Autism spectrum disorder: Comorbidity and demographics in a clinical sample

Abstract

Objective: To determine the demographic and clinical characteristics of children followed up with the diagnosis of autism spectrum disorder (ASD) at a tertiary center in Southeeast Turkey.

Methods: Children followed up with the diagnosis of ASD at a university hospital child psychiatry clinic between June 2016 and June 2021 were evaluated retrospectively for comorbidities, intellectual functioning and age at diagnosis.

Results: In the preschool group, females displayed significantly more frequent cognitive developmental delay. Median age at diagnosis was 36 months (IQR= 22) regardless of gender. Approximately three-fourth (73.7%) of the cases had at least one psychiatric comorbid disorder while 22.8% had at least one medical diagnosis. Psychiatric comorbidity was found to be associated with later diagnosis.

Conclusion: Although the age at first diagnosis in this study is relatively earlier than the studies in the literature, most of the children with ASD are still diagnosed very late. Psychiatric comorbidities may lead to later diagnosis due to overshadowing. Training of educational and primary healthcare workers on symptoms of ASD may enable earlier diagnosis.

Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with onset in early childhood characterized by problems in social communication—interaction, repetitive and restricted behaviors, interests, or activities along with sensory dysregulation (American Psychiatric Association 2013). Median global prevalence of ASD was reported as 1.0% (range = 0.01%–4.36%) while the US Centers for Disease Control and prevention estimated that one in 44 among eight years old children may have the diagnosis in 2018 (Maenner et al. 2021, Zeidan et al. 2022). Similar to other countries, children in Turkey are also being increasingly diagnosed with ASD, although literature on the prevalence of this condition is scant (Oner and Munir 2020).

ASD may be commoner among males with a global median ratio of 4.2:1 and female children with the diagnosis display more severe symptoms (Zeidan et al. 2022). Some authors suggest that female children with milder symptoms may be underdiagnosed due to their increased tendencies for imaginative play and emotional words, restricted interests focused on pets and celebrities and use of coping strategies such as mimicry in social interactions (Evans et al. 2019, Maenner et al. 2021, Nichols et al. 2009, Zeidan et al. 2022). Gender disparities may be reduced among children with ASD who have comorbid intellectual disability (ID, Evans et al. 2019, Nichols et al. 2009).

Globally, almost one third of children with ASD may have accompanying ID with similar rates in Turkey (Kilicaslan and Kutuk 2020, Zeidan et al. 2022). The effects of gender on ASD-ID comorbidity is controversial with some studies reporting greater cognitive impairment among female children while others report similar rates of ID across genders (Katusic et al. 2021, Maenner et al. 2021, Zeidan et al. 2022). Earlier age at diagnosis and intervention is known to be related with better prognosis (Mukaddes et al. 2017). Although ASD can be reliably diagnosed as early as two years old, most children are still being diagnosed after four years of age (Maenner et al. 2021).

Early diagnosis and intervention significantly affect the child's prognosis (Mukaddes and Tanıdır 2015). Although a subset of children with ASD may have hyperserotonemia and macrocephaly which may be prominent in early childhood, the diagnosis is still based on careful examination of the child along with developmental history (Cabana-Domínguez et al. 2022, Cummings et al. 2022).

ASD among children increases risks for other neurodevelopmental and/or psychiatric disorders as well as early mortality and those complications increase treatment costs as well as caregiver demands (Bougeard et al. 2021, Hawks and Constantino 2020, Jokiranta-Olkoniemi et al. 2021). Among clinical populations, 70.0%–96.0% of individuals with ASD may have at least one comorbid psychiatric condition (Hawks and Constantino 2020). The most common comorbidities may consist of attention deficit hyperactivity disorder (ADHD, up to 86.0%), anxiety (AD, up to 82.2%), depressive disorders (up to 74.8%), ID (up to 91.7%), sleep disorders (SD, up to 72.5%, Bougeard et al. 2021). Gender may affect some of the comorbidities with ADHD being commoner among males while developmental levels may affect others (i.e., depression rates may rise after adolescence, Bougeard et al. 2021). Regardless of age and gender, it is important to screen for those comorbidities among individuals with ASD in order to develop appropriate treatment strategies and increase the quality of life of these individuals as well as their parents (Hawks and Constantino 2020).

