Biodiversity and the risk of asthma: a meta-analysis of the empirical evidence

Biodiversity and the risk of asthma: a meta-analysis of the empirical evidence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Biodiversity and the risk of asthma: a meta-analysis of the empirical evidence Jouni Jaakkola, Inês Paciência, Needhi Sharma, Timo Hugg, Aino Rantala, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6344350/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Climate change and urbanization are associated with reduced greenness and vegetation diversity, depletion of biodiversity, and impoverishment of human microbiota. These changes may influence immune regulation and increase the risk of many chronic inflammatory diseases, such as asthma. This short communication presents the results of a meta-analysis of the association between exposure to outer and inner layers of biodiversity and the development of asthma. The effect estimates for biodiversity were summarized as the standardized mean difference or relative risk with 95% confidence interval applying the Hedges method and the restricted maximum likelihood estimator, respectively. Our meta-analysis of existing evidence suggests exposure to high environmental biodiversity reduces the risk of asthma, while high inner-layer bacterial biodiversity may increase the risk of asthma. Health sciences/Risk factors Earth and environmental sciences/Environmental sciences Figures Figure 1 Figure 2 Introduction There is increasing evidence on the impacts of climate change on the environment and biodiversity 1 , 2 . Climate change may significantly affect biodiversity, not only through global warming and precipitation, but also by affecting ocean acidification, land use and nutrients, and the proliferation of invasive species into new habitats 3 – 5 . These global changes are altering the structure and function of ecosystems, and affecting individual species and the way they interact with other organisms and their habitats 6 . Furthermore, climate change has also been associated with a reduction in natural spaces, and depletion and/or change of environmental microbiota reservoirs, which can affect the distribution, composition, and interactions between microorganisms in nature 7 – 11 . In parallel, loss of biodiversity and limited exposure to diverse natural environments may negatively affect the composition and diversity of the human microbiota, leading to immune dysfunction and contributing to an increase in immune-mediated diseases such as asthma and allergic diseases 12 – 14 . Our previous state-of-the-science review summarized the current knowledge on the relationship between exposure to biodiversity and the development of asthma, wheezing, and allergic sensitization 15 . However, there exists no previous quantitative summary of current evidence on the role biodiversity in the development of asthma. This short communication presents the results of a meta-analysis of the association between exposure to outer (environmental) and inner (human microbiota) layers of biodiversity and the development of asthma. Results A total of 18 studies provided quantitative information on the relations between outer and/or inner layer biodiversity (Shannon diversity index and/or bacterial richness) and the risk of asthma and were included in the meta-analysis (Table S1 ). The meta-analysis comprised data from 31 048 subjects [28 119 in the outer layer assessment (ranging from 86 to 26 367 participants) and 2 929 in the inner layer assessment (ranging from 40 to 923 participants)] and the studies were published between 2011 and 2021 15 . Outer layer (environmental) biodiversity: Shannon diversity index and bacterial richness Figure 1 a presents the forest plot for the association between Shannon diversity index and the risk of asthma. The summary effect estimate indicated a protective effect, but it was not statistically significant [summary OR (95% CI) = 0.77 (0.55; 1.06)]. Considerable heterogeneity (I 2 = 72.4%, p = 0.027) was observed across the studies (Fig. 1 a). The funnel plot (Fig. S1 ) suggested an asymmetric pattern, but Egger’s test for publication bias was not statistically significant (t = 3.16, p = 0.195). The summary effect estimates for the association between bacterial richness and asthma [summary OR (95% CI) = 0.74 (0.57; 0.96)] was consistent with the hypothesis that exposure to high biodiversity, assessed as bacterial richness, has a protective effect on the development of asthma (Fig. 1 b). There was also considerable heterogeneity (I 2 = 71.8%, p = 0.003) across the studies (Fig. 1 b). The funnel plot (Fig. S2) was asymmetric, indicating some publication bias (Egger’s test: t = 5.15, p = 0.007). Inner layer (human microbiota) biodiversity: Shannon diversity index and bacterial richness The mean/median of the Shannon diversity index among individuals with and without asthma was reported in 6 studies. The random effects model provided a significantly increased standardized mean difference [SMD (95% CI) = 0.31 (0.14; 0.48)], indicating that the risk of asthma was associated with high bacterial diversity. The study-specific estimates were rather homogenous (I 2 = 0%, p = 0.88) (Fig. 2 a). The mean/median of the bacterial richness/abundance among individuals with and without asthma was reported in 4 studies. The summary standardized mean difference (95% CI) from the random effects model was 0.29 (0.10; 0.49) (Fig. 2 b), indicating that the risk of asthma was associated with high bacterial richness/abundance. Consistently with Shannon diversity index, the study-specific estimates were homogenous (I 2 = 0%, p = 0.97) (Fig. 2 b). The funnel plots (Fig. S3, S4) show an apparently asymmetrical pattern. Despite this apparent asymmetry, Egger’s tests for publication bias were not statistically significant (t=-1.43, p = 0.226 for studies on Shannon diversity index, and t=-0.67, p = 0.572 for studies on bacterial richness), suggesting absence of publication bias. The meta-analysis of 4 study-specific effect estimates, investigating associations between bacterial richness and asthma, indicated an increased risk of asthma related to high bacterial richness, although the finding was not statistically significant [OR (95% CI) = 1.14 (0.83; 1.56)] (Fig. 2 c). The forest plot shown in Fig. 2 c demonstrates significant heterogeneity (I 2 = 62.0%, p = 0.048) across the studies. The funnel plot (Fig. S5) suggested an asymmetric pattern; however, the Egger’s test indicated no publication bias (t=-0.26, p = 0.819). Discussion Based on a systematic search, ours is the first meta-analysis aiming to summarize current existing evidence on the role of outer (environmental) and inner layer (human microbiota) biodiversity in the development of asthma. The results of our meta-analysis showed a protective effect of exposure to high environmental biodiversity on the development of asthma. The evidence on the effect of inner layer biodiversity suggested that high bacterial diversity increases the risk of asthma. The purpose of this meta-analysis was to quantitatively summarize the existing evidence on the role of biodiversity in the development of asthma. Knowledge on the role of biodiversity on respiratory outcomes, including asthma, is under construction, and translating