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. 2025 Nov 7;104(45):e45561. doi: 10.1097/MD.0000000000045561

Status and trends in research of noise exposure and metabolic syndrome over the past 2 decades in global, 2004 to 2024: A bibliometric analysis

Yanna Le a, Qingyun Xu a, Feiqi Xu c, Jing Li b,*
PMCID: PMC12599705  PMID: 41204526

Abstract

Background:

The non-auditory health damage caused by noise exposure has received increasing attention. This study aimed to identify the patterns and prominent themes in research on noise exposure and metabolic syndrome (MetS) through bibliometric analysis, thereby facilitating the exploration of innovative research directions.

Methods:

A comprehensive literature review of studies on noise exposure and MetS from 2004 to 2024 was conducted using the Web of Science Core Collection database. Information, including “all recorded and cited references,” was extracted. CiteSpace and VOSviewer were employed for bibliometric analysis of relevant publications, covering aspects such as countries, institutions, authors, journals, citations, and keywords.

Results:

Since 2004, studies related to noise exposure and MetS had shown an upward trend. Our bibliometric analysis identified 1023 studies published before 2024. The United States is a leading force in the field of noise exposure and MetS research, showing the highest number of publications, with the England and Germany also making significant contributions. Cooperation among European institutions forms a strong pillar in this field and has had an extraordinary impact. NOISE HEALTH and ENVIRONMENTAL RESEARC emerged as the most prolific journals, while the EUROPEAN HEART JOURNAL ranked among the top 10 most-influential journals. The German researcher Munzel Thomas had a notable influence. Jonannes Gutenberg University of Main was the institution with the highest number of publications and citations. Widely cited papers and popular keyword clusters reflected the status and trends in noise exposure and MetS research.

Conclusions:

The summarized research focuses include experimental and epidemiological studies on the effects of noise on blood pressure, blood glucose, and blood lipids, especially the special effects of traffic noise and occupational noise. Future research should concentrate on the effects of noise on lipid metabolism, the combined effects of noise and environmental pollutants, and the mechanism of MetS induced by noise. It is hypothesized that targeting gene loci associated with noise-induced MetS could be an innovative direction in this field.

Keywords: bibliometric analysis, future prospect, metabolic syndrome, noise exposure, research trend

1. Introduction

Noise is ubiquitous in daily life and plays a key role in environmental factors. In addition to noise-induced hearing loss, the non-auditory health damage caused by noise has also raised significant concerns.[1,2] It has been documented that noise exposure posed a threat to human health by causing a range of problems such as cardiovascular disease, atherosclerosis, mental disorders, sleep disorders, and multiple organ damage.[3–7]

Metabolic syndrome (MetS) is characterized by a range of metabolic disorders (elevated blood pressure, impaired fasting blood sugar, abnormal cholesterol and/or triglyceride levels, and abdominal obesity) and is a serious pathological condition.[8,9] According to the International Diabetes Federation, the global prevalence of MetS is about 25% based on race, age, and gender factors.[10] In addition, MetS increases health utilization and healthcare spending by an estimated 1.2 to 2.2 times, imposing a substantial economic burden.[2,11] In this context, it is urgent to intensify research on modifiable risk factors for MetS. In recent years, a number of large-scale epidemiological studies have indicated that noise exposure increases the risks of various phenotypes for MetS.[12–14] Therefore, it is necessary to visualize relevant study information to help raise awareness of the increased risk of MetS associated with noise.

Bibliometric analysis is a quantitative method that applies mathematical and statistical principles to describe the state of scientific research on a given topic by analyzing publications, which helps to gain insight into the frontiers and trends of research of interest.[15,16] It is also useful for tracking research growth and comparing the contributions of different countries, institutions, authors, and journals in specific fields.[17]

To date, the research trends and prospects regarding the relationship between noise exposure and metabolic syndrome remain unclear. To fill this gap, we conducted a bibliometrics analysis using the above-mentioned tools to better understand the complex relationship between noise and MetS, providing direction for future research in this field.

2. Methods

2.1. Data sources and search strategies utilized

The study extensively searched for studies related to noise exposure and MetS from 2004 to 2024. The Web of Science Core Collection database (WoSCC) was used to ensure the authority and impact of publications.[18] With an advanced search strategy, use the following parameters: Title = (noise) AND Topic = ((Mets) OR (metabolic syndrome) OR (obesity) OR (overweight) OR (triglycerides) OR (HDL-c) OR (cholesterol*) OR (hypertension) OR (blood pressure) OR (hyperglycemia) OR (hyperglycemia) OR (diabetes) [Topic]). A total of 1023 studies (article: 778; review: 110) published between 2004 and 2024 were included.

