Abstract
BACKGROUND:
Autism is a group of developmental disorders of the nervous system, the main manifestations of which are defects in social interactions and communication, as well as repetitive behaviors and limited interests. The etiology of autism is not limited to a single factor. Therefore, the aim of this study was to compare the relationship between pregnancy and childbirth factors and autism in healthy children and children with autism.
MATERIALS AND METHODS:
The present study was a cross-sectional study that was performed on 200 children in Isfahan in 2021. The instrument in this study was a researcher-made questionnaire. The collected data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 22 software.
RESULTS:
The results of data analysis between the two groups with Mann–Whitney U test showed that there was a significant relationship between maternal age at delivery, father's age at delivery, gestational age at delivery, interval between pregnancies, and the length of hospital stay (P ≤ 0.05). Also, the results of data analysis with Chi-squared test showed that there is a significant relationship between the two groups in terms of economic status, place of residence, multiple pregnancies, neonatal sex, and disease in infancy (P ≤ 0.05).
CONCLUSION:
The results of this study showed that economic status, place of residence, multiple pregnancies, sex of the baby, and disease in infancy can be effective factors for this disease. According to the results of the study, by considering the factors related to autism, many cases can be adjusted and corrected as much as possible before attempting to conceive.
Keywords: Autism, children, children's health, developmental neurological disorders
Introduction
Autism spectrum disorder (ASD) is a group of developmental disorders of the nervous system, the main manifestations of which are defects in social interactions and communication, as well as the presence of repetitive behaviors and limited interests.[1] Autistic children also have delayed motor skills. Delays in motor abilities in autistic children are varied and include delays in sitting, crawling, and walking, as well as abnormal gait, poor posture control, and inability to plan movement.[2] The main manifestations of social deficits in autism include poor eye communication, lack of emotion or social interaction, deficits in the use of non-verbal behaviors, and lack of age-appropriate communication.[3] Its diagnostic criteria are based on the Fifth Diagnostic and Statistical Manual of Mental Disorders as a persistent lack of communication and social interactions in different situations and patterns of limited interests, behaviors, and repetitive activities in the present or past and early development.[4,5,6] The exact pathophysiology of ASD is unclear due to the frequency and dispersion of the mechanisms involved.[7,8] The results show that the etiology of ASD is not only due to a single factor, but is also due to environmental, genetic, or a combination of both risk factors in the etiology of ASD.[9,10,11] The long course of this disorder and their multiple needs provide a great economic burden for families and society, most of which is spent on special education and treatment.[12] This has posed many challenges in terms of care and management.[11,12] A wide range of demographic causes and factors, including factors of pregnancy, psychological, social, hereditary, and environmental factors are involved in its occurrence.[13] According to studies, mothers under the age of 20 and mothers over the age of 35 are more likely than women between the ages of 20 and 29 to give birth to underweight babies, which is directly related to developmental disorders and, of course, autism. Short intervals between births increase the likelihood of preterm delivery. Premature infants are more prone to developmental delays in their early childhood and school years. The incidence of preterm labor has increased significantly in recent decades.[14] Birth weight is an important indicator of pediatric disability and infant mortality, and this incomplete weight gain itself can be a cause of short pregnancy intervals. The rate of these disabilities is higher in boys than in girls. Progression towards developmental disorders in infants weighing less than 2 kg is 30 times that of normal weight infants.[15] According to the World Health Organization (WHO) standards, a short interval between deliveries refers to a pregnancy of less than 18 months and a long interval to more than 60 months.[16] Lack of awareness of mothers about the consequences of not observing the appropriate distance between births endangers the health and efficiency of women in society and with the birth of children who may have developmental problems, the health of the next generation is also threatened.[17] Studies have shown a strong association between a reduction in gestational age of less than 18 months and an increase in gestational age of more than 60 months with a child with autism as well as other developmental disorders.[18,19,20,21] Children with developmental neurological disorders pose a great psychological and economic burden on the family and ultimately society. In the long run, due to their cognitive weakness, they have a negative effect on the growth of culture, art and science of a country. Therefore, the aim of this study was to compare the relationship between pregnancy and childbirth factors and autism in healthy children and children with autism.
