Body adiposity index, body fat content and incidence of type 2 diabetes

Effects of ACLY Inhibition on Body Weight Distribution: A Drug Target Mendelian Randomization Study

Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: -1.17; 95% confidence interval (CI): -1.61 to -0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = -1.41; 95%CI = -1.81 to -1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts.

Dose-response association of obesity and risk of mental health among tehranian residents: result of a cross-sectional study

BACKGROUND

Obesity and mental health issues are two of the most prevalent global public health issues for a significant portion of people. The purpose of this study was to investigate the relationship between obesity indicators and mental health in Tehran-dwelling Iranian adults.

METHODS

We conducted a cross-sectional study on healthy Iranian adults using a convenience sampling technique. The short form of the Depression Anxiety and Stress Scale (DASS-21) was used to measure the outcome, and independent variables included body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body adiposity index (BAI), and a body shape index (ABSI). The relationship between obesity and mental health was investigated using a multivariate logistic regression model. The non-linear dose-response relationships were evaluated using restricted cubic splines (RCS) with three knots. The Benjamini-Hochberg procedure was used to adjust for multiple testing.

RESULTS

In our study of 434 participants, females made up 52% of the participants, with a mean age of 38.57 years. In all, 54.6%, 53.9%, and 56.6% were classified as having anxiety, depression, and stress respectively. Logistic regression analysis showed that the odds of mental health components including anxiety, depression, or stress was not significantly different across the tertiles of the obesity indicators. We observed a significant dose-response relationship between BAI and ABSI and the risk of anxiety (PBenjamini-Hochberg 0.028 > Pdose-response 0.023) and stress (PBenjamini-Hochberg 0.028 > Pdose-response 0.003) but not depression (PBenjamini-Hochberg 0.014 < Pdose-response 0.018). The lowest risk for anxiety was observed in people with a BAI of 28% and ABSI equal to 0.079. The risk of stress seemed to increase beyond an ABSI of 0.086.

CONCLUSION

Our findings showed no direct linear association between obesity indices and anxiety. However, a dose-response relationship was observed between BAI and ABSI and the risk of anxiety and stress, indicating the need for further investigation.

The Lipid Accumulation Product Index (LAP) and the Cardiometabolic Index (CMI) Are Useful for Predicting the Presence and Severity of Metabolic Syndrome in Adult Patients with Obesity

Background: The concomitant occurrence of obesity and metabolic syndrome (MetS) causes a significant worsening of a patient's clinical condition. Indexes that employ anthropometric measurements alone or associated with blood parameters have been investigated for their ability to identify MetS. This study aimed to evaluate the diagnostic accuracy of three of these indexes, the body adiposity index (BAI), the lipid accumulation product index (LAP), and the cardiometabolic index (CMI), in a cohort of 1912 adult subjects with obesity. Methods and Results: MetS was found in 62.3% of the enrolled subjects, with a higher prevalence in males (72.5%) than females (60.9%). Receiver operating characteristic (ROC) analysis was used to define which index performed better. The BAI was found to be the lowest-performing index, with an ROC area of 0.50, a sensitivity of 30.31%, a specificity of 74.48%, and a likelihood ratio of 1.19. On the contrary, the LAP and the CMI showed a comparable ROC area of 0.82. The LAP had a sensitivity of 63.06%, a specificity of 86.55%, and a likelihood ratio of 4.69, while the CMI had a sensitivity of 67.59%, specificity of 81.55%, and a likelihood ratio of 3.66. The analysis was also performed in the group divided into males and females, with overlapping results. Conclusions: The LAP and the CMI performed better than the BAI in detecting MetS both in the general population with obesity and in the male/female subgroups. In the future, it will be important to validate these useful diagnostic tools in order to employ them in clinical practices.

Adult obesity diagnostic tool: A narrative review

Obesity is a complex chronic metabolic disorder characterized by abnormalities in lipid metabolism. Obesity is not only associated with various chronic diseases but also has negative effects on physiological functions such as the cardiovascular, endocrine and immune systems. As a global health problem, the incidence and prevalence of obesity have increased significantly in recent years. Therefore, understanding assessment methods and measurement indicators for obesity is critical for early screening and effective disease control. Current methods for measuring obesity in adult include density calculation, anthropometric measurements, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, computerized imaging, etc. Measurement indicators mainly include weight, hip circumference, waist circumference, neck circumference, skinfold thickness, etc. This paper provides a comprehensive review of the literature to date, summarizes and analyzes various assessment methods and measurement indicators for adult obesity, and provides insights and guidance for the innovation of obesity assessment indicators.

Association between walking pace and incident type 2 diabetes by adiposity level: A prospective cohort study from the UK Biobank

AIMS

To investigate the combined association of adiposity and walking pace with incident type 2 diabetes.

METHODS

We undertook a prospective cohort study in 194 304 White-European participants (mean age 56.5 years, 55.9% women). Participants' walking pace was self-reported as brisk, average or slow. Adiposity measures included body mass index (BMI), waist circumference (WC) and body fat percentage (BF%). Associations were investigated using Cox proportional hazard models, with a 2-year landmark analysis. A four-way decomposition analysis was used for mediation and additive interaction.

RESULTS

The median (interquartile range) follow-up was 5.4 (4.8-6.3) years. During the follow-up period, 4564 participants developed type 2 diabetes. Compared to brisk-walking participants with normal BMI, those with obesity who walked briskly were at an approximately 10- to 12-fold higher risk of type 2 diabetes (hazard ratio [HR] 9.64, 95% confidence interval [CI] 7.24-12.84, in women; HR 11.91, 95% CI 8.80-16.12, in men), whereas those with obesity and walked slowly had an approximately 12- to 15-fold higher risk (HR 12.68, 95% CI 9.62-16.71, in women; HR 15.41, 95% CI 11.27-21.06, in men). There was evidence of an additive interaction between WC and BF% and walking pace among women, explaining 17.8% and 47.9% excess risk respectively. Obesity mediated the association in women and men, accounting for 60.1% and 44.9%, respectively.

CONCLUSIONS

Slow walking pace is a risk factor for type 2 diabetes independent of adiposity. Promoting brisk walking as well as weight management might be an effective type 2 diabetes prevention strategy given their synergistic effects.

Development and validation of a prediction equation for body fat percentage from measured BMI: a supervised machine learning approach

Body mass index is a widely used but poor predictor of adiposity in populations with excessive fat-free mass. Rigorous predictive models validated specifically in a nationally representative sample of the US population and that could be used for calibration purposes are needed. The objective of this study was to develop and validate prediction equations of body fat percentage obtained from Dual Energy X-ray Absorptiometry using body mass index (BMI) and socio-demographics. We used the National Health and Nutrition Examination Survey (NHANES) data from 5931 and 2340 adults aged 20 to 69 in 1999-2002 and 2003-2006, respectively. A supervised machine learning using ordinary least squares and a validation set approach were used to develop and select best models based on R² and root mean square error. We compared our findings with other published models and utilized our best models to assess the amount of bias in the association between predicted body fat and elevated low-density lipoprotein (LDL). Three models included BMI, BMI², age, gender, education, income, and interaction terms and produced R-squared values of 0.87 and yielded the smallest standard errors of estimation. The amount of bias in the association between predicted BF% and elevated LDL from our best model was -0.005. Our models provided strong predictive abilities and low bias compared to most published models. Its strengths rely on its simplicity and its ease of use in low-resource settings.

Nomogram model for the risk of insulin resistance in obese children and adolescents based on anthropomorphology and lipid derived indicators

OBJECTIVE

This study aims to screen for measures and lipid-derived indicators associated with insulin resistance (IR) in obese children and adolescents and develop a nomogram model for predicting the risk of insulin resistance.

