Relationship between "a body shape index (ABSI)" and body composition in obese patients with type 2 diabetes

A Body Shape Index (ABSI) as a risk factor for all-cause mortality among US adults with type 2 diabetes: evidence from the NHANES 1999-2018

Background and objective

A Body Shape Index (ABSI) serves as a potential indicator of fat distribution, offering a more reliable association with all-cause mortality compared to overall adiposity. The present cohort study aims to explore the relationship between ABSI and all-cause mortality in US adults with Type 2 Diabetes (T2D).

Methods

For this cohort study, we extracted information on 5,461 US adults with T2D from the National Health and Nutrition Examination Survey (NHANES) and the NHANES Linked Mortality File. Trends in ABSI from 1999 to 2018 were calculated and analyzed using partial Mann-Kendall tests. To assess the relationship between ABSI and all-cause mortality, as well as the robustness of the association results, we employed weighted restricted cubic splines (RCS), weighted Cox proportional hazards models, sensitivity analyses, and stratified analyses. Additionally, we conducted time-dependent receiver operating characteristic (ROC) curve analysis to evaluate ABSI's predictive capability for all-cause mortality over 3, 5, and 10 years.

Results

Among US adults with Type 2 Diabetes (T2D), the mean ABSI gradually increased from 0.08333 to 0.08444 between 1999 and 2018. Following a median follow-up period of 90 months, 1,355 deaths (24.8% of the participants) occurred due to all causes. A left J-shaped association was observed between ABSI and all-cause mortality, with a 39% increased risk among US adults with T2D who had an ABSI below 0.08105 after full adjustment.

Conclusion

Our research has demonstrated a significant association between an elevated ABSI and the risk of all-cause mortality among US adults with T2D. These findings support the potential use of ABSI as a noninvasive tool to estimate mortality risk among US adults with T2D.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-025-01570-3.

Association between a body shape index and low back pain: a cross-sectional study highlighting gender-specific differences in NHANES data

BACKGROUND

This study aimed to investigate the association between A Body Shape Index (ABSI) and low back pain, with a focus on gender and age differences, using cross-sectional data from the NHANES database.

METHODS

A total of 14,268 participants were included from four NHANES cycles (1999-2004 and 2009-2010). Low back pain was assessed based on self-reported pain over the past three months, and ABSI was calculated using waist circumference, height, and weight. Multivariate logistic regression models were used to evaluate the association between ABSI and low back pain, adjusting for potential confounders. Restricted cubic spline (RCS) analysis was conducted to assess non-linear relationships, and subgroup analyses were performed based on gender, age and BMI.

RESULTS

Higher ABSI was significantly associated with an increased risk of low back pain (OR for highest quartile = 1.27, 95% CI: 1.07-1.50, p = 0.008). RCS analysis indicated a linear relationship between ABSI and low back pain, with the risk significantly rising when ABSI exceeded 0.85. Subgroup analyses revealed that this association was more pronounced in males (OR = 25.89, 95% CI: 3.11-215.86, p = 0.004) and participants aged ≥ 60 years (OR = 11.11, 95% CI: 2.61-47.26, p = 0.002), while no significant association was observed in females.

CONCLUSIONS

The ABSI was associated with low back pain. This association was more prominent in males and older adults. Our findings suggest that ABSI may provide a more nuanced understanding of low back pain risk, particularly in populations with abdominal obesity. Further studies are needed to explore the underlying mechanisms and potential clinical applications of ABSI in low back pain risk assessment.

[Performance of the "a body shape index" as a discriminator of obesity and sarcopenic obesity - ELSA-Brasil]

The scope of this study was to determine the diagnostic performance of ABSI for obesity and sarcopenic obesity, compared to the results of bioimpedance analysis (BIA) and BMI, by sex and age group. It involved a cross-sectional study with 12,793 participants in the second round of ELSA-Brasil (Longitudinal Study of Adult Health in Brazil), which obtained measurements of body fat percentage using BIA and anthropometry, verifying the performance of the diagnostic tests in order to compare the indices. The results showed that for obesity in men in all three age groups, the sensitivity was below 49%. Specificity ranged from 73% to 93%, with a higher percentage in the 65 to 79 age group. The same pattern was found for women, with sensitivity lower than 42%, and specificity ranged from 85% to 92%, and was higher in older women. With respect to sarcopenic obesity, the sensitivity and specificity among men in the three age groups were 72% was 99%, respectively. Among women, sensitivity was around 95% and specificity around 70% in all age groups. ABSI, compared to BIA, showed a reduced ability to identify obesity. However, it proved to be a good marker of sarcopenic obesity.

Relationship Between A Body Shape Index and Self-Reported Stress Urinary Incontinence Among US Women: A Cross-Sectional Analysis

INTRODUCTION AND HYPOTHESIS

Stress urinary incontinence (SUI) is common among women, but its link with A Body Shape Index (ABSI) is not well understood. This study investigates the association between ABSI and SUI risk in women, exploring variations across different subgroups.

METHODS

Data from National Health and Nutrition Examination Survey (2001-2020) were analyzed. A weighted multivariable logistic regression was performed to examine the relationship between ABSI and SUI risk, calculating odds ratios and 95% confidence intervals. A restricted cubic spline (RCS) analysis was used to assess any nonlinear associations. Subgroup analyses and interaction tests were conducted to explore the influence of factors on the ABSI-SUI relationship. Sensitivity analyses were also performed to ensure the robustness of the findings.

RESULTS

The analysis, after adjusting for potential confounders, showed a significant association between ABSI and SUI risk (p < 0.001). The RCS analysis indicated a nonlinear relationship (p for nonlinear = 0.02) with a turning point at an ABSI of 0.081. Subgroup analyses revealed that the association between ABSI and SUI was stronger in women with lower BMI, non-Mexican ethnicity, and those without hypertension (p for interaction < 0.05). Sensitivity analyses confirmed the consistency of these findings, supporting their robustness.

CONCLUSION

Higher ABSI is associated with an increased risk of SUI in US women, particularly in specific subgroups. This suggests that ABSI could be a valuable measure for identifying women at higher risk of SUI.

Relationship between METS-IR and ABSI index and the prevalence of nocturia: a cross-sectional analysis from the 2005-2020 NHANES data

Nocturia, marked by frequent nighttime urination, significantly impacts quality of life. This study explores the association of METS-IR (Metabolic Score for Insulin Resistance) and ABSI (A Body Shape Index) with nocturia, using data from the National Health and Nutrition Examination Survey (NHANES). A cross-sectional analysis of NHANES data from 2005 to 2020 was performed. Multivariable logistic regression assessed the associations between METS-IR, ABSI, and nocturia, adjusting for demographic characteristics, chronic diseases, and lifestyle factors. Generalized additive models and smoothing splines were used to describe relationship dynamics. Among the 16,450 participants, both METS-IR (OR = 1.15, 95% CI: 1.11-1.20, p < 0.0001) and ABSI (OR = 1.14, 95% CI: 1.10-1.19, p < 0.0001) were significantly associated with nocturia based on z-scores. An incremental rise in the quartiles of METS-IR and ABSI was associated with a higher risk of nocturia. Specifically, compared to the lowest quartile (Q1), participants in the highest quartile (Q4) had an OR of 1.45 (95% CI: 1.30-1.61, p < 0.0001) for METS-IR and 1.38 (95% CI: 1.23-1.55, p < 0.0001) for ABSI. Subgroup analyses showed a stronger association between ABSI and nocturia among individuals living alone and those aged 20-38 years. Nonlinear modeling indicated a threshold effect for ABSI, with nocturia risk significantly increasing when ABSI exceeded 76.2. Higher METS-IR and ABSI indices are closely linked to a greater prevalence of nocturia, indicating that these indices can be valuable in clinical assessments for evaluating nocturia risk and supporting preventive strategies.

Clinical utility of novel anthropometric indices in identifying type 2 diabetes mellitus among South African adult females

AIM

To assess the clinical utility of novel anthropometric indices and other traditional anthropometric indices in identifying the risk of type 2 diabetes mellitus (T2D) among South African adult females.

METHODS

In the first South African National Health and Nutrition Examination Survey (SANHANES-1), traditional [body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)] and novel [a-body shape index (ABSI), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI), conicity index (CI), and Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE)] anthropometric indices were assessed. T2D was diagnosed using glycated haemoglobin (HbA1c) ≥ 6.5% among participants without known T2D. Basic statistics and multiple regression analyses were explored the association between anthropometric indices and newly diagnosed T2D. Receiver operating characteristic (ROC) curve analysis was used to measure the predictive ability of both traditional and novel indices.

RESULTS

Among 2 623 participants, 384 (14.6%) had newly diagnosed T2D. All anthropometric indices mean values were significantly higher among participants with T2D (most p < 0.001). Higher mean values increased T2D odds e.g., in the model adjusted for age, employment, residence, and population group, odds ratio (OR) and 95% confidence interval (CI) for T2D with some of anthropometric indices were: 1.86 (1.60-2.15) for WC, 1.84 (1.59-2.13) for WHtR, 1.73 (1.51-1.99) for AVI, 1.71 (1.49-1.96) for BRI and 1.86 (1.57-2.20) for CUN-BAE. The top quartile for all indices had the highest T2D odds (p < 0.05). These outcomes were the highest for WC, AVI, and CUN-BAE and remained so even after removing the confounding effects of age, employment, population group, and residence. Based on the ROC analysis, none of the anthropometrical indices performed excellently (i.e., had an area under the curve [AUC] > 0.80). The WC, WHtR, AVI, BRI, and CUN-BAE, however, performed acceptably (AUCs 0.70-0.79), while also exhibiting corresponding cutoff values of 86.65 cm, 0.57, 15.52, 3.83, and 38.35, respectively.

