ArticleFrontiers in public health2026
Resident-side health information for identifying community noise risks in digital public health governance.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Digital public health governance needs to identify community-level health risks beyond data generated after residents enter medical-service settings. In this study, resident-side health information refers to resident-reported information on residential noise perception, sleep disturbance, and health behavior that can supplement medical-service data. Noise pollution is a frequently perceived environmental problem in everyday life, and China's source-based noise governance framework needs resident-side evidence on whether different noise sources correspond to different sleep-related risks. Methods: This study used cross-sectional questionnaire data from urban residents in China. A total of 451 valid responses were retained. Noise exposure was measured through subjective noise annoyance and self-reported residential noise-environment proxy indicators. Sleep disturbance and health behavior were also measured through self-reported items. The analysis included descriptive statistics, reliability and validity tests, correlation analysis, regression models, mediation analysis, and exploratory comparisons across source-specific noise annoyance. Results: Subjective noise annoyance ( Discussion: In this cross-sectional self-reported sample, community noise exposure was linked to health behavior through sleep disturbance as a statistical pathway rather than as causal evidence. The findings provide exploratory resident-side evidence for identifying community noise risks and suggest that source-specific noise governance should consider how different noise sources enter residents' rest and recovery contexts.
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