Materials and Method
Study design and setting
The present study is a correlational study that was conducted on households covered by Isfahan Autism Center and Farvardin Center that have at least two children, one of whom has autism by convenience sampling method.
Study participants and sampling
The sample size was 200 based on the following formula (100 children with autism and 100 healthy children).
n = z (1-α/2) 2 × p (1-p)/d2
Inclusion criteria were the following: those who gave written consent to participate in the study; those who were Iranian; parents being of reproductive age (mother 18–35 years and father 18–55 years); parents who did not have a child with a disease other than autism, those who did not have children from previous marriages of each couple, those who did not adopt children; absence of medical illness of parents in the period immediately before pregnancy and during pregnancy; children who were not born prematurely and whose weight was not too high or too low; couples who were non-smoking and not addicted to alcohol, drugs, and psychotropics; households with at least two children, eventually 8 years old. In the first group, all children were healthy and in the second group, at least one child had ASD.
Data collection tool and technique
This study was conducted in primary schools for healthy children and autism education centers (Ordibehesht, Hazrat Zahra, Hazrat Zeinab) in Isfahan province. This research was conducted after obtaining the necessary permits and obtaining parental consent and explaining the working method to parents.
The instrument in this study was a researcher-made questionnaire that had three parts (the first and second part of the researcher-made questionnaire, the third part of the autism diagnostic interview-revised (ADI-R) International Questionnaire for families with autistic children). The first part consisted of demographic information of the research units (6 questions). The second part consisted of information about pregnancy, delivery, and delivery intervals (11 questions). To confirm the validity of the first and second parts of the questionnaire, face and content validity were used. The third part of the questionnaire was taken from the ADI-R International Questionnaire. This questionnaire was completed in the form of an interview and assessed the child's skills based on the three sections of communication and language skills of the child, social interactions of the child, and repetitive behaviors or other different behaviors. The validity and reliability of this questionnaire have been confirmed in a study by Gorji et al.[20] In this study, the reliability of the retest and alpha test was confirmed to be 0.79.
After completing the questionnaires, the data were coded and entered into the Statistical Package for the Social Sciences (SPSS) version 22 software and analyzed.
Ethical considerations
This study was conducted after the approval of the plan in the Student Research Committee of Isfahan University of Medical Sciences and receiving the code of ethics from the Vice Chancellor for Research of Isfahan University of Medical Sciences. Written consent was obtained from all participants. All study participants were assured that their information would be kept confidential.
Results
In the non-autism group, mean maternal age was 30.80 ± 5.07 years, mean paternal age was 36.12 ± 5.76 years, gestational age at delivery was 37.60 ± 1.76 weeks, gestational age was 1.85 ± 4.18 years, and hospital stay was 3.52 ± 1.23 days. In the autism group, mean mothers’ age was 28.28 ± 5.07 years, mean fathers’ age was 32.48 ± 5.56 years, gestational age at delivery was 38.60 ± 1.73 weeks, gestational age was 2.53 ± 3.44 years, and hospital stay was 2.84 ± 10.34 days.
The results of data analysis between the two groups using Mann–Whitney U test showed that there was a significant relationship between mother's age at delivery, father's age at delivery, gestational age at delivery, interval between pregnancies, and length of hospital stay (P ≤ 0.05) [Table 1].
Table 1.
