ASD is a complex lifelong developmental incapability that causes a burden to affected kids and their families. Early detection and early intervention of this problem lead to a better prognosis with fewer burdens on the family. So, our research aimed to detect preschool children in Sharika Governorate who have a high risk for ASD to assess prevalence and risk factors of ASD among them.
In this study, the sex distribution of the studied subjects in the screening phase was 50.7% males and 49.3% females. That is similar to the sex distribution in a cross-sectional study performed in Lebanon to assess the prevalence of ASD in kindergartens toddlers in Beirut and Mount-Lebanon [15].
Our results showed that 2.8% of children assessed using M-CHAT-R during the screening phase were at high risk for ASD, which is in line with the cross-sectional descriptive study of Moussa S and his colleagues, who found that 2% of children showed an increased risk for ASD [13].
However, this was different from a study that was conducted in India to screen children aged 16–30 months for ASD using M-CHAT-R, and to find an association between maternal, birth, and postnatal risk factors of ASD, and found that 9.4% of children were at high risk for ASD [16]. This difference could be explained by the difference in the locality and age group of research participants.
In our study, the mean score on CARS used in the diagnostic phase was 22.73 (SD = 6.99) with a range of 16-43. That was not consistent with the study of Reszka S and colleagues, which performed in the USA and showed that the CARS mean score was 33.37 (SD = 7.31) with a range of 15–55.5. This difference may be attributed to the difference in purpose and sampling technique. In our study, CARS was used for diagnosis of ASD among the high-risk children, with more than 80% of them were non-autistic (score < 30), while in the American study, most of the children were autistic (score > 30) [17].
Our study showed that 65% of autistic children were mild to moderate ASD, and 35% were severe ASD. That was comparable in Saudi Arabia, where 66.7% of autistic children had mild to moderate ASD, and 33.3% had severe ASD [18].
An Egyptian study found that 43% of cases had mild to moderate degree of ASD, and 57% of them had a severe degree of ASD [19], also different from our study, a study in Rome, Italy, where 44% of autistic children were with mild to moderate ASD, and 56% of them were with severe ASD [20]. Those differences were because of the variations in methodology and age groups studied.
In this research, 20 out of 3722 children were diagnosed with ASD using the research diagnostic criteria of DSM-5 and CARS which means Sharkia Governorate ASD prevalence was 5.4/1000 children. The estimated global prevalence was 7.6 per 1000, according to the systematic review [21].
In the United Arab Emirates, it was 2.9/1000 [22], and in Oman, it was 0.14/1000 [21]. In the UK, the prevalence of ASD was 1.1% [22], and in the USA, it was 2.24% [7].
The differences in localities could explain the difference in the prevalence rates of ASD. Diagnosing autism is more common to clinicians in developed countries. Mental health services for autistic children are more available, and families often are more aware of the disorder. These aspects make the diagnosis of ASD more convenient in developed countries than in developing ones. Also, the time difference between this study and the older studies might be responsible for the different prevalence rates. There was an increasing prevalence rate of ASD over the last decade. Additionally, the wide age group interval included in the American study (3-17 years) in comparison to the limited age group interval of this study (2-5 years) was responsible for the prevalence difference from that of American studies.
In our study, most autistic children (80%) diagnosed by the research diagnostic criteria of DSM-5 and CARS were from 4 to 5 years old, which was in line with Iranian research results [23]. In which ASD patients detected mainly were males (75%). That was similar to the studies in the USA, which found that 75% of children having ASD were males [7] and also with that one which was conducted in Oman to determine ASD prevalence among 0–14 years subjects and found that ASD was more prevalent among boys (75%) [21]. It was different from the Lebanese study, which found that male: female ratio was 1.05 in Beirut and 1.2 in Mount Lebanon.
This difference might be due to the small sample size of that Lebanese study and the age group difference between the two studies [15]. Ninety percent of mothers of autistic children were university graduates in comparison to 49.4% of non-autistic children, and this difference was statistically significant. That is consistent with the research undertaken in Saudi Arabia to establish potential risk factors for autism and found a statistically significant disparity between the autistic patients and the control group in mothers’ university education [18]. That was also consistent with the study conducted in Assiut City in Egypt to recognize the risk factors for ASD and found that 61.7% of mothers of autistic children had a university level of education [24].
