Associations between dietary intake of flavonoids and adiposity: cross-sectional findings from the Fenland Study, the United Kingdom.

Abdominal fat distribution and insulin resistance in Indian women with polycystic ovarian syndrome

Background/Aim. Obesity status can be assessed with numerous anthropometric, morphological and functional indices and this study was designed to assess relationship among them. The aim of this study was to investigate associations between anthropometric indices, ultrasonography measurement of visceral and subcutaneous fat tissue thickness and certain proinflammatory adipokines level. Methods. This cross-sectional study comprised a consecutive sample of 60 obese respondents without obesity-related comorbidities, and 20 age-matched healthy normal-weight controls. Anthropometric [body mass index (BMI), waist circumference (WC), neck circumference (NC), body fat, a body shape index (ABSI)], and ultrasonographic indices [thickness of intraabdominal fatt tissue (IAFT), visceral fat (VF), maximum subcutaneous fat (Max SFT), minimal subcutaneous fat (Min SFT)], and serum levels of chemerin and resistin were assessed in all subjects. Results. All anthropometric indices showed statistically significant differences between study groups. The mean IAFT, Max SFT, Min SFT and VF were significantly higher in the obese group compared to controls (p < 0.01, for all). Serum levels of chemerin and resistin correlated positively with BMI, percentage of fat adipose tissue (FAT, %), total FAT (kg), and VF (p < 0.05, for all). Also, we observed significant correlation between resistin and NC (r = 0.23, p = 0.03) and ABSI (r = 0.22, p = 0.04). In multivariable linear regression analysis, chemerin (? = 0.23; p = 0.008) and resistin (? = 0.43; p =0.002) were independently and significantly associated only with VF. Conclusion. Obesity indices, both classical and newer ones, are in positive, statistically significant correlation with the level of proinflammatory cytokines. Ultrasonographically measured VF thickness, independently associated with adipokine levels, may improve assessment of proinflammatory fat tissue characteristics. Further studies are needed to precisely define the use of ultrasonographic fat tissue measurements into clinical practice.

Interventions such as testosterone treatment may change body composition and metabolic outcomes without substantial changes in weight and BMI. Using testosterone treatment as a paradigm, we hypothesized that a body shape index (ABSI) reflects body composition changes more accurately than traditional markers, such as weight, BMI and waist circumference. Secondary analysis of a 56-week RCT in 100 dieting obese men with low-normal testosterone receiving testosterone treatment or placebo, and subsequent off-treatment follow-up. At the end of the trial period, ABSI-unlike weight, BMI or waist circumference-had significantly decreased in the treatment group, compared with placebo (mean adjusted difference -0.18 [95% CI:-0.32, -0.05] × 10-2 m11/6kg-2/3, overall P<0.001). Changes in ABSI during the active trial phase correlated with changes in fat mass (tau = 0.18, P = 0.02), and not with lean mass (tau = -0.11, P = 0.14), BMI (tau = 0.10, P = 0.17), or visceral fat (tau = 0.07, P = 0.37). ABSI baseline values were positively correlated with waist circumference (tau = 0.21, P = 0.002) and visceral fat (tau = 0.18, P = 0.009), correlated inversely with lean mass (tau = -0.21, P = 0.002), and were uncorrelated with BMI (tau = -0.10, P = 0.15) and fat mass (tau = 0.01, P = 0.83). Two years after cessation of treatment, ABSI again reflected body composition as the between-group differences in all parameters did not persist. A readily obtainable anthropomorphic measure, ABSI reflects the differential loss of fat mass mediated by testosterone in dieting obese men more closely than BMI or waist circumference. It may serve as a clinically useful marker to monitor body composition changes, particularly in response to interventions.