the results of the effect of exposure to inner and outer layers of biodiversity on asthma into applicable environmental and/or clinical guidelines benefits from a systematic approach and meta-analysis of the existing studies. Our meta-analysis included evidence from longitudinal studies on biodiversity and respiratory outcomes 16 , 19 , 20 , 26 – 29 , 31 , 33 , which allowed assessment of the time-dependent effects related to outer and inner layer biodiversity on the development of asthma. Both funnel plot and Egger’s test showed an asymmetric pattern when addressing the effect of exposure to bacterial richness (outer layer biodiversity), but no significant publication bias was observed for the other exposure indicators. However, caution is needed when interpreting the summary results, because of a small number of studies included, as well as due to heterogeneity in definitions of exposure and outcomes, sampling methods and different types of samples, namely in the inner layer, and temporal variation in biodiversity. The results of the present meta-analysis are consistent with the hypothesis that exposure to biodiversity may modulate the immune system resulting in susceptibility to develop asthma. Several studies included in this meta-analysis assessed the effect of early exposure to outer and inner layers of biodiversity on asthma, highlighting that exposure during early life (prenatal and early childhood) may have a strong effect on asthma and allergic diseases pathogenesis. However, Haahtela 14 suggested that the interaction between the environment (outer layer) and human microbiota (inner layer) never stops. Abrahamsson et al. 28 and Rook 34 also highlight that innate immunity needs constant and lifelong exposure to new bacterial and/or repeated exposure to create and maintain tolerance. Furthermore, the diversity and composition of human microbiota are also influenced by several environmental exposures, namely by the outer layer, being continuously colonized by the microbiome present in air, soil, water, and living organisms 35 . As suggested by the biodiversity hypothesis 14 , 36 , the reduced contact and interaction of people with natural spaces and biodiversity may adversely affect the composition and diversity of the human commensal microbiota and its immunomodulatory capacity, increasing the risk of developing allergies and/or inflammatory diseases. Previous studies provided evidence that environmental biodiversity, human microbiota, and allergic diseases and asthma are interrelated 9 , 12 , 37 – 39 . A study including 14- to 18-y-old school children showed that the diversity of proteobacteria was higher on the skin of individuals living in an environment with more forest and agricultural land compared with those living in built areas and near water bodies 12 . Authors also reported that in healthy individuals, IL-10 expression, a key anti-inflammatory cytokine in immunologic tolerance, was positively correlated with the abundance of the gammaproteobacterial genus Acinetobacter on the skin 12 . The results of the present meta-analysis also suggest that high bacterial diversity increases the risk of asthma. This finding is consistent with the interpretation of a role for pathogenic bacteria, which may disturb the local bacterial ecology and the balance of the immune system response, supporting the hypothesis of an association between inner layer biodiversity and the development of asthma 40 – 42 . The imbalance in the distribution of microbial taxa, i.e. , loss of beneficial microbial organisms and expansion of pathobionts or potentially harmful microorganisms, has been linked to the development of asthma 43 , 44 . Additionally, according to Følsgaard et al. 45 the airway colonization with M. catarrhalis and H. influenzae , induced a mixed Th1/Th2/Th17 response, which may result in chronic inflammation, and consequently increase the risk of asthma 40 . It is important to highlight that the studies on inner layer biodiversity included in this meta-analysis did not assess the association between environmental and human microbial diversity and the development of asthma. However, Depner et al. 32 reported that the detrimental effect of Moraxella colonization was not observed among farm children [adjusted OR (aOR) = 0.94 (95% CI: 0.34, 2.63)] compared with nonfarm children [aOR = 6.88 (95% CI: 2.27, 20.86)], suggesting that the exposure to natural environment may neutralize the effect of pathogenic bacteria. Climate change and growing urbanization have also been associated with a reduction and/or deterioration in natural spaces, loss of habitats, depletion and/or change of environmental microbiota reservoirs. These changes in the ecological conditions of nature affects the distribution, composition, and interactions between microorganisms in nature, which may adversely affect the human commensal microbiota and its immunomodulatory capacity 7 – 11 . Therefore, understanding the interactions between climate change, outer and inner layers of biodiversity, and immune system is also needed for assessing the role of biodiversity in the development of asthma. In conclusion, this meta-analysis provides evidence that exposure to high outer layer (environmental) biodiversity may have a protective effect on the development of asthma. Furthermore, the evidence on the effect of inner layer (human microbiota) biodiversity suggests that high bacterial diversity may increase the risk of asthma. Methods We conducted systematic search and a meta-analysis of relevant studies identified up to March 5, 2024, in SciVerse Scopus, PubMed MEDLINE, and Web of Science 15 . A study was included in the meta-analysis if (i) it used a priori recognized measure to assess biodiversity (Shannon diversity index and/or bacterial richness) and (ii) it analyzed biodiversity as a continuous variable. Meta-analyses applying the random-effects model were performed on the available effect estimates applying the R software, Version 1.4.1106 (dmetar package) and Stata software. A total of 1986 studies were screened, 355 of these were assessed for eligibility, and 330 were excluded. After a full-text review of the 405 studies, 18 studies were included in the meta-analysis (Table S1 ). The effect estimates (EE) for biodiversity were summarized as the standardized mean difference (SMD) or relative risk (RR) with 95% confidence interval applying the Hedges method and the restricted maximum likelihood (REML) estimator, respectively. The magnitude of heterogeneity between the included studies was estimated using the Higgins I 2 statistic and τ 2 . Publication bias was assessed through visual examination of a funnel plot and by applying the Egger’s test. The risk of bias was independently assessed by two reviewers applying the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies 46 . An adapted version of the NOS developed by Herzog et al. 47 was used for cross-sectional studies. The results from the NOS were translated into the Agency for Health Research and Quality standards, and applying these the studies were classified as good, fair or poor 48 . In order to improve the validity of the meta-analysis, only studies with a total NOS score higher than 3 were meta-analyzed (Table S1 ) 49 . Declarations Acknowledgments The authors gratefully