CONCLUSIONS

The data shows that traditional and novel anthropometric indices similarly identifying newly diagnosed T2D among adult South African females. We recommend the continuing the use of traditional indices, as they are affordable and easy to use in our setting.

Relationship between Body Adiposity Indices and Reversal of Metabolically Unhealthy Obesity 6 Months after Roux-en-Y Gastric Bypass

The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.

Association between a body shape index and female infertility: a cross-sectional study

BACKGROUND

The relationship between A Body Shape Index (ABSI) and female infertility is not well understood. ABSI, a novel anthropometric measure, is gaining recognition for its ability to more accurately capture visceral fat characteristics than traditional metrics like BMI. This study aims to explore the association between ABSI and female infertility, considering its potential applications in medical screening and risk assessment.

METHODS

This cross-sectional study analyzed data from the NHANES from 2013 to 2020. Female infertility was assessed through reproductive health questionnaires, and ABSI was calculated using waist circumference, BMI, and height. Weighted logistic regression models and trend tests were used to evaluate the association between ABSI and female infertility. Restricted cubic splines (RCS) were employed to explore potential nonlinear relationships. Subgroup analyses were conducted to examine the consistency of the association across various demographic and health-related factors. Sensitivity analyses were also performed, including the exclusion of participants with missing covariate data, the application of propensity score matching, and restricting the analysis to women aged 20-45 years.

RESULTS

The study included 3,718 participants, 433 of whom were diagnosed with infertility. Higher ABSI was associated with an increased risk of female infertility (OR = 1.56, 95% CI: 1.21-2.00, P = 0.001), as demonstrated by weighted logistic regression and trend tests. Women in the highest ABSI quartile had a significantly higher prevalence of infertility compared to those in the lowest quartile (OR = 1.73, 95% CI: 1.27-2.37, P = 0.001). RCS curves indicated a linear positive relationship between ABSI and infertility risk, with a critical value at 0.079. Subgroup and sensitivity analyses confirmed the stability of these findings.

CONCLUSION

This study demonstrates a positive linear relationship between ABSI and the risk of female infertility. The use of a simple, non-invasive ABSI measurement could facilitate the early identification of high-risk individuals in large-scale screenings, potentially helping to prevent or reduce the incidence of infertility.

The association between the dietary behavior, diet quality, and lifestyle scores with anthropometric indices and happiness levels among university students

BACKGROUND

Limited information exists linking food habits, diet quality, and lifestyle scores with anthropometric indices and happiness levels. Our aim was to examine the association between food habits, diet quality, and lifestyle scores with anthropometric indices and happiness levels in the Iranian population.

METHODS

This cross-sectional study included 200 students randomly selected from a university in Iran. Dietary intakes, physical activity (PA), and happiness levels of study participants were assessed using validated questionnaires. The anthropometric indices examined in this study included the body shape index (ABSI), body roundness index (BRI), and abdominal volume index (AVI). Multiple logistic regression models were used to examine the association between food habits, diet quality, and lifestyle scores with anthropometric indices and happiness levels.

RESULTS

The mean age and body mass index (BMI) of study participants were 23.5 years ± 4.52 and 23.8 kg/m2 ± 3.17, respectively. In the study population, no significant association was seen between ABSI, BRI, AVI and happiness with food habits, diet quality, and lifestyle scores respectively. After adjusting for potential confounders (age, energy intake, marital status, education, smoking, physical activity, gender, and BMI), the association remained not significant for ABSI and food habits, diet quality, and lifestyle scores respectively (OR: 0.56, 95% CI (0.25-1.34), P = 0.193; OR: 0.59, 95% CI (0.22-1.57), P = 0.413; OR:1.19, 95%CI (0.54-2.63), P = 0.652), BRI and food habits, diet quality, and lifestyle scores respectively (OR:1.98, 95% CI (0.41-9.49), P = 0.381; OR: 0.57, 95%CI (0.12-2.74), P = 0.512; OR: 1.19, 95% CI (0.3-4.71), P = 0.811), AVI and food habits, diet quality, and lifestyle scores (OR:1.15, 95% CI (0.53-2.48), P = 0.743, OR:1.01, 95% CI (0.47-2.18), P = 0.965; OR: 1.3, 95% CI (0.64-2.65), P = 0.465) and happiness and food habits, diet quality, and lifestyle scores respectively (OR:0.3, 95%CI (0.07-1.25), P = 0.972; OR: 0.77, 95%CI (0.18-3.19), P = 0.724, OR: 0.3, 95% CI (0.07-1.25), P = 0.083).

CONCLUSIONS

No significant association was detected between food habits, diet quality, and lifestyle scores with anthropometric indices and happiness levels. However, longitudinal studies are required to confirm these findings.

Dietary diversity and its association with changes in anthropometric indices of community-dwelling older adults in Tehran, Iran: a longitudinal study (2017-2021)

BACKGROUND

Dietary diversity refers to the consumption of a variety of foods or food groups over a given reference period, which is crucial for improving nutrition and overall health. This longitudinal study aimed to investigate the association between dietary diversity and anthropometric indices in community-dwelling older adults living in Tehran in 2017 and 2021.

METHODS

The current study was conducted on 368 older adults [204 (55.4%) women and 164 (44.6%) men] over 60 years of age living in Tehran, who were selected by a systematic cluster sampling method at two-time points, 2017 and 2021. Anthropometric measures (weight, height, hip circumference, and waist circumference) were assessed with standard methods. The participants' dietary intake was assessed by completing two non-consecutive 24-hour recalls, and dietary diversity score (DDS) was calculated based on Kant's method. Statistical analysis was performed using R software by the mixed effect model method.

RESULTS

The mean DDS of the participants in 2017 (5.07 ± 1.20) was higher than that in 2021 (4.94 ± 1.09) (p < 0.05). DDS and dairy diversity score decreased significantly over time. After adjusting for confounders, there was an inverse relationship between the DDS and Body Mass Index (BMI) (B = -0.22; SE = 0.09), but the interaction effect of year × DDS (B = 0.19; SE = 0.10) was not significant (p = 0.06). However, there was a positive relationship between the DDS and A Body Shape Index (ABSI) (B = 0.00; p = 0.022), after adjusting for confounders, this relationship was no longer significant. Additionally, the interaction effect of year and DDS on the ABSI was not significant.

CONCLUSION

The dietary intake and dietary diversity of older adult residents of Tehran declined dramatically with age, and a higher DDS was associated with improved anthropometric indices. DDS had an inverse relationship with general obesity in the studied participants, and the passage of time did not affect this relationship. The DDS can be used as a predictive index and is a powerful tool for investigating changes in nutritional status in longitudinal studies of old age. However, longer-duration studies are needed to obtain more conclusive results.

Exploring the diabesity characteristics and associated all-cause mortality at a population level: results from a small European island state

Aim

Diabesity, the co-occurrence of diabetes and obesity, presents a global health crisis. Understanding its prevalence, associated risk factors, and mortality outcomes is crucial for effective public health interventions. This study aims to investigate the prevalence of diabesity and diabetes, assess associated risk factors, and analyze mortality outcomes over a 7-year period in the diabetogenic country of Malta.

Subject and methods

A nationwide health examination survey (2014–16) was conducted involving 3947 adults aged 18–70 years. Sociodemographic data, anthropometric measurements, and blood samples were collected. Relationships between different adiposity indices were explored. Mortality data was obtained by cross-referencing with the national mortality register. Statistical analyses included chi-square tests, logistic regression, and Cox proportional hazard models.

Results

Prevalence of obesity was 34.08%, diabetes 10.31%, and diabesity 5.78%. Sociodemographic characteristics were similar across all three cohorts. Multivariable regression identified increasing age (OR 1.10 CI95% 1.07–1.12; p≤ 0.001), male gender (OR 0.53 CI95% 0.30–0.93; p = 0.03), and low educational level (OR 2.19 CI95% 1.39–3.45; p = 0.001) as significant predictors of diabesity. Only diabetes showed a significant increase in mortality risk (HR 3.15 CI95% 1.31–7.62; p = 0.02) after adjustment, with gender (HR 3.17 CI95% 1.20–8.37) and body adiposity index (HR 1.08 CI95% 1.01–1.16) also significant (p ≤ 0.05).

Conclusion

Diabesity represents a substantial public health challenge in Malta, with implications for mortality outcomes. Targeted interventions addressing sociodemographic disparities and promoting healthy lifestyles are essential to mitigate its impact. The findings underscore the need for comprehensive healthcare strategies and policy initiatives to combat diabesity and reduce associated mortality rates.

Diabetes Management Based on the Phenotype and Stage of the Disease: An Expert Proposal from the AGORA Diabetes Collaborative Group

Diabetes is a complex and rapidly growing disease with heterogeneous clinical presentations. Recent advances in molecular and genetic technologies have led to the identification of various subtypes of diabetes. These advancements offer the potential for a more precise, individualized approach to treatment, known as precision medicine. Recognizing high-risk phenotypes and intervening early and intensively is crucial. A staging system for type 1 diabetes has been proposed and accepted globally. In this article, we will explore the different methods for categorizing and classifying type 2 diabetes (T2D) based on clinical characteristics, progression patterns, risk of complications, and the use of molecular techniques for patient grouping. We, as a team of experts, will also present an easy-to-follow treatment plan and guidance for non-specialists, particularly primary care physicians, that integrates the classification and staging of diabetes. This will help ensure that the most suitable therapy is applied to the different types of T2D at each stage of the disease's progression.

