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REVIEW article

Front. Public Health, 03 August 2023
Sec. Environmental Health and Exposome
This article is part of the Research Topic Air Pollution as a Risk Factor Affecting Human Health and Economic Costs View all 18 articles

Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men

Junjie Liu
&#x;Junjie Liu1*Yanpeng Dai&#x;Yanpeng Dai2Runqing LiRunqing Li3Jiayi YuanJiayi Yuan3Quanxian WangQuanxian Wang1Linkai WangLinkai Wang1
  • 1Henan Human Sperm Bank, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 2Department of Clinical Laboratory, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
  • 3The Neonatal Screening Center in Henan Province, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China

Background: Air pollution may impair male fertility, but it remains controversial whether air pollution affects semen quality until now.

Objectives: We undertake a meta-analysis to explore potential impacts of six pollutants exposure during the entire window (0–90 days prior to ejaculation) and critical windows (0–9, 10–14, and 70–90 days prior to ejaculation) on semen quality.

Methods: Seven databases were retrieved for original studies on the effects of six pollutants exposure for 90 days prior to ejaculation on semen quality. The search process does not limit the language and search date. We only included original studies that reported regression coefficients (β) with 95% confidence intervals (CIs). The β and 95% CIs were pooled using the DerSimonian-Laird random effect models.

Results: PM2.5 exposure was related with decreased total sperm number (10–14 lag days) and total motility (10–14, 70–90, and 0–90 lag days). PM10 exposure was related with reduced total sperm number (70–90 and 0–90 lag days) and total motility (0–90 lag days). NO2 exposure was related with reduced total sperm number (70–90 and 0–90 lag days). SO2 exposure was related with declined total motility (0–9, 10–14, 0–90 lag days) and total sperm number (0–90 lag days).

Conclusion: Air pollution affects semen quality making it necessary to limit exposure to air pollution for Chinese men. When implementing protective measures, it is necessary to consider the key period of sperm development.

Introduction

8–12% of reproductive-age couples are infertile in the world and its prevalence may be increasing (1). Male factors cause 40–50% of infertile couples (2). Total sperm number, sperm concentration, progressive and total motility are commonly adopted to evaluate male reproductive potential. Sperm quality of sperm donors in China’s Henan Province showed a decreasing trend from 2009 to b2019 (3). Although the exact cause remains unclear, air pollution might be a hazard factor for declining semen quality (4).

Particulate matter (PM) pollution included PM ≤ 10 μm (PM10) as well as PM ≤2.5 μm (PM2.5). Gaseous pollutants included sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3). Due to different economic growth levels and economic development patterns, air pollution varies greatly from place to place (59). Air pollution was serious in China due to rapid industrialization (1013). Air pollution could cause respiratory symptoms (1416), cardiovascular disease (1720), kidney disease (2123), adverse prenatal outcomes (24), and impaired neurodevelopment (25, 26). It remains controversial whether air pollution exposure during the whole sperm development window has an influence on sperm quality (2747). A meta-analysis of relevant research data is needed.

The growth period of mature sperm is approximately 90 days, including three critical windows: 0–9 days prior to ejaculation (epididymal storage), 10–14 days prior to ejaculation (development of sperm motility), and 70–90 days prior to ejaculation (spermatogenesis) (48). There are fewer studies on which stage of sperm development is most vulnerable to air pollution, but the findings remain controversial (27, 29, 33, 34, 3640, 4244, 47). A meta-analysis of relevant research data is needed.

Although there are five systematic review and meta-analyses on whether semen quality is affected by air contaminants (4953), the measured indicators of the four systematic review and meta-analyses were the mean differences and the exposure periods were not 90 days (4952). The four systematic review and meta-analyses compare semen quality between men exposed to high levels of air pollution and men exposed to low levels of air pollution and were not standardized when merging the effects of air pollution from different studies (4952). The main distinction between the reported four meta-analyses and the present work is that we have studied the association air pollution exposure during the whole 90 day period as well as the three critical windows of sperm development. A systematic review and meta-analysis by Xu et al. reported the effect of air pollution exposure during lag 0–90 days or 0–12 weeks on semen quality based on exposure-response relationships but did not report the effect of air pollution exposure during the three critical windows of sperm development (53). The included articles did not include those published in Chinese and those published recently in 2023, and subgroup or sensitivity analyses were also not performed (53). There is still no systematic review on whether semen quality is affected by air pollution exposure during the three critical windows of sperm development.

Therefore, the first meta-analysis was done for analyzing the relation of air pollution exposure during the whole and three critical windows of sperm development and sperm quality in China.

Methods

The present meta-analysis was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (54) as well as PRISMA 2020 checklist had been provided in Supplementary Materials A. This meta-analysis was registered on the PROSPERO website (No. CRD42022374712). Literature search.

We retrieved the Cochrane Library, EMBASE, Web of Science, PubMed, VIP, China National Knowledge Infrastructure (CNKI) as well as Wanfang databases for articles. The search process does not limit the language and search date. Only epidemiological observational studies published in Chinese or English would be included. The applied search words and detailed search strategies are shown in Supplementary Table S1; Supplementary Materials B, respectively. Searches were performed independently by RL and JY Disagreement was resolved by a third author (JL)

Outcomes

Outcomes included total sperm number, sperm concentration, total and progressive motility.

Inclusion and exclusion criteria

Inclusion criteria were: (a) reporting the effect of at least one air pollutant exposure during the whole window and/or critical stages of sperm development on sperm quality; (b) cross-sectional or cohort studies; (c) reporting regression coefficients (β) and 95% confidence intervals (CIs); (d) Chinese males; and (e) English and Chinese articles. The measured indicators of case-control studies were the means and standard deviations (SDs) rather than β and 95% CIs.