acknowledge funding from the University of Oulu and the Academy of Finland Profi Biodiverse Anthropocenes no. 336449 and Academy of Finland grant no. 310371 and no. 310372 (GLORIA consortium). Author Contributions All authors contributed to the design of the review protocol. IP and NS performed the study quality assessment. All steps from screening to quality assessment were done in consultation with the wider review team. IP analyzed the data and drafted the manuscript. JJ initiated the study and supervised all the steps. All authors contributed to the critical revision and approved the final version of the manuscript. Funding Academy of Finland (no. 310372 and no. 336449) and Horizon 2020 Framework Programme (Project 101056883 - INCHILDHEALTH HORIZON-HLTH-2021-ENVHLTH-02). Competing interests The authors declare no competing interests. Data availability All data analysed in the paper have been derived from previously published materials, which are included in the listed references. All datasets generated and analysed are available upon request from the corresponding author. References Fakana S. Causes of Climate Change: Review Article. 2020. Nunez S, et al. Assessing the impacts of climate change on biodiversity: is below 2 °C enough? Climatic Change 2019;154(3):351-65. Reed DH. Impact of Climate Change on Biodiversity. In: Chen W-Y, Seiner J, Suzuki T, Lackner M, editors. Handbook of Climate Change Mitigation. New York, NY: Springer US; 2012. p. 505-30. Rinawati F, et al. Climate Change Impacts on Biodiversity—The Setting of a Lingering Global Crisis. Diversity [Internet]. 2013; 5(1):[114-23 pp.]. Bellard C, et al. Impacts of climate change on the future of biodiversity. Ecology letters 2012;15(4):365-77. Weiskopf SR, et al. Climate change effects on biodiversity, ecosystems, ecosystem services, and natural resource management in the United States. Science of The Total Environment 2020;733:137782. Nurkolis F, et al. Human activities and changes in the gut microbiome: A perspective. Human Nutrition & Metabolism 2022;30:200165. Pecl GT, et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science (New York, NY) 2017;355(6332). Tasnim N, et al. Linking the Gut Microbial Ecosystem with the Environment: Does Gut Health Depend on Where We Live? Frontiers in microbiology 2017;8:1935. Jain PK, et al. Chapter 13 - Effect of climate change on microbial diversity and its functional attributes. In: De Mandal S, Bhatt P, editors. Recent Advancements in Microbial Diversity: Academic Press; 2020. p. 315-31. Cavicchioli R, et al. Scientists’ warning to humanity: microorganisms and climate change. Nature Reviews Microbiology 2019;17(9):569-86. Hanski I, et al. Environmental biodiversity, human microbiota, and allergy are interrelated. Proceedings of the National Academy of Sciences of the United States of America 2012;109(21):8334-9. Seastedt H, Nadeau K. Factors by which global warming worsens allergic disease. Annals of Allergy, Asthma & Immunology 2023;131(6):694-702. Haahtela T. A biodiversity hypothesis. Allergy 2019;74(8):1445-56. Paciência I, et al. The Role of Biodiversity in the Development of Asthma and Allergic Sensitization: A State-of-the-Science Review. Environmental Health Perspectives ;132(6):066001. Birzele LT, et al. Environmental and mucosal microbiota and their role in childhood asthma. Allergy 2017;72(1):109-19. Donovan GH, et al. The natural environment, plant diversity, and adult asthma: A retrospective observational study using the CDC's 500 Cities Project Data. Health Place 2021;67:102494. Lai PS, et al. The classroom microbiome and asthma morbidity in children attending 3 inner-city schools. The Journal of allergy and clinical immunology 2018;141(6):2311-3. Kirjavainen PV, et al. Farm-like indoor microbiota in non-farm homes protects children from asthma development. Nature Medicine 2019;25(7):1089-95. Karvonen AM, et al. Indoor bacterial microbiota and development of asthma by 10.5 years of age. The Journal of allergy and clinical immunology 2019;144(5):1402-10. Fu X, et al. Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru, Malaysia. Environment international 2020;138:105664. Fu X, et al. Derived habitats of indoor microbes are associated with asthma symptoms in Chinese university dormitories. Environ Res 2021;194:110501. Fu X, et al. Indoor bacterial, fungal and viral species and functional genes in urban and rural schools in Shanxi Province, China-association with asthma, rhinitis and rhinoconjunctivitis in high school students. Microbiome 2021;9(1):138. Dannemiller KC, et al. Indoor microbial communities: Influence on asthma severity in atopic and nonatopic children. J Allergy Clin Immunol 2016;138(1):76-83.e1. Espuela-Ortiz A, et al. Bacterial salivary microbiome associates with asthma among african american children and young adults. Pediatric pulmonology 2019;54(12):1948-56. Niemeier-Walsh C, et al. Exposure to traffic-related air pollution and bacterial diversity in the lower respiratory tract of children. PloS one 2021;16(6):e0244341. Thorsen J, et al. Infant airway microbiota and topical immune perturbations in the origins of childhood asthma. Nature Communications 2019;10(1):5001. Abrahamsson TR, et al. Low gut microbiota diversity in early infancy precedes asthma at school age. Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology 2014;44(6):842-50. Toivonen L, et al. Longitudinal Changes in Early Nasal Microbiota and the Risk of Childhood Asthma. Pediatrics 2020;146(4). Lee JJ, et al. Different upper airway microbiome and their functional genes associated with asthma in young adults and elderly individuals. Allergy 2019;74(4):709-19. Schei K, et al. Allergy-related diseases and early gut fungal and bacterial microbiota abundances in children. Clinical and translational allergy 2021;11(5):e12041. Depner M, et al. Bacterial microbiota of the upper respiratory tract and childhood asthma. The Journal of allergy and clinical immunology 2017;139(3):826-34.e13. Bisgaard H, et al. Reduced diversity of the intestinal microbiota during infancy is associated with increased risk of allergic disease at school age. The Journal of allergy and clinical immunology 2011;128(3):646-52.e1-5. Rook GA. Regulation of the immune system by biodiversity from the natural environment: an ecosystem service essential to health. Proceedings of the National Academy of Sciences of the United States of America 2013;110(46):18360-7. Biagioni B, et al. Environmental influences on childhood asthma: Climate change. Pediatric Allergy and Immunology 2023;34(5):e13961. von Hertzen L, et al. Natural immunity. Biodiversity loss and inflammatory diseases are two global megatrends that might be related. EMBO reports 2011;12(11):1089-93. Ruokolainen L, et al. Green areas around homes reduce atopic sensitization in children. Allergy 2015;70(2):195-202. Lehtimäki J, et al. Urbanized microbiota in infants, immune constitution, and later risk of atopic diseases. Journal of Allergy and Clinical Immunology 2021;148(1):234-43. Lehtimäki J, et al. Nature-oriented daycare diversifies skin microbiota in children-No robust association with allergies. Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology 2018;29(3):318-21. Bisgaard H, et al. Childhood asthma after bacterial colonization of the airway in neonates. The New England journal of medicine 2007;357(15):1487-95. Marri PR, et al. Asthma-associated differences in microbial composition of induced sputum. The Journal of allergy and clinical immunology 2013;131(2):346-52.e1-3. Fiuza BSD, et al. Understanding asthma and allergies by the lens of biodiversity and epigenetic changes. Frontiers in immunology 2021;12:623737. Abdel-Aziz MI, et al. The crosstalk between microbiome and asthma: Exploring associations and challenges. Clinical & Experimental Allergy 2019;49(8):1067-86. Petersen C, Round JL. Defining dysbiosis and its influence on host immunity and disease. Cellular microbiology 2014;16(7):1024-33. Følsgaard NV, et al. Pathogenic bacteria colonizing the airways in asymptomatic neonates stimulates topical inflammatory mediator release. American journal of respiratory and critical care medicine 2013;187(6):589-95. 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(9):603-5. Herzog R, et al. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? a systematic review. BMC Public Health 2013;13(1):154. Penson D, et al. Newcastle-Ottawa quality assessment form for cohort studies. Ottawa: Ottawa Hospital Research Institute 2012. Gates M, et al. Impact of fatigue and insufficient sleep on physician and patient outcomes: a systematic review. BMJ Open 2018;8(9):e021967. Additional Declarations There is NO Competing Interest. Supplementary Files Supplementarydatajj.docx Supplementary data Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6344350","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":440081529,"identity":"68513c01-7a6e-47b2-82e4-25ebf9f9ade0","order_by":0,"name":"Jouni Jaakkola","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYBACxgYgkcDAxsDAA8QPGGwYGNiBIhUGxGpJYEhjYGAGipzBowUBIFoOQ7XgUcjc3mP24AEDnzx/z7HEBwk15+UMDvMYMBwowOOwnjPmBkCHGc4423bYIOHYbWOIFnx+mZFjJgHUwthwnr1NIoHtduIGoBbmD0RosZ8P1vLvHFgLUbYkbjjbdkwise0AEVp6jpVJJBiwJW88cyzZILEv2VjyMFvBAXxaDNubt0n+qDhmO+9MmuGDD9/s5PiON298cOAPHi0NINLgGKroAdwaGBjkIVQNPjWjYBSMglEw0gEACvRRi171ybEAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-4168-4683","institution":"University of Oulu","correspondingAuthor":true,"prefix":"","firstName":"Jouni","middleName":"","lastName":"Jaakkola","suffix":""},{"id":440081530,"identity":"d7b6f2a7-3245-4dc7-b80f-54acd4c29bc9","order_by":1,"name":"Inês Paciência","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"prefix":"","firstName":"Inês","middleName":"","lastName":"Paciência","suffix":""},{"id":440081531,"identity":"90933449-c818-46f0-ba67-59281756d14d","order_by":2,"name":"Needhi Sharma","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Needhi","middleName":"","lastName":"Sharma","suffix":""},{"id":440081532,"identity":"15748ad4-ddb7-416f-aa40-fe07b7f352f2","order_by":3,"name":"Timo Hugg","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"prefix":"","firstName":"Timo","middleName":"","lastName":"Hugg","suffix":""},{"id":440081533,"identity":"146637ff-c91a-4308-afd0-3ac33bc7bbe4","order_by":4,"name":"Aino Rantala","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"prefix":"","firstName":"Aino","middleName":"","lastName":"Rantala","suffix":""},{"id":440081534,"identity":"ec35ee0a-268f-4d07-bec4-11af1e62b898","order_by":5,"name":"Maritta Jaakkola","email":"","orcid":"","institution":"University of Oulu","correspondingAuthor":false,"prefix":"","firstName":"Maritta","middleName":"","lastName":"Jaakkola","suffix":""},{"id":440081535,"identity":"fc965499-3abf-4c4a-87d8-2408eb187d4d","order_by":6,"name":"Wael Al-Delaimy","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Wael","middleName":"","lastName":"Al-Delaimy","suffix":""}],"badges":[],"createdAt":"2025-03-31 11:30:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6344350/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6344350/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80192038,"identity":"1b1fcbb6-bb6f-4fd7-8b01-7f7800e459c3","added_by":"auto","created_at":"2025-04-09 04:31:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":130705,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) Forest plot for the association between Shannon diversity index and the risk of asthma. (b) Forest plot for the association between bacterial richness and asthma. \u003c/strong\u003eThe area of the grey square represents the weight of each study, the center represents the odds ratio (ORs), and the length of each line around the point represents its 95% confidence interval (95% CI). The summary effect estimate (result of the meta-analysis) is represented by a blue lozenge at the bottom of the graph.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6344350/v1/ae6e0c0bfda4e1c164f4b2fb.png"},{"id":80192039,"identity":"012b1c38-7e4a-40ba-923f-b8c37cff75ac","added_by":"auto","created_at":"2025-04-09 04:31:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":256121,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) Forest plot for the standardized mean difference of the Shannon diversity index among individuals with and without asthma. (b) Forest plot for the standardized mean difference of the bacterial richness among individuals with and without asthma. (c) Forest plot for the association between bacterial richness and asthma. \u003c/strong\u003e(a, b) The area of the grey square represents the weight of each study, the centre represents the standardised mean difference (SMD), and the length of each line around the point represents its 95% confidence interval (95% CI). The summary pooled estimate is represented by a grey lozenge at the bottom of the graph. The results of the studies conducted by Abrahamsson et al. \u003csup\u003e28\u003c/sup\u003e and Toivonen et al. \u003csup\u003e29\u003c/sup\u003e correspond to Shannon diversity index assessed at 12 months of age. The results of the study conducted by Lee et al. \u003csup\u003e30\u003c/sup\u003e corresponds to Shannon diversity index/ bacterial richness assessed among young adults. (c) The grey square represents the weight of each study, the centre represents the odds ratio (OR), and the length of each line around the point represents its 95% confidence interval (95% CI). The summary effect estimate is represented by a blue lozenge at the bottom of the graph.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6344350/v1/9da9b1dac51304909bc45e49.png"},{"id":80192735,"identity":"4b12ad71-246c-470d-8f29-e63b28a8bd1c","added_by":"auto","created_at":"2025-04-09 04:47:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":993316,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6344350/v1/3f673853-d947-46cd-a80e-755edfbcd891.pdf"},{"id":80192045,"identity":"2e3f1644-2786-4f32-8811-91eaf9cae4fc","added_by":"auto","created_at":"2025-04-09 04:31:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":267896,"visible":true,"origin":"","legend":"Supplementary data","description":"","filename":"Supplementarydatajj.docx","url":"https://assets-eu.researchsquare.com/files/rs-6344350/v1/610c5f5c509caa9d30fbfd04.