Autism Spectrum Disorder in Offspring of Maternal asthma occurrence, and exacerbations during pregnancy: a population-based cohort study

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The connection between maternal asthma exacerbation and the development of ASD in offspring remains unclear. The aim of this study was to investigate the association between maternal asthma, including asthma exacerbation during pregnancy, and the risk of ASD in offspring. Methods: Information from over two million mothers and their live newborns, collected from the Taiwan Birth Certificate Registry spanning from January 1, 2004, to December 31, 2017, was utilized in this nationwide cohort study based on the population. The Cox regression model was employed to assess the risk of ASD in children between mothers with and without asthma. The analysis adjusted for sociodemographic characteristics, parity, birth weight, and parents’ physical and mental illnesses. Sibling control was implemented to investigate the impact of asthma exacerbation during pregnancy on the risk of offspring ASD. Result: Children with asthmatic parents face a significantly higher risk of developing ASD compared to those with non-asthmatic parents. Maternal asthma had an HR of 1.44 ( 95% confidence interval of 1.34 to 1.55), while paternal asthma had an HR of 1.12 ( 95% confidence interval of 1.03 to 1.22). Interestingly, acute asthma exacerbations during pregnancy didn't seem to affect the likelihood of having more ASD children in a distinctive way (Adjusted HR 1.23, 95% CI: 0.68–2.24). Conclusion: Offspring born to parents with asthma face an elevated risk of having ASD, with a higher risk associated maternal asthma. There was no obvious correlation between mother asthma exacerbations during pregnancy and the likelihood of ASD in the offspring. asthma pregnancy maternal autism spectrum disorder Introduction Asthma ranks among the most common inflammatory diseases during pregnancy, affecting 5–13% of pregnant females worldwide. (Mendola, Laughon et al. 2013 , Jolving, Nielsen et al. 2016 ) Several studies suggest increased perinatal risks for maternal asthma occurrence and exacerbation(Wang, Murphy et al. 2014 , Liu, Agerbo et al. 2018 , Liu, Dalsgaard et al. 2019 ). Poorly controlled maternal asthma may contribute to adverse perinatal outcomes, including small-for-gestational-age infants, and low birth weight (Rejno, Lundholm et al. 2014 ). Maternal asthma can lead to the placenta’s hypoxia, potentially interfering with fetal development. Furthermore, the systemic inflammation of the mother can alter the fetal environment and may cause aberrant development in the fetal central nervous system(Namazy, Murphy et al. 2013 , Hughes, Mills Ko et al. 2018 ). Autism spectrum disorder (ASD) is a neurodevelopmental disease and the diagnosis of ASD is based on symptoms encompassing limitations in social communication and the presence of restricted, repetitive patterns of behavior or interests. The incidence of ASD cases has dramatical increased over the past decades, ranging from 0.48–3.13% in Europe and the United States (Delobel-Ayoub, Saemundsen et al. 2020 , Maenner, Shaw et al. 2020 ). This surge could be attributed to increased public awareness and altered diagnostic criteria, but it is also possible that actual risk factors have risen. ASD is regarded as highly variable with numerous etiologies and its symptoms manifested early in childhood, resulting in many different types of disability. Currently, it is thought that ASD results from the interplay of hereditary and environmental variables(Chaste and Leboyer 2012 ). Epidemiological studies have suggested a connection between ASD and prenatal infections and inflammation was suggested by epidemiological studies (Atladottir, Thorsen et al. 2010 , Hughes, Mills Ko et al. 2018 ). However, earlier research had small sample sizes. The connection between maternal asthma and the development of ASD in offspring remains unclear, especially for acute exacerbation during pregnancy. In this study, we examined the association between maternal asthma identified before childbirth and the risks of ASD in offspring utilizing birth certificate registration in a Taiwanese cohort comprising over 2.3 million live-born singletons. Additionally, we explore the impact of acute exacerbation during pregnancy on the risk of offspring ASD. Method Study Source This nationwide population-based cohort study utilized data from the National Health Insurance Research Database of Taiwan (NHIRD). The present study received approval from the Research Ethics Committee of the Chang Gung Medical Foundation. Our study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)guideline. Since this study employed anonymized data from the Taiwan National Health Insurance Research Database, informed permission is not necessary. The Taiwan National Health Insurance Research Database was launched on March 1, 1995.Every resident in Taiwan is mandated to enroll in the National Health Insurance program, and this obligation persists until emigration or death. As a result, the coverage rate for Taiwanese residents exceeds 99%. (Wu, Majeed et al. 2010 ) This study derives all of its datasets from the Taiwan National Health Insurance Research Database (NHIRD). Birth certificate registration in Taiwan is compulsory for all hospitals or medical institutions. We obtained data on gestational age and verified full-term births (> 37 weeks) for all live-born children using the Taiwan birth certificate registration. Between 2004 and 2017, the Taiwan Birth Certificate Registry database covered 99.78% of all births in Taiwan. (Chen 2022 ) The entire study sample consisted of live-born infants from the Taiwan Birth Certificate Registry from January 1, 2004, to December 31, 2017, on more than two million mothers and live births. In order to gather comprehensive information on children and their parents, the Taiwan Birth Certificate Registration dataset was linked to the Maternal and Child Health Database of Taiwan ,utilizing the mother's identity, the children's sex, and the year of their birth as the key factors. Maternal asthma history. We utilized the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), to define asthma cases; asthma was coded as 493 and the International Classification of Diseases, Tenth Revision (ICD-10) code J45.Mothers were categorized as having a lifelong asthma diagnosis from 2004 to 2018 if they received an asthma diagnosis at any time, whether it was before or after pregnancy. The diagnosis of asthma was made based on at least one inpatient record or at least three outpatients visiting. Maternal asthma exacerbations during pregnancy were defined if she sought inpatient care, visited the ER for problems linked to asthma or obtained an oral corticosteroid prescription. Mothers without documented asthma were categorized as "non-asthmatic." Outcome Measures Offspring of asthmatic mother or non-asthmatic were tracked from birth until the occurrence of diagnoses related ASD, death ,or emigration, concluding at the end of the study in 2018. Diagnoses were established using the International Classification of Diseases, Ninth Revision (ICD-9) criteria for Autism Spectrum Disorder (ASD) (ICD-9 code 299,xx) and