BACKGROUND: Given that hypomagnesemia is related with hyperglycemia, hypertension, hypertriglyceridemia, and insulin resistance, the objective of this study was to determine whether serum magnesium levels are associated with the metabolically obese normal weight (MONW) and the metabolically healthy obese (MHO) phenotypes. METHODS: Population-based cross-sectional study that enrolled 427 subjects, men and non-pregnant women aged 20 to 65years, to participate in the study. Subjects were allocated into groups with and without obesity; among non-obese individuals, the subgroup of MONW subjects was compared with a control group of healthy normal-weight individuals. Among obese individuals, the subgroup of MHO subjects was compared with a control group of obese subjects who exhibited at least one metabolic abnormality. In the absence of obesity, the presence of fasting hyperglycemia, insulin resistance, hypertriglyceridemia, and/or hypertension defined the presence of MONW phenotype. In the absence of hypertension, insulin resistance and metabolic abnormalities of fasting glucose and triglycerides levels, the phenotypically obese subjects were defined as MHO individuals. RESULTS: The sex-adjusted prevalence of MONW and MHO phenotypes was 40.8% and 27.9%. The multivariate logistic regression model adjusted by family history of diabetes, age, body mass index, and waist-circumference, showed a positive association between hypomagnesemia and the MONW phenotype (OR 6.4; 95%CI 2.3-20.4) and negative relationship between serum magnesium and the MHO phenotype (OR 0.32; 95%CI 0.17-0.61). CONCLUSIONS: Our results show that hypomagnesemia is positively associated with the presence of MONW phenotype, and the normomagnesemia negatively with the MHO phenotype.
BACKGROUND: Given that hypomagnesemia is related with hyperglycemia, hypertension, hypertriglyceridemia, and insulin resistance, the objective of this study was to determine whether serum magnesium levels are associated with the metabolically obese normal weight (MONW) and the metabolically healthy obese (MHO) phenotypes. METHODS: Population-based cross-sectional study that enrolled 427 subjects, men and non-pregnant women aged 20 to 65years, to participate in the study. Subjects were allocated into groups with and without obesity; among non-obese individuals, the subgroup of MONW subjects was compared with a control group of healthy normal-weight individuals. Among obese individuals, the subgroup of MHO subjects was compared with a control group of obese subjects who exhibited at least one metabolic abnormality. In the absence of obesity, the presence of fasting hyperglycemia, insulin resistance, hypertriglyceridemia, and/or hypertension defined the presence of MONW phenotype. In the absence of hypertension, insulin resistance and metabolic abnormalities of fasting glucose and triglycerides levels, the phenotypically obese subjects were defined as MHO individuals. RESULTS: The sex-adjusted prevalence of MONW and MHO phenotypes was 40.8% and 27.9%. The multivariate logistic regression model adjusted by family history of diabetes, age, body mass index, and waist-circumference, showed a positive association between hypomagnesemia and the MONW phenotype (OR 6.4; 95%CI 2.3-20.4) and negative relationship between serum magnesium and the MHO phenotype (OR 0.32; 95%CI 0.17-0.61). CONCLUSIONS: Our results show that hypomagnesemia is positively associated with the presence of MONW phenotype, and the normomagnesemia negatively with the MHO phenotype.
Authors: Rebecca B Costello; Ronald J Elin; Andrea Rosanoff; Taylor C Wallace; Fernando Guerrero-Romero; Adela Hruby; Pamela L Lutsey; Forrest H Nielsen; Martha Rodriguez-Moran; Yiqing Song; Linda V Van Horn Journal: Adv Nutr Date: 2016-11-15 Impact factor: 8.701
Authors: Anatoly V Skalny; Jung-Su Chang; Igor P Bobrovnitsky; Philippe Yu Kopylov; Margarita G Skalnaya; Shih-Yi Huang; Monica Maria Bastos Paoliello; Ekaterina S Ivanova; Weu Wang; Alexey A Tinkov Journal: Biol Trace Elem Res Date: 2020-10-16 Impact factor: 3.738
Authors: Iwona Rotter; Danuta Kosik-Bogacka; Barbara Dołęgowska; Krzysztof Safranow; Anna Lubkowska; Maria Laszczyńska Journal: Int J Environ Res Public Health Date: 2015-04-10 Impact factor: 3.390
Authors: Alexey A Tinkov; Paweł Bogdański; Damian Skrypnik; Katarzyna Skrypnik; Anatoly V Skalny; Jan Aaseth; Margarita G Skalnaya; Joanna Suliburska Journal: Biomolecules Date: 2021-05-04