Associations between body mass index, cardiorespiratory fitness, metabolic syndrome, and impaired fasting glucose in young, urban native american women. Academic Article uri icon

abstract

  • Background: To investigate the baseline associations between body composition, cardiorespiratory fitness, physical activity, family history of type 2 diabetes, metabolic syndrome and impaired fasting glucose (IFG) among 200 asymptomatic urban Native American women aged 18-40 years participating in a diabetes prevention intervention. Methods: Participants without diabetes who self-identified as Native American were recruited from the general urban community into a randomized controlled trial. Inclusion criteria included not being pregnant and willingness to stay in the urban area for 2 years. From June 2002 to June 2004, baseline measures were taken and included fasting serum glucose, insulin, and lipids, body mass index (BMI), waist circumference, percent body fat, submaximal predicted cardiorespiratory fitness, and self-reported leisure physical activity and family history of type 2 diabetes. Results: Most participants were overweight or obese (mean BMI = 29.4 +/- 6.3 kg/m(2); mean percent body fat = 41.2% +/- 6.2%). Fifty-five (27.5%) had metabolic syndrome and 42 (21%) had IFG. Stepwise logistic regression indicated that BMI (odd ratio [OR] = 1.24; p < 0.001) and a family history of type 2 diabetes (OR = 4.96; p = 0.008) were significantly associated with metabolic syndrome. BMI (OR = 1.13; p = 0.003) was strongly positively associated with IFG. After adjusting for BMI, age (OR = 1.08; p = 0.021) was positively, and high-density lipoprotein cholesterol (HDL-C; OR = 0.93; p = 0.008) and cardiorespiratory fitness (OR = 0.36; p = 0.046) were inversely significantly associated with IFG. Conclusions: BMI, cardiorespiratory fitness, and physical activity levels are important variables to modify when attempting to reduce the prevalence of metabolic syndrome and IFG among young, asymptomatic Native American women. This information can be used to design effective diabetes prevention interventions.

publication date

  • 2007