De-identified dataset and supporting files for: Sedentary behavior, eating habits, and their association with fast food consumption among Bangladeshi university students

This repository contains the de-identified dataset and supporting materials for the study titled “Sedentary behavior, eating habits, and their association with fast food consumption: a cross-sectional study among Bangladeshi university students.”

The study was conducted among 433 undergraduate and postgraduate students at the University of Chittagong, Bangladesh, in August 2025. It examines the relationships between sedentary behavior, eating habits, and fast food consumption frequency, with additional analysis of sugary beverage consumption.

Data were collected using a structured self-administered questionnaire covering:

Fast food consumption frequency (ordinal outcome)
Sugary beverage consumption frequency
Eating habits (snacking patterns, breakfast frequency, TV-eating, meal timing, meal source)
Sedentary behavior (social media use, screen time, commuting duration)
Lifestyle factors (physical activity, sleep patterns)
Sociodemographic variables (gender, academic year, residential status, income)

The dataset supports ordinal logistic regression analyses examining independent predictors of dietary behaviors and moderation effects by residential status.

Files included:

De-identified dataset in SPSS format (.sav)
CSV version of the dataset for universal access
Codebook with variable definitions and coding scheme
Questionnaire used for data collection (if included)
Statistical analysis syntax/scripts (if included)

Data processing and ethics:
All data have been fully de-identified prior to public release. No personally identifiable information is included. Ethical approval was obtained from the Bangladesh Institute of Innovative Health Research (Approval: BIIHR-2025-021), and all participants provided informed consent.

Reuse notes:

Variables are coded primarily as ordinal categories; refer to the codebook for detailed definitions.
The dataset is suitable for replication of the published analyses and for secondary research on dietary behavior and public health among university students in low- and middle-income settings.

Software compatibility:

.sav file: IBM SPSS Statistics
.csv file: Compatible with R, Python, Stata, Excel, and other statistical software

Licence:
This dataset is released under a Creative Commons CC0/Public Domain dedication unless otherwise specified.