Anthropometric parameter that best predict metabolic syndrome in South west Nigeria

Adejumo, Esther Ngozi; Adejumo, Olusola Adedeji; Azenabor, Alfred; Ekun, Ayodele Oloruntoba; Enitan, Seyi Samson; Adebola, Olayimika Kehinde; Ogundahunsi, Omobola A

doi:10.1016/j.dsx.2018.08.009

Cited by 34 publications

(39 citation statements)

References 39 publications

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“…However, BRI is limited in predicting percentage of fat mass in elite athletes when compared with other commonly and readily available field methods such as bio‐impedance analysis or skinfold prediction models 63 . Several recent studies have shown that BRI could be used as an adipose indicator for determining the presence of eccentric left ventricular hypertrophy, 64 hyperuricaemia, 41,65 arterial stiffness, 66–69 CVD, 70,71 diabetes, 41,72–75 dyslipidaemia, 41,76–78 hypertension 41,79,80 and MetS 41–55 …”

Section: Discussionmentioning

confidence: 99%

“…BRI is a predictor of body fat percentage and visceral adiposity tissue, and its values range from 1 to 16 35 . Although studies have compared the prediction of MetS by BRI with traditional and novel anthropometric indices, 41–55 there is currently no meta‐analysis indicating whether BRI is a better predictor of MetS than BMI, WC, WHR, WHtR, ABSI or BAI. Therefore, this meta‐analysis aims to investigate whether BRI is superior to BMI WC, WHR, WHtR, ABSI or BAI in predicting MetS.…”

Section: Introductionmentioning

confidence: 99%

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Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis

et al. 2020

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Body roundness index (BRI) is a new anthropometric index developed to predict both body fat and the percentage of visceral adipose tissue. Our aim was to investigate whether BRI is superior to traditional anthropometric indices in predicting metabolic syndrome (MetS). This systematic review and meta-analysis was conducted using Pubmed, Scopus and Web of Sciences databases. The estimated pooled areas under curve (AUCs) for BRI predicting MetS was higher than body mass index (BMI), waistto-hip ratio (WHR), body shape index (ABSI) and body adiposity index (BAI), similar to waist circumference (WC) and lower than waist-to-height ratio (WHtR). However, the difference between BRI and BMI, WC and WHtR predicting MetS was statistically non-significant. Similar results were found with the summary receiver operating characteristic curve (AUC-SROC). In addition, the non-Chinese population had pooled AUCs greater than the Chinese population for all indices. Pooled ORs showed that BRI is associated with an increased MetS risk. In conclusion, BRI had good discriminatory power for MetS in adults of both sexes from diverse populations (AUC > 0.7; AUC-SROC>0.7). However, WC and WHtR offer the best performance when screening for MetS, and non-significant differences were found with BRI. In contrast, BRI was superior to BMI, WHR, ABSI and BAI in predicting MetS. K E Y W O R D Santhropometric indices, body roundness index, metabolic syndrome, review

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis

et al. 2020

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“…The prevalence of MetS in Taiwan is approximately 16%, according to a nationwide cross-sectional population-based survey conducted in the early 2000s [16]. Several indices have been developed as surrogate markers of central obesity and insulin resistance and have been shown to be highly correlated with the diagnosis of MetS and the risk of further developing diabetes or atherosclerotic cardiovascular diseases [17][18][19]. The potential pathways of these central obesity-representing indices associated with MetS could be related to visceral fat, increasing production of nonesterified fatty acids (NEFAs), inflammatory cytokines, prothrombotic factors such as plasminogen activator inhibitor (PAI-1), and the activation of renin-angiotensin-aldosterone (RAAS) system, but decreasing production of an anti-inflammatory and antiatherogenic adipokine, adiponectin [20,21].…”

Section: Introductionmentioning

confidence: 99%

“…The potential pathways of these central obesity-representing indices associated with MetS could be related to visceral fat, increasing production of nonesterified fatty acids (NEFAs), inflammatory cytokines, prothrombotic factors such as plasminogen activator inhibitor (PAI-1), and the activation of renin-angiotensin-aldosterone (RAAS) system, but decreasing production of an anti-inflammatory and antiatherogenic adipokine, adiponectin [20,21]. These indices include lipid accumulation product (LAP), visceral adiposity index (VAI), and anthropometric indices, including body roundness index (BRI), conicity index (CI), body adiposity index (BAI), and abdominal volume index (AVI), all of which can easily be calculated and quantified using factors such as waist circumference, hip circumference, body mass index (BMI), body height (BH), body weight (BW), triglycerides (TGs), and high-density lipoprotein (HDL) cholesterol [17].…”