the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) criteria for ASD (ICD-10 code F840).Children who has diagnoses were defined as having at least 1 inpatient record or at least 3 outpatient visits. Children born to mothers diagnosed with asthma before childbirth were regarded as prenatally exposed to maternal asthma. Covariates Prenatal variables that have been associated with ASD include advanced mother age, fetal distress, and gestational respiratory infections(Hisle-Gorman, Susi et al. 2018 ).A cohort study in Denmark suggested that Type 1 diabetes in the mother and rheumatoid arthritis during pregnancy were linked to the mental health of the children. (He, Yu et al. 2022 )In the present study, covariates were categorized into a) maternal covariates b) offspring covariates, and c) paternal covariates. The selected maternal covariates include maternal smoking during pregnancy, parity, maternal age at delivery, and maternal physical and mental disorders preceding pregnancy (including ASD, ADHD, SLE, rheumatoid arthritis Preeclampsia, and gestational diabetes)(Hisle-Gorman, Susi et al. 2018 ). Offspring covariates encompass gender, low birth weight (birth body weight lower than 2500 gm), year of birth, preterm birth (gestational age lower than 37 weeks), and low-income family status. As for paternal covariates, autoimmune diseases of father were utilized as the negative control exposure which includes paternal age at delivery, paternal physical and mental disorders before pregnancy (including ASD, ADHD, SLE, rheumatoid arthritis) (Estes and McAllister 2016 ). Statistical analysis For descriptive statistics of categorical and continuous data, we employed frequency with percentage and mean with standard deviation, respectively. The Cox regression model was utilized to assess the risk of ASD in children born to parents with and without asthma. The model was adjusted for sociodemographic characteristics, physical and mental illnesses, parity, and birth weight. To investigate whether maternal asthma exacerbation during pregnancy had additional effects on child ASD, we conducted a comparison among siblings using conditional Cox proportional hazards regression with the biological mother as the stratum variable between siblings with and without acute asthma during pregnancy, with adjustment for covariates. Results We conducted the data analysis from September 1, 2022, through January 30, 2023. This study encompassed 2,338,087 live births between January 1, 2004, and December 31, 2017, with 3.27% born to mothers with asthma during this period in Taiwan. Table 1 provided specifics about the study participants' characteristics. Compared to mothers who were not asthmatic, mothers who had asthma had an increased chance of developing ADHD, ASD, or other immunological abnormalities. (i.e., systemic lupus erythematosus, rheumatoid arthritis, preeclampsia, and gestational diabetes). It was discovered that women who had asthma were more likely to be of lower social status and to smoke during pregnancy than mothers who did not have asthma. Table 1 Baseline Characteristics of the Offspring According to Prenatal Exposure to Maternal asthma maternal covariates b) offspring covariates, and c) paternal covariates Characteristics Children with Non- asthmatic mothers Children with Asthmatic mothers N = 2261625 N = 76462 Maternal age at delivery (years) < 25 236623 (10.5) 8850 (11.6) 25–34 1568886 (69.4) 49448 (64.7) ≥ 35 456116 (20.2) 18164 (23.8) Parity 1 1305209 (57.7) 39982 (52.3) ≥ 2 956416 (42.3) 36480 (47.7) Maternal smoking during pregnancy 1076 (< 0.1) 79 (0.1) Low-income 136016 (6.0) 5709 (7.5) Maternal disorders before pregnancy ASD 33 (< 0.1) 9 (< 0.1) ADHD 696 (< 0.1) 83 (0.1) Systemic Lupus Erythematosus 5278 (0.2) 387 (0.5) Rheumatoid arthritis 5384 (0.2) 396 (0.5) Preeclampsia 12390 (0.5) 642 (0.8) Gestational diabetes 164327 (7.3) 8041 (10.5) Abbreviations: ASD, autism spectrum disorder; ADHD, attention deficit hyperactivity disorder HR, hazard ratio; CI, confidence interval. Offspring covariates Offspring covariate Preterm birth (gestational age <37 weeks) 197040 (8.7) 8084 (10.6) Low birth weight (<2500 g) 177960 (7.9) 6834 (8.9) Child sex Boys 1177487 (52.1) 40121 (52.5) Girls 1084138 (47.9) 36341 (47.5) Age, y 8.0 (3.8) 7.1 (3.7) Paternal covariates Paternal age at delivery (years) <25 83715 (3.7) 3801 (5.0) 25–34 1293019 (57.2) 41562 (54.4) ≥35 884891 (39.1) 31099 (40.7) Paternal mental disorder before pregnancy ASD 55 (<0.1) 9 (<0.1) ADHD 1245 (0.1) 94 (0.1) Systemic Lupus Erythematosus 824 (<0.1) 41 (0.1) rheumatoid arthritis 4774 (0.2) 176 (0.2) Abbreviations: ASD, autism spectrum disorder; ADHD, attention deficit hyperactivity disorder In Table 2 , the result indicated that children whose mother had asthma were more likely to be born prematurely and to have low birth weights. Furthermore, children with asthmatic parents exhibited a significantly higher risk of developing ASD compared to those with non-asthmatic parents. Maternal asthma had an HR of 1.44 (95% confidence interval of 1.34 to 1.55), while paternal asthma had an HR of 1.12 (95% confidence interval of 1.03 to 1.22). Specifically, the HR for maternal asthma in boys with autism spectrum disorder was 1.36, with a 95% confidence interval ranging from 1.26 to 1.47. For girls, the HR was 1.52, with a range of 1.30 to 1.77. Table 2 Risk of ASD in children whose parents with asthma Maternal asthmas Paternal asthmas aHR(95% CI) aHR(95% CI) ASD Total 1.44 (1.34–1.55) 1.12 (1.03–1.22) Boy 1.36 (1.26–1.47) 1.21 (1.11–1.32) Girl 1.52 (1.30–1.77) 1.08 (0.89–1.30) Abbreviations: ASD, autism spectrum disorder; aHR, adjusted hazard ratio; CI, confidence interval. Adjusted for parental age, and parental diagnosis (i.e., autism spectrum disorder, ADHD, systemic lupus erythematosus, rheumatoid arthritis preeclampsia, gestational diabetes), parity, low-income status, preterm birth and low birth weight Table 3 illustrated that only mothers with asthma who have had at least two pregnancies—one complicated by asthma exacerbations during pregnancy and the other not—and who have sibling control are only eligible. Surprisingly, acute asthma exacerbation during pregnancy did not appear to significantly affect the likelihood of having mor children with ASD in any distinctive way (Adjusted HR 1.23, 95% CI: 0.68–2.24). Table 3 Sibling comparisons of risk of ASD among children whose mother with asthma exacerbation during pregnancy Discordant pairs Number Exposed to asthma during pregnancy event Number Unexposed to asthma during pregnancy event Adjusted HR (95% CI) ASD 2997 34 3247 39 1.23 (0.68–2.24) Abbreviations: ASD, autism spectrum disorder; aHR, adjusted hazard ratio; CI, confidence interval. Adjusted for parental age, and parental diagnosis (i.e., autism spectrum disorder, ADHD, systemic lupus erythematosus, rheumatoid arthritis preeclampsia, gestational diabetes), parity, low-income status, preterm birth and low birth weight. Discussion In this population-based cohort study, which included 2,338,087 newborn births, children born to parents who have asthma were more likely to have ASD, with the risk being greater for maternal asthma. Moreover, there was no discernable relationship between the chance of ASD in the kids and the