Neurological/medical disorders and genetic syndromes as well as inborn errors of metabolism are also elevated among youth with ASD (Bougeard et al. 2021, Manoli and State 2021, Pan et al. 2021). Most common problems reported were epilepsy (up to 77.5%), vision—auditory problems (up to 14.9%) and gastro-intestinal problems (up to 67.8%, Bougeard et al. 2021). Due to the importance of those comorbidities for morbidity and mortality and the effects of development on comorbidities, the screening of accompanying disorders should be an important part of both baseline assessment and follow-up of children with ASD.

Number of Turkish youth with autism <18 years old have been estimated previously as around 250.000 (Turkish Autism Council 2018, ODFED 2021). A recent nation-wide survey found that awareness of ASD was significantly greater in Mediterranean, Black sea and Marmara regions of Turkey (Tohum Autism Foundation 2021). Reflecting this finding, most of the previous studies on ASD from Turkey were conducted in western regions (Mukaddes et al. 2017, Oner and Munir 2020, Yildiz et al. 2022). In this study, it was aimed to examine the demographic characteristics, accompanying psychiatric and medical conditions of Turkish children with ASD who were evaluated at a tertiary center in Southeastern Anatolia.

Methods

Study center, sampling, evaluation procedures and ethics

The files of patients who applied to the child and adolescent psychiatry outpatient clinic of Harran University Medical Faculty Hospital for any reason in between June 1, 2016 and 2021 were evaluated (See Fig. 1 for flowchart in accordance with RECORD statement, Benchimol et al. 2015, Gearing et al. 2006).

Figure 1.

Flow chart of study participants.

In the 2021 Turkish consensus, there were 1048957 inhabitants ≤18 years living in the Sanliurfa county (28.0% between 0 and 4 years old and 27.3% between 5 and 9 years old; Turkish Institute of Statistics 2021). According to the Sanliurfa County Directorate of Health, there were four centers with child and adolescent psychiatry outpatients in the year 2021 with roughly equal numbers of applications (https://sanliurfaism.saglik.gov.tr/, Accessed on 20.03.2022).

A total of 295 patients with ASD (F84.0, F84.1, F 84.5 and F84.9) according to DSM-5 criteria (APA 2013) were found among all cases. Sixty-three of the sample (21.4%) had to be excluded having incomplete records. All patients were evaluated by a senior child and adolescent psychiatry resident and an experienced child and adolescent psychiatrist at their initial application for ASD and comorbid psychiatric diagnoses. ASD symptoms were evaluated with Childhood Autism Rating Scales (for patients ≥4 years old). Developmental evaluations among those <6 years old was conducted by clinical psychologists using the Ankara Developmental Screening Inventory (ADSI, AGTE) while intellectual functioning of children >6 years was evaluated with Kent E.G.Y (verbal), Porteus Mazes (performance) or Wechsler Intelligence Scale for Children-Revised form (both verbal and performance). Patient’s age, gender, age at diagnosis, developmental levels/intellectual functioning, severity of ASD symptoms, comorbid neurodevelopmental/psychiatric diagnoses and accompanying medical disorders were recorded from hospital charts.

IRB of Harran University Medical Faculty approved the study protocol (No: 2021/22) and permission of hospital administration was also obtained for retrospective chart reviews.

Measures

Ankara Developmental Screening Inventory (ADSI, “Ankara Gelişimsel Tarama Envanteri, AGTE”)

ADSI was developed by Savasir, Sezgin and Erol (1994) to evaluate the development of 0–6 years old Turkish children in four domains (cognitive–language, fine motor, gross motor, social skills—grooming) in 154 developmentally arranged items. The items are evaluated according to maternal reports and observation of children with positive responses denoting greater levels of development. The test is terminated whenever eight consecutive items in a developmental domain were answered negatively and the combination of four domains yields a general developmental quotient. ADSI was normed initially on 860 mother-child dyads and revised in 1998, 2005 and 2006. Previous studies found that developmental domain scores from ADSI correlated significantly with scores from Denver Developmental Screening Test-II (r = 0.87), Bayley Scales of Infant Development (r = 0.46–0.91) and Vineland Adaptive Behavior Scales (r = 0.74–0.98, Gunes 2017, Savasir, Sezgin and Erol 1994, Sezgin 2011) and the measure is widely used in Turkish institutions to evaluate development of children <6 years old. In this study, ADSI was used to evaluate development of participants younger than 6 years old.