The following exclusion criteria were adopted: (a) animal studies, case reports, commentaries, reviews, protocols, editorials, conference abstracts, letters, or book chapters; (b) case-control studies; (c) studies in countries other than China; (d) reported shorter or longer exposure period; (e) focused on indoor air pollution; and (f) multivariate logistic regression.

Study selection

Two authors (RL and JY) conducted the literature selection independently. If any disagreement arose during the selection process, it would be resolved by discussing with the third author (JL).

Data extraction

Using a standardized form, the following information was extracted independently from eligible publications by two authors (RL and JY): publication year, first author, design of study, region, setting, research period, study subjects, size of the sample, pollutants exposure measurement, outcome, exposure period, statistical model, adjusted confounding factors, adjusted β with their corresponding 95% CIs. Through discussion with the third author (JL), any disagreement in the data extraction was resolved. The missing information of the original study was requested by contacting the corresponding author.

Quality assessment

Quality assessments of eligible publications were executed independently by two researchers (QW and LW). If there was any inconsistent opinion, it would be resolved by discussing with the third researcher (YD). The Newcastle-Ottawa Scale (NOS) checklist was adopted for evaluating the quality of retrospective as well as prospective cohort studies (55). The Joanna Briggs Institute (JBI) critical appraisal checklist was adopted for evaluating the quality of cross-sectional studies (56). Based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines (57), the certainty of evidence was started with moderate and further downgraded based on the following items: publication bias, directness, study limitations, consistency, and precision (58, 59), and upgraded for dose-response gradient, strong effect size as well as plausible confounding effect (60).

Data analyses

If the articles did not give interquartile range (IQR) values or original incremental units of pollutant exposure, we would contact the authors by email. For parts per billion (ppb) units, the following equations were used to convert to μg/m3: 1 ppb = 48/22.4 μg/m3 (O3); 1 ppb = 46/22.4 μg/m3 (NO2). It was assumed that the standard ratio of 24 h average, 8 h max, and 1 h max was 8:15:20, which was widely used for O3 conversion (6163). To improve comparability, we converted all estimates to 24-h average. The standardized increment was 10 μg/m3 in this study, otherwise it would be converted using the following formula (64, 65):

β ( standardized ) = β ( original ) × Increment ( 10 ) / Increment ( original )

Statistical analyses were conducted with Stata v12.1 (Stata Corp., United States). The β and 95% CIs were combined using the DerSimonian-Laird random effect models. Chi-squared test and I2 statistics were used to quantify the heterogeneity. Heterogeneity existed when p < 0.05 or I2 > 50% (66). In order to find sources of heterogeneity, we conducted sub-group analyses based on design of the study (cross-sectional and cohort), location (northern and southern China), and exposure assessment approaches (estimating models or monitoring station). Egger’s test as well as funnel plots were adopted for assessing publication bias. Stability of the findings was judged with the help of sensitivity analysis. p < 0.05 was statistical significance.

Results

Study characteristics

As depicted in Figure 1, 3,952 publications were retrieved from the seven databases, and 34 articles remained after duplicate literature, abstracts and titles exclusion. After reading the full article, 14 articles were further excluded and detailed exclusion reasons were given in Supplementary Table S2. The remaining 21 eligible publications were eventually included in this meta-analysis. Missing data of original articles were requested by contacting the authors via email or WeChat. Studies with missing information were excluded if multiple contacts with the corresponding author remained unanswered. Table 1 illustrates the primary characteristics of the eligible publications. Table 2 demonstrates the original incremental units, outcomes, statistical models used and adjusted confounding factors of all the eligible studies. If the increment unit of the original study was not 10 μg/m3, effect sizes were converted. The credibility of the evidence was categorized as very low or low (Supplementary Table S3).

FIGURE 1
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Figure 1. Flow diagram of literature selection.

TABLE 1
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Table 1. Characteristics of the included studies in this meta-analysis.

TABLE 2
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Table 2. Pollutants, outcomes, and statistical information of the 19 included studies.

Air pollutants and sperm quality

Six air pollutants exposure during the whole window did not affect sperm concentration (Supplementary Table S4; Figure 2). PM10, SO2, and NO2 exposure during the whole window were related with decreased total sperm number, while such association was not found for PM2.5, CO, and O3 exposure (Supplementary Table S4; Figure 2). PM2.5, PM10 as well as SO2 exposure during the entire window were negatively related with total motility, while such association was not found for other pollutants.

FIGURE 2
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Figure 2. Regression coefficients and 95% confidence intervals for the relation between six pollutants exposure during the whole window and sperm quality.

In order to find sources of heterogeneity, we conducted sub-group analyses based on design of the study (cohort and cross-sectional), location (northern China and southern China), and exposure assessment approaches (monitoring station or estimating models). The majority of sub-group results were consistent with the pooled results (Supplementary Table S5; Figure 3).

FIGURE 3
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Figure 3. Regression coefficients and 95% confidence intervals for the relation between six pollutants exposure during three critical windows and sperm quality.

During 0–9 lag days, only SO2 exposure was related with declined total motility (Supplementary Table S5; Figure 3). During 10–14 lag days, PM.2.5 exposure was adversely related with total sperm number and total motility, SO2 with total motility (Supplementary Table S5; Figure 3). During 70–90 lag days, PM10 and NO2 exposure were adversely related with total sperm number, PM2.5 with total motility (Supplementary Table S5; Figure 3).

Sensitivity analysis

In the sensitivity analyses for six pollutants exposure during the whole window and sperm quality, pooled effect sizes did not change significantly by omitting one study from each analysis, thus indicating that our findings were stable (Supplementary Table S4; Supplementary Figure S1). However, when the study of Wu et al. (40) was omitted from sensitivity analyses of PM2.5 exposure and progressive motility, a significant association disappeared (p = 0.081; Supplementary Table S4; Supplementary Figure S1A). When the study of (34) was omitted from sensitivity analyses of PM10 exposure and sperm concentration, a significant association disappeared (p = 0.119; Supplementary Table S4; Supplementary Figure S1B). When the study by Ma et al. (33) was omitted from the sensitivity analysis of O3 exposure and total motility, a significant association disappeared (p = 0.104; Supplementary Table S4; Supplementary Figure S1F).

