Impact of Prenatal Antidepressant Exposure on Trajectories of Childhood Emotions and Behaviors: Evidence from a Birth Cohort  

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We analyzed data from the Longitudinal Study of Australian Children (LSAC), a nationally representative birth cohort. Prenatal antidepressant exposure was determined based on self-reported medication use during pregnancy. Neurodevelopmental outcomes, including emotional problems and hyperactivity, were assessed using the Strengths and Difficulties Questionnaire (SDQ) at ages 4, 6, and 8. To adjust for confounding, inverse probability weighting (IPW) was applied. Growth curve models (GCMs) and repeated measures mixed models (RMMMs) were used to assess developmental trajectories. The results indicate that prenatal antidepressant exposure was not significantly associated with overall differences in emotional problems or hyperactivity. However, exposed children exhibited a steeper increase in emotional problems over time compared to non-exposed peers (GCM interaction: β = 0.05, p = 0.003; RMMM age 6 vs. 4: β = 0.12, p < 0.001; age 8 vs. 4: β = 0.09, p = 0.006). Hyperactivity differences emerged only at age 8, with exposed children showing a significant increase in symptoms (GCM interaction: β = 0.15, p < 0.001; RMMM age 8 vs. 4: β = 0.30, p < 0.001). Maternal stress was consistently associated with higher emotional and hyperactivity scores (p < 0.001), while low household income and lower maternal education were linked to greater neurodevelopmental difficulties. Our findings suggest that although prenatal antidepressant exposure does not directly determine neurodevelopmental differences between the age of 4 and 8, it might influence the trajectory of emotional and behavioral regulation over time. The delayed effects on hyperactivity and the progressive increase in emotional difficulties highlight the importance of long-term follow-up in exposed children. Figures Figure 1 INTRODUCTION Mental health in pregnancy has become an increasingly significant global health issue in recent years. For example, nearly 10% of Australian women reporting anxiety and depression during pregnancy in 2020 [ 1 ], and an estimated 1 in 5 pregnant and postpartum individuals experience mental health conditions annually in the United States [ 2 ]. The need for adequate treatment of maternal depression and anxiety in the perinatal period is underpinned by the clear association with poorer outcomes in fetal and child development, including deficits in cognitive function, higher rates of insecure attachments and subsequent maladaptive behaviors [ 3 ]. However, some concerns also surround the prescription of antidepressants to treat such illness, given that antidepressants themselves may also be associated with negative outcomes for the child in later life [ 4 , 5 ], including poorer neurodevelopmental outcomes with emotional and behavioral difficulties [ 6 , 7 ]. Antidepressants are increasingly being used to treat mothers with moderate to severe depression [ 1 , 5 ] and have undergone the largest rise in prescription rate of the drugs prescribed in pregnancy [ 8 ]. Current guidelines recommend selective serotonin reuptake inhibitors (SSRIs) as first-line therapy in moderate to severe perinatal depression [ 1 , 4 , 5 ], although other antidepressants, such as serotonin-noradrenaline reuptake inhibitors (SNRIs) may also be considered [ 4 ]. SSRIs and SNRIs work by inhibiting serotonin reuptake in the presynaptic nerve terminals, which increases the concentration of serotonin in the synaptic cleft [ 9 ]. This increases serotonergic availability for adult brain functions such as mood control and social behaviors [ 9 ]. In pregnancy, the placenta serves as the primary source of serotonin for the fetus [ 10 ], where it is responsible for facilitating cell proliferation, nerve cell migration and synapse formation [ 10 ]. However, maternal antidepressants can also cross the placenta into fetal circulation [ 10 , 11 ] and, therefore, imbalances in fetal serotonin may be potentially linked with alterations in fetal brain development [ 12 – 15 ]. Prenatal SSRI exposure has been associated with decreased salivary cortisol levels in offspring at 3 months [ 12 ] and 6 years of age [ 13 ], possibly reflecting a dampened reactivity in the hypothalamic-pituitary-adrenal (HPA) axis which regulates the body's stress response [ 12 ]. Zusman et al. also found that this effect was enhanced in SSRI-exposed children with SLC6A4 genotype [ 13 ], suggesting some genetic factors may be involved. Additionally, in a study conducted by Koc et. al, children with antenatal SSRI exposure as well as active maternal depressive symptoms displayed a reduced white matter microstructure at age 7 when compared with children without exposure [ 14 ], although this effect was also moderated by faster growth in white matter pathways between 7 and 15 years of age, suggesting compensatory development [ 14 ]. Finally, in a study conducted by Meyer et. al., offspring of mice injected with sertraline in pregnancy showed markedly elevated cortical mRNA levels of various serotonin receptors and transporters but displayed no behavioral differences of statistical significance from the saline-injected controls [ 15 ]. As such, research supports that morphological variations may be linked with maternal antidepressant use in utero [ 12 – 14 ], although further clarification is needed to translate physiological findings into measurable behavioral outcomes in humans [ 15 ]. Some concern surrounds the potential for adverse outcomes with prenatal antidepressant use including cognitive delays, behavioral difficulties and neurodevelopmental issues [ 7 , 16 – 18 ]; however, there are inconsistencies in current research. Whilst several studies have found significant associations with poorer neurodevelopmental and behavioral outcomes [ 16 – 18 ], these findings were largely attenuated by adjustment for confounding factors, with other studies showing no significant associations following adjustment analyses [ 6 , 19 , 20 ]. The inconsistencies in studies are likely due to the challenges in isolating the effects of antidepressant exposure from other confounding factors, such as maternal mental health and the broader childhood environment. Many studies suggest that maternal mental illness itself is a significant factor impacting child behaviors [ 16 – 20 ], including a review by Anns et. al. which found no significant risk linked with antenatal antidepressant exposure but identified an independent association between maternal depression and behavioral difficulties in children [ 19 ]. Additional factors, such as the timing of exposure and the infant sex, may also contribute to differences in behavioral outcomes. For example, Erickson et. al. found sex-specific differences in behavioral outcomes in infants [ 21 ], while Lupattelli et. al. identified an increased risk of anxiety and depression symptoms at 5 years of age only in late-pregnancy exposure to SSRIs compared; no such risk was present with earlier exposure [ 22 ]. Ultimately, these findings highlight how unmeasured confounding factors may contribute to discrepancies in research [ 16 – 21 ]. To better address unmeasured confounding effects in the current study, we proposed to use inverse probability weighted (IPW) method, which offers a robust solution for addressing confounding factors, such as maternal depression and socioeconomic status[ 23 ]. This approach helps us balance covariates between exposed and unexposed groups, reducing potential bias and improving effect estimate accuracy. Further, we proposed cross-validation between growth curve models and repeated measure mixed models to capture the complex trajectories of neurodevelopment over time [ 24 ]. These complementary approaches can provide a more nuanced understanding of the long-term effects of prenatal antidepressant exposure, accounting for both time-invariant and time-varying confounders. By employing these methods, we aim to disentangle the direct effects of antidepressant exposure from other influential factors, potentially resolving inconsistencies in previous research findings. The overarching objective of this study is to investigate the joint influence of perinatal factors associated with prenatal antidepressant exposure on neurodevelopmental trajectories during childhood. Specifically, we aim to: Examine how prenatal antidepressant exposure and other perinatal factors collectively shape the trajectory of emotional problems in children. Determine how these perinatal factors jointly influence the trajectory of hyperactivity problems throughout childhood. METHODS Study Setting and Sampling This study utilized data from the Longitudinal Study of Australian Children (LSAC), a nationally representative birth cohort designed to examine child development and well-being across multiple domains. The sampling strategies and how multiple waves were collected are described elsewhere [ 25 ]. For this secondary data analysis, we extracted data on perinatal history from wave 0, which included information on prenatal antidepressant exposure, maternal health, and socioeconomic factors. The sample consisted of 3,814 individuals with complete data on prenatal antidepressant exposure and neurodevelopmental outcomes at multiple time points. Developmental outcomes of children were assessed every two years for this birth cohort. Measures Key prenatal exposure: Prenatal antidepressant exposure was determined based on self-reported medication use during pregnancy. This was the primary exposure of interest, with additional perinatal and socioeconomic factors included as covariates to adjust for potential confounding effects. Perinatal Factors: To account for confounders influencing both prenatal antidepressant exposure and neurodevelopmental outcomes, we included maternal self-reported intra-partum stress, maternal smoking during pregnancy, gestational age at birth, and birth weight. These covariates were incorporated into the propensity score estimation process to model the likelihood of prenatal antidepressant exposure. Socioeconomic Factors: Maternal educational attainment (categorized as less than high school versus higher education levels) and family income (classified as greater than A $ 60,000 per year, a median income in Australia in 2023, versus lower income levels) were included to adjust for socioeconomic disparities potentially associated with both antidepressant use and child neurodevelopment. These variables were used to estimate propensity scores, which were subsequently employed in the inverse probability weighting calculations to enhance the robustness of the analysis. Neurodevelopmental outcomes: The two scores for emotional problems and hyperactivity based on the measures using Strength and Difficulty Questionnaire (SDQ) [ 26 ] at ages 4, 6, and 8, were the primary outcome measures. It measures five key domains: emotional symptoms, conduct problems, hyperactivity or inattention, peer relationship problems, and prosocial behavior, which can evaluate children's psychological well-being and identify potential mental health concerns. Statistical methods 1. Descriptive analysis Differences between children with a presence of prenatal antidepressant exposure and children without a presence of prenatal antidepressant exposure were examined for all key covariates. Continuous variables such as neurodevelopmental outcome variables (i.e., hyperactivity and emotional problem scores) were analyzed using t-tests. Categorical variables were analyzed using chi-square tests. 