Prenatal and Perinatal Risk Factors Associated with Autism Spectrum Disorder: A National Cohort Study

Prenatal and Perinatal Risk Factors Associated with Autism Spectrum Disorder: A National Cohort Study | 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 Research Article Prenatal and Perinatal Risk Factors Associated with Autism Spectrum Disorder: A National Cohort Study Joško Osredkar, Uroš Godnov This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8333327/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a multifactorial etiology involving both genetic and environmental factors. While genetic risks are well-characterized, the contribution of specific prenatal and perinatal environmental exposures remains less understood. This study aimed to comprehensively investigate pregnancy-related and birth complications associated with ASD in a large, population-based national cohort. Methods We conducted a retrospective cohort study of all singleton pregnancies delivered in Slovenia between 2005 and 2017 (N = 302,476). We identified 117 children with a confirmed clinical diagnosis of ASD and compared them to the remaining 302,322 pregnancies. Data were obtained from the National Perinatal Information System. We analyzed maternal demographics, medication exposures, obstetric complications, and neonatal outcomes using logistic regression to calculate odds ratios (OR) with 95% confidence intervals (CI). Results ASD cases showed a profound male predominance (83.7% vs. 51.4%; OR 4.88, 95% CI: 2.98–7.97). Early preterm birth (< 31 weeks) was significantly more frequent in the ASD group (4.2% vs. 1.4%; OR 3.14, 95% CI: 1.28–7.70). Postpartum hemorrhage risk was nearly tripled in mothers of children with ASD (6.0% vs. 2.3%; OR 2.70, 95% CI: 1.26–5.81). Neonatal respiratory morbidity was strongly associated with ASD, including Respiratory Distress Syndrome (RDS) (OR 3.42, 95% CI: 1.67–7.02), transient tachypnea of the newborn (OR 3.90, 95% CI: 1.44–10.57), and surfactant administration (OR 6.55, 95% CI: 2.08–20.65). Antenatal dexamethasone exposure was also elevated (OR 3.67), likely reflecting confounding by indication for threatened preterm labor. Conclusions In this national cohort, male sex, extreme prematurity, placental hemorrhage, and neonatal respiratory complications were robust risk factors for ASD. These findings implicate placental dysfunction and perinatal hypoxia-ischemia as key mechanistic pathways in neurodevelopmental vulnerability. While observational data cannot prove causality, the strong associations with markers of hypoxia suggest that optimizing perinatal respiratory management and placental health may be relevant for ASD prevention. Trial registration: 0120–201/2016-2 KME 78/03/16; 3 February 2021 Autism spectrum disorder Cohort study Preterm birth Perinatal hypoxia Placental dysfunction Epidemiology Figures Figure 1 Figure 2 1. Background Autism spectrum disorder (ASD) represents a heterogeneous group of neurodevelopmental conditions characterized by persistent deficits in social communication and interaction across multiple contexts, along with restricted, repetitive patterns of behavior, interests, or activities that manifest early in the developmental period and cause clinically significant impairment in social, occupational, or other important areas of functioning ( 1 ). The global prevalence of ASD has increased substantially over recent decades, with current estimates ranging from 1% to 2% of children in developed countries, though this rise likely reflects improved recognition, broadened diagnostic criteria, and enhanced surveillance rather than solely increased incidence ( 2 ). One of the most consistent and striking epidemiological features of ASD is its pronounced male predominance, with male-to-female ratios typically ranging from 3:1 to 4:1 across populations ( 3 , 4 ). This sex bias represents a critical clue to underlying etiology and has prompted extensive research into biological mechanisms that may confer differential vulnerability or protection based on sex. The etiology of ASD is recognized as multifactorial, involving complex interactions between genetic susceptibility and environmental influences during critical windows of neurodevelopment. Twin and family studies have established that ASD has substantial heritability, with concordance rates in monozygotic twins reaching 60–90% and recurrence risk in siblings elevated 10–20 fold compared to the general population ( 5 ). Genome-wide association studies and exome sequencing have identified hundreds of common genetic variants and dozens of rare mutations that contribute to ASD risk, affecting genes involved in synaptic function, chromatin remodeling, transcriptional regulation, and neuronal migration. However, genetic factors alone cannot fully account for ASD etiology, as even monozygotic twins show incomplete concordance and the rapid increase in diagnosed prevalence suggests important environmental contributions. Environmental risk factors implicated in ASD etiology span the prenatal, perinatal, and early postnatal periods, with particular emphasis on exposures that may disrupt critical neurodevelopmental processes during vulnerable windows. Proposed prenatal risk factors include advanced parental age, maternal metabolic conditions (diabetes, obesity), maternal psychiatric disorders, maternal infections and inflammatory conditions, exposure to certain medications (valproate, selective serotonin reuptake inhibitors), vitamin D insufficiency, and environmental toxicants (air pollution, pesticides) ( 6 ). Perinatal and neonatal risk factors that have been investigated include gestational complications (preeclampsia, placental abnormalities), birth asphyxia, prematurity, low birth weight, neonatal jaundice, and need for intensive respiratory support ( 7 – 10 ). Among the proposed environmental risk factors, perinatal hypoxia-ischemia has emerged as a particularly compelling mechanistic candidate based on converging evidence from human epidemiological studies, animal models, and mechanistic investigations. Hypoxic-ischemic injury during critical windows of brain development can disrupt oxygen-dependent processes including synaptogenesis, neuronal migration, myelination, programmed cell death, and establishment of neural circuits ( 11 ). Additionally, hypoxia triggers oxidative stress—an imbalance between pro-oxidant and antioxidant systems leading to accumulation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) that damage cellular macromolecules including lipids, proteins, and DNA ( 12 ). Multiple studies have documented elevated markers of oxidative stress in individuals with ASD, including decreased glutathione levels, increased lipid peroxidation products (malondialdehyde), and altered antioxidant enzyme activities ( 13 ). Furthermore, oxidative stress can activate inflammatory cascades, disrupt mitochondrial function, alter epigenetic regulation, and impair the blood-brain barrier—all of which have been implicated in ASD pathophysiology ( 14 ). Placental dysfunction represents another critical pathway through which prenatal complications may influence fetal brain development and contribute to ASD risk. The placenta serves not merely as a passive conduit for nutrient and gas exchange, but as an active endocrine and immunological organ that senses maternal physiological and environmental signals and modulates fetal exposure accordingly. Placental abnormalities identified in association with ASD include abnormal trophoblast inclusions, inflammatory changes (fetal inflammatory response syndrome or FIRS), vascular malperfusion, and altered expression of genes involved in steroid hormone metabolism and immune regulation ( 15 , 16 ). Placental inflammation has been specifically linked to increased risk of ASD diagnosis, with children born with placentas meeting criteria for FIRS showing significantly elevated odds of developing autism, attention-deficit/hyperactivity disorder, and other psychiatric conditions ( 17 , 18 ). Mechanistically, placental inflammation may alter the balance of pro-inflammatory and anti-inflammatory cytokines transferred to the fetal circulation, disrupt the development of hematopoietic stem cells that later populate the brain as microglia, modify steroid hormone levels that influence sexual differentiation of the brain, and impair nutrient and oxygen delivery to the developing fetus. The placenta also exhibits sexual dimorphism, with male and female placentas differing in gene expression patterns, steroid production, inflammatory responses, and vulnerability to complications. Male placentas produce higher levels of steroid hormones, are more vulnerable to early pregnancy complications, and show different responses to maternal immune activation compared to female placentas ( 19 ). These sex-specific placental characteristics may partially mediate the male predominance observed in ASD by creating differential exposure to hormones and inflammatory mediators during critical periods of brain sexual differentiation ( 5 , 20 ). Maternal immune activation (MIA) during pregnancy has received substantial attention as a potential contributor to ASD risk based on animal models showing that immune challenges during pregnancy can produce ASD-like behaviors in offspring through placental transmission of inflammatory cytokines ( 20 ). In humans, maternal infections during pregnancy, particularly in the first and second trimesters, have been associated with modest increases in ASD risk in some but not all studies. Meta-analyses show an overall odds ratio of 1.13–1.32 for maternal infection during pregnancy, with stronger associations for hospitalized infections (OR 1.30–1.48) ( 21 , 22 ). The effects of MIA appear to be sex-specific, with male offspring showing greater vulnerability to immune-mediated neurodevelopmental disruption than females. Recent studies have demonstrated that MIA produces differential effects on placental and fetal brain cytokine profiles in male versus female offspring, with males showing higher placental levels of pro-inflammatory cytokines (GM-CSF, IL-6, TNF-α) and sex-specific alterations in genes related to synaptic development ( 20 ). Prenatal sex steroid hormones, particularly testosterone and estrogens, play critical roles in sexual differentiation of the brain and have been proposed as mediators of sex differences in ASD vulnerability through mechanisms including the "extreme male brain" theory ( 23 ). This hypothesis suggests that elevated prenatal testosterone exposure may underlie autistic traits, supported by evidence that amniotic fluid testosterone levels correlate with later autistic traits and that conditions involving androgen excess (such as polycystic ovary syndrome) are associated with increased ASD risk in offspring. However, the relationship between prenatal hormones and ASD is complex and likely involves interactions with genetic factors, placental function, and other environmental exposures ( 24 , 25 ). Despite extensive research, the specific contribution of obstetric complications and perinatal events to ASD risk remains debated. Many reported associations are subject to potential confounding by familial factors—that is, shared genetic or environmental characteristics within families that predispose to both pregnancy complications and offspring neurodevelopmental disorders. Recent large-scale sibling-comparison studies have demonstrated that many prenatal risk factor associations with ASD are substantially attenuated or eliminated when comparing affected and unaffected siblings within the same family, suggesting that apparent associations may reflect familial confounding rather than direct causal effects ( 26 – 29 ). For example, a Danish study of over 1.1 million children found that while 30 maternal diagnoses during pregnancy showed associations with offspring ASD in population-level analyses, most associations disappeared in within-family comparisons, indicating that shared familial factors rather than direct exposure effects explained the majority of observed associations ( 10 ). Preterm birth represents one of the most extensively studied perinatal risk factors for ASD, with meta-analyses reporting elevated risk particularly for extreme prematurity (birth < 28 weeks gestation), though findings have been inconsistent and effect sizes modest after adjustment for confounders ( 30 ). The mechanisms through which prematurity might influence ASD risk are multifactorial and include: ( 1 ) interruption of critical third-trimester brain development when rapid cortical expansion, synaptogenesis, and myelination occur ( 31 , 32 ); ( 2 ) exposure to neonatal intensive care interventions including mechanical ventilation, oxygen therapy, and medications that may have neurodevelopmental impacts ( 33 , 34 ); ( 3 ) increased risk of intraventricular hemorrhage, periventricular leukomalacia, and other forms of brain injury ( 35 – 37 ); ( 4 ) prolonged exposure to stress hormones and inflammation ( 31 ); and ( 5 ) underlying maternal-fetal conditions that precipitate preterm delivery and may independently affect brain development ( 10 ). The relationship between prematurity and ASD is further complicated by the fact that extremely premature infants face elevated risk for multiple neurodevelopmental disabilities including intellectual disability, cerebral palsy, attention deficits, and learning disorders, making it challenging to isolate specific risk for autism independent of global developmental delay ( 38 , 39 ). Additionally, recent analyses suggest that the association between preterm birth and ASD may be confounded by familial factors, as sibling studies show attenuated effects ( 10 , 30 , 40 , 41 ). Respiratory complications in the immediate newborn period, including respiratory distress syndrome (RDS), transient tachypnea of newborn (TTN), need for mechanical ventilation, and surfactant administration, represent markers of perinatal compromise that may involve hypoxic-ischemic injury to the developing brain. RDS, caused by surfactant deficiency in immature lungs, results in impaired gas exchange and can lead to both hypoxemia (low blood oxygen) and hyperoxia (excessive oxygen exposure during treatment), both of which generate oxidative stress and can damage vulnerable brain structures (42–44). Animal models demonstrate that even brief periods of hypoxia during critical developmental windows can produce lasting alterations in brain structure, neurochemistry, and behavior reminiscent of ASD ( 45 , 46 ). In humans, markers of perinatal hypoxia including low Apgar scores, umbilical cord complications, fetal distress, and need for resuscitation have been associated with increased ASD risk in multiple studies ( 47 – 50 ). Maternal hemorrhage and placental complications such as placental abruption, preeclampsia, and placental insufficiency have been linked to ASD risk through mechanisms involving chronic fetal hypoxia, inflammatory signaling, and impaired nutrient delivery ( 51 ). Preeclampsia, characterized by maternal hypertension and proteinuria, is associated with placental vascular abnormalities that compromise uteroplacental blood flow, potentially resulting in fetal growth restriction and chronic oxygen deprivation ( 52 ). A large case-control study found significantly elevated ASD risk among children born to mothers with preeclampsia or other indicators of placental insufficiency, with children with ASD twice as likely to have been exposed to preeclampsia in utero (adjusted OR 2.36; 95% CI 1.18–4.68), and risk increasing in proportion to preeclampsia severity ( 51 ). Antenatal corticosteroid administration for fetal lung maturation in threatened preterm labor represents a ubiquitous intervention in high-risk obstetrics, with established benefits for reducing neonatal respiratory morbidity and mortality ( 53 ). However, concerns have been raised about potential long-term neurodevelopmental effects of glucocorticoid exposure during critical windows of brain development, based on animal studies showing that prenatal corticosteroids can alter neuronal differentiation, synaptic pruning, stress axis programming, and behavior ( 54 – 56 ). Human follow-up studies of single-course antenatal corticosteroids administered at appropriate gestational ages have generally been reassuring, showing no adverse effects on cognitive development or psychiatric outcomes ( 57 – 59 ). However, observational studies have reported associations between antenatal corticosteroid exposure and increased risk of mental and behavioral disorders, though these findings are likely confounded by the underlying pregnancy complications necessitating treatment ( 60 – 62 ). A 2025 Danish cohort study of 1.06 million infants reported that prenatal glucocorticoid exposure was associated with higher risk of some mental disorders; however, the study explicitly acknowledges that confounding cannot be ruled out and that disease severity could not be controlled for in comparisons of offspring born to mothers with vs without the same underlying illness. Notably, this Danish study included all systemic glucocorticoids (including chronic prednisolone for autoimmune/inflammatory conditions) rather than being limited to acute antenatal betamethasone/dexamethasone for preterm prevention. A quasi-experimental study that compared children born just before vs just after the clinical cutoff for antenatal corticosteroid administration (thereby comparing high-probability vs minimal exposure while minimizing confounding by indication) found little evidence of increased ADHD risk in the exposed group, providing reassurance that confounding by indication likely explains the associations observed in purely observational studies. These conflicting findings underscore the challenge of disentangling causal effects of antenatal corticosteroids from confounding by the severe pregnancy complications (preterm labor, preeclampsia, maternal infection) that necessitate their administration—complications that themselves carry substantial risks for offspring neurodevelopmental disorders ( 61 ). Despite decades of research, fundamental questions remain regarding which prenatal and perinatal exposures represent genuine causal contributors to ASD versus markers of underlying familial susceptibility, how these environmental factors interact with genetic variants to modify risk, what biological mechanisms mediate observed associations, and whether modifiable risk factors exist that could serve as targets for preventive interventions. Large, population-based cohort studies with comprehensive exposure assessment, long-term neurodevelopmental follow-up, and appropriate control for confounding are essential to address these questions. 2. Materials and Methods 2.1 Aim of the Study The primary aim of this study was to comprehensively investigate prenatal and perinatal risk factors associated with autism spectrum disorder in offspring using a large, national birth cohort. Specific objectives were to: Compare maternal demographic characteristics and pregnancy exposures (including medications) between mothers of children with ASD and control pregnancies Assess the prevalence of obstetric complications and delivery outcomes in ASD versus control groups Evaluate neonatal characteristics and early morbidity patterns, with particular focus on respiratory complications as markers of perinatal hypoxia Calculate odds ratios and confidence intervals for significant risk factors to quantify the magnitude of associations Interpret findings in the context of contemporary understanding of ASD etiology, including potential biological mechanisms and considerations of causality versus confounding Form subgroups for autism and high functional autism and compare results We hypothesized that ASD cases would demonstrate elevated rates of extreme prematurity, perinatal hypoxic events (reflected in respiratory complications), and obstetric complications compared to controls, and that these associations would remain significant after accounting for maternal age and other demographic factors. 2.2 Study Design and Setting This was a retrospective, population-based cohort study using data from the Slovenian National Perinatal Information System, which prospectively records all deliveries in Slovenia. The cohort included all singleton pregnancies delivered between 1 January 2005 and 31 December 2017, providing near-complete national coverage of births during this 12-year period. 2.3 Study Population and Case Ascertainment The source population comprised 302,476 singleton pregnancies recorded in the national registry during the study period. Children with autism spectrum disorder (ASD) were identified through linkage with national clinical diagnostic records using ICD-10 codes corresponding to autism spectrum conditions, including childhood autism and Asperger syndrome, subsequently harmonized into a single ASD category according to DSM-5 criteria. The final ASD group included 117 children with a confirmed clinical diagnosis of ASD, while all remaining singleton births without ASD formed the comparison group (“all others”; n = 302,322). 2.4 Data Sources and Variables Perinatal data were obtained from standardized registry fields completed at delivery, including maternal characteristics, pregnancy complications, delivery variables, and neonatal outcomes. Maternal variables included age, use of selected medications during pregnancy (dexamethasone, iron supplements, folic acid, antihypertensives, and thyroid medications), and obstetric complications such as postpartum hemorrhage. Pregnancy and delivery variables included gestational age at birth, mode of delivery (vaginal vs cesarean section), onset of labor (spontaneous vs induced), and occurrence of preterm birth defined as delivery before 37 completed weeks, with a predefined subgroup of early preterm birth before 31 weeks. Neonatal variables included sex, small for gestational age (SGA), respiratory distress syndrome (RDS), transient tachypnea of the newborn (TTN), need for mechanical ventilation, surfactant administration, and use of early intervention services documented in the registry. 