Prediction the changes of anthropometric indices following a weight-loss diet in overweight and obese women by mathematical models

Estimating the change rates in body size following the weight loss programs is very important in the compliance of those programs. Although, there is enough evidence on the significant association of body weight change with the other anthropometric indices and/ or body composition, there is so limited studies that have depicted this relationship as mathematical formulas. Therefore, the present research designed to use a mathematical model to predict changes of anthropometric indices following a weight-loss diet in the overweight and obese women. In this longitudinal study, 212 overweight/obese women who received an individualized low-calorie diet (LCD) were selected and followed-up for five months. Anthropometric measurements such as weight, waist circumference (WC), hip circumference (HC), and body composition (lean mass and fat mass) were performed. Then, body mass index, waist to hip ratio (WHR), waist to height ratio (WHtR), a body shape index (ABSI), abdominal volume index (AVI), and body adiposity index (BAI) were calculated using the related formula. Following the LCD led to the substantial and consistent changes in various anthropometric indices over time. All of these anthropometric variations were significantly related with the percent change (PC) of body weight except than WHR. Moreover, according to the mathematical formulas, weight loss was closely related to the decrease of WC (PC-WC =  - 0.120 + 0.703 × PC-WT), HC (PC-HC =  - 0.350 + 0.510 × PC-WT), body fat percentage (PC-Body Fat =  - 0.019 + 0.915 × PC-WT), WHtR (PC-WHtR =  - 0.113 + 0.702 × PC-WT), and improvements in ABSI (PC-ABSI =  - 0.112 + 0.034 × PC-WT) and AVI (PC-AVI =  - 0.324 + 1.320 × PC-WT). The decreasing rates of WC, HC, body fat percentage, WHtR, ABSI, and AVI in relation to the weight loss were clinically and statistically significant. This means that a healthy weight lowering diet would be accompanied by decreasing the body fat, body size and also the risk of morbidities.

Association between a body shape index and cognitive impairment among us older adults from a cross-sectional survey of the NHANES 2011-2014

PURPOSE

This study aimed to assess the relationship between A Body Shape Index (ABSI) and cognitive impairment among older adults in the United States.

METHODS

This cross-sectional study analyzed cognitive function in 2,752 individuals aged 60 and older using data from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Cognitive assessments were conducted using the Immediate Recall Test (IRT), Delayed Recall Test (DRT), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST). A Body Shape Index (ABSI) was calculated from waist circumference (WC), weight, and height. The relationship between ABSI and cognitive outcomes was examined through multifactorial linear regression, smooth curve fitting, and subgroup and interaction analyses.

RESULTS

With complete data, 2752 persons 60 and older participated in the study. After adjusting for covariables, these results showed statistically significant negative relationships between ABSI, IRT, and DSST scores. The negative correlation between DSST and ABSI is more substantial in males than females. There is less of a negative link between ABSI, AFT, and DSST among drinkers who consume 12 or more drinks annually compared to those who consume less. Furthermore, compared to individuals without high blood pressure(HBP), those who suffered HBP showed a more significant negative connection between ABSI and AFT.

CONCLUSION

Lower cognitive function was linked to higher ABSI.

Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese

To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut‑off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle‑aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis

BACKGROUND

Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP.

METHOD

The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test.

RESULTS

Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784.

CONCLUSIONS

This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

Does excess body weight accelerate immune aging?

BACKGROUND

Overweight and obesity in older adults increase the risk of a range of comorbidities by sustaining chronic inflammation and thus enhancing immunosenescence. This study aimed to assess whether excess body mass affected disproportion in T lymphocytes. Therefore, the study was designed to explain whether excess body mass in older individuals affected the disproportion in numbers of T lymphocytes and whether anthropometric indices and immune risk profile expressed as CD4/CD8 ratio are diagnostically useful in the analysis of immunosenescence.

MATERIALS & METHODS

One hundred three individuals aged 73.6 ± 3.1 years were allocated to the normal body mass (body mass index (BMI) 18.5-24.9 kg/m2,n = 39), the pre-obesity (BMI 25.0-29.9 kg/m2, n = 44) or the obesity (BMI ≥30.0 kg/m2, n = 20) group, based on WHO recommendations. Details on the subjects' medical history and lifestyle were obtained by health questionnaire. Anthropometric analysis was performed by bioelectrical impedance method, biochemical analysis was made by the automatic analyzer and ELISA immunoassays, and T and B lymphocyte counts were determined by eight-parameter flow cytometry. Additionally, visceral adiposity index, body adiposity index (BAI), and body shape index (ABSI) were evaluated based on body circumference, BMI and lipid-lipoprotein profile measurements.

RESULTS

The highest percentage of CD3+CD4+ T lymphocytes (59.4 ± 12.6 %) and the lowest CD3+CD8+ T lymphocytes (31.6 ± 10.0 %) were noted in patients the obesity group. The highest cut-off value of 1.9 for CD4/CD8 ratio was recorded in the normal body mass vs pre-obesity model. CD4/CD8 ratio > 2.5 was recorded in >20 % of our pre-obesity and obesity groups while 64.5 % of the normal body mass group had CD4/CD8 ratio < 1. High diagnostic usefulness was demonstrated for both BAI and lipid accumulation product (LAP) (AUC values of ~0.800 and ~ 0.900 respectively) in three models: normal body mass vs pre-obesity, normal body mass vs obesity, and pre-obesity vs obesity.

CONCLUSION

The odds ratios (OR) for CD4/CD8 ratio in the normal body mass vs obesity model (OR = 16.1, 95%CI 3.8-93.6) indicated a potential diagnostic value of T lymphocytes for clinical prognosis of immune aging in relation to excess body weight in older adults. High values of AUC obtained for the following models: CD4/CD8 + BAI (AUC = 0.927), CD4/CD8 + LAP (AUC = 1.00), CD4/CD8 + ABSI (AUC = 0.865) proved to provide excellent discrimination between older adults with obesity and with normal body mass.

A body shape index is useful for BMI-independently identifying Japanese patients with obesity at high risk of cardiovascular disease

BACKGROUND AND AIM

Obesity with multiple metabolic syndrome (MetS) components and/or with skeletal muscle loss is at high risk of cardiovascular disease (CVD). This study aimed to clarify the utility of anthropometric indices for identifying patients with overweight/obese at high risk of CVD based on having multiple MetS components and skeletal muscle loss.

METHODS & RESULTS

This cross-sectional study included 188 overweight/obese (BMI ≥25 kg/m2, Japanese patients; 73 men and 115 women, mean age 55.7 years). First, we performed correlation analysis among seven anthropometric indices, body mass index (BMI), percentage body fat, waist circumference (WC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR), a body shape index (ABSI), and body roundness index (BRI). Unlike the others, only ABSI was not correlated with BMI. Then, we conducted receiver operating characteristic analysis to assess the predictive abilities of anthropometric indices for having multiple MetS components. WC, WHpR, WHtR, BRI, and ABSI had significant predictive abilities for having multiple MetS components. Furthermore, multiple regression analysis showed that only ABSI had significantly negative associations with all sarcopenia-evaluated indices (skeletal muscle mass index [SMI], handgrip strength [HGS], and muscle quality [MQ]), irrespective of sex and age. Finally, an analysis of covariance showed that the high ABSI group had significantly lower SMI and HGS than the low ABSI group, irrespective of sex and age.

CONCLUSION

ABSI was deemed useful for BMI-independently identifying Japanese patients with overweight/obese at high risk of CVD based on having multiple MetS components and skeletal muscle loss. Clinical trials (the unique trial number and the name of the registry) ID: UMIN000042726.

Prevalence of sarcopenic obesity in patients with diabetes and adverse outcomes: A systematic review and meta-analysis

BACKGROUND & AIMS

Sarcopenic obesity (SO), which refers to the coexistence of sarcopenia and obesity. The aim of this systematic review and meta-analysis was first to assess the prevalence of SO in patients with diabetes, and second, to evaluate possible adverse outcomes.

METHODS

This study was conducted in adherence to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines and the data were collated by means of meta-analysis and narrative synthesis. We comprehensively and systematically searched PubMed, Embase, Web of Science, CBM, CNKI, Wanfang Database from the establishment of the database to December 2022, and collected related studies on SO in patients with diabetes. Using Stata 16.0 software to pool the estimates for the prevalence of SO in patients with diabetes, and a descriptive systematic review of possible adverse outcomes was performed.

RESULTS

The prevalence of 20 included studies were pooled by a random-effects model, which showed that the prevalence of SO in patients with diabetes was 27%. Subgroup analyses showed that the prevalence of SO was higher among studies using BIA (24%) to assess muscle mass, and those focused on literature of moderate-quality (29%), being published from 2013 to 2016 (29%), female patients with diabetes (17%), North Americans (30%). SO in patients with diabetes can lead to adverse outcomes including decreased glomerular filtration rate, massive proteinuria, cognitive decline, and insulin resistance.

CONCLUSION

The systematic review and meta-analysis revealed a prevalence of 27% for SO in patients with diabetes, and it is associated with potential serious adverse outcomes. Therefore, we should attach importance to the screening of SO in patients with diabetes and early detection of susceptible groups, then selecting appropriate interventions to reduce the occurrence of it and various adverse outcomes in this demographic.

