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1 Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, California, United States of America;
2 Pan Association Health Society, Los Angeles, California, United States of America;
3 Internal Medicine & Psychiatry, Walter Reed National Military Medical Center, Bethesda, Maryland, United States of America
Corresponding Author: 1) Jing Liang MD. PhD., Professor, Clinical Pharmacology, USC School of Pharmacy, PSC 504, 1985 Zonal Ave. Los Angeles, California 90089, USA; Phone: 323-442-3118; E-mail: jliang1@usc.edu. 2) Amy S. Shao MD., Internal Medicine & Psychiatry, Walter Reed National Military Medical Center, Bethesda, Maryland, USA. Email: amy.s.shao.mil@health.mil.
¶ These authors contributed equally to this work.
* These authors contributed equally to the corresponding work.
Running title: PARENTAL CONDITIONS AND AUTISM INCIDENCE
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ABSTRACT
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Individuals with autism spectrum disorder (ASD) often face unique barriers in daily life, education, and social interactions. Family members also face challenges in caregiving, education, and social interactions, often contributing to heightened stress, depression, and trauma. This questionnaire-based survey study aimed to understand the roles of parental and prenatal conditions in ASD development. Data were collected through online questionnaires completed by families of individuals with clinically diagnosed ASD. The questionnaire consisted of multiple-choice questions and was distributed via email to families (n=123) affiliated with the Pan American Health Society. We found: 1) A significant association between paternal age and incidence of ASD. 2) A strong association between maternal stress levels during pregnancy and incidence of ASD. 3) An association between autism and male gender. This survey highlights several critical parental and prenatal factors associated with ASD. Paternal age and maternal stress during pregnancy emerged as contributors to ASD development, underscoring the need for awareness and preventative strategies. The observed association between autism status and male gender provides a basis for further investigation into biological and environmental mechanisms. These findings emphasize the importance of targeted interventions and enhanced support systems to address risk factors and improve outcomes for individuals with ASD and their families.
KEY WORDS: Autism spectrum disorder; parental and maternal, stress during pregnancy|
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INTRODUCTION |
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Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social interaction, communication, and restricted or repetitive behaviors (1, 2). The prevalence of ASD has risen significantly over recent decades (3), and current estimates suggest that approximately 1 in 36 children in the United States is diagnosed with ASD (4), highlighting the urgent need for deeper understanding and improved support for affected individuals and their families.
While research has advanced our knowledge of the genetic and environmental factors contributing to ASD, much less attention has been paid to the experiences and needs of families living with autism. Families of individuals with ASD often face a range of challenges, including heightened caregiving demands, social stigma, and difficulties accessing appropriate education and healthcare services (5). These stressors can result in significant psychological, emotional, and financial burdens, leaving families at risk of elevated levels of stress, depression, and even trauma (5, 6). Consequently, addressing the needs of families is an essential component of improving overall outcomes for individuals with ASD.
Genetic and environmental factors are major etiological contributors to ASD development (7), 20. Parental and prenatal factors, including elevated maternal stress during pregnancy, have been increasingly linked to the development of ASD. (7, 8). However, the interplay of these factors, along with their potential contributions to the condition, remains unclear. Additionally, gender-related differences in the prevalence and presentation of ASD suggest the involvement of distinct biological and environmental mechanisms that require further investigation (9).
This study aims to understand the potential risk factors for ASD development. Through a questionnaire-based survey distributed via the Pan American Health Society, we gathered information from families affected by ASD. By identifying associations between parental and prenatal factors and ASD, this research seeks to inform preventative strategies, targeted interventions, and the development of support systems that address the needs of families and individuals with autism.
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MATERIALS AND METHODS |
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Survey form (Table 1)
The studies were reviewed and approved by the University of Southern California Institutional Review Board (IRB approval ID: UP-24-00954). The participants provided their written informed consent to participate in this study. This study adheres to CONSORT guidelines.
The questionnaire consisted of multiple-choice questions and was distributed via email to families affiliated with the Pan American Health Society, the regional office of the World Health Organization in the Americas. Every child reported to have ASD received the diagnosis from at least one licensed physician. Data collection was conducted through online questionnaires completed by families of individuals with ASD. Each participating family received: 1) a Google Forms link to access and complete the questionnaire; 2) an explanation of the study’s purpose, procedures, and participant rights; and 3) an informed consent form outlining voluntary participation, confidentiality, and data usage.
Within the questionnaire, the ages of the autistic family members are grouped into 0-4, 5-12, 13-17, and over 18 years of age. Child’s daily activity levels are defined as level 0: entirely inactive, showing no engagement in physical, cognitive, or social activities; level 1: very limited movement or interaction, requiring frequent prompting to participate; level 2: occasionally engages in simple activities but spends most of the day inactive; level 3: participates in moderate activities with some sustained engagement and regular breaks; level 4: the child actively engages in a variety of tasks or play with consistent energy and focus; and level 5: the child is highly energetic, constantly engaged in activities with minimal need for rest. Stress is defined as the physical, emotional, or psychological responses to an external cause in which the demands of a situation (such as problems or challenges from work, family, friends, health, finances, or the environment) exceed the resources of the individual in a way that affects the individual’s emotional state or ability to carry out daily tasks (10). As such, we summarized common stressors and classified stress levels into six categories.