2.5 Definitions of Exposures and Outcomes Preterm birth was defined as delivery at gestational age < 37 weeks, and early preterm birth as 500 mL following delivery. SGA was recorded when birth weight was below the gestational age– and sex-specific threshold used in the national perinatal system. Neonatal respiratory morbidity included RDS, TTN, requirement for mechanical ventilation, and surfactant administration as recorded by attending clinicians. Early intervention services captured referrals to developmental or rehabilitative services in early childhood as coded in the linked registry data. 2.6 Statistical Analysis Maternal age was analyzed as a continuous variable and summarized as mean ± standard deviation, while all other variables were analyzed as categorical percentages. Group comparisons between ASD cases and all other pregnancies used chi-square tests for categorical variables and analysis of variance (ANOVA) for continuous variables. Crude odds ratios (OR) with 95% confidence intervals (CI) were calculated using logistic regression to quantify associations between ASD and each exposure, with ASD as the outcome and the “all others” group as the reference. A two-sided p-value < 0.05 was considered statistically significant. All analyses were performed using MedCalc statistical software (MedCalc Software Ltd., Ostend, Belgium). 2.7 Ethical Considerations The registry-based component of this study was approved by the National Institute of Public Health responsible for registry-data approvals (approval number: [968- 1 0O/1 8 − 1 /007]) on 26th February 2018. The analysis was conducted on fully anonymized data extracted from the National Perinatal Information System and linked health records. In line with national regulations and the terms of this approval, individual informed consent was not required, and a waiver of consent was granted for this retrospective use of anonymized registry data. All procedures complied with national regulations on personal data protection and with the principles of the Declaration of Helsinki. 3. Results The demographic characteristics, medication exposures, and obstetric and neonatal outcomes for the ASD group (n = 117) compared to the general population (n = 302,322) are summarized in Table 1 . Table 1 Maternal, Obstetric, and Neonatal Characteristics by Study Group Comparison of maternal demographics, pregnancy complications, medication use, delivery outcomes, and neonatal interventions among autism spectrum disorder (ASD), control, and all other pregnancies (n = 302,476). Variable ASD (n = 117) All Others (n = 302,322) p-value OR (95% CI) Demographics Maternal age (mean ± SD) 30.03 ± 4.59 29.55 ± 4.80 0.180 – Medication use (%) Dexamethasone 9.6 2.8 – – Iron supplements 49.7 41.8 – – Folic acid 66.2 64.7 – – Antihypertensives 1.7 1.4 – – Thyroid medications 0.8 1.4 – – Obstetric outcomes (%) Preterm birth (< 37 weeks) 13.7 7.6 0.021* 1.93 (1.14–3.26) Early preterm ( 500 mL) 6.0 2.3 0.019* 2.70 (1.26–5.81) Cesarean section 26.5 18.0 0.023* 1.64 (1.09–2.48) Spontaneous labor 76.1 73.8 – – Neonatal outcomes (%) Male sex 83.7 51.4 < 0.001*** 4.88 (2.98–7.97) Small for gestational age (SGA) 7.7 5.2 – – Ventilation required 2.5 0.8 0.105 3.26 (1.04–10.27) Surfactant administration 2.5 0.4 0.003** 6.55 (2.08–20.65) Respiratory distress syndrome (RDS) 6.8 2.1 0.001** 3.42 (1.67–7.02) Transient tachypnea of newborn (TTN) 3.4 0.9 0.017* 3.90 (1.44–10.57) Early intervention services 12.8 4.7 < 0.001*** 2.98 (1.73–5.13) *p < 0.05; **p < 0.01; ***p < 0.001. OR = Odds ratio comparing ASD versus All Others. CI = Confidence interval. 3.1 Results: Detailed Interpretation This study enrolled 117 children with autism spectrum disorder (ASD). Comprehensive prenatal and perinatal data were extracted from the National Registry for a study group as well as for the entire cohort of 302,476 singleton pregnancies delivered during the 2005–2017 period. This design enabled comparison of ASD cases against the broader population to identify prenatal and perinatal risk factors associated with autism diagnosis. 3.1.1 Demographics Maternal age showed no significant difference across groups (ASD: 30.03 ± 4.59 years; All others: 29.55 ± 4.80 years; p = 0.180), eliminating advanced maternal age as a confounding variable in this cohort and suggesting that observed associations operate independently of maternal age effects. 3.1.2 Medication Exposure Patterns Dexamethasone use was 3.4-fold higher in ASD pregnancies (9.6%) compared to the general cohort (2.8%), reflecting increased obstetric interventions for threatened preterm labor requiring fetal lung maturation. This association likely represents confounding by indication rather than direct neurodevelopmental toxicity, as dexamethasone administration signals high-risk pregnancies with impending preterm delivery. Iron supplementation was slightly elevated in ASD (49.7% vs 41.8%), possibly indicating higher maternal anemia prevalence. 3.1.3 Obstetric Complications and Delivery Outcomes Preterm birth demonstrated a dose-response relationship with ASD risk. Overall preterm delivery (< 37 weeks) occurred in 13.7% of ASD pregnancies versus 7.6% in all others (p = 0.021; OR = 1.93, 95% CI: 1.14–3.26), representing a near-doubling of risk. More strikingly, early preterm birth (< 31 weeks) was three times more frequent in ASD (4.2% vs 1.4%; p = 0.024; OR = 3.14, 95% CI: 1.28–7.70). This pronounced association at extremes of prematurity aligns with neurobiological plausibility: birth before 31 weeks disrupts critical third-trimester neurodevelopmental processes including cortical organization, synaptogenesis, myelination, and establishment of neural circuits. Postpartum hemorrhage (> 500 mL) was 2.7-fold higher in ASD pregnancies (6.0% vs 2.3%; p = 0.019; OR = 2.70, 95% CI: 1.26–5.81), implicating placental dysfunction, abnormal trophoblast invasion, or coagulation abnormalities that compromise uteroplacental perfusion and fetal oxygenation. Maternal bleeding complications may reflect underlying inflammatory or thrombotic disorders affecting placental function and fetal brain development. Cesarean section rates were significantly elevated in ASD (26.5% vs 18.0%; p = 0.023; OR = 1.64, 95% CI: 1.09–2.48), though this association may reflect underlying obstetric complications necessitating surgical delivery rather than mode of delivery per se contributing to ASD risk. 3.1.4 Neonatal Characteristics and Respiratory Morbidity The most striking finding was pronounced male predominance in ASD: 83.7% of cases were male compared to 51.4% in the general population (p < 0.001; OR = 4.88, 95% CI: 2.98–7.97). This nearly 5-fold increase in odds exceeds the typically reported 3–4:1 male-to-female ratio in ASD epidemiology, potentially reflecting diagnostic ascertainment bias, female protective factors, or genuine sex-specific vulnerability to prenatal insults mediated by sex chromosomes and hormonal influences. Respiratory complications emerged as a dominant cluster of neonatal risk factors: Respiratory distress syndrome (RDS): 6.8% vs 2.1% (p = 0.001; OR = 3.42, 95% CI: 1.67–7.02) Transient tachypnea of newborn (TTN): 3.4% vs 0.9% (p = 0.017; OR = 3.90, 95% CI: 1.44–10.57) Surfactant administration: 2.5% vs 0.4% (p = 0.003; OR = 6.55, 95% CI: 2.08–20.65) Mechanical ventilation: 2.5% vs 0.8% (p = 0.105; OR = 3.26, 95% CI: 1.04–10.27) These findings strongly implicate perinatal hypoxia-ischemia as a mechanistic contributor to ASD risk. Recent research demonstrates that markers of perinatal oxygen deprivation—including RDS, low Apgar scores, umbilical cord complications, and need for respiratory support—are robustly associated with increased ASD risk. Experimental models reveal that even transient hypoxia during critical neurodevelopmental windows disrupts synaptogenesis, alters cortical organization, damages subcortical structures (particularly thalamus and basal ganglia), and triggers persistent neuroinflammatory cascades. The 6.5-fold increase in surfactant requirement represents the highest odds ratio among all measured outcomes, emphasizing the severity of respiratory compromise in ASD-associated pregnancies. Early intervention services were utilized 2.7-fold more frequently in ASD (12.8% vs 4.7%; p < 0.001; OR = 2.98, 95% CI: 1.73–5.13), reflecting both the developmental needs of children who will later receive autism diagnoses and potentially earlier recognition of developmental concerns prompting timely referral. To visualize the magnitude and pattern of significant risk factor associations identified in our study, Fig. 1 presents a comparative analysis of nine key pregnancy and birth outcomes that demonstrated statistical significance (p < 0.05) when comparing the ASD group to the general population cohort. This graphical representation serves several analytical purposes: it illustrates the breadth of affected domains (extreme prematurity, obstetric hemorrhage, and neonatal respiratory complications), demonstrates the dose-response relationship for prematurity outcomes, highlights the remarkable male sex predominance in ASD, and quantifies the magnitude of increased risk across outcomes of varying clinical severity. Figure 1 displays nine outcomes organized into four thematic categories: ( 1 ) Prematurity outcomes (early preterm birth < 31 weeks and preterm birth 500 mL and male sex), ( 3 ) Neonatal respiratory interventions (mechanical ventilation requirement, surfactant administration, respiratory distress syndrome, and transient tachypnea), and ( 4 ) Developmental services (early intervention service utilization). Each outcome is presented as a horizontal bar chart comparing the prevalence percentage in the ASD group (dark blue bars) versus the general population cohort (light blue bars), with the actual percentage labeled on each bar for precise interpretation. Figure 2 displays pregnancy medication utilization patterns comparing autism spectrum disorder (ASD) cases (n = 117) to the national cohort (n = 302,322). Dexamethasone exposure was significantly elevated in ASD pregnancies (9.6% vs. 2.8%; p < 0.01), reflecting the higher prevalence of threatened preterm labor requiring antenatal corticosteroid administration for fetal lung maturation. This elevation likely represents confounding by indication rather than direct medication neurotoxicity. Iron supplementation showed modest elevation (49.7% vs. 41.8%). Folic acid (66.2% vs. 64.7%), antihypertensives (1.7% vs. 1.4%), and thyroid medications (0.8% vs. 1.4%) showed comparable rates across groups 3.2 Integrated Interpretation The results reveal convergent risk pathways centered on placental dysfunction, extreme prematurity, and perinatal hypoxia-ischemia. The associations between ASD and early preterm birth, postpartum hemorrhage, and neonatal respiratory complications form a coherent mechanistic narrative: compromised placentation leads to maternal hemorrhagic complications and preterm delivery, which in turn increases risk of neonatal respiratory failure and hypoxic brain injury. These obstetric and neonatal stressors likely interact with underlying genetic susceptibility—potentially mediated by sex chromosomes and autism risk genes—to perturb neurodevelopmental trajectories. However, causality cannot be inferred from observational data, as recent family-based studies demonstrate that many prenatal risk factor associations are attenuated after controlling for familial confounding. 4. Discussion This large national cohort study of 302,476 pregnancies provides comprehensive evidence for multiple prenatal and perinatal factors associated with autism spectrum disorder in offspring. The most robust findings include profound male sex bias (OR = 4.88), elevated rates of extreme prematurity (OR = 3.14 for birth < 31 weeks), increased obstetric hemorrhage (OR = 2.70), and markedly higher neonatal respiratory complications—particularly respiratory distress syndrome (OR = 3.42) and surfactant administration (OR = 6.55). These associations form a coherent mechanistic narrative centered on placental dysfunction, perinatal hypoxia-ischemia, and oxidative stress as potential contributors to neurodevelopmental vulnerability in genetically susceptible individuals. 4.1 Male Predominance and Sex-Specific Vulnerability The observed male predominance of 83.7% in our ASD cohort, yielding an odds ratio of 4.88 (95% CI: 2.98–7.97), substantially exceeds the general population sex ratio and aligns with the well-established 3–4:1 male-to-female ratio reported in ASD epidemiology. This pronounced sex bias likely reflects multiple interacting mechanisms operating at genetic, hormonal, and developmental levels ( 3 , 5 , 20 , 63 ). At the genetic level, several mechanisms may contribute to male vulnerability. The X chromosome harbors a disproportionate number of genes involved in brain development and synaptic function, and males' hemizygous state for X-linked genes means that deleterious variants cannot be compensated by a second X chromosome as in females ( 64 , 65 ). Conversely, the "female protective effect" hypothesis posits that females require a higher mutational burden to manifest ASD, supported by evidence that female ASD cases carry more deleterious copy number variants and disruptive mutations than males ( 66 , 67 ). Skewed X-inactivation, genomic imprinting of parent-of-origin alleles, and genes that escape X-inactivation represent additional sex chromosome mechanisms that may modulate ASD risk differentially in males versus females ( 68 ). Prenatal sex steroid hormones, particularly testosterone, represent another critical pathway mediating sex differences in ASD. The "extreme male brain" theory proposes that elevated fetal testosterone exposure during critical windows of brain sexual differentiation increases autistic traits by masculinizing cognitive and behavioral profiles ( 23 ). Supporting evidence includes findings that amniotic fluid testosterone levels correlate with later autistic traits, that maternal conditions involving androgen excess (polycystic ovary syndrome) are associated with increased offspring ASD risk, and that steroidogenic activity is elevated during fetal development in males who are subsequently diagnosed with ASD ( 69 , 70 ). The placenta plays a central role in this pathway, as it exhibits sexual dimorphism in steroid hormone production, with male placentas generating higher testosterone levels that may influence brain development ( 71 , 72 ). Placental sex differences extend beyond steroid production to include differential inflammatory responses and vulnerability to pregnancy complications. Male placentas show greater susceptibility to early pregnancy insults, produce more pro-inflammatory cytokines in response to maternal immune activation, and express different levels of genes involved in immune regulation and neurodevelopmental signaling ( 20 ). A recent study demonstrated that maternal immune activation produces sex-specific effects on placental cytokine profiles, with male offspring showing elevated GM-CSF, IL-6, and TNF-α—cytokines known to influence synaptic development—whereas females showed different patterns ( 20 ). These placental sex differences may create differential prenatal environments that modulate brain development trajectories and ASD susceptibility. Differential vulnerability to perinatal hypoxia may also contribute to male predominance, as experimental evidence suggests that male brains are more susceptible to hypoxic-ischemic injury than female brains, potentially mediated by sex differences in oxidative stress responses, antioxidant enzyme expression, mitochondrial function, and inflammatory signaling ( 73 ). In our cohort, the strong associations between ASD and markers of perinatal hypoxia (RDS, ventilation, surfactant) may disproportionately affect males if they have reduced capacity to withstand oxygen deprivation during the vulnerable perinatal transition. The interaction between genetic susceptibility and environmental exposures likely differs by sex, with males potentially showing greater sensitivity to prenatal insults in the context of vulnerable genotypes. Gene-environment interaction models suggest that early prenatal stress, including hypoxia and inflammation, may be especially detrimental to males carrying ASD risk variants ( 74 ). 4.2 Extreme Prematurity and Interrupted Neurodevelopment The 3-fold elevation in early preterm birth (< 31 weeks gestation) among ASD cases (OR = 3.14; 95% CI: 1.28–7.70) represents a critical finding with strong neurobiological plausibility. Birth before 31 weeks interrupts the third trimester of pregnancy, a period of extraordinarily rapid and complex brain development during which critical processes are unfolding that establish the foundation for later cognitive and social function ( 31 , 75 , 76 ). During the third trimester, the fetal brain undergoes a dramatic expansion in cortical volume, driven by proliferation of neurons and glia, elaboration of dendritic trees, and formation of billions of synaptic connections ( 77 ). The cortical surface area increases exponentially as primary gyri and sulci form through coordinated programs of neuronal migration, differential growth, and mechanical forces ( 78 ). Premature birth interrupts this process, resulting in altered patterns of cortical folding, reduced cortical thickness and surface area, and abnormal organization of cortical layers—structural abnormalities that have been documented in neuroimaging studies of individuals with ASD ( 79 ). Synaptogenesis—the formation of synaptic connections between neurons—reaches peak velocity during the third trimester and continues through early postnatal life ( 80 ). This process is exquisitely sensitive to oxygen availability, as synaptic formation requires substantial energy expenditure and involves oxygen-dependent enzymatic processes. Hypoxic disruption of synaptogenesis may lead to altered patterns of synaptic connectivity, potentially contributing to the aberrant neural circuits implicated in ASD ( 81 ). Consistent with this, ASD is characterized by evidence of both excessive local connectivity (over-connectivity within specific brain regions) and reduced long-range connectivity (under-connectivity between distant regions), patterns that could arise from disrupted synaptic refinement during critical periods ( 82 , 83 ). Myelination—oligodendrocytes, the cells responsible for producing myelin, are particularly vulnerable to hypoxic-ischemic injury, and white matter abnormalities are common sequelae of prematurity ( 84 ). Diffusion tensor imaging studies in ASD have consistently identified altered white matter microstructure, suggesting abnormalities in myelination or axonal organization that could stem from perinatal disruptions ( 85 ). Subcortical structures critical for social cognition, emotional regulation, and sensory processing—including the thalamus, amygdala, hippocampus, and basal ganglia—undergo critical developmental processes during the third trimester ( 86 ). Neuroimaging studies have found that individuals with ASD who experienced prenatal hypoxia show enlarged third ventricle volumes and thalamic abnormalities that correlate with sensory dysfunction and sleep disturbances—core features of ASD ( 87 ). The association between prematurity and ASD may be confounded by underlying maternal and fetal conditions that precipitate preterm delivery and may independently affect neurodevelopment. Spontaneous preterm birth often occurs in the context of intrauterine infection and inflammation, placental insufficiency, maternal autoimmune conditions, or fetal genetic abnormalities—factors that may themselves contribute to ASD risk through inflammatory, hypoxic, or direct genetic mechanisms ( 88 ). Recent sibling-comparison studies have shown that associations between preterm birth and ASD are attenuated when comparing preterm and term siblings within the same family, suggesting that shared familial factors (genetic variants, maternal characteristics, environmental exposures) contribute substantially to observed population-level associations ( 10 , 30 ). The dose-response relationship observed in our study—with stronger associations at more extreme degrees of prematurity—supports biological plausibility but also raises questions about confounding, as extreme prematurity is more likely to result from severe underlying pathology. The fact that overall preterm birth (< 37 weeks) showed weaker association (OR = 1.93) than early preterm birth (< 31 weeks; OR = 3.14) suggests that ASD risk is concentrated among the most severely premature infants, consistent with mechanisms involving hypoxic-ischemic brain injury and interrupted neurodevelopment being most pronounced at extreme gestational ages ( 89 ). 