2. Calculate inverse probability weight based on the likelihood for prenatal antidepressant exposure To account for potential confounding in the association between prenatal antidepressant exposure and child outcomes, we applied inverse probability weighting (IPW). First, we estimated the propensity score, defined as the predicted probability of prenatal antidepressant exposure, using a logistic regression model. This model included key maternal and perinatal covariates such as maternal age, education, income, smoking status, perceived stress during pregnancy, and birth weight. Each participant was then assigned an inverse probability weight (IPW), calculated as the inverse of the estimated probability of their observed exposure status. This approach aimed to balance observed covariates between exposed and non-exposed groups, thereby reducing confounding bias. The resulting weighted sample approximates a pseudo-randomized population, allowing for a more robust estimation of the causal effects of prenatal antidepressant exposure on neurodevelopmental outcomes. 3. Growth curve model analysis To examine the longitudinal trajectories of hyperactivity and emotional problems in children exposed to prenatal antidepressants, we employed a growth curve model (GCM) using mixed-effects regression. This approach accounts for individual variability and allows us to estimate both baseline differences and changes over time. We fit two separate linear mixed-effects models (LMMs) using maximum likelihood estimation (MLE): one for hyperactivity and one for emotional problems. Fixed effects included Prenatal antidepressant exposure, time (centered at baseline), and their interaction (i.e., antidepressant exposure × time) to estimate exposure-related differences in developmental trends. Additional covariates included maternal smoking, maternal stress, maternal age, maternal education attainment (less than high school versus at least high school), annual household income (less than A $ 60,000 versus at least A $ 60,000), and birth weight. The final models were estimated as follows normalized neurodevelopmental outcome = β 0 + β 1 (antidepressanti) + β 2 (ctime) + β 3 (antidepressant × ctime) + ∑β k X ik + u i + ϵ it , where ctime represents the time variable subtracted with 1, β 3 estimates whether prenatal antidepressant exposure affects the rate of change in hyperactivity over time, represents additional covariates, u i is the random intercept, capturing individual variability, and ϵ it is the residual error. Random effects were individual-specific random intercepts to account for between-subject variability. Weighting was based on IPW to adjust for confounding due to selection bias. 4. Repeated measure mixed model analysis To further investigate the longitudinal effects of prenatal antidepressant exposure on child neurodevelopment, we conducted a repeated measures mixed model (RMMM) analysis. This approach accounts for within-subject correlations across different time points while adjusting for potential confounders IPW. Similar to GCM, the model was estimated using maximum likelihood (ML), and an unstructured covariance matrix was used to allow for flexible modeling of within-subject correlations. The time variable was based on the original codes values for the three ages (i.e., 4, 6, and 8 years). RESULTS 1. Characteristics of the cohort Table 1 summarizes features of children with prenatal exposure to antidepressants versus children without prenatal exposure to antidepressants. Children exposed to prenatal antidepressants exhibited significantly higher hyperactivity and emotional problem scores compared to non-exposed children (p < 0.05), suggesting potential impacts on early childhood behavioral outcomes. Table 1 Characteristic of the birth cohort stratified by presence of prenatal antidepressant exposure Variable Exposed (Mean ± SD or %) N Non-Exposed (Mean ± SD or %) N p-value Neurodevelopmental Outcomes Hyperactivity 5.4 ± 2.1 245 4.8 ± 1.9 780 0.012* Emotional Problems 6.1 ± 2.4 250 5.3 ± 2.1 795 0.006* Birth Weight (mg) 2940 ± 650 255 3120 ± 580 820 0.021* Maternal Age < 25 years 10.80% 260 8.20% 830 0.093 25–29 years 24.50% 260 22.70% 830 0.218 30–34 years 36.10% 260 37.90% 830 0.542 ≥ 35 years 28.70% 260 31.20% 830 0.089 Low Maternal Education (< HS vs. HS) 22.60% 250 18.40% 810 0.048* Low Income (< $ 60K vs. Others) 38.20% 248 30.50% 805 0.022* Maternal Smoking 16.30% 255 10.20% 815 0.010* Maternal Stress 45.80% 258 23.40% 825 < 0.001** In terms of perinatal factors, birth weight was significantly lower among exposed children (p = 0.021), indicating potential differences in fetal growth. However, maternal age categories (< 25, 25–29, 30–34, ≥ 35 years) did not significantly differ between the two groups, suggesting that maternal age alone may not be a key determinant of exposure-related outcomes. Maternal and socioeconomic factors also differed between groups. Mothers of exposed children were more likely to have lower education levels (less than high school) and report lower household income (< $ 60K), with both factors reaching statistical significance (p < 0.05). Additionally, maternal smoking and perceived stress during pregnancy were significantly more prevalent in the exposed group (p < 0.05 and p < 0.001, respectively), highlighting important environmental and psychosocial risk factors associated with prenatal antidepressant exposure. [Insert Table 1 here] 2. Growth curve models (GCM) The results from the analyses based on growth curve models (GCM) for the two neurodevelopmental outcomes are summarized in Table 2 . Table 2 Results from the growth curve model analyses Predictor Emotional Problems (β, 95% CI) p-value Hyperactivity (β, 95% CI) p-value Prenatal Antidepressant Exposure 0.10 (-0.06 to 0.25) 0.22 -0.06 (-0.24 to 0.11) 0.49 Time (Per 2 Years) 0.10 (0.08 to 0.12) < 0.001 0.03 (0.01 to 0.05) < 0.001 Antidepressant × Time 0.05 (0.02 to 0.08) 0.003 0.15 (0.13 to 0.18) < 0.001 Maternal Stress 0.26 (0.19 to 0.32) < 0.001 0.19 (0.11 to 0.26) < 0.001 Maternal Smoking -0.08 (-0.15 to -0.01) 0.03 -0.27 (-0.35 to -0.20) < 0.001 Low Maternal Education 0.03 (-0.02 to 0.09) 0.25 0.14 (0.07 to 0.20) < 0.001 Low Income 0.08 (0.02 to 0.13) 0.005 0.06 (0.003 to 0.11) 0.04 Birth Weight -0.06 (-0.10 to -0.01) 0.01 -0.002 (-0.05 to 0.05) 0.94 Intercept 0.14 (-0.07 to 0.34) 0.19 0.37 (0.15 to 0.59) 0.001 2.1. Emotional Problems Prenatal antidepressant exposure was not significantly associated with baseline emotional problems (β = 0.095, p = 0.223), indicating that exposed and non-exposed children had similar levels of emotional difficulties at age 4. However, emotional problems increased significantly over time for all children, as shown by the positive main effect of time (β = 0.100, p < 0.001), suggesting worsening symptoms as children aged. Importantly, the interaction between antidepressant exposure and time remained significant (β = 0.046, p = 0.003), indicating that exposed children experienced a greater increase in emotional problems over time compared to their non-exposed peers. This finding suggests that while prenatal exposure was not linked to immediate emotional difficulties, its effects became more pronounced with age, leading to a widening gap in emotional problems between exposed and non-exposed children. Among the covariates, maternal stress was strongly associated with increased emotional problems (β = 0.255, p < 0.001), while maternal smoking was inversely associated with emotional problems (β = -0.080, p = 0.033). Low household income was also a significant predictor of increased emotional difficulties (β = 0.076, p = 0.005), while maternal education was not significantly associated with emotional problems (p = 0.252). Additionally, lower birth weight was associated with higher emotional problem scores (β = -0.000058, p = 0.014). 2.2. Hyperactivity Prenatal antidepressant exposure was not significantly associated with baseline hyperactivity (β = -0.062, p = 0.490), suggesting that exposed and non-exposed children had similar levels of hyperactivity at age 4. However, hyperactivity increased significantly over time for all children (β = 0.033, p < 0.001), indicating a general upward trajectory of hyperactivity symptoms with age. Notably, the interaction between antidepressant exposure and time was highly significant (β = 0.151, p < 0.001), suggesting that children exposed to prenatal antidepressants exhibited a steeper increase in hyperactivity over time compared to non-exposed children. This delayed effect implies that while no early differences in hyperactivity were observed, exposed children showed increasing hyperactivity symptoms as they aged. Among the covariates, maternal stress was a strong independent predictor of increased hyperactivity symptoms (β = 0.186, p < 0.001). Lower maternal education was significantly associated with higher hyperactivity scores (β = 0.136, p < 0.001), as was low household income (β = 0.059, p = 0.039). Maternal smoking was inversely associated with hyperactivity symptoms (β = -0.275, p < 0.001), and birth weight was not significantly associated with hyperactivity (p = 0.941). [Insert Table 2 here] 3. Repeated measure mixed model (RMMM) The results from the RMMM analyses are summarized in Table 3 . Table 3 Results from the repeated measure mixed model analyses Predictor Emotional Problems (β, 95% CI) p-value Hyperactivity (β, 95% CI) p-value Prenatal Antidepressant Exposure 0.07 (-0.09 to 0.22) 0.39 -0.02 (-0.19 to 0.16) 0.85 Time: Age 6 vs. 4 0.16 (0.12 to 0.21) < 0.001 0.09 (0.05 to 0.12) < 0.001 Time: Age 8 vs. 4 0.20 (0.16 to 0.24) < 0.001 0.07 (0.03 to 0.10) < 0.001 Antidepressant × Age 6 0.12 (0.06 to 0.18) < 0.001 0.03 (-0.02 to 0.08) 0.31 Antidepressant × Age 8 0.09 (0.02 to 0.15) 0.006 0.30 (0.25 to 0.36) < 0.001 Maternal Stress 0.25 (0.19 to 0.32) < 0.001 0.19 (0.11 to 0.26) < 0.001 Maternal Smoking -0.08 (-0.15 to -0.01) 0.03 -0.27 (-0.35 to -0.20) < 0.001 Low Maternal Education 0.03 (-0.02 to 0.09) 0.26 0.14 (0.07 to 0.20) < 0.001 Low Income 0.08 (0.02 to 0.13) 0.005 0.06 (0.003 to 0.11) 0.04 Birth Weight (per 1000g) -0.06 (-0.10 to -0.01) 0.02 -0.002 (-0.05 to 0.05) 0.95 Intercept 0.11 (-0.09 to 0.32) 0.29 0.35 (0.13 to 0.57) 0.002 3.1. Emotional Problems Prenatal antidepressant exposure was not significantly associated with baseline emotional problems at age 4 (β = 0.067, p = 0.393), suggesting no initial differences between exposed and non-exposed children. However, emotional problems increased significantly over time for all children, as indicated by the main effects of time (age 6 vs. 4: β = 0.163, p < 0.001; age 8 vs. 4: β = 0.200, p < 0.001). The interaction terms between prenatal antidepressant exposure and time remained significant, indicating that exposed children experienced a steeper increase in emotional problems compared to non-exposed children (age 6 vs. 4: β = 0.122, p < 0.001; age 8 vs. 4: β = 0.085, p = 0.006). This suggests that while prenatal exposure was not associated with higher emotional problems at age 4, its effects emerged over time, leading to a widening gap between exposed and non-exposed children by age 8. Among the covariates, maternal stress was strongly associated with higher emotional problem scores (β = 0.255, p < 0.001), while maternal smoking and birth weight were inversely associated with emotional problems (maternal smoking: β = -0.079, p = 0.034; birth weight: β = -0.000057, p = 0.015). Low household income was also a significant predictor of increased emotional problems (β = 0.076, p = 0.005), while maternal education was not significantly associated (p = 0.261). 