OBJECTIVE: Metabolic syndrome (MetS) is strongly linked with cardiovascular disease and type-II diabetes, but there has been debate over which metabolic measures constitute MetS. Obese individuals with binge eating disorder (BED) are one of the high risk populations for developing MetS due to their excess weight and maladaptive eating patterns, yet, the clustering patterns of metabolic measures have not been examined in this patient group. METHODS: 347 adults (71.8% women) were recruited for treatment studies for obese individuals with BED. We used the VARCLUS procedure in the Statistical Analysis System (SAS) to investigate the clustering pattern of metabolic risk measures. RESULTS: The analysis yielded four factors: obesity (body-mass-index [BMI] and waist circumference), lipids (HDL and triglycerides), blood pressure (systolic and diastolic blood pressure), and glucose regulation (fasting serum glucose and Hb1Ac). The four factors accounted for 84% of the total variances, and variances explained by each factor were not substantially different. There was no inter-correlation between the four factors. Subgroup analyses by sex and by race (Caucasian vs. African American) yielded the same four-factor structure. CONCLUSION: The factor structure of MetS in obese individuals with BED is not different from those found in normative population studies. This factor structure may be applicable to the diverse population.
OBJECTIVE:Metabolic syndrome (MetS) is strongly linked with cardiovascular disease and type-II diabetes, but there has been debate over which metabolic measures constitute MetS. Obese individuals with binge eating disorder (BED) are one of the high risk populations for developing MetS due to their excess weight and maladaptive eating patterns, yet, the clustering patterns of metabolic measures have not been examined in this patient group. METHODS: 347 adults (71.8% women) were recruited for treatment studies for obese individuals with BED. We used the VARCLUS procedure in the Statistical Analysis System (SAS) to investigate the clustering pattern of metabolic risk measures. RESULTS: The analysis yielded four factors: obesity (body-mass-index [BMI] and waist circumference), lipids (HDL and triglycerides), blood pressure (systolic and diastolic blood pressure), and glucose regulation (fasting serum glucose and Hb1Ac). The four factors accounted for 84% of the total variances, and variances explained by each factor were not substantially different. There was no inter-correlation between the four factors. Subgroup analyses by sex and by race (Caucasian vs. African American) yielded the same four-factor structure. CONCLUSION: The factor structure of MetS in obese individuals with BED is not different from those found in normative population studies. This factor structure may be applicable to the diverse population.
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