ABSI (A Body Shape Index) and ARI (Anthropometric Risk Indicator) in Bariatric Surgery. First Application on a Bariatric Cohort and Possible Clinical Use

Association of body indices and risk of mortality in patients with type 2 diabetes

INTRODUCTION

A body shape index (ABSI) is independently associated with mortality in general population, but studies on the predictability of ABSI in the risk of mortality in patients with type 2 diabetes (T2D) are limited. We aimed to examine the independent and joint association of ABSI, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body roundness index (BRI) with mortality in patients with T2D.

RESEARCH DESIGN AND METHODS

The study included 11 872 patients (46.5% women) aged 30 years and older and who took part in diabetes care management program of a medical center in Taiwan. Body indices were evaluated by anthropometric measurements at baseline between 2001 and 2016, and their death status was followed up through 2021. Multivariate Cox regression models were used to assess the effect of body indices on mortality.

RESULTS

During a mean follow-up of 10.2 years, 560 cardiovascular disease (CVD) deaths and 3043 deaths were recorded. For ABSI, WC, WHR, WHtR and BRI, all-cause mortality rates were statistically significantly greater in Q4 versus Q2. For BMI and WHtR, all-cause mortality rates were also statistically significantly greater in Q1 versus Q2. The combination of BMI and ABSI exhibited a superiority in identifying risks of all-cause mortality and CVD mortality (HRs: 1.45 and 1.37, both p<0.01).

CONCLUSIONS

Combined use of ABSI and BMI can contribute to the significant explanation of the variation in death risk in comparison with the independent use of BMI or other indices.

Association of novel and conventional obesity indices with colorectal cancer risk in older Chinese: a 14-year follow-up of the Guangzhou Biobank Cohort Study

Background

Visceral adiposity index (VAI) and a body shape index (ABSI) were newly developed indices for visceral fat mass. Whether they are superior to conventional obesity indices in predicting colorectal cancer (CRC) remains unclear. We examined the associations of VAI and ABSI with CRC risk, and investigated their performance in discriminating CRC risk compared with conventional obesity indices in the Guangzhou Biobank Cohort Study.

Methods

A total of 28,359 participants aged 50 + years without cancer history at baseline (2003-8) were included. CRC were identified from the Guangzhou Cancer Registry. Cox proportional hazards regression was used to assess the association of obesity indices with the CRC risk. Discriminative abilities of obesity indices were assessed using Harrell’s C-statistic.

Results

During an average follow-up of 13.9 (standard deviation = 3.6) years, 630 incident CRC cases were recorded. After adjusting for potential confounders, the hazard ratio (95% confidence interval) of incident CRC for per standard deviation increment in VAI, ABSI, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) was 1.04 (0.96, 1.12), 1.13 (1.04, 1.22), 1.08 (1.00, 1.17), 1.15 (1.06, 1.24), 1.16 (1.08, 1.25)and 1.13 (1.04, 1.22), respectively. Similar results for colon cancer were found. However, the associations of obesity indices with risk of rectal cancer were non-significant. All obesity indices showed similar discriminative abilities (C-statistics from 0.640 to 0.645), with WHR showing the highest whilst VAI and BMI the lowest.

Conclusions

ABSI, but not VAI, was positively associated with a higher risk of CRC. However, ABSI was not superior to the conventional abdominal obesity indices in predicting CRC.

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.

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.

Can an Exercise-Based Educational and Motivational Intervention be Durably Effective in Changing Compliance to Physical Activity and Anthropometric Risk in People with Type 2 Diabetes? A Follow-Up Study

AIMS

A nine-month motivational exercise-based intervention was previously offered to subjects with type 2 diabetes (T2D). A year after the end of the intervention, compliance to physical activity (PA) and anthropometric indices of participants were analyzed to evaluate the durability of its effects.

METHODS

PA levels, expressed as total energy expenditure per week, were assessed with the International Physical Activity Questionnaire (IPAQ). Changes in Body Mass Index (BMI), A Body Shape Index (ABSI), Hip Index (HI) z-scores, the relative mortality risk related to each of these measures, and a combined Anthropometric Risk Index (ARI) were also evaluated.

RESULTS

Of a total of the 52 subjects examined (67.9% males, mean age 61.8 ± 6.0), 46 (88.4%) were still sufficiently active as defined by IPAQ thresholds at follow-up. PA levels, anthropometric indices and related risks improved at follow-up in respect to the baseline and to the end of the intervention, although only PA levels, BMI and related measures, and ARI risk changed significantly. Habitual PA increased significantly after the intervention (p < 0.01) and this increase correlated with changes in BMI z-scores (r = -0.29, p = 0.04). BMI risk was significantly lower (p < 0.01) in participants still active at follow-up.

CONCLUSIONS

This study testifies to the persistence of compliance to PA and health benefits of a combined exercise-based and motivational intervention in subjects with T2D.

Anthropometrics, Metabolic Syndrome, and Mortality Hazard

Independent indices (height, body mass index, a body shape index, and hip index) derived from basic anthropometrics have been found to be powerful predictors of mortality hazard, especially when the attributable risks are summed over these indices to give an anthropometric risk index (ARI). The metabolic syndrome (MS) is defined based on the co-occurrence of anthropometric, clinical, and laboratory criteria and is also widely employed for evaluating disease risk. Here, we investigate correlations between ARI and MS in a general population sample, the United States Third National Health and Nutrition Examination Survey. Baseline values of ARI and MS were also evaluated for their association with mortality over approximately 20 years of follow-up. ARI was found to be positively correlated with each component of MS, suggesting connections between the two entities as measures of cardiometabolic risk. ARI and MS were both significant predictors of mortality hazard. Although the association of ARI with mortality hazard was stronger than that of MS, a combined model with both ARI and MS score as predictors improved predictive ability over either construct in isolation. We conclude that the combination of anthropometrics and clinical and laboratory measurements holds the potential to increase the effectiveness of risk assessment compared to using either anthropometrics or the current components of MS alone.