2.2. Bibliometric analysis

CiteSpace is a Java-based application for data analysis and visualization and is a unique and influential application software in the field of information visualization analysis.[19] Besides, WOSviewer supports researchers in revealing the knowledge base, research direction, and development trend of a specific subject field by analyzing citation relationships and co-occurrence keywords in the literature.[20] In the present study, we adopted 6.4.R1, 64-bit version of CiteSpace software and 1.6.20 version of WOSviewer to visually analyze the country, institution, journal, authors, keywords, and citation relationships of the literatures.

3. Results

3.1. Analysis of the distribution and trend in publication outputs

Annual publications from 2004 to 2022, a total of 1023 relevant publications were retrieved through WoSCC. These publications were distributed in 467 academic journals, mainly articles (76.1%) and reviews (10.8%). The top 10 most-influential articles were listed in Table 1. Despite slight fluctuations, there has been an overall upward trend in the number of publications over the past 20 years (Fig. 1). In 1998, Griefahn and Kotseva et al, proposed noise exposure as a risk factor for hypertension.[21,22] Since then, until 2006, the study of noise exposure and MetS was still in its embryonic stage, and the output of publications was low. The number of publications increased steadily between 2006 and 2013. From 2014 to 2024, the number of publications presented a fluctuating rise, peaking in 2022 at 89. During this period, the number of relevant publications accounted for 73.1% of the publications in the last 20 years. Therefore, the relationship between noise exposure and MetS is still a promising hot topic.

Table 1.

The top 10 most-influential articles with the most citation.

Ranking Title Citation Journal First author Year
1 Auditory and non-auditory effects of noise on health 1336 LANCET Basner, Mathias 2014
2 Cardiovascular effects of environmental noise exposure 484 EUROPEAN HEART JOURNAL Muenzel, Thomas 2014
3 Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome 408 MBIO Sze, Marc A. 2016
4 Traffic noise and risk of myocardial infarction 393 EPIDEMIOLOGY Babisch, WF 2005
5 WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Cardiovascular and Metabolic Effects: A Summary 389 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH van Kempen, Elise 2018
6 WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Effects on Sleep 348 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH Basner, Mathias 2018
7 Hypertension and exposure to noise near airports: the HYENA study 326 ENVIRONMENTAL HEALTH PERSPECTIVES Jarup, Lars 2008
8 The quantitative relationship between road traffic noise and hypertension: a meta-analysis 318 JOURNAL OF HYPERTENSION van Kempen 2012
9 Environmental Noise and the Cardiovascular System 295 JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY Muenzel, Thomas 2018
10 Long-Term Exposure to Road Traffic Noise and Incident Diabetes: A Cohort Study 264 ENVIRONMENTAL HEALTH PERSPECTIVES Sorensen, Mette 2013
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Figure 1.

Figure 1.

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Annual and cumulative growth trend of all publications associated with noise exposure and metabolic syndrome.

3.2. Analysis of leading country

Publications from Taiwan are included under China. Table 2 listed the top 10 countries that have contributed to noise exposure and MetS over the past 2 decades. Notably, the United States (USA) led the way with 176 publications, accounting for 17.2% of total publications, with 7456 cumulative citations, an average of 14.6 citations per paper, and an H-index of 40. China followed with 166 publications (16.2%) and 2424 citations, with an average of 14.6 citations per paper and an H-index of 30. Germany ranked 3rd, with 155 published papers (15.2%) and 9529 citations, an average of 61.5 citations per paper, with an H-index of 47. Although Germany has fewer publications than USA and China, it exceeds the 2 countries in terms of total citations and citations per paper, indicating that Germany has a higher influence in this field. Figure 2 shows the annual production trends for the 3 most productive countries from 2004 to 2024, along with a visual map of international cooperation. It is worth noting that European countries have formed strong cooperation, laying the cornerstone of international cooperation pattern.

Table 2.

Top 10 countries contributing the most to publications.

Ranking Countries Publications Citation Average citation H-index Year (start of research)
1 The United States 176 7456 42.4 40 2004
2 People’s Republic of China 166 2424 14.6 30 2011
3 Germany 155 9529 61.5 47 2004
4 England 90 5515 61.3 39 2004
5 Sweden 64 3778 59.0 32 2005
6 Netherlands 62 6027 97.2 41 2004
7 Switzerland 56 4401 78.6 31 2009
8 Canada 54 2154 39.9 25 2005
9 Denmark 48 2995 62.4 26 2009
10 Iran 46 502 10.9 13 2009
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Figure 2.

Figure 2.

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Contribution of different countries to noise exposure and metabolic syndrome-related studies. (A) Annual trends in the number of publications of the top 3 countries. (B) Cooperation chart of all countries (number of publications ≥ 5).