Within the survey, ‘Stress levels’ refer to: No stress experienced. Mild: Low, manageable stress. Moderate: Noticeable but not overwhelming stress. Severe: Intense, potentially overwhelming stress. Stress with dreaming: Stress accompanied by vivid or disruptive dreams. Stress with sleep problems: Stress causing sleep difficulties, such as trouble falling or staying asleep. Anyone diagnosed with disease(s), such as attention-deficit/hyperactivity disorder (ADHD) and mental problems were not included in this survey study.
The online survey was created on Google forms by our team member: https://docs.google.com/forms/d/e/1FAIpQLSffP5uZ6VDnGr38tIf9XaPbS2g9Zxp_TEbFfO4Pm66oy1nBfQ/viewform?usp=sf_link
The volunteer participants
The survey inclusion criteria required participants to be able to read and understand English, provide informed consent, and have access to the internet and an electronic device to complete the online survey.
Participants who failed to complete the required sections of the survey were excluded from the final analysis.
Statistical Analyses
Categorical data are expressed as medians and box plots, analyzed with Chi-Square Statistics. Data of continuous variables are expressed as mean ± SE and bar chats, analyzed with ANOVA followed by multiple comparison Sidak method. p ≤ 0.05 was considered statistically significant.
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RESULTS |
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Gender Differences in ASD and Non-ASD Populations (Table 2)
The gender data of ASD and non-ASD groups are listed in Table 2. Chi-square Statistic = 8.89 (p-value: 0.00286), which suggests a significant association between the group (ASD vs. Non-ASD) and gender distribution. The odds ratio (OR) = 3.45 indicates that males are 3.45 times more likely to have ASD compared to females in this dataset. The observed data suggests that males are more likely to have autism compared to females.
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Activity Level Differences in ASD and Non-ASD Populations (Figure 1)
Both ASD males and females exhibit lower median activity levels compared to their non-ASD counterparts, reflecting reduced overall activity in children with ASD (One way ANOVA, Holm-Sidak method, p < 0.05). Non-ASD Groups: Non-ASD males and females show significantly higher activity levels, as indicated by the higher median values and broader interquartile ranges.
Statistical Analysis: Asterisks indicate statistically significant differences in activity levels between the ASD and non-ASD groups (p < 0.05), suggesting a meaningful impact of ASD on daily activity levels. This result highlights a notable reduction in daily activity levels among children with ASD compared to non-ASD children.
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The Correlation Between Parental Age and ASD Development (Figure 2)
One-way ANOVA followed by multiple comparison Sidek method was performed. The paternal ages are significantly higher in children with ASD compared to children without ASD. The data suggest a relationship between advanced parental age and the development of ASD, with older parental age, particularly paternal age, associated with increased ASD risk.
The findings suggest a relationship between advanced parental age and the development of ASD, with older parental age, particularly paternal age, being associated with an increased risk of ASD. The study highlights that the parents of children with ASD, especially fathers, tend to be older than the parents of non-ASD children, emphasizing a potential link between advanced parental age and the likelihood of ASD development.
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Maternal Stress Levels During Pregnancy are associated with ASD Development (Figure 3)
Our survey shows that maternal stress levels during pregnancy are notably higher in cases where the child is diagnosed with ASD compared to mothers of non-ASD children. These results suggest that heightened maternal stress during pregnancy is associated with the likelihood of ASD development in children.
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Maternal Infection During Pregnancy and ASD (Table 3)
In this survey study, we also collected data and analyzed the relationship between the mother catching the flu or a cold during pregnancy and the incidence of ASD children.
Chi-square test analysis shows there is no statistically significant association between maternal infection during pregnancy and the incidence of ASD. However, the analysis result (p = 0.052) approaches the significant level of 0.05, suggesting a potential trend. Further investigation on whether specific infections contribute to the ASD risk is warranted (probably with a larger dataset).
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DISCUSSION |
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This survey study highlights several critical factors associated with ASD, including gender differences, activity levels, parental age, and maternal stress during pregnancy. These findings provide valuable insights into potential risk factors and behavioral characteristics of ASD, contributing to our understanding of the condition and informing future research and interventions.
Gender Differences in ASD and Non-ASD Populations
The analysis revealed a statistically significant gender difference between the ASD and non-ASD populations, with males being disproportionately affected by ASD (Table 2). OR = 3.45 indicates that males are 3.45 times more likely to have ASD compared to females in this dataset. This result is consistent with previous research showing that ASD is more prevalent among males than females, with estimated male-to-female ratios ranging from 3:1 to 4:1 (11, 12). While the underlying mechanisms for this gender difference in incidence of ASD remain unclear, genetic, hormonal, or neurodevelopmental differences may contribute to the increased susceptibility of males to ASD. Further investigations on these biological and environmental factors can help gain insight into the mechanisms underlying the development of ASD (11, 12). While the underlying mechanisms for this gender difference in incidence of ASD remain unclear, genetic, hormonal, or neurodevelopmental differences may contribute to the increased susceptibility of males to ASD. Further investigations on these biological and environmental factors can help gain insight into the mechanisms underlying the development of ASD.
