CONTEXT: 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. DESIGN: Cross-sectional, observation study. SETTING: University of Alabama at Birmingham (UAB), EatRight Weight Management Program. PATIENTS: Study subjects (n = 74) were former participants of UAB's EatRight Weight Management Program who completed the program at least 1 year ago. MAIN OUTCOME MEASURES: 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.
CONTEXT: 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. DESIGN: Cross-sectional, observation study. SETTING: University of Alabama at Birmingham (UAB), EatRight Weight Management Program. PATIENTS: Study subjects (n = 74) were former participants of UAB's EatRight Weight Management Program who completed the program at least 1 year ago. MAIN OUTCOME MEASURES: 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: Frederick F Samaha; Nayyar Iqbal; Prakash Seshadri; Kathryn L Chicano; Denise A Daily; Joyce McGrory; Terrence Williams; Monica Williams; Edward J Gracely; Linda Stern Journal: N Engl J Med Date: 2003-05-22 Impact factor: 91.245
Authors: Janet E Schebendach; Laurel E Mayer; Michael J Devlin; Evelyn Attia; Isobel R Contento; Randi L Wolf; B Timothy Walsh Journal: J Am Diet Assoc Date: 2011-05