Sex Differences in the Association of Weight-Adjusted-Waist Index with Sarcopenic Obesity: A Cross-Sectional Study of Hemodialysis Patients

Objective: To explore the association between weight-adjusted-waist index (WWI) and sarcopenic obesity (SO) in patients with maintenance hemodialysis (MHD). Methods: A multicenter, cross-sectional study that included 3311 adult MHD patients was conducted in 20 hemodialysis (HD) centers from June 1, 2021, to August 30, 2021. Body composition was evaluated by body composition monitor based on bioimpedance spectroscopy. Hand grip strength was measured by CAMRY® dynamometer. WWI was calculated as waist circumference (cm) divided by the square root of body weight (kg). Multiple logistic regression models, spearman correlation analysis, and receiver-operating characteristic (ROC) analyses were conducted. Results: The median age of the study was 55 years, and 39.4% of patients were female. The prevalence of SO was 22.7% in the total population, and patients with SO had higher WWI. Higher WWI quartiles were independently associated with a higher risk of SO in men after adjusting for potential confounders, including age, dialysis vintage, body mass index, biochemical indicators, and various medical histories; the odds ratio (OR) of SO was highest in the fourth quartile of the WWI (OR: 4.08, 95% confidence interval: 2.65-6.27, P for trend <0.001). Age-adjusted WWI provided a better diagnostic power than WWI only for SO in men (area under the ROC curve: 0.72 vs. 0.68, P < 0.001). WWI was not associated with SO in female HD patients. Conclusion: WWI is independently associated with SO in male but not female MHD patients. This anthropometric index is simple to calculate, making it applicable in clinical practice.

Differential Associations of 6 Adiposity Indices With Dementia in Older Adults: The MIND-China Study

OBJECTIVES

The cross-sectional association between late-life obesity and dementia is often explained by the obesity paradox. We assessed the potential differential associations of various adiposity indices with dementia and subtypes of dementia in rural Chinese older adults.

DESIGN

A population-based cross-sectional study.

SETTING AND PARTICIPANTS

A total of 5277 participants (age ≥60 years; 57.23% female) who were living in rural communities and were examined in March-September 2018 for MIND-China.

METHODS

We used weight, height, and waist circumference (WC) to calculate 6 adiposity indices: body mass index (BMI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI), A Body Shape Index (ABSI), body roundness index (BRI), and Conicity Index (ConI). Dementia, Alzheimer's disease (AD), and vascular dementia (VaD) were clinically diagnosed following the international criteria. Data were analyzed with logistic regression models.

RESULTS

Of the 5277 participants, 303 were diagnosed with dementia, including 193 with AD and 99 with VaD. The multivariable-adjusted odds ratio (95% CI) of dementia associated with the highest (vs lowest) quintile of adiposity index was 2.32 (1.40-3.85) for WWI, 1.56 (1.03-2.36) for ABSI, and 1.40 (0.92-2.11) for ConI. Similarly, higher levels of these 3 adiposity indices were significantly associated with an increased likelihood of AD, whereas a higher BMI was associated with a decreased likelihood of AD. None of the 6 examined adiposity indices was significantly associated with VaD when adjusting for multiple confounders.

CONCLUSIONS AND IMPLICATIONS

The adiposity index WWI is linearly associated with the likelihood of dementia and AD. An increased WWI may be a clinical marker for the dementia syndrome and Alzheimer's dementia.

Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning

Background

Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims to describe and compare the body composition profiles between metabolic healthy (MH) and metabolic unhealthy (MU) phenotype in normal and obesity population in China, and to explore the predictive ability of body composition indices to distinguish MU by generating machine learning algorithms.

Methods

A cross-sectional study was conducted and the subjects who came to the hospital to receive a health examination were enrolled. Body composition was assessed using bioelectrical impedance analyser. A model generator with a gradient-boosting tree algorithm (LightGBM) combined with the SHapley Additive exPlanations method was adapted to train and interpret the model. Receiver-operating characteristic curves were used to analyze the predictive value.

Results

We found the significant difference in body composition parameters between the metabolic healthy normal weight (MHNW), metabolic healthy obesity (MHO), metabolic unhealthy normal weight (MUNW) and metabolic unhealthy obesity (MUO) individuals, especially among the MHNW, MUNW and MUO phenotype. MHNW phenotype had significantly lower whole fat mass (FM), trunk FM and trunk free fat mass (FFM), and had significantly lower visceral fat areas compared to MUNW and MUO phenotype, respectively. The bioimpedance phase angle, waist-hip ratio (WHR) and free fat mass index (FFMI) were found to be remarkably lower in MHNW than in MUNW and MUO groups, and lower in MHO than in MUO group. For predictive analysis, the LightGBM-based model identified 32 status-predicting features for MUNW with MHNW group as the reference, MUO with MHO as the reference and MUO with MHNW as the reference, achieved high discriminative power, with area under the curve (AUC) values of 0.842 [0.658, 1.000] for MUNW vs. MHNW, 0.746 [0.599, 0.893] for MUO vs. MHO and 0.968 [0.968, 1.000] for MUO and MHNW, respectively. A 2-variable model was developed for more practical clinical applications. WHR > 0.92 and FFMI > 18.5 kg/m2 predict the increased risk of MU.

Conclusion

Body composition measurement and validation of this model could be a valuable approach for the early management and prevention of MU, whether in obese or normal population.

A mixed-methods study exploring women's perceptions and recommendations for a pregnancy app with monitoring tools

Digital health tools such as apps are being increasingly used by women to access pregnancy-related information. Conducted during the COVID-19 pandemic, this study investigated: (i) pregnant women's current usage of digital health tools to self-monitor and (ii) their interest in theoretical pregnancy app features (a direct patient-to-healthcare-professional communication tool and a body measurement tool). Using a mixed methods approach, 108 pregnant women were surveyed and 15 currently or recently pregnant women were interviewed online. We found that pregnant women used digital health tools to mainly access pregnancy related information and less so to self-monitor. Most participants were interested and enthusiastic about a patient-to-healthcare-professional communication tool. About half of the survey participants (49%) felt comfortable using a body measurement tool to monitor their body parts and 80% of interview participants were interested in using the body measurement to track leg/ankle swelling. Participants also shared additional pregnancy app features that they thought would be beneficial such as a "Digital Wallet" and a desire for a holistic pregnancy app that allowed for more continuous and personalised care. This study highlights the gaps and needs of pregnant women and should inform all stakeholders designing pregnancy digital healthcare. This study offers a unique insight into the needs of pregnant women during a very particular and unique period in human history.

Association of Body Shape Index with Cerebral Small Vessel Disease

INTRODUCTION

A body shape index (ABSI) is an anthropometric index designed to reflect the influence of visceral fat. ABSI has been previously associated with various atherosclerosis, metabolic diseases, and cardiovascular diseases; however, relatively few studies have been conducted on cerebrovascular disease. In this study, we evaluated the association between ABSI and cerebral small vessel disease (cSVD) in health check-up participants.

METHODS

We evaluated consecutive health check-up participants between January 2006 and December 2013. As subtypes of cSVD, we quantitatively measured the volume of white matter hyperintensity (WMH) and qualitatively measured the presence of silent brain infarct (SBI) and cerebral microbleed (CMB). ABSI was calculated according to the following formula: ABSI (m11/6/kg-2/3) = waist circumference (m)/(body mass index [kg/m2]2/3 × height [m]1/2).

RESULTS

A total of 3,219 health check-up participants were assessed (median age, 56 years; male sex, 54.0%). In the multivariable analysis, ABSI was significantly associated with WMH volume (β = 0.107, 95% confidence interval [CI] = 0.013-0.200), SBI (adjusted odds ratio [aOR] = 1.62, 95% CI = 1.14-2.31), and CMB (aOR = 1.64, 95% CI = 1.16-2.33) after adjusting for confounders (per 100 m11/6/kg-2/3). Furthermore, ABSI showed a dose-response relationship with the burden of each cSVD pathology.

CONCLUSIONS

High ABSI was associated with a higher burden of cSVD in health check-up participants. As ABSI showed close associations with all subtypes of cSVD, visceral fat may be a common risk factor penetrating cSVD pathologies.

The Use of Different Anthropometric Indices to Assess the Body Composition of Young Women in Relation to the Incidence of Obesity, Sarcopenia and the Premature Mortality Risk

The objective of the study was to evaluate the stratification of young women based on the assessment of body composition according to several currently recommended anthropometric indices and parameters, as well as the presence of obesity, sarcopenic obesity and the risk of premature death. Three hundred and three young Caucasian women aged 18-25 years were included in the cross-sectional observational study. For the purposes of the study, we used the bioelectrical impedance method and applied the obtained data to calculate indices defining obesity, sarcopenic obesity and premature mortality risk (ABSI z-score). We found significant differences between indicators of total and abdominal obesity when determining the rate of risk of premature death and diagnosis of obesity. Our results also suggest that FMI and FM/FFM indices correlate excellently with fat mass and visceral adipose tissue, better than BMI. Even in the case of abdominal obesity, FMI appears to correlate relatively strongly, more so than BMI. The results of the study support the opinion that in the assessment of body composition and health status, the presence of obesity (sarcopenic obesity) and the risk of premature death, anthropometric parameters and indices focusing not only on body weight (BMI, ABSI), but also on the proportionality and distribution of fat (WC, WHR, WHtR, VFA) and muscle tissue (FFMI, SMMI, FM/FFM ratio) should be used.