Our results also showed a statistically significant association between ASD and the presence of factories near the house. We used a proximity method to classify the existence of the child’s home from factories with industries that could emit air pollutants and toxins to be near or not. The proximity approach is widely used in many influential environmental epidemiology studies [25,26,27,28]. In addition, this method is used frequently in many environmental investigation studies such as in the environmental impact assessment and environmental justice studies [25]. The threshold distance used in the studies assessing the effects of air pollutant industrial complex was up to 20 km [25]. To determine the most appropriate definition of the minimum distance for exposure, we reviewed several examples of international housing policies upon that we considered that if the distance of the child home from the factory is > 20 km so it is not near the home and if the distance is ≤ 20 km, so the home of the child is near the factory. Factories were sources of air pollution leading to perinatal exposure of those children to the hazardous chemicals and fumes emitted from those factories. That was consistent with the research performed in the USA to examine the theory that perinatal air pollutants exposure is correlated with ASD [29].
In our study, a statistical difference between autistic and non-autistic children in birth orders where 40% of autistic children were first born while 50% were of middle birth order. That was inconsistent with the finding of the meta-analysis study of Gardener and his colleagues that aimed at providing the first quantitative review and meta-analysis of the association between maternal pregnancy complications, and pregnancy-related factors, and risk of Autism, and found that being firstborn versus third or later was significantly increased autism risk [5]. That was also inconsistent with the finding of the other meta-analysis study that aimed at identifying pre-, peri-, and neonatal risk factors for pervasive developmental disorders (PDD), including autism and found that being firstborn was significantly associated with risk ASD [30].
This difference might be due to the difference in locality and population characteristics, as all the studies included in the meta-analysis of both studies were from developed foreign countries. This study showed a statistically significant association between ASD and artificial feeding and early weaning. This was consistent with the Indian study, which showed that delayed initiation of breastfeeding was significantly associated with the risk of ASD. In contrast, exclusive breastfeeding in the first 6 months of life was associated with decreased risk [16]. The systematic review study in Arab Gulf countries findings found that delayed breastfeeding and no colostrum ingestion were linked to a higher risk of autism. Extended breastfeeding (up to 24 months) significantly decreased the likelihood of developing it [31].
In this study, 60% of autistic children consumed artificial, preserved, and canned food in comparison to 13.1% of non-autistic, and this difference was statistically significant. That was consistent with a study conducted in Turkey to examine the connection between ASD development and exposure to MEHP, DEHP, and BPA which are used in some food like meat products and canned beef, also in drink packaging, and to coat metal products such as food cans and bottle tops. This Turkish study found that autistic children showed elevated serum MEHP, DEHP, and BPA levels. Significantly, compared to healthy control subjects, they might play a part in autism spectrum disorder pathogenesis [32].
Our results showed a significant increase in congenital anomalies in autistic children compared to non-autistic children. This finding is similar to that of the meta-analysis study that aimed at providing the first review and meta-analysis of the correlation between perinatal and neonatal factors and autism risk and found that congenital deformities have been linked with the risk of ASD [6].
Our results showed that chronic medical conditions (mainly epilepsy) and GIT troubles were significantly correlated with autism in the affected children, consistent with the study in Iran, which showed that ADHD and epileptic disorders were the leading comorbidities [33]. And also, an American study showed that functional constipation was the most prevalent form of GID in autistic children (85.0%), GID was not correlated with specific feeding habits or medical status in children with ASD, and the likelihood of constipation was associated with younger age, more social impairment, and lack of expressive language [34]..
This study showed a statistically significant difference between autistic and non-autistic children in the duration of watching TV and attachment to TV. The mean time spent in TV watching by the ASD cases was more than 6 h per day, and 60% of those autistic children were firmly attached to a TV compared to only 2.4% of non-autistic. These findings were consistent with the study conducted in Bangladesh to clarify the association between risk and autism for families, communities, and the environment. They found that the diagnosis of autism is closely connected to excessive watching of TV and the insufficient ability to social interaction and poor contact with family members in early childhood [35].