In the sensitivity analyses of six pollutants exposure during critical windows and sperm quality, the pooled effect sizes did not change significantly by omitting one study from each analysis, thus indicating that our findings were stable. However, when the study of Ma et al. (33) was omitted from the sensitivity analyses of O3 (70–90 lag days) exposure and total motility, a significant association disappeared (p = 0.197) with heterogeneity decreasing from 51 to 0% (Supplementary Table S5).

Discussion

Summary of study results

China has a population of more than 1.4 billion and covers a land area of approximately 9.6 million km2. Due to the vast territory of China, it varies greatly in climate conditions, landforms, geography, population density, and economic development level in different regions. Based on economic development levels and climatic conditions, China is generally grouped into seven geographic regions (6769). Detailed geographic location is presented in Supplementary Figure S2. China is roughly classified as southern and northern China (7072). Distribution of southern and northern China is shown in Figure 4. As a result of the limited sample size, we performed sub-group analysis by location (northern China and southern China). Air quality is closely related with climatic conditions and economic development levels. Air quality is better in western China than in eastern China (67). Economic development levels in western and eastern regions result in different chemical compositions of pollutants (73, 74). In the eastern and central regions, industry and traffic are the primary causes of air pollution (75). Biomass burning and soil dust are the primary reasons of air pollution in the western region. Different sources of air pollution in different regions result in different toxicity, concentrations, and chemical compositions. This may explain, to some extent, the inconsistent results.

FIGURE 4
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Figure 4. Distribution of northern and southern China.

Different individual exposure assessment approaches can partially explain the controversial results. Lao et al. estimated individual exposure levels of PM2.5 using a high-resolution (1 × 1 km) spatiotemporal model (31). Zhou et al. (44) adopted the ordinary Kriging model to measure individual exposure concentrations. Some studies used the land-use random forest model (41) or inverse distance weighting model (28, 29, 32, 34, 39, 40) to assess the actual individual exposure levels. Some other studies used the averaged levels of the city-wide or the nearest monitoring station to assess actual individual pollutant exposure concentrations (27, 30, 3538, 42, 43, 45, 46).

This is the first meta-analysis to analyze potential impacts of ambient air pollution exposure during the whole window and three critical windows on semen quality in China. Sperm motility, a conventional semen parameter, is one of the common indicators of fertility assessment. Sperm motility is commonly used as one of the most important sperm functions to determine whether female partners can successfully conceive without any assisted reproductive technology (ART). Sperm motility parameters are also sensitive indicators of male reproductive toxicity (76). PM10, PM2.5 as well as SO2 exposure were adversely related with total motility during 0–90 days prior to ejaculation. PM2.5, CO as well as O3 exposure were adversely related with total sperm number during 0–90 lag days.

In order to find sources of heterogeneity, we conducted sub-group analyses based on design of the study (cohort and cross-sectional), location (northern China and southern China), and exposure assessment approaches (monitoring station or estimating models). Although subgroup analysis reduced heterogeneity to some extent, heterogeneity remained high level in some subgroups, and it was necessary to continue to explore potential sources of between-studies heterogeneity.

In addition, the possible exposure susceptibility window was also investigated. PM2.5 exposure affected total motility (10–14 and 70–90 lag days) and total sperm number (10–14 lag days). PM10 affected total sperm number (70–90 lag days). SO2 influenced total sperm number (0–9 and 10–14 lag days). NO2 affected total sperm number (70–90 lag days). The findings suggested that pollutants exposure might affect total motility and total sperm number.

Biological mechanisms

The biological mechanisms that environmental pollutant exposure may damage the development of total motility have not been elucidated. PM10, PM2.5, and O3 exposure can lead to elevated concentrations of reactive oxygen species (77, 78), which may disrupt the blood-testis barrier, detriment spermatogenesis and result in declined sperm motility (7982). PM exposure can also cause systemic inflammatory reactions by elevating tumor necrosis factor (TNF) as well as interleukin-1β (IL-1β) levels (8386). Higher concentrations of IL-1β and TNF are related with impaired total sperm motility (8789). Significant reduction in air pollutants emissions was accompanied by improvements in people’s markers of inflammatory conditions, thrombosis as well as oxidation stress (90). We hypothesized that environmental pollutant exposure would elevate oxidative stress levels and inflammatory reactions, which could lead to decreased total sperm motility. This hypothesis requires further toxicological studies to elucidate the detailed mechanism of reduced sperm motility caused by environmental pollutant exposure.

Strengths and limitations

This present meta-analysis has three advantages. First, it is the first meta-analysis to analyze whether semen quality is affected by air pollution exposure during the whole and critical windows. Second, the findings are relatively new as a result of most eligible studies being published within recent 4 years. Third, results of different original studies were difficult to compare since the exposure increment units were different in most cases. Therefore, the comparability of the results was improved by standardizing the data through transformation.

However, the present meta-analysis still has four limitations. First, a high degree of heterogeneity for some pollutants was found, which may be explained by differences in pollutant concentrations, types of air pollutants, chemical components of particulate matter, individual exposure assessment approaches, design of the study, study setting, sample size, study regions, selection bias, and adjustment confounding factors. Due to the high degree of heterogeneity, caution should be given when interpreting some pooled effects. A high degree of heterogeneity may also hinder the detection of publication bias. Second, selective bias may occur due to some of the included studies selecting patients from infertility clinics. Third, subgroup analysis by exposure assessment approaches was not performed as a result of the insufficient sample size. Fourth, the sample size is still inadequate, with only 2 articles from northern China being included. Insufficient data might lead to inescapable errors, and the original researches need to be further supplemented. Fifth, many of the included studies obtained estimates of air pollution exposure from ecological data or modeling and did not examine individual exposure to air pollution.

