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Comparison of anthropometric indices for predicting the risk of metabolic syndrome and its components in Chinese adults: a prospective, longitudinal study
OBJECTIVES: Our study aimed to distinguish the ability of anthropometric indices to assess the risk of metabolic syndrome (MetS). DESIGN: Prospective cohort study. SETTING: Shenyang, China. PARTICIPANTS: A total of 379 residents aged between 40 and 65 were enrolled. 253 of them were free of MetS and...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5623484/ https://www.ncbi.nlm.nih.gov/pubmed/28928179 http://dx.doi.org/10.1136/bmjopen-2017-016062 |
Sumario: | OBJECTIVES: Our study aimed to distinguish the ability of anthropometric indices to assess the risk of metabolic syndrome (MetS). DESIGN: Prospective cohort study. SETTING: Shenyang, China. PARTICIPANTS: A total of 379 residents aged between 40 and 65 were enrolled. 253 of them were free of MetS and had been followed up for 4.5 years. METHODS: At baseline, all the participants underwent a thorough medical examination. A variety of anthropometric parameters were measured and calculated, including waist circumference (WC), body mass index (BMI), a body shape index (ABSI), abdominal volume index (AVI), body adiposity index, body roundness index, conicity index, waist-to-hip ratio and visceral adiposity index (VAI). After 4.5 year follow-up, we re-examined whether participants were suffering from MetS. A receiver operating characteristic (ROC) curve was applied to examine the potential of the above indices to identify the status and risk of MetS. OUTCOMES: Occurrence of MetS. RESULTS: At baseline, 33.2% participants suffered from MetS. All of the anthropometric indices showed clinical significance, and VAI was superior to the other indices as it was found to have the largest area under the ROC curve. After a 4.5 year follow-up, 37.8% of men and 23.9% of women developed MetS. ROC curve analysis suggested that baseline BMI was the strongest predictor of MetS for men (0.77 (0.68–0.85)), and AVI was the strongest for women (0.72 (0.64–0.79)). However, no significant difference was observed between WC and both indices. In contrast, the baseline ABSI did not predict MetS in both genders. CONCLUSIONS: The present study indicated that these different indices derived from anthropometric parameters have different discriminatory abilities for MetS. Although WC did not have the largest area under the ROC curve for diagnosing and predicting MetS, it may remain a better index of MetS status and risk because of its simplicity and wide use. |
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