3.3. Analysis of major institutions

Over the past 20 years, solid collaborations have also emerged between different institutions, providing valuable insights into the academic dynamics for noise exposure and MetS. As shown in Table 3, Johannes Gutenberg University of Mainz was identified as the institution with the most publications, with 58 publications, a total of 3278 citations, an average citations of 56.5, and an H value of 24. The Karolinska Institutet and the German Centre for Cardiovascular Research followed, with 49 (citation: 3157, average citation: 64.4, H-index: 29) and 42 (citation: 2059, average citation: 49.0, H-index: 21) publications, respectively. Among the top 10 institutions, KAROLINSKA INSTITUTET presented a high H value, demonstrating its authority in this field. From Figure 3 for top 20 colleges and universities of partnership and its time distribution can be seen that the European institutions of the dominant cooperation have already formed the core architecture of cooperation, exerting a considerable influence.

Table 3.

Top 10 institutions contributing the most to publications.

Ranking Institutions Publications Citation Average citation H-index Year (start of research)
1 Johannes Gutenberg
University of Mainz		 58 3278 56.5 24 2018
2 Karolinska institute 49 3157 64.4 29 2005
3 German Centre for Cardiovascular 42 2059 49.0 21 2017
4 University of Basel 38 2524 66.4 25 2010
5 Imperial College London 37 2302 62.2 23 2005
6 Swiss Tropical Public Health Institute 36 2508 69.7 25 2010
7 Netherlands National Institute for Public Health and the Environment 32 3056 95.5 24 2005
8 Danish Cancer Society 31 2745 88.6 23 2011
9 Aarhus University 30 1634 54.5 15 2011
10 University of London 28 2812 100.4 19 2012
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Figure 3.

Figure 3.

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Contribution of different institutions to noise exposure and metabolic syndrome-related studies. (A) Collaboration chart of the top 20 institutions by publication volume. (B) Collaboration map of all agencies (number of publications ≥ 5) based on timeline.

3.4. Analysis of active author

Table 4 listed the top 10 authors based on the number of publications on noise exposure and MetS. Munzel Thomas led the way with a large number of publications (n = 52) and an H-index of 24. Daiber Andreas and Hahad Omar were in second and third place with 47 and 36 papers. It was worth noting that Babisc 29 publications have an average citation count of 146.2, far exceeding that of other authors, demonstrating extraordinary influence.

Table 4.

Top 10 authors who contributed the most publications.

Ranking Authors Publications Citation Average citation H-index Year (start of research)
1 Munzel, Thomas 52 3168 60.9 24 2018
2 Daiber, Andreas 47 2105 44.8 21 2018
3 Hahad, Omar 36 1074 29.8 17 2019
4 Pershagen, Goran 35 2694 77.0 23 2009
5 Sorensen, Mette 33 2749 83.3 23 2016
6 Babisch, W. 29 4240 146.2 22 2008
7 Steven, Sebastian 23 1303 56.7 15 2018
8 Hansell, Anna L 22 1408 64.0 16 2013
9 Chang, Ta-Yuan 22 670 30.5 16 2009
10 Oelze, Matthias 21 847 40.3 13 2020
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3.5. Analysis of noteworthy journals and draw a dual-map overlay

Among the 467 academic journals that published research articles on noise exposure and MetS, NOISE HEALTH (N = 60, average citation = 29.0, impact factor [IF] = 1.31) and ENVIRONMENTAL RESEARCH (N = 46, average citation = 36.6, IF = 7.13) had the highest number of publications (Table 5). Remarkably, although the JOURNAL EUROPEAN HEART JOURNAL had only 22 publications, its analysis showed an extremely high citation per article of 108.09, which is an influential journal with an IF of 32.24. In addition, the annual publication volume of the top 10 journals was analyzed to better understand their annual publication trends (Fig. 4A). A co-citation analysis of the 20 most cited journals was performed and visualized by CiteSpace (Fig. 4B).

Table 5.

Top 10 journals with the most publications regarding noise exposure and metabolic syndrome.

Ranking Journals Publications Citation Average citation H-index IF (2024) JCR (2024) Country
1 NOISE HEALTH 60 1741 29.0 23 1.31 Q3 ENGLAND
2 ENVIRONMENTAL RESEARCH 46 1682 36.6 25 7.13 Q1 AMERICA
3 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 44 2011 45.7 20 / / NETHERLANDS
4 SCIENCE OF THE TOTAL ENVIRONMENT 33 1470 44.6 21 5.21 Q1 NETHERLANDS
5 ENVIRONMENT INTERNATIONAL 32 1484 46.4 24 8.92 Q1 AMERICA
6 EPIDEMIOLOGY 23 1063 46.2 7 3.77 Q1 AMERICA
7 ENVIRONMENTAL HEALTH PERSPECTIVES 22 2168 98.6 18 8.96 Q1 AMERICA
8 EUROPEAN HEART JOURNAL 22 2378 108.1 15 32.24 Q1 ENGLAND
9 OCCUPATIONAL AND ENVIRONMENTAL MEDICINE 20 1192 59.6 16 2.88 Q1 ENGLAND
10 JOURNAL OF HYPERTENSION 17 415 24.4 6 3.64 Q1 AMERICA
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IF = impact factor, JCR = journal citation reports.