mother's aggravation of asthma during pregnancy, even after accounting for siblings. Our results support previous studies that have suggested, a connection between maternal asthma and ASD in offspring. In a case-control study involving 2095 controls and 407 cases. It was observed that 10.3% of case women and 8.2% of control mothers were diagnosed with an autoimmune disorder in the four years preceding pregnancy. Specifically maternal asthma in the second trimester was associated with a more than 2-fold increased incidence of ASD(Croen, Grether et al. 2005 ). Similarly, in a cohort of 363 ASD children, the prevalence of immunological disorder particularly maternal asthma was notable. Compared to girls, there was a higher likelihood of maternal immunological disorders in boys with ASD. (p = 0.009) (Patel, Dale et al. 2020 ) These findings were supported by a case-control study in Sweden, demonstrating an increased risk of developing ASD in offspring among asthmatic mother after adjusting for shared familial factors. The point estimates showing the connection between maternal asthma and the probability that offspring will receive an ASD diagnosis were similar in the analyses carried out within extended families, regardless of the kind of family structure. The adjusted odds ratio (OR) was 1.20 (95% CI 0.80–1.81) for half-siblings, 1.28 (95% CI 1.16–1.41) for full-cousins, and 1.30 (95% CI 1.10–1.54) for half-cousins. Prenatal exposure to asthma medications was not linked to later autism spectrum disorders in subjects whose mothers had asthma. (Gong, Lundholm et al. 2019 ) One meta-analysis investigated the association between maternal illness during pregnancy and a higher incidence of ASD in offspring (OR = 1.13, with 95% confidence interval : 1.03–1.23). It was suggested that pathogens may directly affect the developing brain or that inflammation may indirectly affect it (Jiang, Xu et al. 2016 ). Moreover, other studies have indicated that the results observed in the children may be due to maternal immune activation rather than the infection itself(Boulanger-Bertolus, Pancaro et al. 2018 ). Additional evidence from the CHildhood Autism Risk from Genetics and the Environment study (CHARGE study) suggests that neurodevelopment of the offspring may be influenced by the mother's immune system. In an analysis involving 560 cases of ASD, 391 cases of typically developing controls, and 168 cases of developmental delay (DD) history, researchers examined whether maternal autoimmune diseases were associated with ASD. ASD alone did not show a substantially link with maternal autoimmune illness. However, the combined ASD + DD risks were considerably increased by maternal autoimmune disease (OR = 1.46, 95% CI 1.01, 2.09)(Lyall, Ashwood et al. 2014 ). One theory about the pathophysiology of neurodevelopmental problems (such as ASD and ADHD) is the involvement of maternal immune activation (MIA). (.(Han, Patel et al. 2021 ) Furthermore, studies have demonstrated a strong connection between ADHD and ASD and elevated levels of inflammatory cytokines.(Theoharides, Tsilioni et al. 2016 , Donfrancesco, Nativio et al. 2020 ) In addition, fever—a typical indicator of inflammation—has been linked to a higher chance of ASD in children, especially if it happens in the second trimester, indicating that the timing of MIA is crucial.(Hornig, Bresnahan et al. 2018 ). An fundamental concept regarding the relationship between ASD and maternal asthma posits that the presence of maternal asthma may impact fetal development by inducing changes in immunological responses within the central nervous system. These changes could result in neuronal damage, potentially increasing the likelihood of children developing ASD.(Gong, Lundholm et al. 2019 ) As a final note, MIA during pregnancy has been linked to an increased incidence of ASD(Ornoy, Weinstein-Fudim et al. 2015 ). In the MIA model for ASD, specific cytokines levels were found to be elevated in the fetal brain, amniotic fluid, maternal serum, and placenta(Hsiao and Patterson 2011 , Knuesel, Chicha et al. 2014 , Meyer 2014 , Choi, Yim et al. 2016 ).In comparison to controls, individuals with ASD generally exhibited significantly higher amniotic fluid levels of IL-4, IL-10, TNF-ɑ, and TNF- ß in patients with ASD. (Abdallah, Larsen et al. 2013 ). Animal models confirm this relationship, demonstrating that maternal immune activation alone is sufficient to transfer permanent neuropathologic behaviors in offspring.(Estes and McAllister 2016 ). Additionally, exacerbations of the mother's asthma during pregnancy have been associated with a higher likelihood of ADHD in the offspring.(Cowell, Bellinger et al. 2019 , Liu, Dalsgaard et al. 2019 ). Notably, the risk of ADHD was unaffected by the frequency of exacerbations. Similarly, other researchers discovered a correlation between maternal asthma exacerbations during pregnancy and ADHD.(Liu, Dalsgaard et al. 2019 ) However, no previous research has illustrated a direct link between asthma exacerbations in pregnant mothers and an increased risk of ASD in their progeny. Using the sibling control method, we investigated this issue in our study and found no association between asthma exacerbations in expectant mothers and an increased risk of ASD in children. Strengths and Limitations The current study has a number of advantages. Firstly, recall bias was minimized by using prospectively gathered registry data. Secondly, with a sample size exceeding 2 million births,encompassing all live births in Taiwan, rreduce the risk of selection bias. Lastly, the availability of comprehensive sociodemographic and clinical information allowed for the correction for the various confounding factors ,particularly through sibling control for acute exacerbation during pregnancy. The research comes with certain limitations. Initially, we identified asthma patients using the ICD, requiring at least one hospitalization or at least three outpatient diagnoses. This approach may lead to an underestimation, as individuals without diagnosed asthma would not be accounted for. Consequently, not all individuals with asthma exacerbations would be admitted to a hospital, go to the emergency room, or get an oral corticosteroid prescription filled. They would have been mistakenly categorized as not experiencing exacerbations. Our exposure group and comparison group will be comparable as a result of these misclassifications, yielding a null result. Moreover, only the most severe ASD cases may be listed in the hospital registry and prescription registration, which restricts generalizability. Conclusions The present study showed that maternal asthma but not exacerbation of asthma during pregnancy was associated to offspring ASD. Further research is required to elucidate the mechanisms underlying these associations and clarify how genetic susceptibilities may interact with environmental factors to influence disease risk. Further research is needed for better understanding of these pathways to the prevention and treatment of ASD. Declarations Author contribution: Yi-Feng Ho, MD、Chiao-Fan Lin, MD : Conception and design of the study, acquisition and analysis of data, drafting the manuscript, contribution to manuscript writing, and app roval of the final