Porteus Mazes Test (PMT)

PMT was developed by Porteus (1959) to evaluate non-verbal planning abilities, visual-spatial perception, adjustment to novelty and nonverbal intelligence among 7–14 years old children regardless of literacy. PMT consists of mazes of increasing complexity arranged according to chronological age and was adapted into Turkish by Toğrol (1974) and normed on 1300 children. Due to low correlations between PMT and Catell scores (r < 0.50), it was suggested to be used together with a verbal intelligence test (Toğrol 1974). In this study, PMT was used for children >6 years old who could not complete the WISC-R protocol and a composite IQ score was formed by combining its results with those of Kent EGY test.

Kent EGY Test (EGY)

This test was developed by Grace Kent in 1941 as a brief test of verbal ability for children between 6 and 14 years and in adults with suspected intellectual disability. In the validity and reliability study of the Turkish version, it was suggested to use a composite score formed by average performance in the PMT and EGY tests (Oner 2008). Despite this caveat, it is still being used frequently as a brief measure of verbal ability (Uzun Cicek and Bora 2020). In this study, EGY was used for children >6 years old who could not complete the WISC-R protocol and a composite IQ score was formed by combining its results with those of PMT.

Wechsler Intelligence Scale for Children-Revised Version (WISC-R)

WISC-R was developed as an individual test of intellectual ability for children between 6 and 16 years old. The test is composed of six verbal (i.e., general knowledge, similarities, arithmetics, vocabulary, judgement and digit span) and six performance (i.e., Picture completion, Picture arrangement, block design, labyrinths, Picture completion and coding) subscales yielding verbal, nonverbal and full scale intellectual quotients (Wechsler 1974). WISC-R was translated into Turkish (Savaşır and Şahin 1995) and normed on a sample of 1639 children with reliability coefficients between 0.96 and 0.98. In the original study correlations between subscales ranged from 0.51 to 0.86. Lately, WISC-R was reevaluated on normally developing and intellectually gifted Turkish children and its psychometric reliability was ascertained (Yigit et al. 2017). WISC-R was applied to children between 7 and 16 years in this study. As suggested by Yazıcı et al. (2020) first, a trial of WISC-R was attempted and if the children were noncompliant, then evaluation commenced with PMT and Kent EGY tests.

Cognitive levels of children who did not comply with intelligence/development tests were determined by the opinion of the child and adolescent psychiatrist in the light of information received from the family, history of developmental stages, academic achievement and psychiatric examination of the child. Patients with IQ or developmental quotient <2 standard deviations were considered to have intellectual disability.

Childhood Autism Rating Scale (CARS)

CARS was developed by Schopler and Reichler in 1971 for assessment of autism among children 4–18 years and have gone through various revisions and iterations (Schopler, Reichler and Renner 1986). CARS consists of 15 items scored from one to four according to observations and caregiver reports. The maximum score that can be obtained is 60 and a cut-off score of 30 was suggested for the original version. The reliability and validity of the Turkish version was established by Sucuoğlu et al. (1996) with later extension of analyses by Incekas Gassaloglu et al. (2016). Cronbach alpha for the Turkish version was 0.95 with excellent test-retest (r = 0.98) and inter-rater (r = 0.98) reliabilities. The cut-off score for the Turkish version was suggested as 29.5. For the study sample first scores on CARS when they were ≥4 years old were evaluated.

Statistical analysis

Statistical analyses were performed on IBM SPSS Statistics version 24.0 software (IBM Inc., Armonk, NY, USA). Descriptive statistics (number, rate, percentage) were employed during the analysis. The normality of data distribution was assessed using Shapiro-Wilk test, skewness, kurtosis, histogram and Q-Q plots. Quantitative variables with skewed distribution are expressed as median [interquartile range]. Categorical variables were compared using Chi-square test between groups. For binary comparisons, Mann Whitney U test was used in continuous variables with skewed distribution. A p value <0.05 was considered as statistically significant (two-tailed).

Results

Rate of ASD at the study center and difference between genders

The study center’s catchment area included 262239 children ≤18 years old for the year 2021 (Turkish Institute of Statistics 2021) which may reflect rates of 0.1% for the community and 2.8% for the clinical sample. Of the 232 patients included in the study, 19.4% (n = 45) were female and 80.6% (n = 187) were male. The overall male-to-female prevalence ratio was 4.2. The mean age of all patients was 77.9 ± 41.8 months (73.6 ± 34.5 months for females vs. 78.9 ± 43.4 months for males). More than half of the sample were ≤6 years old (n = 131, 56.5%) while the rest (n = 101, 43.5%) were between 7 and 17 years old (Table 1).

