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. 2025 Nov 18;27(128):570–582. doi: 10.4103/nah.nah_163_24

Data Driven Bibliometric Analysis of Studies on Aircraft Noise and Health Effects

TianLun He 1, JiaYu Hou 2, Xiang Guo 3, Da Chen 4,✉
PMCID: PMC12677276  PMID: 41259605

Abstract

Background:

The substantial growth in global air traffic has expanded the range of aircraft noise impacts the health outcomes, making aircraft noise a key limiting factor for future airport expansions. This study presents a comprehensive review and data-driven bibliometric analysis of the health outcomes of aircraft noise, aiming to clarify the network structure and development trends in this research field.

Methods:

Relevant keywords (aircraft, airport noise hazard, annoyance, exposure, damage, risk, illness, resident, worker health, sound quality) were used to extract literature from the Web of Science database, covering the period from 2001 to May 2024. Only journal articles were retained, and publications in unrelated fields were excluded. Visualization was performed using Citespace, VOSviewer, and Bibliometrix.

Results:

A total of 1512 articles were analyzed. The number of publications increased significantly in 2019. “Annoyance” and “exposure” were among the most frequently used keywords. The top co-cited journals were Journal of Acoustical Society of America (JASA, 2334 citations), Noise and Health (1315 citations), and Journal of Sound and Vibration (JSV, 1298 citations). The analysis also summarized preliminary quantitative results on noise metrics and health outcomes. For example, an increase of 10 dB in day–evening–night noise exposure was associated with a 1.09% increase in the exposure–response relationship for ischemic heart disease.

Conclusion:

Aircraft noise has been shown to adversely affect human health, contributing to sleep disturbance, cardiovascular disease, and decreased quality of life in airport communities. This study advocates for effective measures to reduce the health impacts of airport noise on communities and highlights the need for interdisciplinary collaboration to address the complex health issues caused by aircraft noise. In the future, a comprehensive synthesis and categorization of research directions in this field could help identify emerging topics and general trends, thereby supporting the development of more effective airport noise management strategies.

Keywords: aircraft, airport, bibliometrics, health, noise, transportation

KEY MESSAGES

  • (1)

    The rapid expansion of global air traffic has intensified aircraft noise exposure and associated health risks, becoming a critical constraint for future airport development.

  • (2)

    This study offers a comprehensive review and bibliometric analysis to reveal the structural patterns and evolving trends in research on the health impacts of aircraft noise.

  • (3)

    Quantitative associations between noise indicators and health outcomes were examined, uncovering a lack of consistent classification frameworks across existing studies.

  • (4)

    The findings underscore the urgency of implementing effective noise mitigation strategies and highlight the importance of interdisciplinary collaboration in addressing complex noise-related health challenges.

INTRODUCTION

The increase in global air traffic has intensified noise pollution issues in airports and surrounding areas.[1] Aircraft noise, characterized by its chronic nature and high intensity, may have more significant health effects than other types of noise.[2,3]

Aircraft noise affects human health in various ways, including cardiovascular health, sleep quality, mental well-being, and children’s cognitive development.[4,5] It has been associated with heightened stress and anxiety.[6] Higher rates of cardiovascular diseases, such as hypertension and coronary artery disease, have been observed in populations living near airports.[2,7] Exposure to noise levels above 50 dB A-weighted Equivalent Continuous Sound Level (LAeq) increases the risk of severe cardiac conditions, including myocardial infarction, heart failure and arrhythmias.[8] Study also suggest that heart rate variability may reflect cardiovascular responses to aircraft noise, particularly in airport workers.[9] Additionally, sleep disturbances are another critical concern. Aircraft noise has been linked to increased wakefulness and decreased sleep quality, especially in children exposed to high noise levels.[10,11]

To date, there has been no comprehensive review of the health impacts of aircraft noise. This study examines key concerns and research trends, aiming to provide a scientific assessment of the topic. It outlines developments over the past two decades and offers recommendations for future studies. Traditional literature reviews are often time-consuming and subjective, which may influence their findings. By contrast, this study employs data-driven bibliometric methods to reduce workload and subjectivity, enabling an objective analysis of current trends and emerging directions. The bibliometric approach integrates perspectives from epidemiology, environmental science, and health policy, offering insights to support policymaking and the development of interventions aimed at mitigating the health effects of airport noise.