3.2. Hyperactivity Similar to emotional problems, prenatal antidepressant exposure was not significantly associated with hyperactivity at age 4 (β = -0.017, p = 0.850), and no significant interaction was observed at age 6 (β = 0.026, p = 0.308), suggesting no early differences in hyperactivity trajectories. However, by age 8, a highly significant interaction between antidepressant exposure and time emerged (β = 0.304, p < 0.001), indicating a delayed effect of prenatal antidepressant exposure on hyperactivity. Several covariates were also significantly associated with hyperactivity outcomes. Maternal stress was a strong independent predictor of higher hyperactivity scores (β = 0.186, p < 0.001), while maternal smoking was associated with lower hyperactivity scores (β = -0.274, p < 0.001). Additionally, lower maternal education was significantly associated with increased hyperactivity symptoms (β = 0.136, p < 0.001), as was low household income (β = 0.059, p = 0.037). Birth weight was not significantly associated with hyperactivity (p = 0.947). Trajectories of the scores for emotional problems and hyperactivity are illustrated in Fig. 1 . The trends indicate that children exposed to prenatal depressants started to show increasingly higher levels of emotional problems than children without prenatal antidepressant exposure after the age of 6. Similarly, children exposed to prenatal depressants started to show increasingly higher levels of hyperactivity than children without prenatal antidepressant exposure, but the difference became significant after the age of 8. [Insert Table 3 here] [Insert Fig. 1 here] DISCUSSIONS In this nationwide community-based cohort study, the results suggest that prenatal antidepressant exposure is not solely responsible for differences in neurodevelopmental outcomes but rather influences their trajectories over time. While exposed and non-exposed children had similar emotional problem and hyperactivity scores at age 4, exposed children exhibited a steeper increase in symptoms as they aged, leading to significant differences by age 8. Emotional problems in exposed children worsened progressively between ages 4 and 8, while hyperactivity differences did not emerge until age 8, suggesting a delayed impact of prenatal antidepressant exposure on behavioral regulation. Additionally, maternal stress and socioeconomic factors, including low household income and lower maternal education, were strongly associated with neurodevelopmental difficulties. These findings underscore the importance of considering the dynamic nature of development when evaluating the effects of prenatal antidepressant exposure, as its impact may not be evident in early childhood but can shape the trajectory of emotional and behavioral outcomes over time. Several systematic reviews and meta-analysis have examined the relationships between the exposure to antidepressants in utero and neurodevelopmental disorders in offspring, often with mixed results [ 27 , 28 ]. Our findings are consistent with the study by Lupatelli et al, showing an increased levels of anxiety behaviors in 5-year-olds exposed to maternal SSRIs in utero [ 22 ]. Conversely, several other studies found no increased risk for anxiety and internalizing behaviors in children. For example, Nulman et al. reported no significant differences in emotional or behavior problems between children with in-utero exposure to tricyclic antidepressant or fluoxetine, compared with children without prenatal antidepressant exposure [ 29 ]. Cohen et al. found that maternal SSRI use during pregnancy was not linked to atypical neurodevelopment, while higher maternal depression burden was associated with internalizing symptoms, while SSRI-exposed children showed better executive function [ 30 ]. One review study summarizing findings from 34 studies also does not support the association between prenatal antidepressant exposure and neurodevelopmental outcomes in children when the analysis controlled for maternal conditions [ 31 ]. Such inconsistent findings across different populations may stem from differences in how prenatal antidepressant exposure data were categorized and how neurodevelopmental outcomes in children were analyzed. Previous studies that did not account for exposure propensity may have been limited in their ability to fully adjust for confounding factors associated with both maternal antidepressant use and child neurodevelopmental outcomes. Without properly modeling the likelihood of exposure, differences observed between exposed and non-exposed groups may reflect underlying maternal characteristics rather than the direct effect of antidepressants themselves. Studies have shown that maternal psychiatric conditions, genetic predisposition, and environmental factors contribute to both prenatal antidepressant exposure during pregnancy and child neurodevelopmental trajectories, highlighting the need for careful confounding control [ 22 , 32 ]. Our approach, which incorporates IPW, might help address confounding by balancing observed differences between exposed and non-exposed groups, thereby providing less biased estimates of the effect of prenatal antidepressant exposure on neurodevelopmental outcomes. Although the detailed mechanism of antidepressants affecting brain neurodevelopment remains elusive, it has been well established that SSRIs are able to cross the placenta and enter the intrauterine environment [ 10 , 11 ]. Accumulating evidence indicates that SSRI exposure during pregnancy prenatal selective serotonin reuptake inhibitor exposure has a significant association with fetal brain development [ 33 , 34 ]. Preclinical evidence also suggests that prenatal antidepressant exposure could impact brain networks involved in sensory perception and processing [ 35 ]. Although evidence suggests a potential role of prenatal SSRI exposure in brain structural variation, it remains uncertain whether this exposure directly results in neurodevelopmental differences at a specific age. Instead, it may subtly influence developmental processes, potentially shaping the trajectory of neurodevelopmental outcomes over time. While most of the studies have found no association between prenatal exposure to antidepressants and risks of neurodevelopmental outcomes, findings of our study highlight subclinical behavioral changes during early childhood. One explanation of these findings is that prenatal exposure to antidepressants can alter developmental trajectories in brain areas associated with emotional regulation leading to increased hyperactivity and emotional dysregulation in offspring. Interestingly, while some changes in brain morphology persisted into adolescence, others did not, suggesting a developmental delay, rather than permanent structural change. Recent findings from the large population cohort study provide further evidence that initial white matter microstructure changes observed in younger children exposed to maternal SSRIs in utero diminish over time, suggesting a phenomenon of catch-up growth during adolescence [ 36 ]. Further studies are needed to investigate the trajectory of the observed behavioral changes in our study into older children and adolescents. Clinical Implications Although there are no clearly defined treatment guidelines regarding the use of antidepressants in pregnancy, concerns regarding the effects of SSRI exposure in utero often the play the critical role in making the decision about the use of antidepressants during pregnancy. Given that up to 15% of women experience the depression in pregnancy this decision can have a long-lasting impact on both maternal and infant mental health. While our study suggests the possibility of prenatal effect on antidepressants on increased risks of child’s externalizing behaviors, specifically emotional dysregulation, and hyperactivity during the ages of 4–8 years old, the impact of maternal mental illness remains unclear. The current study contributes to our understanding of the effects of the prenatal antidepressant exposure on neurobehavioral outcomes of the offspring, however the information is still incomplete. At this time, it would be premature to restrict use of antidepressant treatment during pregnancy based on the results of our study. Further research is needed on the longitudinal trajectory of neurobehavioral outcomes throughout the childhood and adolescence in children exposed to maternal SSRIs in utero. SUMMARY Prenatal antidepressant exposure has been extensively studied in relation to child neurodevelopment, but findings remain inconsistent, with some studies indicating increased risks for emotional and behavioral problems while others report no significant effects. This study suggests that while prenatal antidepressant exposure does not result in immediate neurodevelopmental differences at age 4, it influences developmental trajectories, leading to a progressive increase in emotional problems and a delayed rise in hyperactivity by age 8. These findings highlight the importance of long-term developmental monitoring in clinical practice to identify emerging emotional and behavioral difficulties. Additionally, the role of maternal stress and socioeconomic factors underscores the need for supportive interventions during pregnancy, which could help mitigate risks and inform policy and service development in maternal mental health care. Declarations Author Contribution P.L. and Y.C. conceptualized the study. P.L. performed the statistical data analysis. Y.C. prepared figure 1. P.L., D.S., and R.K. wrote the main manuscript text. All authors reviewed and edited the manuscript. Data Availability This study uses data from the Longitudinal Study of Australian Children (LSAC), a nationally representative cohort study conducted by the Australian Government Department of Social Services (DSS) in partnership with the Australian Institute of Family Studies (AIFS). Access to LSAC data is restricted and available to approved researchers through an application process via the National Centre for Longitudinal Data (NCLD). More information on data access and application procedures can be found at https://growingupinaustralia.gov.au/. References Royal Australia and New Zealand College of Obstetrics and Gynaecology. Mental health care in the perinatal period: Clinical practice guideline. 2023. 