SynthesisNoise & health
Systematic Review and Meta-Analysis of the Association between Environmental Noise Exposure and Depression and Anxiety Symptoms in Community-Dwelling Adults.
Synthesis in Noise & health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effects of green exercise on mental health in older adults: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Urban noise-induced stress and decision-making: effects of high-intensity acoustic exposure on risk-based and intertemporal choices.Frontiers in psychology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEnvironmental noise pollution has emerged as an increasingly significant public health concern, particularly in relation to its potential impact on the mental health of adults aged 35 years or older. This study aims to systematically examine the association between environmental noise exposure and the incidence of depression and anxiety symptoms within this demographic.
methodsFollowing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a comprehensive search of multiple electronic databases was conducted. A total of 11 eligible studies were identified, comprising 15,525 adults aged 35 years or older, among whom 2205 (14.2%) individuals reported experiencing symptoms of depression or anxiety. A random-effects model was used for meta-analysis with heterogeneity assessment, sensitivity analysis and exploratory subgroup analyses to evaluate the robustness and variability of the findings.
resultsThe meta-analysis demonstrated a significant association between long-term environmental noise exposure and an increased risk of depression and anxiety symptoms in adults aged 35 years or older (risk ratio [RR] = 1.29, 95% confidence interval: 1.16-1.51, P < 0.05). Substantial heterogeneity was observed across the included studies (I2 = 68.1%), suggesting moderate variability in study design, geographic location and exposure assessment methodologies. Sensitivity analyses confirmed the robustness of the findings, and recalculated RRs ranged from 1.27 to 1.35. Exploratory subgroup analyses revealed that road traffic noise was the most commonly investigated source and consistently exhibited positive associations. Notably, both aircraft noise and community-level or multi-source noise were linked to adverse mental health outcomes.
conclusionLong-term exposure to environmental noise increases the risk of depression and anxiety in adults aged 35 or older. Key factors such as socioeconomic status, residential environment and individual sensitivity to noise moderate this association. Future research should further explore the role of socioeconomic factors.
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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 OpenQuestion graph.