The EAT-Lancet Commission’s Planetary Health Diet Compared with the IHME GBD Ecological Data Analysis: data, Excel files, and SAS codes

Description

An analysis database of Global Burden of Disease 2017 risk factor and health outcome data (GBD2017) originates from raw data files from the Institute of Health Metrics and Evaluation (IHME) affiliated with the University of Washington. We are volunteer collaborators with IHME and not employed by IHME or the University of Washington. The population weighted GBD2017 data are on male and female cohorts ages 15-69 years including noncommunicable diseases (NCDs), body mass index (BMI), cardiovascular disease (CVD), and other health outcomes and associated dietary, metabolic, and other risk factors. The purpose of creating this population-weighted, formatted database is to explore the univariate and multiple regression correlations of health outcomes with risk factors. Our research hypothesis is that we can successfully model NCDs, BMI, CVD, and other health outcomes with their attributable risks. These Global Burden of Disease data relate to the paper in Cureus: The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325883/ The data archive includes the following files: 1. Text file to import the GBD dataset setup into SAS (`GBD GLOBAL BURDEN OF DISEASE DATASET IMPORT & SETUP.txt`) 2. Step 1 formatting script for NCD, BMI, and CVD analyses (`NCD, BMI, and CVD step 1 formatting file.txt`) 3. Analysis text file and code for the Planetary Health Diet versus GBD comparisons (`PHD of EAT Lancet Commission versus GBD data.txt`) 4. Population-weighted analysis database (`wtedCVDRfsCov2017.xlsx`) containing over 40 health risk factors and NCD mortality rates for male and female cohorts ages 15-69 years across 195 countries (including primary outcome variables covering over 100 types of noncommunicable diseases). For questions, please email davidkcundiff@gmail.com. Thanks.

Steps to reproduce

Download the above files for NCDs analyses. Upload the analysis dataset and SAS files into SAS software Note the descriptions of the files. Run the SAS files with the analysis database. These data accompany a paper titled "The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis" For questions, email davidkcundiff@gmail.com

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• University of Washington

  WA, Seattle

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