4.3 Perinatal Hypoxia and Oxidative Stress The significant increase in neonatal respiratory complications among ASD cases, such as mechanical ventilation (OR = 3.26), TTN (OR = 3.90), surfactant administration (OR = 6.55), and RDS (OR = 3.42), offers strong evidence that perinatal hypoxia-ischemia is a mechanistic factor in ASD risk. These results are consistent with the increasing understanding that oxidative stress is a fundamental pathophysiological characteristic of ASD and with a variety of data from mechanistic studies, animal models, and biomarker research showing that oxygen deprivation during critical windows can result in long-lasting neurodevelopmental effects ( 90 – 92 ). Respiratory distress syndrome results from surfactant deficiency in immature lungs, leading to alveolar collapse, impaired gas exchange, and resultant hypoxemia ( 93 ). The consequent reduction in arterial oxygen content compromises oxygen delivery to the brain, creating cellular hypoxia that disrupts energy-dependent neurodevelopmental processes. When oxygen availability is insufficient, ATP production via oxidative phosphorylation declines, forcing cells to rely on anaerobic glycolysis—an inefficient pathway that produces lactate and acidosis ( 94 ). Energy failure from hypoxia triggers a cascade of cellular injury mechanisms. Insufficient ATP impairs the function of Na+/K + ATPase pumps that maintain electrochemical gradients across cell membranes, leading to membrane depolarization and uncontrolled influx of calcium ions (Ca2+) into cells ( 95 ). Excessive intracellular Ca2 + activates proteases, lipases, and nucleases that damage cellular structures; triggers excitotoxicity through excessive glutamate release and NMDA receptor activation; and activates apoptotic cell death pathways ( 96 ). These mechanisms are particularly detrimental during neurodevelopment when programmed cell death must be tightly regulated and excessive neuronal loss can permanently alter circuit formation ( 97 ). Ironically, by producing reactive oxygen species (ROS), reperfusion—the process of restoring oxygen delivery—after hypoxia can be just as harmful as hypoxia itself. During hypoxia, the electron transport chain in mitochondria becomes disrupted, and enzymes such as xanthine oxidase accumulate in partially reduced states ( 98 ). When oxygen is reintroduced, these systems generate superoxide anion (O2- −), hydrogen peroxide (H2O2), and hydroxyl radical (- OH)—highly reactive molecules that oxidize lipids, proteins, and nucleic acids. The immature brain is particularly vulnerable to oxidative damage due to high lipid content (myelin membranes are especially susceptible to lipid peroxidation), high metabolic rate, relatively low antioxidant defense capacity, and high iron content that catalyzes ROS production via Fenton reactions ( 99 ).. Oxidative stress has been shown to be a key pathophysiological characteristic of ASD. Biomarker studies have consistently documented altered redox status in individuals with ASD, including decreased levels of the primary cellular antioxidant glutathione (particularly the reduced form, GSH), increased lipid peroxidation products (malondialdehyde, isoprostanes), elevated markers of protein oxidation (protein carbonyls), and altered activities of antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase) ( 91 , 100 , 101 ). In ASD, mitochondrial dysfunction both contributes to and results from oxidative stress. Under physiological conditions, mitochondria are the main generator of cellular ROS because of electron leakage from the respiratory chain. Oxidative damage to mitochondrial DNA, lipids, and proteins also impairs mitochondria's ability to function. On the other hand, an endless loop of oxidative damage is produced when mitochondrial malfunction results in decreased ATP synthesis and increased ROS generation ( 102 ). Multiple studies have identified mitochondrial abnormalities in ASD, including respiratory chain enzyme deficiencies, altered mitochondrial membrane potential, abnormal mitochondrial morphology, and increased susceptibility to mitochondrial permeability transition pore opening—a catastrophic event that triggers apoptosis ( 103 – 105 ). Some individuals with ASD have primary genetic mitochondrial disorders, but mitochondrial dysfunction appears to be a broader feature present in substantial subsets of ASD cases even without identified genetic causes ( 106 ). Oxidative stress activates inflammatory signaling cascades, creating additional neurodevelopmental risk through neuroinflammation. ROS activate redox-sensitive transcription factors including NF-κB, which upregulates expression of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), chemokines, and adhesion molecules ( 107 ).These inflammatory mediators can disturb synaptic formation and function, activate microglia, the brain's resident immune cells, and penetrate the blood-brain barrier, which may be weakened by oxidative damage. Neuroinflammation has been extensively documented in ASD through postmortem studies showing activated microglia and astrocytes, elevated brain tissue cytokine levels, and peripheral immune abnormalities ( 108 ). Epigenetic dysregulation represents another mechanism through which oxidative stress may exert lasting effects on neurodevelopment. ROS have the ability to affect chromatin structure, histone post-translational modifications, and DNA methylation patterns, which can result in changed gene expression programs that last after the initial oxidative attack ( 109 ).These epigenetic changes may affect genes critical for synaptic development, neuronal differentiation, and other neurodevelopmental processes, creating lasting alterations in brain structure and function ( 110 ). The strongest correlation found in our study is a 6.5-fold increase in surfactant administration among ASD cases (OR = 6.55; 95% CI: 2.08–20.65; p = 0.003), suggesting that the most severe respiratory compromise—requiring exogenous surfactant to maintain gas exchange—carries a notably high risk. Although surfactant therapy is vital and life-saving for RDS, infants who require it are those who have the most acute respiratory failure and lung immaturity, with the resulting severe hypoxemia both before and after treatment ( 111 ). Although mechanical ventilation is required to promote gas exchange in respiratory failure, it presents iatrogenic dangers, such as systemic inflammation from ventilator-associated lung injury, oxygen toxicity from hyperoxia during treatment, and ventilator-induced lung injury from barotrauma and volutrauma. The systemic inflammatory response triggered by ventilator-induced lung injury can produce circulating cytokines that reach the brain and contribute to neuroinflammation. Additionally, the transition from hypoxia to hyperoxia during aggressive oxygen therapy can exacerbate oxidative stress through ROS generation ( 112 ). ASD was also substantially linked to transient tachypnea in newborns, which is often self-limiting syndrome involving delayed clearance of fetal lung fluid (OR = 3.90; 95% CI: 1.44–10.57; p = 0.017). This finding is somewhat unexpected because TTN does not usually involve hypoxemia. It could indicate that TTN is a sign of subtle underlying neurological or cardiorespiratory dysfunction, or it could indicate that the association is a result of confounding by gestational age or delivery method (because vaginal delivery lacks thoracic compression, cesarean section is a risk factor for TTN) ( 113 , 114 ). 4.4 Placental Dysfunction and Obstetric Hemorrhage The 2.7-fold increase in postpartum hemorrhage (> 500 mL) among pregnancies with ASD (OR = 2.70; 95% CI: 1.26–5.81; p = 0.019) suggests that vascular abnormalities and placental dysfunction may be risk factors for ASD. Postpartum hemorrhage most commonly results from uterine atony (inadequate contraction of the uterus after delivery), but can also stem from placental abnormalities (retained placental tissue, placenta accreta), coagulation disorders, or genital tract trauma ( 115 , 116 ). The placenta represents the critical interface between maternal and fetal circulations, responsible for nutrient transfer, gas exchange, waste removal, endocrine signaling, and immunological regulation ( 117 ). Through a variety of mechanisms, such as chronic hypoxia from insufficient oxygen transfer, nutrient restriction that results in fetal growth restriction, altered hormone exposure that affects brain sexual differentiation, and inflammatory signaling that triggers fetal immune responses, placental dysfunction can impair fetal development. Numerous studies have directly connected placental insufficiency—inadequate placental function to meet fetal metabolic demands—to the risk of ASD. This condition frequently presents as fetal growth restriction, or small-for-gestational-age newborns ( 51 , 118 – 120 ). A large case-control study found that preeclampsia and other indicators of placental insufficiency were significantly associated with ASD and intellectual disability in offspring ( 51 ). In terms of mechanism, placental insufficiency results in oxidative stress and persistent fetal hypoxia, limits the transport of nutrients (which may impact brain growth and myelination), and may cause compensatory reactions in the fetal hypothalamic-pituitary-adrenal axis that modify neurodevelopment ( 121 ). One particularly strong risk factor for ASD is placental inflammation, which is defined by the infiltration of inflammatory cells into placental tissues and increased cytokine production. Even after controlling for maternal psychiatric history and medication use, a large cohort study revealed that fetal inflammatory response syndrome (FIRS), which is characterized by the presence of chorionic vasculitis and/or funisitis on placental histopathology, significantly increases the risk of ASD, ADHD, conduct disorder, and PTSD ( 18 ). Inflammatory insults during the prenatal period could influence neurodevelopmental paths toward psychiatric susceptibility, as evidenced by the increased probabilities of diagnosing ASD in children delivered with placentas that met FIRS criteria ( 18 ). The sexual dimorphism of the placenta may contribute to male vulnerability to placental complications. Compared to female placentas, male placentas have different gene expression patterns, generate different inflammatory responses to maternal immune activation, and are more vulnerable to early pregnancy insults ( 122 ). These sex-specific variations in placental function could result in unique prenatal settings that affect brain development and the risk of ASD in ways that are specific to each sex. Abnormal implantation (placenta previa, placenta accreta), placental abruption, or insufficient spiral artery remodeling that impairs uteroplacental blood flow are some of the underlying placental vascular abnormalities that may be reflected in postpartum hemorrhage. Chronic placental hypoxia brought on by these vascular anomalies can cause oxidative stress and inflammatory signaling in the placental tissues, which may spread to the fetus. Additionally, if placental perfusion is impaired due to maternal bleeding, hypoxic-ischemic damage may result in abrupt fetal hypoxia ( 123 ). Another possible connection between maternal haemorrhage and ASD is coagulation disorders, since both bleeding diatheses and thrombophilic conditions (increasing clotting) have been studied in connection with prenatal problems and neurodevelopmental outcomes. Placental thrombosis and infarction can result from maternal autoimmune diseases that involve antibodies against phospholipids or other coagulation factors, impairing placental function ( 124 , 125 ). 4.5 Antenatal Corticosteroids and Confounding by Indication The 3.4-fold increase in dexamethasone use during pregnancy among ASD cases (9.6% vs. 2.8% for all others) must be carefully interpreted in light of confounding by indication, meaning that the association is probably explained by the underlying condition that requires treatment (threatened preterm labour) rather than the treatment itself. The basis of obstetric care for women at risk of preterm delivery between 24- and 34-weeks’ gestation is antenatal corticosteroids, usually betamethasone or dexamethasone. This is supported by strong evidence from randomized trials showing significant decreases in neonatal respiratory distress syndrome, intraventricular haemorrhage, necrotizing enterocolitis, and neonatal mortality ( 126 ). The important trial found no differences in cognitive function, behavioural outcomes, or health status at a 30-year follow-up, which is generally comforting in long-term neurodevelopmental follow-up studies of children exposed to acceptable regimens of prenatal corticosteroids ( 127 ). More recent large cohort studies have similarly found no association between guideline-concordant antenatal corticosteroid exposure and risk of psychiatric disorders including ASD, ADHD, or other mental health conditions ( 60 , 128 ). In line with our finding of a three-fold increase in early preterm delivery, the higher rates of threatened preterm labour in our sample are probably reflected in the higher dexamethasone use among pregnancies with ASD (9.6% vs. 2.8%). The link between ASD and corticosteroid exposure is probably mediated by the underlying maternal-foetal abnormalities that cause threatened preterm labour, such as intrauterine infection, placental insufficiency, cervical insufficiency, or maternal medical issues. The fact that dexamethasone treatment acts as a marker of pregnancies at high risk for preterm delivery and that early preterm birth itself was substantially linked to ASD lend credibility to this interpretation. However, the issue of whether antenatal corticosteroids have separate neurodevelopmental effects is still unanswered and needs more research using carefully planned studies that can evaluate dose-response relationships, account for confounding by indication, and look at susceptible subgroups and possible vulnerability windows. 4.6 Cesarean Section and Mode of Delivery It is unclear whether surgical delivery affects ASD risk or if caesarean sections are a sign of underlying complications that require operative delivery, due to the significantly higher caesarean section rate among pregnancies with ASD (26.5% vs. 18.0%; OR = 1.64; 95% CI: 1.09–2.48; p = 0.023). There has been conflicting research on the relationship between mode of delivery and ASD risk; some studies have found no correlation after controlling for covariates, while others have reported an increased risk with caesarean sections ( 10 , 129 – 131 ). Although there is little and contradicting evidence, a number of explanations have been put out to explain how caesarean delivery may affect neurodevelopment. One hypothesis involves alterations in the infant microbiome, as caesarean-born infants are not exposed to maternal vaginal and faecal microbiota during birth and show different patterns of gut colonization in early life compared to vaginally delivered infants ( 132 ). Although causative linkages are yet unknown, the gut microbiota has been linked to ASD through the gut-brain axis. Several studies have shown that people with ASD have altered microbiome composition and gastrointestinal symptoms ( 133 – 135 ). Another proposed mechanism involves stress responses, with some authors suggesting that the physiological stress of labour and vaginal delivery may provide beneficial programming of stress-response systems, though evidence is speculative ( 136 ). More realistically, a caesarean delivery could be an indication of underlying issues such foetal distress, atypical foetal presentation, placental abnormalities, maternal health issues, or difficulties from a prior pregnancy that have an independent impact on neurodevelopment. The greater rates of preterm, respiratory issues, and obstetric haemorrhage in our sample are probably the cause of the higher caesarean rate among ASD cases, which would raise the possibility of an operational delivery. Uncomfortable foetal cardiac tracings or emergency caesarean sections for foetal distress may indicate episodes of intrapartum hypoxia that lead to brain damage ( 137 ). Crucially, our analysis found no significant differences in spontaneous labour rates between groups, indicating that the manner of birth itself is not a risk factor in and of itself but rather represents the series of difficulties seen in pregnancies linked to ASD. 4.7 Early Intervention and Developmental Surveillance The threefold increase in early intervention service use among ASD cases (12.8% vs. 4.7%; OR = 2.98; 95% CI: 1.73–5.13; p < 0.001) is indicative of both the developmental requirements of children who will subsequently be diagnosed with autism and the possibility of early identification of developmental issues in this group. The fact that developmental issues frequently appear prior to a formal autism diagnosis, which usually takes place between the ages of 2–4, is consistent with the increased use of early intervention in ASD. Even before autism-specific symptoms are completely evident, parents and medical professionals may notice delays in language development, motor milestones, social interaction, or abnormal behaviours that warrant referral to early intervention. Regardless of the final diagnostic classification, this discovery emphasizes the value of thorough developmental surveillance for children exposed to prenatal risk factors because early detection and intervention can enhance long-term outcomes. Furthermore, developmental delays, intellectual disabilities, motor impairments, and other disorders that require therapeutic services beyond autism-specific interventions are often co-occurring in children with ASD. Determining whether early intervention was started for autism-related concerns or other developmental issues is difficult due to the overlap between ASD and global developmental delay, especially in children who were born extremely preterm or with serious perinatal abnormalities. From a clinical and public health standpoint, the correlation between perinatal risk factors and the use of early intervention suggests that high-risk infants—such as those born very preterm, with severe respiratory complications, or with other indicators of perinatal compromise—can benefit from proactive service referral and targeted developmental surveillance. 4.8 Maternal Age and Sociodemographic Factors In contrast to meta-analytic evidence that links advanced maternal age (≥ 35 years) to higher risk for ASD, our cohort did not show significant differences in maternal age among groups (p = 0.180). With too few pregnancies in older age groups to detect age-stratified effects, this disparity probably reflects the very youthful mean age across all groups (29.6–31.1 years). There are complex links between the diagnosis of ASD and sociodemographic characteristics including as socioeconomic position, education, race/ethnicity, and healthcare access. These relationships include both actual differences in incidence/prevalence and inequalities in diagnostic recognition and service access. We were unable to account for potential confounding by socioeconomic and healthcare characteristics because we lacked data on these variables in our study. 4.9 Familial Confounding and Causality The possibility of familial confounding—shared genetic or environmental factors within families that predispose to both pregnancy problems and offspring ASD rather than direct causal effects of prenatal exposures—is a crucial restriction in interpreting our results. Recent large-scale sibling comparison studies have shown that when comparing affected and unaffected siblings within the same household, many observed links between prenatal variables and ASD are significantly reduced or eliminated ( 138 , 139 ). For example, a Danish study of 1.1 million children found that while 30 maternal diagnoses during pregnancy showed population-level associations with ASD, most associations disappeared in within-family analyses, suggesting that familial factors rather than direct exposure effects explained the associations ( 10 ). Similarly, sibling studies of preterm birth and ASD have shown attenuated effects when comparing preterm and term siblings, indicating that familial factors contribute substantially to the observed association ( 140 , 141 ). 4.10 Strengths This study has a number of significant advantages that increase trust in the results and their applicability: Large cohort based on population: Incorporating 302,476 pregnancies from national birth registries over a 12-year span reduces selection bias present in clinic-based or convenience samples, improves generalizability to the general population, and offers extraordinary statistical power to identify relationships. The assessment of uncommon exposures and outcomes, as well as the discovery of modest effect sizes, are made possible by the huge denominator population. Thorough data collection: By minimizing loss to follow-up and differential participation, which can skew case-control and cohort studies, the use of national registry data guarantees nearly comprehensive ascertainment of births, diagnoses, and outcomes within the healthcare system. Compared to self-reported exposure data, registry-based research reduces measurement error and recall bias by utilizing routinely obtained clinical data. Comprehensive evaluation of several domains: Rather than focusing on isolated single-exposure effects, the study analysed maternal demographics, medication exposures, obstetric complications, delivery characteristics, and neonatal outcomes in an integrated manner, enabling the characterization of risk factor patterns and possible mechanistic pathways. Clinical diagnosis of ASD: To improve diagnostic validity, cases were found using clinical diagnosis based on predetermined diagnostic criteria rather than screening questionnaires or parental reports. However, it is difficult to discover unusual outcomes in registry studies, as seen by the limited number of ASD patients compared to the broad background population. Standard, suitable methodology for cohort studies includes the use of ANOVA for continuous variables, chi-square testing for categorical comparisons, and logistic regression to compute odds ratios with confidence intervals. Reproducibility and accuracy were guaranteed by the use of established software (MedCalc) for statistical analyses. Biological plausibility: The findings have biological credibility because the found relationships are consistent with current knowledge of the genesis of ASD and suggested molecular pathways involving placental malfunction, hypoxia-ischemia, oxidative stress, and neuroinflammation. Relevance to the present: The research period (2005–2017) offers current data that reflects contemporary infant care standards, obstetric procedures, and diagnostic techniques, improving relevance to contemporary clinical settings. 