Conclusion

This evidence suggested that ambient air pollution could reduce semen quality in Chinese men and may even lead to infertility. For Chinese men, there is a need to reduce the duration of exposure. Further studies should be conducted to explore the possible biological mechanisms behind the findings observed in this study.

Author contributions

JL and YD proposed the idea and designed the present study, interpreted the findings, and were responsible for statistical analysis and manuscript writing. RL and JY performed literature retrieval, study selection, and data extraction. QW and LW performed the quality assessment. All authors contributed to the article and approved the submitted version.

Funding

The present study was funded by the Henan Provincial Science and Technology Research Project (No. LHGJ20190389).

Acknowledgments

We thank authors of the included eligible studies for their timely responses to our questions.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.1219340/full#supplementary-material

References

1. Inhorn, MC , and Patrizio, P . Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Hum Reprod Update. (2015) 21:411–26. doi: 10.1093/humupd/dmv016

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Odisho, AY , Nangia, AK , Katz, PP , and Smith, JF . Temporal and geospatial trends in male factor infertility with assisted reproductive technology in the United States from 1999-2010. Fertil Steril. (2018) 110:5–11. doi: 10.1016/j.fertnstert.2018.03.008

CrossRef Full Text | Google Scholar

3. Liu, J , Dai, Y , Li, Y , Yuan, E , Wang, Q , Wang, X, et al. A longitudinal study of semen quality among Chinese sperm donor candidates during the past 11 years. Sci Rep. (2020) 10:10771. doi: 10.1038/s41598-020-67707-x

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Krzastek, SC , Farhi, J , Gray, M , and Smith, RP . Impact of environmental toxin exposure on male fertility potential. Transl Androl Urol. (2020) 9:2797–813. doi: 10.21037/tau-20-685

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Jones, MR , Diez-Roux, AV , Hajat, A , Kershaw, KN , O'Neill, MS , Guallar, E, et al. Race/ethnicity, residential segregation, and exposure to ambient air pollution: the multi-ethnic study of atherosclerosis (MESA). Am J Public Health. (2014) 104:2130–7. doi: 10.2105/AJPH.2014.302135

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Su, JG , Jerrett, M , de Nazelle, A , and Wolch, J . Does exposure to air pollution in urban parks have socioeconomic, racial or ethnic gradients? Environ Res. (2011) 111:319–28. doi: 10.1016/j.envres.2011.01.002

CrossRef Full Text | Google Scholar

7. Zhang, Y , Zhang, H , Fu, Y , Wang, L , and Wang, T . Effects of industrial agglomeration and environmental regulation on urban ecological efficiency: evidence from 269 cities in China. Environ Sci Pollut Res Int. (2021) 28:66389–408. doi: 10.1007/s11356-021-15467-0

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Jiang, M , Kim, E , and Woo, Y . The relationship between economic growth and air pollution-a regional comparison between China and South Korea. Int J Environ Res Public Health. (2020) 17:17. doi: 10.3390/ijerph17082761

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Li, Y , Chiu, YH , and Lin, TY . The impact of economic growth and air pollution on public health in 31 Chinese cities. Int J Environ Res Public Health. (2019) 16:393. doi: 10.3390/ijerph16030393

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Liu, L , Yang, X , Liu, H , Wang, M , Welles, S , Márquez, S, et al. Spatial-temporal analysis of air pollution, climate change, and Total mortality in 120 cities of China, 2012-2013. Front Public Health. (2016) 4:143. doi: 10.3389/fpubh.2016.00143

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Zeng, Y , Cao, Y , Qiao, X , Seyler, BC , and Tang, Y . Air pollution reduction in China: recent success but great challenge for the future. Sci Total Environ. (2019) 663:329–37. doi: 10.1016/j.scitotenv.2019.134180

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Song, C , Wu, L , Xie, Y , He, J , Chen, X , Wang, T, et al. Air pollution in China: status and spatiotemporal variations. Environ Pollut. (2017) 227:334–47. doi: 10.1016/j.envpol.2017.04.075

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Guo, P , Umarova, AB , and Luan, Y . The spatiotemporal characteristics of the air pollutants in China from 2015 to 2019. PLoS One. (2020) 15:e0227469. doi: 10.1371/journal.pone.0227469

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Collaco, JM , Aoyama, BC , Rice, JL , and McGrath-Morrow, SA . Influences of environmental exposures on preterm lung disease. Expert Rev Respir Med. (2021) 15:1271–9. doi: 10.1080/17476348.2021.1941886

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Guan, WJ , Zheng, XY , Chung, KF , and Zhong, NS . Impact of air pollution on the burden of chronic respiratory diseases in China: time for urgent action. Lancet. (2016) 388:1939–51. doi: 10.1016/S0140-6736(16)31597-5

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Dutta, A , and Jinsart, W . Air pollution in Delhi, India: It's status and association with respiratory diseases. PLoS One. (2022) 17:e0274444. doi: 10.1371/journal.pone.0274444

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Cosselman, KE , Navas-Acien, A , and Kaufman, JD . Environmental factors in cardiovascular disease. Nat Rev Cardiol. (2015) 12:627–42. doi: 10.1038/nrcardio.2015.152

PubMed Abstract | CrossRef Full Text | Google Scholar

18. Hayes, RB , Lim, C , Zhang, Y , Cromar, K , Shao, Y , Reynolds, HR, et al. PM2.5 air pollution and cause-specific cardiovascular disease mortality. Int J Epidemiol. (2020) 49:25–35. doi: 10.1093/ije/dyz114

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Joshi, SS , Miller, MR , and Newby, DE . Air pollution and cardiovascular disease: the Paul wood lecture, British cardiovascular society 2021. Heart. (2022) 108:1267–73. doi: 10.1136/heartjnl-2021-319844