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Biodiversity and the risk of asthma: a meta-analysis of the empirical evidence","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThere is increasing evidence on the impacts of climate change on the environment and biodiversity\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Climate change may significantly affect biodiversity, not only through global warming and precipitation, but also by affecting ocean acidification, land use and nutrients, and the proliferation of invasive species into new habitats\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These global changes are altering the structure and function of ecosystems, and affecting individual species and the way they interact with other organisms and their habitats\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Furthermore, climate change has also been associated with a reduction in natural spaces, and depletion and/or change of environmental microbiota reservoirs, which can affect the distribution, composition, and interactions between microorganisms in nature\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In parallel, loss of biodiversity and limited exposure to diverse natural environments may negatively affect the composition and diversity of the human microbiota, leading to immune dysfunction and contributing to an increase in immune-mediated diseases such as asthma and allergic diseases\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Our previous state-of-the-science review summarized the current knowledge on the relationship between exposure to biodiversity and the development of asthma, wheezing, and allergic sensitization\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, there exists no previous quantitative summary of current evidence on the role biodiversity in the development of asthma. This short communication presents the results of a meta-analysis of the association between exposure to outer (environmental) and inner (human microbiota) layers of biodiversity and the development of asthma.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 18 studies provided quantitative information on the relations between outer and/or inner layer biodiversity (Shannon diversity index and/or bacterial richness) and the risk of asthma and were included in the meta-analysis (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The meta-analysis comprised data from 31 048 subjects [28 119 in the outer layer assessment (ranging from 86 to 26 367 participants) and 2 929 in the inner layer assessment (ranging from 40 to 923 participants)] and the studies were published between 2011 and 2021\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eOuter layer (environmental) biodiversity: Shannon diversity index and bacterial richness\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea presents the forest plot for the association between Shannon diversity index and the risk of asthma. The summary effect estimate indicated a protective effect, but it was not statistically significant [summary OR (95% CI)\u0026thinsp;=\u0026thinsp;0.77 (0.55; 1.06)]. Considerable heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;72.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027) was observed across the studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The funnel plot (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) suggested an asymmetric pattern, but Egger\u0026rsquo;s test for publication bias was not statistically significant (t\u0026thinsp;=\u0026thinsp;3.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.195). The summary effect estimates for the association between bacterial richness and asthma [summary OR (95% CI)\u0026thinsp;=\u0026thinsp;0.74 (0.57; 0.96)] was consistent with the hypothesis that exposure to high biodiversity, assessed as bacterial richness, has a protective effect on the development of asthma (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). There was also considerable heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;71.8%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) across the studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The funnel plot (Fig. S2) was asymmetric, indicating some publication bias (Egger\u0026rsquo;s test: t\u0026thinsp;=\u0026thinsp;5.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInner layer (human microbiota) biodiversity: Shannon diversity index and bacterial richness\u003c/h3\u003e\n\u003cp\u003eThe mean/median of the Shannon diversity index among individuals with and without asthma was reported in 6 studies. The random effects model provided a significantly increased standardized mean difference [SMD (95% CI)\u0026thinsp;=\u0026thinsp;0.31 (0.14; 0.48)], indicating that the risk of asthma was associated with high bacterial diversity. The study-specific estimates were rather homogenous (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.88) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The mean/median of the bacterial richness/abundance among individuals with and without asthma was reported in 4 studies. The summary standardized mean difference (95% CI) from the random effects model was 0.29 (0.10; 0.49) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), indicating that the risk of asthma was associated with high bacterial richness/abundance. Consistently with Shannon diversity index, the study-specific estimates were homogenous (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.97) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The funnel plots (Fig. S3, S4) show an apparently asymmetrical pattern. Despite this apparent asymmetry, Egger\u0026rsquo;s tests for publication bias were not statistically significant (t=-1.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.226 for studies on Shannon diversity index, and t=-0.67, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.572 for studies on bacterial richness), suggesting absence of publication bias.\u003c/p\u003e \u003cp\u003eThe meta-analysis of 4 study-specific effect estimates, investigating associations between bacterial richness and asthma, indicated an increased risk of asthma related to high bacterial richness, although the finding was not statistically significant [OR (95% CI)\u0026thinsp;=\u0026thinsp;1.14 (0.83; 1.56)] (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The forest plot shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec demonstrates significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;62.0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048) across the studies. The funnel plot (Fig. S5) suggested an asymmetric pattern; however, the Egger\u0026rsquo;s test indicated no publication bias (t=-0.26, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.819).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBased on a systematic search, ours is the first meta-analysis aiming to summarize current existing evidence on the role of outer (environmental) and inner layer (human microbiota) biodiversity in the development of asthma. The results of our meta-analysis showed a protective effect of exposure to high environmental biodiversity on the development of asthma. The evidence on the effect of inner layer biodiversity suggested that high bacterial diversity increases the risk of asthma.