title: Future body mass index modelling based on macronutrient profiles and physical activity.
abstract: BACKGROUND
  An accurate system of determining the relationship of macronutrient profiles of foods and beverages to the long-term weight impacts of foods is necessary for evidence-based, unbiased front-of-the-package food labels.
  
  
  METHODS
  Data sets on diet, physical activity, and BMI came from the Food and Agriculture Organization (FAO), the World Health Organization (WHO), the Diabetes Control and Complications Trial (DCCT), and Epidemiology Diabetes Intervention and Complications (EDIC). To predict future BMI of individuals, multiple regression derived FAO/WHO and DCCT/EDIC formulas related macronutrient profiles and physical activity (independent variables) to BMI change/year (dependent variable). Similar formulas without physical activity related macronutrient profiles of individual foods and beverages to four-year weight impacts of those items and compared those forecasts to published food group profiling estimates from three large prospective studies by Harvard nutritional epidemiologists.
  
  
  RESULTS
  FAO/WHO food and beverage formula: four-year weight impact (pounds)=(0.07710 alcohol g+11.95 (381.7+carbohydrates g per serving)*4/(2,613+kilocalories per serving)-304.9 (30.38+dietary fiber g per serving)/(2,613+kilocalories per serving)+19.73 (84.44+total fat g)*9/(2,613+kilocalories per serving)-68.57 (20.45+PUFA g per serving)*9/(2,613+kilocalories per serving))*2.941-12.78 (n=334, R(2)=0.29, P < 0.0001). DCCT/EDIC formula for four-year weight impact (pounds)=(0.898 (102.2+protein g per serving)*4/(2,297+kilocalories per serving)+1.063 (264.2+carbohydrates g per serving)*4/(2,297+ kilocalories per serving)-13.19 (24.29+dietary fiber g per serving)/ (2,297+kilocalories per serving)+ 0.973 (74.59+(total fat g per serving-PUFA g per serving)*9/(2,297+kilocalories per serving))*85.82-68.11 (n=1,055, R(2)=0.03, P < 0.0001). (FAO/WHO+ DCCT/EDIC formula forecasts averaged correlated strongly with published food group profiling findings except for potatoes and dairy foods (n=12, r=0.85, P = 0.0004). Formula predictions did not correlate with food group profiling findings for potatoes and dairy products (n=10, r= -0.33 P=0.36). A formula based diet and exercise analysis tool is available to researchers and individuals: http://thehealtheconomy.com/healthTool/.
  
  
  CONCLUSIONS
  Two multiple regression derived formulas from dissimilar databases produced markedly similar estimates of future BMI for 1,055 individuals with type 1 diabetes and female and male cohorts from 167 countries. These formulas predicted the long-term weight impacts of foods and beverages, closely corresponding with most food group profiling estimates from three other databases. If discrepancies with potatoes and dairy products can be resolved, these formulas present a potential basis for a front-of-the-package weight impact rating system.
authors.affiliation: dkcundiff@thehealtheconomy.com
authors.forename: David K
authors.initials: DK
authors.lastname: Cundiff
authors.forename: Nikunj
authors.initials: N
authors.lastname: Raghuvanshi
mesh_terms: D000293:Adolescent; D000328:Adult; D015992:Body Mass Index; D015331:Cohort Studies; D004032:Diet / Q000592:standards* / Q000639:trends; D015444:Exercise; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009043:Motor Activity; D055815:Young Adult