Table 1.

Participant demographics.

Variables	Mean ± SD or n, %
Age (months)	77.89 ± 41.8
Male	78.93 ± 43.39
Female	73.58 ± 34.53
Gender, male	187, 80.6%
Under 6 years	131, 56.5%

Note: SD = Standard Deviation.

According to CARS scores, 54.7% of the sample had mild-moderate symptoms while the rest had severe symptoms. The rates of severe autistic symptoms for females and males were 55.6% and 42.8%; respectively with no statistically significant difference (Chi square test, p = 0.122).

Cognitive abilities among children with ASD

According to ADSI and clinical examinations, more than half of the sample <6 years old (n = 131, 55.0%) qualified for cognitive-developmental delay (CDD). Rates of CDD among female and male children were 75.9% and 49.0%; respectively with a significant difference (Chi square test, p = 0.01). Among children older than six years old with ASD (n = 101) who were assessed with tests, 72.3% were classified as having intellectual disability (ID) (IQ ≤70) at their most recent test or examination, 11.9% were functioning at the borderline range (IQ = 71–85), and 15.8% were classified as having average or higher cognitive ability (IQ >85). The rates of children classified as having an intellectual disability between genders were similar (75.0% females and 71.8% males, respectively) for children older than six years (Chi square test, p = 0.791) (Table 2).

Table 2.

Differences in cognitive ability by gender and age.

		Female, n (%)	Male, n (%)	p*
Under 6 years, CDD	Yes	22 (75.9%)	50 (49%)	0.01
	No	7 (24.1%)	52 (51%)
Over 6 years, ID	Yes	12 (75%)	61 (71.8%)	0.791
	No	4 (25%)	24 (28.2%)

^*Chi-squared test; CDD, cognitive developmental delay; ID, intellectual disability.

Age at diagnosis

The median age at diagnosis for the whole sample was 36 months (IQR = 22.0, Minimum= 12, maximum= 84 months). A statistically significant difference was found between the median ages at diagnosis of children <6 and those ≥6 years old (34.0 months, IQR= 16 and 36.0 months, IQR= 18; respectively, p < 0.001, Mann-Whitney U test). There was no statistically significant difference between genders in terms of median age at diagnosis (36 months and 36 months, respectively, p = 0.493, Mann-Whitney U test). There was also no statistically significant difference between children with and without CDD/ID in terms of the median age at diagnosis (36 months and 35 months, respectively, p = 0.369). However, children with psychiatric comorbidity were diagnosed later than those a sole diagnosis of ASD (36 months, IQR = 21 and 32 months, IQR = 10, respectively, p = 0.002). Presence of medical comorbidity did not affect median age at diagnosis (36 months and 36 months, respectively, p = 0.287) (Table 3).

Table 3.

Differences in age at first diagnosis.

Variable (Percent of Sample)	Age at first diagnosis (n = 232) Median (IQR)	p*	Z
Age
Under 6 years (56.5)	34 (16)	<0.001	-4.267
Over 6 years (43.5)	36 (18)
Sex
Female (19.4)	36 (23)	0.493	−0.685
Male (80.6)	36 (2)
Intellectual disability
Yes (62.5)	36 (24)	0.369	−0.898
No (37.5)	35 (17)
Comorbid psychiatric disorder diagnosis
Diagnosed (73.7)	36 (21)
Never diagnosed (26.3)	32 (10)	0.002	−3.104
Comorbid medical diagnoses
Diagnosed (22.8)	36 (18)
Never diagnosed (77.2)	36 (23)	0.287	−1.065

^*Mann-Whitney U test, IQR: Inter-Quartile Range.