Comparison of quantitative variables in two groups of children with autism and non-autism
| Variables | Levine test | Significance level | t | df | P |
|---|---|---|---|---|---|
| Mother’s age at delivery | 0.003 | 0.959 | −2.482 | 98 | 0.015 |
| Father’s age at delivery | 0.015 | 0.902 | −3.211 | 98 | 0.002 |
| Gestational age at delivery | 0.038 | 0.845 | 2.396 | 98 | 0.018 |
| The interval between pregnancies | 4.497 | 0.036 | −1.665 | 98 | 0.099 |
| Duration of hospitalization | 2.355 | 0.492 | 1.845 | 98 | 0.001 |
Also, the results of data analysis with Chi-squared test showed that there was a significant relationship between the two groups in terms of economic status, place of residence, multiple pregnancies, neonatal sex, and disease in infancy (P ≤ 0.05) [Table 2].
Table 2.
Evaluation and comparison of qualitative variables in two groups of children with autism and non-autism
| Variable | Autism | Non-autism | Chi-squared test | P |
|---|---|---|---|---|
| Mother’s education | ||||
| Primary school | 2 | 1 | 1.961 | 0.580 |
| High school | 4 | 7 | ||
| Diploma | 21 | 24 | ||
| University | 23 | 18 | ||
| Father’s education | ||||
| Primary school | 5 | 8 | 2.102 | 0.452 |
| High school | 10 | 15 | ||
| Diploma | 20 | 16 | ||
| University | 13 | 11 | ||
| Mother’s job | ||||
| Housewife | 40 | 29 | 1.279 | 0.734 |
| Official | 7 | 8 | ||
| Free | 1 | 0 | ||
| Other | 2 | 3 | ||
| Father’s job | ||||
| Official | 10 | 12 | 2.441 | 0.295 |
| Free | 10 | 18 | ||
| Manual worker | 17 | 7 | ||
| Unemployed | 13 | 13 | ||
| Economic situation | ||||
| Good | 8 | 8 | 5.974 | 0.05 |
| Medium | 29 | 38 | ||
| Bad | 13 | 4 | ||
| Place of living | ||||
| Personal | 17 | 30 | 6.784 | 0.009 |
| Rent | 33 | 20 | ||
| How many pregnancies | ||||
| 1 | 10 | 2 | 12.829 | 0.012 |
| 2 | 31 | 29 | ||
| 3 | 9 | 12 | ||
| 4 | 0 | 5 | ||
| 5 | 0 | 2 | ||
| Gender of the baby | ||||
| Boy | 35 | 21 | 7.955 | 0.005 |
| Girl | 15 | 29 | ||
| Method of childbirth | ||||
| Natural childbirth | 19 | 21 | 0.167 | 0.683 |
| Cesarean section | 21 | 29 | ||
| Disease in pregnancy | ||||
| Diabetes | 2 | 3 | 3.420 | 0.331 |
| Blood pressure | 5 | 4 | ||
| Hyperthyroidism - hypothyroidism | 0 | 3 | ||
| No disease | 43 | 40 | ||
| Supplementation during pregnancy | ||||
| Yes | 44 | 47 | 1.099 | 0.295 |
| No | 6 | 3 | ||
| Infantile disease | ||||
| Yes | 17 | 7 | 1.084 | 0.001 |
| No | 33 | 43 | ||
| Mother’s education | ||||
| Primary school | 2 | 1 | 1.961 | 0.580 |
| high school | 4 | 7 | ||
| Diploma | 21 | 24 | ||
| University | 23 | 18 | ||
| Father’s education | ||||
| Primary school | 5 | 8 | 2.102 | 0.452 |
| High school | 10 | 15 | ||
| Diploma | 20 | 16 | ||
| University | 13 | 11 | ||
| Mother’s job | ||||
| Housewife | 40 | 29 | 1.279 | 0.734 |
| Official | 7 | 8 | ||
| Free | 1 | 0 | ||
| Other | 2 | 3 | ||
| Father’s job | ||||
| Official | 10 | 12 | 2.441 | 0.295 |
| Free | 10 | 18 | ||
| Manual worker | 17 | 7 | ||
| Unemployed | 13 | 13 | ||
| The economic | ||||
| Good | 8 | 8 | 5.974 | 0.05 |
| Medium | 29 | 38 | ||
| Bad | 13 | 4 | ||
| Situation place of living | ||||
| Personal | 17 | 30 | 6.784 | 0.009 |
| Rent | 33 | 20 | ||
| How many pregnancies | ||||
| 1 | 10 | 2 | 12.829 | 0.012 |
| 2 | 31 | 29 | ||
| 3 | 9 | 12 | ||
| 4 | 0 | 5 | ||
| 5 | 0 | 2 | ||
| Gender of the baby | ||||
| Boy | 35 | 21 | 7.955 | 0.005 |
| Girl | 15 | 29 | ||
| Method of childbirth | ||||
| Natural childbirth | 19 | 21 | 0.167 | 0.683 |
| Cesarean section | 21 | 29 | ||
| Disease in pregnancy | ||||
| Diabetes | 2 | 3 | 3.420 | 0.331 |
| Blood pressure | 5 | 4 | ||
| Hyperthyroidism - hypothyroidism | 0 | 3 | ||