4.11 Limitations Interpreting the study's conclusions requires considering a number of important limitations: Few instances of ASD: Only 117 ASD cases were included. Wide confidence intervals for some estimates are the result of the small number of cases, which also restricts statistical power for detecting lower impact sizes and precludes thorough subgroup analysis. Confounding from unmeasured variables, such as genetic factors, socioeconomic status, maternal education, healthcare access, environmental exposures, paternal characteristics, and postnatal factors, may limit the ability to draw conclusions about causality in this retrospective observational study. Although we corrected for maternal age, analyses did not account for other significant factors. Familial confounding: Rather than being the direct result of prenatal exposures, many reported relationships might be the result of shared familial variables (genetic or environmental). We are unable to differentiate these pathways without family-based comparisons. The study period (2005–2017) covers the shift from the DSM-IV to the DSM-5 diagnostic criteria for autism. The DSM-5 (2013) did away with the distinct diagnoses of Asperger syndrome and PDD-NOS in favor of a single ASD spectrum. This change in diagnosis could have an impact on case determination, categorization, and cross-temporal comparability. By merging Asperger and pure autism patients into a single ASD category, we were able to partially alleviate issue. Absence of comprehensive clinical data Although registry-based research offers a wide range of coverage, its clinical depth is limited. Mechanistic understanding could be informed by information on placental pathology, prenatal biomarkers (cytokines, oxidative stress markers, hormones), cognitive functioning, co-occurring disorders, ASD symptom severity, precise drug dose and timing, and postnatal environmental exposures. Evaluation of drug exposure: Information on medications was restricted to general categories (dexamethasone, iron, folic acid, antihypertensives, thyroid drugs) and lacked specifics regarding dosage, occurrence, duration, or indication. This restricts our capacity to evaluate crucial exposure windows or dose-response correlations. Confounding by indication is another significant issue, especially with dexamethasone. Limited generalizability: Results from a single national registry might not apply to groups with distinct sociodemographic traits, genetic backgrounds, healthcare systems, environmental exposures, or diagnostic procedures. Applicability elsewhere may be limited by the cohort's unique obstetric practices, ASD prevalence, and community factors. Absence of mechanistic biomarkers: rather than focusing on the underlying biological mechanisms, the study looked at clinical outcomes (preterm birth, RDS, haemorrhage). Mechanistic inferences might be strengthened by biomarker data on oxidative stress, inflammatory cytokines, placental function, or fetal oxygenation, however these were unavailable. Cross-sectional exposure measurement: Rather than being described in terms of severity, length, or temporal patterns, many exposures (medications, problems) were evaluated as binary (present/absent). For instance, it was not possible to assess the extent and duration of hypoxia during RDS, the severity of placental malfunction, or the gestational age during exposure to dexamethasone. Despite these drawbacks, the study offers important epidemiological data on prenatal and perinatal variables linked to ASD in a sizable population-based cohort and pinpoints particular risk factors and plausible mechanistic pathways that demand more research in prospective, mechanistic studies. 5. Conclusions The 302,476 pregnancies in this extensive nationwide cohort study offer strong evidence for a number of prenatal and postnatal variables linked to autism spectrum disorder in the offspring. The strongest evidence points to perinatal hypoxia-ischemia as a key mechanistic contributor. These findings include significant male sex bias (nearly 5-fold increased odds), elevated rates of extreme prematurity (3-fold increase for birth < 31 weeks), increased obstetric hemorrhage (2.7-fold increase), and significantly elevated neonatal respiratory complications, particularly respiratory distress syndrome (3.4-fold) and surfactant administration (6.6-fold). These correlations create a logical mechanistic picture that focuses on perinatal hypoxia, oxidative stress, placental malfunction, extreme preterm, and neuroinflammation as interconnected pathways that may disrupt neurodevelopment in people who are genetically predisposed. The biological plausibility of these pathways is supported by the convergence of our findings with substantial evidence from animal models, biomarker studies, and mechanistic research, while also accepting that causality cannot be proved only from observational data. In line with established ASD epidemiology, our cohort's marked male predominance underscores the crucial role that sex-specific biological mechanisms—such as sex chromosome effects, prenatal hormone exposure, placental sexual dimorphism, and differential susceptibility to oxidative stress and hypoxia—play in mediating the risk for ASD. The intricate relationships between sex, genes, hormones, and environmental exposures that result in the notable male bias in ASD should be further explored in future studies. There are still important uncertainties about which prenatal and perinatal exposures are indicators of underlying familial risk and which are actual causal factors. Genetic pleiotropy, maternal traits, and shared environmental factors are thought to play a significant role in the observed population-level relationships, according to recent sibling-comparison studies showing attenuation of numerous prenatal risk factor associations within families. Family-based study designs, Mendelian randomization techniques, prospective cohorts with comprehensive exposure biomarkers, and, finally, intervention trials focusing on modifiable risk variables are necessary to distinguish causal from confounding correlations. Our findings highlight a number of significant consequences from the standpoints of clinical and public health: Optimize prenatal care and prevent extreme prematurity: As potential primary prevention strategies for ASD and other neurodevelopmental disorders, evidence-based interventions to reduce preterm birth should be given priority. These interventions include cervical cerclage for cervical insufficiency, progesterone supplementation for high-risk women, treatment of maternal infections, and lifestyle modifications. Promote placental health: More investigation into therapies that promote placental function and lessen inflammation may present chances to lower the risk of neurodevelopment. This could involve anti-inflammatory methods, antioxidant supplements, or therapies for particular maternal diseases that have an impact on placental health Reduce perinatal hypoxia: Appropriate management of respiratory issues in preterm infants, such as early surfactant administration when necessary, gentle ventilation techniques to minimize lung damage, and prudent use of supplemental oxygen to prevent both hypoxia and hyperoxia, may help lessen hypoxic-ischemic brain injury. Establish early developmental surveillance: When issues are detected, children who have been exposed to severe respiratory problems, obstetric hemorrhage, extreme prematurity, or other known risk factors should be referred to early intervention services at a low threshold and have their developmental monitoring improved. Regardless of the final diagnostic classification, functional outcomes can be improved with early identification and intervention. Avoid unwarranted attribution or mother blame: Because of the intricate, multivariate etiology of ASD, which involves gene-environment interactions, individual pregnancy exposures or difficulties only slightly increase absolute risk. In order to prevent guilt or self-blame, healthcare professionals should advise families that ASD is caused by a variety of interrelated variables rather than a single, identifiable cause. Use antenatal interventions appropriately: Although our results indicate a link between dexamethasone use and ASD, this is probably due to indication-specific confounding rather than the negative effects of corticosteroids, which are still an essential evidence-based intervention for reducing neonatal morbidity and mortality in cases of threatened preterm delivery. Prenatal corticosteroid usage should continue in accordance with guidelines, avoiding needless courses outside of advised purposes. Future research priorities should include: Strong epidemiological data is shown in this study to support links between prenatal and perinatal variables, specifically extreme preterm, perinatal hypoxia, and obstetric difficulties, and child ASD. These findings raise awareness of the role that the environment plays in the etiology of ASD, point to possible molecular pathways involving neuroinflammation and oxidative stress, and point to areas that could benefit from improved surveillance and preventive measures. To separate causal from confounded associations and convert epidemiological findings into practical strategies for lowering the risk of ASD and improving outcomes for impacted individuals and families, more research employing cutting-edge methodologies is necessary due to the intricate interactions between genetic susceptibility, familial factors, and environmental exposures. Abbreviations ASD Autism Spectrum Disorder RDS Respiratory Distress Syndrome TTN Transient Tachypnea of Newborn SGA Small for Gestational Age OR Odds Ratio CI Confidence Interval FIRS Fetal Inflammatory Response Syndrome MIA Maternal Immune Activation ROS Reactive Oxygen Species ATP Adenosine Triphosphate Ca²⁺ Calcium ions GSH Reduced Glutathione NaK-ATPase Sodium-Potassium ATPase NMDA N-methyl-D-aspartate DSM-5 Diagnostic and Statistical Manual, 5th Ed ICD-10 International Classification of Diseases, 10th Rev ADHD Attention Deficit Hyperactivity Disorder HIE Hypoxic-Ischemic Encephalopathy ANOVA Analysis of Variance SD Standard Deviation NICU Neonatal Intensive Care Unit PDD-NOS Pervasive Developmental Disorder - NOS H₂O₂ Hydrogen peroxide O₂⁻ Superoxide anion ·OH Hydroxyl radical Declarations Ethics approval and consent to participate The registry-based component of this study was approved by the National Institute of Public Health responsible for registry-data approvals (approval number: [968- 1 0O/1 8-1 /007]) on 26 th February 2018. The analysis was conducted on fully anonymized data extracted from the National Perinatal Information System and linked health records. In line with national regulations and the terms of this approval, individual informed consent was not required, and a waiver of consent was granted for this retrospective use of anonymized registry data. Consent for publication Not applicable. The study used anonymized registry data without individual identifiers. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request, subject to ethical approval and data protection regulations. Competing interests The authors declare no competing interests. Funding This research was funded by the Slovenian Research Agency through scientific research program grants P3-0124 and project J3-1756. Authors' contributions Conceptualization: J.O.; methodology: J.O. and U.G.; software: U.G.; validation: J.O. and U.G.; formal analysis: U.G.; investigation: J.O.; resources: J.O.; data curation: J.O.; writing—original draft preparation: J.O.; writing—review and editing: J.O. and U.G.; visualization: J.O.; supervision: J.O.; project administration: J.O.; funding acquisition: J.O. Both authors have read and agreed to the published version of the manuscript. Acknowledgements We thank the staff of the National Perinatal Information System for data management support and the National Medical Ethics Committee for expedited review of the research protocol. References American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM–5). Washington, DC: American Psychiatric Association; 2013. Jinan Zeidan E, Fombonne J, Scorah A, Ibrahim MS, Durkin S, Saxena, et al. Global prevalence of autism: a systematic review update. Autism Res. 2022;15(5):778–90. 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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-8333327","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":575211809,"identity":"39bb37c7-42db-46e3-82df-96e000ad5b9e","order_by":0,"name":"Joško Osredkar","email":"","orcid":"","institution":"Ljubljana University Medical Centre","correspondingAuthor":false,"prefix":"","firstName":"Joško","middleName":"","lastName":"Osredkar","suffix":""},{"id":575211810,"identity":"a6aa700b-19f8-4f95-a85a-d6b51d41f6d4","order_by":1,"name":"Uroš 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14:46:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":435182,"visible":true,"origin":"","legend":"","description":"","filename":"BMCPregnancyandChildbirth6.1.2026.docx","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/8867be863dada06a07721896.docx"},{"id":100600614,"identity":"30c06bf9-c2f5-497d-9bb7-71fc7f5499c6","added_by":"auto","created_at":"2026-01-19 14:49:03","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5420,"visible":true,"origin":"","legend":"","description":"","filename":"12a6f63d54934cafa5315ae4242d1aa6.json","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/1691ce63d65162d53ce07a4e.json"},{"id":100600267,"identity":"fde5264e-aef6-4f15-8832-bb7636174cdc","added_by":"auto","created_at":"2026-01-19 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14:48:09","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":19718,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/02bd0e2cd94782c7c52d6730.png"},{"id":100600261,"identity":"2baa4620-c958-4280-b679-0a2d13f41ff9","added_by":"auto","created_at":"2026-01-19 14:47:20","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":270442,"visible":true,"origin":"","legend":"","description":"","filename":"12a6f63d54934cafa5315ae4242d1aa61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/d6f16c7d86607a734b164bae.xml"},{"id":100600184,"identity":"00a04efd-d75e-4728-94e4-53ac6c9ba259","added_by":"auto","created_at":"2026-01-19 14:46:53","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":288441,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/2baeb967d5bc06948b82333a.html"},{"id":100600400,"identity":"6c7d1f81-868f-4b7c-b155-563b75d237b7","added_by":"auto","created_at":"2026-01-19 14:47:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208125,"visible":true,"origin":"","legend":"\u003cp\u003eKey pregnancy and birth outcomes showing significant differences between children with ASD and control population\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/9bf07797627c52c1516d7995.png"},{"id":100600181,"identity":"a7c4c621-dbe6-44a5-8ce8-7ac19203bdef","added_by":"auto","created_at":"2026-01-19 14:46:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":72584,"visible":true,"origin":"","legend":"\u003cp\u003ePregnancy medication use patterns comparing ASD cases (n=117) to the national cohort (n=302,322). Dexamethasone exposure was significantly elevated in ASD pregnancies (9.6% vs 2.8%), likely reflecting confounding by indication for threatened preterm labor\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/baf950ef6a40ce6f671e8504.png"},{"id":108806773,"identity":"0188c57a-b84c-4887-8d9c-d660814fcec1","added_by":"auto","created_at":"2026-05-08 15:29:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":707223,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8333327/v1/33896cc7-f681-4650-a712-3208372ab26d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prenatal and Perinatal Risk Factors Associated with Autism Spectrum Disorder: A National Cohort Study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eAutism spectrum disorder (ASD) represents a heterogeneous group of neurodevelopmental conditions characterized by persistent deficits in social communication and interaction across multiple contexts, along with restricted, repetitive patterns of behavior, interests, or activities that manifest early in the developmental period and cause clinically significant impairment in social, occupational, or other important areas of functioning (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The global prevalence of ASD has increased substantially over recent decades, with current estimates ranging from 1% to 2% of children in developed countries, though this rise likely reflects improved recognition, broadened diagnostic criteria, and enhanced surveillance rather than solely increased incidence (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). One of the most consistent and striking epidemiological features of ASD is its pronounced male predominance, with male-to-female ratios typically ranging from 3:1 to 4:1 across populations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This sex bias represents a critical clue to underlying etiology and has prompted extensive research into biological mechanisms that may confer differential vulnerability or protection based on sex.\u003c/p\u003e \u003cp\u003eThe etiology of ASD is recognized as multifactorial, involving complex interactions between genetic susceptibility and environmental influences during critical windows of neurodevelopment. Twin and family studies have established that ASD has substantial heritability, with concordance rates in monozygotic twins reaching 60\u0026ndash;90% and recurrence risk in siblings elevated 10\u0026ndash;20 fold compared to the general population (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Genome-wide association studies and exome sequencing have identified hundreds of common genetic variants and dozens of rare mutations that contribute to ASD risk, affecting genes involved in synaptic function, chromatin remodeling, transcriptional regulation, and neuronal migration. However, genetic factors alone cannot fully account for ASD etiology, as even monozygotic twins show incomplete concordance and the rapid increase in diagnosed prevalence suggests important environmental contributions.\u003c/p\u003e \u003cp\u003eEnvironmental risk factors implicated in ASD etiology span the prenatal, perinatal, and early postnatal periods, with particular emphasis on exposures that may disrupt critical neurodevelopmental processes during vulnerable windows. Proposed prenatal risk factors include advanced parental age, maternal metabolic conditions (diabetes, obesity), maternal psychiatric disorders, maternal infections and inflammatory conditions, exposure to certain medications (valproate, selective serotonin reuptake inhibitors), vitamin D insufficiency, and environmental toxicants (air pollution, pesticides) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Perinatal and neonatal risk factors that have been investigated include gestational complications (preeclampsia, placental abnormalities), birth asphyxia, prematurity, low birth weight, neonatal jaundice, and need for intensive respiratory support (\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the proposed environmental risk factors, perinatal hypoxia-ischemia has emerged as a particularly compelling mechanistic candidate based on converging evidence from human epidemiological studies, animal models, and mechanistic investigations. Hypoxic-ischemic injury during critical windows of brain development can disrupt oxygen-dependent processes including synaptogenesis, neuronal migration, myelination, programmed cell death, and establishment of neural circuits (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Additionally, hypoxia triggers oxidative stress\u0026mdash;an imbalance between pro-oxidant and antioxidant systems leading to accumulation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) that damage cellular macromolecules including lipids, proteins, and DNA (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Multiple studies have documented elevated markers of oxidative stress in individuals with ASD, including decreased glutathione levels, increased lipid peroxidation products (malondialdehyde), and altered antioxidant enzyme activities (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Furthermore, oxidative stress can activate inflammatory cascades, disrupt mitochondrial function, alter epigenetic regulation, and impair the blood-brain barrier\u0026mdash;all of which have been implicated in ASD pathophysiology (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlacental dysfunction represents another critical pathway through which prenatal complications may influence fetal brain development and contribute to ASD risk. The placenta serves not merely as a passive conduit for nutrient and gas exchange, but as an active endocrine and immunological organ that senses maternal physiological and environmental signals and modulates fetal exposure accordingly. Placental abnormalities identified in association with ASD include abnormal trophoblast inclusions, inflammatory changes (fetal inflammatory response syndrome or FIRS), vascular malperfusion, and altered expression of genes involved in steroid hormone metabolism and immune regulation (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Placental inflammation has been specifically linked to increased risk of ASD diagnosis, with children born with placentas meeting criteria for FIRS showing significantly elevated odds of developing autism, attention-deficit/hyperactivity disorder, and other psychiatric conditions (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Mechanistically, placental inflammation may alter the balance of pro-inflammatory and anti-inflammatory cytokines transferred to the fetal circulation, disrupt the development of hematopoietic stem cells that later populate the brain as microglia, modify steroid hormone levels that influence sexual differentiation of the brain, and impair nutrient and oxygen delivery to the developing fetus.