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Future body mass index modelling based on macronutrient profiles and physical activity

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 Fo...

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Autores principales: Cundiff, David K, Raghuvanshi, Nikunj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3551753/
https://www.ncbi.nlm.nih.gov/pubmed/23106911
http://dx.doi.org/10.1186/1742-4682-9-43
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author Cundiff, David K
Raghuvanshi, Nikunj
author_facet Cundiff, David K
Raghuvanshi, Nikunj
author_sort Cundiff, David K
collection PubMed
description 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.
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spelling pubmed-35517532013-01-24 Future body mass index modelling based on macronutrient profiles and physical activity Cundiff, David K Raghuvanshi, Nikunj Theor Biol Med Model Research 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. BioMed Central 2012-10-29 /pmc/articles/PMC3551753/ /pubmed/23106911 http://dx.doi.org/10.1186/1742-4682-9-43 Text en Copyright ©2012 Cundiff and Raghuvanshi.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Cundiff, David K
Raghuvanshi, Nikunj
Future body mass index modelling based on macronutrient profiles and physical activity
title Future body mass index modelling based on macronutrient profiles and physical activity
title_full Future body mass index modelling based on macronutrient profiles and physical activity
title_fullStr Future body mass index modelling based on macronutrient profiles and physical activity
title_full_unstemmed Future body mass index modelling based on macronutrient profiles and physical activity
title_short Future body mass index modelling based on macronutrient profiles and physical activity
title_sort future body mass index modelling based on macronutrient profiles and physical activity
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3551753/
https://www.ncbi.nlm.nih.gov/pubmed/23106911
http://dx.doi.org/10.1186/1742-4682-9-43
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