| No disease | 43 | 40 | ||
| Supplementation during pregnancy | ||||
| Yes | 44 | 47 | 1.099 | 0.295 |
| No | 6 | 3 | ||
| Infantile disease | ||||
| Yes | 17 | 7 | 1.084 | 0.001 |
Discussion
The results show that there was a significant difference between the variables of mother's age at delivery, father's age at delivery, gestational age at delivery, interval between pregnancies, and length of hospital stay. The results also showed that there was a significant difference between the two groups in terms of economic status, place of residence, multiple pregnancies, neonatal sex, and disease in infancy. In this regard, the results of the study by Toomaroglu et al.[14] showed that family history, the child's gender, parental age, stressful pregnancy, and maternal exposure to high-risk substances are among the factors associated with autism. The study by Fernandez Carrocera et al.[15] showed that developmental disorders were significantly associated with days of artificial respiration and days of hospitalization in the neonatal intensive care unit (NICU) and gestational age. The results of a study by Laura Schieve et al.[22] showed that ASD increased in the second and subsequent children who became pregnant less than 18 months or 60 months or more after the mother's previous birth. Also, the results of the study by Soleimani et al.[23] showed that high-risk infants and children and those who were born earlier need special attention in order to have a favorable and appropriate development. These children are more likely than other children to have developmental or developmental delays, including motor, cognitive, speech, hearing, and visual impairments. To prevent this, it is necessary to prevent delays or developmental disorders by detecting their problems early using appropriate assessment tools and timely interventions. The results of a study by Carlsson et al.[24] showed that low birth weight, birth defects, and congenital hypoxia and respiratory stress with autism spectrum disorder (ASD) and gestational age and family income were associated with attention-deficit/hyperactivity disorder (ADHD). The results of a study by Chen et al.[25] showed that variability in the rate of mental retardation, ADHD, and autism among children in Taiwan depends on age, year of birth, period, and socioeconomic status. The relationship between age and the first diagnosis of mental retardation varies at different levels of urbanization and socioeconomic status. The results of the study by Namazzi et al.[26] showed that low birth weight and immediate and exclusive breastfeeding were not significantly associated with developmental neurological disorders. The results of the study by Nawaz et al.[27] showed that high birth weight and preterm delivery were significantly associated with developmental and neurological disorders. According to the results, it can be said that since the studies have been performed on different groups of children and infants, the cultural, social, and economic level of individuals some of the factors that affect birth weight. Contradictory results can be justified. However, inconsistent with the results of the present study, a study of Soltani et al.[13] showed that developmental disorders in children aged 4–24 months were not significantly associated with mechanical ventilation, length of hospital stay, surfactant and betamethasone injections, and initial and final diagnosis of diseases. Also, there was no significant relationship with high-risk delivery and advanced resuscitation in children with developmental disorders and healthy children.