Activity Levels in ASD and Non-ASD Groups
The comparison of daily activity levels (Figure 2) demonstrated that children with ASD exhibit significantly lower activity levels compared to their non-ASD peers. Reduced activity levels in ASD populations may reflect impairments in motor skills, social engagement, or cognitive flexibility. These findings are consistent with prior studies (13) showing that children with ASD often face challenges in initiating or maintaining physical activities, which could also impact their overall health and well-being. These findings are consistent with prior studies (14) showing that children with ASD often face challenges in initiating or maintaining physical activities, which could also impact their overall health and well-being. Interventions aimed at improving physical activity levels in ASD children, such as tailored exercise programs or play-based therapies, could be beneficial in enhancing their quality of life and social interactions.
Correlation Between Parental Age and ASD
Figure 2 highlights the relationship between parental age and ASD incidence. Paternal age shows significant correlations with ASD development. Fathers of ASD children were older compared to those of non-ASD children. Advanced parental age has been previously linked to increased risk for ASD (15), potentially due to age-related genetic mutations (e.g., de novo mutations) or epigenetic changes. These findings underscore the importance of considering parental age as a risk factor in future epidemiological studies.
Maternal Stress Levels During Pregnancy are associated with ASD Development
Our data show that elevated maternal stress during pregnancy was associated with ASD development in children. These results support the hypothesis that prenatal stress contributes to neurodevelopmental alterations linked to ASD, potentially through stress-induced dysregulation of maternal cortisol or inflammatory pathways (15). Such dysregulation could impair fetal brain development, highlighting the importance of stress-reduction strategies during pregnancy as a potential preventative measure.
Study Limitations
Despite these significant findings, our study has several limitations that warrant discussion. First, the small sample size limits the generalizability of the results and the statistical power to detect smaller effects. Future studies using larger, more diverse cohorts are needed to validate these findings. Second, the reliance on self-reported questionnaires introduces potential biases, including recall bias and reporting inaccuracies. Objective measures of maternal stress, activity levels, and socioeconomic factors would strengthen the study’s robustness. Also, confounding factors such as socioeconomic status, education level, nutrition, substance use during pregnancy, and maternal mental health history were not explicitly examined but may interact with parental age and maternal stress to influence ASD risk. Future studies should incorporate these variables to provide a more holistic understanding of ASD pathogenesis.
Implications for Public Health and Interventions. The findings have important implications for prenatal care and public health strategies: 1) Public health campaigns should raise awareness about the risks associated with advanced paternal age and maternal stress, encouraging proactive planning and support. 2) Prenatal care programs should integrate stress-reduction interventions, such as mindfulness therapies, emotional support, and lifestyle counseling, to mitigate maternal stress. 3) Addressing additional prenatal factors, such as maternal nutrition and substance use, could improve outcomes for at-risk pregnancies.
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CONCLUSIONS |
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This study identifies significant associations between gender, parental age, maternal stress, activity levels, and ASD development. Understanding these risk factors advances our knowledge of ASD etiology and lays the groundwork for targeted prevention and intervention strategies. Emphasizing early parental education, prenatal care, and supportive therapies is critical for mitigating the impact of ASD on affected individuals and their families.
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ABBREVIATIONS |
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| ASD | autism spectrum disorder |
| IRB | Institutional Review Board |
| ADHD | attention-deficit/hyperactivity disorder |
| IQR | interquartile range |
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DECLARATIONS |
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Ethics approval and consent to participate.
The studies were reviewed and approved by the University of Southern California Institutional Review Board (IRB approval ID: UP-24-00954). The participants provided their written informed consent to participate in this study. This study adheres to CONSORT guidelines.
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CONSENT FOR PUBLICATION |
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Not applicable.
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COMPETING INTERESTS |
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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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AUTHOR CONTRIBUTIONS |
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K.L discussed the survey design and collected data.
HY. M. analyzed data and wrote manuscript.
X.L. analyzed data and wrote manuscript.
S.R. created Google questionnaires and wrote manuscript.
J.C. wrote manuscript.
A.S.S. worked on protocol, hypothesized, designed, statistical analyses and wrote manuscript.
J.L. worked on IRB application and protocol, hypothesized, designed, and organized data analysis, statistical analyses; and wrote manuscript.
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ACKNOWLEDGEMENTS |
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We would like to thank Dr. Tie Ng, PharmD., Chair and Professor of the Titus Family Department of Clinical Pharmacy, for his advice on IRBs and human trials.
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AVAILABILITY OF DATA AND MATERIALS |
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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FUNDING |
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This work was supported by the funding of USC School of Pharmacy.
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REFERENCES |
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