METHODS

Data Source and Research Process

The literature and data used in this study were primarily sourced from the Web of Science database, which offers a comprehensive collection of high-quality, peer-reviewed articles and has been widely adopted in previous academic research.

Studies examining the health effects of aircraft noise are often subjective and fragmented. Therefore, to ensure comprehensive coverage of the relevant literature, a variety of synonymous terms were strategically combined in the keyword search strategy.

The literature screening process is illustrated in Figure 1. First, keywords (listed in the supplementary material) were used to retrieve related literature. Second, the focus was placed on the time period from 2001 to May 2024. Third, only journal articles were included to ensure scholarly rigor and relevance. Finally, articles from unrelated fields (also detailed in the supplementary material) were excluded to maintain a focused and pertinent scope. This systematic approach ensures a comprehensive and targeted analysis of the health impacts of aircraft noise, drawing insights from the most relevant and authoritative sources.

Figure 1.

Figure 1

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Data-driven bibliometric analyses.

Mapping and Visualization

Bibliometric tools facilitated a detailed analysis that included descriptive, collaboration and citation network, and trend analysis. The results were visually represented using tools like CiteSpace (version: 6.2.R4, Drexel University, Philadelphia, USA), VOSviewer (version: 1.6.19, Leiden University, Netherlands), and Bibliometrix (version: 4.0, University of Naples Federico II, Italy), enhancing the clarity and interpretability of the analysis. This methodology ensures a systematic and holistic research approach, enabling a comprehensive understanding of the scientific landscape and progress in the field. It facilitates the identification of research trends, boundaries, key themes, and foundational studies.[12,13]

VOSviewer is known for its user-friendly interface and efficiency in large bibliographic databases, allowing for rapid generation of keyword networks and co-citation maps. However, it is limited in performing temporal analyses and burst detection. CiteSpace offers broader parameter outcomes, though it is comparatively more complex to operate. Bibliometrix, built on the R programming language, is a flexible statistical analysis tool freedom in analysis but requires a certain level of coding proficiency. This study combines the three tools to capitalize on their respective strengths, ensuring both precision and comprehensiveness in the analysis.

The research process consists of three main components: retrieval of basic bibliographic information, analysis of keyword co-occurrence clustering and trend evolution, and co-citation analysis to identify highly influential literature and potential future research directions.

  • (a)

    The analysis of publication volume, source countries, and annual trends provides insights into the structure and development of the research landscape on aircraft noise and its health impacts, highlighting major research frontiers.

  • (b)

    Within this framework, VOSviewer identifies keywords as “nodes,” represented by circles. The larger the node, the more frequently the keyword appears and the greater its weight, indicating higher importance. Bibliometrix is used to generate a Sankey diagram illustrating the evolution of keyword trends across three time points. CiteSpace is employed to display clusters of research directions based on keyword co-occurrence.

  • (c)

    Co-citation analysis involves examining the co-citation relationships among journals, authors, and highly cited articles, allowing for a thorough investigation of key research focuses and their evolution over time. This section also summarizes quantitative associations between aircraft noise and health effects and discusses key areas for future research.

RESULTS

Total Number of Publications

Figure 2 illustrates the chronological distribution of the literature on the impact of aircraft noise on human health, revealing a generally upward trend in annual publication volume from 2002 to May 2024. Notable surges in output occurred in 2009 and 2019. Following 2019, increased public concern regarding the health implications of airport noise, alongside growing academic interest, became more evident.

Figure 2.

Figure 2

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Evolution of publications over the 2002–2024 period (created by Bibliometrix).

Our analysis also includes publication output by country, as shown in both Figures 2 and 3. In 2002, most of the literature originated in the United States, which gradually expanded internationally to include more international contributions over the following two decades. The United States accounts for 23.26% of total publications, representing the largest national share. In contrast, China’s independent research on civil aviation emerged later, with relatively few publications addressing the health hazards of aircraft noise prior to 2010. A steady increase was observed between 2011 and 2018, followed by a notable surge after 2019.

Figure 3.

Figure 3

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Most productive and influential countries (created by Bibliometrix).