Changes in Novel Anthropometric Indices of Abdominal Obesity during Weight Loss with Selected Obesity-Associated Single-Nucleotide Polymorphisms: A Small One-Year Pilot Study

Whether BMI and the competing waist circumference (WC)-based anthropometric indices are associated with obesity-related single-nucleotide polymorphisms (SNPs) is as yet unknown. The current study aimed to evaluate the anthropometric indices (fat mass index, body shape index, visceral adiposity index, relative fat mass, body roundness index, and conicity index) during a weight loss intervention in 36 obese individuals. Blood biochemical parameters (total cholesterol, low-density lipoprotein, high-density lipoprotein, and triglycerides) and three SNPs (FTO rs9939609, TFAP2B rs987237, and PLIN1 rs894160) were assessed in 22 women and 14 men (35.58 ± 9.85 years, BMI 35.04 ± 3.80 kg/m2) who completed a 12-month balanced energy-restricted diet weight loss program. Body composition was assessed via bioelectrical impedance (SECA mBCA515). At the end of the weight loss intervention, all anthropometric indices were significantly reduced (p < 0.05). For the SNP FTO rs9939609, the higher risk allele (A) was characteristic of 88.9% of the study group, in which 10 participants (27.8%) were homozygous. We found a similar distribution of alleles in TFAP2B and PLIN1. Heterozygous genotypes in FTO rs9939609 and TFAP2B rs987237 were predisposed to significant reductions in WC-based novel anthropometric indices during weight loss. The influence of PLIN1 rs894160 polymorphisms on the changes in the analyzed indices during weight loss has not been documented in the present study.

Association between body shape index and risk of mortality in the United States

The body mass index (BMI) neither differentiates fat from lean mass nor does it consider adipose tissue distribution. In contrast, the recently introduced z-score of the log-transformed A Body Shape Index (LBSIZ) can be applied to measure obesity using waist circumference (WC), height, and weight. We aimed to investigate the association between LBSIZ and mortality. We used data from the National Health and Nutrition Examination Survey 1999–2014 and linked the primary dataset to death certificate data from the National Death Index with mortality follow-up through December 31, 2015. A multiple Cox regression analysis was performed to evaluate the hazard ratio (HR) of all-cause and cardiovascular disease (CVD) mortalities with adjustment for baseline characteristics. LBSIZ, WC, and BMI showed positive association with total fat percentage (P < 0.001); however, only WC and BMI were positively associated with appendicular skeletal mass index (ASMI) (P < 0.001). In the multiple Cox regression analysis, only LBSIZ showed a significant HR for all-cause and CVD mortalities. Under restricted cubic spline regression, mortality risk increased with LBSIZ. However, BMI and WC showed a U-shape association. In conclusion, LBSIZ is strongly associated with all-cause and CVD mortalities. Since LBSIZ is independent of BMI, LBSIZ complements BMI to identify high-risk groups for mortality even in individuals with low or normal BMI.

Identification of sarcopenic obesity in adults undergoing orthopaedic surgery: Relationship between “a body shape index” (ABSI) and fat-free mass. A cross -sectional study

Background

Sarcopenic obesity is a condition characterised by the coexistence of low muscle mass and function (sarcopenia) and excessive fat mass (obesity). The aim of this study was to determine the prevalence of this condition in patients undergoing orthopaedic surgery by gender and type of orthopaedic surgery. In addition, this study investigated the suitability of a waist circumference-based anthropometric measure, body shape index (ABSI), for predicting sarcopenic obesity and the predictive power of ABSI for fat-free mass index (FFMI), a surrogate marker of lean body mass.

Methods and findings

A cross-sectional study of overweight and obese orthopaedic patients undergoing knee or hip and spine surgery was conducted between October 2019 and March 2020 in Orthopaedic Hospital Valdoltra, Slovenia. General anthropometric parameters body mass index (BMI) and ABSI = (WC/(BMI^2/3x height^½) as well as body composition data (fat mass FM, fat-free mass FFM, FFMI, and the ratio FM/FFM as an index of sarcopenic obesity) were determined in 120 women (aged 66.5 ± 9.6 years) and 89 men (aged 65.5 ± 7.8 years) with overweight (25 kg/m² ≤ BMI < 30 kg/m²) and obesity (BMI ≥ 30 kg/m²) by bioelectrical impedance analysis (BIA). Sarcopenic obesity phenotypes based on FM/FFM ratio > 0.80 was present in 15.3% of patients, mainly in female patients undergoing knee surgery. ABSI was significantly associated with age in all women and obese men and with waist circumference (WC) in all patients. ABSI did not correlate with BMI in women and men; however, multiple linear regression analysis showed that BMI independently predicted FFMI (R = 0.83 and 0.70, respectively, p < 0.001) in women and men (β-coefficients: 0.801 and 0.686, respectively) and ABSI in women only (β-coefficient: -0.104). Women with a lower ABSI had a significantly higher FFMI than the group with a higher ABSI.

Conclusions

Sarcopenic obesity was most prevalent in obese women scheduled for knee surgery. In addition, ABSI, independently predicted FFMI in women and represents a significant predictor of sarcopenic obesity.

Anthropometric Indices as Predictive Screening Tools for Obesity in Adults; The Need to Define Sex-Specific Cut-Off Points for Anthropometric Indices

Due to the lack of full agreement as to the best indicators for obesity diagnosis and type, the aim of this study was to assess the comparative classification capabilities with the use of BIA results and selected anthropometric indices in individuals aged 20–60 years. This was a cross-sectional observational study among 368 Caucasian subjects aged 20–60 years. Body size and four skinfolds measurement were taken. To assess individual body composition, the bioelectrical impedance (BIA) method was applied. The results of fat mass (FM, kg) and fat-free mass (FFM, kg) were taken to calculate FM/FFM, fat mass index (FMI), and fat free mass index (FFMI). Receiver-operating characteristic (ROC) curve analysis was employed to compare the predictive power of different anthropometric indices in differentiating the classification of obesity in adults. The results of this study demonstrated and confirmed the need to change the approach to commonly used indicators such as BMI (body mass index) or WHtR (waist-to-height ratio), which should lead to the establishment of new criteria for the diagnosis of obesity that will also be sex-specific, in the adult population. The measurement of body fat content should become a generally accepted indicator for effective diagnosis, as well as for screening, of obesity.

The A Body Shape Index Might Be a Stronger Predictor of Chronic Kidney Disease Than BMI in a Senior Population

The A Body Shape Index (ABSI) was recently introduced to quantify abdominal adiposity relative to the body mass index (BMI) and height. This cross-sectional study was performed to explore whether the ABSI is linked to chronic kidney disease (CKD) in older adults and compare the predictive capacity of the ABSI versus BMI for CKD. In total, 7053 people aged ≥ 60 years were divided into normal, mild, and moderate-to-severe CKD groups based on their estimated glomerular filtration rate (eGFR). The correlation of the ABSI with the eGFR and the differences and trends in the ABSI and BMI among the groups were analyzed, and the cutoff points for moderate-to-severe CKD were calculated. The association between the ABSI and CKD was stronger than that between the BMI and CKD. The ABSI had a better capacity to discriminate the CKD stage than did the BMI. The capacity of the ABSI to predict moderate-to-severe CKD was higher than that of the BMI and was more substantial in women than men. The ABSI cutoff points for CKD were ≥0.0822 and 0.0795 in men and women, respectively. In conclusion, the ABSI serves as a better index than the BMI for screening and detecting high-risk individuals with CKD.

A body shape index could serve to identify individuals with metabolic syndrome and increased arterial stiffness in the middle-aged population

BACKGROUND

A body shape index (ABSI) is a novel anthropometric measure calculated using waist circumference (WC), body mass index (BMI), and body height. This study investigated the usefulness of ABSI to identify individuals with metabolic syndrome (MetS) and increased arterial stiffness in the middle-aged population.

METHODS

Middle-aged workers who underwent periodic health check-ups and who were without previous cardiovascular events were enrolled (n = 10,182). In addition to ABSI, visceral fat area (VFA) was evaluated using computed tomography. Obesity and MetS were diagnosed on the basis of WC, VFA, and ABSI. Arterial stiffness was examined by measuring the cardio-ankle vascular index (CAVI).

RESULTS

ABSI was significantly associated with CAVI in multivariable regression analysis. Logistic regression analysis revealed that ABSI was independently associated with the presence of MetS diagnosed on the basis of WC or VFA after adjustment for potential confounders, including BMI. Subjects with MetS diagnosed on the basis of each obesity index showed higher CAVI values than those without. Among subjects with MetS diagnosed on the basis of WC or VFA, those with MetS who met the definition of ABSI obesity showed significantly higher CAVI than those who did not. The other logistic regression analysis demonstrated that CAVI was independently associated with MetS defined on the basis of ABSI.

CONCLUSIONS

ABSI was significantly associated with CAVI and the presence of MetS in the middle-aged population and helped to discriminate individuals with MetS and increased CAVI. ABSI could serve to identify individuals with MetS and increased arterial stiffness.

Associations of A Body Shape Index (ABSI) with Cancer Incidence, All-Cause, and at 23 Sites-Findings from the UK Biobank Prospective Cohort Study

BACKGROUND

Few studies have explored the emerging adiposity marker A Body Shape Index (ABSI) with cancer risk. This study investigated the associations between ABSI and the incidence of cancer at 23 sites and all cancer combined.

METHODS

Data from 442,610 participants from the UK Biobank prospective study were included in this study. ABSI was used as the exposure. Incidence of cancer at 23 sites was the outcome. Cox proportional hazard models were performed to explore the association of ABSI, and combined ABSI and body mass index (BMI) with cancer risk, after adjusting for multiple testing.

