Rethinking the planetary health diet: GBD data reveal a 'sweet spot' for red and processed meat and longevity
Description
An analysis database of Global Burden of Disease 2017 (GBD2017) data originating from raw data files from the Institute for Health Metrics and Evaluation (IHME). The population-weighted data cover male and female cohorts aged 15–69 across 195 countries, evaluating noncommunicable disease (NCD) mortality and metabolic, dietary, and lifestyle risk factors. This dataset accompanies the Frontiers in Nutrition paper, "Rethinking the Planetary Health Diet: GBD Data Reveal a 'Sweet Spot' for Red and Processed Meat and Longevity." It includes: Formatted analysis database (.xlsx file) SAS formatting file NCD, BMI, and CVD step 1 (.txt files) Calculated summary Tables 1-3 corresponding to the regression analyses in the publication For questions, please contact davidkcundiff@gmail.com.
Files
Steps to reproduce
To reproduce the regression analyses and summary tables for the manuscript "Rethinking the Planetary Health Diet: GBD Data Reveal a 'Sweet Spot' for Red and Processed Meat and Longevity," follow these steps: 1. Download all files into the same local working directory or SAS server environment: - wtedCVDRfsCov2017.xlsx -GBD GLOBAL BURDEN OF DISEASE DATASET IMPORT & SETUP.txt - NCD, BMI, and CVD step 1 formatting file.txt - Frontiers in Nutrition 'Sweet Spot' paper.txt 2. Open your SAS environment (e.g., SAS Studio or Enterprise Guide) and update the file directory path in the SAS scripts to point to your local working folder. 3. Execute the import and formatting scripts: - Run "GBD GLOBAL BURDEN OF DISEASE DATASET IMPORT & SETUP.txt" and "NCD, BMI, and CVD step 1 formatting file.txt" to import, label, and structure the GBD2017 population-weighted data (wtedCVDRfsCov2017.xlsx) for male and female cohorts aged 15–69 across 195 countries. 4. Derive the output models and tables: - Run "Frontiers in Nutrition 'Sweet Spot' Paper.txt" to execute the models for noncommunicable disease (NCD) mortality, cardiovascular disease (CVD), and dietary/lifestyle risk factors. 5. Verify that the generated SAS output tables match the derived paired and unpaired male/female summary metrics reported in the publication.