Keywords Analysis

We analyzed the evolution of the keywords average publication year related to aircraft noise and its health impacts, as shown in Figure 4. The most frequent terms include “aircraft noise,” “exposure,” “hypertension,” and “annoyance.”

Figure 4.

Figure 4

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Keywords average publication year related to aircraft noise and its health impacts. Note: Figure 4 is created by VOSviewer. The connections represent co-occurrence relationships.

By examining keyword trends, Figure 5 reveals how research themes have evolved. The timeline is divided into the following three periods: 2002–2010, 2011–2015, and 2016–2024. “Aircraft noise” remained the core focus throughout. In the first stage, the emphasis was on “noise exposure,” “epidemiology,” and “exercise,” with methodologies centered on epidemiological surveys and case–control studies using traditional data collection and analysis to assess potential health impacts of noise.[14,15,16] In the second stage, research expanded to include “annoyance,” “children,” “mortality,” and “inflammation.” This stage is marked by diversification in research themes, with growing attention to various dimensions of annoyance and physiological effects. In the third stage, attention shifted toward topics such as “performance,” “brain,” “identification,” “prediction,” and “management.”

Figure 5.

Figure 5

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Trends in research focus over time. Note: Figure 5 is created by Bibliometrix. The lines represent the flow and evolution of keywords.

Keyword clustering helps identify and summarize central themes and directions within the literature, offering a clearer understanding of prevailing topics and their interrelations. This method supports researchers in discovering underexplored areas, generating new hypotheses, and guiding future inquiry. For illustration, correlated keywords are grouped and color-coded in Figure 6. “Annoyance” emerges as a key theme in the study of aircraft noise effects keywords include “aircraft noise,” “traffic noise,” and “environmental noise.”

Figure 6.

Figure 6

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Keywords classification (by CiteSapce).

Journal Co-citation

The study first quantified the number of articles published in leading source journals, as shown in Figure 7. Top journals include Journal of Acoustical Society of America (JASA), International Journal of Environmental Research and Public Health (IJERPH), Applied Acoustics, Noise and Health, Environment Research and Transportation Research Part D. These journals span the fields of environment, health, acoustic, and transportation management, reflecting the interdisciplinary nature of aircraft noise and health research.

Figure 7.

Figure 7

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Most relevant sources (by Bibliometrix).

Academic exploration of the relationship between aircraft noise and health encompasses disciplines such as aerospace engineering, medical sciences, and acoustic research. Co-citation analysis and content clustering using the Area Clustering Map (ACM) model identified the most frequently cited journals and highlighted key thematic areas, as shown in Figure 8. J Acoust Soc Am (JASA), leads with 2334 citations, followed by Noise and Health with 1315 citations, and J Sound Vib (JSV) with 1298 citations. Environmental Health Perspectives (Environ Health Persp) ranks fourth with 1044 citations. J Acoust Soc Am and JSV, as leading publications in acoustics, play a major role in shaping both theoretical and applied research. Noise and Health and Environ Health Persp focus more directly on the public health implications of noise pollution.

Figure 8.

Figure 8

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Journal co-citation analysis (by VOSviewer).

We conducted clustering analysis of co-cited journals to identify correlations and shared research foci. Cluster 1 includes journals such as Environ Health Persp, Noise & Health, Journal of Occupational and Environmental Medicine (Occup Environ Med), and The Lancet, which are recognized leaders in medical and health-related fields. Cluster 2 consists of Transportation Research Part D, JASA, JSV, Applied Acoustics, and Building and Environment, providing foundational theoretical frameworks. Cluster 3 contains journals such as Environment International and Environmental Research, which concentrate on the public health and environmental consequences of aircraft noise. Lastly, Cluster 4 features the Journal of Environmental Psychology and Psychological Medicine, which focus on psychomedical research, particularly the perception and psychological effects of aircraft noise, with psychoacoustics serving as a research theme.

Citation of Author

We set a minimum threshold of 70 co-citations for inclusion in the analysis, and 41 authors met this criterion. The results of the cluster analysis based on research orientation are shown in Figure 9. The highly influential paper “Annoyance from transportation noise…” by Miedema and Oudshoorn[16] investigates the effects of transportation noise, with particular emphasis on aircraft, on human annoyance. This seminal work is widely cited for its comprehensive analysis of the relationship between various noise exposure metrics and the resulting annoyance experienced by individuals. The article’s significant contribution to aviation noise hazard research is attributed to its methodological rigor and innovation in quantifying and interpreting the impact of noise exposure on human annoyance.