METHODS

A total of 404 eligible obese children and adolescents aged 10-17 years were recruited for this study from a summer camp between 2019 and 2021. The risk factors were screened using the least absolute shrinkage and selection operator (LASSO)-logistic regression model, and a nomogram model was developed. The diagnostic value of the model was evaluated by plotting the receiver operator characteristic curve and calculating the area under the curve. Internal validation was performed using the Bootstrap method, with 1000 self-samples to evaluate the model stability. The clinical applicability of the model was assessed by plotting the clinical decision curve.

RESULTS

On the basis of the LASSO regression analysis results, three lipid-related derivatives, TG/HDL-c, TC/HDL-c, and LDL-c/HDL-c, were finally included in the IR risk prediction model. The nomogram model AUC was 0.804 (95% CI: 0.760 to 0.849). Internal validation results show a C-Index of 0.799, and the mean absolute error between the predicted and actual risks of IR was 0.015. The results of the Hosmer-Lemeshow goodness-of-fit test show a good model prediction (χ² = 9.523, P = 0.300).

CONCLUSION

Three early warning factors, TG/HDL-c, TC/HDL-c, and LDL-c/HDL-c, were screened, which can effectively predict the risk of developing IR in obese children and adolescents, and the nomogram model has an eligible diagnostic value.

Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements

BACKGROUND

The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches.

METHODS

A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate the DT's accuracy, sensitivity, and specificity using R software.

RESULTS

Traditionally, 1461 women and 875 men with T2DM (T2DM group). According to the LR, in males, WC and BIA (p-value < 0.001) and in females, demispan and WC (p-value < 0.001) had the highest correlation with T2DM development risk. The DT indicated that WC has the most crucial effect on T2DM development risk, followed by HC, and BAI.

CONCLUSIONS

Our results showed that in both men and women, WC was the most important anthropometric factor to predict T2DM.

Comparison of different obesity indices associated with type 2 diabetes mellitus among different sex and age groups in Nantong, China: a cross-section study

Background

Obesity is associated with type 2 diabetes mellitus (T2DM). However, the obesity index that is most closely related to type 2 diabetes remains controversial. Therefore, the aim of this study was to compare the associations of five anthropometric indices (body mass index [BMI], body adiposity index, waist circumference [WC], waist-to-hip ratio, and waist-to-height ratio [WHtR]) with T2DM among Chinese adults divided into four groups according to sex and age.

Methods

A total of 4007 adult participants (1669 men and 2338 women) were included in the study. Odds ratios (ORs) and 95% confidence intervals were used with binary logistic regression models to estimate the risk of T2DM for each obesity index. Furthermore, we compared the area under the receiver operating characteristic curve (AUC) of each obesity index for the criterion of T2DM under the influence of risk factors.

Results

WC had the highest OR (3.211 and 1.452) and AUC (0.783 and 0.614) in both age groups of men. However, WHtR (OR = 2.366, AUC = 0.771) and BMI (OR = 1.596, AUC = 0.647) were the optimal criteria for predicting T2DM among females in the 18–59 and ≥ 60 years age groups, respectively.

Conclusions

This study suggests that there is a positive association between obesity-related anthropometric indices and T2DM in different sex and age groups. WC appears to be the optimal anthropometric index for predicting T2DM in men. The optimal obesity indices related to T2DM were WHtR and BMI for women aged 18–59 and ≥ 60 years, respectively.

Anthropometric Indices as Long-Term Predictors of Diabetes in Impaired Fasting Glucose Metabolism: Findings in the PURE Study in Poland

This study aimed to assess the predictive value of anthropometric measurements in impaired fasting glucose progression to type 2 diabetes (T2DM) after 9 years of follow-up in the Prospective Urban and Rural Epidemiology (PURE) study run in Poland. The study group consisted of 283 patients aged 54.3 ± 8.9 years who had impaired fasting glucose at baseline and completed a 9-year-long follow-up. We analyzed body weight, height, waist (WC) and hip (HC) circumferences, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body mass index (BMI), and body adiposity index (BAI). Most individuals were overweight or obese according to BMI. Obesity occurred more often in men than women. The analysis highlighted the following three anthropometric parameters WHtR, BMI, and WC, each having equally good predictive power concerning the development of full-fledged T2DM in people with impaired fasting glucose. In conclusion, we confirmed the distinct harmfulness of obesity and pointed out the potential of easy-measured anthropometric parameters to self-control the risk of passing the impaired fasting glucose into T2DM.

Association of adiposity with diabetes: A national research among Chinese adults

BACKGROUND

Adiposity is an established risk factor for diabetes. The different measurements of adiposity for predicting diabetes have been compared in recent studies in Western countries. However, similar researches among Chinese adults are limited.

METHODS

Data were collected from a national survey conducted during September 2014 and May 2015 Among Chinese adults aged 40 years and older across 30 China's provinces. Multilevel model analysis was performed to examine the impacts of different obesity indices [body mass index (BMI), waist circumference (WC), lipid accumulation product index (LAP), visceral adiposity index (VAI), and body adiposity index (BAI)] on the risk of diabetes.

RESULTS

A total of 162 880 participants were included in this study. Of them, 54.47% were female. With an increase in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes significantly grew (P < 0.001). The multilevel model analysis showed that WC has the strongest impact on diabetes prevalence, while BAI was the weakest. For one SD increment in BMI, WC, LAP, VAI, and BAI, the prevalence of diabetes increased by 27.0% (Odds Ratio (OR) = 1.270, 95% Confidence interval (CI) = 1.251-1.289), 37.4% (OR = 1.374, 95% CI = 1.346-1.401), 28.1% (OR = 1.281, 95% CI = 1.266-1.297), 22.0% (OR = 1.220, 95% CI = 1.204-1.236), and 17.4% (OR = 1.174, 95% CI = 1.151-1.192), respectively.

CONCLUSION

Obesity indicators of BMI, WC, LAP, VAI, and BAI have significant positive relationships with the risk of diabetes. WC has the strongest impact on diabetes, while BAI has the weakest.

Comparison of different obesity indices related with hypertension among different sex and age groups in China

BACKGROUND AND AIMS

To compare the relationships of five obesity-related routine anthropometric indicators (body mass index (BMI), body adiposity index (BAI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR)) for hypertension in both sexes and among different age groups of the Chinese population.

METHODS AND RESULTS

A total of 12,064 adult participants (5638 males and 6426 females) were included. Odds ratios (OR) and 95% confidence intervals were used with binary logistic regression models to estimate the risk of hypertension for each obesity index. For the males, WHtR had the highest OR value in all age groups. The degrees of correlation between hypertension and the obesity indices for different age groups were different among the females. WC, BMI, and WHtR were the highest in the 18-44, 45-59, and ≥60 years age groups, respectively. Furthermore, we compared the area under the ROC curve (AUC) of each obesity index for the criterion of hypertension under the influence of risk factors. For the males, the AUC of WHtR was the largest (0.814, 0.710, and 0.662). WC (AUC = 0.820), BMI (AUC = 0.765), and WHtR (AUC = 0.668) tended to be the best criteria for hypertension among females in the 18-44, 45-59, and ≥60 years age groups respectively. In addition, BAI, as an obesity indicator proposed in recent years, has a positive association with hypertension except in 18-44 years women, which was not stronger than other obesity indicators.

CONCLUSIONS

For males, WHtR appears to be the best obesity index related with hypertension. For young, middle-aged, and elderly women, the best obesity indices related with hypertension are WC, BMI, and WHtR, respectively.

A new anthropometric index to predict percent body fat in young adults

OBJECTIVE

To propose a new anthropometric index that can be employed to better predict percent body fat (PBF) among young adults and to compare with current anthropometric indices.

DESIGN

Cross-sectional.

SETTING

All measurements were taken in a controlled laboratory setting in Seoul (South Korea), between 1 December 2015 and 30 June 2016.

