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Data Sheet 1_A cross-sectional analysis of air pollution in primary schools and children fatigue.docx

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_A_cross-sectional_analysis_of_air_pollution_in_primary_schools_and_children_fatigue_docx/30021391
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IntroductionChildhood fatigue is influenced by various factors, including health status, socioeconomic conditions, lifestyle choices, and environmental factors like air pollution. In this study we aimed to explore the relationship between children’s fatigue and air pollution in the classrooms. Methods547 children from eight primary schools were enrolled into the study. Air pollution was measured in the classrooms including concentration of particulate matter (PM1, PM2.5, PM10) and micro elemental analysis of dust. Fatigue was assessed by the Pediatric Quality of Life Inventory Multidimensional Fatigue Scale self-reports in scores ranging from 0 to 100. Higher scores indicated less fatigue. Multivariate linear regression was performed to explore factors independently associated with children’s fatigue. ResultsMean age (± standard deviation [SD]) of respondents was 9.03 (±0.42) years; 44.9% were males. The mean (±SD) total fatigue score was 80.13 (±7.99). We found that higher levels of fatigue in children were linked to worse overall health, lower academic performance, and fewer extracurricular activities. Additionally, levels of particulate matter, barium, and vanadium in the natural dust aggregates were independently related to increased fatigue. ConclusionA cross-sectional type of our study only allows for the confirmation of statistical associations between fatigue levels and their possible determinants as specific air pollutants; further research is needed to explain and understand causal pathways better.
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2025-09-01
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