Figure 4.

Figure 4.

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Analysis of published and cited journals of noise exposure and metabolic syndrome-related studies. (A) Annual publication trends of the top 10 journals. (B) Visualization of the co-citation analysis network of top 20 journals using CiteSpace software. A node represents a journal, and the size of the node and label is positively correlated with the number of citations. (C) A dual-map overlay drawn by CiteSpace software. On the left of the line are the published journals of noise exposure and metabolic syndrome-related studies, and on the right of the line are the cited journals. Different colored lines indicate that the journal has a citation relationship. The disciplines of journals have been enlarged on either side of the bold lines to present the most important journal disciplines.

The journal’s dual-map overlay revealed the overall scientific contribution.[23] In this representation, each point on the map represents a journal, with the network of citing journals on the left and the network of cited journals on the right. The connecting lines between the left and right sides of the map represented citation relationships between journals, and the thick lines represent strong knowledge flows within the cluster. The size of the ellipse represented the number of authors, while the width of the ellipse represented the number of published works. As shown in Figure 4C, the cited papers are mainly from journals related to health/ nursing/ medicine and psychology/ environmental health/ social sciences.

3.6. Analysis of reference co-citation

Using CiteSpace software, 14 clusters of co-cited references related to noise exposure and MetS were generated, revealing different research focuses and thematic bases within the field.[24] The modularity Q value of the network was 0.828 and the average profile score was 0.950, which indicated that the clustering reliability was high.[25] The cluster with the most cited references was “annoyance sleep disturbance,” followed by “community noise” (Fig. 5A). A timeline view was generated to observe the distribution of these clusters at different time points (Fig. 5B). The top 25 references associated with the strongest citation bursts have been compiled. As presented in Figure 5C, the strongest reference for citation bursts since 2008 comes from Lars Jarup 2008 paper entitled “Hypertension and exposure to noise near airports: the HYENA study.”[26] This study was an early recognition for the adverse effects of traffic noise on blood pressure and found a significant dose–response relationship between noise intensity and hypertension, laying the foundation for further research on the association between noise exposure and MetS.

Figure 5.

Figure 5.

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Bibliometric analysis of co-cited references associated with noise exposure and metabolic syndrome-related studies. (A) 13 clusters of co-citations distinguished by CiteSpace. Different clusters appear in different colors; the co-citations of the same cluster have high homogeneity. (B) A timeline view of 13 clusters drawn by CiteSpace software. (C) Analysis of the top 25 references to the strongest bursts using CiteSpace software. The higher the value of strength, the stronger the influence.

3.7. Analysis of keyword

Keyword co-occurrence analysis can effectively reveal the popular hot topics in this field. A visual project density map was constructed by extracting keywords from 1032 publications, with each keyword appearing at least 5 times (Fig. 6A). The brightness of the color indicates the keyword frequency, the brighter the color indicates the higher the frequency, and the darker the color indicates the lower the frequency. Notably, “noise” was the most common author keyword and had a significant impact on other keywords (number of occurrences: 236; TLS: 458). Figure 6B depicteed the temporal distribution of keywords and its 11 clusters, with the colored area representing the keyword frequency. Figure 6C depicted the top 15 author keywords with the highest co-occurrence frequency.

Figure 6.

Figure 6.

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Co-occurrence analysis of keywords associated with noise exposure and metabolic syndrome. (A) Author keyword co-occurrence density map drawn by VOSviewer (frequency of ≥ 5 times). The brighter the color, the more the co-occurrence times. (B) Landscape view of keywords. CiteSpace software divided the keywords into 13 clusters. (C) The top 10 author keywords with the highest frequency. (D) Analysis of the top 25 keywords to the strongest outbreaks using CiteSpace software. The higher the value of strength, the stronger the influence.

Burst keyword analysis revealed large changes in keywords over a short period of time to detect cutting-edge and dynamic trends in the field (Fig. 6D). Among the top 25 keywords with high burst intensity in the study filed, the strongest burst keyword was “blood pressure,” and the outbreak intensity reached 13.86. The keyword with the longest outburst was “myocardial infarction,” which lasted 8 years. Notably, “oxidative stress,” “endothelial function,” “heart rate variability,”” risk factors “, “adults,” “induced hearing loss” and “noise exposure” have persisted until now and may remain hot topics for future research.

4. Discussion

4.1. General information on noise exposure and MetS

This study explored the research trajectories of noise exposure and MetS over the past 2 decades through a bibliometric analysis. Analysis of the annual number of publications shows a significant increase, especially since 2014. This upward trend may be attributed to global economic growth, improved living standards, and enhanced public awareness of health-related issues. Analysis of collaborative networks between countries, institutions, and authors showed that the USA is a major contributor to the field of noise exposure and MetS research, exhibiting the highest number of publications, with significant contributions from England and Germany. It is worth noting that cooperation between European institutions forms a strong backbone of the field and has had an extraordinary impact. Despite the staggering number of relevant publications in China, its average citation and H-index were low, and there was less cooperation between China and other countries, which reminds China of the need to increase the quality of research results and strengthen cooperation between cross-national institutions.