PARTICIPANTS

Eighty-seven young adults (18-35 years) who underwent dual-energy x-ray absorptiometry (DXA) were used for analysis. Multiple regression analyses were conducted to develop a body fat index (BFI) using simple demographic and anthropometric information. Correlations of DXA measured PBF (DXA_PBF) with previously developed anthropometric indices and the BFI were analysed. Receiver operating characteristic curve analyses were conducted to compare the ability of anthropometric indices to identify obese individuals.

RESULTS

BFI showed a strong correlation with DXA_PBF (r = 0·84), which was higher than the correlations of DXA_PBF with the traditional (waist circumference, r = 0·49; waist to height ratio, r = 0·68; BMI, r = 0·36) and alternate anthropometric indices (a body shape index, r = 0·47; body roundness index, r = 0·68; body adiposity index, r = 0·70). Moreover, the BFI showed higher accuracy at identifying obese individuals (area under the curve (AUC) = 0·91), compared with the other anthropometric indices (AUC = 0·71-0·86).

CONCLUSIONS

The BFI can accurately predict DXA_PBF in young adults, using simple demographic and anthropometric information that are commonly available in research and clinical settings. However, larger representative studies are required to build on our findings.

Is Body Adiposity Index a Better and Easily Applicable Measure for Determination of Body Fat?

Objective: The BAI can be used to reflect %body fat. This study aimed to compare BAI with other methods used in the determination of body fat.Materials and Methods: A cross-sectional study was conducted in Turkish adults. BAI, BMI, WHR, WHtR, body weight, hip and waist circumference (WC), skinfold thicknesses (biceps, triceps, subscapular, suprailiac) were measured. Body fat was measured using Bioelectric Impedance Analysis.Results: The Bland-Altman analyses conducted in this study showed that for % body fat estimations, BIA was in excellent agreement with skinfold measurements (p = 0.131) without proportional bias (p = 0.082), but that BAI was not in agreement with BIA and skinfold measurement. There were a statistically significant positive correlation between BAI and other measurements in terms of females and males and also regardless of sex.Conclusion: BAI was not in agreement with BIA and skinfold measurement methods for % body fat estimations, it had a significantly stronger correlation with % fat calculated using BIA and skinfold thickness.

Association between dietary flavonoid intake and obesity among adults in Korea

This study aimed to investigate the association between dietary flavonoid intake and the prevalence of obesity using body mass index (BMI), waist circumference, and percent body fat (%BF) according to sex among Korean adults. Based on the Korean Health and Nutrition Examination Survey 2008-2011, 23 118 adults in Korea were included. Dietary intakes were obtained using 24-h dietary recall data. A higher total intake of flavonoid was associated with a lower prevalence of obesity in women, based on %BF (odds ratio [95% confidence interval] = 0.82 [0.71-0.94]), and abdominal obesity (0.81 [0.71-0.92]). The intake of flavonols (0.88 [0.78-0.99]), flavanones (0.81 [0.72-0.92]), flavanols (0.85 [0.74-0.97]), isoflavones (0.85 [0.75-0.96]), and proanthocyanidins (0.81 [0.71-0.92]) was inversely associated with abdominal obesity, and a higher intake of flavanones (0.87 [0.76-0.99]) and proanthocyanidins (0.85 [0.75-0.98]) was associated with a lower prevalence of obesity, with respect to %BF in women. In contrast, the intake of flavonols (1.16 [1.02-1.33]), flavanones (1.18 [1.04-1.35]), and anthocyanidins (1.27 [1.11-1.46]) was positively associated with obesity based on BMI in men. In conclusion, high intake of dietary flavonoids may be associated with a decreased prevalence of abdominal obesity and obesity, based on %BF, among women. Novelty Higher flavonoid intake was associated with decreased prevalence of abdominal obesity and obesity based on %BF in Korean women. However, in men, the intake of flavonols, flavanones, and anthocyanidins was positively associated with obesity as given by BMI.

Capacity of different anthropometric measures to predict diabetes in a Chinese population in southwest China: a 15-year prospective study

AIM

To investigate whether conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product compared with waist circumference could predict future diabetes in a 15-year prospective study.

METHODS

The data were collected in 1992 and recollected in 2007 from the same group of 687 individuals. Anthropometric indices and biochemical data were obtained. Cox's proportional hazards regression models were used to estimate the hazard ratios of anthropometric measures. The discriminatory power of anthropometric measures for incident diabetes were assessed by Harrell's C-statistic.

RESULTS

During follow-up, 74 participants were newly diagnosed with diabetes. In multivariable Cox regression analysis after adjusting potential for confounders, log₁₀ -conicity index [HR: 1.67 (95% CI: 1.31-2.11) per sd; P < 0.0001], log₁₀ -abdominal volume index [HR: 1.95 (95% CI: 1.50-2.55) per sd; P < 0.0001], log₁₀ -body adiposity index [HR: 1.82 (95% CI: 1.33-2.50) per sd; P < 0.0001], log₁₀ -body roundness index [HR: 2.16 (95% CI: 1.63-2.88) per sd; P < 0.0001], log₁₀ -cardiometabolic index [HR: 1.70 (95% CI: 1.39-2.09) per sd; P < 0.0001], log₁₀ -lipid accumulation product [HR: 2.06 (95% CI: 1.56-2.73) per sd; P < 0.0001] and log₁₀ -waist circumference [HR: 1.99 (95% CI: 1.51-2.46) per sd; P < 0.0001] were significantly associated with incident diabetes. Additionally, lipid accumulation product had the highest Harrell's C-statistic at 0.715 (95% CI: 0.656-0.775), followed by body roundness index at 0.714 (95% CI: 0.658-0.770) and cardiometabolic index at 0.704 (95% CI: 0.643-0.764) then by waist circumference at 0.701 (95% CI: 0.644-0.759).

CONCLUSIONS

Conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product were independent predictors of future diabetes. The discriminatory power of body roundness index, cardiometabolic index and lipid accumulation product for diabetes prediction were higher than that of waist circumference.

Triglycerides and waist to height ratio are more accurate than visceral adiposity and body adiposity index to predict impaired fasting glucose

AIMS

To evaluate the clinical accuracy of novel indices visceral adiposity index (VAI) and body adiposity index (BAI) to identify patients with impaired fasting glucose (IFG) and compare with its individual components and other obesity indicators.

METHODS

A cross-sectional study was conducted in Mexican population. Body mass index (BMI), waist circumference, hip circumference, triglycerides (TG), High density lipoprotein cholesterol (HDL-C), VAI, BAI, waist to hip ratio (WHR) and waist to height ratio (WHtR) were determined. We plotted a receiver operating characteristic curves to assess the abilities to discriminate subjects with IFG from those with normal glucose tolerance (NGT) of the measurements. A binary logistic regression analysis was performed to determine the strength of association with IFG.

RESULTS

A total of 280 individuals were included, from which 144 (51.3%) have IFG; the mean age was 47.14 years and 164 (55.5%) were females. Compared with NGT subjects, the participants with IFG had significantly higher levels of BMI, WHtR, VAI, BAI and TG. The measurements with highest area under the curve were TG, (0.631, 95% confidence interval [CI] 0.566-0.697) VAI (0.628, 95% CI 0.563-0.693) and WHtR (0.622, 95% CI 0.557-0.688) and in the adjusted binary logistic regression model, were found to be independently associated with IFG, Odds Ratio of 2.665, (95% CI 1.567-4.533) 2.567 (95% CI 1.527-4.317) and 2.171 (95% CI 1.102-4.276) respectively.

CONCLUSIONS

Our data provide evidence that TG, VAI and WHtR could be considered potential tools for the risk assessment of type 2 diabetes mellitus (T2DM) in this population.