RESULTS

36,961 individuals developed cancer during the 8.8 years median follow-up. In multivariable analyses, participants in the highest tertile of ABSI had higher risk of lung [HR, 1.58; 95% confidence interval (CI), 1.44-1.74], liver (HR, 1.45; 95% CI, 1.18-1.77), esophagus (HR, 1.32; 95% CI, 1.12-1.57), colorectal (HR, 1.19; 95% CI, 1.10-1.28), and breast (HR, 1.05; 95% CI, 1.04-1.17) cancers, and all cancers combined (HR, 1.11; 95% CI, 1.08-1.14) compared with the lowest tertile. These associations remained significant after adjustment for BMI. When ABSI was combined with BMI, participants in the highest ABSI who also had a BMI ≥ 25 kg/m² were at higher risk of uterus, esophagus, liver, stomach, colorectal, and breast cancers, as well as all cancers combined, compared with those in the lowest ABSI tertile with a normal BMI.

CONCLUSIONS

ABSI is associated with an increased risk of five cancers as well as all cancers combined, independently of BMI.

IMPACT

ABSI is a useful marker for adiposity. However, cancer risk prediction improves with the combination of BMI.

Evaluation of the Relationships between Simple Anthropometric Measures and Bioelectrical Impedance Assessment Variables with Multivariate Linear Regression Models to Estimate Body Composition and Fat Distribution in Adults: Preliminary Results

BACKGROUND

Overweight and obesity are conditions associated with sedentary lifestyle and accumulation of abdominal fat, determining increased mortality, favoring chronic diseases, and increasing cardiovascular risk. Although the evaluation of body composition and fat distribution are highly relevant, the high cost of the gold standard techniques limits their wide utilization. Therefore, the aim of this work was to explore the relationships between simple anthropometric measures and BIA variables using multivariate linear regression models to estimate body composition and fat distribution in adults.

METHODS

In this cross-sectional study, sixty-eight adult individuals (20 males and 48 females) were subjected to bioelectrical impedance analysis (BIA), anthropometric measurements (waist circumference (WC), neck circumference (NC), mid-arm circumference (MAC)), allowing the calculation of conicity index (C-index), fat mass/fat-free mass (FM/FFM) ratios, body mass index (BMI) and body shape index (ABSI). Statistical analyzes were performed with the R program. Nonparametric Statistical tests were applied to compare the characteristics of participants of the groups (normal weight, overweight and obese). For qualitative variables, the Fisher's exact test was applied, and for quantitative variables, the paired Wilcoxon signed-rank test. To evaluate the linear association between each pair of variables, the Pearson correlation coefficient was calculated, and Multivariate linear regression models were adjusted using the stepwise variable selection method, with Akaike Information Criterion (p ≤ 0.05).

RESULTS

BIA variables with the highest correlations with anthropometric measures were total body water (TBW), body fat percentage (BFP), FM, FFM and FM/FFM. The multiple linear regression analysis showed, in general, that the same variables can be estimated through simple anthropometric measures.

CONCLUSIONS

The assessment of fat distribution in the body is desirable for the diagnosis and definition of obesity severity. However, the high cost of the instruments (dual energy X-ray absorptiometry, hydrostatic weighing, air displacement plethysmography, computed tomography, magnetic resonance) to assess it, favors the use of BMI in the clinical practice. Nevertheless, BMI does not represent a real fat distribution and body fat percentage. This highlights the relevance of the findings of the current study, since simple anthropometric variables can be used to estimate important BIA variables that are related to fat distribution and body composition.

Performance of adiposity indicators in predicting metabolic syndrome in older adults

OBJECTIVE

To evaluate the association between some indicators of adiposity and markers of metabolic disorder, evaluate their performance in predicting metabolic syndrome (MetS), and identify their cutoff values among older adults, both in the overall sample and according to sex.

METHODS

Cross-sectional study in 159 older men and women. MetS was defined according to the harmonized criteria. The assessments included waist circumference (WC), waist-to-height ratio (WHtR), conicity index (C index), lipid accumulation product (LAP), visceral adiposity index (VAI), body mass index (BMI), A body shape index (ABSI), area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.

RESULTS

LAP and WHtR resulted in the largest AUC values (>0.80). In both sexes, the best indicators were LAP, WC, and WHtR. Both LAP and WHtR presented the highest Youden's index values in the overall sample, with cutoff values of approximately 46.9 (sensitivity 75.0%, specificity 76.7%) and 0.56 (sensitivity 79.3%, specificity 69.8%), respectively. When analyzed by sex, BMI, WC, WHtR, and LAP yielded the highest Youden's index values for the prediction of MetS in older women.

CONCLUSION

The indicators LAP, WC, and WHtR performed well in identifying the presence of MetS in older women and could be used to individually or collectively assess and monitor MetS.

Serum uric acid is associated with incident metabolic syndrome independent of body shape index and body roundness index in healthy individuals

BACKGROUND AND AIMS

Elevated serum uric acid (SUA) levels, body shape index (BSI) and body roundness index (BRI) were associated with incident metabolic syndrome (MetS). We aimed to investigate the relationship among the SUA level, BSI, and BRI on the incidence of MetS.

METHODS AND RESULTS

We retrospectively included 6221 healthy individuals from annual health exams at our hospital between 2016/1/1 and 2016/12/31. We defined hyperuricemia as SUA levels greater than 7 mg/dl in men and 6 mg/dl in women and MetS according to the contemporary definition. The study cohort included 6221 healthy individuals with an overall incidence rate of MetS of 9.8%. Compared with the normouricemic group, the hyperuricemic group had a greater incidence of MetS (17.2% vs. 9.6%, P < 0.001). After full adjustment for confounders, the SUA level was significantly associated with incident MetS in addition to body mass index (BMI) (adjusted OR [aOR]: 1.161, 95% CI: 1.071-1.259, P < 0.001), BRI (aOR: 1.196, 95% CI: 1.104-1.296, P < 0.001), and BSI (aOR: 1.297, 95% CI: 1.200-1.403, P < 0.001). Regarding the anthropometric indices, BMI and BRI were independent predictors of incident MetS, but the BSI lost its significant association in multivariate logistic regression analyses. In sensitivity analyses, various thresholds of elevated SUA levels remained associated with incident MetS.

CONCLUSION

We showed a dose-response effect of SUA on incident MetS independent of BMI, BRI and BSI in healthy individuals. Future studies can use SUA levels to stratify cardiometabolic risk in healthy individuals.

CLINICAL TRIALS

ClinicalTrials.gov with the identification number NCT03473951.

Changes in prevalence of cognitive impairment and associated risk factors 2000-2015 in São Paulo, Brazil

INTRODUCTION

Decreases in prevalence of cognitive impairment and dementia over the last two decades have been observed in different countries for cohorts entering older age. This study aimed to assess the cognitive impairment prevalence and explore associated factors among subjects aged >60 living in São Paulo, Brazil.

METHOD

Data came from a population-based Health, Welfare and Aging survey conducted in 2000, 2006, 2010, and 2015. Cognitive impairment was detected using the abbreviated Mini-Mental State Exam corrected by formal education years. In total, there were 5922 respondents in the statistical analyses.

RESULTS

Logistic regression models adjusted for age group, income, race, cardiovascular risk factors, and depression were used to estimate cognitive impairment prevalence. Between 2015 and 2000, respondents were more likely to report formal education, hypertension, diabetes, and overweight/obesity. Moreover, the weighted analyses showed that cognitive impairment prevalence was higher in 2015, even adjusting for sociodemographic and socioeconomic characteristics, cardiovascular risk factors, and depression.

CONCLUSION

In contrast to decreases in cognitive impairment prevalence in other countries and despite increases in educational years, our findings suggest no secular improvements in cognitive health for the 2015 wave of older adults residing in São Paulo.

Association of body-shape phenotypes with imaging measures of body composition in the UK Biobank cohort: relevance to colon cancer risk

Background

Body mass index (BMI), waist and hip circumference are strongly correlated and do not reflect body composition. A Body Shape Index (ABSI) and Hip Index (HI) define waist and hip size among individuals with the same weight and height and would thus reflect body density. We examined differences in body composition between body-shape phenotypes defined with ABSI and HI and used this information to propose explanations for associations between body-shape phenotypes and colon cancer risk.

Methods

We used data from the UK Biobank Resource for 15,520 men, 16,548 women with dual-emission X-ray absorptiometry (DXA) measurements; 3997 men, 4402 women with magnetic resonance imaging (MRI) measurements; 200,289 men, 230,326 women followed-up for colon cancer. We defined body-shape phenotypes as: large-ABSI-small-HI (“apple”), small-ABSI-large-HI (“pear”), small-ABSI-small-HI (“slim”), large-ABSI-large-HI (“wide”). We evaluated differences in body composition in linear models and associations with colon cancer risk in Cox proportional hazards models adjusted for confounders and explored heterogeneity by BMI.

Results

Among individuals with the same height and weight, visceral adipose tissue (VAT) was lowest for “pear” and highest for “apple”, while abdominal subcutaneous adipose tissue (ASAT) was lowest for “slim” and highest for “wide” phenotype. In the gynoid region, differences between “apple” and “pear” phenotypes were accounted for mainly by fat mass in women but by lean mass in men. In men, lean mass was inversely associated with waist size, while the pattern of gynoid fat resembled ASAT in women. Lean and fat mass were higher for higher BMI, but not hand grip strength. Compared to normal weight “pear”, the risk of colon cancer in men (1029 cases) was higher for “apple” phenotype for normal weight (hazard ratio HR = 1.77; 95% confidence interval: 1.16–2.69) and comparably for overweight and obese, higher for “wide” phenotype for overweight (HR = 1.60; 1.14–2.24) and comparably for obese, but higher for “slim” phenotype only for obese (HR = 1.98; 1.35–2.88). Associations with colon cancer risk in women (889 cases) were weaker.