Figure 9.

Figure 9

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Author citation analysis (by VOSviewer).

Note: Node colors represent author clusters: green for annoyance and exposure–response studies, blue for cognitive and psychological effects, red for cardiovascular epidemiology, and yellow for biomedical mechanism research on noise-induced health outcomes.

3.5 Co-citation of Articles

For this study, we established a co-citation threshold of 45. The analysis yielded 10 most frequently cited articles in the periods 2000–2009 and 2010–2023, which are presented in Table 1.

Table 1.

List of the most cited articles

Ranking 2000–2009
 2010–2023
Article Citation Article Citation
1 Miedema and Oudshoorn[16] 152 Basner et al.[17] 107
2 Jarup et al.[15] 112 Munzel et al.[18] 68
3 Stansfeld et al.[19] 106 Ban Kempen et al.[20] 65
4 Fields et al.[21] 104 Schmidt et al.[22] 60
5 Babisch et al.[14] 64 Guski et al. [23] 60
6 Muzet et al. [24] 62 Basner et al. [25] 54
7 Babisch et al. [26] 58 Hansell et al. [27] 50
8 Franssen et al. [28] 58 Huss et al. [29] 50
9 Babisch et al.[30] 57 Sorensen et al. [31] 48
10 Stansfeld et al. [32] 56 WHO[33] 48
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Quantitative Analysis and Management Strategies for Aircraft Noise’s Health Effects

During the literature analysis, we reviewed the strength of epidemiological and mechanistic evidence on the health effects of noise, with particular attention to studies providing quantitative results. We prioritized articles based on the chronological order of publication, availability of data, and whether the findings were peer-reviewed. The results show that the health effects of aircraft noise can be quantified to a certain extent by assessing statistically significant relative risks (RR) with 95% confidence intervals that do not include zero Specifically, we identified relative risks uniquely attributable to aircraft noise, and screened three methods for calculating exposure–response relationships (ERRs): highly annoyed (HA),[23] highly sleep disturbed (HSD), and ischemic heart disease [Table 2].[20,34]

Table 2.

Exposure–response relationships of aircraft noise to major health outcomes

Health outcome Noise metric ERR function/relative risk estimate [95% confidence interval] ERR lower
Highly annoyed Lden %HA = −50.9693 + 1.0168 × Lden + 0.0072 × (Lden)2 40 dB
Highly sleep disturbed Lnight %HSD = 17.07421 − 1.12624 × Lnight + 0.02502 ×(Lnight)2 40 dB
Ischemic heart disease Lden 1.09 [1.04 − 1.15] per 10 dBA 47 dB
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Note: ERR = exposure–response relationship, %HA = percentage of highly annoyed population, %HSD = percentage of highly sleep disturbed population, Lden = day-evening-night sound Level, Lnight = night sound level.

The method of calculating ERRs enables the initial establishment of a basic quantitative relationship between aircraft noise and health outcomes. It also allows for the estimation of the population affected by different health impacts, using direct noise metrics such as Lden or Lnight. This method not only quantifies the direct health effects of noise on the population, but also serves as an indicator to evaluate the effectiveness of noise management measures. Through this approach, the link between specific management strategies and their outcomes on various health indicators can be more accurately assessed, thereby supporting the development of more targeted noise control strategies.

Accordingly, we further identified authoritative papers most relevant to aircraft noise management by focusing on keywords such as aircraft noise, human health, and good management. We then summarized and analyzed various noise mitigation strategies proposed in recent years.

Adaptation of Measures to Aircraft and Operational Characteristics

Consideration of noise levels across different engine types (e.g., turboprop vs. jet), wake turbulence categories, available runway lengths to optimize flight trajectories, and takeoff/landing strategies.[35] Planning transportation routes is to minimize noise exposure in densely populated areas.

Trade-offs between Environmental Protection and Noise Pollution

Efforts to reduce carbon emissions and fuel consumption may inadvertently increase noise, such as thorough rapid climb procedures.[36] Consideration of multi-airport systems to alleviate noise pressure concentrated around a single airport.