Association between body adiposity index and coronary risk in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

BACKGROUND & AIMS

The body adiposity index (BAI) was recently proposed as a better indicator of body adiposity than body mass index in adults. The association between BAI and cardiometabolic risk factors has been widely investigated. However, the strength and magnitude of these associations varied as a function of the endpoint evaluated, the study design, the population investigated, and the cut-off points used. The aim of this study was to investigate the association between BAI and coronary heart disease (CHD) risk in a large sample of Brazilian adults and to propose the most appropriate cut-off points for BAI for the identification of CHD risk in the adult Brazilian population.

METHODS

Data from 15,092 civil servants (54.4% women) from universities and research institutes in six Brazilian states were evaluated in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). All were aged 35-74 years at baseline. The Framingham coronary risk score was used to identify a very high risk of CHD (≥20% risk of CHD over the next 10 years) and a high risk of CHD (≥10% risk). BAI cut-off points capable of detecting a risk of CHD were determined using ROC curves and associations were tested using Poisson regression with robust variance, according to sex and age. Three multivariable models were examined.

RESULTS

BAI remained positively associated with a very high and high risk of CHD following adjustment for potential confounding factors in all the strata and multivariable models (p < 0.05), with the exception of model 3 (adjusted for education level and waist-to-hip ratio) for very a high risk of CHD in younger women (p = 0.06). In the adjusted models, the prevalence ratios for a very high and high risk of CHD, irrespective of age group, varied between 1.23 (95%CI: 1.09-1.39) and 1.64 (1.33-2.03) and 1.07 (1.03-1.12) and 1.47 (1.36-1.60) in men; and 1.57 (1.08-2.31) and 2.42 (1.36-4.31) and 1.29 (1.13-1.47) and 1.82 (1.54-2.15) in women, respectively. The optimal cut-off points of BAI to determine a risk of CHD were: 28.0 in men of both age groups, and 34.0 in younger women and 36.0 in older women to determine a very high risk; and 26.0 in younger men and 34.0 in women of both age groups to determine a high risk. BAI showed a reasonable ability to predict coronary risk in participants of the ELSA-Brasil (AUC>60%, except for the group of men of 60-74 years of age).

CONCLUSIONS

Higher BAI levels were found to be associated with a greater risk of developing CHD in both men and women of different ages participating in the ELSA-Brasil, suggesting that BAI may be a useful tool for screening for CHD risk in Brazilian adults.

Prevalence of prediabetes and type 2 diabetes in two non-random populations aged 44-77 years in the Faroe Islands

AIMS

The prevalence of type 2 diabetes is increasing worldwide but little known about the status in the Faroe Islands. The aim was therefore to determine the prevalence of type 2 diabetes mellitus and prediabetes in two non-random populations aged 44-77 years.

METHODS

This cross-sectional survey was conducted between 2011 and 2012 and included two sub-populations, namely 518 Septuagenarians aged 74-77 years (84% of the invited) and 401 Mark aged 44-73 years (87% of the invited). Subjects were screened for glycosylated haemoglobin, type A1c, non-fasting random plasma glucose, fasting plasma glucose followed by an oral glucose tolerance test. The screening was based on a diagnostic algorithm that included screening, diagnostic and confirmatory steps.

RESULTS

Each group was analysed separately. In the Septuagenarian group 20.4% had type 2 diabetes, with 5.2% being newly detected and a total of 59% had prediabetes. In the Mark group 4.1% had diabetes, with 2.1% being newly detected and 22.3% had prediabetes. Diabetes increased with age and was significantly more prevalent among men. Women had lower mean fasting plasma glucose concentrations and men had lower values for 2-hours plasma glucose. Significant predictors associated with diabetes mellitus included obesity (BMI ≥ 30, abnormal waist/hip ratio and vegetable consumption.

CONCLUSIONS

Among the Faroese populations studied, the prevalence of type 2 diabetes increased with age and was more prevalent among men. The detected prevalence was comparable to other Nordic countries for all age-groups.

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.

A comparison of body mass index and percent body fat as predictors of cardiovascular risk factors

BACKGROUND

Cardiovascular disease (CVD) is an important cause of global mortality and morbidity. Body mass index (BMI) is the measure of adiposity that is used most frequently in CVD risk algorithms.

AIMS

We aimed to assess the relationship between several CVD risk factors (RFs) and percent body fat (PBF), and to compare the predictive values obtained using PBF for these cardiovascular RFs with the values obtained using BMI. The CVD RFs included, hypertension (HTN), diabetes mellitus (DM) and the presence of dyslipidemia (DLP).

METHODS AND MATERIALS

The data were derived from the MASHAD study, a cohort study of 9704 volunteers, aged 35-65 years and living in the city of Mashhad. Based on BMI and PBF values, subjects were classified into 4 groups; group 1 (low or normal BMI and PBF, N = 1670), group 2 (low or normal BMI but high PBF, N = 992), group 3 (high BMI and low or normal PBF, N = 837), and group 4 (high BMI and PBF, N = 6245). Chi-square, covariance and logistic regression were used to analyze the data at a significance level of 0.05.

RESULTS

There was an increasing trend from group 1 to group 4 for the mean values of all CVD RFs and their prevalence. There were significant differences in the frequency of a low HDL-C, this was substantially higher in Group 3 (38.6% in Group 3 versus 12.2% in Group 2); the frequency of a high serum TG (24% in Group 3 versus 9.9% in Group 2) and the frequency of dyslipidemia overall (56.2% in Group 3 and 28.8% in Group 2) (P-value<0.001 for all comparisons). The frequency of hypertension (22.9% in Group 3 versus 16.2% in Group 2) and IFG (8.5% in Group 3 versus 5.0% in Group 2) were also substantially higher in Group 3 compared to Group 2 (P-value<0.001 for both comparisons). All the mean values for the RFs were higher in group 3 from group 2 except HDL-C. When Group 1 was used as a reference and calculated OR of any RF for any group 2-4 rather than group 1, OR for all RF in group 3 was higher from group 2.

CONCLUSION

The differences in frequency, means and OR of RFs between Groups 2 and 3 showed a differential impact of a high BMI or high PBF. Compared to PBF, BMI may be a better predictor for several RFs for CVD.

Prevalence of type 2 diabetes and prediabetes in the Faroe Islands

AIMS

To determine the prevalence of type 2 diabetes mellitus and prediabetes among the population aged 40-74 years in the Faroe Islands.

METHODS

This population-based cross-sectional survey, conducted between 2011 and 2012, invited 2186 randomly selected individuals (corresponding to 11.1% of the entire population aged 40-74 years). Subjects were screened using finger capillary blood for glycosylated hemoglobin, type A1c, non-fasting random plasma glucose, fasting plasma glucose followed by oral glucose tolerance test. The test was based on an algorithm that accounts for screening, diagnostic and confirmatory steps. Anthropometric measures and a questionnaire including medical history, medication, hereditary conditions, and food intake were included.

RESULTS

The study included 1772 participants. Of the 1772, 169 (9.5%) had type 2 diabetes mellitus (3.0% of which were diagnosed upon study inclusion), thus 31.4% of subjects with diabetes were undiagnosed at the time of examination. A total of 271 (15.3%) had prediabetes. Diabetes was more prevalent among men, significantly from age ≥60 years. Women had lower mean fasting plasma glucose concentrations and men had lower values for 2-h plasma glucose. Predictors associated with diabetes mellitus included obesity (BMI ≥ 30), abnormal waist/hip ratio, history of hypertension or cardiovascular attack and family history of diabetes mellitus and leisure activity.

CONCLUSIONS

The prevalences of diabetes and prediabetes increased with age and were more frequent among men. The detected prevalence in the Faroe Islands was slightly higher than other Nordic countries.

