Abdominal Obesity in India 🇮🇳

🚀 This README provides comprehensive instructions for setting up and utilizing this repository within RStudio. The repository contains code and data related to a correspondence article to the following paper: Chaudhary M, Sharma P. Abdominal obesity in India: analysis of the National Family Health Survey-5 (2019–2021) data. The Lancet Regional Health - Southeast Asia 2023; 14: 100208..

🔥 The motivation for reproducing the analysis is presented here.

📜 Table of Contents

1. Getting Started
   • Clone the Repository
   • Importing Data
2. Running the Analysis
   • Order of Execution
3. Outputs
4. License

🚀 Getting Started

📦 Clone the Repository

To begin, you'll need to clone this repository and set it up as a version-controlled project in RStudio. Please follow these steps:

1. Install R and RStudio: If you haven't already, make sure you have R and RStudio installed on your machine. You can download them from the following links:

   • R: Download R
   • RStudio: Download RStudio

2. Clone the Repository:

• Open RStudio.
• Click on "File" in the top menu.
• Select "New Project..."
• Choose "Version Control" and then "Git".
• In the "Repository URL" field, enter the URL of this repository.
• Choose a directory where you want to create your project.
• Click "Create Project".

RStudio will clone the repository and set it up as a project, ensuring you have all the necessary files and environment ready for use.

🔗 Importing Data

Once the project is set up, you'll need to import the essential data files. Ensure that the data files are placed in a directory within the project's root directory. Follow these steps:

1. Create a 'Data_raw' Folder:

• In your project directory, create a new folder named 'Data_raw'.

1. Download Data Files:

• Download the Household Members Recode, Individual Recode, and Men's Recode STATA files from the DHSProgram website. The files to download are IAPR7EDT, IAIR7EDT, and IAMR7EDT, respectively.

1. Extract Data Files:

• Extract the downloaded .rar files in such a way that each .rar file corresponds to a separate folder within the 'Data_raw' directory.

Here's the expected file structure:

NFHS_AbdominalObesity ├───Data_clean ├───Data_raw │ ├───IAIR7EDT │ ├───IAMR7EDT │ ├───IAPR7EDT │ ├───sdr_subnational_boundaries_2023-08-21 │ │ └───shps │ └───shapefile ├───Output └───Session info

The Output directory is the location for exporting output from running the R Markdown and Scripts files. The Session info folder contains details regarding the packages used in the code, as well as the locations of the files corresponding to the packages.

📈 Running the Analysis

To perform the analysis, follow these steps:

1. Execute R Markdown Files:

• The variables used can be seen in Dataraw/variablekey.csv.
• Open the following .Rmd files in RStudio:
  • women.Rmd
  • men.Rmd
  • visualizations.Rmd
  • maps.Rmd
  • flowcharts.R

1. Run All Chunks:

• For each .Rmd file, run all code chunks. We recommend using the "Restart R and Run All Chunks" command to minimize the risk of R Session suspension.

By following this order, you'll ensure that each file builds upon the results of the previous ones and that the project progresses as intended.

Outputs

Prevalence of Abdominal Obesity by State

Prevalence of Abdominal Obesity among Women by District

Sample Selection Flowchart

Prevalence of Obesity

Model estimates for association of abdominal obesity with different socioeconomic factors

🔐 License

This work is licensed under a Creative Commons Attribution 4.0 International License.