\u003c/p\u003e \u003cp\u003eThe purpose of this meta-analysis was to quantitatively summarize the existing evidence on the role of biodiversity in the development of asthma. Knowledge on the role of biodiversity on respiratory outcomes, including asthma, is under construction, and translating the results of the effect of exposure to inner and outer layers of biodiversity on asthma into applicable environmental and/or clinical guidelines benefits from a systematic approach and meta-analysis of the existing studies. Our meta-analysis included evidence from longitudinal studies on biodiversity and respiratory outcomes\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, which allowed assessment of the time-dependent effects related to outer and inner layer biodiversity on the development of asthma. Both funnel plot and Egger\u0026rsquo;s test showed an asymmetric pattern when addressing the effect of exposure to bacterial richness (outer layer biodiversity), but no significant publication bias was observed for the other exposure indicators. However, caution is needed when interpreting the summary results, because of a small number of studies included, as well as due to heterogeneity in definitions of exposure and outcomes, sampling methods and different types of samples, namely in the inner layer, and temporal variation in biodiversity.\u003c/p\u003e \u003cp\u003eThe results of the present meta-analysis are consistent with the hypothesis that exposure to biodiversity may modulate the immune system resulting in susceptibility to develop asthma. Several studies included in this meta-analysis assessed the effect of early exposure to outer and inner layers of biodiversity on asthma, highlighting that exposure during early life (prenatal and early childhood) may have a strong effect on asthma and allergic diseases pathogenesis. However, Haahtela \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e suggested that the interaction between the environment (outer layer) and human microbiota (inner layer) never stops. Abrahamsson et al. \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and Rook \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e also highlight that innate immunity needs constant and lifelong exposure to new bacterial and/or repeated exposure to create and maintain tolerance. Furthermore, the diversity and composition of human microbiota are also influenced by several environmental exposures, namely by the outer layer, being continuously colonized by the microbiome present in air, soil, water, and living organisms\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. As suggested by the biodiversity hypothesis\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, the reduced contact and interaction of people with natural spaces and biodiversity may adversely affect the composition and diversity of the human commensal microbiota and its immunomodulatory capacity, increasing the risk of developing allergies and/or inflammatory diseases. Previous studies provided evidence that environmental biodiversity, human microbiota, and allergic diseases and asthma are interrelated\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. A study including 14- to 18-y-old school children showed that the diversity of proteobacteria was higher on the skin of individuals living in an environment with more forest and agricultural land compared with those living in built areas and near water bodies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Authors also reported that in healthy individuals, IL-10 expression, a key anti-inflammatory cytokine in immunologic tolerance, was positively correlated with the abundance of the gammaproteobacterial genus \u003cem\u003eAcinetobacter\u003c/em\u003e on the skin\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe results of the present meta-analysis also suggest that high bacterial diversity increases the risk of asthma. This finding is consistent with the interpretation of a role for pathogenic bacteria, which may disturb the local bacterial ecology and the balance of the immune system response, supporting the hypothesis of an association between inner layer biodiversity and the development of asthma\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The imbalance in the distribution of microbial taxa, \u003cem\u003ei.e.\u003c/em\u003e, loss of beneficial microbial organisms and expansion of pathobionts or potentially harmful microorganisms, has been linked to the development of asthma\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Additionally, according to F\u0026oslash;lsgaard et al. \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e the airway colonization with \u003cem\u003eM. catarrhalis\u003c/em\u003e and \u003cem\u003eH. influenzae\u003c/em\u003e, induced a mixed Th1/Th2/Th17 response, which may result in chronic inflammation, and consequently increase the risk of asthma\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. It is important to highlight that the studies on inner layer biodiversity included in this meta-analysis did not assess the association between environmental and human microbial diversity and the development of asthma. However, Depner et al. \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e reported that the detrimental effect of \u003cem\u003eMoraxella\u003c/em\u003e colonization was not observed among farm children [adjusted OR (aOR)\u0026thinsp;=\u0026thinsp;0.94 (95% CI: 0.34, 2.63)] compared with nonfarm children [aOR\u0026thinsp;=\u0026thinsp;6.88 (95% CI: 2.27, 20.86)], suggesting that the exposure to natural environment may neutralize the effect of pathogenic bacteria.\u003c/p\u003e \u003cp\u003eClimate change and growing urbanization have also been associated with a reduction and/or deterioration in natural spaces, loss of habitats, depletion and/or change of environmental microbiota reservoirs. These changes in the ecological conditions of nature affects the distribution, composition, and interactions between microorganisms in nature, which may adversely affect the human commensal microbiota and its immunomodulatory capacity\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Therefore, understanding the interactions between climate change, outer and inner layers of biodiversity, and immune system is also needed for assessing the role of biodiversity in the development of asthma.\u003c/p\u003e \u003cp\u003eIn conclusion, this meta-analysis provides evidence that exposure to high outer layer (environmental) biodiversity may have a protective effect on the development of asthma. Furthermore, the evidence on the effect of inner layer (human microbiota) biodiversity suggests that high bacterial diversity may increase the risk of asthma.