Limitation and recommendation
This study investigated the factors of pregnancy and childbirth related to autism and did not examine the cultural, social, and medical factors of the parents. Several other factors such as folic acid supplementation, folic acid levels in early pregnancy, and inflammatory diseases in pregnancy were not considered.
Conclusion
According to the results of this study, a number of demographic variables and pregnancy and childbirth were significantly different between the two groups.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Isfahan University of Medical Science.
Conflicts of interest
There are no conflicts of interest.
Acknowledgements
This study is the result of a research project approved by Isfahan University of Medical Sciences. For this purpose, the Vice Chancellor for Research of Isfahan University of Medical Sciences is appreciated and thanked.
References
- 1.Liu J, Yao L, Zhang W, Xiao Y, Liu L, Gao X. Gray matter abnormalities in pediatric autism spectrum disorder: A meta-analysis with signed differential mapping. Euro Child Adole Psych. 2017;26:933–45. doi: 10.1007/s00787-017-0964-4. [DOI] [PubMed] [Google Scholar]
- 2.MacDonald M, Hatfield B, Twardzik E. Child behaviors of young children with autism spectrum disorder across play settings. Adapted Physic Activ Quart. 2017;34:19–32. doi: 10.1123/APAQ.2016-0028. [DOI] [PubMed] [Google Scholar]
- 3.Guo X, Duan X, Long Z, Chen H, Wang Y, Zheng J. Decreased amygdala functional connectivity in adolescents with autism: A resting-state fMRI study. Psychiatry Res Neuroimaging. 2016;257:47–56. doi: 10.1016/j.pscychresns.2016.10.005. [DOI] [PubMed] [Google Scholar]
- 4.Charoghchian Khorasani E, Peyman N, Esmaily H. Effect of education based on the theory of self-efficacy and health literacy strategies on exclusive breastfeeding: A randomized clinical trial. Koomesh. 2019;21:633–8. [Google Scholar]
- 5.Murphy R. SPICe Briefing: Autism Spectrum Disorder. Edinburgh: Scottish Parliament Information Centre; 2017. [Google Scholar]
- 6.Jiujias M, Kelley E, Hall L. Restricted, repetitive behaviors in autism spectrum disorder and obsessive–compulsive disorder: A comparative review. Child Psych Human Develop. 2017;48:944–59. doi: 10.1007/s10578-017-0717-0. [DOI] [PubMed] [Google Scholar]
- 7.Gross C. Defective phosphoinositide metabolism in autism. J Neuro Res. 2017;95:1161–73. doi: 10.1002/jnr.23797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Zhang R, Zhang HF, Han JS, Han SP. Genes related to oxytocin and arginine-vasopressin pathways: Associations with autism spectrum disorders. Neuro Bull. 2017;33:238–46. doi: 10.1007/s12264-017-0120-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ronemus M, Iossifov I, Levy D, Wigler M. The role of de novo mutations in the genetics of autism spectrum disorders. Nature Rev Gene. 2014;15:133–41. doi: 10.1038/nrg3585. [DOI] [PubMed] [Google Scholar]
- 10.Olsson NC. Social Skills Group Training for Children and Adolescents with Autism Spectrum Disorder. Sweden: Karolinska Institutet; 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Mokhtari B, Karimzadeh F. A review on the Authism with the most approach on the critical biomarkers. Razi J Med Sci. 2018;24:35–46. [Google Scholar]
- 12.Ramshini M, Hasanzadeh S, Afroz GA, Hashemi Razini H. The effect of family-centered nature therapy on children with autism spectrum disorder. Arch Rehabil. 2018;19:150–9. [Google Scholar]