Conclusions

ABSI-by-HI body-shape phenotypes provide information for body composition. Colon cancer risk in men appears related to ASAT quantity for “slim” and “wide” but to factors determining VAT accumulation for “apple” phenotype.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08820-6.

Anthropometric Indices and Age at Natural Menopause: A 15-Year Follow-up Population-Based Study

BACKGROUND

Following menopause, the risk of many diseases is increased, and this situation may be due to changes in anthropometric indices (AI), while the association between adiposity and age at natural menopause (ANM) is not clear yet.

OBJECTIVES

This longitudinal study was conducted to investigate the ability of AI in predicting ANM.

METHODS

For this purpose, a total of 3,876 women aged > 20 years old from participants of the Tehran lipid and glucose study (TLGS) met our eligibility criteria. The association between ANM and various AIs was assessed using the Accelerated Failure Time (AFT) model, and time ratio (TR) with 95% confidence intervals was reported in this longitudinal study.

RESULTS

The median [interquartile range (IQR) 25 - 75] of the survival time was 12.5 (7.9 - 15.8) years. At the end of the follow-up, 1,479 (38.2%) of the participants reached menopause. The median time to natural menopause was decreased by about 2% with one standard deviation (SD) increase of both a body shape index (ABSI) (time ratio (TR): 0.98, 95% CI: 0.97, 0.99) and lipid accumulation product (LAP) (TR: 0.98, 95% CI: 0.98, 0.99) z-scores; and this time was increased by about 1% (TR: 1.01, 95% CI: 1.00, 1.02) with one SD increase in body mass index (BMI) z-score.

CONCLUSIONS

The ABSI, LAP, and BMI were the most useful AIs for identification of the time to menopause onset, and ABSI and LAP were inversely associated with the ANM. Also, the BMI was directly associated with the ANM.

Associations between new and old anthropometric indices with type 2 diabetes mellitus and risk of metabolic complications: a cross-sectional analytical study

BACKGROUND

Obesity can increase the risk of diabetes mellitus and complications associated with it.

OBJECTIVES

The aim of this study was to estimate the associations between new and old anthropometric indices and the risk of type 2 diabetes mellitus (T2DM) and its metabolic complications.

METHODS

In this cross-sectional analytical study, 110 T2DM subjects and 110 healthy controls were selected by convenience sampling. Metabolic factors were evaluated including the atherogenic index of plasma (AIP), glycemic status, lipid profile, blood pressure, kidney indices, new anthropometric indices (abdominal volume index [AVI], body shape index [ABSI], lipid accumulation product [LAP], body adiposity index [BAI], and conicity index [CI]), and old anthropometric indices (weight, body mass index [BMI], and waist and hip circumference [WC and HC]).

RESULTS

Significant positive correlations were observed between AVI, LAP, and BAI and fasting blood glucose and HbA1c in the T2DM group (p < 0.001 for all associations). The odds ratio (OR) for T2DM elevated significantly with increasing BMI (OR: 1.30, 95% CI: 1.20-1.42), LAP (OR: 1.20, 95% CI: 1.13-1.27), and BAI (OR: 1.32, 95% CI: 1.21-1.43). The indices AVI (OR: 1.90, 95% CI: 1.57-2.29), LAP (OR: 1.19, 95% CI: 1.13-1.27), BAI (OR: 1.19, 95% CI: 1.12-1.26), WC (OR: 1.29, 95% CI: 1.18, 1.42), and HC (OR: 1.07, 95% CI: 1.01, 1.14) significantly increased the risk of metabolic syndrome (MetS).

CONCLUSIONS

Associations were identified between obesity indices and diabetes. These indices could be used in clinical practice for evaluation and control of T2DM.

Weight Loss After One Anastomosis Gastric Bypass-Mini Gastric Bypass (OAGB-MGB): Patient-Related Perioperative Predictive Factors

AIM

The aim of this study was to find independent perioperative factors predicting unsuccessful weight loss following one anastomosis gastric bypass-mini gastric bypass (OAGB-MGB), a recently developed technique of bariatric surgery.

METHODS

Using regression analysis, this prospective cohort study assessed the role of demographic and socioeconomic factors, clinical features, body composition, length of biliopancreatic limb (LBL), nutritional habits, comorbidities, and early post-operative weight reduction values, in predicting 1-year weight loss after OAGB-MGB. All patients at the center who underwent laparoscopic OAGB-MGB between October 2010 and May 2017 were included. The dependent variable was the percent of excess weight loss (%EWL) after 12-month follow-up. Weight loss outcome was defined as successful EWL (≥ 50%) or unsuccessful EWL (< 50%).

RESULTS

Follow-up data at 1 year was available for 1309 (77%) patients. Mean EWL and BMI reduction were 81.63% and 16.82 ± 4.37 kg/m² at 1 year. In addition, 48 (3.7%) patients had unsuccessful weight loss. Pre-operative higher BMI (OR, 1.34; p = 0.001), type 2 diabetes (OR, 4.26; p = 0.039), pre-surgery volume eating habit (OR, 0.12; p = 0.003), weight reduction value in the first month after surgery (OR, 0.80; p = 0.002), and length of biliopancreatic limb (LBL) (OR, 1.05; p = 0.017) were independently associated with unsuccessful weight loss at 1-year follow-up.

CONCLUSIONS

OAGB-MGB provides considerable weight loss for most patients. Initial lower BMI, absence of diabetes, being volume eater, and higher first month weight loss are independently associated with successful weight loss after 1 year.

Association of serum 25-hydroxy vitamin D with obesity-related indices in Chinese adults: A cross-sectional study

Obesity has been a well-known risk factor of low-level serum vitamin D. Compared with the traditional obesity-related indicator (body mass index, BMI), associations for two novel anthropometric indices, a body shape index (ABSI) and body roundness index (BRI) with vitamin D deficiency or insufficiency, still remain unclear. This study aimed to assess the associations of serum 25-hydroxy vitamin D (25(OH)D) status with these three obesity-related indices among Chinese adults. A total of 1666 individuals were included. Anthropometric measurements were performed to calculate the indices, and fasting blood was collected to determine serum 25(OH)D deficiency (<12 ng/ml) and insufficiency (12-20 ng/ml). Deficiency or insufficiency of 25(OH)D was found in 37.5% and 43.1% of the participants, respectively. After adjustment for potential confounders, a significantly increased prevalence of 25(OH)D deficiency was observed for higher ABSI (OR Q4 vs Q1 2.334, 95% CI 1.458-3.734; p trend = 0.002) and BRI (OR Q4 vs Q1 2. 215, 95%CI 1.365-3.594; p trend = 0.010), and for higher BMI in men. Regarding 25(OH)D insufficiency, a significant association was also found for ABSI (OR Q4 vs Q1 2.372, 95%CI 1.558-3.612; p trend = 0.001). The area under the ROC of ABSI (0.731, 95%CI 0.687-0.774) for predicting a low level of 25(OH)D was significantly larger than that of BMI (0.695, 95%CI 0.649-0.741) in men, but not in women. A positive association between obesity and lower 25(OH)D serum concentration was found among Chinese adults. Besides BMI, novel obesity-related indicator, ABSI and BRI were associated with lower serum 25(OH)D to some extent, and further studies are needed to clarify their potential to be used as screening tools in clinical practice.

Effect of Sarcopenia and Body Shape on Cardiovascular Disease According to Obesity Phenotypes

Background

This study aimed to assess the effects of sarcopenia and A Body Shape Index (ABSI) on cardiovascular disease (CVD) risk according to obesity phenotypes.

Methods

We used data from the National Health and Nutrition Examination Survey 1999 to 2012. A total of 25,270 adults were included and classified into the following groups: metabolically healthy normal weight (MHNW), metabolically healthy overweight/obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight/obese (MUO). Sarcopenia was defined as the appendicular skeletal mass index <7 kg/m2 in men and <5.5kg/m2 in women. A multivariate logistic regression analysis was performed to evaluate the odds ratio (OR) of sarcopenia and ABSI for CVD events according to the obesity phenotype.

Results

The MHNW participants with sarcopenia had higher risk for CVD than those without sarcopenia (OR, 2.69; 95% confidence interval [CI], 1.56 to 4.64). In the analysis with MHNW participants without sarcopenia as a reference, the participants with sarcopenia showed a higher OR for CVD than those without sarcopenia in both MHO (OR in participants without sarcopenia, 3.31; 95% CI, 1.94 to 5.64) (OR in participants with sarcopenia, 8.59; 95% CI, 2.63 to 28.04) and MUO participants (OR in participants without sarcopenia, 5.11; 95% CI, 3.21 to 8.15) (OR in participants with sarcopenia, 8.12; 95% CI, 4.04 to 16.32). Participants within the second and third tertiles of ABSI had higher ORs for CVDs than the counterpart of obesity phenotypes within the first tertile.

Conclusion

These results suggest that clinical approaches that consider muscle and body shape are required.