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe conducted systematic search and a meta-analysis of relevant studies identified up to March 5, 2024, in SciVerse Scopus, PubMed MEDLINE, and Web of Science\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. A study was included in the meta-analysis if (i) it used \u003cem\u003ea priori\u003c/em\u003e recognized measure to assess biodiversity (Shannon diversity index and/or bacterial richness) and (ii) it analyzed biodiversity as a continuous variable. Meta-analyses applying the random-effects model were performed on the available effect estimates applying the R software, Version 1.4.1106 (dmetar package) and Stata software. A total of 1986 studies were screened, 355 of these were assessed for eligibility, and 330 were excluded. After a full-text review of the 405 studies, 18 studies were included in the meta-analysis (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effect estimates (EE) for biodiversity were summarized as the standardized mean difference (SMD) or relative risk (RR) with 95% confidence interval applying the Hedges method and the restricted maximum likelihood (REML) estimator, respectively. The magnitude of heterogeneity between the included studies was estimated using the Higgins I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic and τ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Publication bias was assessed through visual examination of a funnel plot and by applying the Egger\u0026rsquo;s test. The risk of bias was independently assessed by two reviewers applying the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. An adapted version of the NOS developed by Herzog et al. \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e was used for cross-sectional studies. The results from the NOS were translated into the Agency for Health Research and Quality standards, and applying these the studies were classified as good, fair or poor\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. In order to improve the validity of the meta-analysis, only studies with a total NOS score higher than 3 were meta-analyzed (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge funding from the University of Oulu and the Academy of Finland Profi Biodiverse Anthropocenes no. 336449 and Academy of Finland grant no. 310371 and no. 310372 (GLORIA consortium).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the design of the review protocol. IP and NS performed the study quality assessment. All steps from screening to quality assessment were done in consultation with the wider review team. IP analyzed the data and drafted the manuscript. JJ initiated the study and supervised all the steps. All authors contributed to the critical revision and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcademy of Finland (no. 310372 and no. 336449) and Horizon 2020 Framework Programme (Project 101056883 - INCHILDHEALTH HORIZON-HLTH-2021-ENVHLTH-02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analysed in the paper have been derived from previously published materials, which are included in the listed references. All datasets generated and analysed are available upon request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFakana S. Causes of Climate Change: Review Article. 2020.\u003c/li\u003e\n \u003cli\u003eNunez S, et al. Assessing the impacts of climate change on biodiversity: is below 2 \u0026deg;C enough? \u003cem\u003eClimatic Change\u003c/em\u003e 2019;154(3):351-65.\u003c/li\u003e\n \u003cli\u003eReed DH. Impact of Climate Change on Biodiversity. In: Chen W-Y, Seiner J, Suzuki T, Lackner M, editors. Handbook of Climate Change Mitigation. New York, NY: Springer US; 2012. p. 505-30.\u003c/li\u003e\n \u003cli\u003eRinawati F, et al. Climate Change Impacts on Biodiversity\u0026mdash;The Setting of a Lingering Global Crisis. Diversity [Internet]. 2013; 5(1):[114-23 pp.].\u003c/li\u003e\n \u003cli\u003eBellard C, et al. Impacts of climate change on the future of biodiversity. \u003cem\u003eEcology letters\u003c/em\u003e 2012;15(4):365-77.\u003c/li\u003e\n \u003cli\u003eWeiskopf SR, et al. Climate change effects on biodiversity, ecosystems, ecosystem services, and natural resource management in the United States. \u003cem\u003eScience of The Total Environment\u003c/em\u003e 2020;733:137782.\u003c/li\u003e\n \u003cli\u003eNurkolis F, et al. Human activities and changes in the gut microbiome: A perspective. \u003cem\u003eHuman Nutrition \u0026amp; Metabolism\u003c/em\u003e 2022;30:200165.\u003c/li\u003e\n \u003cli\u003ePecl GT, et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. \u003cem\u003eScience (New York, NY)\u003c/em\u003e 2017;355(6332).\u003c/li\u003e\n \u003cli\u003eTasnim N, et al. Linking the Gut Microbial Ecosystem with the Environment: Does Gut Health Depend on Where We Live? \u003cem\u003eFrontiers in microbiology\u003c/em\u003e 2017;8:1935.\u003c/li\u003e\n \u003cli\u003eJain PK, et al. Chapter 13 - Effect of climate change on microbial diversity and its functional attributes. In: De Mandal S, Bhatt P, editors. Recent Advancements in Microbial Diversity: Academic Press; 2020. p. 315-31.\u003c/li\u003e\n \u003cli\u003eCavicchioli R, et al. Scientists\u0026rsquo; warning to humanity: microorganisms and climate change. \u003cem\u003eNature Reviews Microbiology\u003c/em\u003e 2019;17(9):569-86.\u003c/li\u003e\n \u003cli\u003eHanski I, et al. Environmental biodiversity, human microbiota, and allergy are interrelated. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e 2012;109(21):8334-9.\u003c/li\u003e\n \u003cli\u003eSeastedt H, Nadeau K. Factors by which global warming worsens allergic disease. \u003cem\u003eAnnals of Allergy, Asthma \u0026amp; Immunology\u003c/em\u003e 2023;131(6):694-702.\u003c/li\u003e\n \u003cli\u003eHaahtela T. A biodiversity hypothesis. \u003cem\u003eAllergy\u003c/em\u003e 2019;74(8):1445-56.\u003c/li\u003e\n \u003cli\u003ePaci\u0026ecirc;ncia I, et al. The Role of Biodiversity in the Development of Asthma and Allergic Sensitization: A State-of-the-Science Review. \u003cem\u003eEnvironmental Health Perspectives\u003c/em\u003e;132(6):066001.\u003c/li\u003e\n \u003cli\u003eBirzele LT, et al. Environmental and mucosal microbiota and their role in childhood asthma. \u003cem\u003eAllergy\u003c/em\u003e 2017;72(1):109-19.\u003c/li\u003e\n \u003cli\u003eDonovan GH, et al. The natural environment, plant diversity, and adult asthma: A retrospective observational study using the CDC\u0026apos;s 500 Cities Project Data. \u003cem\u003eHealth Place\u003c/em\u003e 2021;67:102494.\u003c/li\u003e\n \u003cli\u003eLai PS, et al. The classroom microbiome and asthma morbidity in children attending 3 inner-city schools. \u003cem\u003eThe Journal of allergy and clinical immunology\u003c/em\u003e 2018;141(6):2311-3.\u003c/li\u003e\n \u003cli\u003eKirjavainen PV, et al. Farm-like indoor microbiota in non-farm homes protects children from asthma development. \u003cem\u003eNature Medicine\u003c/em\u003e 2019;25(7):1089-95.\u003c/li\u003e\n \u003cli\u003eKarvonen AM, et al. Indoor bacterial microbiota and development of asthma by 10.5 years of age. \u003cem\u003eThe Journal of allergy and clinical immunology\u003c/em\u003e 2019;144(5):1402-10.\u003c/li\u003e\n \u003cli\u003eFu X, et al. Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru, Malaysia. \u003cem\u003eEnvironment international\u003c/em\u003e 2020;138:105664.\u003c/li\u003e\n \u003cli\u003eFu X, et al. Derived habitats of indoor microbes are associated with asthma symptoms in Chinese university dormitories. \u003cem\u003eEnviron Res\u003c/em\u003e 2021;194:110501.\u003c/li\u003e\n \u003cli\u003eFu X, et al. Indoor bacterial, fungal and viral species and functional genes in urban and rural schools in Shanxi Province, China-association with asthma, rhinitis and rhinoconjunctivitis in high school students. \u003cem\u003eMicrobiome\u003c/em\u003e 2021;9(1):138.\u003c/li\u003e\n \u003cli\u003eDannemiller KC, et al. Indoor microbial communities: Influence on asthma severity in atopic and nonatopic children. \u003cem\u003eJ Allergy Clin Immunol\u003c/em\u003e 2016;138(1):76-83.e1.