- 13.Soltani M, Razavi Ardekani SM, Erami A, Eskandari Kootahi Z, Yazdani N. Study of factors associated with developmental delay in low birth weight infants admitted to the neonatal intensive care unit. Razi J Med Sci. 2017;24:1–9. [Google Scholar]
- 14.Toomaroglu KH, Nobakht M. Causes and causes of autism in Ardabil. The 1st National Conference of the Future School. 2019 [Google Scholar]
- 15.Fernandez Carrocera LA, Jonguitud Aguilar A, Ortigosa Corona E, Barrera Reyes RH, Martinez Cruz C, Ibarra Reyes MP. Neurologic development of children at age two who had been treated at a neonatal intensive care unit. Rev Panam Salud Publica. 1999;5:29–35. doi: 10.1590/s1020-49891999000100005. [DOI] [PubMed] [Google Scholar]
- 16.Al-Naddawi M, Ibraheem MF, Alwan SH. Causes of global developmental delay in children welfare teaching hospital-Baghdad. Iraqi Postgrad Med J. 2013;12:383–9. [Google Scholar]
- 17.de Moura RD, Costa JC, Santos IS, Barros DAJ, Matijasevich A, Halpern R, et al. Risk factors for suspected developmental delay at age 2 years in a Brazilian birth cohort. Pediatr Perinat Epidemiol. 2010;24:211–21. doi: 10.1111/j.1365-3016.2010.01115.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.WHO_RHR_07.1_eng. pdf technical consultation on birth spacing. 2005 [Google Scholar]
- 19.Shachar B, Liell D, Lookwood CH, Barss V. Interpregnancy interval and obstetrical complications. Up To Date. 2018 doi: 10.1097/OGX.0b013e31826b2c3e. [DOI] [PubMed] [Google Scholar]
- 20.Gorji R, Hassanzadeh S, Ghasemzadeh S, Qolamali Lavasani M. Sensitivity and specificity gilliam autism rating scale (GARS) in diagnosis autism spectrum disorders: Systematic review. Shefaye Khatam. 2020;8:80–9. [Google Scholar]
- 21.Jafari A, Alami A, Charoghchian E, Delshad Noghabi A, Nejatian M. The impact of effective communication skills training on the status of marital burnout among married women. BMC Womens Health. 2021;21:231. doi: 10.1186/s12905-021-01372-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Schieve LA, Tian LH, Drews-Botsch C, Windham GC, Newschaffer C, Daniels JL, et al. Autism spectrum disorder and birth spacing: Findings from the study to explore early development (SEED) Autism Res. 2018;11:81–94. doi: 10.1002/aur.1887. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Soleimani F, Sharifi N, Rasti Borujeni F, Amiri M, Khazaiyan S, Fathnezhad Kazemi A. Nourodevelopmental follow-up in high-risk infants: Review article. Tehran Univ Med J. 2015;72:733–41. [Google Scholar]
- 24.Carlsson T, Molander F, Taylor MJ, Jonsson U, Bölte S. Early environmental risk factors for neurodevelopmental disorders-A systematic review of twin and sibling studies. Dev Psychopathol. 2021;33:1448–95. doi: 10.1017/S0954579420000620. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Chen CY, Liu CY, Su WC, Huang SL, Lin KM. Factors associated with the diagnosis of neurodevelopmental disorders: A population-based longitudinal study. Pediatrics. 2007;119:e435–43. doi: 10.1542/peds.2006-1477. [DOI] [PubMed] [Google Scholar]
- 26.Namazzi G, Hildenwall H, Mubiri P. Prevalence and associated factors of neurodevelopmental disability among infants in eastern Uganda: A population based study. BMC Pediatr. 2019:19.379. doi: 10.1186/s12887-019-1769-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Nawaz FA, Sultan MA. Low birth weight prevalence in children diagnosed with neurodevelopmental disorders in Dubai. Glob Pediatr Health. 2021 doi: 10.1177/2333794X211031782. doi: 10.1177/2333794X211031782. [DOI] [PMC free article] [PubMed] [Google Scholar]