However, from a global perspective, research in this area is clearly unbalanced, concentrated in developed countries such as USA and Europe, while many developing and low-income countries have conducted relatively few studies. Due to industrial structure and noise governance capabilities, urban residents in some low- or middle-income countries may be exposed to noise levels well above international and national health guidelines.[27,28] For example, a study in Delhi, India, one of the most polluted cities in the world, simulated cyclists’ noise exposure and after an hour of riding in an area with moderate noise pollution predictions, the noise dose on major roads hit 49.0% of the reference dose.[29] In the Greater Accra metropolitan area in Africa, predictive modeling by researchers revealed that nearly the entire population lives in areas where noise surpasses the WHO’s road traffic noise guidelines.[30] Mohammad Reza Monazzam et al, through a cross-sectional study in Tehran, Iran, showed that 46.0% of the population was exposed to sound levels above the standard daytime level, and 84.6% to levels above the standard nighttime limit.[31]

Given industrial development and productivity improvements, noise pollution posed a significant challenge to socioeconomic development and healthcare systems. As a serious pathological state, MetS is an important risk factor for cardiovascular disease, diabetes, stroke, and even cancer.[32–34] Therefore, it is urgent for low- or middle-income country and regions to intensify research efforts, actively participate in international cooperation and exchange, and contribute more to the research and prevention of noise exposure and MetS.

4.2. Research hotspot on noise exposure and MetS

Based on 13 clusters mapped by keyword co-occurrence analysis, combining high-frequency keywords and Burst keyword trend analysis, we summarize the research hotspots in this field as follows.

First, with the rapid economic development and the popularity of advanced transportation such as aircraft and high-speed rail, the impact of noise on health has received more and more attention. Therefore, experimental and epidemiological studies on the impact of traffic noise on MetS and other related diseases have become a hot spot. A study based on UK Biobank with 502,651 individuals aged 40 to 69 years showed evidence of long-term exposure to road traffic noise above 65 dB and elevated levels of systolic and diastolic blood pressure, triglycerides, and glycated hemoglobin.[35] Noemie Letellier and Mette Sørensen et al based on epidemiological studies found that participants chronically exposed to high traffic noise had significantly increased levels of insulin resistance and a higher risk of type 2 diabetes.[36,37] Besides, a study used C57BL/6 mice with a diabetic model to aircraft noise with an average sound pressure of 72 dB(A) for 44 consecutive days and found that the noise reduced insulin secretion in all diabetic models, while the noise increased blood pressure and exacerbated diabetes-induced endothelial dysfunction in the aorta, mesentery, and cerebral arterioles.[38] All in all, the recent 5 years of research on traffic noise and MetS have provided crucial scientific evidence in this field.

Second, among the harmful noises, occupational noise occupies a crucial position. In 2016, according to the GBD Occupational Risk Factors Collaborators, the total disdisability adjusted life year of occupational noise was 7,108,277, and the total population attribution score (based on disdisability adjusted life year) was 19.6%, imposing a significant disease burden.[39] Recently, the effects of occupational noise on noise-induced hearing loss and non-auditory diseases such as MetS have received increasing attention from researchers. One study demonstrated that high noise exposure was associated with a significantly increased risk of hypertension (adjusted OR = 1.59) and hearing loss (adjusted OR = 1.28) compared with low noise exposure, especially in the 30 to 45-year-old age group and among male workers.[40] In addition, several researchers observed a linear positive dose–response relationship between occupational noise exposure and the prevalence of MetS and hearing loss in Chinese workers, with evidence of a significant association between hearing loss and the risk of MetS in subgroup analyses.[41,42] Given the characteristics of high-exposure and easy-intervention among workers, it is more and more practical to study the auditory and non-auditory health effects caused by occupational noise.

Third, based on epidemiological studies, researchers have begun to explore the potential mechanisms of MetS and related diseases in noise. In recent years, it has become a hot topic to explore the biological mechanism of MetS caused by noise through inducing endothelial dysfunction, oxidative stress, and inflammation. On one hand, noise is associated with oxidative stress-induced endothelial dysfunction (mainly caused by phagocytic NADPH oxidase and coupled nitric oxide synthase, as well as increased inflammation caused by immune cell infiltration), in which NADPH oxidase and heme oxidase-1 play a crucial role.[43,44] Long-term effects of these factors may lead to elevated blood pressure, insulin disorders, dyslipidemia and other MetS phenotypes.[45–47] On the other hand, overactivation of the hypothalamic–pituitary–adrenal and sympathetic-adrenal axes may lead to the release of noise-induced stress hormones, metabolic disorders promote the secretion of the adrenal hormone cortisol, which in particular may inhibit insulin secretion from islets and reduce insulin sensitivity in skeletal muscle, liver and adipose tissue.[48] It was noteworthy that the physiopathological mechanism of noise on MetS has not been clearly defined, and an increasing number of researchers are committed to carrying out mechanism-based studies.

