ArticleJournal of urban health : bulletin of the New York Academy of Medicine2025
The U-Shape Association Between Noise and Individual Depression: Nationwide Longitudinal Evidence from Three Waves of CHARLS.
Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- The Impact of Noise Pollution on Cognitive Function in Middle-Aged and Older Adults: Empirical Evidence from the CHARLS.Behavioral sciences (Basel, Switzerland) · 2025Article
- Can New-type Urbanization Pave a Way against Depression? Evidence from a Quasi-Natural Experiment in China.Journal of urban health : bulletin of the New York Academy of Medicine · 2025Article
- Intergenerational Psychological Capital, Disability, and Depressive Symptoms in the Shadow of Functional Deprivation Among Middle-Aged and Older Adults in China.Psychology research and behavior management · 2025Article
- Is Too Noisy as Bad as Too Quiet? The Inverted U-shaped Relationship between Noise and Sleep Duration.Noise & healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Depression is a common mental disorder formed by a combination of various factors. Existing researches have already demonstrated that noise indeed impacts the level of depression, but their results were inconsistent. To reconcile seemingly contradictory findings, this study aims to investigate how noise affects individual depression using big data mining and analysis techniques. The individual data was obtained from the China Health and Retirement Longitudinal Study (CHARLS) over 3 years (2013, 2015, and 2018) totaling 9693 participants coming from 125 different cities. The Chinese version of the 10-item Center for Epidemiologic Studies Depression Scale (CES-D) was employed to assess depression scores, while the search index for noise-related keywords was obtained from Baidu Index to measure noise levels across different cities. A curvilinear model with fixed effects was applied to analyze the relationship between noise and depression. Additionally, moderating effect analyses were conducted to examine the influence of city size and green space. The results indicate a U-shaped relationship between depression and noise, wherein depression initially decreases with increased noise, then subsequently rises. The moderating effect analysis suggests that both city size and green space influence this U-shaped curve; notably, in cities with larger populations or higher green coverage rates, the curve flattens. This study reveals that the impact of noise on depression is complex, which is the result of a multifactorial synergy. It underscores the necessity for urban planning and management to prioritize the creation of friendly sound environments, which could enhance the physical and mental health of urban residents.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.