Adiposity cut-off points for cardiovascular disease and diabetes risk in the Portuguese population: The PORMETS study

Objectives

The contribution of adiposity to cardiovascular and diabetes risk justifies the inclusion of an adiposity measure, usually waist circumference, in the definition of metabolic syndrome. However, waist circumference thresholds differ across populations. Our aim was to assess which adiposity measure performs the best in identifying the metabolic syndrome in a sample of Portuguese participants and to estimate cut-off values for these measures.

Methods

Data were obtained from a cross-sectional study (PORMETS study) conducted in Portugal between 2007 and 2009. A representative sample of non-institutionalized adults, comprising 3,956 participants, aged 18 years and older, was evaluated. A structured questionnaire was administered, collecting information on personal medical history, socio-demographics and behavioral characteristics. Anthropometrics, blood pressure and venous blood samples were also obtained. Metabolic syndrome was defined according to the Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology recommended criteria. Elevated cardiometabolic risk was considered when two or more of the four criteria of metabolic syndrome were present, excluding the waist circumference component. A receiver operating characteristic curve was used to estimate cut-off points.

Results

This study found that waist-to-height ratio, waist circumference and body adiposity index performed better than other adiposity measures, such as body mass index. The estimated cut-off points for waist-to-height ratio, waist circumference and body adiposity index in women and men were 0.564 / 89 cm / 27.4 and 0.571 / 93.5 cm / 25.5, respectively.

Conclusion

As waist circumference is currently used as the adiposity measure in the definition of metabolic syndrome and as no relevant differences were observed between this measure and waist-to-height ratio, it is likely that no modification to the metabolic syndrome definition needs to be proposed. Moreover, this study also confirmed the applicability of European cut-off points in the Portuguese population.

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.

Impact of body fat percentage change on future diabetes in subjects with normal glucose tolerance

The aim of the work was to determine the effect of body fat change on risk of diabetes in normal glucose tolerance (NGT) population. A total of 1,857 NGT subjects were included and followed up for an average period of 44.57 months. Body fat percentage (BF%) was measured by bioelectrical impedance analysis. Subjects were grouped based on the BF% and/or body mass index (BMI) state. Among all subjects, 28 developed diabetes after follow-up. Compared with subjects with stable normal BF% (control), subjects who became obesity at follow-up were defects in insulin secretion and had a higher risk of developing diabetes (7.102, 95% confidence intervals [CI] 1.740-28.993), while no difference in diabetic risk could be viewed between subjects with abnormal BF% at baseline but normal at the end of follow-up and control subjects after adjustment of confounding factors. Moreover, compared with those keeping normal BF% and BMI both at baseline and follow-up, subjects who had normal BMI at baseline and follow-up, but abnormal BF% at baseline or/and follow-up still had a higher risk to develop diabetes (4.790, 95% CI 1.061-21.621), while those with normal BF% at baseline and follow-up, but abnormal BMI at baseline or/and follow-up had not. Subjects from normal BF% at baseline to obese at follow-up are associated with an increased risk of diabetes. Maintaining normal body fat is more relevant than BMI in preventing diabetes. © 2017 IUBMB Life, 69(12):947-955, 2017.

Comparison of new adiposity indices for the prediction of body fat in hospitalized patients

OBJECTIVE

To measure the accuracy of the body mass index (BMI), BMI adjusted for fat mass (BMIfat), body adiposity index (BAI), BAI for the Fels Longitudinal Study sample, Clínica Universidad de Navarra-Body Adiposity Estimator, and fat mass index and to compare the accuracy to that of bioelectrical impedance and dual-energy x-ray absorptiometry (DXA) in a sample of the Brazilian population.

METHODS

A cross-sectional study conducted on 240 hospitalized patients, 43 (18%) male and 197 (83%) female. Mean patient ages were 53.0 ± 13.3 y for males and 53.49 ± 14.0 y for females. All subjects underwent anthropometric evaluation, bioelectrical impedance, and DXA, which permitted the calculation of the indices. The level of significance was set at P < 0.05 in the statistical analyses.

RESULTS

Mean subject age (y), weight (kg), and height (cm) were 53.0 ± 13.3 and 53.4 ± 14.0; 72.8 ± 14.9 and 67.6 ± 14.0; and 171.0 ± 8.0 and 157.0 ± 7.0 for men and women, respectively. Excess weight was detected in 67.4% and 66% according to the BMI, in 30% and 69.5% according to the BMIfat, and in 51% and 38% according to the BAI for men and women, respectively. Pearson correlation revealed that BMIfat clearly showed a better correlation (r = 0.67) with DXA than the remaining tools. The Clínica Universidad de Navarra-Body Adiposity Estimator was the only body adiposity parameter that was significantly higher in men compared to women.

CONCLUSION

The results suggest that BMIfat is the index best related to the prediction of body fat and that the BAI did not exceed the limits of the BMI. Further studies of this type are needed to strengthen the present findings.

Independent Aftereffects of Fat and Muscle: Implications for neural encoding, body space representation, and body image disturbance

Although research addressing body size misperception has focused on socio-cognitive processes, such as internalization of the “ideal” images of bodies in the media, the perceptual basis of this phenomenon remains largely unknown. Further, most studies focus on body size per se even though this depends on both fat and muscle mass – variables that have very different relationships with health. We tested visual adaptation as a mechanism for inducing body fat and muscle mass misperception, and assessed whether these two dimensions of body space are processed independently. Observers manipulated the apparent fat and muscle mass of bodies to make them appear “normal” before and after inspecting images from one of four adaptation conditions (increased fat/decreased fat/increased muscle/decreased muscle). Exposure resulted in a shift in the point of subjective normality in the direction of the adapting images along the relevant (fat or muscle) axis, suggesting that the neural mechanisms involved in body fat and muscle perception are independent. This supports the viability of adaptation as a model of real-world body size misperception, and extends its applicability to clinical manifestations of body image disturbance that entail not only preoccupation with thinness (e.g., anorexia nervosa) but also with muscularity (e.g., muscle dysmorphia).

Comparison of estimates of body fat content in childhood-onset systemic lupus erythematosus

Objective We aimed to compare estimates of body fat content with respect to their ability to predict the percentage of body fat, confirmed by dual-energy X-ray absorptiometry scans in childhood-onset systemic lupus erythematosus. Methods We included 64 consecutive childhood-onset systemic lupus erythematosus patients and 64 healthy age and sex-matched controls in a cross-sectional study. Anthropometric data, body mass index and body adiposity index were calculated for all subjects. Childhood-onset systemic lupus erythematosus patients were further assessed for clinical and laboratory childhood-onset systemic lupus erythematosus manifestations and fat mass, lean mass and percentage of body fat evaluated by dual-energy X-ray absorptiometry. Results Elevated waist/hip ratio was observed in childhood-onset systemic lupus erythematosus patients when compared to controls ( p < 0.001). We did not find differences between body mass index and body adiposity index classification in childhood-onset systemic lupus erythematosus patients and controls. Using dual-energy X-ray absorptiometry as gold standard we observed that all indirect estimates of body fat were correlated with whole body fat mass. We observed a correlation between height and cumulative corticosteroid dose adjusted by weight ( r = 0.429, p = 0.005) in childhood-onset systemic lupus erythematosus. On whole body analysis we observed a correlation between lean mass and ACR Damage Index scores ( r = -0.395; p = 0.019); percentage of body fat and adjusted Systemic Lupus Erythematosus Disease Activity Index ( r = 0.402; p = 0.008), disease duration ( r = -0.370; p = 0.012). On trunk analysis we observed a correlation between lean mass and ACR Damage Index ( r = -0.319; p = 0.042); percentage of body fat with adjusted Systemic Lupus Erythematosus Disease Activity Index ( r = 0.402; p = 0.005), disease duration ( r = -0.408; p = 0.005). Conclusions This is the first study analyzing body adiposity index in childhood-onset systemic lupus erythematosus patients. We observed that all indirect estimates of body fat were correlated with whole body fat mass. This study shows that we should not replace body mass index by body adiposity index to evaluating fat levels in childhood-onset systemic lupus erythematosus. In consideration of the importance of overweight classification in cardiovascular diseases, any direct estimates of body fat can be used in an attempt to improve the prognosis of patients. Note We believe that we have presented evidence of body adiposity index accuracy in childhood-onset systemic lupus erythematosus patients but further research on the generalizability of body adiposity index to other patient groups needs to be done.