Background Previous research has demonstrated that waist circumference (WC) and hip circumference (HC) are both important predictors of mortality, independent of established risk factors. Their combined influence on risk, and whether they are superior to established obesity measures, has not been thoroughly examined in large cohorts. Purpose We investigated whether WC and HC are better joint predictors of all-cause and cardiovascular disease (CVD) mortality than individual measures of obesity: WC, HC, waist hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), and body mass index (BMI). Methods We used data from 90,487 males and females, 25–74 years of age with no prior history of CVD, from the MOnica Risk, Genetics, Archiving and Monogram (MORGAM) project. Hazard mortality ratios (HR) were estimated using sex-specific Cox models stratified by cohort/country, with age as the time scale. Obesity measures were categorized based on sex specific sample means and standard deviations (SD). All final fully adjusted models included baseline age, total and HDL cholesterol, systolic blood pressure,antihypertensive drugs, current smoker and diabetes. Results During a mean follow-up of 11 years, 9105 all-cause and 2577 CVD deaths were recorded. All obesity measures were found to be associated with all-cause and CVD death after taking account of known CVD risk factors, with the strongest statistical evidence of associations seen for WC and HC combined and ABSI. J- or U-shaped associations with mortality were observed for BMI, WC, HC and WHtR for both males and females, and WHR and ABSI for males. Monotonic associations with mortality were observed for WHR and ABSI for females. For WC and HC combined, HC was an important predictor of death among those with smaller WC (≤1 SD above the mean: below 99cm in women and 106cm in men), with larger HCs associated with reduced risk. No additional increase in mortality risk was found to be associated with HC for those with a WC &gt;1SD above the mean. Of those who would not have been identified as being at higher risk based on their WC alone, 55.7% (n=8350) of females and 30.6% (n=4510) of males are identified as being at higher risk when their smaller HC is taken into consideration. Conclusion The use of single measurements of obesity such as BMI, WC or WHR does not capture the complex relationship between body shape and risk of premature death. Both WC and HC, but not as a ratio, should be used by clinicians to help identify those at increased risk of premature death. Acknowledgement/Funding Individual grants to included cohorts

Visceral fat is associated with cardiovascular and kidney disease. However, the relationship between body composition and anthropometric measures in type 1 diabetes is unknown. Using z-statistics, we ranked the ability of body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR) and a body shape index (ABSI) to capture measures of body composition from 603 Dual-energy-X-Ray-Absorptiometry scans of adults with type 1 diabetes. Albuminuria was defined as urinary albumin excretion rate of at least 30 mg/24 h. Women with albuminuria had higher visceral fat mass % (VFM%) (0.9 vs. 0.5%, p = 0.0017) and lower appendicular lean mass % (AppLM%) (25.4 vs 26.4%, p = 0.03) than those without. Men with albuminuria had higher VFM% (1.5 vs. 1.0%, p = 0.0013) and lower AppLM% (30.0 vs 32.3, p < 0.0001) than those without. In men, WHtR estimated VFM% best (z-statistics = 21.1), followed by WC (z = 19.6), BMI (z = 15.1), WHR (z = 14.6) and ABSI (z = 10.1). In women, the ranking was WC (z = 28.9), WHtR (z = 27.3), BMI (z = 20.5), WHR (z = 12.7) and ABSI (z = 10.5). Overall, the ranking was independent of albuminuria. Adults with type 1 diabetes and albuminuria have greater VFM% and lower AppLM% than those without. WHtR and WC best estimate the VFM% in this population, independently of albuminuria and sex.

Ratio of visceral fat area to body fat mass (VBR) is a superior predictor of coronary heart disease.