Operational and Social Impact Trade-offs

Operational changes, such as removal of departure speed limits, may reduce environmental pollution and long-distance noise, but lead to increased low-level noise exposure.[37] Allocation of arrival and departure routes should consider both spatial distribution and temporal variation in population density.[38,39]

Perception and Management of Sensitivity to Specific Groups

Development of management strategies based on the noise tolerance of different population groups.[40] Implementation of effective communication strategies and participatory decision-making mechanisms.[41,42]

Integration of Technology and Consulting Tools

Use of GIS, hotspot analysis, and sleep disruption indices to better evaluate the health impacts of noise and related healthcare costs.[43,44,45] Development of 3D sound propagation models that incorporate terrain and structural influences to simulate and predict noise distribution more accurately.[46,47] Use of multi-objective optimization model based on sound quality metrics.[48]

Reasonable Noise Charging Policy

Noise exposure levels are calculated based on international civil aviation organization (ICAO) standards, with different charges imposed on aircraft according to their noise level, along with noise restrictions. Aircraft with higher noise levels is charged more, and their operations are restricted during nighttime or specific hours, effectively reducing noise pollution.[49]

DISCUSSION

Total Publication Trends

The onset of the Coronavirus Disease 2019 (COVID-19) pandemic in 2019 marked the beginning of a 3-year period of significant disruption to the global aviation sector.[50,51] According to the International Air Transport Association, passenger demand in 2020 dropped by 65.9% compared to previous year, representing the steepest decline in the industry since the Second World War and highlighting the pandemic’s role in intensifying health-related concerns.[52] The United States, with its well-developed civil aviation infrastructure, has emerged as a leader in research on airport and aircraft noise. This increase in research activity is likely associated with national policy shifts and technological advancements in the aviation sector, which, in turn, have driven investigations into the environmental acoustic impacts of aircraft noise and its health effects on populations living near airports, including local residents, airport staff, and other related personnel.

Keywords Changing Trends

In 2020, the COVID-19 pandemic caused a sharp decline in global air travel and heightened public awareness of infectious diseases, leading to the emergence of terms such as “COVID-19” and “epidemiology” in keyword trends.[53]

Methodologically, most studies employ epidemiological surveys and case–control designs, relying on conventional data collection and analysis techniques to assess the potential health effects of noise exposure. Research primarily focuses on identifying and verifying associations between aircraft noise and specific health issues (e.g., hearing loss, sleep disorders), thereby providing an initial scientific foundation for environmental noise management.[15,24,54] Over time, the research scope has expanded to include long-term effects on children’s physical health, cognitive development, and psychological well-being. In addition, growing attention has been given to the role of noise in triggering biologically based inflammatory responses that are closely associated with cardiovascular diseases.[22,27,29,55] This inflammatory mechanism has increasingly become a target for therapeutic and preventive interventions.[55]

The integration of advanced technologies such as big data analytics has significantly enhanced noise monitoring and large-scale data processing. Techniques like neural networks have improved the ability to extract and interpret massive datasets.[2,13,56] Meanwhile, research goals have gradually shifted toward more comprehensive risk and noise management strategies, aiming to mitigate noise impacts both at the source and along transmission paths, thereby reducing potential health risks to populations residing near airports.[39] Observing the overall trend across three stages of development reveals that interdisciplinarity has become a key driver of future research. Utilizing large-scale aircraft noise monitoring data in conjunction with machine learning analysis of human health data is emerging as a forward-looking strategy, reinforcing the notion that prevention remains more valuable than treatment.[48,49]

Overall, these converging research directions reflect the increasing complexity and interdisciplinary nature of investigations into the health effects of aircraft noise. This progression—from initial studies, identifying associations to active management and mitigation strategies—demonstrates an evolving research landscape that is increasingly aligned with public health priorities and technological advancement. Such an evolution not only informs current public health interventions but also charts a future path for minimizing the environmental health risks associated with aircraft noise, ultimately contributing to the development of healthier communities in airport-adjacent areas.

