TY - JOUR
T1 - Evaluation of anthropometric indices and lipid parameters to predict metabolic syndrome among adults in Mexico
AU - Banik, Sudip Datta
AU - Pacheco-Pantoja, Elda
AU - Lugo, Roberto
AU - Gómez-De-regil, Lizzette
AU - Aké, Rodolfo Chim
AU - González, Rosa María Méndez
AU - Solis, Ana Ligia Gutiérrez
N1 - Publisher Copyright:
© 2021 Datta Banik et al.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - 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.
AB - 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.
KW - Blood pressure
KW - BMI
KW - Cardiometabolic index
KW - Castelli Risk Index
KW - Cut-off values
KW - Lipid accumulation product
KW - Lipid profile
KW - Waist circumference
UR - http://www.scopus.com/inward/record.url?scp=85101239621&partnerID=8YFLogxK
U2 - 10.2147/DMSO.S281894
DO - 10.2147/DMSO.S281894
M3 - Artículo
AN - SCOPUS:85101239621
SN - 1178-7007
VL - 14
SP - 691
EP - 701
JO - Diabetes, Metabolic Syndrome and Obesity
JF - Diabetes, Metabolic Syndrome and Obesity
ER -