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Placental transfer of antidepressant medications: implications for postnatal adaptation syndrome. Clin Pharmacokinet. 2015;54: 359–370. Pawluski J, Brain U, Underhill C, Hammond G, Oberlander T. Prenatal SSRI exposure alters neonatal corticosteroid binding globulin, infant cortisol levels, and emerging HPA function. Psychoneuroendocrinology. 2011;37: 1019–1028. doi:10.1016/j.psyneuen.2011.11.011 Zusman EZ, Chau CMY, Bone JN, Hookenson K, Brain U, Glier MB, et al. Prenatal serotonin reuptake inhibitor antidepressant exposure, SLC6A4 genetic variations, and cortisol activity in 6-year-old children of depressed mothers: A cohort study. Dev Psychobiol. 2023;65: e22425. doi:https://doi.org/10.1002/dev.22425 Koc D, El Marroun H, Stricker BH, Muetzel RL, Tiemeier H. Intrauterine Exposure to Antidepressants or Maternal Depressive Symptoms and Offspring Brain White Matter Trajectories From Late Childhood to Adolescence. Biol Psychiatry Cogn Neurosci Neuroimaging. 2024;9: 217–226. doi:https://doi.org/10.1016/j.bpsc.2023.10.009 Meyer LR DBLCKEHTRRHS. Perinatal SSRI exposure permanently alters cerebral serotonin receptor mRNA in mice but does not impact adult behaviors. . J Matern Fetal Neonatal Med. 2018;31: 1393–1401. Upadhyaya S, Brown A, Cheslack-Postava K, Gissler M, Gyllenberg D, Heinonen E, et al. Maternal SSRI use during pregnancy and offspring depression or anxiety disorders: A review of the literature and description of a study protocol for a register-based cohort study. Reproductive Toxicology. 2023;118: 108365. doi:https://doi.org/10.1016/j.reprotox.2023.108365 Christensen J, Trabjerg BB, Sun Y, Dreier JW. Association of Maternal Antidepressant Prescription During Pregnancy With Standardized Test Scores of Danish School-aged Children. JAMA. 2021;326: 1725–1735. doi:10.1001/jama.2021.17380 Park M, Hanley GE, Guhn M, Oberlander TF. Prenatal antidepressant exposure and child development at kindergarten age: a population-based study. Pediatr Res. 2021;89: 1515–1522. doi:10.1038/s41390-020-01269-6 Anns F, Waldie KE, Peterson ER, Walker C, Morton SMB, D’Souza S. Behavioural outcomes of children exposed to antidepressants and unmedicated depression during pregnancy. J Affect Disord. 2023;338: 144–154. doi:https://doi.org/10.1016/j.jad.2023.05.097 Lupattelli A, Mahic M, Handal M, Ystrom E, Reichborn-Kjennerud T, Nordeng H. Attention-deficit/hyperactivity disorder in children following prenatal exposure to antidepressants: results from the Norwegian mother, father and child cohort study. BJOG. 2021;128: 1917–1927. doi:https://doi.org/10.1111/1471-0528.16743 Erickson NL, Hancock GR, Oberlander TF, Brain U, Grunau RE, Gartstein MA. Prenatal SSRI antidepressant use and maternal internalizing symptoms during pregnancy and postpartum: Exploring effects on infant temperament trajectories for boys and girls. J Affect Disord. 2019;258: 179–194. doi:https://doi.org/10.1016/j.jad.2019.08.003 Lupattelli A, Wood M, Ystrom E, Skurtveit S, Handal M, Nordeng H. Effect of Time-Dependent Selective Serotonin Reuptake Inhibitor Antidepressants During Pregnancy on Behavioral, Emotional, and Social Development in Preschool-Aged Children. J Am Acad Child Adolesc Psychiatry. 2018;57. doi:10.1016/j.jaac.2017.12.010 Andrade C. Gestational Exposure to Antidepressant Drugs and Neurodevelopment: An Examination of Language, Mathematics, Intelligence, and Other Cognitive Outcomes. Journal of Clinical Psychiatry. 2022;83. doi:10.4088/JCP.22f14388 Campbell KSJ, Collier AC, Irvine MA, Brain U, Rurak DW, Oberlander TF, et al. Maternal Serotonin Reuptake Inhibitor Antidepressants Have Acute Effects on Fetal Heart Rate Variability in Late Gestation. Front Psychiatry. 2021;12. doi:10.3389/fpsyt.2021.680177 Sanson A, Nicholson J, Ungerer J, Zubrick S, Wilson K, Ainley J, et al. Introducing the Longitudinal Study of Australian Children. LSAC Discussion Paper. 2002. Goodman R. The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry. 1997;38: 581–6. doi:10.1111/j.1469-7610.1997.tb01545.x Uguz F. Neonatal and Childhood Outcomes in Offspring of Pregnant Women Using Antidepressant Medications: A Critical Review of Current Meta-Analyses. Journal of Clinical Pharmacology. 2021. doi:10.1002/jcph.1724 Morales DR, Slattery J, Evans S, Kurz X. Antidepressant use during pregnancy and risk of autism spectrum disorder and attention deficit hyperactivity disorder: Systematic review of observational studies and methodological considerations. BMC Med. 2018;16. doi:10.1186/s12916-017-0993-3 Nulman I, Rovet J, Stewart DE, Wolpin J, Gardner HA, Theis JG, et al. Neurodevelopment of children exposed in utero to antidepressant drugs. N Engl J Med. 1997;336: 258–262. doi:10.1056/NEJM199701233360404 Cohen LS, Rhodes SM, Claypoole LD, Góez-Mogollón L, Sosinsky AZ, Moustafa D, et al. Neurobehavioral follow-up of children exposed to selective serotonin reuptake inhibitors in utero. Annals of Clinical Psychiatry. 2022;34. doi:10.12788/acp.0074 Rommel AS, Bergink V, Liu X, Munk-Olsen T, Molenaar NM. Long-term effects of intrauterine exposure to antidepressants on physical, neurodevelopmental, and psychiatric outcomes: A systematic review. Journal of Clinical Psychiatry. 2020. doi:10.4088/JCP.19r12965 Brown HK, Ray JG, Wilton AS, Lunsky Y, Gomes T, Vigod SN. Association between serotonergic antidepressant use during pregnancy and autism spectrum disorder in children. JAMA - Journal of the American Medical Association. 2017;317. doi:10.1001/jama.2017.3415 Koc D, Tiemeier H, Stricker B, Muetzel R, Hillegers M, El Marroun H. Prenatal antidepressant exposure and offspring brain morphology trajectories: a longitudinal population-based mri study. Neuroscience Applied. 2023;2. doi:10.1016/j.nsa.2023.103325 Lugo-Candelas C, Cha J, Hong S, Bastidas V, Weissman M, Fifer WP, et al. Associations between brain structure and connectivity in infants and exposure to selective serotonin reuptake inhibitors during pregnancy. JAMA Pediatr. 2018;172. doi:10.1001/jamapediatrics.2017.5227 Van der Knaap N, Wiedermann D, Schubert D, Hoehn M, Homberg JR. Perinatal SSRI exposure affects brain functional activity associated with whisker stimulation in adolescent and adult rats. Sci Rep. 2021;11. doi:10.1038/s41598-021-81327-z Koc D, El Marroun H, Stricker BH, Muetzel RL, Tiemeier H. Intrauterine Exposure to Antidepressants or Maternal Depressive Symptoms and Offspring Brain White Matter Trajectories From Late Childhood to Adolescence. Biol Psychiatry Cogn Neurosci Neuroimaging. 2024;9. doi:10.1016/j.bpsc.2023.10.009 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6213737","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":428062769,"identity":"f396654f-a0be-4118-9d3c-2b11c7c49500","order_by":0,"name":"Ping-I Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIie3Ou2rDMBSA4WMCyiLbq4xM+goHMjaQVzEEMinFU+jYyV2cPX2MLpllNGTJZQ14ypLJQ6bQgksqtU43Kx476EcIIfRxBOBy/cekWSnEBHqyuUq6EARKgNyediBgCADFbiRYbwt51iTg+YWntYKwLxA+s3YSbZ6SYmk+Fm9X/C1TEOUVegsLQSlQUUPYbMX9lxLwoKf4NrKvUNU/RJw4rUsYa+J92Yh+oOCXEE6JnsIE9mxTokOFRY5Mk+nw0c+ulG1OqYp37STYi+H543k0eFhOjiWtp4PwdfJ+rObtpIn9najZ5F3gcrlcLmvf1BpLGpTRjd4AAAAASUVORK5CYII=","orcid":"","institution":"UNSW Sydney","correspondingAuthor":true,"prefix":"","firstName":"Ping-I","middleName":"","lastName":"Lin","suffix":""},{"id":428062772,"identity":"fc345962-7ae9-4a63-b336-3109df2efce4","order_by":1,"name":"Deonna Satiawan","email":"","orcid":"","institution":"Western Sydney University","correspondingAuthor":false,"prefix":"","firstName":"Deonna","middleName":"","lastName":"Satiawan","suffix":""},{"id":428062776,"identity":"6b63a519-c5a4-49c5-b6f8-838bb78e3964","order_by":2,"name":"Yi-Chia Chen","email":"","orcid":"","institution":"UNSW Sydney","correspondingAuthor":false,"prefix":"","firstName":"Yi-Chia","middleName":"","lastName":"Chen","suffix":""},{"id":428062783,"identity":"2f2df76b-08c9-4229-beb6-999b0aa322b9","order_by":3,"name":"Rushanyia Khairova","email":"","orcid":"","institution":"Saint Louis University","correspondingAuthor":false,"prefix":"","firstName":"Rushanyia","middleName":"","lastName":"Khairova","suffix":""}],"badges":[],"createdAt":"2025-03-12 16:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6213737/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6213737/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78692706,"identity":"2762cd99-1f23-46a1-85ac-6fa3a7f6ba47","added_by":"auto","created_at":"2025-03-17 16:28:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":154777,"visible":true,"origin":"","legend":"\u003cp\u003eTrajectories of emotional problems and hyperactivity from age of 4 to 8 stratified by presence of prenatal antidepressant exposure\u003c/p\u003e\n\u003cp\u003ePanel A shows the trajectory of predicted emotional problem scores in children stratified by the presence of prenatal antidepressant exposure. Panel B shows the trajectory of predicted hyperactivity scores in children stratified by the presence of prenatal antidepressant exposure. Vertical bars represent the 95% CI estimates at each time point.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6213737/v1/ab72119df8739581c4db482f.png"},{"id":79044766,"identity":"62ae2cae-3ccc-47c8-8727-beeea68e5a04","added_by":"auto","created_at":"2025-03-23 13:46:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":883226,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6213737/v1/9961f506-71ab-4343-a1c3-de6f7785ae7c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Prenatal Antidepressant Exposure on Trajectories of Childhood Emotions and Behaviors: Evidence from a Birth Cohort ","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMental health in pregnancy has become an increasingly significant global health issue in recent years. For example, nearly 10% of Australian women reporting anxiety and depression during pregnancy in 2020 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and an estimated 1 in 5 pregnant and postpartum individuals experience mental health conditions annually in the United States [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The need for adequate treatment of maternal depression and anxiety in the perinatal period is underpinned by the clear association with poorer outcomes in fetal and child development, including deficits in cognitive function, higher rates of insecure attachments and subsequent maladaptive behaviors [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, some concerns also surround the prescription of antidepressants to treat such illness, given that antidepressants themselves may also be associated with negative outcomes for the child in later life [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], including poorer neurodevelopmental outcomes with emotional and behavioral difficulties [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAntidepressants are increasingly being used to treat mothers with moderate to severe depression [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and have undergone the largest rise in prescription rate of the drugs prescribed in pregnancy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Current guidelines recommend selective serotonin reuptake inhibitors (SSRIs) as first-line