Evaluation of Anthropometric Indices and Lipid Parameters to Predict Metabolic Syndrome Among Adults in Mexico
Received 15 September 2020
Accepted for publication 20 November 2020
Published 16 February 2021 Volume 2021:14 Pages 691—701
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Antonio Brunetti
Sudip Datta Banik,1 Elda Pacheco-Pantoja,2 Roberto Lugo,3 Lizzette Gómez-de-Regil,3 Rodolfo Chim Aké,3 Rosa María Méndez González,1 Ana Ligia Gutiérrez Solis3
1Center for Research and Advanced Studies (Cinvestav-IPN), Merida, Yucatan, Mexico; 2School of Medicine, Health Sciences Division, Universidad Anáhuac Mayab, Merida, Yucatan, Mexico; 3Regional High Speciality Hospital of the Yucatan Peninsula (HRAEPY), Merida, Yucatan, Mexico
Correspondence: Ana Ligia Gutiérrez Solis Email email@example.com
Background: Metabolic syndrome (MetS) is a cluster of conditions that increases the risk of cardiovascular disease (CVD) and is related to genetic background, dietary habits, and lifestyle. Anthropometric indices and lipid parameters have been shown to be simple and useful tools in clinical practice for predicting MetS. The aim of the present study was to evaluate the differential magnitudes of anthropometric characteristics (waist circumference and body mass index [BMI]) and lipid parameters, namely, lipid accumulation product (LAP), cardiometabolic index (CMI), and Castelli Risk Index (CRI-I), to estimate MetS, usingappropriate cut-off values, among adults from a public hospital in Yucatan, Mexico.
Methods: A cross-sectional study among 250 adults (77 men, 173 women) was carried out in the Regional High Speciality Hospital of the Yucatan Peninsula (HRAEPY) in Merida, Yucatan. MetS was diagnosed using standard criteria (central obesity, arterial hypertension, hyperglycemia, and dyslipidemia), and derived parameters (LAP, CMI, and CRI-I) were calculated. Binary logistic regression analysis-based receiver operating characteristics (ROC) curves were used to predict MetS.
Results: Of the 250 participants, 48% had MetS. High prevalences of overweight (35.2%) and obesity (48.8%) were found in the sample. The CMI and LAP were found to be the best parameters in the prediction of MetS in men and women. The optimal cut-off values of the parameters were higher in men and decreased with advancing age.
Conclusion: The CMI and LAP were shown to be the most effective indicators to diagnose MetS among adults from Yucatan, Mexico.
Keywords: BMI, waist circumference, blood pressure, lipid profile, lipid accumulation product, cardiometabolic index, Castelli Risk Index, cut-off values
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