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Franklin, BA , Brook, R , and Arden Pope, C . Air pollution and cardiovascular disease. Curr Probl Cardiol. (2015) 40:207–38. doi: 10.1016/j.cpcardiol.2015.01.003

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Chen, Y , Cao, F , Xiao, JP , Fang, XY , Wang, XR , Ding, LH, et al. Emerging role of air pollution in chronic kidney disease. Environ Sci Pollut Res Int. (2021) 28:52610–24. doi: 10.1007/s11356-021-16031-6

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Xu, X , Nie, S , Ding, H , and Hou, FF . Environmental pollution and kidney diseases. Nat Rev Nephrol. (2018) 14:313–24. doi: 10.1038/nrneph.2018.11

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Okoye, OC , Carnegie, E , and Mora, L . Air pollution and chronic kidney disease risk in oil and gas-situated communities: a systematic review and Meta-analysis. Int J Public Health. (2022) 67:1604522. doi: 10.3389/ijph.2022.1604522

CrossRef Full Text | Google Scholar

24. Ghosh, R , Causey, K , Burkart, K , Wozniak, S , Cohen, A , and Brauer, M . Ambient and household PM2.5 pollution and adverse perinatal outcomes: a meta-regression and analysis of attributable global burden for 204 countries and territories. PLoS Med. (2021) 18:e1003718. doi: 10.1371/journal.pmed.1003718

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Morris, RH , Counsell, SJ , McGonnell, IM , and Thornton, C . Early life exposure to air pollution impacts neuronal and glial cell function leading to impaired neurodevelopment. BioEssays. (2021) 43:e2000288. doi: 10.1002/bies.202000288

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Levy, RJ . Carbon monoxide pollution and neurodevelopment: a public health concern. Neurotoxicol Teratol. (2015) 49:31–40. doi: 10.1016/j.ntt.2015.03.001

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Dai, X , Chen, G , Zhang, M , Mei, K , Liu, Y , Ding, C, et al. Exposure to ambient particulate matter affects semen quality: a case study in Wenzhou, China. J Androl. (2023) 11:444–55. doi: 10.1111/andr.13326

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Guan, Q , Chen, S , Wang, B , Dou, X , Lu, Y , Liang, J, et al. Effects of particulate matter exposure on semen quality: a retrospective cohort study. Ecotoxicol Environ Saf. (2020) 193:110319:110319. doi: 10.1016/j.ecoenv.2020.110319

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Huang, G , Zhang, Q , Wu, H , Wang, Q , Chen, Y , Guo, P, et al. Sperm quality and ambient air pollution exposure: a retrospective, cohort study in a southern province of China. Environ Res. (2020) 188:109756. doi: 10.1016/j.envres.2020.109756

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Huang, X , Zhang, B , Wu, L , Zhou, Y , Li, Y , Mao, X, et al. Association of Exposure to ambient fine particulate matter constituents with semen quality among men attending a fertility Center in China. Environ Sci Technol. (2019) 53:5957–65. doi: 10.1021/acs.est.8b06942

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Lao, XQ , Zhang, Z , Lau, AKH , Chan, TC , Chuang, YC , Chan, J, et al. Exposure to ambient fine particulate matter and semen quality in Taiwan. Occup Environ Med. (2018) 75:148–54. doi: 10.1136/oemed-2017-104529

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Liu, Y , Zhou, Y , Ma, J , Bao, W , Li, J , Zhou, T, et al. Inverse association between ambient Sulfur dioxide exposure and semen quality in Wuhan, China. Environmental Buyers' Guide. (2017) 51:12806–14. doi: 10.1021/acs.est.7b03289

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Ma, Y , Peng, X , Pan, Z , Hu, C , Xia, Q , Cai, G, et al. Linear and non-linear relationships between sulfur dioxide and semen quality: a longitudinal study in Anhui. China Environ Res. (2023) 216:114731. doi: 10.1016/j.envres.2022.114731

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Ma, Y , Zhang, J , Cai, G , Xia, Q , Xu, S , Hu, C, et al. Inverse association between ambient particulate matter and semen quality in Central China: evidence from a prospective cohort study of 15,112 participants. Sci Total Environ. (2022) 833:155252. doi: 10.1016/j.scitotenv.2022.155252

CrossRef Full Text | Google Scholar

35. Qiu, Y , Yang, T , Seyler, BC , Wang, X , Wang, Y , Jiang, M, et al. Ambient air pollution and male fecundity: a retrospective analysis of longitudinal data from a Chinese human sperm bank (2013-2018). Environ Res. (2020) 186:109528. doi: 10.1016/j.envres.2020.109528

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Tian, XJ , Wang, XC , Ye, B , Li, CL , Zhang, Y , and Ma, L . The effects of exposure to ozone on sperm quality in Wuhan. Zhonghua Yu Fang Yi Xue Za Zhi. (2017) 51:197–202. doi: 10.3760/cma.j.issn.0253-9624.2017.03.002

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Wang, X , Tian, X , Ye, B , Zhang, Y , Li, C , Liao, J, et al. Gaseous pollutant exposure affects semen quality in Central China: a cross-sectional study. Andrology. (2020) 8:117–24. doi: 10.1111/andr.12655

CrossRef Full Text | Google Scholar

38. Wang, XC , Tian, XJ , Ye, B , Ma, L , Zhang, Y , and Yang, J . The effect of ambient PM(10) on sperm quality in Wuhan. Zhonghua Yu Fang Yi Xue Za Zhi. (2018) 52:73–8. doi: 10.3760/cma.j.issn.0253-9624.2018.01.014

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Wu, L , Jin, L , Shi, T , Zhang, B , Zhou, Y , Zhou, T, et al. Association between ambient particulate matter exposure and semen quality in Wuhan, China. Environ Int. (2017) 98:219–28. doi: 10.1016/j.envint.2016.11.013

