title: Cross-sectional association of dietary patterns with insulin-resistant phenotypes among adults without diabetes in the Framingham Offspring Study.
abstract: Cluster analysis is a valuable tool for exploring the health consequences of consuming different dietary patterns. We used this approach to examine the cross-sectional relationship between dietary patterns and insulin-resistant phenotypes, including waist circumference, BMI, fasting insulin, 2 h post-challenge insulin, insulin sensitivity index (ISI0,120), HDL-cholesterol, TAG and blood pressure, using data from the fifth examination cycle of the Framingham Offspring Study. Among 2875 participants without diabetes, we identified four dietary patterns based on the predominant sources of energy: 'Fruits, Reduced Fat Dairy and Whole Grains', 'Refined Grains and Sweets', 'Beer' and 'Soda'. After adjusting for multiple comparisons and potential confounders, compared with the 'Fruits, Reduced Fat Dairy and Whole Grains' pattern, the 'Refined Grains and Sweets' pattern had significantly higher mean waist circumference (92.4 v. 90.5 cm; P = 0.008) and BMI (27.3 v. 26.6 kg/m2; P = 0.02); the 'Soda' pattern had significantly higher mean fasting insulin concentration (31.3 v. 28.0 microU/ml; P < or = 0.001); the 'Beer' pattern had significantly higher mean HDL-cholesterol concentration (1.46 v. 1.31 mmol/l; P < 0.001). No associations were observed between dietary patterns and ISI0,120, TAG, and systolic or diastolic blood pressure. Our findings suggest that consumption of a diet rich in fruits, vegetables, whole grains and reduced-fat dairy protects against insulin-resistant phenotypes and displacing these healthy choices with refined grains, high-fat dairy, sweet baked foods, candy and sugar-sweetened soda may promote insulin-resistant phenotypes.
authors.affiliation: Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA.
authors.forename: Enju
authors.initials: E
authors.lastname: Liu
authors.forename: Nicola M
authors.initials: NM
authors.lastname: McKeown
authors.forename: P K
authors.initials: PK
authors.lastname: Newby
authors.forename: James B
authors.initials: JB
authors.lastname: Meigs
authors.forename: Ramachandran S
authors.initials: RS
authors.lastname: Vasan
authors.forename: Paula A
authors.initials: PA
authors.lastname: Quatromoni
authors.forename: Ralph B
authors.initials: RB
authors.lastname: D'Agostino
authors.forename: Paul F
authors.initials: PF
authors.lastname: Jacques
mesh_terms: D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D004032:Diet; D004041:Dietary Fats / Q000008:administration & dosage; D019422:Dietary Sucrose / Q000008:administration & dosage; D005260:Female; D005638:Fruit; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D008297:Male; D008460:Meat; D008875:Middle Aged; D009765:Obesity / Q000097:blood; D012737:Sex Factors; D014280:Triglycerides / Q000097:blood; D014675:Vegetables
chemical_list: D008076:Cholesterol, HDL; D004041:Dietary Fats; D019422:Dietary Sucrose; D007328:Insulin; D014280:Triglycerides