Comorbid psychiatric and neurodevelopmental disorders

Among all cases, 73.7% had at least one comorbid diagnosis according to DSM-5 diagnostic criteria. Comorbid diagnoses in order of frequency were ADHD (61.2%), disruptive, impulse-control, and conduct disorders (DICCD, 19.8%), SD (11.2%), obsessive compulsive disorder (OCD, 5.6%), AD (4.7%) and, feeding and eating disorders (FED, 2.6%) (Figure 2). There was no statistically significant difference between genders in terms of comorbid psychopathology (77.8% and 72.7% respectively for females and males, p = 0.490). Rates of all mental disorders, ADHD, DICCD and OCD increased significantly after the age of 6 years (p < 0.001; for all). There were also trends for AD and SD to increase after 6 years of age without reaching significance (p = 0.217; p = 0.480). FED tended to be more frequent among preschool children, although this too did not reach significance (p = 0.236) (Table 4).

Figure 2.

Comorbid psychiatric disorders among children with ASD.

ADHD, attention-deficit hyperactivity disorder; DICCD, disruptive, impulse-control, and conduct disorders; OCD, obsessive compulsive disorder; AD, anxiety disorder; FED, feeding and eating disorders; SD, sleeping disorder.

Table 4.

Differences in comorbid psychiatric and medical disorders according to age groups in children with ASD.

	Under 6 years n (%)	Over 6 years n (%)	p*
Comorbid psychiatric disorders
All MHD	76 (58)	95 (94.1)	<0.001
ADHD	60 (45.8)	82 (81.2)	<0.001
DICCD	13 (9.9)	33 (32.7)	<0.001
OCD	0 (0)	13 (12.9)	<0.001
AD	4 (3.1)	7 (6.9)	0.217
SD	13 (9.9)	13 (12.9)	0.480
FED	5 (3.8)	1 (1)	0.236
Comorbid medical diagnoses
Diagnosed	20 (15.3)	33 (32.7)	0.002
Never diagnosed	111 (84.7)	68 (67.3)
Comorbid epilepsy
Diagnosed	16 (12.2)	28 (27.7)	0.003
Never diagnosed	115 (87.8)	73 (72.3)

^*Chi-squared test; All MHD, all mental health disorders; ADHD, attention-deficit hyperactivity disorder; DICCD, disruptive, impulse-control, and conduct disorders; OCD, obsessive compulsive disorder; AD, anxiety disorder; SD, sleeping disorder; FED, feeding and eating disorders.

Comorbid medical disorders

More than one fifth of the whole sample (22.8%) had medical comorbidities. The most common comorbidities in order of frequency were epilepsy (19.0%), cerebral palsy (1.7%) and hearing loss (1.3%). Other diagnoses include biotidinase deficiency, tuberous sclerosis, hyperthyroidism, hypothyroidism, Rubinstein-Taybi syndrome, Angelman syndrome, Mucopolysaccharidosis type III, homocystinuria, Down syndrome, and visual impairment (0.4% for each). Comorbid epilepsy tended to be more frequent among females without reaching significance (28.9% and 16.6% respectively, p = 0.059). Also, epilepsy comorbidity was significantly elevated among children with comorbid CDD/ID compared to those without (24.8% and 9.2%, respectively, p = 0.003). Rate of medical comorbidities among children <6 years old was (15.3%) significantly lower than those ≥6 years old (32.7%, p = 0.002) with the difference being primarily due to epilepsy (12.2% vs. 27.7%, respectively, p = 0.003) (Table 4).

Discussion

In this study, the demographic and clinical characteristics of patients with ASD who applied to a university hospital clinic between 2016 and 2021 were examined. The rate of ASD among clinical sample was 2.82% while it may correspond to a rate of 0.1% in o the community inhabiting the epidemiological catchment area. The ratio of males to females was 4.2 with CDD/ID being significantly elevated in females <6 years. The median age at diagnosis was 36 (IQR = 22) months for the whole sample. It was determined that there was at least one psychiatric/neurodevelopmental comorbidity in 73.7% of the cases. The presence of psychiatric comorbidity was associated with advanced age of diagnosis. More than one fifth (22.8%) of the sample had at least one concomitant medical disease, and the presence of intellectual disability was a risk factor for medical comorbidities.