PubMed Abstract | CrossRef Full Text | Google Scholar

40. Wu, W , Chen, Y , Cheng, Y , Tang, Q , Pan, F , Tang, N, et al. Association between ambient particulate matter exposure and semen quality in fertile men. Environ Health. (2022) 21:16. doi: 10.1186/s12940-022-00831-5

PubMed Abstract | CrossRef Full Text | Google Scholar

41. Yu, X , Wang, Q , Wei, J , Zeng, Q , Xiao, L , Ni, H, et al. Impacts of traffic-related particulate matter pollution on semen quality: a retrospective cohort study relying on the random forest model in a megacity of South China. Sci Total Environ. (2022) 851:158387. doi: 10.1016/j.scitotenv.2022.158387

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Zhang, HT , Zhang, Z , Cao, J , Tang, WH , Zhang, HL , Hong, K, et al. Ambient ozone pollution is associated with decreased semen quality: longitudinal analysis of 8945 semen samples from 2015 to 2018 and during pollution-control period in Beijing, China. AJA. (2019) 21:501–7. doi: 10.4103/aja.aja_116_18

PubMed Abstract | CrossRef Full Text | Google Scholar

43. Zhao, Y , Zhu, Q , Lin, J , and Cai, J . Association of Exposure to particulate matter air pollution with semen quality among men in China. JAMA Netw Open. (2022) 5:e2148684. doi: 10.1001/jamanetworkopen.2021.48684

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Zhou, L , Li, L , Hao, G , Li, B , Yang, S , Wang, N, et al. Sperm mtDNA copy number, telomere length, and seminal spermatogenic cells in relation to ambient air pollution: results of a cross-sectional study in Jing-Jin-Ji region of China. J Hazard Mater. (2021) 406:124308–124308. doi: 10.1016/j.jhazmat.2020.124308

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Zhou, N , Cui, Z , Yang, S , Han, X , Chen, G , Zhou, Z, et al. Air pollution and decreased semen quality: a comparative study of Chongqing urban and rural areas. Environ Pollut (2014) 187:145–152. doi: 10.1016/j.envpol.2013.12.030

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Zhou, N , Jiang, C , Chen, Q , Yang, H , Wang, X , Zou, P, et al. Exposures to atmospheric PM10 and PM10-2.5 affect male semen quality: results of MARHCS study. Environ Sci Technol. (2018) 52:1571–81. doi: 10.1021/acs.est.7b05206

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Zhang, F , Li, H , Xu, W , Song, G , Wang, Z , Mao, X, et al. Sulfur dioxide may predominate in the adverse effects of ambient air pollutants on semen quality among the general population in Hefei, China. Sci Total Environ. (2023):165681. doi: 10.1016/j.scitotenv.2023.165681

PubMed Abstract | CrossRef Full Text | Google Scholar

48. Ing, NH , Curley, KO , Welsh, TH , Johnson, L , and Staub, C . Anatomy and Physiology of the Male Reproductive System and Potential Targets of Toxicants. Comprehensive Toxicology. Amsterdam: Elsevier; (2018). 2–63.

Google Scholar

49. Deng, Z , Chen, F , Zhang, M , Lan, L , Qiao, Z , Cui, Y, et al. Association between air pollution and sperm quality: a systematic review and meta-analysis. Environ Pollut. (2016) 208:663–9. doi: 10.1016/j.envpol.2015.10.044

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Qian, H , Xu, Q , Yan, W , Fan, Y , Li, Z , Tao, C, et al. Association between exposure to ambient air pollution and semen quality in adults: a meta-analysis. Environ Sci Pollut Res Int. (2022) 29:10792–801. doi: 10.1007/s11356-021-16484-9

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Zhang, J , Cai, Z , Ma, C , Xiong, J , and Li, H . Impacts of outdoor air pollution on human semen quality: a Meta-analysis and systematic review. Biomed Res Int. (2020) 2020:7528901. doi: 10.1155/2020/7528901

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Fathi Najafi, T , Latifnejad Roudsari, R , Namvar, F , Ghavami Ghanbarabadi, V , Hadizadeh Talasaz, Z , and Esmaeli, M . Air pollution and quality of sperm: a meta-analysis. Iran Red Crescent Med J. (2015) 17:e26930. doi: 10.5812/ircmj.17(4)2015.26930

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Xu, R , Zhong, Y , Li, R , Li, Y , Zhong, Z , Liu, T, et al. Association between exposure to ambient air pollution and semen quality: a systematic review and meta-analysis. Sci Total Environ. (2023) 870:161892. doi: 10.1016/j.scitotenv.2023.161892

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Page, MJ , McKenzie, JE , Bossuyt, PM , Boutron, I , Hoffmann, TC , Mulrow, CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. (2021) 372:n71. doi: 10.1136/bmj.n71

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Stang, A . Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. (2010) 25:603–5. doi: 10.1007/s10654-010-9491-z

PubMed Abstract | CrossRef Full Text | Google Scholar

56. Moola, S , Munn, Z , Tufanaru, C , Aromataris, E , Sears, K , Sfetic, R, et al. Chapter 7: systematic reviews of etiology and risk. JBI Reviewer's Manual. (2019). doi: 10.46658/JBIRM-17-06

CrossRef Full Text | Google Scholar

57. Morgan, RL , Thayer, KA , Bero, L , Bruce, N , Falck-Ytter, Y , Ghersi, D, et al. GRADE: assessing the quality of evidence in environmental and occupational health. Environ Int. (2016) 92-93:611–6. doi: 10.1016/j.envint.2016.01.004

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Balshem, H , Helfand, M , Schünemann, HJ , Oxman, AD , Kunz, R , Brozek, J, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. (2011) 64:401–6. doi: 10.1016/j.jclinepi.2010.07.015