4.3. Future prospect

In light of the research hotspots in this field, it is proposed that future research could focus on the following 4 aspects. First, several studies in recent years have found a potential association between noise and lipid metabolism in the population, a topic that has been lacking in this field.[49,50] Therefore, future epidemiological and experimental studies can further investigate the impact of noise on lipid metabolism. Second, air pollutants and noise often co-exist, and it is of practical interest to explore the combined effects of air pollutants and noise on individuals, especially in the workplace. Third, the mechanism of noise exposure and MetS remains unclear, and there may be other potential pathways besides the oxidative stress and endothelial dysfunction. Exploring the mechanism pathway by which noise causes MetS and identifying intervention targets will bring significant clinical value. Fourth, there is a lack of genotypic studies related to noise-induced MetS. Further excavation for the susceptibility loci of noise-induced MetS will help focus follow-up and intervention on high-risk populations, which is of great public health significance for preventing noise-induced MetS.

4.4. Limitations

However, its limitations should not be ignored. Firstly, current software limitations impede cross-database analysis, restricting this study to the WoSCC for literature screening. This increases the risk of overlooking relevant literature. Secondly, only English-language literature was retrieved using a specific search string, inevitably introducing language-related biases. Nevertheless, it is nearly impossible to include all relevant studies. Thirdly, search engines have inconsistent and unsatisfactory search features, limited coverage, and produce inconsistent and unreliable search results. Despite these limitations, this bibliometric analysis can still guide researchers in studying the hotspots and emerging trends related to noise and MetS.

5. Conclusion

In summary, the current study provides a quantitative and qualitative bibliometrics analysis of the literature on noise and MetS. The summarized research hotspots include experimental studies and epidemiological studies on the effects of noise on blood pressure, glucose metabolism and lipid metabolism, especially the special effects of traffic noise and occupational noise. In addition, collaboration between countries, institutions, and authors needs to be strengthened, especially in low- or middle-income countries and regions. In the future, research emphasis can be shifted towards the effects of noise on lipid metabolism, the combined effects of noise and environmental pollutants, and the mechanism through which noise causes MetS. It is hypothesized that research on susceptibility loci related to noise-induced MetS could be an innovative direction in this field.

Acknowledgments

The authors want to thank CiteSpace and VOSviewer for free access by researchers.

Author contributions

Conceptualization: Yanna Le, Feiqi Xu, Jing Li.

Data curation: Yanna Le, Qingyun Xu, Jing Li.

Funding acquisition: Jing Li.

Investigation: Yanna Le.

Methodology: Yanna Le, Qingyun Xu, Jing Li.

Resources: Qingyun Xu, Feiqi Xu.

Software: Yanna Le, Qingyun Xu, Feiqi Xu.

Supervision: Jing Li.

Validation: Yanna Le, Qingyun Xu.

Writing – original draft: Yanna Le, Qingyun Xu, Feiqi Xu.

Writing – review & editing: Yanna Le, Jing Li.

Abbreviations:

IF
impact factor
MetS
metabolic syndrome
USA
the United States
WoSCC
Web of Science Core Collection database.

This study was supported by the National Natural Science Foundation of China (grant: 81900921), the Director's Foundation of Hangzhou Hospital for Prevention and Treatment of Occupational Disease (grant: 2025HZFKY3).

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

How to cite this article: Le Y, Xu Q, Xu F, Li J. Status and trends in research of noise exposure and metabolic syndrome over the past 2 decades in global, 2004 to 2024: A bibliometric analysis. Medicine 2025;104:45(e45561).

YL and QX contributed to this article equally.

Contributor Information

Yanna Le, Email: LYNhzy@163.com.

Qingyun Xu, Email: xufeiqiqq@163.com.

Feiqi Xu, Email: xufeiqiqq@163.com.

