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 include the following: 1. The Excel files that accompanied the above SAS code to produce the tables 2. A text file to import the analysis database into SAS 3. The SAS code to format the analysis database to be used for analytics 4. SAS code for deriving Tables 11-19 of EAT Lancet v GBD data 5. Analysis database (wtedCVDRfsCov2017) of population weighted GBD2017 data that includes over 40 health risk factors, noncommunicable disease deaths/100k/year of male and female cohorts ages 15-69 years from 195 countries (the primary outcome variable that includes over 100 types of noncommunicable diseases) and over 20 individual noncommunicable diseases (e.g., ischemic heart disease, colon cancer, etc). For questions, please email davidkcundiff@gmail.com. Thanks.
Files
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. Check the corresponding Excel files of Tables 1-19 to see that they correspond with the SAS codes. 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