\u003c/p\u003e \u003cp\u003eThe placenta also exhibits sexual dimorphism, with male and female placentas differing in gene expression patterns, steroid production, inflammatory responses, and vulnerability to complications. Male placentas produce higher levels of steroid hormones, are more vulnerable to early pregnancy complications, and show different responses to maternal immune activation compared to female placentas (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). These sex-specific placental characteristics may partially mediate the male predominance observed in ASD by creating differential exposure to hormones and inflammatory mediators during critical periods of brain sexual differentiation (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMaternal immune activation (MIA) during pregnancy has received substantial attention as a potential contributor to ASD risk based on animal models showing that immune challenges during pregnancy can produce ASD-like behaviors in offspring through placental transmission of inflammatory cytokines (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In humans, maternal infections during pregnancy, particularly in the first and second trimesters, have been associated with modest increases in ASD risk in some but not all studies. Meta-analyses show an overall odds ratio of 1.13\u0026ndash;1.32 for maternal infection during pregnancy, with stronger associations for hospitalized infections (OR 1.30\u0026ndash;1.48) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The effects of MIA appear to be sex-specific, with male offspring showing greater vulnerability to immune-mediated neurodevelopmental disruption than females. Recent studies have demonstrated that MIA produces differential effects on placental and fetal brain cytokine profiles in male versus female offspring, with males showing higher placental levels of pro-inflammatory cytokines (GM-CSF, IL-6, TNF-α) and sex-specific alterations in genes related to synaptic development (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrenatal sex steroid hormones, particularly testosterone and estrogens, play critical roles in sexual differentiation of the brain and have been proposed as mediators of sex differences in ASD vulnerability through mechanisms including the \"extreme male brain\" theory (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). This hypothesis suggests that elevated prenatal testosterone exposure may underlie autistic traits, supported by evidence that amniotic fluid testosterone levels correlate with later autistic traits and that conditions involving androgen excess (such as polycystic ovary syndrome) are associated with increased ASD risk in offspring. However, the relationship between prenatal hormones and ASD is complex and likely involves interactions with genetic factors, placental function, and other environmental exposures (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite extensive research, the specific contribution of obstetric complications and perinatal events to ASD risk remains debated. Many reported associations are subject to potential confounding by familial factors\u0026mdash;that is, shared genetic or environmental characteristics within families that predispose to both pregnancy complications and offspring neurodevelopmental disorders. Recent large-scale sibling-comparison studies have demonstrated that many prenatal risk factor associations with ASD are substantially attenuated or eliminated when comparing affected and unaffected siblings within the same family, suggesting that apparent associations may reflect familial confounding rather than direct causal effects (\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). For example, a Danish study of over 1.1\u0026nbsp;million children found that while 30 maternal diagnoses during pregnancy showed associations with offspring ASD in population-level analyses, most associations disappeared in within-family comparisons, indicating that shared familial factors rather than direct exposure effects explained the majority of observed associations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePreterm birth represents one of the most extensively studied perinatal risk factors for ASD, with meta-analyses reporting elevated risk particularly for extreme prematurity (birth\u0026thinsp;\u0026lt;\u0026thinsp;28 weeks gestation), though findings have been inconsistent and effect sizes modest after adjustment for confounders (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The mechanisms through which prematurity might influence ASD risk are multifactorial and include: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) interruption of critical third-trimester brain development when rapid cortical expansion, synaptogenesis, and myelination occur (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) exposure to neonatal intensive care interventions including mechanical ventilation, oxygen therapy, and medications that may have neurodevelopmental impacts (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) increased risk of intraventricular hemorrhage, periventricular leukomalacia, and other forms of brain injury (\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e); (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) prolonged exposure to stress hormones and inflammation (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e); and (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) underlying maternal-fetal conditions that precipitate preterm delivery and may independently affect brain development (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relationship between prematurity and ASD is further complicated by the fact that extremely premature infants face elevated risk for multiple neurodevelopmental disabilities including intellectual disability, cerebral palsy, attention deficits, and learning disorders, making it challenging to isolate specific risk for autism independent of global developmental delay (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Additionally, recent analyses suggest that the association between preterm birth and ASD may be confounded by familial factors, as sibling studies show attenuated effects (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRespiratory complications in the immediate newborn period, including respiratory distress syndrome (RDS), transient tachypnea of newborn (TTN), need for mechanical ventilation, and surfactant administration, represent markers of perinatal compromise that may involve hypoxic-ischemic injury to the developing brain. RDS, caused by surfactant deficiency in immature lungs, results in impaired gas exchange and can lead to both hypoxemia (low blood oxygen) and hyperoxia (excessive oxygen exposure during treatment), both of which generate oxidative stress and can damage vulnerable brain structures (42\u0026ndash;44). Animal models demonstrate that even brief periods of hypoxia during critical developmental windows can produce lasting alterations in brain structure, neurochemistry, and behavior reminiscent of ASD (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). In humans, markers of perinatal hypoxia including low Apgar scores, umbilical cord complications, fetal distress, and need for resuscitation have been associated with increased ASD risk in multiple studies (\u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMaternal hemorrhage and placental complications such as placental abruption, preeclampsia, and placental insufficiency have been linked to ASD risk through mechanisms involving chronic fetal hypoxia, inflammatory signaling, and impaired nutrient delivery (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Preeclampsia, characterized by maternal hypertension and proteinuria, is associated with placental vascular abnormalities that compromise uteroplacental blood flow, potentially resulting in fetal growth restriction and chronic oxygen deprivation (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). A large case-control study found significantly elevated ASD risk among children born to mothers with preeclampsia or other indicators of placental insufficiency, with children with ASD twice as likely to have been exposed to preeclampsia in utero (adjusted OR 2.36; 95% CI 1.18\u0026ndash;4.68), and risk increasing in proportion to preeclampsia severity (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAntenatal corticosteroid administration for fetal lung maturation in threatened preterm labor represents a ubiquitous intervention in high-risk obstetrics, with established benefits for reducing neonatal respiratory morbidity and mortality (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). However, concerns have been raised about potential long-term neurodevelopmental effects of glucocorticoid exposure during critical windows of brain development, based on animal studies showing that prenatal corticosteroids can alter neuronal differentiation, synaptic pruning, stress axis programming, and behavior (\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Human follow-up studies of single-course antenatal corticosteroids administered at appropriate gestational ages have generally been reassuring, showing no adverse effects on cognitive development or psychiatric outcomes (\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). However, observational studies have reported associations between antenatal corticosteroid exposure and increased risk of mental and behavioral disorders, though these findings are likely confounded by the underlying pregnancy complications necessitating treatment (\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). A 2025 Danish cohort study of 1.06\u0026nbsp;million infants reported that prenatal glucocorticoid exposure was associated with higher risk of some mental disorders; however, the study explicitly acknowledges that confounding cannot be ruled out and that disease severity could not be controlled for in comparisons of offspring born to mothers with vs without the same underlying illness. Notably, this Danish study included all systemic glucocorticoids (including chronic prednisolone for autoimmune/inflammatory conditions) rather than being limited to acute antenatal betamethasone/dexamethasone for preterm prevention. A quasi-experimental study that compared children born just before vs just after the clinical cutoff for antenatal corticosteroid administration (thereby comparing high-probability vs minimal exposure while minimizing confounding by indication) found little evidence of increased ADHD risk in the exposed group, providing reassurance that confounding by indication likely explains the associations observed in purely observational studies. These conflicting findings underscore the challenge of disentangling causal effects of antenatal corticosteroids from confounding by the severe pregnancy complications (preterm labor, preeclampsia, maternal infection) that necessitate their administration\u0026mdash;complications that themselves carry substantial risks for offspring neurodevelopmental disorders (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite decades of research, fundamental questions remain regarding which prenatal and perinatal exposures represent genuine causal contributors to ASD versus markers of underlying familial susceptibility, how these environmental factors interact with genetic variants to modify risk, what biological mechanisms mediate observed associations, and whether modifiable risk factors exist that could serve as targets for preventive interventions. Large, population-based cohort studies with comprehensive exposure assessment, long-term neurodevelopmental follow-up, and appropriate control for confounding are essential to address these questions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Aim of the Study\u003c/h2\u003e \u003cp\u003eThe primary aim of this study was to comprehensively investigate prenatal and perinatal risk factors associated with autism spectrum disorder in offspring using a large, national birth cohort. Specific objectives were to:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCompare maternal demographic characteristics and pregnancy exposures (including medications) between mothers of children with ASD and control pregnancies\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAssess the prevalence of obstetric complications and delivery outcomes in ASD versus control groups\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEvaluate neonatal characteristics and early morbidity patterns, with particular focus on respiratory complications as markers of perinatal hypoxia\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCalculate odds ratios and confidence intervals for significant risk factors to quantify the magnitude of associations\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInterpret findings in the context of contemporary understanding of ASD etiology, including potential biological mechanisms and considerations of causality versus confounding\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eForm subgroups for autism and high functional autism and compare results\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eWe hypothesized that ASD cases would demonstrate elevated rates of extreme prematurity, perinatal hypoxic events (reflected in respiratory complications), and obstetric complications compared to controls, and that these associations would remain significant after accounting for maternal age and other demographic factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Design and Setting\u003c/h2\u003e \u003cp\u003eThis was a retrospective, population-based cohort study using data from the Slovenian National Perinatal Information System, which prospectively records all deliveries in Slovenia. The cohort included all singleton pregnancies delivered between 1 January 2005 and 31 December 2017, providing near-complete national coverage of births during this 12-year period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Study Population and Case Ascertainment\u003c/h2\u003e \u003cp\u003eThe source population comprised 302,476 singleton pregnancies recorded in the national registry during the study period. Children with autism spectrum disorder (ASD) were identified through linkage with national clinical diagnostic records using ICD-10 codes corresponding to autism spectrum conditions, including childhood autism and Asperger syndrome, subsequently harmonized into a single ASD category according to DSM-5 criteria. The final ASD group included 117 children with a confirmed clinical diagnosis of ASD, while all remaining singleton births without ASD formed the comparison group (\u0026ldquo;all others\u0026rdquo;; n\u0026thinsp;=\u0026thinsp;302,322).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Sources and Variables\u003c/h2\u003e \u003cp\u003ePerinatal data were obtained from standardized registry fields completed at delivery, including maternal characteristics, pregnancy complications, delivery variables, and neonatal outcomes. Maternal variables included age, use of selected medications during pregnancy (dexamethasone, iron supplements, folic acid, antihypertensives, and thyroid medications), and obstetric complications such as postpartum hemorrhage. Pregnancy and delivery variables included gestational age at birth, mode of delivery (vaginal vs cesarean section), onset of labor (spontaneous vs induced), and occurrence of preterm birth defined as delivery before 37 completed weeks, with a predefined subgroup of early preterm birth before 31 weeks. Neonatal variables included sex, small for gestational age (SGA), respiratory distress syndrome (RDS), transient tachypnea of the newborn (TTN), need for mechanical ventilation, surfactant administration, and use of early intervention services documented in the registry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Definitions of Exposures and Outcomes\u003c/h2\u003e \u003cp\u003ePreterm birth was defined as delivery at gestational age\u0026thinsp;\u0026lt;\u0026thinsp;37 weeks, and early preterm birth as \u0026lt;\u0026thinsp;31 weeks. Postpartum hemorrhage was defined in the registry as estimated blood loss\u0026thinsp;\u0026gt;\u0026thinsp;500 mL following delivery. SGA was recorded when birth weight was below the gestational age\u0026ndash; and sex-specific threshold used in the national perinatal system. Neonatal respiratory morbidity included RDS, TTN, requirement for mechanical ventilation, and surfactant administration as recorded by attending clinicians. Early intervention services captured referrals to developmental or rehabilitative services in early childhood as coded in the linked registry data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical Analysis\u003c/h2\u003e \u003cp\u003eMaternal age was analyzed as a continuous variable and summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while all other variables were analyzed as categorical percentages. Group comparisons between ASD cases and all other pregnancies used chi-square tests for categorical variables and analysis of variance (ANOVA) for continuous variables. Crude odds ratios (OR) with 95% confidence intervals (CI) were calculated using logistic regression to quantify associations between ASD and each exposure, with ASD as the outcome and the \u0026ldquo;all others\u0026rdquo; group as the reference. A two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using MedCalc statistical software (MedCalc Software Ltd., Ostend, Belgium).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Ethical Considerations\u003c/h2\u003e \u003cp\u003eThe registry-based component of this study was approved by the National Institute of Public Health responsible for registry-data approvals (approval number: [968- 1 0O/1 8\u0026thinsp;\u0026minus;\u0026thinsp;1 /007]) on 26th February 2018. The analysis was conducted on fully anonymized data extracted from the National Perinatal Information System and linked health records. In line with national regulations and the terms of this approval, individual informed consent was not required, and a waiver of consent was granted for this retrospective use of anonymized registry data. All procedures complied with national regulations on personal data protection and with the principles of the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe demographic characteristics, medication exposures, and obstetric and neonatal outcomes for the ASD group (n\u0026thinsp;=\u0026thinsp;117) compared to the general population (n\u0026thinsp;=\u0026thinsp;302,322) are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaternal, Obstetric, and Neonatal Characteristics by Study Group Comparison of maternal demographics, pregnancy complications, medication use, delivery outcomes, and neonatal interventions among autism spectrum disorder (ASD), control, and all other pregnancies (n\u0026thinsp;=\u0026thinsp;302,476).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eASD (n\u0026thinsp;=\u0026thinsp;117)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll Others (n\u0026thinsp;=\u0026thinsp;302,322)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.55\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication use (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDexamethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron supplements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntihypertensives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid medications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetric outcomes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreterm birth (\u0026lt;\u0026thinsp;37 weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.93 (1.14\u0026ndash;3.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly preterm (\u0026lt;\u0026thinsp;31 weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.14 (1.28\u0026ndash;7.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostpartum hemorrhage (\u0026gt;\u0026thinsp;500 mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.70 (1.26\u0026ndash;5.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.64 (1.09\u0026ndash;2.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpontaneous labor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal outcomes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.88 (2.98\u0026ndash;7.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall for gestational age (SGA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVentilation required\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.26 (1.04\u0026ndash;10.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurfactant administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.55 (2.08\u0026ndash;20.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory distress syndrome (RDS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.42 (1.67\u0026ndash;7.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransient tachypnea of newborn (TTN)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.017*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.90 (1.44\u0026ndash;10.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly intervention services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.98 (1.73\u0026ndash;5.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. OR\u0026thinsp;=\u0026thinsp;Odds ratio comparing ASD versus All Others. CI\u0026thinsp;=\u0026thinsp;Confidence interval.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Results: Detailed Interpretation\u003c/h2\u003e \u003cp\u003eThis study enrolled 117 children with autism spectrum disorder (ASD). Comprehensive prenatal and perinatal data were extracted from the National Registry for a study group as well as for the entire cohort of 302,476 singleton pregnancies delivered during the 2005\u0026ndash;2017 period. This design enabled comparison of ASD cases against the broader population to identify prenatal and perinatal risk factors associated with autism diagnosis.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Demographics\u003c/h2\u003e \u003cp\u003eMaternal age showed no significant difference across groups (ASD: 30.03\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59 years; All others: 29.55\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80 years; p\u0026thinsp;=\u0026thinsp;0.180), eliminating advanced maternal age as a confounding variable in this cohort and suggesting that observed associations operate independently of maternal age effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Medication Exposure Patterns\u003c/h2\u003e \u003cp\u003eDexamethasone use was 3.4-fold higher in ASD pregnancies (9.6%) compared to the general cohort (2.8%), reflecting increased obstetric interventions for threatened preterm labor requiring fetal lung maturation. This association likely represents confounding by indication rather than direct neurodevelopmental toxicity, as dexamethasone administration signals high-risk pregnancies with impending preterm delivery. Iron supplementation was slightly elevated in ASD (49.7% vs 41.8%), possibly indicating higher maternal anemia prevalence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Obstetric Complications and Delivery Outcomes\u003c/h2\u003e \u003cp\u003ePreterm birth demonstrated a dose-response relationship with ASD risk. Overall preterm delivery (\u0026lt;\u0026thinsp;37 weeks) occurred in 13.7% of ASD pregnancies versus 7.6% in all others (p\u0026thinsp;=\u0026thinsp;0.021; OR\u0026thinsp;=\u0026thinsp;1.93, 95% CI: 1.14\u0026ndash;3.26), representing a near-doubling of risk. More strikingly, early preterm birth (\u0026lt;\u0026thinsp;31 weeks) was three times more frequent in ASD (4.2% vs 1.4%; p\u0026thinsp;=\u0026thinsp;0.024; OR\u0026thinsp;=\u0026thinsp;3.14, 95% CI: 1.28\u0026ndash;7.70). This pronounced association at extremes of prematurity aligns with neurobiological plausibility: birth before 31 weeks disrupts critical third-trimester neurodevelopmental processes including cortical organization, synaptogenesis, myelination, and establishment of neural circuits.