CrossRef Full Text | Google Scholar

59. Guyatt, GH , Oxman, AD , Kunz, R , Brozek, J , Alonso-Coello, P , Rind, D, et al. GRADE guidelines 6. Rating the quality of evidence--imprecision. J Clin Epidemiol. (2011) 64:1283–93. doi: 10.1016/j.jclinepi.2011.01.012

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Ravindra, K , Chanana, N , and Mor, S . Exposure to air pollutants and risk of congenital anomalies: a systematic review and metaanalysis. Sci Total Environ. (2021) 765:142772. doi: 10.1016/j.scitotenv.2020.142772

CrossRef Full Text | Google Scholar

61. Bell, ML , Dominici, F , and Samet, JM . A meta-analysis of time-series studies of ozone and mortality with comparison to the national morbidity, mortality, and air pollution study. Epidemiology. (2005) 16:436–45. doi: 10.1097/01.ede.0000165817.40152.85

PubMed Abstract | CrossRef Full Text | Google Scholar

62. Wong, CM , Vichit-Vadakan, N , Kan, H , and Qian, Z . Public health and air pollution in Asia (PAPA): a multicity study of short-term effects of air pollution on mortality. Environ Health Perspect. (2008) 116:1195–202. doi: 10.1289/ehp.11257

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Yin, P , Chen, R , Wang, L , Meng, X , Liu, C , Niu, Y, et al. Ambient ozone pollution and daily mortality: a Nationwide study in 272 Chinese cities. Environ Health Perspect. (2017) 125:117006. doi: 10.1289/EHP1849

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Huang, S , Zhang, X , Huang, J , Lu, X , Liu, F , and Gu, D . Ambient air pollution and body weight status in adults: a systematic review and meta-analysis. Environ Pollut. (2020) 265:114999. doi: 10.1016/j.envpol.2020.114999

PubMed Abstract | CrossRef Full Text | Google Scholar

65. Yang, BY , Qian, Z , Howard, SW , Vaughn, MG , Fan, SJ , Liu, KK, et al. Global association between ambient air pollution and blood pressure: a systematic review and meta-analysis. Environ Pollut. (2018) 235:576–88. doi: 10.1016/j.envpol.2018.01.001

PubMed Abstract | CrossRef Full Text | Google Scholar

66. Higgins, JP , Thompson, S , Deeks, JJ , Jj, D , Altman, DG , and Altman, DG . Measuring inconsistency in meta-analyses. BMJ. (2003) 327:557–60. doi: 10.1136/bmj.327.7414.557

PubMed Abstract | CrossRef Full Text | Google Scholar

67. Hao, Y , Niu, X , and Wang, J . Impacts of haze pollution on China's tourism industry: a system of economic loss analysis. J Environ Manag. (2021) 295:113051. doi: 10.1016/j.jenvman.2021.113051

PubMed Abstract | CrossRef Full Text | Google Scholar

68. Tang, H , Zhang, S , and Chen, W . Assessing representative CCUS layouts for China's power sector toward carbon neutrality. Environ Sci Technol. (2021) 55:11225–35. doi: 10.1021/acs.est.1c03401

PubMed Abstract | CrossRef Full Text | Google Scholar

69. Li, J , Huang, Y , Zhang, BN , Fan, JH , Huang, R , Zhang, P, et al. Body mass index and breast cancer defined by biological receptor status in pre-menopausal and post-menopausal women: a multicenter study in China. PLoS One. (2014) 9:e87224. doi: 10.1371/journal.pone.0087224

PubMed Abstract | CrossRef Full Text | Google Scholar

70. Hu, Y , Chen, J , Wang, R , Li, M , Yun, C , Li, W, et al. Vitamin D nutritional status and its related factors for Chinese children and adolescents in 2010-2012. Nutrients. (2017) 9:1024. doi: 10.3390/nu9091024

PubMed Abstract | CrossRef Full Text | Google Scholar

71. Lv, MQ , Ge, P , Zhang, J , Yang, YQ , Zhou, L , and Zhou, DX . Temporal trends in semen concentration and count among 327 373 Chinese healthy men from 1981 to 2019: a systematic review. Hum Reprod. (2021) 36:1751–75. doi: 10.1093/humrep/deab124

PubMed Abstract | CrossRef Full Text | Google Scholar

72. Wang, XD , Yang, X , Xu, HB , Cao, P , Gao, P , and Liang, J . Exposure status and health risk assessment of deoxynivalenol from cereals in Chinese population in different regions. Zhonghua Yu Fang Yi Xue Za Zhi. (2019) 53:394–7. doi: 10.3760/cma.j.issn.0253-9624.2019.04.012

PubMed Abstract | CrossRef Full Text | Google Scholar

73. Zheng, J , Yang, X , Hu, S , Wang, Y , and Liu, J . Association between short-term exposure to air pollution and respiratory diseases among children in China: a systematic review and meta-analysis. Int J Environ Health Res. (2022) 32:2512–32. doi: 10.1080/09603123.2021.1974822

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Liu, Y , Xie, S , Yu, Q , Huo, X , Ming, X , Wang, J, et al. Short-term effects of ambient air pollution on pediatric outpatient visits for respiratory diseases in Yichang city, China, Environ Pollut B (2017); 227:116–124. doi: 10.1016/j.envpol.2017.04.029

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Chai, G , He, H , Sha, Y , Zhai, G , and Zong, S . Effect of PM2.5 on daily outpatient visits for respiratory diseases in Lanzhou, China. Sci Total Environ. (2019) 649:1563–72. doi: 10.1016/j.scitotenv.2018.08.384

CrossRef Full Text | Google Scholar

76. Kwack, SJ , and Lee, BM . Comparative cytotoxicity and sperm motility using a computer-aided sperm analysis system (CASA) for isomers of phthalic acid, a common final metabolite of phthalates. J Toxicol Environ Health A. (2015) 78:1038–50. doi: 10.1080/15287394.2015.1067503