Although ASD was thought to be rare when first defined, subsequent studies revealed that it was not so rare (Kılıçaslan and Kütük 2020, Maenner et al. 2021). Despite the increase in studies conducted in Turkey to elucidate the etiopathogenesis of ASD in recent years, studies on the community and clinical prevalence of ASD are still limited (Ayaydın et al. 2021, Kutuk et al. 2020, Oner and Munir 2020). Recently, estimations on Turkish youth with ASD <18 years old suggested approximately 250.000 qualified for the diagnosis (Turkish Autism Council 2018, ODFED 2021). Community awareness of ASD was greater in western Turkey, leading to increased number of studies conducted on urban samples residing in Marmara and west Anatolia (Mukaddes et al. 2017, Oner and Munir 2020, Tohum Autism Foundation 2021, Yildiz et al. 2022). According to a meta-analysis, the median global prevalence of ASD may be 1.0% (Zeidan et al. 2022). In a 2008 study conducted by an NGO, rate of children under ASD risk was found as 2.2% in five (Adana, Bursa, Gaziantep, Izmir, Kocaeli) counties of Turkey with 0.5% being under elevated risk according to M-CHAT scores (Turkish Ministry of Health and Tohum Foundation 2008). Recent regional studies for autism risk assessment in Turkey state that this rate may vary between 0.8% and 1.0% (Gölbaşı 2018, Oner and Munir 2020, Sentosun 2020). Additionally, a nation-wide study evaluating 5830s to fourth grade students residing in 30 urban centers in Turkey found the rate of ASD as 0.1% (Ercan et al. 2019). In our study, the rate of ASD in clinical sample and that calculated for the community were in accordance with results of previous studies although the latter may be subject to selection bias. Further studies focusing on ASD prevalence in Turkey are needed to replicate our results.

Studies show that ASD is more common in boys and the global male to female ratio was estimated as 4.2 (Zeidan et al. 2022). However, our knowledge of gender disparities in ASD, effects of ID comorbidity and the causes of gender disparity are still limited (Evans et al. 2019, Maenner et al. 2021, Nichols et al. 2009). The gender disparity may be more pronounced among clinical samples (Loomes et al. 2017, Zeidan et al. 2022). Previously male: female ratio for ASD among Turkish clinical samples was reported as 4.1 (Uğur and Göker 2018) which is consistent with our results (i.e., 4.2). The greater gender disparity in clinical samples may be due to effects of gender on expression of symptoms. This hypothesis should be evaluated with community surveys.

Globally almost one third of children with ASD may have comorbid CDD/ID with the effects of gender on this comorbidity being still debated (Katusic et al. 2021, Loomes et al. 2017, Maenner et al. 2021, Zeidan et al. 2022). Previous studies on Turkish samples reported that the rate of CDD/ID among ASD may vary between 11.0% and 65.0% (Mukaddes et al. 2017). Recently, Uğur and Göker (2018) reported that 73.8% of their sample had comorbid ID/CDD (55.0% among children <6 years old and 72.3% among those ≥6 years). In our sample, 55.0% of children <6 years old had CDD while 72.3% of those ≥6 years old had ID. While we observed that girls were diagnosed with ID significantly more frequently in the preschool period, this gender disparity was reduced among older children. Baio et al. (2018) reported that rates of ID/CDD comorbidity among younger female children were significantly elevated compared to males. This may be due to greater threshold for vulnerability to ASD among female children leading to elevated severity of symptoms in affected females, especially in early childhood and shared genetic vulnerabilities for ID/CDD (Lai et al. 2015). Also, mildly affected older females with borderline to normal/above normal intellectual functioning may use mimicry and camouflaging to overcome their problems (Loomes et al. 2017, Schuck et al. 2019). Male gender was also recently associated with greater rates of challenging behavior among children with ASD, leading to an increase in referrals while females with ASD may have comorbid internalizing and/or eating disorders which are diagnosed later (Leader et al. 2022, Nichols et al. 2009). Due to the cross-sectional nature of our study we could not evaluate those hypotheses which should be tested with longitudinal studies.

Earlier diagnosis and intervention in ASD are crucial for prognosis (Zeidan et al. 2022). Although the first concerns of parents of children with ASD about their children begin before the age of 2 years, the most recent reviews show that globally, the mean age at diagnosis of ASD varied between 30.9 and 234.6 months (Hyman et al. 2020, Van’t Hof et al. 2021). Children with milder symptoms and those from low-middle income countries may be diagnosed later (Zeidan et al. 2022), although some studies do not support the effects of symptom severity (Jayanath and Ozonoff 2020). We also could not find an effect of symptom severity on age at diagnosis which may be due to our grouping mild-moderate symptoms in CARS together. Separating those groups along with inclusion of parent and teacher reports of symptom severity may have enriched our results. On the other hand we found that children with co-occurring psychiatric or developmental difficulties may receive their diagnosis later. This may reflect diagnostic overshadowing. Other developmental problems or behavioral symptoms may overshadow basic ASD symptoms, especially in the presence of neurodevelopmental disorders such as ADHD and intellectual disability, and thus may result in a later age in the diagnosis of ASD (Leader et al. 2022, Nichols et al. 2009, Vant’t Hof et al. 2020, Zeidan et al. 2022). The effects of comorbidities on age of diagnosis of ASD should be replicated in studies conducted at different clinical centers in Turkey.