References

  • [1].Basner M, Babisch W, Davis A, et al. Auditory and non-auditory effects of noise on health. Lancet. 2014;383:1325–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Chong KS, Chang Y-H, Yang C-T, Chou C-K, Ou H-T, Kuo S. Longitudinal economic burden of incident complications among metabolic syndrome populations. Cardiovasc Diabetol. 2024;23:246. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [3].Münzel T, Molitor M, Kuntic M, et al. Transportation noise pollution and cardiovascular health. Circ Res. 2024;134:1113–35. [DOI] [PubMed] [Google Scholar]
  • [4].Ritz B, Yu Y. Noise exposure and dementia: a rising concern in ageing populations. BMJ. 2021;374:n2120. [DOI] [PubMed] [Google Scholar]
  • [5].Smith MG, Cordoza M, Basner M. Environmental noise and effects on sleep: an update to the WHO systematic review and meta-analysis. Environ Health Perspect. 2022;130:76001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Yang L, Gutierrez DE, Guthrie OW. Systemic health effects of noise exposure. J Toxicol Environ Health B Crit Rev. 2024;27:21–54. [DOI] [PubMed] [Google Scholar]
  • [7].Kälsch H, Hennig F, Moebus S, et al. Are air pollution and traffic noise independently associated with atherosclerosis: the Heinz Nixdorf Recall Study. Eur Heart J. 2014;35:853–60. [DOI] [PubMed] [Google Scholar]
  • [8].Alberti KG, Zimmet P, Shaw J. The metabolic syndrome – a new worldwide definition. Lancet. 2005;366:1059–62. [DOI] [PubMed] [Google Scholar]
  • [9].Grundy SM, Cleeman JI, Daniels SR, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112:2735–52. [DOI] [PubMed] [Google Scholar]
  • [10].O’Neill S, O’Driscoll L. Metabolic syndrome: a closer look at the growing epidemic and its associated pathologies. Obes Rev. 2015;16:1–12. [DOI] [PubMed] [Google Scholar]
  • [11].Boudreau DM, Malone DC, Raebel MA, et al. Health care utilization and costs by metabolic syndrome risk factors. Metab Syndr Relat Disord. 2009;7:305–14. [DOI] [PubMed] [Google Scholar]
  • [12].Chen Z, Li W, Zhang H, et al. Association of noise exposure, plasma microRNAs with metabolic syndrome and its components among Chinese adults. Sci Total Environ. 2024;921:171123. [DOI] [PubMed] [Google Scholar]
  • [13].Khosravipour M, Abdollahzad H, Khosravi F, Rezaei M, Mohammadi Sarableh H, Moradi Z. The effects of exposure to different noise frequencies on the prevalence of metabolic syndrome. Eur J Prev Cardiol. 2020;27:1451–4. [DOI] [PubMed] [Google Scholar]
  • [14].Yu Y, Paul K, Arah OA, et al. Air pollution, noise exposure, and metabolic syndrome - a cohort study in elderly Mexican-Americans in Sacramento area. Environ Int. 2020;134:105269. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Thompson DF, Walker CK. A descriptive and historical review of bibliometrics with applications to medical sciences. Pharmacotherapy. 2015;35:551–9. [DOI] [PubMed] [Google Scholar]
  • [16].Xu HQ, Chung CC, Yu C. Visualizing research trends on culture neuroscience (2008–2021): a bibliometric analysis. Front Psychol. 2022;13:884929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].Ma D, Yang B, Guan B, et al. A bibliometric analysis of pyroptosis from 2001 to 2021. Front Immunol. 2021;12:731933. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Zhang L, Zheng H, Jiang S-T, et al. Worldwide research trends on tumor burden and immunotherapy: a bibliometric analysis. Int J Surg. 2024;110:1699–710. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [19].Chen C. Searching for intellectual turning points: progressive knowledge domain visualization. Proc Natl Acad Sci U S A. 2004;101:5303–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Bao Y, Deng Z, Wang Y, et al. Using machine learning and natural language processing to review and classify the medical literature on cancer susceptibility genes. JCO Clin Cancer Inform. 2019;3:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Griefahn B. Noise as a potential health hazard. Nervenheilkunde. 1998;17:23–9. [Google Scholar]
  • [22].Kotseva KP. Occupational noise exposure as a risk factor for arterial hypertension. J Hypertens. 1998;16:S263–S263. [Google Scholar]
  • [23].Chen CM, Leydesdorff L. Patterns of connections and movements in dual-map overlays: a new method of publication portfolio analysis. J Assoc Inform Sci Technol. 2014;65:334–51. [Google Scholar]
  • [24].González-Alcaide G, Calafat A, Becoña E, Thijs B, Glänzel W. Co-citation analysis of articles published in substance abuse journals: intellectual structure and research fields (2001-2012). J Stud Alcohol Drugs. 2016;77:710–22. [DOI] [PubMed] [Google Scholar]
  • [25].Du Z, Wang Z, Guo F, Wang T. Dynamic structures and emerging trends in the management of major trauma: a bibliometric analysis of publications between 2012 and 2021. Front Public Health. 2022;10:1017817. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Jarup L, Babisch W, Houthuijs D, et al. Hypertension and exposure to noise near airports: the HYENA study. Environ Health Perspect. 2008;116:329–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [27].Chen Y, Hansell AL, Clark SN, Cai YS. Environmental noise and health in low–middle-income-countries: a systematic review of epidemiological evidence. Environ Pollut. 2023;316:120605. [DOI] [PubMed] [Google Scholar]