Also, in agreement with these findings, the study conducted in Thailand to analyze the level and degree of television consumption in children with ASD relative to typically developed subjects identified a greater incidence of television viewing in autistic children than children with typical development. And that there was an early initiation of TV exposure in autistic children compared to children with typical developments [36].
We found a statistically significant delay in language, early cognitive, social, and psychological development among children with ASD in our study. On the other hand, there was no statistically significant delay in motor development. That was similar to the Saudi study findings that did not show a significant difference between cases and controls in motor mil-stones (sitting and walking) [18].
Meanwhile, we found a statistically significant difference between autistic children and the control group in delayed language development and mother recognition. That was inconsistent with the Egyptian study; El-Baz F and his colleagues examined the potential risk factors of autism and found that all the developmental milestones analyzed were delayed in the autistic children than the control group [19]. This difference might be because 55% of autistic patients in that study had an intellectual disability, while those with intellectual disability were excluded from our research.
The Egyptian study of El-Baz F and his colleagues also showed a statistically significant difference for autistic children and controls in the elevated maternal age (mother = 35 years) at birth, advanced parent age (father = 35 years) at birth, and positive family history of autism [19] that was in contrast to the results of our study which showed no differences. This difference might be due to the methodological difference between the two studies.
Our study showed a statistically significant increase in the maternal consumption of artificial, preserved, and canned food during pregnancy among the mothers of autistic children (65%) compared to (36.9%) mothers of non-autistic, consistent with the study of De Cock M and his colleagues which was conducted to provide a review of research on perinatal human sensitivity to endocrine disrupting chemicals (EDCs) in relation to ASD and ADHD and identified significant correlations between ASD and the exposure to the examined chemicals, including toxic air contaminants, pesticides, and bisphenol [37].
We found a statistically significant difference between autistic and non-autistic children in the presence of a history of chronic medical condition during pregnancy where 35% of autistic children had a history of maternal hypertension with pregnancy, and 15% had a history of maternal celiac disease. This was in line with the findings of the research of Walker Ch and his colleagues in the USA, which found that preeclampsia was associated with the development of ASD [38], and in Denmark, a study of Atladóttir HO1 and his colleagues found that maternal history of rheumatoid arthritis and celiac disease elevated the like hood of developing autism [39].
In our study, 10% of autistic children had a family history of psychiatric disorders than 0% of non-autistic children, which was statistically significant. This is similar to the study of Alsulaimani A and his colleagues in Saudi Arabia [18].
The statistically significant risk factors for ASD among the studied group by using binary logistic regression analysis were the presence of factories near the house, first and middle child order, congenital anomalies, child medication during the first year of life, chronic medical condition of child, child attachment to TV, medical condition affecting mother during pregnancy, and psychiatric disorders history in the family.
The statistically significant risk factors for ASD in that Saudi study were the older age of the fathers, positive family history of the psychiatric disorder including autism, history of maternal diabetes mellitus, and the mother’s exposure to stress during pregnancy. Also, Gardener H and his colleagues in their meta-analysis research revealed that advanced paternal age at birth, maternal prenatal medication usage, gestational diabetes, bleeding, and firstborn were associated with ASD risk were [6].
Our present study had some limitations; first, we included only the children with high risk for ASD in the diagnostic phase due to limited time and resources. Second, the preschool children who go to kindergartens were only included in this study without including household preschoolers. This study did not include those younger than two years of age. Third, The MCHAT-R has a high false-positive rate. Fourth, the risk factors assessment questionnaires included items that were very subjective like the attachment to TV. Fifth, the nonresponse rate was increased by about 40% due to the refusal of many parents to participate in the study, refusal of some school managers to perform the study on their children, illiteracy and low educational level of many parents, and neglect of some parents to fill in the checklist. Some parents refused to complete the second diagnostic phase of the study, causing some dropouts among the high-risk group, and we excluded them from the second diagnostic phase’s statistical analysis. This might be attributed to the fear of stigma perceived by some parents if their children were diagnosed with ASD and the feeling of some parents that the study was not useful for them.