The issue of body size between methods and substance

ABSTRACTObjective: The role of dietary glycemic index (GI) and glycemic load (GL) in the development of obesity has been debated globally. The relationship with body shape and fat distribution was examined in this cross-sectional association study among apparently healthy Iranian adults.Methods and materials: A study population of 265 (126 males and 139 females) aged 18–55 years participated in this cross-sectional study from the communities of Tehran based on cluster sampling. GI and GL were assessed by the 147-item food frequency questionnaire (FFQ) completed by a trained dietitian. Weight, height, waist circumference (WC), and hip circumference of the participants were measured, and body mass index (BMI), waist-to-hip ratio (WHR), and A Body Shape Index (ABSI) were further calculated. Fat mass and fat-free mass were also measured using a body composition analyzer, and fat mass index (FMI) and fat-free mass index (FFMI) were then calculated. Multivariate regression models were fitted to assess the association between GI/GL and fat distribution measures such as FMI, FFMI, WC, BMI, WHR, and ABSI, considering potential confounding factors such as sex, age, BMI, and physical activity.Results: There was a statistically significant inverse association between GL and WC, BMI, and ABSI found in the adjusted model. GL was inversely associated with WC for both the adjusted model (p-trend = 0.027) and the crude model. Also, an inverse association was seen between GL and BMI (p-trend = 0.019) in the adjusted model but a marginal association in the crude model. GL was also inversely associated with ABSI (p-trend = 0.089) in the highest tertile.Conclusion: Dietary GL but not GI is inversely associated with fat distribution measures such as WC, BMI, and ABSI in the study population. This result may suggest a beneficial role of higher-GL diets in the prevention of obesity.

IntroductionBody mass index (BMI) is unable to make a distinction between muscle mass and fat mass. Therefore, new anthropometric measurements, such as a body shape index (ABSI), body round index (BRI), and body adiposity index (BAI), have been formulated in recent years. Many studies have reported a correlation between BMI and thyroid function. In this study, we aimed to investigate the relationship between the above-mentioned new anthropometric measurements and thyroid functions in euthyroid obese subjects.MethodsWe included 675 euthyroid (TSH ≥ 0.4 and < 4.5 mIU/l) individuals from the obesity outpatient clinic, aged between 18 and 65 years old, with BMI ≥ 30. Thyroid-stimulating hormone (TSH), free T4 (fT4) and free T3 (fT3), anthropometric measurements (weight, height, and waist circumference), and bioelectric impedance analyses [percent body fat (PBF) and fat-free mass (FFM)] of individuals were measured and recorded. ABSI, BRI, and BAI were calculated with the data from these measurements. Anthropometric measurements were compared to thyroid function tests.ResultsEighty percent of the subjects were female. The mean age and BMI were 38 ± 17 years and 38 ± 6 kg/m2, respectively. TSH was found to be negatively correlated with ABSI (p = 0.006) and positively correlated with BAI (p < 0.001), but a statistically significant relationship with BRI (p = 0.193) was not determined. Free T4 was not associated with any of the anthropometric measurements.While fT3 was determined to be positively correlated with ABSI (p = 0.008) and negatively correlated with PBF and BAI (p = 0.001, p = 0.002, respectively), no statistically significant relationship with fT3 and BRI was determined.ConclusionTSH is positively correlated with measurements of adiposity such as BMI, PBF, BAI while indexes in which abdominal obesity increases, such as waist circumference (WC), waist-hip ratio (WHR), and ABSI, are correlated with fT3 levels.

ObjectiveAmong indirect measures of visceral adiposity, A Body Shape Index (ABSI), which is defined as waist circumference (WC)/(body mass index (BMI)2/3×height1/2), is unique in that ABSI is positively correlated with...

Determining the best method for evaluating obesity and the risk for non-communicable diseases in women of childbearing age by measuring the body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, A Body Shape Index, and hip index

Obesity, a prevalent global health issue, is associated with testosterone deficiency (TD). A body shape index (ABSI) provides a more precise assessment of obesity and visceral fat, but its relationship with testosterone remains unclear. This study aimed to explore the association between ABSI and testosterone levels leading to TD. Data from 5256 adult males participating in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016 were collected to analyze of the association between ABSI and TD. The data underwent analysis using multivariate linear regression, logistic regression, restricted cubic spline (RCS) analysis, subgroup analysis, and interaction testing. The predictive ability of ABSI based on weight, height, and waist circumference, as well as body mass index (BMI) based on weight and height, alongside a multiplicative combination of both metrics, BMI × ABSI, and optimal proportional combination OBMI + ABSI for assessing TD risk, was valuated using receiver operating characteristic (ROC) curves. Following adjustment for all confounding factors, ABSI exhibited a negative linear correlation with testosterone (β = -6.99, 95% confidence interval (CI): -8.25 to -5.73; p < 0.001) and a positive association with TD risk (odds ratio (OR) = 1.06, 95% CI: 1.04-1.08; p < 0.001). Notably, these associations remained consistent in the subgroup analysis. Additionally, age and hypertension demonstrated significant interactions between ABSI and TD (p < 0.05). Moreover, combining metrics, such as BMI × ABSI and OBMI + ABSI, proved to be more reliable predictors of TD compared to BMI or ABSI alone. This study identified a negative linear correlation between ABSI and total testosterone levels in adult American males, as well as a positive linear correlation with TD prevalence. ABSI represents a valuable addition to BMI for assessing obesity and the association between obesity and TD.