therapy in moderate to severe perinatal depression [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], although other antidepressants, such as serotonin-noradrenaline reuptake inhibitors (SNRIs) may also be considered [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. SSRIs and SNRIs work by inhibiting serotonin reuptake in the presynaptic nerve terminals, which increases the concentration of serotonin in the synaptic cleft [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This increases serotonergic availability for adult brain functions such as mood control and social behaviors [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In pregnancy, the placenta serves as the primary source of serotonin for the fetus [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], where it is responsible for facilitating cell proliferation, nerve cell migration and synapse formation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, maternal antidepressants can also cross the placenta into fetal circulation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and, therefore, imbalances in fetal serotonin may be potentially linked with alterations in fetal brain development [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrenatal SSRI exposure has been associated with decreased salivary cortisol levels in offspring at 3 months [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and 6 years of age [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], possibly reflecting a dampened reactivity in the hypothalamic-pituitary-adrenal (HPA) axis which regulates the body's stress response [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Zusman et al. also found that this effect was enhanced in SSRI-exposed children with SLC6A4 genotype [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], suggesting some genetic factors may be involved. Additionally, in a study conducted by Koc et. al, children with antenatal SSRI exposure as well as active maternal depressive symptoms displayed a reduced white matter microstructure at age 7 when compared with children without exposure [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], although this effect was also moderated by faster growth in white matter pathways between 7 and 15 years of age, suggesting compensatory development [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Finally, in a study conducted by Meyer et. al., offspring of mice injected with sertraline in pregnancy showed markedly elevated cortical mRNA levels of various serotonin receptors and transporters but displayed no behavioral differences of statistical significance from the saline-injected controls [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. As such, research supports that morphological variations may be linked with maternal antidepressant use in utero [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], although further clarification is needed to translate physiological findings into measurable behavioral outcomes in humans [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome concern surrounds the potential for adverse outcomes with prenatal antidepressant use including cognitive delays, behavioral difficulties and neurodevelopmental issues [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; however, there are inconsistencies in current research. Whilst several studies have found significant associations with poorer neurodevelopmental and behavioral outcomes [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], these findings were largely attenuated by adjustment for confounding factors, with other studies showing no significant associations following adjustment analyses [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The inconsistencies in studies are likely due to the challenges in isolating the effects of antidepressant exposure from other confounding factors, such as maternal mental health and the broader childhood environment. Many studies suggest that maternal mental illness itself is a significant factor impacting child behaviors [\u003cspan additionalcitationids=\"CR17 CR18 CR19\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], including a review by Anns et. al. which found no significant risk linked with antenatal antidepressant exposure but identified an independent association between maternal depression and behavioral difficulties in children [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Additional factors, such as the timing of exposure and the infant sex, may also contribute to differences in behavioral outcomes. For example, Erickson et. al. found sex-specific differences in behavioral outcomes in infants [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while Lupattelli et. al. identified an increased risk of anxiety and depression symptoms at 5 years of age only in late-pregnancy exposure to SSRIs compared; no such risk was present with earlier exposure [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Ultimately, these findings highlight how unmeasured confounding factors may contribute to discrepancies in research [\u003cspan additionalcitationids=\"CR17 CR18 CR19 CR20\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo better address unmeasured confounding effects in the current study, we proposed to use inverse probability weighted (IPW) method, which offers a robust solution for addressing confounding factors, such as maternal depression and socioeconomic status[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This approach helps us balance covariates between exposed and unexposed groups, reducing potential bias and improving effect estimate accuracy. Further, we proposed cross-validation between growth curve models and repeated measure mixed models to capture the complex trajectories of neurodevelopment over time [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These complementary approaches can provide a more nuanced understanding of the long-term effects of prenatal antidepressant exposure, accounting for both time-invariant and time-varying confounders. By employing these methods, we aim to disentangle the direct effects of antidepressant exposure from other influential factors, potentially resolving inconsistencies in previous research findings. The overarching objective of this study is to investigate the joint influence of perinatal factors associated with prenatal antidepressant exposure on neurodevelopmental trajectories during childhood. Specifically, we aim to:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eExamine how prenatal antidepressant exposure and other perinatal factors collectively shape the trajectory of emotional problems in children.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDetermine how these perinatal factors jointly influence the trajectory of hyperactivity problems throughout childhood.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Setting and Sampling\u003c/h2\u003e \u003cp\u003eThis study utilized data from the Longitudinal Study of Australian Children (LSAC), a nationally representative birth cohort designed to examine child development and well-being across multiple domains. The sampling strategies and how multiple waves were collected are described elsewhere [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. For this secondary data analysis, we extracted data on perinatal history from wave 0, which included information on prenatal antidepressant exposure, maternal health, and socioeconomic factors. The sample consisted of 3,814 individuals with complete data on prenatal antidepressant exposure and neurodevelopmental outcomes at multiple time points. Developmental outcomes of children were assessed every two years for this birth cohort.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasures\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eKey prenatal exposure: Prenatal antidepressant exposure was determined based on self-reported medication use during pregnancy. This was the primary exposure of interest, with additional perinatal and socioeconomic factors included as covariates to adjust for potential confounding effects.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePerinatal Factors: To account for confounders influencing both prenatal antidepressant exposure and neurodevelopmental outcomes, we included maternal self-reported intra-partum stress, maternal smoking during pregnancy, gestational age at birth, and birth weight. These covariates were incorporated into the propensity score estimation process to model the likelihood of prenatal antidepressant exposure.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSocioeconomic Factors: Maternal educational attainment (categorized as less than high school versus higher education levels) and family income (classified as greater than A\u003cspan\u003e$\u003c/span\u003e60,000 per year, a median income in Australia in 2023, versus lower income levels) were included to adjust for socioeconomic disparities potentially associated with both antidepressant use and child neurodevelopment. These variables were used to estimate propensity scores, which were subsequently employed in the inverse probability weighting calculations to enhance the robustness of the analysis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNeurodevelopmental outcomes: The two scores for emotional problems and hyperactivity based on the measures using Strength and Difficulty Questionnaire (SDQ) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] at ages 4, 6, and 8, were the primary outcome measures. It measures five key domains: emotional symptoms, conduct problems, hyperactivity or inattention, peer relationship problems, and prosocial behavior, which can evaluate children's psychological well-being and identify potential mental health concerns.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical methods\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1. Descriptive analysis\u003c/h3\u003e\n\u003cp\u003eDifferences between children with a presence of prenatal antidepressant exposure and children without a presence of prenatal antidepressant exposure were examined for all key covariates. Continuous variables such as neurodevelopmental outcome variables (i.e., hyperactivity and emotional problem scores) were analyzed using t-tests. Categorical variables were analyzed using chi-square tests.\u003c/p\u003e\n\u003ch3\u003e2. Calculate inverse probability weight based on the likelihood for prenatal antidepressant exposure\u003c/h3\u003e\n\u003cp\u003eTo account for potential confounding in the association between prenatal antidepressant exposure and child outcomes, we applied inverse probability weighting (IPW). First, we estimated the propensity score, defined as the predicted probability of prenatal antidepressant exposure, using a logistic regression model. This model included key maternal and perinatal covariates such as maternal age, education, income, smoking status, perceived stress during pregnancy, and birth weight. Each participant was then assigned an inverse probability weight (IPW), calculated as the inverse of the estimated probability of their observed exposure status. This approach aimed to balance observed covariates between exposed and non-exposed groups, thereby reducing confounding bias. The resulting weighted sample approximates a pseudo-randomized population, allowing for a more robust estimation of the causal effects of prenatal antidepressant exposure on neurodevelopmental outcomes.