Project Title
Exposure to tobacco content and the risk of initiation of tobacco use among nonsmoking adolescents (13-15 years)? A secondary analysis of the 2018 Global Youth Tobacco Survey conducted in Uganda.
Description
This project examines the association between gender and the future risk of tobacco use among nonsmoking adolescents aged 13–15 years in Uganda. Using data from the 2018 Global Youth Tobacco Survey (GYTS), the analysis evaluates predictors of tobacco use, including peer influence, parental smoking, and exposure to anti-smoking advertisements. The goal is to inform strategies for preventing tobacco use in low- and middle-income countries.
Features Full analysis provided in a reproducible R Markdown file (analysis.Rmd). Includes data wrangling, visualization, and statistical modeling steps. Use of Logistic regressions to analyze predictors.
Contents analysis.Rmd: The R Markdown file containing all code, analyses, and visualizations. README.md: A guide to understanding and reproducing this project. LICENSE: Licensing information.
Requirements To reproduce the analysis, ensure you have the following:
Software:
R (version 4.4.1 or higher)
RStudio
R Packages (loaded via pacman): haven: Imports and exports data in various formats, such as SPSS, SAS, and Stata. readr: Provides efficient functions for reading and writing rectangular data (CSV, TSV, etc.) into R, offering faster and more user-friendly methods than base R. tidyverse: A collection of packages that make data science tasks easier and more consistent. It includes packages for data manipulation (dplyr), visualization (ggplot2), tidying data (tidyr), and more. table1: Generates publication-ready tables, typically used for summarizing descriptive statistics or presenting baseline characteristics in clinical studies. DiagrammeR: Allows you to create diagrams and flowcharts, such as flow diagrams, network graphs, and more complex visual representations of data and processes. rsvg: Converts SVG (Scalable Vector Graphics) files into raster images (e.g., PNG), allowing you to export vector graphics from R. dplyr: A core package of the tidyverse that provides a suite of functions for efficient data manipulation (e.g., filtering, selecting, mutating, summarizing). car: Provides a wide range of tools for regression analysis, including diagnostic tools and tests for linear models (e.g., hypothesis testing, variance inflation factors). lmtest: Offers tools for conducting diagnostic tests on linear regression models, such as tests for heteroscedasticity and autocorrelation. openxlsx: Provides tools for reading, writing, and formatting Excel files without needing to rely on external software like Excel or Java, allowing you to manipulate Excel files directly from R. broom: Designed to convert the outputs of statistical models into tidy data frames, making it easier to work with, manipulate, and visualize model results.
Usage Clone the repository to your local machine:
bash Copy code git clone https://github.com/Atwebembere/Final-Project.git Open the analysis.Rmd file in RStudio.
Run the .Rmd file:
Click Knit to generate an HTML or PDF report of the analysis and results. Alternatively, execute code chunks interactively to explore the workflow.
Results Key findings: The study highlights the pervasive impact of tobacco industry marketing and social perceptions on adolescent smoking intentions in Uganda. It also underscores the protective role of school-based education in reducing tobacco use intentions. Stricter regulation of marketing practices and the promotion of culturally tailored, education-based interventions are crucial for reducing tobacco initiation among youth.