Papers Co-citation Analysis

Period 2000–2009

Miedema and and Oudshoorn[16] had introduced a computational tool to enhance the accuracy of assessing the health impacts of noise exposure at different times of the day. Jarup et al.[15] identified a strong exposure–response relationship between nighttime aircraft noise—more pronounced than that of road traffic noise—and hypertension. As the first large-scale, multi-nation European study under the HYENA project, it systematically evaluated the association between noise and hypertension.[15] Other frequently cited publications from this period provided a comprehensive analysis of the diverse impacts of aircraft noise on public health.[14,19,21,24,26,28,32] These studies examined the relationship between traffic noise and myocardial infarction incidence, assessed the effects of noise exposure on sleep, social behavior, and physiological responses, and explored how aviation noise affects children’s cognitive development, particularly reading comprehension and memory. They also emphasized the need for standardized research methodologies to systematically investigate noise-related issues in airport environments.

Period 2009–2023

In the second period (2009–2023), Basner et al.[17] integrated environmental, physiological, and psychological factors, providing a robust scientific basis for noise regulation and mitigation policy. Their study highlighted the importance of incorporating health considerations into airport planning and operations. Munzel et al.[18] identified sleep disruption as a key pathway linking chronic noise exposure to cardiovascular harm and advocated targeted interventions, including transportation optimization and sound insulation. Furthermore, other highly co-cited studies during this period systematically analyzed the effects of airport noise on neurological disorders and mortality risks, thus broadening the evidence base regarding its public health implications.[20,22,23,27,29] These studies examined the impact of noise exposure across various populations, evaluating its association with hypertension, myocardial infarction, and stroke, and reinforcing the need for noise mitigation strategies to reduce the long-term health risks associated with chronic environmental noise.

Cluster Analysis

We categorized these highly cited studies into four clusters based on the specific health effects of environmental noise they address and the research methods employed.

Cluster A: Quantification and Standardization of Transportation Noise Impact

This cluster comprises studies that established the relationship between day-night average sound level (DNL), day-evening-night noise level (DENL), and the percentage of highly annoyed individuals (%HA), forming a basis for assessing noise impacts.[57] The findings indicate that aircraft noise is more disturbing than road and rail noise at equivalent DNL levels, underscoring the necessity of differentiating noise sources in policymaking. Additionally, this cluster emphasizes the development of empirical formulas to convert DNL to DENL, thereby improving the noise exposure assessments.[21] A key contribution lies in the standardization of annoyance measurement tools, advocating for harmonized response formats such as the five-point descriptive scale and a corresponding 0–10 numerical scale.[26] These standardized instruments enable global comparison and cross-study validation of community response to noise exposure.

Cluster B: Non-Auditory Impacts

Prolonged noise exposure has been associated with elevated adrenaline levels, impaired memory and reading comprehension in children, and increased blood pressure in adults. These studies also examine how aviation and road traffic noise affect children’s health, incorporating socio-demographic and socioeconomic variables.[19,32] Cross-sectional data from three countries suggest that aviation noise may reduce cognitive performance in children, highlighting the urgency of implementing effective noise control strategies, particularly in environments that include vulnerable populations.

Cluster C: Hypertension Risk

Two key studies exemplify this focus. The first, based on a hospital-based case–control design in Berlin, found that exposure to daytime noise levels exceeding 70 dB(A) significantly increased the risk of myocardial infarction among men, particularly those, who had resided at the same address for over a decade.[14] The second study, part of the HYENA project, investigated the effects of aircraft and road traffic noise on hypertension near airports. It reported a clear exposure–response relationship, showing that a 10 dB increase in nighttime aircraft noise corresponded to a 14% risk of hypertension [odds ratio (OR) = 1.14; 95% confidence interval (CI): 1.01–1.29].[15]

These findings suggest that long-term exposure to elevated noise levels, especially at night, may disrupt cardiovascular health. The proposed mechanisms include increased stress, sleep disturbance, and alterations in autonomic nervous system function. These results reinforce the need to recognize noise exposure as a significant public health issue, particularly in community areas near airports.