\u003c/li\u003e\n \u003cli\u003eEspuela-Ortiz A, et al. Bacterial salivary microbiome associates with asthma among african american children and young adults. \u003cem\u003ePediatric pulmonology\u003c/em\u003e 2019;54(12):1948-56.\u003c/li\u003e\n \u003cli\u003eNiemeier-Walsh C, et al. Exposure to traffic-related air pollution and bacterial diversity in the lower respiratory tract of children. \u003cem\u003ePloS one\u003c/em\u003e 2021;16(6):e0244341.\u003c/li\u003e\n \u003cli\u003eThorsen J, et al. Infant airway microbiota and topical immune perturbations in the origins of childhood asthma. \u003cem\u003eNature Communications\u003c/em\u003e 2019;10(1):5001.\u003c/li\u003e\n \u003cli\u003eAbrahamsson TR, et al. Low gut microbiota diversity in early infancy precedes asthma at school age. \u003cem\u003eClinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology\u003c/em\u003e 2014;44(6):842-50.\u003c/li\u003e\n \u003cli\u003eToivonen L, et al. Longitudinal Changes in Early Nasal Microbiota and the Risk of Childhood Asthma. \u003cem\u003ePediatrics\u003c/em\u003e 2020;146(4).\u003c/li\u003e\n \u003cli\u003eLee JJ, et al. Different upper airway microbiome and their functional genes associated with asthma in young adults and elderly individuals. \u003cem\u003eAllergy\u003c/em\u003e 2019;74(4):709-19.\u003c/li\u003e\n \u003cli\u003eSchei K, et al. Allergy-related diseases and early gut fungal and bacterial microbiota abundances in children. \u003cem\u003eClinical and translational allergy\u003c/em\u003e 2021;11(5):e12041.\u003c/li\u003e\n \u003cli\u003eDepner M, et al. Bacterial microbiota of the upper respiratory tract and childhood asthma. \u003cem\u003eThe Journal of allergy and clinical immunology\u003c/em\u003e 2017;139(3):826-34.e13.\u003c/li\u003e\n \u003cli\u003eBisgaard H, et al. Reduced diversity of the intestinal microbiota during infancy is associated with increased risk of allergic disease at school age. \u003cem\u003eThe Journal of allergy and clinical immunology\u003c/em\u003e 2011;128(3):646-52.e1-5.\u003c/li\u003e\n \u003cli\u003eRook GA. Regulation of the immune system by biodiversity from the natural environment: an ecosystem service essential to health. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e 2013;110(46):18360-7.\u003c/li\u003e\n \u003cli\u003eBiagioni B, et al. Environmental influences on childhood asthma: Climate change. \u003cem\u003ePediatric Allergy and Immunology\u003c/em\u003e 2023;34(5):e13961.\u003c/li\u003e\n \u003cli\u003evon Hertzen L, et al. Natural immunity. Biodiversity loss and inflammatory diseases are two global megatrends that might be related. \u003cem\u003eEMBO reports\u003c/em\u003e 2011;12(11):1089-93.\u003c/li\u003e\n \u003cli\u003eRuokolainen L, et al. Green areas around homes reduce atopic sensitization in children. \u003cem\u003eAllergy\u003c/em\u003e 2015;70(2):195-202.\u003c/li\u003e\n \u003cli\u003eLehtim\u0026auml;ki J, et al. Urbanized microbiota in infants, immune constitution, and later risk of atopic diseases. \u003cem\u003eJournal of Allergy and Clinical Immunology\u003c/em\u003e 2021;148(1):234-43.\u003c/li\u003e\n \u003cli\u003eLehtim\u0026auml;ki J, et al. Nature-oriented daycare diversifies skin microbiota in children-No robust association with allergies. \u003cem\u003ePediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology\u003c/em\u003e 2018;29(3):318-21.\u003c/li\u003e\n \u003cli\u003eBisgaard H, et al. Childhood asthma after bacterial colonization of the airway in neonates. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e 2007;357(15):1487-95.\u003c/li\u003e\n \u003cli\u003eMarri PR, et al. Asthma-associated differences in microbial composition of induced sputum. \u003cem\u003eThe Journal of allergy and clinical immunology\u003c/em\u003e 2013;131(2):346-52.e1-3.\u003c/li\u003e\n \u003cli\u003eFiuza BSD, et al. Understanding asthma and allergies by the lens of biodiversity and epigenetic changes. \u003cem\u003eFrontiers in immunology\u003c/em\u003e 2021;12:623737.\u003c/li\u003e\n \u003cli\u003eAbdel-Aziz MI, et al. The crosstalk between microbiome and asthma: Exploring associations and challenges. \u003cem\u003eClinical \u0026amp; Experimental Allergy\u003c/em\u003e 2019;49(8):1067-86.\u003c/li\u003e\n \u003cli\u003ePetersen C, Round JL. Defining dysbiosis and its influence on host immunity and disease. \u003cem\u003eCellular microbiology\u003c/em\u003e 2014;16(7):1024-33.\u003c/li\u003e\n \u003cli\u003eF\u0026oslash;lsgaard NV, et al. Pathogenic bacteria colonizing the airways in asymptomatic neonates stimulates topical inflammatory mediator release. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e 2013;187(6):589-95.\u003c/li\u003e\n \u003cli\u003eStang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. \u003cem\u003eEur J Epidemiol\u003c/em\u003e 2010;25(9):603-5.\u003c/li\u003e\n \u003cli\u003eHerzog R, et al. Are healthcare workers\u0026rsquo; intentions to vaccinate related to their knowledge, beliefs and attitudes? a systematic review. \u003cem\u003eBMC Public Health\u003c/em\u003e 2013;13(1):154.\u003c/li\u003e\n \u003cli\u003ePenson D, et al. Newcastle-Ottawa quality assessment form for cohort studies. \u003cem\u003eOttawa: Ottawa Hospital Research Institute\u003c/em\u003e 2012.\u003c/li\u003e\n \u003cli\u003eGates M, et al. Impact of fatigue and insufficient sleep on physician and patient outcomes: a systematic review. \u003cem\u003eBMJ Open\u003c/em\u003e 2018;8(9):e021967.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6344350/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6344350/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change and urbanization are associated with reduced greenness and vegetation diversity, depletion of biodiversity, and impoverishment of human microbiota. These changes may influence immune regulation and increase the risk of many chronic inflammatory diseases, such as asthma. This short communication presents the results of a meta-analysis of the association between exposure to outer and inner layers of biodiversity and the development of asthma. The effect estimates for biodiversity were summarized as the standardized mean difference or relative risk with 95% confidence interval applying the Hedges method and the restricted maximum likelihood estimator, respectively. Our meta-analysis of existing evidence suggests exposure to high environmental biodiversity reduces the risk of asthma, while high inner-layer bacterial biodiversity may increase the risk of asthma.\u003c/p\u003e","manuscriptTitle":"Biodiversity and the risk of asthma: a meta-analysis of the empirical evidence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-09 04:31:46","doi":"10.21203/rs.3.rs-6344350/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"58720489-6d97-4301-8f92-9a63fabd5155","owner":[],"postedDate":"April 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":46850463,"name":"Health sciences/Risk factors"},{"id":46850464,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-02-10T08:16:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-09 04:31:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6344350","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6344350","identity":"rs-6344350","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}