manuscript. Vincent Chin-Hung Chen, MD ,PhD: Patient recruitment, clinical assessments ,acquisition of data interpretation of data, study coordination, critical revision of the manuscript for important intellectual content, and final approval of the version to be published. Yi-Lung Chen, PhD: Statistical analysis, data interpretation, and drafting sections of the manuscript, and final approval of the version to be published. Tsai-Ching Hsu, PhD: Study supervision , critical revision of the manuscript, and final approval of the version to be published. All authors: Contributed to the writing and review of the manuscript, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Ethical Statement: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Chang Gung Medical Foundation (Date2020.05.25/ No.202000880B0). Conflict of Interest: The authors declare no conflicts of interest related to this study. Funding: This research was supported by grant from the Chang Gung Memorial Hospital (CMRPG3K1121). The present study was based on the National Health Insurance Research Database provided by the Central Bureau of National Health Insurance, the Department of Health, and managed by the National Health Research Institutes. Data Availability: The data supporting the findings of this study are available within the article. 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"The risk of maternal and placental complications in pregnant women with asthma: a systematic review and meta-analysis." J Matern Fetal Neonatal Med 27 (9): 934-942. Wu, T. Y., A. Majeed and K. N. Kuo (2010). "An overview of the healthcare system in Taiwan." London J Prim Care (Abingdon) 3 (2): 115-119. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted 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. 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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-4493797","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":311721435,"identity":"19cc2fd3-f3a2-4b31-9973-b807a05024dc","order_by":0,"name":"Yi-Feng Ho","email":"","orcid":"","institution":"Chung Shan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yi-Feng","middleName":"","lastName":"Ho","suffix":""},{"id":311721436,"identity":"e4760af1-0e21-4603-9c0f-f18a799f261f","order_by":1,"name":"Chiao-Fan Lin","email":"","orcid":"","institution":"Linkou Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chiao-Fan","middleName":"","lastName":"Lin","suffix":""},{"id":311721437,"identity":"eece71df-b697-4999-9e07-7ec4ca367a18","order_by":2,"name":"Vincent Chin-Hung Chen","email":"","orcid":"","institution":"Chang Gung University","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"Chin-Hung","lastName":"Chen","suffix":""},{"id":311721438,"identity":"657a1b58-95c1-468b-b911-15ba8b804aa5","order_by":3,"name":"Yi-Lung Chen","email":"","orcid":"","institution":"Asia University","correspondingAuthor":false,"prefix":"","firstName":"Yi-Lung","middleName":"","lastName":"Chen","suffix":""},{"id":311721439,"identity":"ea44084e-a045-4986-995f-9e61ac084d5a","order_by":4,"name":"Tsai-Ching Hsu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAp0lEQVRIiWNgGAWjYBACAwYGxgcINlFa2BiYYUqBdAJxWtgkSNNiLt/8rOLHn22JDezN2yQYfxwmrMWyjc3sZm/b7cQGnmNlEgwJRGgxOMbDdpuxAahFIscMqOU2cVqKGf4Atci/IUELMwMbyBYeorWkGUsC/WLcxpNWbJGQ9p8ILYcPP/zw489t2X72wxtvfLBJI6wFDthARAIJGkbBKBgFo2AU4AEAtFY3B1EdqcgAAAAASUVORK5CYII=","orcid":"","institution":"Chung Shan Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tsai-Ching","middleName":"","lastName":"Hsu","suffix":""}],"badges":[],"createdAt":"2024-05-29 02:40:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4493797/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4493797/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83452332,"identity":"2d0c734f-35ab-4874-9fed-61102c173597","added_by":"auto","created_at":"2025-05-26 13:23:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":757844,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4493797/v1/5dc96d65-50e7-4bcd-9163-6414c3cfb4d7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Autism Spectrum Disorder in Offspring of Maternal asthma occurrence, and exacerbations during pregnancy: a population-based cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAsthma ranks among the most common inflammatory diseases during pregnancy, affecting 5\u0026ndash;13% of pregnant females worldwide. (Mendola, Laughon et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Jolving, Nielsen et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Several studies suggest increased perinatal risks for maternal asthma occurrence and exacerbation(Wang, Murphy et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Liu, Agerbo et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Liu, Dalsgaard et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Poorly controlled maternal asthma may contribute to adverse perinatal outcomes, including small-for-gestational-age infants, and low birth weight (Rejno, Lundholm et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Maternal asthma can lead to the placenta\u0026rsquo;s hypoxia, potentially interfering with fetal development. Furthermore, the systemic inflammation of the mother can alter the fetal environment and may cause aberrant development in the fetal central nervous system(Namazy, Murphy et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Hughes, Mills Ko et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAutism spectrum disorder (ASD) is a neurodevelopmental disease and the diagnosis of ASD is based on symptoms encompassing limitations in social communication and the presence of restricted, repetitive patterns of behavior or interests. The incidence of ASD cases has dramatical increased over the past decades, ranging from 0.48\u0026ndash;3.13% in Europe and the United States (Delobel-Ayoub, Saemundsen et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Maenner, Shaw et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This surge could be attributed to increased public awareness and altered diagnostic criteria, but it is also possible that actual risk factors have risen. ASD is regarded as highly variable with numerous etiologies and its symptoms manifested early in childhood, resulting in many different types of disability. Currently, it is thought that ASD results from the interplay of hereditary and environmental variables(Chaste and Leboyer \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Epidemiological studies have suggested a connection between ASD and prenatal infections and inflammation was suggested by epidemiological studies (Atladottir, Thorsen et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Hughes, Mills Ko et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, earlier research had small sample sizes. The connection between maternal asthma and the development of ASD in offspring remains unclear, especially for acute exacerbation during pregnancy.\u003c/p\u003e \u003cp\u003eIn this study, we examined the association between maternal asthma identified before childbirth and the risks of ASD in offspring utilizing birth certificate registration in a Taiwanese cohort comprising over 2.3\u0026nbsp;million live-born singletons. Additionally, we explore the impact of acute exacerbation during pregnancy on the risk of offspring ASD.