Additionally, changes in access to care and diagnostic practices may affect age at diagnosis, regardless of clinical presentation. For example, younger children in cross-sectional studies have earlier ages of first diagnosis than older children in the same samples (Van’t Hof et al. 2021). Similarly, in the present study, the age of first diagnosis of children in the preschool age group was found to be significantly lower than that of older children while the median age at diagnosis for the whole sample was 36 months. Although the age at diagnosis in our study was relatively lower than in other studies, early detection of ASD should continue to be a global priority and studies on this subject should have priority.

Developmental, psychiatric and neurological disorders are frequently seen together in children with ASD, and the identification of children with ASD can have a significant impact on their treatment needs, functional status and progress. Limited speech-communication skills and ID/CDD may prevent identification of some comorbidities (Nichols et al. 2009, Van’t Hof et al. 2021, Zeidan et al. 2022). Although subject to methodological variations, it is estimated that approximately 70.0% of individuals with ASD may have at least one comorbid psychiatric disorder, with approximately 40% having two or more psychiatric disorders (Bougeard et al. 2021). Individuals with ASD are likely to have a higher prevalence of mental disorders than typically developing individuals and those with ID alone (Bougeard et al. 2021). Lai et al. (2019) report rates of comorbid ADHD, AD, SD, DICDD, depressive, obsessive compulsive, bipolar and schizophrenia spectrum disorders as 28.0%, 20.0%, 13.0%, 12.0%, 11.0%, 9.0%, 5.0% and 4.0%; respectively. In our study, psychiatric comorbidity was seen at a high rate of 73.7%, with the most common comorbidities being ADHD, DICCD, SD, OCD, AD, and FED. Both of those results are consistent with previous studies in the literature.

Among the general medical conditions associated with autism, neurological disorders are arguably the most prominent (Pan et al. 2021). Epilepsy may be the most common neurological comorbidity and may affect up to 77.5% of children with ASD (Bougeard et al. 2021, Manoli and State 2021, Pan et al. 2021). It may especially affect females and those with comorbid CDD/ID (Pan et al. 2021). Our study, in accordance with the literature, found that rates of both medical diseases and epilepsy were elevated in ASD, and that intellectual disability is a risk factor for epilepsy. However, contrary to other studies, the rate of epilepsy did not differ between genders in our sample (Pan et al. 2021). The fact that our study was conducted in a clinical sample from a single center may have affected our results.

Limitations of the study

Although most of the findings of our study have parallel findings with previous studies, the fact that the sample collected from a single center limits the generalizability of the results to other centers and to the community. Younger children may be followed with another ICD code reflecting the preliminary nature of their complaints and pending completion of evaluations (e.g., F81.9, R62.50 etc.). Also, comorbid neurological emergencies such as epilepsy may have led to applications to the departments of pediatric neurology and delay in developmental evaluations while seizures are being stabilized (e.g., G40 codes). Also, limited number of children with comorbid/neurological syndromes have reduced our ability to evaluate the effects of those comorbidities. Community-based prospective studies on larger samples may lead to increased generalizability. However, our study also has some strengths. The number of participants seems sufficient compared to other studies. Appropriate assessment tools were used to determine the intelligence levels and severity of symptoms of the patients.

Conclusion

Despite continuing studies globally, our knowledge on ASD is still limited. Early diagnosis provides the chance for early treatment and has important effects on prognosis. On the other hand, accompanying disorders can cause significant clinical deterioration and additional disease burden on children with autism and their families. It is of great importance to determine the risk factors of autism that affects a significant part of the society and to have information about possible accompanying psychiatric and medical comorbid conditions. Our results may contribute to the characterization of Turkish children with ASD.

Disclosure statement

No potential conflict of interest was reported by the authors.