (p < 0.05). ROC analysis indicated that BF% and FMI can be used with moderate accuracy to identify MetS in university-aged students. BF% and FMI thresholds of 25.55% and 6.97 kg/m² in men, and 38.95% and 11.86 kg/m² in women, were found to be indicative of high MetS risk. Based on the IDF criteria, both indexes’ thresholds seem to be good tools to identify university students with unfavorable metabolic profiles.