\u003c/p\u003e \u003cp\u003ePostpartum hemorrhage (\u0026gt;\u0026thinsp;500 mL) was 2.7-fold higher in ASD pregnancies (6.0% vs 2.3%; p\u0026thinsp;=\u0026thinsp;0.019; OR\u0026thinsp;=\u0026thinsp;2.70, 95% CI: 1.26\u0026ndash;5.81), implicating placental dysfunction, abnormal trophoblast invasion, or coagulation abnormalities that compromise uteroplacental perfusion and fetal oxygenation. Maternal bleeding complications may reflect underlying inflammatory or thrombotic disorders affecting placental function and fetal brain development.\u003c/p\u003e \u003cp\u003eCesarean section rates were significantly elevated in ASD (26.5% vs 18.0%; p\u0026thinsp;=\u0026thinsp;0.023; OR\u0026thinsp;=\u0026thinsp;1.64, 95% CI: 1.09\u0026ndash;2.48), though this association may reflect underlying obstetric complications necessitating surgical delivery rather than mode of delivery per se contributing to ASD risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Neonatal Characteristics and Respiratory Morbidity\u003c/h2\u003e \u003cp\u003eThe most striking finding was pronounced male predominance in ASD: 83.7% of cases were male compared to 51.4% in the general population (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;4.88, 95% CI: 2.98\u0026ndash;7.97). This nearly 5-fold increase in odds exceeds the typically reported 3\u0026ndash;4:1 male-to-female ratio in ASD epidemiology, potentially reflecting diagnostic ascertainment bias, female protective factors, or genuine sex-specific vulnerability to prenatal insults mediated by sex chromosomes and hormonal influences.\u003c/p\u003e \u003cp\u003eRespiratory complications emerged as a dominant cluster of neonatal risk factors:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eRespiratory distress syndrome (RDS): 6.8% vs 2.1% (p\u0026thinsp;=\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;3.42, 95% CI: 1.67\u0026ndash;7.02)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTransient tachypnea of newborn (TTN): 3.4% vs 0.9% (p\u0026thinsp;=\u0026thinsp;0.017; OR\u0026thinsp;=\u0026thinsp;3.90, 95% CI: 1.44\u0026ndash;10.57)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSurfactant administration: 2.5% vs 0.4% (p\u0026thinsp;=\u0026thinsp;0.003; OR\u0026thinsp;=\u0026thinsp;6.55, 95% CI: 2.08\u0026ndash;20.65)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMechanical ventilation: 2.5% vs 0.8% (p\u0026thinsp;=\u0026thinsp;0.105; OR\u0026thinsp;=\u0026thinsp;3.26, 95% CI: 1.04\u0026ndash;10.27)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThese findings strongly implicate perinatal hypoxia-ischemia as a mechanistic contributor to ASD risk. Recent research demonstrates that markers of perinatal oxygen deprivation\u0026mdash;including RDS, low Apgar scores, umbilical cord complications, and need for respiratory support\u0026mdash;are robustly associated with increased ASD risk. Experimental models reveal that even transient hypoxia during critical neurodevelopmental windows disrupts synaptogenesis, alters cortical organization, damages subcortical structures (particularly thalamus and basal ganglia), and triggers persistent neuroinflammatory cascades. The 6.5-fold increase in surfactant requirement represents the highest odds ratio among all measured outcomes, emphasizing the severity of respiratory compromise in ASD-associated pregnancies.\u003c/p\u003e \u003cp\u003eEarly intervention services were utilized 2.7-fold more frequently in ASD (12.8% vs 4.7%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; OR\u0026thinsp;=\u0026thinsp;2.98, 95% CI: 1.73\u0026ndash;5.13), reflecting both the developmental needs of children who will later receive autism diagnoses and potentially earlier recognition of developmental concerns prompting timely referral.\u003c/p\u003e \u003cp\u003eTo visualize the magnitude and pattern of significant risk factor associations identified in our study, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents a comparative analysis of nine key pregnancy and birth outcomes that demonstrated statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) when comparing the ASD group to the general population cohort. This graphical representation serves several analytical purposes: it illustrates the breadth of affected domains (extreme prematurity, obstetric hemorrhage, and neonatal respiratory complications), demonstrates the dose-response relationship for prematurity outcomes, highlights the remarkable male sex predominance in ASD, and quantifies the magnitude of increased risk across outcomes of varying clinical severity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays nine outcomes organized into four thematic categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Prematurity outcomes (early preterm birth\u0026thinsp;\u0026lt;\u0026thinsp;31 weeks and preterm birth\u0026thinsp;\u0026lt;\u0026thinsp;37 weeks), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Obstetric complications (postpartum hemorrhage\u0026thinsp;\u0026gt;\u0026thinsp;500 mL and male sex), (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Neonatal respiratory interventions (mechanical ventilation requirement, surfactant administration, respiratory distress syndrome, and transient tachypnea), and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Developmental services (early intervention service utilization). Each outcome is presented as a horizontal bar chart comparing the prevalence percentage in the ASD group (dark blue bars) versus the general population cohort (light blue bars), with the actual percentage labeled on each bar for precise interpretation.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displays pregnancy medication utilization patterns comparing autism spectrum disorder (ASD) cases (n\u0026thinsp;=\u0026thinsp;117) to the national cohort (n\u0026thinsp;=\u0026thinsp;302,322). Dexamethasone exposure was significantly elevated in ASD pregnancies (9.6% vs. 2.8%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), reflecting the higher prevalence of threatened preterm labor requiring antenatal corticosteroid administration for fetal lung maturation. This elevation likely represents confounding by indication rather than direct medication neurotoxicity. Iron supplementation showed modest elevation (49.7% vs. 41.8%). Folic acid (66.2% vs. 64.7%), antihypertensives (1.7% vs. 1.4%), and thyroid medications (0.8% vs. 1.4%) showed comparable rates across groups\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Integrated Interpretation\u003c/h2\u003e \u003cp\u003eThe results reveal convergent risk pathways centered on placental dysfunction, extreme prematurity, and perinatal hypoxia-ischemia. The associations between ASD and early preterm birth, postpartum hemorrhage, and neonatal respiratory complications form a coherent mechanistic narrative: compromised placentation leads to maternal hemorrhagic complications and preterm delivery, which in turn increases risk of neonatal respiratory failure and hypoxic brain injury. These obstetric and neonatal stressors likely interact with underlying genetic susceptibility\u0026mdash;potentially mediated by sex chromosomes and autism risk genes\u0026mdash;to perturb neurodevelopmental trajectories.\u003c/p\u003e \u003cp\u003eHowever, causality cannot be inferred from observational data, as recent family-based studies demonstrate that many prenatal risk factor associations are attenuated after controlling for familial confounding.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis large national cohort study of 302,476 pregnancies provides comprehensive evidence for multiple prenatal and perinatal factors associated with autism spectrum disorder in offspring. The most robust findings include profound male sex bias (OR\u0026thinsp;=\u0026thinsp;4.88), elevated rates of extreme prematurity (OR\u0026thinsp;=\u0026thinsp;3.14 for birth\u0026thinsp;\u0026lt;\u0026thinsp;31 weeks), increased obstetric hemorrhage (OR\u0026thinsp;=\u0026thinsp;2.70), and markedly higher neonatal respiratory complications\u0026mdash;particularly respiratory distress syndrome (OR\u0026thinsp;=\u0026thinsp;3.42) and surfactant administration (OR\u0026thinsp;=\u0026thinsp;6.55). These associations form a coherent mechanistic narrative centered on placental dysfunction, perinatal hypoxia-ischemia, and oxidative stress as potential contributors to neurodevelopmental vulnerability in genetically susceptible individuals.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Male Predominance and Sex-Specific Vulnerability\u003c/h2\u003e \u003cp\u003eThe observed male predominance of 83.7% in our ASD cohort, yielding an odds ratio of 4.88 (95% CI: 2.98\u0026ndash;7.97), substantially exceeds the general population sex ratio and aligns with the well-established 3\u0026ndash;4:1 male-to-female ratio reported in ASD epidemiology. This pronounced sex bias likely reflects multiple interacting mechanisms operating at genetic, hormonal, and developmental levels (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the genetic level, several mechanisms may contribute to male vulnerability. The X chromosome harbors a disproportionate number of genes involved in brain development and synaptic function, and males' hemizygous state for X-linked genes means that deleterious variants cannot be compensated by a second X chromosome as in females (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Conversely, the \"female protective effect\" hypothesis posits that females require a higher mutational burden to manifest ASD, supported by evidence that female ASD cases carry more deleterious copy number variants and disruptive mutations than males (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). Skewed X-inactivation, genomic imprinting of parent-of-origin alleles, and genes that escape X-inactivation represent additional sex chromosome mechanisms that may modulate ASD risk differentially in males versus females (\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrenatal sex steroid hormones, particularly testosterone, represent another critical pathway mediating sex differences in ASD. The \"extreme male brain\" theory proposes that elevated fetal testosterone exposure during critical windows of brain sexual differentiation increases autistic traits by masculinizing cognitive and behavioral profiles (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Supporting evidence includes findings that amniotic fluid testosterone levels correlate with later autistic traits, that maternal conditions involving androgen excess (polycystic ovary syndrome) are associated with increased offspring ASD risk, and that steroidogenic activity is elevated during fetal development in males who are subsequently diagnosed with ASD (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e). The placenta plays a central role in this pathway, as it exhibits sexual dimorphism in steroid hormone production, with male placentas generating higher testosterone levels that may influence brain development (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlacental sex differences extend beyond steroid production to include differential inflammatory responses and vulnerability to pregnancy complications. Male placentas show greater susceptibility to early pregnancy insults, produce more pro-inflammatory cytokines in response to maternal immune activation, and express different levels of genes involved in immune regulation and neurodevelopmental signaling (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). A recent study demonstrated that maternal immune activation produces sex-specific effects on placental cytokine profiles, with male offspring showing elevated GM-CSF, IL-6, and TNF-α\u0026mdash;cytokines known to influence synaptic development\u0026mdash;whereas females showed different patterns (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). These placental sex differences may create differential prenatal environments that modulate brain development trajectories and ASD susceptibility.\u003c/p\u003e \u003cp\u003eDifferential vulnerability to perinatal hypoxia may also contribute to male predominance, as experimental evidence suggests that male brains are more susceptible to hypoxic-ischemic injury than female brains, potentially mediated by sex differences in oxidative stress responses, antioxidant enzyme expression, mitochondrial function, and inflammatory signaling (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). In our cohort, the strong associations between ASD and markers of perinatal hypoxia (RDS, ventilation, surfactant) may disproportionately affect males if they have reduced capacity to withstand oxygen deprivation during the vulnerable perinatal transition.\u003c/p\u003e \u003cp\u003eThe interaction between genetic susceptibility and environmental exposures likely differs by sex, with males potentially showing greater sensitivity to prenatal insults in the context of vulnerable genotypes. Gene-environment interaction models suggest that early prenatal stress, including hypoxia and inflammation, may be especially detrimental to males carrying ASD risk variants (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Extreme Prematurity and Interrupted Neurodevelopment\u003c/h2\u003e \u003cp\u003eThe 3-fold elevation in early preterm birth (\u0026lt;\u0026thinsp;31 weeks gestation) among ASD cases (OR\u0026thinsp;=\u0026thinsp;3.14; 95% CI: 1.28\u0026ndash;7.70) represents a critical finding with strong neurobiological plausibility. Birth before 31 weeks interrupts the third trimester of pregnancy, a period of extraordinarily rapid and complex brain development during which critical processes are unfolding that establish the foundation for later cognitive and social function (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDuring the third trimester, the fetal brain undergoes a dramatic expansion in cortical volume, driven by proliferation of neurons and glia, elaboration of dendritic trees, and formation of billions of synaptic connections (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). The cortical surface area increases exponentially as primary gyri and sulci form through coordinated programs of neuronal migration, differential growth, and mechanical forces (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). Premature birth interrupts this process, resulting in altered patterns of cortical folding, reduced cortical thickness and surface area, and abnormal organization of cortical layers\u0026mdash;structural abnormalities that have been documented in neuroimaging studies of individuals with ASD (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSynaptogenesis\u0026mdash;the formation of synaptic connections between neurons\u0026mdash;reaches peak velocity during the third trimester and continues through early postnatal life (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). This process is exquisitely sensitive to oxygen availability, as synaptic formation requires substantial energy expenditure and involves oxygen-dependent enzymatic processes. Hypoxic disruption of synaptogenesis may lead to altered patterns of synaptic connectivity, potentially contributing to the aberrant neural circuits implicated in ASD (\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e). Consistent with this, ASD is characterized by evidence of both excessive local connectivity (over-connectivity within specific brain regions) and reduced long-range connectivity (under-connectivity between distant regions), patterns that could arise from disrupted synaptic refinement during critical periods (\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMyelination\u0026mdash;oligodendrocytes, the cells responsible for producing myelin, are particularly vulnerable to hypoxic-ischemic injury, and white matter abnormalities are common sequelae of prematurity (\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). Diffusion tensor imaging studies in ASD have consistently identified altered white matter microstructure, suggesting abnormalities in myelination or axonal organization that could stem from perinatal disruptions (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSubcortical structures critical for social cognition, emotional regulation, and sensory processing\u0026mdash;including the thalamus, amygdala, hippocampus, and basal ganglia\u0026mdash;undergo critical developmental processes during the third trimester (\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e). Neuroimaging studies have found that individuals with ASD who experienced prenatal hypoxia show enlarged third ventricle volumes and thalamic abnormalities that correlate with sensory dysfunction and sleep disturbances\u0026mdash;core features of ASD (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe association between prematurity and ASD may be confounded by underlying maternal and fetal conditions that precipitate preterm delivery and may independently affect neurodevelopment. Spontaneous preterm birth often occurs in the context of intrauterine infection and inflammation, placental insufficiency, maternal autoimmune conditions, or fetal genetic abnormalities\u0026mdash;factors that may themselves contribute to ASD risk through inflammatory, hypoxic, or direct genetic mechanisms (\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e). Recent sibling-comparison studies have shown that associations between preterm birth and ASD are attenuated when comparing preterm and term siblings within the same family, suggesting that shared familial factors (genetic variants, maternal characteristics, environmental exposures) contribute substantially to observed population-level associations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe dose-response relationship observed in our study\u0026mdash;with stronger associations at more extreme degrees of prematurity\u0026mdash;supports biological plausibility but also raises questions about confounding, as extreme prematurity is more likely to result from severe underlying pathology. The fact that overall preterm birth (\u0026lt;\u0026thinsp;37 weeks) showed weaker association (OR\u0026thinsp;=\u0026thinsp;1.93) than early preterm birth (\u0026lt;\u0026thinsp;31 weeks; OR\u0026thinsp;=\u0026thinsp;3.14) suggests that ASD risk is concentrated among the most severely premature infants, consistent with mechanisms involving hypoxic-ischemic brain injury and interrupted neurodevelopment being most pronounced at extreme gestational ages (\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Perinatal Hypoxia and Oxidative Stress\u003c/h2\u003e \u003cp\u003eThe significant increase in neonatal respiratory complications among ASD cases, such as mechanical ventilation (OR\u0026thinsp;=\u0026thinsp;3.26), TTN (OR\u0026thinsp;=\u0026thinsp;3.90), surfactant administration (OR\u0026thinsp;=\u0026thinsp;6.55), and RDS (OR\u0026thinsp;=\u0026thinsp;3.42), offers strong evidence that perinatal hypoxia-ischemia is a mechanistic factor in ASD risk. These results are consistent with the increasing understanding that oxidative stress is a fundamental pathophysiological characteristic of ASD and with a variety of data from mechanistic studies, animal models, and biomarker research showing that oxygen deprivation during critical windows can result in long-lasting neurodevelopmental effects (\u003cspan additionalcitationids=\"CR91\" citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRespiratory distress syndrome results from surfactant deficiency in immature lungs, leading to alveolar collapse, impaired gas exchange, and resultant hypoxemia (\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e). The consequent reduction in arterial oxygen content compromises oxygen delivery to the brain, creating cellular hypoxia that disrupts energy-dependent neurodevelopmental processes. When oxygen availability is insufficient, ATP production via oxidative phosphorylation declines, forcing cells to rely on anaerobic glycolysis\u0026mdash;an inefficient pathway that produces lactate and acidosis (\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnergy failure from hypoxia triggers a cascade of cellular injury mechanisms. Insufficient ATP impairs the function of Na+/K\u0026thinsp;+\u0026thinsp;ATPase pumps that maintain electrochemical gradients across cell membranes, leading to membrane depolarization and uncontrolled influx of calcium ions (Ca2+) into cells (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e). Excessive intracellular Ca2\u0026thinsp;+\u0026thinsp;activates proteases, lipases, and nucleases that damage cellular structures; triggers excitotoxicity through excessive glutamate release and NMDA receptor activation; and activates apoptotic cell death pathways (\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e). These mechanisms are particularly detrimental during neurodevelopment when programmed cell death must be tightly regulated and excessive neuronal loss can permanently alter circuit formation (\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIronically, by producing reactive oxygen species (ROS), reperfusion\u0026mdash;the process of restoring oxygen delivery\u0026mdash;after hypoxia can be just as harmful as hypoxia itself. During hypoxia, the electron transport chain in mitochondria becomes disrupted, and enzymes such as xanthine oxidase accumulate in partially reduced states (\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e). When oxygen is reintroduced, these systems generate superoxide anion (O2- \u0026minus;), hydrogen peroxide (H2O2), and hydroxyl radical (- OH)\u0026mdash;highly reactive molecules that oxidize lipids, proteins, and nucleic acids. The immature brain is particularly vulnerable to oxidative damage due to high lipid content (myelin membranes are especially susceptible to lipid peroxidation), high metabolic rate, relatively low antioxidant defense capacity, and high iron content that catalyzes ROS production via Fenton reactions (\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e)..