Dietary fiber intake and metabolic syndrome in postmenopausal African American women with obesity.
Krista LeppingLucile L Adams-CampbellJennifer HicksMary MillsChiranjeev DashPublished in: PloS one (2022)
Fiber intake may be associated with lower risk of metabolic syndrome (MetS) but data from metabolically unhealthy African American women is sparse. We examined the association of dietary fiber intake and MetS among postmenopausal African American women with obesity. Baseline cross-sectional data from the Focused Intervention on Exercise to Reduce CancEr (FIERCE) trial of 213 women (mean age 58.3 years) were used. Dietary intake was assessed by Food Frequency Questionnaires (FFQs). Multivariate linear and logistic regressions were performed to estimate associations of MetS with fiber intake and adherence to dietary fiber intake guidelines, respectively. Mean daily fiber intake was (10.33 g/1000kcal) in women with impaired metabolic health. We observed an inverse association of total fiber intake with MetS. One unit increase in energy-adjusted fiber intake was associated with a 0.10 unit decrease in the MetS z-score (p = 0.02). Similar results were obtained for both soluble and insoluble fiber. In multivariate-adjusted analyses, participants not adherent to fiber intake recommendations were more likely to have MetS as compared to those reporting intakes in the recommended range (adjusted odds ratio 4.24, 95% CI: 1.75, 10.30). Of the MetS components, high fasting glucose and high triglycerides were all associated with lower intake of fiber. Study participants who consumed a higher amount of fiber had a better overall metabolic profile and were less likely to have MetS in our cross-sectional analysis of postmenopausal African American women with obesity and unhealthy metabolic profiles.
Keyphrases
- african american
- metabolic syndrome
- weight gain
- insulin resistance
- cross sectional
- type diabetes
- physical activity
- public health
- weight loss
- healthcare
- emergency department
- pregnant women
- cardiovascular disease
- squamous cell carcinoma
- polycystic ovary syndrome
- machine learning
- skeletal muscle
- electronic health record
- study protocol
- postmenopausal women
- phase ii
- papillary thyroid
- breast cancer risk
- young adults
- neural network
- adverse drug