Body roundness index and body adiposity index: two new anthropometric indices to identify metabolic syndrome among Chinese postmenopausal women

OBJECTIVES

Body roundness index (BRI) and body adiposity index (BAI) have been recently proposed to assess obesity. The objectives of this cross-sectional study were to compare their potential for identifying metabolic syndrome (MetS) with traditional obesity indices in Chinese postmenopausal women.

METHODS

A total of 817 participants were involved in this study. Odds ratio and corresponding 95% confidence intervals (CI) between MetS and all indices were evaluated by binary logistic regression analysis. Receiver operating characteristic curve and area under curve (AUC) were employed to evaluate the abilities to identify MetS among all the indices. The differences in the AUC values between traditional indices and BAI as well as BRI were also evaluated.

RESULTS

The upper values of all indices were significantly associated with the presence of MetS after adjusting for potential confounders, except for BAI. There were no significant differences in the AUC values between BRI and the traditional indices; however, the AUC values of all the traditional indices were significantly larger than that of BAI.

CONCLUSIONS

Neither BAI nor BRI was superior to traditional obesity indices for predicting MetS. BAI showed the weakest predictive ability, while BRI showed potential for use as an alternative obesity measure in assessment of MetS.

Correlation of adiposity indices with cardiovascular disease risk factors in healthy adults of Singapore: a cross-sectional study

Background

Obesity has long been highlighted for its association with increased incidence of cardiovascular disease (CVD). Nonetheless, the best adiposity indices to evaluate the CVD risk factors remain contentious and few studies have been performed in Asian populations. In the present study, we compared the association strength of percent body fat (PBF) to indirect anthropometric measures of general adiposity (body mass index (BMI) and body adiposity index (BAI)) and central adiposity (waist circumference (WC), and waist-to-hip ratio (WHR)) for the prediction of CVD risk factors in healthy men and women living in Singapore.

Methods

A total of 125 individuals (63 men and 62 women) took part in this study. PBF was measured by using three different techniques, including bioelectrical impedance analysis (BIA), BOD POD, and dual-energy X-ray absorptiometry (DEXA). Anthropometric measurements (WC, hip circumference (HC), height, and weight), fasting blood glucose (FBG), fasting serum insulin (FSI), and lipid profiles were determined according to standard protocols. Correlations of anthropometric measurements and PBF with CVD risk factors were compared.

Results

Irrespective of the measuring techniques, PBF showed strong positive correlations with FSI, HOMA-IR, TC/HDL, TG/HDL, and LDL/HDL in both genders. While PBF was highly correlated with FBG, SBP, and DBP in females, no significant relationships were observed in males. Amongst the five anthropometric measures of adiposity, BAI was the best predictor for CVD risk factors in female participants (r = 0.593 for HOMA-IR, r = 0.542 for TG/HDL, r = 0.474 for SBP, and r = 0.448 for DBP). For males, the combination of WC (r = 0.629 for HOMA-IR, and r = 0.446 for TG/HDL) and WHR (r = 0.352 for SBP, and r = 0.366 for DBP) had the best correlation with CVD risk factors.

Conclusion

Measurement of PBF does not outperform the simple anthropometric measurements of obesity, i.e. BAI, WC, and WHR, in the prediction of CVD risk factors in healthy Asian adults. While measures of central adiposity (WC and WHR) tend to show stronger associations with CVD risk factors in males, measures of general adiposity (BAI) seems to be the best predictor in females. The gender differences in the association between adiposity indices and CVD risk factors may relate to different body fat distribution in males and females living in Singapore. These results may find further clinical utility to identify patients with CVD risk factors in a more efficient way.

Electronic supplementary material

The online version of this article (doi:10.1186/s40608-016-0114-4) contains supplementary material, which is available to authorized users.

The Olivetti Heart Study: Predictive value of a new adiposity index on risk of hypertension, blood pressure, and subclinical organ damage

BACKGROUND AND AIMS

Recently, some studies have indicated that a new anthropometric index, body adiposity index (BAI), could be more strongly correlated with the percentage of body fat than BMI. However, the results on its role in predicting cardiovascular risk were not univocal. Therefore, the aim of our study was to compare the predictive role of BMI and BAI on risk of hypertension (HP), blood pressure (BP) changes, and subclinical organ damage after an 8-year follow-up, in a sample of adult men participating in the Olivetti Heart Study.

METHODS AND RESULTS

Participants were 350 untreated normotensive men without diabetes, examined twice at baseline (1994-95) and after 8 years of follow-up [2002-04]. BMI was expressed as kg/m(2). BAI was calculated according to the following formula: [(hip circumference (cm)/height(1.5) (m)) - 18]. Subclinical organ damage was detected by urinary albumin excretion (UAE) and left ventricular mass, evaluated by the Cornell product (CP). At baseline, BAI and BMI were both associated with diastolic blood pressure (DBP) and mean arterial pressure (MAP). After 8 years, both baseline BAI and BMI were associated with changes (Δ) in systolic BP, MAP and pulse pressure, while only BMI was also positively related to ΔDBP. Analysis of HP incidence showed that both indices were significant predictors of HP. In addition, both BAI and BMI were significantly associated with ΔUAE, but not with ΔCP. Analysis of the changes in BAI and BMI confirmed these results, as the two indices were significantly associated with risk of HP and changes in BP and UAE, but not with changes in CP.

CONCLUSIONS

In this sample of healthy adult men, BAI and BMI were significant predictors of risk of HP and changes in BP, after an 8-years follow-up. In addition both indices predicted UAE changes, but neither was associated with the CP changes.

The Validity of Body Adiposity Indices in Predicting Metabolic Syndrome and Its Components among Egyptian Women

AIM

To assess the associations between the body adiposity indices and risk of metabolic syndrome (MS) and its components in Egyptian women and to evaluate their predictive power.

MATERIALS AND METHODS

This was a cross-sectional analysis performed on 180 Egyptian women aged between 25-35 years. They were 90 women with MS diagnosed by International Diabetes Federation (IDF) and 90 healthy age matched controls. Body adiposity index (BAI), body mass index (BMI), waist to hip ratio (WHR) and waist to height ratio (WHtR) were calculated and serum samples were analyzed for metabolic parameters. Receiver operating characteristic curves (ROC) was used to determine the discriminatory capacity of BAI, WHR WHtR and BMI for MS.

RESULTS

Area under the curve (AUC) was highest for BIA, followed by WHR, WHtR and then BMI. All adiposity indices were significantly correlated with metabolic components and BAI had the highest correlation coefficients compared to other indices.

CONCLUSION

BAI is a practical predictor for MS and has satisfactory diagnostic accuracy for diagnosing MS among Egyptian women and can be used in addition to WHR, WHtR and BMI for identifying MS in the field studies.

Utility of novel body indices in predicting fat mass in elite athletes

OBJECTIVE

Recently, new body indices, including body adiposity (BAI), a body shape (ABSI), and body roundness (BRI) indices have been developed to estimate adiposity. The aim of this study was to compare percent fat mass (%FM) with novel indices in an elite athlete population.

METHODS

Using a cross-sectional design, %FM in 159 male and 50 female athletes using a four-component model was assessed. The %FM was compared with body mass index (BMI), BAI, ABSI, BRI, and with other %FM field methods (bioimpedance spectroscopy and skinfold prediction equation). These associations were determined using multilinear regression analysis, which resulted in predictive models of %FM in athletes. Cross-validation was performed using the prediction residual error sum of squares (PRESS) statistics method.