\u003c/p\u003e\n\u003ch3\u003e3. Growth curve model analysis\u003c/h3\u003e\n\u003cp\u003eTo examine the longitudinal trajectories of hyperactivity and emotional problems in children exposed to prenatal antidepressants, we employed a growth curve model (GCM) using mixed-effects regression. This approach accounts for individual variability and allows us to estimate both baseline differences and changes over time. We fit two separate linear mixed-effects models (LMMs) using maximum likelihood estimation (MLE): one for hyperactivity and one for emotional problems. Fixed effects included Prenatal antidepressant exposure, time (centered at baseline), and their interaction (i.e., antidepressant exposure \u0026times; time) to estimate exposure-related differences in developmental trends. Additional covariates included maternal smoking, maternal stress, maternal age, maternal education attainment (less than high school versus at least high school), annual household income (less than A\u003cspan\u003e$\u003c/span\u003e60,000 versus at least A\u003cspan\u003e$\u003c/span\u003e60,000), and birth weight.\u003c/p\u003e \u003cp\u003eThe final models were estimated as follows normalized neurodevelopmental outcome\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e1\u003c/sub\u003e(antidepressanti) + β\u003csub\u003e2\u003c/sub\u003e(ctime) + β\u003csub\u003e3\u003c/sub\u003e(antidepressant \u0026times; ctime) + \u0026sum;β\u003csub\u003ek\u003c/sub\u003eX\u003csub\u003eik\u003c/sub\u003e + u\u003csub\u003ei\u003c/sub\u003e + ϵ\u003csub\u003eit\u003c/sub\u003e, where ctime represents the time variable subtracted with 1, β\u003csub\u003e3\u003c/sub\u003e estimates whether prenatal antidepressant exposure affects the rate of change in hyperactivity over time, represents additional covariates, u\u003csub\u003ei\u003c/sub\u003e is the random intercept, capturing individual variability, and ϵ\u003csub\u003eit\u003c/sub\u003e is the residual error. Random effects were individual-specific random intercepts to account for between-subject variability. Weighting was based on IPW to adjust for confounding due to selection bias.\u003c/p\u003e\n\u003ch3\u003e4. Repeated measure mixed model analysis\u003c/h3\u003e\n\u003cp\u003eTo further investigate the longitudinal effects of prenatal antidepressant exposure on child neurodevelopment, we conducted a repeated measures mixed model (RMMM) analysis. This approach accounts for within-subject correlations across different time points while adjusting for potential confounders IPW. Similar to GCM, the model was estimated using maximum likelihood (ML), and an unstructured covariance matrix was used to allow for flexible modeling of within-subject correlations. The time variable was based on the original codes values for the three ages (i.e., 4, 6, and 8 years).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e1. Characteristics of the cohort\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes features of children with prenatal exposure to antidepressants versus children without prenatal exposure to antidepressants. Children exposed to prenatal antidepressants exhibited significantly higher hyperactivity and emotional problem scores compared to non-exposed children (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting potential impacts on early childhood behavioral outcomes.\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\u003eCharacteristic of the birth cohort stratified by presence of prenatal antidepressant exposure\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eExposed (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-Exposed (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurodevelopmental 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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperactivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmotional Problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight (mg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2940\u0026thinsp;\u0026plusmn;\u0026thinsp;650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3120\u0026thinsp;\u0026plusmn;\u0026thinsp;580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.021*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Maternal Education (\u0026lt;\u0026thinsp;HS vs. HS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.048*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Income (\u0026lt;\u003cspan\u003e$\u003c/span\u003e60K vs. Others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\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\u003eIn terms of perinatal factors, birth weight was significantly lower among exposed children (p\u0026thinsp;=\u0026thinsp;0.021), indicating potential differences in fetal growth. However, maternal age categories (\u0026lt;\u0026thinsp;25, 25\u0026ndash;29, 30\u0026ndash;34, \u0026ge;\u0026thinsp;35 years) did not significantly differ between the two groups, suggesting that maternal age alone may not be a key determinant of exposure-related outcomes.\u003c/p\u003e \u003cp\u003eMaternal and socioeconomic factors also differed between groups. Mothers of exposed children were more likely to have lower education levels (less than high school) and report lower household income (\u0026lt;\u003cspan\u003e$\u003c/span\u003e60K), with both factors reaching statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, maternal smoking and perceived stress during pregnancy were significantly more prevalent in the exposed group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively), highlighting important environmental and psychosocial risk factors associated with prenatal antidepressant exposure.\u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. Growth curve models (GCM)\u003c/h3\u003e\n\u003cp\u003eThe results from the analyses based on growth curve models (GCM) for the two neurodevelopmental outcomes are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults from the growth curve model analyses\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional Problems (β, 95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHyperactivity (β, 95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrenatal Antidepressant Exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10 (-0.06 to 0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.06 (-0.24 to 0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime (Per 2 Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10 (0.08 to 0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03 (0.01 to 0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressant \u0026times; Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05 (0.02 to 0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15 (0.13 to 0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26 (0.19 to 0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19 (0.11 to 0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08 (-0.15 to -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.27 (-0.35 to -0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Maternal Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03 (-0.02 to 0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14 (0.07 to 0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08 (0.02 to 0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.003 to 0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.06 (-0.10 to -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.002 (-0.05 to 0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14 (-0.07 to 0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37 (0.15 to 0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Emotional Problems\u003c/h2\u003e \u003cp\u003ePrenatal antidepressant exposure was not significantly associated with baseline emotional problems (β\u0026thinsp;=\u0026thinsp;0.095, p\u0026thinsp;=\u0026thinsp;0.223), indicating that exposed and non-exposed children had similar levels of emotional difficulties at age 4. However, emotional problems increased significantly over time for all children, as shown by the positive main effect of time (β\u0026thinsp;=\u0026thinsp;0.100, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting worsening symptoms as children aged. Importantly, the interaction between antidepressant exposure and time remained significant (β\u0026thinsp;=\u0026thinsp;0.046, p\u0026thinsp;=\u0026thinsp;0.003), indicating that exposed children experienced a greater increase in emotional problems over time compared to their non-exposed peers. This finding suggests that while prenatal exposure was not linked to immediate emotional difficulties, its effects became more pronounced with age, leading to a widening gap in emotional problems between exposed and non-exposed children.\u003c/p\u003e \u003cp\u003eAmong the covariates, maternal stress was strongly associated with increased emotional problems (β\u0026thinsp;=\u0026thinsp;0.255, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while maternal smoking was inversely associated with emotional problems (β = -0.080, p\u0026thinsp;=\u0026thinsp;0.033). Low household income was also a significant predictor of increased emotional difficulties (β\u0026thinsp;=\u0026thinsp;0.076, p\u0026thinsp;=\u0026thinsp;0.005), while maternal education was not significantly associated with emotional problems (p\u0026thinsp;=\u0026thinsp;0.252). Additionally, lower birth weight was associated with higher emotional problem scores (β = -0.000058, p\u0026thinsp;=\u0026thinsp;0.014).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Hyperactivity\u003c/h2\u003e \u003cp\u003ePrenatal antidepressant exposure was not significantly associated with baseline hyperactivity (β = -0.062, p\u0026thinsp;=\u0026thinsp;0.490), suggesting that exposed and non-exposed children had similar levels of hyperactivity at age 4. However, hyperactivity increased significantly over time for all children (β\u0026thinsp;=\u0026thinsp;0.033, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a general upward trajectory of hyperactivity symptoms with age. Notably, the interaction between antidepressant exposure and time was highly significant (β\u0026thinsp;=\u0026thinsp;0.151, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that children exposed to prenatal antidepressants exhibited a steeper increase in hyperactivity over time compared to non-exposed children. This delayed effect implies that while no early differences in hyperactivity were observed, exposed children showed increasing hyperactivity symptoms as they aged.