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Source\u003c/h2\u003e \u003cp\u003eThis nationwide population-based cohort study utilized data from the National Health Insurance Research Database of Taiwan (NHIRD). The present study received approval from the Research Ethics Committee of the Chang Gung Medical Foundation. Our study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE)guideline. Since this study employed anonymized data from the Taiwan National Health Insurance Research Database, informed permission is not necessary.\u003c/p\u003e \u003cp\u003eThe Taiwan National Health Insurance Research Database was launched on March 1, 1995.Every resident in Taiwan is mandated to enroll in the National Health Insurance program, and this obligation persists until emigration or death. As a result, the coverage rate for Taiwanese residents exceeds 99%. (Wu, Majeed et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) This study derives all of its datasets from the Taiwan National Health Insurance Research Database (NHIRD). Birth certificate registration in Taiwan is compulsory for all hospitals or medical institutions. We obtained data on gestational age and verified full-term births (\u0026gt;\u0026thinsp;37 weeks) for all live-born children using the Taiwan birth certificate registration. Between 2004 and 2017, the Taiwan Birth Certificate Registry database covered 99.78% of all births in Taiwan. (Chen \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) The entire study sample consisted of live-born infants from the Taiwan Birth Certificate Registry from January 1, 2004, to December 31, 2017, on more than two million mothers and live births. In order to gather comprehensive information on children and their parents, the Taiwan Birth Certificate Registration dataset was linked to the Maternal and Child Health Database of Taiwan ,utilizing the mother's identity, the children's sex, and the year of their birth as the key factors.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMaternal asthma history.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWe utilized the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), to define asthma cases; asthma was coded as 493 and the International Classification of Diseases, Tenth Revision (ICD-10) code J45.Mothers were categorized as having a lifelong asthma diagnosis from 2004 to 2018 if they received an asthma diagnosis at any time, whether it was before or after pregnancy.\u003c/p\u003e \u003cp\u003eThe diagnosis of asthma was made based on at least one inpatient record or at least three outpatients visiting. Maternal asthma exacerbations during pregnancy were defined if she sought inpatient care, visited the ER for problems linked to asthma or obtained an oral corticosteroid prescription. Mothers without documented asthma were categorized as \"non-asthmatic.\"\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Measures\u003c/h2\u003e \u003cp\u003eOffspring of asthmatic mother or non-asthmatic were tracked from birth until the occurrence of diagnoses related ASD, death ,or emigration, concluding at the end of the study in 2018. Diagnoses were established using the International Classification of Diseases, Ninth Revision (ICD-9) criteria for Autism Spectrum Disorder (ASD) (ICD-9 code 299,xx) and the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) criteria for ASD (ICD-10 code F840).Children who has diagnoses were defined as having at least 1 inpatient record or at least 3 outpatient visits. Children born to mothers diagnosed with asthma before childbirth were regarded as prenatally exposed to maternal asthma.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003ePrenatal variables that have been associated with ASD include advanced mother age, fetal distress, and gestational respiratory infections(Hisle-Gorman, Susi et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).A cohort study in Denmark suggested that Type 1 diabetes in the mother and rheumatoid arthritis during pregnancy were linked to the mental health of the children. (He, Yu et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)In the present study, covariates were categorized into a) maternal covariates b) offspring covariates, and c) paternal covariates. The selected maternal covariates include maternal smoking during pregnancy, parity, maternal age at delivery, and maternal physical and mental disorders preceding pregnancy (including ASD, ADHD, SLE, rheumatoid arthritis Preeclampsia, and gestational diabetes)(Hisle-Gorman, Susi et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Offspring covariates encompass gender, low birth weight (birth body weight lower than 2500 gm), year of birth, preterm birth (gestational age lower than 37 weeks), and low-income family status. As for paternal covariates, autoimmune diseases of father were utilized as the negative control exposure which includes paternal age at delivery, paternal physical and mental disorders before pregnancy (including ASD, ADHD, SLE, rheumatoid arthritis) (Estes and McAllister \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor descriptive statistics of categorical and continuous data, we employed frequency with percentage and mean with standard deviation, respectively. The Cox regression model was utilized to assess the risk of ASD in children born to parents with and without asthma. The model was adjusted for sociodemographic characteristics, physical and mental illnesses, parity, and birth weight.\u003c/p\u003e \u003cp\u003eTo investigate whether maternal asthma exacerbation during pregnancy had additional effects on child ASD, we conducted a comparison among siblings using conditional Cox proportional hazards regression with the biological mother as the stratum variable between siblings with and without acute asthma during pregnancy, with adjustment for covariates.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe conducted the data analysis from September 1, 2022, through January 30, 2023. This study encompassed 2,338,087 live births between January 1, 2004, and December 31, 2017, with 3.27% born to mothers with asthma during this period in Taiwan. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e provided specifics about the study participants\u0026apos; characteristics. Compared to mothers who were not asthmatic, mothers who had asthma had an increased chance of developing ADHD, ASD, or other immunological abnormalities. (i.e., systemic lupus erythematosus, rheumatoid arthritis, preeclampsia, and gestational diabetes). It was discovered that women who had asthma were more likely to be of lower social status and to smoke during pregnancy than mothers who did not have asthma.