RESULTS

Although higher associations than other indices were observed, BRI still presented low coefficients of determination (men: R(2) = 0.36; women: R(2) = 0.25) when comparing with other field methods (R(2) range, 0.33-0.75). Using BAI as the independent variable, the R(2) was 0.07 for men and 0.14 for women. ABSI did not result in a significant association with %FM in women (R(2) = 0.05) while in men a significant association was found (R(2) = 0.22). The BMI model resulted in a R(2) = 0.20 for men and R(2) = 0.22 for women. Waist circumference and the sum of skinfolds were the anthropometric variables with the highest association with adiposity. New alternatives were presented with higher coefficients of determination (PRESS R(2) ranged from 0.47 to 0.71).

CONCLUSIONS

The newly developed body indices are limited in predicting %FM in elite athletes, particularly when compared with other commonly and readily available field methods like bioimpedance analysis or skinfold prediction models.

Body mass index and waist circumference rather than body adiposity index are better surrogates for body adiposity in a Chinese population

BACKGROUND

Several studies have found that body adiposity index (BAI) is a better index of body adiposity than body mass index (BMI) in African and Mexican American adults. This study aims to evaluate the ability of BAI to predict body adiposity in Chinese children and adults.

MATERIALS AND METHODS

In total, 2425 children and 5726 adults were recruited from rural China. All participants completed whole-body dual-energy X-ray absorptiometry (DXA) and anthropometric measures. The correlation of BMI, BAI, and waist circumference (WC) to DXA adiposity indexes was performed across sex-specific adult and age- and sex-specific child cohorts, using Spearman correlation and linear regression models, respectively.

RESULTS

Both BMI and WC had a higher correlation with all adiposity indexes (whole body fat, percent body fat [Bfat%], trunk fat, and percent trunk fat [Tfat%]) measured by DXA than did BAI in both adults and children. Meanwhile, most of the linear regression model associations for BMI with Bfat% and Tfat% had a greater adjusted R(2) than those for BAI among both children and adults.

CONCLUSION

This study indicates that BMI and WC are better tools than BAI for estimating whole body fat and central body fat in a Chinese population.

Body mass index and body adiposity index in relation to percent body fat: a study in adult men of three endogamous groups of South Bengal

Body adiposity index (BAI), based on height and hip circumference data from Mexican-Americans and African-Americans established its relation to body fat (BF). The aim of our study was to compare body mass index (BMI) and BAI in relation to BF%. Participants were adult men of three endogamous social groups (Brahmin, Muslim and Namasudra) in a village of South 24 Parganas district in West Bengal, India. Height, weight and hip circumference of 952 individuals (370 Brahmins, 307 Muslims and 275 Namasudras) were recorded. The BMI-based nutritional status and bioelectrical impedance-based BF% were evaluated. Namasudras (33.8%) and Muslims (33.6%) had high frequency undernutrition compared to Brahmins (7.3%). High prevalence (46.22%) of excess weight (overweight+obesity) was recorded only among Brahmins. There was significant social group difference in rates of nutritional status (χ(2) = 93.10, p < 0.0001). The BF% had higher correlation with BMI than BAI. A cut-off value of BAI (22%) was determined by binomial logistic regression analysis (BLRA). The value had best estimated relation to BF% and also coincided with WHO standard mean BF (22%) for overweight adults at BMI (≥ 25 kg/m(2)). However, greater area under the receiver operating characteristic curve, higher correct prediction rate, and other results of BLRA for the cut-off value of BMI-based overweight (≥ 25 kg/m(2)) showed its better relation to BF% than that observed for BAI cut-off at 22%. The BMI was observed to be a better indicator of adiposity compared to BAI in relation with body fat (%).

Alteration of postprandial glucose and insulin concentrations with meal frequency and composition

A frequent eating pattern may alter glycaemic control and augment postprandial insulin concentrations in some individuals due to the truncation of the previous postprandial period by a subsequent meal. The present study examined glucose, insulin, C-peptide and glucose-dependent insulinotropic peptide (GIP) responses in obese individuals when meals were ingested in a high-frequency pattern (every 2 h, 6M) or in a low-frequency pattern (every 4 h, 3M) over 12 h. It also examined these postprandial responses to high-frequency, high-protein meals (6MHP). In total, thirteen obese subjects completed three 12 h study days during which they consumed 6276 kJ (1500 kcal): (1) 3M - 15 % protein and 65 % carbohydrate; (2) 6M - 15 % protein and 65 % carbohydrate; (3) 6MHP - 45 % protein and 35 % carbohydrate. Blood samples were collected every 10 min and analysed for glucose, insulin, C-peptide and GIP. Insulin total AUC (tAUC) and peak insulin concentrations (P< 0·05) were higher in the 3M condition than in the 6M condition, but there were no differences in glucose tAUC between the conditions. The 6MHP regimen (glucose: 3569 (se 83) mmol/l × min (64·3 (se 1·5) g/dl × min), insulin: 1·577 (se 0·146) pmol/l (22·7 (se 2·1) μIU/dl) for 12 h) lowered glucose and insulin excursions more so over 12 h than either the 3M regimen (glucose: 3913 (se 78) mmol/l × min (70·5 (se 1·4) g/dl × min), insulin: 2·195 (se 0·146) pmol/l × min (31·6 (se 2·1) μIU/dl × min) for 12 h) or the 6M regimen (glucose: 3902 (se 83) mmol/l × min (70·3 (se 1·5) g/dl × min), insulin: 1·861 (se 0·174) pmol/l × min (26·8 (se 2·5) μIU/dl × min) for 12 h; P< 0·01). Insulin secretion, GIP concentrations and the glucose:insulin ratio were not altered by meal frequency or composition. In obese subjects, ingestion of meals in a low-frequency pattern does not alter glucose tAUC, but increases postprandial insulin responses. The substitution of carbohydrates with protein in a frequent meal pattern results in tighter glycaemic control and reduced postprandial insulin responses.

The validity of the body adiposity index in predicting percentage body fat and cardiovascular risk factors among Chinese

OBJECTIVE

Recent research has suggested that body adiposity index (BAI) correlates more closely with percentage body fat (PBF) than body mass index (BMI). Here, we aimed to evaluate BAI's predictive power for PBF and for obesity-associated risk factors in the Chinese population.

SUBJECTS

A total of 1707 women and 680 men aged 51-77 years were analysed in this community-based cross-sectional study.

MEASUREMENTS

Body weight, height, waist circumference (WC) and hip circumference (HC) were measured, and BMI and BAI were calculated. Percentage body fat was determined by dual-energy X-ray absorptiometry (DXA). Blood pressure, fasting lipid profiles, glucose and Carotid ultrasound examination determined intima-media thickness (IMT) at the common carotid arteries (CCA) were also measured.

RESULTS

The Pearson correlation analysis indicated a stronger correlation between BAI and PBF when women and men were pooled together, but this effect disappeared in sex-stratified analysis. Bland-Altman plots suggested that BAI underestimated 5·8% of PBF in women and slightly overestimated 0·28% of PBF in men, but the magnitudes of these biases showed a fat mass-dependent manner. Both the logistic regression and the receiver operating characteristic curve (ROC) analysis indicated that BAI has an inferior predictive power for the presence of hypertension, dyslipidaemia, metabolic syndrome and CCA-intima-media thickening, compared with BMI and WC.

CONCLUSION

We concluded that BAI was neither a better predictor for PBF nor for cardiovascular risks in Chinese population compared with BMI and WC.