Obesity is a global epidemic and belongs to major risk factors for the most prevalent diseases. Anthropometric measures are simple, inexpensive, non-invasive tools to diagnosis obesity and to assess the risk of morbidity and mortality. The most widely used are body mass index (BMI), waist circumference (WC), waist-to-hip (WHR) and waist-to-height ratios, visceral fat area (VFA), body fat (BFP) and a new body shape index (ABSI). The aim of this study was to examine the usefulness of the ABSI in obesity diagnosis compared with other anthropometric parameters like WC, WHR, BMI, VFA, and BFP. We also compared the predictability between ABSI and above mentioned common anthropometric indices. The study group was composed of 236 university students. Body height, weight, WC was measured and BMI, WHR, ABSI and ABSI z-score were calculated. The anthropometric measurements were made by using InBody 720 (Biospace Co. Ltd., Seoul, Republic of Korea). Body composition, especially VFA, BFP, FFM was diagnosed by multifrequency bioelectrical impedance analysis. We evaluated the collected data statistically and graphically in Microsoft Office Excel 2010 (Los Angeles, CA, USA). Statistical analyses were performed using the program STATISTICA Cz version 10. The diagnosis of obesity among participants according to anthropometric measures and indices showed considerable differences. We found that obesity was diagnosed according to waist circumference in 31% of participants. According to BMI 20.3% of subjects were overweight and 5.1% obese. With increasing BMI values, the values of WC, WHR and VFA also increased linearly. According to visceral fat area 11.4% of participants were in the risk obese group and by ABSI mortality risk there were 22% of subjects with high risk (4.8% and 28.3% for men and women, respectively) and 19.1% with very high risk (11.1% and 22% for men and women, respectively). VFA and BFP values increased with increasing risk of mortality, and in men also waist circumference values. When evaluating the ABSI in relation to BMI, the U-shaped curve was confirmed and in the case of WC the J-shaped curve. The FFM evaluation showed that the very low ABSI mortality risk group reached the highest values of this parameter and the lowest values showed the average mortality risk group, not only in the study group but also in male and female groups. Our findings suggest the relevance of ABSI to screen at-risk population.