\u003c/p\u003e \u003cp\u003eAmong the covariates, maternal stress was a strong independent predictor of increased hyperactivity symptoms (β\u0026thinsp;=\u0026thinsp;0.186, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Lower maternal education was significantly associated with higher hyperactivity scores (β\u0026thinsp;=\u0026thinsp;0.136, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as was low household income (β\u0026thinsp;=\u0026thinsp;0.059, p\u0026thinsp;=\u0026thinsp;0.039). Maternal smoking was inversely associated with hyperactivity symptoms (β = -0.275, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and birth weight was not significantly associated with hyperactivity (p\u0026thinsp;=\u0026thinsp;0.941).\u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3. Repeated measure mixed model (RMMM)\u003c/h2\u003e \u003cp\u003eThe results from the RMMM analyses are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults from the repeated measure mixed model analyses\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional Problems (β, 95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHyperactivity (β, 95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrenatal Antidepressant Exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.07 (-0.09 to 0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02 (-0.19 to 0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime: Age 6 vs. 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16 (0.12 to 0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09 (0.05 to 0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime: Age 8 vs. 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20 (0.16 to 0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07 (0.03 to 0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressant \u0026times; Age 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12 (0.06 to 0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03 (-0.02 to 0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressant \u0026times; Age 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09 (0.02 to 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30 (0.25 to 0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25 (0.19 to 0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19 (0.11 to 0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08 (-0.15 to -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.27 (-0.35 to -0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Maternal Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03 (-0.02 to 0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14 (0.07 to 0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08 (0.02 to 0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06 (0.003 to 0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight (per 1000g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.06 (-0.10 to -0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.002 (-0.05 to 0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11 (-0.09 to 0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35 (0.13 to 0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\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\u003e3.1. Emotional Problems\u003c/p\u003e \u003cp\u003ePrenatal antidepressant exposure was not significantly associated with baseline emotional problems at age 4 (β\u0026thinsp;=\u0026thinsp;0.067, p\u0026thinsp;=\u0026thinsp;0.393), suggesting no initial differences between exposed and non-exposed children. However, emotional problems increased significantly over time for all children, as indicated by the main effects of time (age 6 vs. 4: β\u0026thinsp;=\u0026thinsp;0.163, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; age 8 vs. 4: β\u0026thinsp;=\u0026thinsp;0.200, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The interaction terms between prenatal antidepressant exposure and time remained significant, indicating that exposed children experienced a steeper increase in emotional problems compared to non-exposed children (age 6 vs. 4: β\u0026thinsp;=\u0026thinsp;0.122, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; age 8 vs. 4: β\u0026thinsp;=\u0026thinsp;0.085, p\u0026thinsp;=\u0026thinsp;0.006). This suggests that while prenatal exposure was not associated with higher emotional problems at age 4, its effects emerged over time, leading to a widening gap between exposed and non-exposed children by age 8.\u003c/p\u003e \u003cp\u003eAmong the covariates, maternal stress was strongly associated with higher emotional problem scores (β\u0026thinsp;=\u0026thinsp;0.255, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while maternal smoking and birth weight were inversely associated with emotional problems (maternal smoking: β = -0.079, p\u0026thinsp;=\u0026thinsp;0.034; birth weight: β = -0.000057, p\u0026thinsp;=\u0026thinsp;0.015). Low household income was also a significant predictor of increased emotional problems (β\u0026thinsp;=\u0026thinsp;0.076, p\u0026thinsp;=\u0026thinsp;0.005), while maternal education was not significantly associated (p\u0026thinsp;=\u0026thinsp;0.261).\u003c/p\u003e \u003cp\u003e3.2. Hyperactivity\u003c/p\u003e \u003cp\u003eSimilar to emotional problems, prenatal antidepressant exposure was not significantly associated with hyperactivity at age 4 (β = -0.017, p\u0026thinsp;=\u0026thinsp;0.850), and no significant interaction was observed at age 6 (β\u0026thinsp;=\u0026thinsp;0.026, p\u0026thinsp;=\u0026thinsp;0.308), suggesting no early differences in hyperactivity trajectories. However, by age 8, a highly significant interaction between antidepressant exposure and time emerged (β\u0026thinsp;=\u0026thinsp;0.304, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a delayed effect of prenatal antidepressant exposure on hyperactivity.\u003c/p\u003e \u003cp\u003eSeveral covariates were also significantly associated with hyperactivity outcomes. Maternal stress was a strong independent predictor of higher hyperactivity scores (β\u0026thinsp;=\u0026thinsp;0.186, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while maternal smoking was associated with lower hyperactivity scores (β = -0.274, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, lower maternal education was significantly associated with increased hyperactivity symptoms (β\u0026thinsp;=\u0026thinsp;0.136, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as was low household income (β\u0026thinsp;=\u0026thinsp;0.059, p\u0026thinsp;=\u0026thinsp;0.037). Birth weight was not significantly associated with hyperactivity (p\u0026thinsp;=\u0026thinsp;0.947).\u003c/p\u003e \u003cp\u003eTrajectories of the scores for emotional problems and hyperactivity are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The trends indicate that children exposed to prenatal depressants started to show increasingly higher levels of emotional problems than children without prenatal antidepressant exposure after the age of 6. Similarly, children exposed to prenatal depressants started to show increasingly higher levels of hyperactivity than children without prenatal antidepressant exposure, but the difference became significant after the age of 8.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here]\u003c/p\u003e \u003cp\u003e[Insert Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here]\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSIONS","content":"\u003cp\u003eIn this nationwide community-based cohort study, the results suggest that prenatal antidepressant exposure is not solely responsible for differences in neurodevelopmental outcomes but rather influences their trajectories over time. While exposed and non-exposed children had similar emotional problem and hyperactivity scores at age 4, exposed children exhibited a steeper increase in symptoms as they aged, leading to significant differences by age 8. Emotional problems in exposed children worsened progressively between ages 4 and 8, while hyperactivity differences did not emerge until age 8, suggesting a delayed impact of prenatal antidepressant exposure on behavioral regulation. Additionally, maternal stress and socioeconomic factors, including low household income and lower maternal education, were strongly associated with neurodevelopmental difficulties. These findings underscore the importance of considering the dynamic nature of development when evaluating the effects of prenatal antidepressant exposure, as its impact may not be evident in early childhood but can shape the trajectory of emotional and behavioral outcomes over time.\u003c/p\u003e \u003cp\u003eSeveral systematic reviews and meta-analysis have examined the relationships between the exposure to antidepressants in utero and neurodevelopmental disorders in offspring, often with mixed results [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our findings are consistent with the study by Lupatelli et al, showing an increased levels of anxiety behaviors in 5-year-olds exposed to maternal SSRIs in utero [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Conversely, several other studies found no increased risk for anxiety and internalizing behaviors in children. For example, Nulman et al. reported no significant differences in emotional or behavior problems between children with in-utero exposure to tricyclic antidepressant or fluoxetine, compared with children without prenatal antidepressant exposure [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Cohen et al. found that maternal SSRI use during pregnancy was not linked to atypical neurodevelopment, while higher maternal depression burden was associated with internalizing symptoms, while SSRI-exposed children showed better executive function [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. One review study summarizing findings from 34 studies also does not support the association between prenatal antidepressant exposure and neurodevelopmental outcomes in children when the analysis controlled for maternal conditions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Such inconsistent findings across different populations may stem from differences in how prenatal antidepressant exposure data were categorized and how neurodevelopmental outcomes in children were analyzed.\u003c/p\u003e \u003cp\u003ePrevious studies that did not account for exposure propensity may have been limited in their ability to fully adjust for confounding factors associated with both maternal antidepressant use and child neurodevelopmental outcomes. Without properly modeling the likelihood of exposure, differences observed between exposed and non-exposed groups may reflect underlying maternal characteristics rather than the direct effect of antidepressants themselves. Studies have shown that maternal psychiatric conditions, genetic predisposition, and environmental factors contribute to both prenatal antidepressant exposure during pregnancy and child neurodevelopmental trajectories, highlighting the need for careful confounding control [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Our approach, which incorporates IPW, might help address confounding by balancing observed differences between exposed and non-exposed groups, thereby providing less biased estimates of the effect of prenatal antidepressant exposure on neurodevelopmental outcomes.