Body adiposity index and incident hypertension: the Aerobics Center Longitudinal Study

BACKGROUND AND AIM

The body adiposity index (BAI) has been recently proposed as a new method to estimate the percentage of body fat. The association between BAI and hypertension risk has not been investigated yet. The aim of our study was to evaluate the ability of BAI to predict hypertension in males and females compared with traditional body adiposity measures.

METHODS AND RESULTS

The present follow-up analysis comprised 10,309 individuals (2259 females) free of hypertension from the Aerobics Center Longitudinal Study, who completed a baseline examination between 1988 and 2003. Body adiposity measures included BAI, body mass index (BMI), waist circumference, hip circumference, percentage of body fat and waist to hip ratio (WHR). Incident hypertension was ascertained from responses to mail-back surveys between 1990 and 2004. During an average of 9.1 years of follow-up, 872 subjects (107 females) became hypertensive. Hazard ratios (HRs) and 95% confidence intervals (95% CI) showed that males in the highest categories of all body adiposity measures showed a higher incident risk of hypertension (HRs ranged from 1.37 to 2.09). Females showed a higher incident risk of hypertension only in the highest categories of BAI, BMI and WHR (HRs ranged from 1.84 to 3.36).

CONCLUSION

Our results suggest that in order to predict incident hypertension BAI could be considered as an alternative to traditional body adiposity measures.

Comparison of the body adiposity index to body mass index in Korean women

PURPOSE

Obesity is a major public health issue and is associated with many metabolic abnormalities. Consequently, the assessment of obesity is very important. A new measurement, the body adiposity index (BAI), has recently been proposed to provide valid estimates of body fat percentages. The objective of this study was to compare the BAI and body mass index (BMI) as measurements of body adiposity and metabolic risk.

MATERIALS AND METHODS

This was a cross-sectional analysis performed on Korean women. The weight, height, and hip circumferences of 2950 women (mean age 25±5 years old, 18-39 years) were measured, and their BMI and BAI [hip circumference (cm)/height (m)1.5-18] values were calculated. Bioelectric impedance analysis was used to evaluate body fat content. Glucose tolerance status was assessed with a 75-g oral glucose tolerance test, and insulin sensitivity was estimated with the insulin sensitivity index.

RESULTS

BMI was more significantly correlated with fat mass and fat percentage. Additionally, BMI was also more significantly associated with metabolic parameters, including fasting glucose, post-load 2-h glucose, fasting insulin, post-load 2-h insulin, triglycerides, and high density lipoprotein cholesterol than BAI. Receiver operating characteristic curve analysis revealed that BMI was a better tool for predicting body fat percentage than BAI. Insulin sensitivity and metabolic syndrome were more significantly associated with BMI than with BAI.

CONCLUSION

In Korean women, the current BMI-based classifications for obesity might be superior to BAI-based measurements for determining obesity and predicting metabolic risk.

Body mass index, waist circumference, body adiposity index, and risk for type 2 diabetes in two populations in Brazil: general and Amerindian

Objective

The use of the anthropometric indices of adiposity, especially body mass index and waist circumference in the prediction of diabetes mellitus has been widely explored. Recently, a new body composition index, the body adiposity index was proposed. The aim of this study was to compare the effectiveness of body mass index, waist circumference, and body adiposity index in the risk assessment for type 2 diabetes mellitus.

Design and methods

A total of 1,572 individuals from the general population of Vitoria City, Brazil and 620 Amerindians from the Aracruz Indian Reserve, Brazil were randomly selected. BMI, waist circumference, and BAI were determined according to a standard protocol. Type 2 diabetes mellitus was diagnosed by the presence of fasting glucose ≥126 mg/dL or by the use of antidiabetic drugs.

Results

The area under the curve was similar for all anthropometric indices tested in the Amerindian population, but with very different sensitivities or specificities. In women from the general population, the area under the curve of waist circumference was significantly higher than that of the body adiposity index. Regarding risk assessment for type 2 diabetes mellitus, the body adiposity index was a better risk predictor than body mass index and waist circumference in the Amerindian population and was the index with highest odds ratio for type 2 diabetes mellitus in men from the general population, while in women from the general population waist circumference was the best risk predictor.

Conclusion

Body adiposity index was the best risk predictor for type 2 diabetes mellitus in the Amerindian population and men from the general population. Our data suggest that the body adiposity index is a useful tool for the risk assessment of type 2 diabetes mellitus in admixture populations.

Multiple measures of adiposity are associated with mean leukocyte telomere length in the northern Finland birth cohort 1966

Studies of leukocyte telomere length (LTL) and adiposity have produced conflicting results, and the relationship between body mass index (BMI) and telomere length throughout life remains unclear. We therefore tested association of adult LTL measured in 5,598 participants with: i) childhood growth measures (BMI and age at adiposity rebound (AR)); ii) change in BMI from childhood to adulthood and iii) adult BMI, waist-to-hip ratio (WHR), body adiposity index (BAI). Childhood BMI at AR was positively associated with LTL at 31 years in women (P = 0.041). Adult BMI and WHR in both men (P = 0.025 and P = 0.049, respectively) and women (P = 0.029 and P = 0.008, respectively), and BAI in women (P = 0.021) were inversely associated with LTL at 31 years. An increase in standardised BMI between early childhood and adulthood was associated with shorter adult LTL in women (P = 0.008). We show that LTL is inversely associated with multiple measures of adiposity in both men and women. Additionally, BMI increase in women from childhood to adulthood is associated with shorter telomeres at age 31, potentially indicating accelerated biological ageing.

A new predictive equation for evaluating women body fat percentage and obesity-related cardiovascular disease risk

BACKGROUND

Obesity represents a global public health problem due to its association with cardiovascular diseases and reduced lifespan. The most widely used classification of obesity is expressed as Body Mass Index (BMI); however, this formula is an imprecise adiposity measurement that ignores several important factors involved. Body Adiposity Index (BAI) was more recently proposed as an indirect evaluation of percentage body fat (PBF). PBF is a direct measure of person's relative body fat and a better predictor of obesity-related risk diseases than BMI and BAI. Since obesity and consequent diseases are considered epidemic, new accurate formulas for epidemiological studies are of interest to the scientific community. Because direct measurement of body composition could be quite expensive, the aims of our work were to analyse the distributions of PBF by Dual X-ray absorptiometry, and the creation of new predictive equation using only anthropometric measures that could be helpful to clinicians to assess easily body fat of female patients.

METHODS/RESULTS

A sample of 1,031 Caucasian Italian women was recruited and BMI, BAI and PBF were evaluated. With the aim of developing a predictive model of PBF a multivariate regression model was fitted to observed data.

CONCLUSIONS

The definition of universally recognized PBF by gender and age could have public health implications. In this study, we developed a new predictive PBF equation that does not require the use of medical instruments or skilled measurement techniques and that may be easily applicable to Italian women.

Obesity as assessed by body adiposity index and multivariable cardiovascular disease risk

To assess the role of body adiposity index (BAI) in predicting cardiovascular disease (CVD) and coronary heart disease (CHD) mortality, in comparison with body mass index (BMI), waist circumference (WC), and the waist circumference to hip circumference ratio (WHR). This study was a prospective 15 year mortality follow-up of 4175 Australian males, free of heart disease, diabetes and stroke. The Framingham Risk Scores (FRS) for CHD and CVD death were calculated at baseline for all subjects. Multivariable logistic regression was used to assess the effects of the measures of obesity on CVD and CHD mortality, before adjustment and after adjustment for FRS. The predictive ability of BAI, though present in the unadjusted analyses, was generally not significant after adjustment for age and FRS for both CVD and CHD mortality. BMI behaved similarly to BAI in that its predictive ability was generally not significant after adjustments. Both WC and WHR were significant predictors of CVD and CHD mortality and remained significant after adjustment for covariates. BAI appeared to be of potential interest as a measure of % body fat and of obesity, but was ineffective in predicting CVD and CHD.