\u003c/p\u003e \u003cp\u003eOxidative stress has been shown to be a key pathophysiological characteristic of ASD. Biomarker studies have consistently documented altered redox status in individuals with ASD, including decreased levels of the primary cellular antioxidant glutathione (particularly the reduced form, GSH), increased lipid peroxidation products (malondialdehyde, isoprostanes), elevated markers of protein oxidation (protein carbonyls), and altered activities of antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase) (\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn ASD, mitochondrial dysfunction both contributes to and results from oxidative stress. Under physiological conditions, mitochondria are the main generator of cellular ROS because of electron leakage from the respiratory chain. Oxidative damage to mitochondrial DNA, lipids, and proteins also impairs mitochondria's ability to function. On the other hand, an endless loop of oxidative damage is produced when mitochondrial malfunction results in decreased ATP synthesis and increased ROS generation (\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e). Multiple studies have identified mitochondrial abnormalities in ASD, including respiratory chain enzyme deficiencies, altered mitochondrial membrane potential, abnormal mitochondrial morphology, and increased susceptibility to mitochondrial permeability transition pore opening\u0026mdash;a catastrophic event that triggers apoptosis (\u003cspan additionalcitationids=\"CR104\" citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e). Some individuals with ASD have primary genetic mitochondrial disorders, but mitochondrial dysfunction appears to be a broader feature present in substantial subsets of ASD cases even without identified genetic causes (\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxidative stress activates inflammatory signaling cascades, creating additional neurodevelopmental risk through neuroinflammation. ROS activate redox-sensitive transcription factors including NF-κB, which upregulates expression of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α), chemokines, and adhesion molecules (\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e).These inflammatory mediators can disturb synaptic formation and function, activate microglia, the brain's resident immune cells, and penetrate the blood-brain barrier, which may be weakened by oxidative damage. Neuroinflammation has been extensively documented in ASD through postmortem studies showing activated microglia and astrocytes, elevated brain tissue cytokine levels, and peripheral immune abnormalities (\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEpigenetic dysregulation represents another mechanism through which oxidative stress may exert lasting effects on neurodevelopment. ROS have the ability to affect chromatin structure, histone post-translational modifications, and DNA methylation patterns, which can result in changed gene expression programs that last after the initial oxidative attack (\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e).These epigenetic changes may affect genes critical for synaptic development, neuronal differentiation, and other neurodevelopmental processes, creating lasting alterations in brain structure and function (\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe strongest correlation found in our study is a 6.5-fold increase in surfactant administration among ASD cases (OR\u0026thinsp;=\u0026thinsp;6.55; 95% CI: 2.08\u0026ndash;20.65; p\u0026thinsp;=\u0026thinsp;0.003), suggesting that the most severe respiratory compromise\u0026mdash;requiring exogenous surfactant to maintain gas exchange\u0026mdash;carries a notably high risk. Although surfactant therapy is vital and life-saving for RDS, infants who require it are those who have the most acute respiratory failure and lung immaturity, with the resulting severe hypoxemia both before and after treatment (\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough mechanical ventilation is required to promote gas exchange in respiratory failure, it presents iatrogenic dangers, such as systemic inflammation from ventilator-associated lung injury, oxygen toxicity from hyperoxia during treatment, and ventilator-induced lung injury from barotrauma and volutrauma. The systemic inflammatory response triggered by ventilator-induced lung injury can produce circulating cytokines that reach the brain and contribute to neuroinflammation. Additionally, the transition from hypoxia to hyperoxia during aggressive oxygen therapy can exacerbate oxidative stress through ROS generation (\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eASD was also substantially linked to transient tachypnea in newborns, which is often self-limiting syndrome involving delayed clearance of fetal lung fluid (OR\u0026thinsp;=\u0026thinsp;3.90; 95% CI: 1.44\u0026ndash;10.57; p\u0026thinsp;=\u0026thinsp;0.017). This finding is somewhat unexpected because TTN does not usually involve hypoxemia. It could indicate that TTN is a sign of subtle underlying neurological or cardiorespiratory dysfunction, or it could indicate that the association is a result of confounding by gestational age or delivery method (because vaginal delivery lacks thoracic compression, cesarean section is a risk factor for TTN) (\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e, \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Placental Dysfunction and Obstetric Hemorrhage\u003c/h2\u003e \u003cp\u003eThe 2.7-fold increase in postpartum hemorrhage (\u0026gt;\u0026thinsp;500 mL) among pregnancies with ASD (OR\u0026thinsp;=\u0026thinsp;2.70; 95% CI: 1.26\u0026ndash;5.81; p\u0026thinsp;=\u0026thinsp;0.019) suggests that vascular abnormalities and placental dysfunction may be risk factors for ASD. Postpartum hemorrhage most commonly results from uterine atony (inadequate contraction of the uterus after delivery), but can also stem from placental abnormalities (retained placental tissue, placenta accreta), coagulation disorders, or genital tract trauma (\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe placenta represents the critical interface between maternal and fetal circulations, responsible for nutrient transfer, gas exchange, waste removal, endocrine signaling, and immunological regulation (\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e). Through a variety of mechanisms, such as chronic hypoxia from insufficient oxygen transfer, nutrient restriction that results in fetal growth restriction, altered hormone exposure that affects brain sexual differentiation, and inflammatory signaling that triggers fetal immune responses, placental dysfunction can impair fetal development.\u003c/p\u003e \u003cp\u003eNumerous studies have directly connected placental insufficiency\u0026mdash;inadequate placental function to meet fetal metabolic demands\u0026mdash;to the risk of ASD. This condition frequently presents as fetal growth restriction, or small-for-gestational-age newborns (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan additionalcitationids=\"CR119\" citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e). A large case-control study found that preeclampsia and other indicators of placental insufficiency were significantly associated with ASD and intellectual disability in offspring (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In terms of mechanism, placental insufficiency results in oxidative stress and persistent fetal hypoxia, limits the transport of nutrients (which may impact brain growth and myelination), and may cause compensatory reactions in the fetal hypothalamic-pituitary-adrenal axis that modify neurodevelopment (\u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne particularly strong risk factor for ASD is placental inflammation, which is defined by the infiltration of inflammatory cells into placental tissues and increased cytokine production. Even after controlling for maternal psychiatric history and medication use, a large cohort study revealed that fetal inflammatory response syndrome (FIRS), which is characterized by the presence of chorionic vasculitis and/or funisitis on placental histopathology, significantly increases the risk of ASD, ADHD, conduct disorder, and PTSD (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Inflammatory insults during the prenatal period could influence neurodevelopmental paths toward psychiatric susceptibility, as evidenced by the increased probabilities of diagnosing ASD in children delivered with placentas that met FIRS criteria (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe sexual dimorphism of the placenta may contribute to male vulnerability to placental complications. Compared to female placentas, male placentas have different gene expression patterns, generate different inflammatory responses to maternal immune activation, and are more vulnerable to early pregnancy insults (\u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e). These sex-specific variations in placental function could result in unique prenatal settings that affect brain development and the risk of ASD in ways that are specific to each sex.\u003c/p\u003e \u003cp\u003eAbnormal implantation (placenta previa, placenta accreta), placental abruption, or insufficient spiral artery remodeling that impairs uteroplacental blood flow are some of the underlying placental vascular abnormalities that may be reflected in postpartum hemorrhage. Chronic placental hypoxia brought on by these vascular anomalies can cause oxidative stress and inflammatory signaling in the placental tissues, which may spread to the fetus. Additionally, if placental perfusion is impaired due to maternal bleeding, hypoxic-ischemic damage may result in abrupt fetal hypoxia (\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother possible connection between maternal haemorrhage and ASD is coagulation disorders, since both bleeding diatheses and thrombophilic conditions (increasing clotting) have been studied in connection with prenatal problems and neurodevelopmental outcomes. Placental thrombosis and infarction can result from maternal autoimmune diseases that involve antibodies against phospholipids or other coagulation factors, impairing placental function (\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e, \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Antenatal Corticosteroids and Confounding by Indication\u003c/h2\u003e \u003cp\u003eThe 3.4-fold increase in dexamethasone use during pregnancy among ASD cases (9.6% vs. 2.8% for all others) must be carefully interpreted in light of confounding by indication, meaning that the association is probably explained by the underlying condition that requires treatment (threatened preterm labour) rather than the treatment itself.\u003c/p\u003e \u003cp\u003eThe basis of obstetric care for women at risk of preterm delivery between 24- and 34-weeks\u0026rsquo; gestation is antenatal corticosteroids, usually betamethasone or dexamethasone. This is supported by strong evidence from randomized trials showing significant decreases in neonatal respiratory distress syndrome, intraventricular haemorrhage, necrotizing enterocolitis, and neonatal mortality (\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe important trial found no differences in cognitive function, behavioural outcomes, or health status at a 30-year follow-up, which is generally comforting in long-term neurodevelopmental follow-up studies of children exposed to acceptable regimens of prenatal corticosteroids (\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e). More recent large cohort studies have similarly found no association between guideline-concordant antenatal corticosteroid exposure and risk of psychiatric disorders including ASD, ADHD, or other mental health conditions (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn line with our finding of a three-fold increase in early preterm delivery, the higher rates of threatened preterm labour in our sample are probably reflected in the higher dexamethasone use among pregnancies with ASD (9.6% vs. 2.8%). The link between ASD and corticosteroid exposure is probably mediated by the underlying maternal-foetal abnormalities that cause threatened preterm labour, such as intrauterine infection, placental insufficiency, cervical insufficiency, or maternal medical issues. The fact that dexamethasone treatment acts as a marker of pregnancies at high risk for preterm delivery and that early preterm birth itself was substantially linked to ASD lend credibility to this interpretation. However, the issue of whether antenatal corticosteroids have separate neurodevelopmental effects is still unanswered and needs more research using carefully planned studies that can evaluate dose-response relationships, account for confounding by indication, and look at susceptible subgroups and possible vulnerability windows.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Cesarean Section and Mode of Delivery\u003c/h2\u003e \u003cp\u003eIt is unclear whether surgical delivery affects ASD risk or if caesarean sections are a sign of underlying complications that require operative delivery, due to the significantly higher caesarean section rate among pregnancies with ASD (26.5% vs. 18.0%; OR\u0026thinsp;=\u0026thinsp;1.64; 95% CI: 1.09\u0026ndash;2.48; p\u0026thinsp;=\u0026thinsp;0.023).\u003c/p\u003e \u003cp\u003eThere has been conflicting research on the relationship between mode of delivery and ASD risk; some studies have found no correlation after controlling for covariates, while others have reported an increased risk with caesarean sections (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR130\" citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough there is little and contradicting evidence, a number of explanations have been put out to explain how caesarean delivery may affect neurodevelopment. One hypothesis involves alterations in the infant microbiome, as caesarean-born infants are not exposed to maternal vaginal and faecal microbiota during birth and show different patterns of gut colonization in early life compared to vaginally delivered infants (\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e). Although causative linkages are yet unknown, the gut microbiota has been linked to ASD through the gut-brain axis. Several studies have shown that people with ASD have altered microbiome composition and gastrointestinal symptoms (\u003cspan additionalcitationids=\"CR134\" citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e135\u003c/span\u003e). Another proposed mechanism involves stress responses, with some authors suggesting that the physiological stress of labour and vaginal delivery may provide beneficial programming of stress-response systems, though evidence is speculative (\u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e136\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMore realistically, a caesarean delivery could be an indication of underlying issues such foetal distress, atypical foetal presentation, placental abnormalities, maternal health issues, or difficulties from a prior pregnancy that have an independent impact on neurodevelopment. The greater rates of preterm, respiratory issues, and obstetric haemorrhage in our sample are probably the cause of the higher caesarean rate among ASD cases, which would raise the possibility of an operational delivery. Uncomfortable foetal cardiac tracings or emergency caesarean sections for foetal distress may indicate episodes of intrapartum hypoxia that lead to brain damage (\u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e137\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCrucially, our analysis found no significant differences in spontaneous labour rates between groups, indicating that the manner of birth itself is not a risk factor in and of itself but rather represents the series of difficulties seen in pregnancies linked to ASD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Early Intervention and Developmental Surveillance\u003c/h2\u003e \u003cp\u003eThe threefold increase in early intervention service use among ASD cases (12.8% vs. 4.7%; OR\u0026thinsp;=\u0026thinsp;2.98; 95% CI: 1.73\u0026ndash;5.13; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) is indicative of both the developmental requirements of children who will subsequently be diagnosed with autism and the possibility of early identification of developmental issues in this group. The fact that developmental issues frequently appear prior to a formal autism diagnosis, which usually takes place between the ages of 2\u0026ndash;4, is consistent with the increased use of early intervention in ASD. Even before autism-specific symptoms are completely evident, parents and medical professionals may notice delays in language development, motor milestones, social interaction, or abnormal behaviours that warrant referral to early intervention. Regardless of the final diagnostic classification, this discovery emphasizes the value of thorough developmental surveillance for children exposed to prenatal risk factors because early detection and intervention can enhance long-term outcomes.\u003c/p\u003e \u003cp\u003eFurthermore, developmental delays, intellectual disabilities, motor impairments, and other disorders that require therapeutic services beyond autism-specific interventions are often co-occurring in children with ASD. Determining whether early intervention was started for autism-related concerns or other developmental issues is difficult due to the overlap between ASD and global developmental delay, especially in children who were born extremely preterm or with serious perinatal abnormalities.\u003c/p\u003e \u003cp\u003eFrom a clinical and public health standpoint, the correlation between perinatal risk factors and the use of early intervention suggests that high-risk infants\u0026mdash;such as those born very preterm, with severe respiratory complications, or with other indicators of perinatal compromise\u0026mdash;can benefit from proactive service referral and targeted developmental surveillance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.8 Maternal Age and Sociodemographic Factors\u003c/h2\u003e \u003cp\u003eIn contrast to meta-analytic evidence that links advanced maternal age (\u0026ge;\u0026thinsp;35 years) to higher risk for ASD, our cohort did not show significant differences in maternal age among groups (p\u0026thinsp;=\u0026thinsp;0.180). With too few pregnancies in older age groups to detect age-stratified effects, this disparity probably reflects the very youthful mean age across all groups (29.6\u0026ndash;31.1 years).\u003c/p\u003e \u003cp\u003eThere are complex links between the diagnosis of ASD and sociodemographic characteristics including as socioeconomic position, education, race/ethnicity, and healthcare access. These relationships include both actual differences in incidence/prevalence and inequalities in diagnostic recognition and service access. We were unable to account for potential confounding by socioeconomic and healthcare characteristics because we lacked data on these variables in our study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.9 Familial Confounding and Causality\u003c/h2\u003e \u003cp\u003eThe possibility of familial confounding\u0026mdash;shared genetic or environmental factors within families that predispose to both pregnancy problems and offspring ASD rather than direct causal effects of prenatal exposures\u0026mdash;is a crucial restriction in interpreting our results. Recent large-scale sibling comparison studies have shown that when comparing affected and unaffected siblings within the same household, many observed links between prenatal variables and ASD are significantly reduced or eliminated (\u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e138\u003c/span\u003e, \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e139\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor example, a Danish study of 1.1\u0026nbsp;million children found that while 30 maternal diagnoses during pregnancy showed population-level associations with ASD, most associations disappeared in within-family analyses, suggesting that familial factors rather than direct exposure effects explained the associations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Similarly, sibling studies of preterm birth and ASD have shown attenuated effects when comparing preterm and term siblings, indicating that familial factors contribute substantially to the observed association (\u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e140\u003c/span\u003e, \u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e141\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.10 Strengths\u003c/h2\u003e \u003cp\u003eThis study has a number of significant advantages that increase trust in the results and their applicability:\u003c/p\u003e \u003cp\u003eLarge cohort based on population: Incorporating 302,476 pregnancies from national birth registries over a 12-year span reduces selection bias present in clinic-based or convenience samples, improves generalizability to the general population, and offers extraordinary statistical power to identify relationships. The assessment of uncommon exposures and outcomes, as well as the discovery of modest effect sizes, are made possible by the huge denominator population.\u003c/p\u003e \u003cp\u003eThorough data collection: By minimizing loss to follow-up and differential participation, which can skew case-control and cohort studies, the use of national registry data guarantees nearly comprehensive ascertainment of births, diagnoses, and outcomes within the healthcare system. Compared to self-reported exposure data, registry-based research reduces measurement error and recall bias by utilizing routinely obtained clinical data.\u003c/p\u003e \u003cp\u003eComprehensive evaluation of several domains: Rather than focusing on isolated single-exposure effects, the study analysed maternal demographics, medication exposures, obstetric complications, delivery characteristics, and neonatal outcomes in an integrated manner, enabling the characterization of risk factor patterns and possible mechanistic pathways.\u003c/p\u003e \u003cp\u003eClinical diagnosis of ASD: To improve diagnostic validity, cases were found using clinical diagnosis based on predetermined diagnostic criteria rather than screening questionnaires or parental reports. However, it is difficult to discover unusual outcomes in registry studies, as seen by the limited number of ASD patients compared to the broad background population.