\u003c/p\u003e\n\u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline Characteristics of the Offspring According to Prenatal Exposure to Maternal asthma maternal covariates b) offspring covariates, and c) paternal covariates\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChildren with Non-\u003c/p\u003e\n \u003cp\u003easthmatic\u003c/p\u003e\n \u003cp\u003emothers\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChildren with Asthmatic mothers\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;2261625\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;76462\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaternal age at delivery (years)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e236623 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8850 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1568886 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49448 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e456116 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18164 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1305209 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39982 (52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e956416 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36480 (47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal smoking during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1076 (\u0026lt;\u0026thinsp;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow-income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136016 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5709 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal disorders before pregnancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33 (\u0026lt;\u0026thinsp;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (\u0026lt;\u0026thinsp;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e696 (\u0026lt;\u0026thinsp;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystemic Lupus Erythematosus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5278 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e387 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRheumatoid arthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5384 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e396 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12390 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e642 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e164327 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8041 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eAbbreviations: ASD, autism spectrum disorder; ADHD, attention deficit hyperactivity disorder\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eHR, hazard ratio; CI, confidence interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eOffspring covariates\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOffspring covariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreterm birth (gestational age \u0026lt;37 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e197040 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e8084 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow birth weight (\u0026lt;2500 g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e177960 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6834 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChild sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1177487 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e40121 (52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGirls\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1084138 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e36341 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.1 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePaternal covariates\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaternal age at delivery (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e83715 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3801 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25\u0026ndash;34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1293019 (57.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e41562 (54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e884891 (39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e31099 (40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaternal mental disorder before pregnancy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e55 (\u0026lt;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e9 (\u0026lt;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eADHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1245 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e94 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSystemic Lupus Erythematosus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e824 (\u0026lt;0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e41 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003erheumatoid arthritis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4774 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e176 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ASD, autism spectrum disorder; ADHD, attention deficit hyperactivity disorder\u003c/p\u003e\n\u003cp\u003eIn Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the result indicated that children whose mother had asthma were more likely to be born prematurely and to have low birth weights. Furthermore, children with asthmatic parents exhibited a significantly higher risk of developing ASD compared to those with non-asthmatic parents. Maternal asthma had an HR of 1.44 (95% confidence interval of 1.34 to 1.55), while paternal asthma had an HR of 1.12 (95% confidence interval of 1.03 to 1.22). Specifically, the HR for maternal asthma in boys with autism spectrum disorder was 1.36, with a 95% confidence interval ranging from 1.26 to 1.47. For girls, the HR was 1.52, with a range of 1.30 to 1.77.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRisk of ASD in children whose parents with asthma\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaternal asthmas\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePaternal asthmas\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaHR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaHR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.44 (1.34\u0026ndash;1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12 (1.03\u0026ndash;1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36 (1.26\u0026ndash;1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21 (1.11\u0026ndash;1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGirl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52 (1.30\u0026ndash;1.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08 (0.89\u0026ndash;1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAbbreviations: ASD, autism spectrum disorder; aHR, adjusted hazard ratio; CI, confidence interval.\u003c/p\u003e\n\u003cp\u003eAdjusted for parental age, and parental diagnosis (i.e., autism spectrum disorder, ADHD, systemic lupus erythematosus, rheumatoid arthritis preeclampsia, gestational diabetes), parity, low-income status, preterm birth and low birth weight\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e illustrated that only mothers with asthma who have had at least two pregnancies\u0026mdash;one complicated by asthma exacerbations during pregnancy and the other not\u0026mdash;and who have sibling control are only eligible. Surprisingly, acute asthma exacerbation during pregnancy did not appear to significantly affect the likelihood of having mor children with ASD in any distinctive way (Adjusted HR 1.23, 95% CI: 0.68\u0026ndash;2.24).