Background: Anthropometric indices are used as predictors of cardiovascular disease (CVD). The most used indices are body mass index (BMI) and waist circumference (WC); however, there are limitations regarding their validity to address different body shapes, fat and lean mass distribution. A body shape index (ABSI) has been proposed as an alternative parameter to reflect differences in body shape and potentially be more useful for predicting CVD. ABSI is calculated by ABSI = WC / (BMI2/3 • Height1/2). The purpose of this cross-sectional study was to determine the utility of ABSI as a predictor or modifiable risk factor of CVD compared to other commonly used measures in clinical practice.Methods: The sample population was from the baseline interview and health examination included in the National Health and Nutrition Examination Survey (NHANES) 2013-2014. Patients (n=5,924, 52% female) were aged 18-80 years (47.4 ± 18.4 years) who completed a series of questionnaires on a spectrum of health-related risks. After the interview, health technicians performed a standardized examination of the participants to collect data on weight, height, BMI, WC, and sagittal abdominal diameter (SAD). Statistical analysis was done using R Studio, version 0.99.903 (RStudio, Inc. Boston, MA). Using logistic regression, the correlation between each predictor (ABSI, BMI, WC, SAD) as a continuous variable, and CVD outcomes was evaluated with two models: a univariable model and a multivariable model. In a secondary analysis, ABSI was reclassified into categorical values based on quartiles of the NHANES dataset. Logistic regressions were again run for overall CVD and all CVD sub-categories, followed by chi-square tests for significance. For comparison, BMI categories of normal, overweight, obese, and severely obese were tested with overall CVD and all CVD subcategories as outcome measures, followed by chi-square tests for significance.Results: Approximately 10% of the sample population had at least one prior manifestation of CVD, the most common being myocardial infarction (MI) (4.0%). ABSI showed little correlation with weight, BMI, WC, and SAD (r<0.3), while BMI had a strong correlation with weight, BMI, WC, and SAD (r ≈ 0.9). In univariable logistic regression, ABSI showed the most robust associations of all predictors with overall CVD and all CVD subcategories. ABSI demonstrated stronger correlations than BMI for all CVD outcomes (except CHF in the multivariable model). This study attempted to create classifications of ABSI and compare them to the normative classifications of BMI. In this categorical analysis, ABSI was also stronger than BMI in all logistic regression analyses for CVD outcomes, except for CHF in the multivariable model. Severe obesity (BMI ≥40 kg/m2) almost doubled the odds of having CVD, while being categorized in Q2, Q3, and Q4 for ABSI increased odds by double, triple, and eight-fold, respectively.Conclusion: An ABSI parameter in the upper three quartiles increases the risk of CVD manifestations more significantly than an elevated BMI per category of overweight, obese, and severely obese, respectively. Since the categories for ABSI were created based on quartiles of a large sample size reflecting the US population, this suggests that the increased risk from an elevated ABSI is more widespread than previously understood. Thus, ABSI should be monitored more closely and managed in preventative medical care than BMI alone.

ObjectiveTo compare the predictive performance of the percentage body fat (PBF), body mass index (BMI), waist circumference (WC), hip circumference (HC), waist–hip ratio (WHR), waist–height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), abdominal volume index (AVI), and conicity index (CI) for identifying hypertension.MethodsA cross-sectional study was conducted among 2,801 adults (1,499 men and 1,302 women) aged 18 to 81 in Ningbo, China. The receiver operator characteristic (ROC) analysis and multiple non-parametric Z tests were used to compare the areas under the curve (AUC). The maximum Youden's indices were used to determine the optimal cut-off points of 10 obesity-related indices (ORI) for hypertension risk.ResultsThe AUC of all the indices were statistically significant (P < 0.05). The AUC of all the indices in men and women were 0.67–0.73 and 0.72–0.79, respectively. Further non-parametric Z tests showed that WHR had the highest AUC values in both men [0.73 (95% CI: 0.70, 0.76)] and women (0.79 (95% CI: 0.75, 0.83)], and several central ORI (men: WHR, WC, BRI, AVI, and CI, 0.71–0.73; women: WC, WHR, and AVI, 0.77–0.79) were higher than general ORI (PBF and BMI, 0.68 in men; 0.72–0.75 in women), with adjusted P < 0.05. The optimal cut-off points for identifying hypertension in men and women were as follows: PBF (23.55%, 32.55%), BMI (25.72 kg/m2, 23.46 kg/m2), HC (97.59 cm, 94.82 cm), WC (90.26 cm, 82.78 cm), WHR (0.91, 0.88), WHtR (0.51, 0.55), ABSI (0.08 m7/6/kg2/3, 0.08 m7/6/kg2/3), BRI (4.05, 4.32), AVI (16.31 cm2, 13.83 cm2), and CI (1.23 m2/3/kg1/2, 1.27 m2/3/kg1/2). Multivariate logistic regression models showed that all indices were statistically significant (P < 0.05) with the adjusted ORs (per 1-SD increase) at 1.39–2.06 and ORs (over the optimal cut-off points) at 1.80–2.64.ConclusionsAll 10 ORI (PBF, BMI, HC, WC, WHR, WHtR, ABSI, BRI, AVI, and CI) can effectively predict hypertension, among which WHR should be recommended as the best predictor. Central ORI (WHR, WC, and AVI) had a better predictive performance than general ORIs (PBF and BMI) when predicting the risk of hypertension.