Section: Introductionmentioning

confidence: 99%

Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices

Wen

Wang

et al. 2020

Nutrients

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Previous studies have revealed associations between heavy metals and extensive health problems. However, the association between heavy metals and metabolic problems remains poorly defined. This study aims to investigate relationships between heavy metals and metabolic syndrome (MetS), lipid accumulation product (LAP), visceral adiposity index (VAI), and anthropometric indices, including body roundness index (BRI), conicity index (CI), body adiposity index (BAI), and abdominal volume index (AVI). We conducted a health survey of people living in southern Taiwan. Six heavy metals were measured: lead (Pb) in blood and nickel (Ni), chromium (Cr), manganese (Mn), arsenic (As), and copper (Cu) in urine. A total of 2444 participants (976 men and 1468 women) were enrolled. MetS was defined according to the Adult Treatment Panel III for Asians. Multivariable analysis showed that participants with high urine Ni (log per 1 μg/L; odds ratio (OR): 1.193; 95% confidence interval (CI): 1.019 to 1.397; p = 0.028) and high urine Cu (log per 1 μg/dL; OR: 3.317; 95% CI: 2.254 to 4.883; p < 0.001) concentrations were significantly associated with MetS. There was a significant trend of a stepwise increase in blood Pb and urine Ni, As, and Cu according to the number of MetS components (from 0 to 5, a linear p ≤ 0.002 for trend). For the determinants of indices, urine Cu was positively correlated with LAP, BRI, CI, and VAI; blood Pb was positively correlated with BRI, BAI, and AVI; urine Ni was positively correlated with LAP. High urine Cu and urine Ni levels were significantly associated with MetS, and there was a significant trend for stepwise increases in blood Pb and urine Ni, As, and Cu, accompanied by an increasing number of MetS components. Furthermore, several indices were positively correlated with urine Cu, urine Ni, and blood Pb.

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“…27 However, Adejumo et al used anthropometric indices including WT index to predict MetS and reported that WT index was not superior to WC alone. 28 Thus, by imitating the triglyceride glucose index (TyG) index, which is a continuous index indicating insulin resistance, 29,30 we developed another form of WT index consisting of TG levels and WC and was calculated as Ln [TG (mg/dl) WC (cm)/2], termed waist-triglyceride index (WTI), in order to investigate whether this form of the index could identify the presence of MetS better than its qualitative form or other indicators of MetS.…”

Section: Introductionmentioning

confidence: 99%

<p>Screening for Metabolic Syndrome Using an Integrated Continuous Index Consisting of Waist Circumference and Triglyceride: A Preliminary Cross-sectional Study</p>

Liu

Zhu

2020

DMSO

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Background: It has been suggested that hypertriglyceridemic waist (HW) phenotype is strongly associated with metabolic syndrome (MetS); however, there are very limited studies integrating triglyceride (TG) and waist circumference (WC) into a continuous variable to investigate the predictive power of this phenotype. Inspired from the triglyceride glucose index (TyG), we developed an integrated continuous index termed waist-triglyceride index (WTI) which was calculated as Ln [TG (mg/dl) WC (cm)/2]. Objective: We aimed to examine the potential of WTI in screening for MetS by comparing this quantitative index with the qualitative HW phenotype and other frequently used indices. Methods: A cross-sectional study was conducted in a total of 3460 non-diabetic adults who participated in an annual health checkup. MetS was defined by the update National Cholesterol Education Program/Adult Treatment Panel ш criteria for Asian Americans. Receiving operating characteristic (ROC) curve and areas under the curve (AUC) were employed to evaluate the performance of the involved indices in screening for MetS. Statistical differences among the AUC values of the indices were compared. Results: In both genders, the AUC value of WTI, TyG or HW phenotype was markedly larger than that of each anthropometric index alone. In men, there were no statistical differences in the AUC values among WTI, TyG and HW phenotype, whereas in women, the AUC value of WTI was significantly larger than that of HW phenotype [difference between area (DBA): 0.042, 95% CI: 0.0224-0.0617, P < 0.0001] and was nominally and significantly smaller than that of TyG (DBA: 0.00646, 95% CI: 0.000903-0.012, P = 0.0227). Conclusion: Our results suggest that there are discriminatory performance between the WTI and HW phenotype in the detection of MetS in women rather than in men. Appropriate markers for screening MetS in population study should be considered according to the genders.

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Anthropometric parameter that best predict metabolic syndrome in South west Nigeria

Cited by 34 publications

References 39 publications

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis

Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis

Associations of Heavy Metals with Metabolic Syndrome and Anthropometric Indices

<p>Screening for Metabolic Syndrome Using an Integrated Continuous Index Consisting of Waist Circumference and Triglyceride: A Preliminary Cross-sectional Study</p>

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