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSibling comparisons of risk of ASD among children whose mother with asthma exacerbation during pregnancy\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiscordant pairs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber Exposed to asthma during pregnancy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eevent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber Unexposed to asthma during pregnancy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eevent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted HR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23 (0.68\u0026ndash;2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviations: ASD, autism spectrum disorder; aHR, adjusted hazard ratio; CI, confidence interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAdjusted for parental age, and parental diagnosis (i.e., autism spectrum disorder, ADHD, systemic lupus erythematosus, rheumatoid arthritis preeclampsia, gestational diabetes), parity, low-income status, preterm birth and low birth weight.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this population-based cohort study, which included 2,338,087 newborn births, children born to parents who have asthma were more likely to have ASD, with the risk being greater for maternal asthma. Moreover, there was no discernable relationship between the chance of ASD in the kids and the mother's aggravation of asthma during pregnancy, even after accounting for siblings.\u003c/p\u003e \u003cp\u003eOur results support previous studies that have suggested, a connection between maternal asthma and ASD in offspring. In a case-control study involving 2095 controls and 407 cases. It was observed that 10.3% of case women and 8.2% of control mothers were diagnosed with an autoimmune disorder in the four years preceding pregnancy. Specifically maternal asthma in the second trimester was associated with a more than 2-fold increased incidence of ASD(Croen, Grether et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Similarly, in a cohort of 363 ASD children, the prevalence of immunological disorder particularly maternal asthma was notable. Compared to girls, there was a higher likelihood of maternal immunological disorders in boys with ASD. (p\u0026thinsp;=\u0026thinsp;0.009) (Patel, Dale et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) These findings were supported by a case-control study in Sweden, demonstrating an increased risk of developing ASD in offspring among asthmatic mother after adjusting for shared familial factors. The point estimates showing the connection between maternal asthma and the probability that offspring will receive an ASD diagnosis were similar in the analyses carried out within extended families, regardless of the kind of family structure. The adjusted odds ratio (OR) was 1.20 (95% CI 0.80\u0026ndash;1.81) for half-siblings, 1.28 (95% CI 1.16\u0026ndash;1.41) for full-cousins, and 1.30 (95% CI 1.10\u0026ndash;1.54) for half-cousins. Prenatal exposure to asthma medications was not linked to later autism spectrum disorders in subjects whose mothers had asthma. (Gong, Lundholm et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eOne meta-analysis investigated the association between maternal illness during pregnancy and a higher incidence of ASD in offspring (OR\u0026thinsp;=\u0026thinsp;1.13, with 95% confidence interval : 1.03\u0026ndash;1.23). It was suggested that pathogens may directly affect the developing brain or that inflammation may indirectly affect it (Jiang, Xu et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, other studies have indicated that the results observed in the children may be due to maternal immune activation rather than the infection itself(Boulanger-Bertolus, Pancaro et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditional evidence from the CHildhood Autism Risk from Genetics and the Environment study (CHARGE study) suggests that neurodevelopment of the offspring may be influenced by the mother's immune system. In an analysis involving 560 cases of ASD, 391 cases of typically developing controls, and 168 cases of developmental delay (DD) history, researchers examined whether maternal autoimmune diseases were associated with ASD. ASD alone did not show a substantially link with maternal autoimmune illness. However, the combined ASD\u0026thinsp;+\u0026thinsp;DD risks were considerably increased by maternal autoimmune disease (OR\u0026thinsp;=\u0026thinsp;1.46, 95% CI 1.01, 2.09)(Lyall, Ashwood et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne theory about the pathophysiology of neurodevelopmental problems (such as ASD and ADHD) is the involvement of maternal immune activation (MIA). (.(Han, Patel et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) Furthermore, studies have demonstrated a strong connection between ADHD and ASD and elevated levels of inflammatory cytokines.(Theoharides, Tsilioni et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Donfrancesco, Nativio et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn addition, fever\u0026mdash;a typical indicator of inflammation\u0026mdash;has been linked to a higher chance of ASD in children, especially if it happens in the second trimester, indicating that the timing of MIA is crucial.(Hornig, Bresnahan et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). An fundamental concept regarding the relationship between ASD and maternal asthma posits that the presence of maternal asthma may impact fetal development by inducing changes in immunological responses within the central nervous system. These changes could result in neuronal damage, potentially increasing the likelihood of children developing ASD.(Gong, Lundholm et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) As a final note, MIA during pregnancy has been linked to an increased incidence of ASD(Ornoy, Weinstein-Fudim et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the MIA model for ASD, specific cytokines levels were found to be elevated in the fetal brain, amniotic fluid, maternal serum, and placenta(Hsiao and Patterson \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, Knuesel, Chicha et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Meyer \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Choi, Yim et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).In comparison to controls, individuals with ASD generally exhibited significantly higher amniotic fluid levels of IL-4, IL-10, TNF-ɑ, and TNF- \u0026szlig; in patients with ASD. (Abdallah, Larsen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Animal models confirm this relationship, demonstrating that maternal immune activation alone is sufficient to transfer permanent neuropathologic behaviors in offspring.(Estes and McAllister \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, exacerbations of the mother's asthma during pregnancy have been associated with a higher likelihood of ADHD in the offspring.(Cowell, Bellinger et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Liu, Dalsgaard et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Notably, the risk of ADHD was unaffected by the frequency of exacerbations. Similarly, other researchers discovered a correlation between maternal asthma exacerbations during pregnancy and ADHD.