DOI: 10.57760/sciencedb.psych.00696
title: Sample Cohort Dataset on Physical and Mental Health in Chinese University Students
title: 大学生身心健康队列样例数据集

description: This "(Sample) Dataset of College Students' Lifestyle and Physical and Mental Health" originates from the "Chinese Student Physical and Mental Health Data Consortium," a large-scale student health tracking and intervention research program initiated by Professor Wei Gaoxia's research team in collaboration with multiple universities across the country. The consortium is dedicated to building mental health risk prediction models based on lifestyle and physical dimensions, systematically addressing the prominent issues of low physical fitness and prevalent mental health problems among college students, and providing a scientific basis for advancing mental health education in universities in the new era.This sample dataset is the open-access version of the consortium's 2024 large-scale cross-sectional survey. Framed within the six core pillars of Lifestyle Medicine, Cohort 1 of the 2024 overall survey covered more than 20 universities nationwide and collected over 35,000 valid, full-length questionnaires. The research team employed a stratified random sampling method to extract 2,717 high-quality samples with no missing values from the 2024 full database to construct this sample dataset.This sample data highly replicates the baseline characteristics of the total 35,000 samples in terms of demographic characteristics and the distribution of core variables. The data file contains 82 variable fields, systematically covering three major modules:Demographic characteristics: Including gender, age (mean ≈ 19.3 years), grade, major, and family background, etc.;Multidimensional lifestyle indicators: Covering dietary habits, physical activity (IPAQ-SF, PARS-3), sleep quality (PSQI), stress management, social support, and smartphone addiction (MPIQ), etc.;Physical and mental health assessment results: Including standardized scores such as self-rated health status, BMI, generalized anxiety (GAD-7), depression (PHQ-9), and perceived stress (PSS-10).Usage Suggestions and Declaration: This sample dataset has undergone rigorous data cleaning and standardized coding. The core scales demonstrate excellent reliability and validity, offering extremely high reusability. This openly accessible sample data is particularly suitable for teaching demonstrations in data analysis, methodological validation (e.g., confirmatory factor analysis), and preliminary modeling for physical and mental health prediction. If researchers have in-depth research needs, such as cross-regional large-sample comparisons or network analysis, they may follow the instructions on the page to sign the "Data Usage Agreement" and apply to our research team for the complete restricted dataset containing over 35,000 samples. Link to the complete dataset: https://doi.org/10.57760/sciencedb.34161
description: This "(Sample) Dataset of College Students' Lifestyle and Physical and Mental Health" originates from the "Chinese Student Physical and Mental Health Data Consortium," a large-scale student health tracking and intervention research program initiated by Professor Wei Gaoxia's research team in collaboration with multiple universities across the country. The consortium is dedicated to building mental health risk prediction models based on lifestyle and physical dimensions, systematically addressing the prominent issues of low physical fitness and prevalent mental health problems among college students, and providing a scientific basis for advancing mental health education in universities in the new era.This sample dataset is the open-access version of the consortium's 2024 large-scale cross-sectional survey. Framed within the six core pillars of Lifestyle Medicine, Cohort 1 of the 2024 overall survey covered more than 20 universities nationwide and collected over 35,000 valid, full-length questionnaires. The research team employed a stratified random sampling method to extract 2,717 high-quality samples with no missing values from the 2024 full database to construct this sample dataset.This sample data highly replicates the baseline characteristics of the total 35,000 samples in terms of demographic characteristics and the distribution of core variables. The data file contains 82 variable fields, systematically covering three major modules:Demographic characteristics: Including gender, age (mean ≈ 19.3 years), grade, major, and family background, etc.;Multidimensional lifestyle indicators: Covering dietary habits, physical activity (IPAQ-SF, PARS-3), sleep quality (PSQI), stress management, social support, and smartphone addiction (MPIQ), etc.;Physical and mental health assessment results: Including standardized scores such as self-rated health status, BMI, generalized anxiety (GAD-7), depression (PHQ-9), and perceived stress (PSS-10).Usage Suggestions and Declaration: This sample dataset has undergone rigorous data cleaning and standardized coding. The core scales demonstrate excellent reliability and validity, offering extremely high reusability. This openly accessible sample data is particularly suitable for teaching demonstrations in data analysis, methodological validation (e.g., confirmatory factor analysis), and preliminary modeling for physical and mental health prediction. If researchers have in-depth research needs, such as cross-regional large-sample comparisons or network analysis, they may follow the instructions on the page to sign the "Data Usage Agreement" and apply to our research team for the complete restricted dataset containing over 35,000 samples. Link to the complete dataset: https://doi.org/10.57760/sciencedb.34161