Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components
Background and aims: Body adiposity index (BAI) and conicity index have been known as useful measures in predicting cardio-metabolic diseases. This study aimed to evaluate the predictive potential of BAI and conicity index for the risk of metabolic syndrome (MetS) in comparison with body mass index...
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Elsevier
2024-12-01
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| Series: | Human Nutrition & Metabolism |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666149724000525 |
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| author | Sorayya Kheirouri Mohammad Alizadeh |
| author_facet | Sorayya Kheirouri Mohammad Alizadeh |
| author_sort | Sorayya Kheirouri |
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| description | Background and aims: Body adiposity index (BAI) and conicity index have been known as useful measures in predicting cardio-metabolic diseases. This study aimed to evaluate the predictive potential of BAI and conicity index for the risk of metabolic syndrome (MetS) in comparison with body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR). Methods: In this cross-sectional study, 174 adults (87 with MetS and 87 healthy individuals) were recruited from a medical weight loss center. Anthropometric parameters, systolic and diastolic blood pressures (SDP and DBP), lipid profile, and fasting blood sugar (FBS) were measured. Results: All anthropometric parameters were significantly higher in subjects with MetS than in healthy subjects. Both in MetS and healthy subjects, females had significantly higher BAI and BMI than males. In the fully adjusted model, the odds of MetS increased for each unit increase in BAI by 27 % (p = 0.001), in BMI by 33 % (p = 0.001), in WC by 13 % (p < 0.001), and in HC by 9 % (p = 0.005). ROC curve analysis showed that all the anthropometric parameters displayed clinical importance in predicting MetS, but WHR had the largest area under the curve (AUC) in total, male, and female patients. In participants with MetS, the conicity index was negatively correlated with FBS; BAI was positively associated with HDL level. Conclusion: All studied anthropometric parameters had acceptable accuracy for predicting MetS. Traditional parameters, particularly the WHR, exhibited a higher predictive power concerning MetS. The results underscore the reliability of conventional anthropometric measures in clinical and epidemiological settings. |
| format | Article |
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| institution | OA Journals |
| issn | 2666-1497 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
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| series | Human Nutrition & Metabolism |
| spelling | doaj-art-abc0a66808694cedbc61dcad672af4412025-08-20T01:54:16ZengElsevierHuman Nutrition & Metabolism2666-14972024-12-013820029010.1016/j.hnm.2024.200290Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and componentsSorayya Kheirouri0Mohammad Alizadeh1Corresponding author. Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Attar Nishabouri St., Tabriz, 5166614711, POBOX: 14711, Iran.; Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, IranCorresponding author. Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Attar Nishabouri St., Tabriz, 5166614711, POBOX: 14711, Iran.; Faculty of Nutrition and Food Sciences, Tabriz University of Medical Sciences, Tabriz, IranBackground and aims: Body adiposity index (BAI) and conicity index have been known as useful measures in predicting cardio-metabolic diseases. This study aimed to evaluate the predictive potential of BAI and conicity index for the risk of metabolic syndrome (MetS) in comparison with body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR). Methods: In this cross-sectional study, 174 adults (87 with MetS and 87 healthy individuals) were recruited from a medical weight loss center. Anthropometric parameters, systolic and diastolic blood pressures (SDP and DBP), lipid profile, and fasting blood sugar (FBS) were measured. Results: All anthropometric parameters were significantly higher in subjects with MetS than in healthy subjects. Both in MetS and healthy subjects, females had significantly higher BAI and BMI than males. In the fully adjusted model, the odds of MetS increased for each unit increase in BAI by 27 % (p = 0.001), in BMI by 33 % (p = 0.001), in WC by 13 % (p < 0.001), and in HC by 9 % (p = 0.005). ROC curve analysis showed that all the anthropometric parameters displayed clinical importance in predicting MetS, but WHR had the largest area under the curve (AUC) in total, male, and female patients. In participants with MetS, the conicity index was negatively correlated with FBS; BAI was positively associated with HDL level. Conclusion: All studied anthropometric parameters had acceptable accuracy for predicting MetS. Traditional parameters, particularly the WHR, exhibited a higher predictive power concerning MetS. The results underscore the reliability of conventional anthropometric measures in clinical and epidemiological settings.http://www.sciencedirect.com/science/article/pii/S2666149724000525Metabolic syndromeBody adiposity indexConicity indexBody mass indexWaist circumferenceHip circumference |
| spellingShingle | Sorayya Kheirouri Mohammad Alizadeh Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components Human Nutrition & Metabolism Metabolic syndrome Body adiposity index Conicity index Body mass index Waist circumference Hip circumference |
| title | Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| title_full | Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| title_fullStr | Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| title_full_unstemmed | Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| title_short | Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| title_sort | contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components |
| topic | Metabolic syndrome Body adiposity index Conicity index Body mass index Waist circumference Hip circumference |
| url | http://www.sciencedirect.com/science/article/pii/S2666149724000525 |
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