Association between "a body shape index" and mortality: Bambuí Cohort Study of Aging, Brazil

This article aims to evaluate the joint and separate association between abdominal and general adiposity indicators and mortality. Data was collected from 1,366 older adults in the Bambuí Cohort Study of Aging with complete information for all variables of interest. The outcome variable was all-cause time until death; exposure variables were a body shape index (ABSI), waist circumference (WC), waist-to-height ratio (WHtR) and body mass index (BMI), assessed at the beginning of the study, and at the 3rd, 5th and 11th year of follow-up. Association between the quartiles of anthropometric indicators and mortality was calculated using an extended Cox proportional hazards model and adjusted for socioeconomic and behavioral confounding factors. Older adults in the 4th ABSI quartile had a higher risk of mortality regardless of BMI (1.27; 95%CI: 1.01-1.58), but this association was not observed in sensitivity analyses. Older adults in the 2nd, 3rd and 4th BMI quartiles had a lower risk of mortality, even when adjusted for WC or ABSI. WC and WHtR showed no association consistent with all-cause mortality after adjustment for confounding factors. Considering the loss of significance in the sensitivity analyses, ABSI's predictive capacity for mortality is still weak. Thus, adopting ABSI in clinical practice or in epidemiological surveys, in conjunction or replacing BMI and WC, requires more in-depth studies.

Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults

Background

Metabolic syndrome (MetS) in non-overweight/obese people is insidiously associated with cardiovascular disease. Novel anthropometric indices can reflect central obesity better than the traditional anthropometric indices. Therefore, we hypothesize that these newly developed anthropometric indices can better identify MetS in non-overweight/obese people than conventional indices.

Methods

Cross-sectional data of sociodemographic, biochemical and anthropometric indices were collected from 2916 non-overweight/obese Chinese people. A body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI) and abdominal volume index (AVI) were calculated. Partial correlation analysis was used to clarify the correlation between anthropometric indices and MetS variables. Binary logistic regression analysis was applied to assess the association between anthropometric indices and MetS and its components. Receiver-operating characteristic curve was used to identify the diagnostic ability of anthropometric indices for MetS and its components. The area under curve (AUC) difference between WHtR and each new anthropometric index was compared in pairs.

Results

After adjusting for covariates, AVI had the optimal ability of identifying MetS (AUC: 0.743 for male, 0.819 for female) and the strongest correlation with high-density lipoprotein cholesterol (HDL-C) (coe: − 0.227 for male, − 0.207 for female) and the highest odds rations (OR) with low HDL-C group (male: OR = 1.37, female: OR = 1.55). The WHtR was comparable to BRI in assessing MetS (AUC: 0.739 for male, 0.817 for female). WHtR or BRI could also well identify hypertension (AUC: 0.602 for male, 0.688 for female) and dysglycemia (AUC: 0.669 for male, 0.713 for female) and female’s high triglyceride level (AUC 0.712). The recognition ability of the two was equivalent. The ability of ABSI and WWI to identify MetS was weak.

Conclusions

AVI is the optimal anthropometric indices to identify MetS in non-overweight/obese Chinese adults. BRI and WHtR can also be considered as discriminators, while ABSI and WWI are weak discriminators. WHtR is easy to measure. So, it is recommended as an early preliminary screening method for the MetS in non-overweight/obese people.

The Obesity Paradox in Lung Cancer: Associations With Body Size Versus Body Shape

Background

The association between obesity and lung cancer (LC) remains poorly understood. However, other indices of obesity on the basis of body shape instead of body size have not been examined yet. The aim of this study was to evaluate the association between different indices of body size and body shape and the risk of LC. In particular, this study examined the association between A Body Shape Index, a more precise indicator of abdominal fat than traditional anthropometric measures, and the risk of LC.

Methods

In the prospective cohort the Rotterdam Study, we analysed data of 9,689 participants. LC diagnoses were based on medical records and anthropometric measurements were assessed at baseline. Cox-regression analyses with corresponding Hazard Ratios were used to examine the association between the anthropometric measurements and the risk of LC with adjustment for potential confounders. Potential non-linear associations were explored with cubic splines using the Likelihood ratio (LR) test.

Results

During follow-up, 319 participants developed LC. Body mass Index (BMI) was inversely associated with the risk of lung cancer (HR 0.94, 95% CI: 0.91–0.97) and persisted after excluding lung cancer cases during the first 10 years of follow-up. There was evidence for a non-linear association between BMI and the risk of lung cancer (0,04, df = 1), which indicated that the inverse association between BMI and lung cancer was mainly present in non-obese participants. Waist circumference (WC) (HR 1.03 95% CI: 1.01–1.05), Waist-to-Hip Ratio (WHR) (HR 1.23 95% CI: 1.09–1.38) and ABSI (A Body Shape Index) (HR 1.17 95% CI: 1.05–1.30) were positively and linearly associated with the risk of lung cancer.

Conclusions

Body shape rather than body size may be an important risk indicator of LC. Future research should focus on the role of visceral fat and the risk of LC as well as the underlying mechanisms.

Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes

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.

A Body Shape Index (ABSI) achieves better mortality risk stratification than alternative indices of abdominal obesity: results from a large European cohort

Abdominal and general adiposity are independently associated with mortality, but there is no consensus on how best to assess abdominal adiposity. We compared the ability of alternative waist indices to complement body mass index (BMI) when assessing all-cause mortality. We used data from 352,985 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) and Cox proportional hazards models adjusted for other risk factors. During a mean follow-up of 16.1 years, 38,178 participants died. Combining in one model BMI and a strongly correlated waist index altered the association patterns with mortality, to a predominantly negative association for BMI and a stronger positive association for the waist index, while combining BMI with the uncorrelated A Body Shape Index (ABSI) preserved the association patterns. Sex-specific cohort-wide quartiles of waist indices correlated with BMI could not separate high-risk from low-risk individuals within underweight (BMI < 18.5 kg/m2) or obese (BMI ≥ 30 kg/m2) categories, while the highest quartile of ABSI separated 18-39% of the individuals within each BMI category, which had 22-55% higher risk of death. In conclusion, only a waist index independent of BMI by design, such as ABSI, complements BMI and enables efficient risk stratification, which could facilitate personalisation of screening, treatment and monitoring.

Anthropometric indices and cut-off points in the diagnosis of metabolic disorders

OBJECTIVE

Identifying metabolic disorders at the earliest phase of their development allows for an early intervention and the prevention of serious consequences of diseases. However, it is difficult to determine which of the anthropometric indices of obesity is the best tool for diagnosing metabolic disorders. The aims of this study were to evaluate the usefulness of selected anthropometric indices and to determine optimal cut-off points for the identification of single metabolic disorders that are components of metabolic syndrome (MetS).

DESIGN

Cross-sectional study.

PARTICIPANTS

We analyzed the data of 12,328 participants aged 55.7±5.4 years. All participants were of European descent.

PRIMARY OUTCOME MEASURE

Four MetS components were included: high glucose concentration, high blood triglyceride concentration, low high-density lipoprotein cholesterol concentration, and elevated blood pressure. The following obesity indices were considered: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), body fat percentage (%BF), Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE), body roundness index (BRI), and a body shape index (ABSI).

RESULTS

The following indices had the highest discriminatory power for the identification of at least one MetS component: CUN-BAE, BMI, and WC in men (AUC = 0.734, 0.728, and 0.728, respectively) and WHtR, CUN-BAE, and WC in women (AUC = 0.715, 0.714, and 0.712, respectively) (p<0.001 for all). The other indices were similarly useful, except for the ABSI.

CONCLUSIONS

For the BMI, the optimal cut-off point for the identification of metabolic abnormalities was 27.2 kg/m2 for both sexes. For the WC, the optimal cut-off point was of 94 cm for men and 87 cm for women. Prospective studies are needed to identify those indices in which changes in value predict the occurrence of metabolic disorders best.

Relationship Between Modified Body Adiposity Index and A Body Shape Index with Biochemical Parameters in Bariatric Surgery Candidates

BACKGROUND

Body mass index, an estimate of body fat percentage, has been previously shown to be associated with metabolic disorders. However, there is little data on the associations between a body shape index (ABSI) or modified body adiposity index (MBAI), which provide valuable definitions of body fat, with serum biochemical parameter levels. Therefore, this study was conducted to find either ABSI or MBAI associations with serum biochemical parameter levels in bariatric surgery candidates.

METHODS

This cross-sectional study was conducted on 776 bariatric surgery candidates (age range 18-69 years) between November 2010 and September 2017. Demographic data, anthropometric indices, biochemical parameters, and body composition analysis data were drawn from the National Obesity Surgery Database, Iran. ABSI and MBAI were calculated using related equations. A stepwise multivariate linear regression was used to evaluate whether ABSI or MBAI was associated with each serum biochemical parameter.

RESULTS

ABSI, age, and multivitamin/mineral supplementation (MVMS) were independently associated with serum vitamin D (β = 24.374, SE 10.756, P value 0.026; β = 0.022, SE 0.007, P value 0.002; β = 0.639, SE 0.235, P value 0.008). However, a negative association was observed between MBAI and vitamin D (β = - 0.037, SE 0.016, P value 0.025) in a model adjusted for age and MVMS. Additionally, MBAI and age showed a significant positive association with serum HDL-c (β = 0.185, SE 0.085, P value 0.028; β = 0.171, SE 0.033, P value < 0.001), although there was a negative association between male sex and HDL-c (β = - 4.004, SE 0.891, P value < 0.001).

CONCLUSION

ABSI and MBAI may be appropriate indices in predicting serum vitamin D and HDL-c levels.