(Liu, Dalsgaard et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) However, no previous research has illustrated a direct link between asthma exacerbations in pregnant mothers and an increased risk of ASD in their progeny. Using the sibling control method, we investigated this issue in our study and found no association between asthma exacerbations in expectant mothers and an increased risk of ASD in children.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe current study has a number of advantages. Firstly, recall bias was minimized by using prospectively gathered registry data. Secondly, with a sample size exceeding 2\u0026nbsp;million births,encompassing all live births in Taiwan, rreduce the risk of selection bias. Lastly, the availability of comprehensive sociodemographic and clinical information allowed for the correction for the various confounding factors ,particularly through sibling control for acute exacerbation during pregnancy.\u003c/p\u003e \u003cp\u003eThe research comes with certain limitations. Initially, we identified asthma patients using the ICD, requiring at least one hospitalization or at least three outpatient diagnoses. This approach may lead to an underestimation, as individuals without diagnosed asthma would not be accounted for. Consequently, not all individuals with asthma exacerbations would be admitted to a hospital, go to the emergency room, or get an oral corticosteroid prescription filled. They would have been mistakenly categorized as not experiencing exacerbations. Our exposure group and comparison group will be comparable as a result of these misclassifications, yielding a null result. Moreover, only the most severe ASD cases may be listed in the hospital registry and prescription registration, which restricts generalizability.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study showed that maternal asthma but not exacerbation of asthma during pregnancy was associated to offspring ASD. Further research is required to elucidate the mechanisms underlying these associations and clarify how genetic susceptibilities may interact with environmental factors to influence disease risk. Further research is needed for better understanding of these pathways to the prevention and treatment of ASD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYi-Feng Ho, MD、Chiao-Fan Lin, MD\u003cstrong\u003e:\u003c/strong\u003e Conception and design of the study, acquisition and analysis of data, drafting the manuscript, contribution to manuscript writing, and app roval of the final manuscript.\u003c/p\u003e\n\u003cp\u003eVincent Chin-Hung Chen, MD ,PhD: Patient recruitment, clinical assessments ,acquisition of data interpretation of data, study coordination, critical revision of the manuscript for important intellectual content, and final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003eYi-Lung Chen, PhD: Statistical analysis, data interpretation, and drafting sections of the manuscript, and final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003eTsai-Ching Hsu, PhD: Study supervision , critical revision of the manuscript, and final approval of the version to be published.\u003c/p\u003e\n\u003cp\u003eAll authors: Contributed to the writing and review of the manuscript, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Statement:\u003c/strong\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Chang Gung Medical Foundation (Date2020.05.25/ No.202000880B0).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e The authors declare no conflicts of interest related to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was supported by grant from the Chang Gung Memorial Hospital (CMRPG3K1121). The present study was based on the National Health Insurance Research Database provided by the Central Bureau of National Health Insurance, the Department of Health, and managed by the National Health Research Institutes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e The data supporting the findings of this study are available within the article. Further inquiries can be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdallah, M. W., N. Larsen, J. 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Kuo (2010). \u0026quot;An overview of the healthcare system in Taiwan.\u0026quot; \u003cu\u003eLondon J Prim Care (Abingdon)\u003c/u\u003e \u003cstrong\u003e3\u003c/strong\u003e(2): 115-119.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"asthma, pregnancy, maternal, autism spectrum disorder","lastPublishedDoi":"10.21203/rs.3.rs-4493797/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4493797/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eThe connection between autism spectrum disorder (ASD) and maternal asthma has drawn researchers\u0026rsquo; interest. The connection between maternal asthma exacerbation and the development of ASD in offspring remains unclear. The aim of this study was to investigate the association between maternal asthma, including asthma exacerbation during pregnancy, and the risk of ASD in offspring.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eInformation from over two million mothers and their live newborns, collected from the Taiwan Birth Certificate Registry spanning from January 1, 2004, to December 31, 2017, was utilized in this nationwide cohort study based on the population. The Cox regression model was employed to assess the risk of ASD in children between mothers with and without asthma. The analysis adjusted for sociodemographic characteristics, parity, birth weight, and parents\u0026rsquo; physical and mental illnesses. Sibling control was implemented to investigate the impact of asthma exacerbation during pregnancy on the risk of offspring ASD.\u003c/p\u003e\u003ch2\u003eResult:\u003c/h2\u003e \u003cp\u003eChildren with asthmatic parents face a significantly higher risk of developing ASD compared to those with non-asthmatic parents. Maternal asthma had an HR of 1.44 ( 95% confidence interval of 1.34 to 1.55), while paternal asthma had an HR of 1.12 ( 95% confidence interval of 1.03 to 1.22). Interestingly, acute asthma exacerbations during pregnancy didn't seem to affect the likelihood of having more ASD children in a distinctive way (Adjusted HR 1.23, 95% CI: 0.68\u0026ndash;2.24).\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eOffspring born to parents with asthma face an elevated risk of having ASD, with a higher risk associated maternal asthma. There was no obvious correlation between mother asthma exacerbations during pregnancy and the likelihood of ASD in the offspring.\u003c/p\u003e","manuscriptTitle":"Autism Spectrum Disorder in Offspring of Maternal asthma occurrence, and exacerbations during pregnancy: a population-based cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 10:48:28","doi":"10.21203/rs.3.rs-4493797/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"907d60d5-1823-473a-8c61-a265c1bc5b8f","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T13:23:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 10:48:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4493797","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4493797","identity":"rs-4493797","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}