title: Diet variety based on macronutrient intake and its relationship with body mass index.
abstract: BACKGROUND
  Increased dietary variety has been associated with increased body weight; however, diet variety is not measured using a standardized methodology.
  
  
  OBJECTIVE
  We developed a new dietary variety score (DVS) based on food macronutrient content, and determined the relationship between DVS and measures of adiposity.
  
  
  METHODS
  Cross-sectional, observation study.
  
  
  METHODS
  University of Alabama at Birmingham (UAB), EatRight Weight Management Program.
  
  
  METHODS
  Study subjects (n = 74) were former participants of UAB's EatRight Weight Management Program who completed the program at least 1 year ago.
  
  
  METHODS
  Unique items from 4-day food records were converted to macronutrient categories using the diabetic exchange. Foods were categorized as a source of carbohydrate if containing > or = 5 g carbohydrate and > or = 20 calories; fat if containing > or = 5 g fat; protein if containing > or = 7 g protein. Height and weight were measured; BMI (kg/m2) was calculated. Dual energy X-ray absorptiometry measured body fat. Generalized linear modeling in SAS (Ver.9) determined relationships between adiposity and DVS.
  
  
  RESULTS
  On average, participants weighed 92.7 -/+ 30.9 kg (BMI = 32.5 kg/m2). Men and women's body fat were 37.4 -/+ 6.4% and 47.3 -/+ 6.4%, respectively. Separate linear regression models containing terms for sex and DVS showed significant relationships between macronutrient DVS and BMI. In a multivariate model controlling for each of the macronutrient DVS, BMI was not related to fat DVS, but was found to be positively related to protein DVS (beta = 0.87, P = .04). Sex modified the relationship between carbohydrate DVS and BMI, with an inverse relationship between BMI and carbohydrate DVS among women, and a positive relationship among men. Percent body and trunk fat were not related to DVS for either gender.
  
  
  CONCLUSIONS
  The new DVS, based on macronutrient content of foods, had significant associations with BMI. These dietary variety scores may provide another way to evaluate the impact of consuming a variety of food types on energy intake and BMI.
authors.affiliation: School of Medicine, University of Alabama at Birmingham.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Lyles
authors.forename: Renee
authors.initials: R
authors.lastname: Desmond
authors.forename: Lori E
authors.initials: LE
authors.lastname: Faulk
authors.forename: Suzanne
authors.initials: S
authors.lastname: Henson
authors.forename: Kathy
authors.initials: K
authors.lastname: Hubbert
authors.forename: Douglas C
authors.initials: DC
authors.lastname: Heimburger
authors.forename: Jamy D
authors.initials: JD
authors.lastname: Ard
mesh_terms: D050154:Adiposity; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000886:Anthropometry; D015992:Body Mass Index; D003430:Cross-Sectional Studies; D004032:Diet; D004040:Dietary Carbohydrates / Q000008:administration & dosage; D004041:Dietary Fats / Q000008:administration & dosage; D004044:Dietary Proteins / Q000008:administration & dosage; D002149:Energy Intake; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009752:Nutritional Status
chemical_list: D004040:Dietary Carbohydrates; D004041:Dietary Fats; D004044:Dietary Proteins