Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia

Abstract

Our study aimed to compare the ability of anthropometric obesity indices to predict MetS and to determine the sex-specific optimal cut-off values for MetS among Malaysian vegetarians. Body weight, height, waist circumference (WC), blood pressure (BP), fasting venous blood sample were collected from 273 vegetarians in Selangor and Kuala Lumpur, Malaysia. The abilities of body mass index (BMI), body fat percentage (BF%), waist to height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), a body shape index (ABSI), and body roundness index (BRI) to identify MetS were tested using receiver operating characteristic (ROC) curve analyses. MetS was defined according to the Joint Interim Statement 2009. The ROC curve analyses show that BMI, BF%, WHtR, LAP and VAI were able to discriminate MetS in both sexes. LAP was a better predictor to predict MetS, followed by WHtR for male and female vegetarians. The suggested WHtR’s optimal cut-offs and LAP’s optimal cut-offs for MetS for male and female vegetarians were 0.541, 0.532, 41.435 and 21.743, respectively. In conclusion, LAP was a better predictor to predict MetS than other anthropometric obesity indices. However, WHtR could be an alternative obesity index in large epidemiology survey due to its convenient and cost-effective characteristics.

Indirect Predictors of Visceral Adipose Tissue in Women with Polycystic Ovary Syndrome: A Comparison of Methods

“…LAP seems to be more accurate in VAT prediction than VAI both in the current study and recent observations [ 19 ]. LAP also seems to better predict MS than VAI [ 17 ].…”

“…WC/Height 0.5 (WHT.5R) has been proposed as an anthropometric index, considered as a good alternative to surrogate markers of visceral fat [ 16 ]. Recently used anthropometric and lipid-derived parameters, lipid accumulation product (LAP), and visceral adiposity index (VAI) are also affordable predictors of excess adiposity, insulin resistance (IR), and metabolic syndrome (MS) [ 17 ]. There is no general agreement on the most effective predictor of VO.…”

Sex Difference in the Associations among Obesity-Related Indices with Metabolic Syndrome in Patients with Type 2 Diabetes Mellitus

“…An increase in the prevalence of obesity has been reported in most Asian countries during the last two decades 29 . Several studies among different populations have shown that obesity-related indices can be used to predict MetS 11 , 13 , 14 , 30 . Xia et al demonstrated that LAP is a powerful marker of IR among people without diabetes 31 .…”

“…Anthropometric indices such as waist-to-height ratio (WHtR), waist-hip ratio (WHR), conicity index (CI), body mass index (BMI), body roundness index (BRI), body adiposity index (BAI), lipid accumulation product (LAP), abdominal volume index (ABSI), visceral adiposity index (VAI), abdominal volume index (AVI) and triglyceride-glucose index (TyG) can easily be calculated and quantified using factors such as triglycerides (TGs), body height (BH), hip circumference (HC), waist circumference (WC) and body weight (BW) [10]. These indices have been reported to be effective indicators of MetS in nonoverweight/obese adults, vegetarians and in Nigeria [11][12][13][14]. We recently identified associations between these obesity-related indices and nonalcoholic fatty liver disease and heavy metals [15,16].…”

Interaction Analysis of Lipid Accumulation Product and Family History of Diabetes on Impaired Fasting Glucose and Diabetes Risk in Population with Normotension in Eastern China: A Community-based Cross-sectional Survey

“…A research conducted in America showed that 33% of elderly adults at a normal weight de ned by BMI have pre-diabetes [14]. Schulze et al [15] reported that WC and WHtR instead of BMI considering their positive correlations with IFG and diabetes, however, WC and WHtR did not show the excess body fat in circulating blood [16]. Therefore, it is urgently to explore other valuable diabetes predicators to enhance screening accuracy.…”