\u003c/p\u003e \u003cp\u003eStandard, suitable methodology for cohort studies includes the use of ANOVA for continuous variables, chi-square testing for categorical comparisons, and logistic regression to compute odds ratios with confidence intervals. Reproducibility and accuracy were guaranteed by the use of established software (MedCalc) for statistical analyses.\u003c/p\u003e \u003cp\u003eBiological plausibility: The findings have biological credibility because the found relationships are consistent with current knowledge of the genesis of ASD and suggested molecular pathways involving placental malfunction, hypoxia-ischemia, oxidative stress, and neuroinflammation.\u003c/p\u003e \u003cp\u003eRelevance to the present: The research period (2005\u0026ndash;2017) offers current data that reflects contemporary infant care standards, obstetric procedures, and diagnostic techniques, improving relevance to contemporary clinical settings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.11 Limitations\u003c/h2\u003e \u003cp\u003eInterpreting the study's conclusions requires considering a number of important limitations:\u003c/p\u003e \u003cp\u003eFew instances of ASD: Only 117 ASD cases were included. Wide confidence intervals for some estimates are the result of the small number of cases, which also restricts statistical power for detecting lower impact sizes and precludes thorough subgroup analysis.\u003c/p\u003e \u003cp\u003eConfounding from unmeasured variables, such as genetic factors, socioeconomic status, maternal education, healthcare access, environmental exposures, paternal characteristics, and postnatal factors, may limit the ability to draw conclusions about causality in this retrospective observational study. Although we corrected for maternal age, analyses did not account for other significant factors.\u003c/p\u003e \u003cp\u003eFamilial confounding: Rather than being the direct result of prenatal exposures, many reported relationships might be the result of shared familial variables (genetic or environmental). We are unable to differentiate these pathways without family-based comparisons.\u003c/p\u003e \u003cp\u003eThe study period (2005\u0026ndash;2017) covers the shift from the DSM-IV to the DSM-5 diagnostic criteria for autism. The DSM-5 (2013) did away with the distinct diagnoses of Asperger syndrome and PDD-NOS in favor of a single ASD spectrum. This change in diagnosis could have an impact on case determination, categorization, and cross-temporal comparability. By merging Asperger and pure autism patients into a single ASD category, we were able to partially alleviate issue.\u003c/p\u003e \u003cp\u003eAbsence of comprehensive clinical data Although registry-based research offers a wide range of coverage, its clinical depth is limited. Mechanistic understanding could be informed by information on placental pathology, prenatal biomarkers (cytokines, oxidative stress markers, hormones), cognitive functioning, co-occurring disorders, ASD symptom severity, precise drug dose and timing, and postnatal environmental exposures.\u003c/p\u003e \u003cp\u003eEvaluation of drug exposure: Information on medications was restricted to general categories (dexamethasone, iron, folic acid, antihypertensives, thyroid drugs) and lacked specifics regarding dosage, occurrence, duration, or indication. This restricts our capacity to evaluate crucial exposure windows or dose-response correlations. Confounding by indication is another significant issue, especially with dexamethasone.\u003c/p\u003e \u003cp\u003eLimited generalizability: Results from a single national registry might not apply to groups with distinct sociodemographic traits, genetic backgrounds, healthcare systems, environmental exposures, or diagnostic procedures. Applicability elsewhere may be limited by the cohort's unique obstetric practices, ASD prevalence, and community factors.\u003c/p\u003e \u003cp\u003eAbsence of mechanistic biomarkers: rather than focusing on the underlying biological mechanisms, the study looked at clinical outcomes (preterm birth, RDS, haemorrhage). Mechanistic inferences might be strengthened by biomarker data on oxidative stress, inflammatory cytokines, placental function, or fetal oxygenation, however these were unavailable.\u003c/p\u003e \u003cp\u003eCross-sectional exposure measurement: Rather than being described in terms of severity, length, or temporal patterns, many exposures (medications, problems) were evaluated as binary (present/absent). For instance, it was not possible to assess the extent and duration of hypoxia during RDS, the severity of placental malfunction, or the gestational age during exposure to dexamethasone.\u003c/p\u003e \u003cp\u003eDespite these drawbacks, the study offers important epidemiological data on prenatal and perinatal variables linked to ASD in a sizable population-based cohort and pinpoints particular risk factors and plausible mechanistic pathways that demand more research in prospective, mechanistic studies.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe 302,476 pregnancies in this extensive nationwide cohort study offer strong evidence for a number of prenatal and postnatal variables linked to autism spectrum disorder in the offspring. The strongest evidence points to perinatal hypoxia-ischemia as a key mechanistic contributor. These findings include significant male sex bias (nearly 5-fold increased odds), elevated rates of extreme prematurity (3-fold increase for birth\u0026thinsp;\u0026lt;\u0026thinsp;31 weeks), increased obstetric hemorrhage (2.7-fold increase), and significantly elevated neonatal respiratory complications, particularly respiratory distress syndrome (3.4-fold) and surfactant administration (6.6-fold).\u003c/p\u003e \u003cp\u003eThese correlations create a logical mechanistic picture that focuses on perinatal hypoxia, oxidative stress, placental malfunction, extreme preterm, and neuroinflammation as interconnected pathways that may disrupt neurodevelopment in people who are genetically predisposed. The biological plausibility of these pathways is supported by the convergence of our findings with substantial evidence from animal models, biomarker studies, and mechanistic research, while also accepting that causality cannot be proved only from observational data.\u003c/p\u003e \u003cp\u003eIn line with established ASD epidemiology, our cohort's marked male predominance underscores the crucial role that sex-specific biological mechanisms\u0026mdash;such as sex chromosome effects, prenatal hormone exposure, placental sexual dimorphism, and differential susceptibility to oxidative stress and hypoxia\u0026mdash;play in mediating the risk for ASD. The intricate relationships between sex, genes, hormones, and environmental exposures that result in the notable male bias in ASD should be further explored in future studies.\u003c/p\u003e \u003cp\u003eThere are still important uncertainties about which prenatal and perinatal exposures are indicators of underlying familial risk and which are actual causal factors. Genetic pleiotropy, maternal traits, and shared environmental factors are thought to play a significant role in the observed population-level relationships, according to recent sibling-comparison studies showing attenuation of numerous prenatal risk factor associations within families. Family-based study designs, Mendelian randomization techniques, prospective cohorts with comprehensive exposure biomarkers, and, finally, intervention trials focusing on modifiable risk variables are necessary to distinguish causal from confounding correlations.\u003c/p\u003e \u003cp\u003eOur findings highlight a number of significant consequences from the standpoints of clinical and public health:\u003c/p\u003e \u003cp\u003eOptimize prenatal care and prevent extreme prematurity: As potential primary prevention strategies for ASD and other neurodevelopmental disorders, evidence-based interventions to reduce preterm birth should be given priority. These interventions include cervical cerclage for cervical insufficiency, progesterone supplementation for high-risk women, treatment of maternal infections, and lifestyle modifications.\u003c/p\u003e \u003cp\u003ePromote placental health: More investigation into therapies that promote placental function and lessen inflammation may present chances to lower the risk of neurodevelopment. This could involve anti-inflammatory methods, antioxidant supplements, or therapies for particular maternal diseases that have an impact on placental health\u003c/p\u003e \u003cp\u003eReduce perinatal hypoxia: Appropriate management of respiratory issues in preterm infants, such as early surfactant administration when necessary, gentle ventilation techniques to minimize lung damage, and prudent use of supplemental oxygen to prevent both hypoxia and hyperoxia, may help lessen hypoxic-ischemic brain injury.\u003c/p\u003e \u003cp\u003eEstablish early developmental surveillance: When issues are detected, children who have been exposed to severe respiratory problems, obstetric hemorrhage, extreme prematurity, or other known risk factors should be referred to early intervention services at a low threshold and have their developmental monitoring improved. Regardless of the final diagnostic classification, functional outcomes can be improved with early identification and intervention.\u003c/p\u003e \u003cp\u003eAvoid unwarranted attribution or mother blame: Because of the intricate, multivariate etiology of ASD, which involves gene-environment interactions, individual pregnancy exposures or difficulties only slightly increase absolute risk. In order to prevent guilt or self-blame, healthcare professionals should advise families that ASD is caused by a variety of interrelated variables rather than a single, identifiable cause.\u003c/p\u003e \u003cp\u003eUse antenatal interventions appropriately: Although our results indicate a link between dexamethasone use and ASD, this is probably due to indication-specific confounding rather than the negative effects of corticosteroids, which are still an essential evidence-based intervention for reducing neonatal morbidity and mortality in cases of threatened preterm delivery. Prenatal corticosteroid usage should continue in accordance with guidelines, avoiding needless courses outside of advised purposes.\u003c/p\u003e \u003cp\u003eFuture research priorities should include:\u003c/p\u003e \u003cp\u003eStrong epidemiological data is shown in this study to support links between prenatal and perinatal variables, specifically extreme preterm, perinatal hypoxia, and obstetric difficulties, and child ASD. These findings raise awareness of the role that the environment plays in the etiology of ASD, point to possible molecular pathways involving neuroinflammation and oxidative stress, and point to areas that could benefit from improved surveillance and preventive measures. To separate causal from confounded associations and convert epidemiological findings into practical strategies for lowering the risk of ASD and improving outcomes for impacted individuals and families, more research employing cutting-edge methodologies is necessary due to the intricate interactions between genetic susceptibility, familial factors, and environmental exposures.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eASD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAutism Spectrum Disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRespiratory Distress Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTransient Tachypnea of Newborn\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmall for Gestational Age\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFIRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFetal Inflammatory Response Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal Immune Activation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eROS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReactive Oxygen Species\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eATP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdenosine Triphosphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCa\u0026sup2;⁺\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCalcium ions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eReduced Glutathione\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNaK-ATPase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSodium-Potassium ATPase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNMDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eN-methyl-D-aspartate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDSM-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiagnostic and Statistical Manual, 5th Ed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eICD-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInternational Classification of Diseases, 10th Rev\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=\"top\"\u003e\n \u003cp\u003eAttention Deficit Hyperactivity Disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHIE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypoxic-Ischemic Encephalopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAnalysis of Variance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePDD-NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePervasive Developmental Disorder - NOS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eH₂O₂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHydrogen peroxide\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO₂⁻\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSuperoxide anion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026middot;OH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHydroxyl radical\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe registry-based component of this study was approved by the National Institute of Public Health responsible for registry-data approvals\u0026nbsp;(approval number: [968- 1 0O/1 8-1 /007]) on 26\u003csup\u003eth\u003c/sup\u003e February 2018. The analysis was conducted on fully anonymized data extracted from the National Perinatal Information System and linked health records. In line with national regulations and the terms of this approval, individual informed consent was not required, and a waiver of consent was granted for this retrospective use of anonymized registry data.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. The study used anonymized registry data without individual identifiers.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request, subject to ethical approval and data protection regulations.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Slovenian Research Agency through scientific research program grants P3-0124 and project J3-1756.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: J.O.; methodology: J.O. and U.G.; software: U.G.; validation: J.O. and U.G.; formal analysis: U.G.; investigation: J.O.; resources: J.O.; data curation: J.O.; writing\u0026mdash;original draft preparation: J.O.; writing\u0026mdash;review and editing: J.O. and U.G.; visualization: J.O.; supervision: J.O.; project administration: J.O.; funding acquisition: J.O. Both authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the staff of the National Perinatal Information System for data management support and the National Medical Ethics Committee for expedited review of the research protocol.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmerican Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM\u0026ndash;5). Washington, DC: American Psychiatric Association; 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJinan Zeidan E, Fombonne J, Scorah A, Ibrahim MS, Durkin S, Saxena, et al. Global prevalence of autism: a systematic review update. Autism Res. 2022;15(5):778\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaafsma SM, Pfaff DW. Etiologies underlying sex differences in Autism Spectrum Disorders. Front Neuroendocrinol. 2014;35(3):255\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRachel Loomes L, Hull, William PL, Mandy. What is the male-to-female ratio in autism spectrum disorder? A systematic review and meta-analysis. J Am Acad Child Adolesc Psychiatry. 2017;56(6):466\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlexios Tsompanidis V, Warrier. Simon Baron\u0026ndash;Cohen. The genetics of autism and steroid-related traits in prenatal and postnatal life. Front Endocrinol. 2023;14:1126036.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCroen LA, Ames JL, Qian Y, Alexeeff S, Ashwood P, Gunderson EP, et al. Inflammatory Conditions During Pregnancy and Risk of Autism and Other Neurodevelopmental Disorders. Biol Psychiatry Glob Open Sci. 2024;4(1):39\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeather Gardener D, Spiegelman SL, Buka. Prenatal risk factors for autism: comprehensive meta\u0026ndash;analysis. Br J Psychiatry. 2009;195(1):7\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArielle Kolevzon R, Gross A, Reichenberg. Prenatal and perinatal risk factors for autism: a review and integration of findings. Arch Pediatr Adolesc Med. 2007;161(4):326\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVojislav Mandic\u0026ndash;Maravic, Milica Mitkovic\u0026ndash;Voncina, Maja Pljesa\u0026ndash;Ercegovac, Aleksandra Savic\u0026ndash;Radojevic, Maja Djordjevic, Tatjana Pekmezovic, et al. Autism Spectrum Disorders and Perinatal Complications\u0026mdash;Is Oxidative Stress the Connection? 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Nutrients. 2025;17(18):2984.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFattorusso A, Di Genova L, Dell\u0026rsquo;Isola G, Mencaroni E, Esposito S. Autism Spectrum Disorders and the Gut Microbiota. Nutrients. 2019;11(3):521.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIglesias-V\u0026aacute;zquez L, Van Ginkel Riba G, Arija V, Canals J. Composition of Gut Microbiota in Children with Autism Spectrum Disorder: A Systematic Review and Meta-Analysis. Nutrients. 2020;12(3):792.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKiilerich P, Cortes R, Lausten-Thomsen U, Borbye-Lorenzen N, Holmgaard S, Skogstrand K. Delivery Modality Affect Neonatal Levels of Inflammation, Stress, and Growth Factors. Front Pediatr. 2021 Sept;22:9:709765.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarabulut B, Sahbudak B. 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Familial confounding of the association between maternal smoking during pregnancy and ADHD in offspring. J Child Psychol Psychiatry. 2014;55(1):61\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaunders GRB, McGue M, Malone SM. Sibling Comparison Designs: Addressing Confounding Bias with Inclusion of Measured Confounders. Twin Res Hum Genet. 2019;22(5):290\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\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":"Autism spectrum disorder, Cohort study, Preterm birth, Perinatal hypoxia, Placental dysfunction, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-8333327/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8333327/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAutism spectrum disorder (ASD) is a complex neurodevelopmental condition with a multifactorial etiology involving both genetic and environmental factors. While genetic risks are well-characterized, the contribution of specific prenatal and perinatal environmental exposures remains less understood. This study aimed to comprehensively investigate pregnancy-related and birth complications associated with ASD in a large, population-based national cohort.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study of all singleton pregnancies delivered in Slovenia between 2005 and 2017 (N\u0026thinsp;=\u0026thinsp;302,476). We identified 117 children with a confirmed clinical diagnosis of ASD and compared them to the remaining 302,322 pregnancies. Data were obtained from the National Perinatal Information System. We analyzed maternal demographics, medication exposures, obstetric complications, and neonatal outcomes using logistic regression to calculate odds ratios (OR) with 95% confidence intervals (CI).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eASD cases showed a profound male predominance (83.7% vs. 51.4%; OR 4.88, 95% CI: 2.98\u0026ndash;7.97). Early preterm birth (\u0026lt;\u0026thinsp;31 weeks) was significantly more frequent in the ASD group (4.2% vs. 1.4%; OR 3.14, 95% CI: 1.28\u0026ndash;7.70). Postpartum hemorrhage risk was nearly tripled in mothers of children with ASD (6.0% vs. 2.3%; OR 2.70, 95% CI: 1.26\u0026ndash;5.81). Neonatal respiratory morbidity was strongly associated with ASD, including Respiratory Distress Syndrome (RDS) (OR 3.42, 95% CI: 1.67\u0026ndash;7.02), transient tachypnea of the newborn (OR 3.90, 95% CI: 1.44\u0026ndash;10.57), and surfactant administration (OR 6.55, 95% CI: 2.08\u0026ndash;20.65). Antenatal dexamethasone exposure was also elevated (OR 3.67), likely reflecting confounding by indication for threatened preterm labor.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this national cohort, male sex, extreme prematurity, placental hemorrhage, and neonatal respiratory complications were robust risk factors for ASD. These findings implicate placental dysfunction and perinatal hypoxia-ischemia as key mechanistic pathways in neurodevelopmental vulnerability. While observational data cannot prove causality, the strong associations with markers of hypoxia suggest that optimizing perinatal respiratory management and placental health may be relevant for ASD prevention.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e \u003cp\u003e0120\u0026ndash;201/2016-2 KME 78/03/16; 3 February 2021\u003c/p\u003e","manuscriptTitle":"Prenatal and Perinatal Risk Factors Associated with Autism Spectrum Disorder: A National Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 13:42:59","doi":"10.21203/rs.3.rs-8333327/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":"faceab0e-6278-42f2-a33e-bf416aba3807","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-07T18:59:23+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T19:09:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 13:42:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8333327","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8333327","identity":"rs-8333327","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}