PubMed Abstract | CrossRef Full Text | Google Scholar

77. Kelly, FJ . Oxidative stress: its role in air pollution and adverse health effects. Occup Environ Med. (2003) 60:612–6. doi: 10.1136/oem.60.8.612

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Saffari, A , Daher, N , Shafer, MM , Schauer, JJ , and Sioutas, C . Global perspective on the oxidative potential of airborne particulate matter: a synthesis of research findings. Environ Sci Technol. (2014) 48:7576–83. doi: 10.1021/es500937x

PubMed Abstract | CrossRef Full Text | Google Scholar

79. Guthrie, HD , and Welch, GR . Effects of reactive oxygen species on sperm function. Theriogenology. (2012) 78:1700–8. doi: 10.1016/j.theriogenology.2012.05.002

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Takeshima, T , Yumura, Y , Yasuda, K , Sanjo, H , Kuroda, S , Yamanaka, H, et al. Inverse correlation between reactive oxygen species in unwashed semen and sperm motion parameters as measured by a computer-assisted semen analyzer. Asian J Androl. (2017) 19:350–4. doi: 10.4103/1008-682X.173933

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Wei, Y , Cao, XN , Tang, XL , Shen, LJ , Lin, T , He, DW, et al. Urban fine particulate matter (PM2.5) exposure destroys blood-testis barrier (BTB) integrity through excessive ROS-mediated autophagy. Toxicol Mech Methods. (2018) 28:302–19. doi: 10.1080/15376516.2017.1410743

PubMed Abstract | CrossRef Full Text | Google Scholar

82. Gurel, C , Kuscu, GC , Buhur, A , Dagdeviren, M , Oltulu, F , Karabay Yavasoglu, NU, et al. Fluvastatin attenuates doxorubicin-induced testicular toxicity in rats by reducing oxidative stress and regulating the blood-testis barrier via mTOR signaling pathway. Hum Exp Toxicol. (2019) 38:1329–43. doi: 10.1177/0960327119862006

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Guan, L , Geng, X , Stone, C , Cosky, EEP , Ji, Y , du, H, et al. PM2.5exposure induces systemic inflammation and oxidative stress in an intracranial atherosclerosis rat model. Environ Toxicol. (2019) 34:530–8. doi: 10.1002/tox.22707

PubMed Abstract | CrossRef Full Text | Google Scholar

84. Xu, F , Shi, X , Qiu, X , Jiang, X , Fang, Y , Wang, J, et al. Investigation of the chemical components of ambient fine particulate matter (PM2.5) associated with in vitro cellular responses to oxidative stress and inflammation. Environ Int (2020) 136:105475. doi: 10.1016/j.envint.2020.105475

PubMed Abstract | CrossRef Full Text | Google Scholar

85. Cao, W , Wang, X , Li, J , Yan, M , Chang, CH , Kim, J, et al. NLRP3 inflammasome activation determines the fibrogenic potential of PM(2.5) air pollution particles in the lung. J Environ Sci (China). (2022) 111:429–41. doi: 10.1016/j.jes.2021.04.021

PubMed Abstract | CrossRef Full Text | Google Scholar

86. Liu, C , Fonken, LK , Wang, A , Maiseyeu, A , Bai, Y , Wang, TY, et al. Central IKKβ inhibition prevents air pollution mediated peripheral inflammation and exaggeration of type II diabetes. Part Fibre Toxicol. (2014) 11:53. doi: 10.1186/s12989-014-0053-5

PubMed Abstract | CrossRef Full Text | Google Scholar

87. Eggert-Kruse, W , Kiefer, I , Beck, C , Demirakca, T , and Strowitzki, T . Role for tumor necrosis factor alpha (TNF-α) and interleukin 1-beta (IL-1β) determination in seminal plasma during infertility investigation. Fertil Steril. (2007) 87:810–23. doi: 10.1016/j.fertnstert.2006.08.103

PubMed Abstract | CrossRef Full Text | Google Scholar

88. Zhou, L , Su, X , Li, B , Chu, C , Sun, H , Zhang, N, et al. PM2.5 exposure impairs sperm quality through testicular damage dependent on NALP3 inflammasome and miR-183/96/182 cluster targeting FOXO1 in mouse. Ecotoxicol Environ Saf. (2019) 169:551–63. doi: 10.1016/j.ecoenv.2018.10.108

PubMed Abstract | CrossRef Full Text | Google Scholar

89. Moretti, E , Cosci, I , Spreafico, A , Serchi, T , Cuppone, AM , and Collodel, G . Semen characteristics and inflammatory mediators in infertile men with different clinical diagnoses. Int J Androl. (2009) 32:637–46. doi: 10.1111/j.1365-2605.2008.00911.x

PubMed Abstract | CrossRef Full Text | Google Scholar

90. Lin, W , Zhu, T , Xue, T , Peng, W , Brunekreef, B , Gehring, U, et al. Association between changes in exposure to air pollution and biomarkers of oxidative stress in children before and during the Beijing Olympics. Am J Epidemiol. (2015) 181:575–83. doi: 10.1093/aje/kwu327

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: semen analysis, air pollution, particulate matter, meta-analysis, systematic review

Citation: Liu J, Dai Y, Li R, Yuan J, Wang Q and Wang L (2023) Does air pollution exposure affect semen quality? Evidence from a systematic review and meta-analysis of 93,996 Chinese men. Front. Public Health. 11:1219340. doi: 10.3389/fpubh.2023.1219340

Received: 09 May 2023; Accepted: 21 July 2023;
Published: 03 August 2023.

Edited by:

Barbara Piekarska, Medical University of Warsaw, Poland

Reviewed by:

Gennaro Lettieri, University Language Center, University of Naples Federico II, Italy
Nitya Kumar, Royal College of Surgeons in Ireland (Bahrain), Bahrain

Copyright © 2023 Liu, Dai, Li, Yuan, Wang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Junjie Liu, zdsfyljj@zzu.edu.cn

These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.