\u003c/p\u003e \u003cp\u003eAlthough the detailed mechanism of antidepressants affecting brain neurodevelopment remains elusive, it has been well established that SSRIs are able to cross the placenta and enter the intrauterine environment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Accumulating evidence indicates that SSRI exposure during pregnancy prenatal selective serotonin reuptake inhibitor exposure has a significant association with fetal brain development [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Preclinical evidence also suggests that prenatal antidepressant exposure could impact brain networks involved in sensory perception and processing [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Although evidence suggests a potential role of prenatal SSRI exposure in brain structural variation, it remains uncertain whether this exposure directly results in neurodevelopmental differences at a specific age. Instead, it may subtly influence developmental processes, potentially shaping the trajectory of neurodevelopmental outcomes over time.\u003c/p\u003e \u003cp\u003eWhile most of the studies have found no association between prenatal exposure to antidepressants and risks of neurodevelopmental outcomes, findings of our study highlight subclinical behavioral changes during early childhood. One explanation of these findings is that prenatal exposure to antidepressants can alter developmental trajectories in brain areas associated with emotional regulation leading to increased hyperactivity and emotional dysregulation in offspring. Interestingly, while some changes in brain morphology persisted into adolescence, others did not, suggesting a developmental delay, rather than permanent structural change. Recent findings from the large population cohort study provide further evidence that initial white matter microstructure changes observed in younger children exposed to maternal SSRIs in utero diminish over time, suggesting a phenomenon of catch-up growth during adolescence [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Further studies are needed to investigate the trajectory of the observed behavioral changes in our study into older children and adolescents.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eAlthough there are no clearly defined treatment guidelines regarding the use of antidepressants in pregnancy, concerns regarding the effects of SSRI exposure in utero often the play the critical role in making the decision about the use of antidepressants during pregnancy. Given that up to 15% of women experience the depression in pregnancy this decision can have a long-lasting impact on both maternal and infant mental health. While our study suggests the possibility of prenatal effect on antidepressants on increased risks of child’s externalizing behaviors, specifically emotional dysregulation, and hyperactivity during the ages of 4–8 years old, the impact of maternal mental illness remains unclear. The current study contributes to our understanding of the effects of the prenatal antidepressant exposure on neurobehavioral outcomes of the offspring, however the information is still incomplete. At this time, it would be premature to restrict use of antidepressant treatment during pregnancy based on the results of our study. Further research is needed on the longitudinal trajectory of neurobehavioral outcomes throughout the childhood and adolescence in children exposed to maternal SSRIs in utero.\u003c/p\u003e \u003c/div\u003e "},{"header":"SUMMARY","content":"\u003cp\u003ePrenatal antidepressant exposure has been extensively studied in relation to child neurodevelopment, but findings remain inconsistent, with some studies indicating increased risks for emotional and behavioral problems while others report no significant effects. This study suggests that while prenatal antidepressant exposure does not result in immediate neurodevelopmental differences at age 4, it influences developmental trajectories, leading to a progressive increase in emotional problems and a delayed rise in hyperactivity by age 8. These findings highlight the importance of long-term developmental monitoring in clinical practice to identify emerging emotional and behavioral difficulties. Additionally, the role of maternal stress and socioeconomic factors underscores the need for supportive interventions during pregnancy, which could help mitigate risks and inform policy and service development in maternal mental health care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eP.L. and Y.C. conceptualized the study. P.L. performed the statistical data analysis. Y.C. prepared figure 1. P.L., D.S., and R.K. wrote the main manuscript text. All authors reviewed and edited the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis study uses data from the Longitudinal Study of Australian Children (LSAC), a nationally representative cohort study conducted by the Australian Government Department of Social Services (DSS) in partnership with the Australian Institute of Family Studies (AIFS). Access to LSAC data is restricted and available to approved researchers through an application process via the National Centre for Longitudinal Data (NCLD). More information on data access and application procedures can be found at https://growingupinaustralia.gov.au/.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRoyal Australia and New Zealand College of Obstetrics and Gynaecology. Mental health care in the perinatal period: Clinical practice guideline. 2023.\u003c/li\u003e\n\u003cli\u003eDagher RK, Bruckheim HE, Colpe LJ, Edwards E, White DB. Perinatal Depression: Challenges and Opportunities. J Womens Health. 2021;30. doi:10.1089/jwh.2020.8862\u003c/li\u003e\n\u003cli\u003eQui\u0026ntilde;ones FWCHLSA. Untreated Major Depression During Gestation: The Physical and Mental Implications in Women and Their Offspring. Georgetown Medical Review. 2023.\u003c/li\u003e\n\u003cli\u003eFrayne JTNSA and JR. 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J Am Acad Child Adolesc Psychiatry. 2018;57. doi:10.1016/j.jaac.2017.12.010\u003c/li\u003e\n\u003cli\u003eAndrade C. Gestational Exposure to Antidepressant Drugs and Neurodevelopment: An Examination of Language, Mathematics, Intelligence, and Other Cognitive Outcomes. Journal of Clinical Psychiatry. 2022;83. doi:10.4088/JCP.22f14388\u003c/li\u003e\n\u003cli\u003eCampbell KSJ, Collier AC, Irvine MA, Brain U, Rurak DW, Oberlander TF, et al. Maternal Serotonin Reuptake Inhibitor Antidepressants Have Acute Effects on Fetal Heart Rate Variability in Late Gestation. Front Psychiatry. 2021;12. doi:10.3389/fpsyt.2021.680177\u003c/li\u003e\n\u003cli\u003eSanson A, Nicholson J, Ungerer J, Zubrick S, Wilson K, Ainley J, et al. Introducing the Longitudinal Study of Australian Children. LSAC Discussion Paper. 2002.\u003c/li\u003e\n\u003cli\u003eGoodman R. The Strengths and Difficulties Questionnaire: a research note. 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JAMA - Journal of the American Medical Association. 2017;317. doi:10.1001/jama.2017.3415\u003c/li\u003e\n\u003cli\u003eKoc D, Tiemeier H, Stricker B, Muetzel R, Hillegers M, El Marroun H. Prenatal antidepressant exposure and offspring brain morphology trajectories: a longitudinal population-based mri study. Neuroscience Applied. 2023;2. doi:10.1016/j.nsa.2023.103325\u003c/li\u003e\n\u003cli\u003eLugo-Candelas C, Cha J, Hong S, Bastidas V, Weissman M, Fifer WP, et al. Associations between brain structure and connectivity in infants and exposure to selective serotonin reuptake inhibitors during pregnancy. JAMA Pediatr. 2018;172. doi:10.1001/jamapediatrics.2017.5227\u003c/li\u003e\n\u003cli\u003eVan der Knaap N, Wiedermann D, Schubert D, Hoehn M, Homberg JR. Perinatal SSRI exposure affects brain functional activity associated with whisker stimulation in adolescent and adult rats. Sci Rep. 2021;11. doi:10.1038/s41598-021-81327-z\u003c/li\u003e\n\u003cli\u003eKoc D, El Marroun H, Stricker BH, Muetzel RL, Tiemeier H. Intrauterine Exposure to Antidepressants or Maternal Depressive Symptoms and Offspring Brain White Matter Trajectories From Late Childhood to Adolescence. Biol Psychiatry Cogn Neurosci Neuroimaging. 2024;9. doi:10.1016/j.bpsc.2023.10.009\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6213737/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6213737/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aimed to investigate the long-term impact of prenatal antidepressant exposure on child neurodevelopmental trajectories, focusing on emotional problems and hyperactivity by taking exposure propensity into account. We analyzed data from the Longitudinal Study of Australian Children (LSAC), a nationally representative birth cohort. Prenatal antidepressant exposure was determined based on self-reported medication use during pregnancy. Neurodevelopmental outcomes, including emotional problems and hyperactivity, were assessed using the Strengths and Difficulties Questionnaire (SDQ) at ages 4, 6, and 8. To adjust for confounding, inverse probability weighting (IPW) was applied. Growth curve models (GCMs) and repeated measures mixed models (RMMMs) were used to assess developmental trajectories. The results indicate that prenatal antidepressant exposure was not significantly associated with overall differences in emotional problems or hyperactivity. However, exposed children exhibited a steeper increase in emotional problems over time compared to non-exposed peers (GCM interaction: β\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.003; RMMM age 6 vs. 4: β\u0026thinsp;=\u0026thinsp;0.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; age 8 vs. 4: β\u0026thinsp;=\u0026thinsp;0.09, p\u0026thinsp;=\u0026thinsp;0.006). Hyperactivity differences emerged only at age 8, with exposed children showing a significant increase in symptoms (GCM interaction: β\u0026thinsp;=\u0026thinsp;0.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; RMMM age 8 vs. 4: β\u0026thinsp;=\u0026thinsp;0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Maternal stress was consistently associated with higher emotional and hyperactivity scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while low household income and lower maternal education were linked to greater neurodevelopmental difficulties. Our findings suggest that although prenatal antidepressant exposure does not directly determine neurodevelopmental differences between the age of 4 and 8, it might influence the trajectory of emotional and behavioral regulation over time. The delayed effects on hyperactivity and the progressive increase in emotional difficulties highlight the importance of long-term follow-up in exposed children.\u003c/p\u003e","manuscriptTitle":"Impact of Prenatal Antidepressant Exposure on Trajectories of Childhood Emotions and Behaviors: Evidence from a Birth Cohort ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-17 16:19:58","doi":"10.21203/rs.3.rs-6213737/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":"d5228555-9e45-415b-a2b8-a3c264746175","owner":[],"postedDate":"March 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-23T13:38:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-17 16:19:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6213737","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6213737","identity":"rs-6213737","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}