Cluster D: Physiological Mechanism of Noise

This cluster explores the physiological mechanisms through which noise exposure affects human health, including impacts on the autonomic nervous system, hormonal responses, and long-term cardiovascular risks. A 2014 review in The Lancet emphasized both occupational hearing damage and concerns about social noise exposure, such as through personal music players.[17] The study demonstrated that noise can cause annoyance and sleep disruption, which in turn increase the prevalence of hypertension and cardiovascular diseases. Munzel et al.[18] further linked environmental noise—especially from aircraft and traffic sources—to endothelial dysfunction and cardiovascular outcomes such as hypertension and stroke. They highlighted the role of nighttime noise in triggering autonomic arousal and stress hormone secretion. Schmidt et al.[22] examined the effects of acute nighttime aircraft noise on endothelial function, finding significant increases in adrenaline levels. Guski et al.[23] showed that each 10 dB increase in noise significantly raised the likelihood of experiencing high annoyance, with a threefold increase in risk.

These findings highlight key areas for future research on the health effects of noise. Although existing studies have established a link between aircraft noise and cardiovascular diseases, the underlying mechanisms remain insufficiently understood. Future research should investigate the effects of nighttime noise exposure on endothelial function and cardiovascular risk. Additionally, further more studies are needed to assess the long-term impact of noise on sleep quality and cognitive function, particularly among vulnerable groups such as children. As urbanization continues to increase transportation-related noise, research should broaden its scope to address the wider health implications and promote the development of effective regulatory policies and preventive strategies to safeguard public health.

Quantitative Analysis and Management Strategies for Aircraft Noise Health Effects

To effectively integrate quantitative assessment outcomes into future noise management strategies, it is essential to incorporate established ERRs into noise control planning. By applying indicators such as Lden and Lnight to quantify health outcomes, it becomes possible to link specific noise levels to adverse effects such as annoyance, sleep disruption, and cardiovascular conditions. This approach facilitates the development of targeted, evidence-based noise management measures that directly address the needs of the most affected populations. Furthermore, taking into account varying levels of noise sensitivity and fostering community engagement enables the design of protective interventions tailored to vulnerable groups, particularly children and the elderly people. The integration of advanced technological tools supports the implementation of personalized strategies and predictive models, thereby significantly reducing the health burden of aircraft noise and improving overall community well-being.

Implications and Limitations

A notable limitation identified in this study is the limited participation of industry professionals, airline–airport collaborators, and policymakers within the academic research clusters.

This lack of engagement may hinder the translation of scientific findings into practical noise management solutions. In addition, the analysis may exhibit temporal bias due to the citation advantage held by older studies, which could overshadow emerging research offering novel insights. Consequently, recent contributions that have the potential to shape future scientific directions may remain underrecognized if they have not yet had sufficient time to establish their academic influence.

CONCLUSIONS

This study explores the public health impacts of aircraft noise in the context of rising global air traffic. The findings indicate that long-term exposure contributes to sleep disturbances, aggravates cardiovascular and mental health conditions, and impairs cognitive development, particularly among children residing near airports. Through bibliometric analysis, the study identifies emerging research trends, influential publications, and key methodologies, underscoring the importance of interdisciplinary approaches in addressing airport noise challenges. It calls for the implementation of advanced, customized noise management strategies tailored to the specific characteristics of airports and surrounding communities. The study provides practical recommendations for policymakers, researchers, and industry stakeholders to adopt measures that protect public health and promote sustainable aviation development.

Availability of Data and Materials

The data supporting the findings of this study are publicly available. All datasets generated or analyzed during the study are available from the corresponding author upon reasonable request. Relevant materials, including the research code and detailed methods, are available in the supplementary files or upon request to the author.

Author Contributions

TianLun He: conceptualization, methodology, investigation, writing − original draft;

JiaYu Hou: data curation, software, validation;

Xiang Guo: conceptualization, funding acquisition;

Da Chen: resources, funding acquisition, writing review.

Ethics Approval and Consent to Participate

This paper merely conducts a statistical analysis of the literature data from the Web of Science, without involving any patient information. Therefore, there are no related ethical issues.

Conflicts of Interest

The authors have no conflicts of interest to declare.

Acknowledgment

Not applicable.

Funding Statement

The authors received no financial support for the research.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data supporting the findings of this study are publicly available. All datasets generated or analyzed during the study are available from the corresponding author upon reasonable request. Relevant materials, including the research code and detailed methods, are available in the supplementary files or upon request to the author.

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