  • [28].Evans GW, Kantrowitz E. Socioeconomic status and health: the potential role of environmental risk exposure. Annu Rev Public Health. 2002;23:303–31. [DOI] [PubMed] [Google Scholar]
  • [29].Apparicio P, Gelb J, Jarry V, Lesage-Mann E. Cycling in one of the most polluted cities in the world: exposure to noise and air pollution and potential adverse health impacts in Delhi. Int J Health Geogr. 2021;20:18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].Clark SN, Alli AS, Ezzati M, et al. Spatial modelling and inequalities of environmental noise in Accra, Ghana. Environ Res. 2022;214:113932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Monazzam MR, Shamsipour M, Zaredar N, Bayat R. Evaluation of the relationship between psychological distress and sleep problems with annoyance caused by exposure to environmental noise in the adult population of Tehran Metropolitan City, Iran. J Environ Health Sci Eng. 2022;20:1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2005;365:1415–28. [DOI] [PubMed] [Google Scholar]
  • [33].Mottillo S, Filion KB, Genest J, et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56:1113–32. [DOI] [PubMed] [Google Scholar]
  • [34].Esposito K, Chiodini P, Colao A, Lenzi A, Giugliano D. Metabolic syndrome and risk of cancer: a systematic review and meta-analysis. Diabetes Care. 2012;35:2402–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [35].Kupcikova Z, Fecht D, Ramakrishnan R, Clark C, Cai YS. Road traffic noise and cardiovascular disease risk factors in UK Biobank. Eur Heart J. 2021;42:2072–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [36].Letellier N, Yang J-A, Cavaillès C, et al. Aircraft and road traffic noise, insulin resistance, and diabetes: the role of neighborhood socioeconomic status in San Diego County. Environ Pollut. 2023;335:122277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Sørensen M, Hvidtfeldt UA, Poulsen AH, et al. Long-term exposure to transportation noise and risk of type 2 diabetes: a cohort study. Environ Res. 2023;217:114795. [DOI] [PubMed] [Google Scholar]
  • [38].Mihalikova D, Stamm P, Kvandova M, et al. Exposure to aircraft noise exacerbates cardiovascular and oxidative damage in three mouse models of diabetes. Eur J Prev Cardiol. 2024;32:301– 14. [DOI] [PubMed] [Google Scholar]
  • [39].Global and regional burden of disease and injury in 2016 arising from occupational exposures: a systematic analysis for the global burden of disease study 2016. Occup Environ Med. 2020;77:133– 41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Li X, Dong Q, Wang B, et al. The influence of occupational noise exposure on cardiovascular and hearing conditions among industrial workers. Sci Rep. 2019;9:11524. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [41].Jin N, Zhong HY, Yuan F, Deng HX. Positive associations between bilateral high-frequency hearing loss and hypertension risk in short-term occupational noise exposure. Biomed Environ Sci. 2021;34:992–7. [DOI] [PubMed] [Google Scholar]
  • [42].Li W, Yi G, Chen Z, et al. Association of occupational noise exposure, bilateral hearing loss with hypertension among Chinese workers. J Hypertens. 2021;39:643–50. [DOI] [PubMed] [Google Scholar]
  • [43].Münzel T, Schmidt FP, Steven S, Herzog J, Daiber A, Sørensen M. Environmental noise and the cardiovascular system. J Am Coll Cardiol. 2018;71:688–97. [DOI] [PubMed] [Google Scholar]
  • [44].Kuntic M, Kuntic I, Krishnankutty R, et al. Co-exposure to urban particulate matter and aircraft noise adversely impacts the cerebro-pulmonary-cardiovascular axis in mice. Redox Biol. 2023;59:102580. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [45].Masenga SK, Kabwe LS, Chakulya M, Kirabo A. Mechanisms of oxidative stress in metabolic syndrome. Int J Mol Sci . 2023;24:7898. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Guzik TJ, Touyz RM. Oxidative stress, inflammation, and vascular aging in hypertension. Hypertension. 2017;70:660–7. [DOI] [PubMed] [Google Scholar]
  • [47].Rains JL, Jain SK. Oxidative stress, insulin signaling, and diabetes. Free Radic Biol Med. 2011;50:567–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [48].Liu C, Li W, Chen X, et al. Dose–response association between transportation noise exposure and type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies. Diabetes Metab Res Rev. 2023;39:e3595. [DOI] [PubMed] [Google Scholar]
  • [49].Chen Z, Zhang H, Huang X, et al. Association of noise exposure with lipid metabolism among Chinese adults: mediation role of obesity indices. J Endocrinol Invest. 2025;48:245–55. [DOI] [PubMed] [Google Scholar]
  • [50].Zhang K, Jiang F, Luo H, Liu F. Occupational noise exposure and the prevalence of dyslipidemia in a cross-sectional study. BMC Public Health. 2021;21:1258. [DOI] [PMC free article] [PubMed] [Google Scholar]

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