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The EAT-Lancet Commission’s Planetary Health Diet Compared With the Institute for Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis

Background This article aimed to compare the EAT-Lancet Commission’s “Planetary Health Diet” (PHD) with the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease Study 1990-2017 (GBD2017) dietary and other risk factor data. In the PHD/GBD comparison, we also intended to show th...

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Detalles Bibliográficos
Autores principales: Cundiff, David K, Wu, Chunyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325883/
https://www.ncbi.nlm.nih.gov/pubmed/37425503
http://dx.doi.org/10.7759/cureus.40061
Descripción
Sumario:Background This article aimed to compare the EAT-Lancet Commission’s “Planetary Health Diet” (PHD) with the Institute for Health Metrics and Evaluation (IHME) Global Burden of Disease Study 1990-2017 (GBD2017) dietary and other risk factor data. In the PHD/GBD comparison, we also intended to show the relevance of a new multiple regression analysis methodology with dietary and non-dietary risk factors (independent variables) for noncommunicable disease (NCD) deaths/100000/year in males and females 15-69 years old from 1990 to 2017 (NCDs, dependent variable). Methods We formatted worldwide GBD2017 dietary risk factors and NCD data on 1120 worldwide cohorts to obtain 7846 population-weighted cohorts. Each cohort represented about one million people, totaling about 7.8 billion people from 195 countries. With an empirically derived methodology, we compared the PHD animal- and plant-sourced food recommended ranges (kilocalories/day=KC/d) with optimal dietary ranges (KC/d) from GBD cohort data. Using GBD data subsets with low and high animal food consumption cohorts, our new GBD multiple regression formula derivation methodology equated risk factor formula coefficients to their population-attributable risk percents (PAR%s). Results We contrasted PHD recommendations for the available 14 dietary risk factors (KC/d means and ranges) with our GBD analysis methodology’s optimal ranges for each dietary variable (KC/d mean and range): PHD beef, lamb, and pork mean: 30 KC/d (range: 0-60 KC/d)/GBD processed meat: 8.86 (1.69-16.03)+GBD red meat: 44.52 (20.37-68.68), PHD fish: 40 (0-143)/GBD: 19.68 (3.45-35.90), PHD whole milk or equivalents: 153 (0-306)/GBD: 40.00 (18.89-61.11), PHD poultry: 62 (0-124)/GBD: 56.10 (24.13-88.07), PHD eggs: 19 (0-37)/GBD: 19.42 (9.99-28.86), PHD: saturated oils 96 (0-96)/GBD added saturated fatty acids (SFA): 116.55 (104.04-129.07), PHD all added sugars: 120 (0-120)/GBD sugary beverages: 286.37 (256.99-315.76), PHD tubers or starchy vegetables: 39 (0-78)/GBD potatoes: 84.16 (75.75-92.58)+GBD sweet potatoes: 9.21 (4.05-14.37), PHD fruits: 126 (63-189)/GBD: 63.03 (21.61-113.71), PHD vegetables: 78.32 (9.48-196.14)/GBD: 85.05 (66.75-103.36), PHD nuts: 291 (0-437)/GBD nuts and seeds: 10.97 (5.95-15.98), PHD whole grains: 811 (811/811)/GBD: 56.14 (50.53-61.76), PHD legumes: 284 (0-379)/GBD: 59.93 (45.43-74.43), and total animal food PHD: (0/400)/GBD: 329.84 (212.49-447.19). Multiple regression low and high animal food subsets’ (animal foods mean=147.09 KC/d versus animal foods mean=482.00 KC/d) formulas each with 28 dietary and non-dietary risk factors (independent variables) accounted for 52.53% and 28.83% of their respective total formula PAR%s with NCDs (dependent variable). Conclusions GBD data modeling supported many but not all the PHD dietary recommendations. GBD data suggested that the amount of consumption of animal foods was the dominant determinate of NCDs of countries globally. Adding to the univariate associations, multiple regression risk factor formulas with risk factor coefficients equated to their PAR%s further elucidated dietary influences on NCDs. This paper and the soon-to-be-released IHME GBD2021 (1990-2021) data should help inform the EAT-Lancet 2.0 Commission’s work.