A Naturalistic Follow-up Study Focusing on Potential Sex Differences in Children and Adolescents with ADHD and Co-occurring Psychiatric Disorders

doi:10.21203/rs.3.rs-4438741/v1

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A Naturalistic Follow-up Study Focusing on Potential Sex Differences in Children and Adolescents with ADHD and Co-occurring Psychiatric Disorders

https://doi.org/10.21203/rs.3.rs-4438741/v1

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A retrospective study assessed the prevalence, timing, and distribution of psychiatric comorbidities in 322 Turkish children with ADHD (aged 6–18 years), focusing on potential sex differences. Data were collected from university-based clinical records. Assessments included periodic psychiatric examination, Wechsler Intelligence Scale for Children-Revised (WISC-R) and Conners’ Parent/Teacher Rating Scales (CP/TRS). Females with ADHD had higher psychiatric comorbidity rates compared to males (83.5% vs. 62.7%, p < .001). Intellectual disabilities and speech disorders were more prevalent in females (p < .001 and p = .028, respectively). Anxiety disorders were prevalent in both sexes. Higher rates of internalizing and externalizing disorders were observed in females. CTRS scores and indexes showed mild negative correlations with the timing of the first comorbidity other than neurodevelopmental disorders. Age and specific learning disorders (SLD) were predictors of comorbidity onset (p = .004 and p = .001, respectively). Females with ADHD need more clinical attention. ADHD severity, age, and SLD are important for the onset of comorbidities.

attention deficit hyperactivity disorder

comorbidity

sex characteristics

Females with ADHD had a higher prevalence of psychiatric comorbidity compared to males. They also had higher rates of intellectual disabilities and speech disorders.

Anxiety disorders as a group were the most prevalent in both sexes with ADHD, while males had higher rates of externalizing disorders and females had higher rates of internalizing disorders.

Within each of the sex-specific comorbidity rankings, depression is the most common comorbid disorder in both sexes individually.

Higher scores on oppositional and hyperactive/impulsive symptoms were associated with an earlier occurrence of internalizing and externalizing comorbidities.

Age and specific learning disorders were identified as predictors for the onset of comorbid internalizing and externalizing disorders in children and adolescents with ADHD.

ADHD is a neurodevelopmental condition characterized by attention deficit, hyperactivity, and impulsivity, and it affects approximately 5–7% of children and adolescents worldwide, impairing daily functioning (Polanczyk et al., 2014). It has consistently been found that ADHD is more prevalent in boys than girls in both epidemiological and clinical samples, potentially due to lower referral rates among girls (Polanczyk & Rohde, 2007). However, if left untreated, both males and females can face serious consequences such as poor academic achievement, divorce, and unemployment (Quinn & Madhoo, 2014).

The prevalence of psychiatric comorbidity in children with ADHD is estimated to be around 60–100%, and it is common for one or more comorbidities to persist into adulthood (Gnanavel et al., 2019). Conditions such as oppositional defiant disorder (ODD), conduct disorder (CD), mood disorders, and anxiety disorders frequently coexist with ADHD and significantly impact its clinical presentation. These comorbidities might worsen the severity of ADHD, complicate its treatment, and have a detrimental effect on the functioning of individuals and their families, surpassing the challenges posed by ADHD itself (Ottosen et al., 2019).

Limited information exists regarding sex differences in the prevalence of psychiatric comorbidities for ADHD, and the current literature on these comorbidities lacks consistency (Tung et al., 2016). According to previous studies, anxiety and mood disorders are more common in female patients, while autism spectrum disorder and disruptive disorders are more common in males (Mohammadi et al., 2021; Slobodin & Davidovitch, 2019; Tung et al., 2016). Interestingly, another study investigating the association rather than the prevalence of comorbidities with ADHD suggested that females with ADHD, unlike males, exhibited a stronger association with autism spectrum disorder, oppositional defiant/conduct disorder, intellectual disability (ID), schizophrenia, and substance use disorders (Ottosen et al., 2019). Conflicting findings point to the complex nature of psychiatric comorbidities in ADHD, highlighting the need to elucidate sex-specific differences.

In addition to sex, the pattern of comorbidities is also influenced by age. Externalizing disorders, which involve behaviors directed outwardly, are more commonly observed in younger age groups. In contrast, internalizing disorders, which involve inward-focused emotional and psychological experiences, are more prevalent among older age groups (Murray et al., 2019). In particular, depression, social phobia, generalized anxiety, obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), conduct disorder, oppositional defiant disorder, smoking, and alcohol consumption were more prevalent among older children. Conversely, separation anxiety was more common among younger children (Mohammadi et al., 2021). In ADHD, a life-long disorder, accurate prediction of the timing and types of sex-specific comorbidities at different stages is important for both the differential diagnosis and diagnosis of these disorders.

Our aim was to assess the prevalence, chronological order (in terms of age), and distribution of comorbid psychiatric disorders in children and adolescents diagnosed with ADHD, while also investigating potential sex differences in sociodemographic and clinical characteristics with respect to ADHD and the comorbidities. It is crucial to consider these variations and develop different strategies when addressing ADHD in children, taking into account age and sex-related factors.

Sample

A retrospective study was conducted using data from 322 children with ADHD who received follow-up at the XXXXX University Child and Adolescent Psychiatry Department from January 2018 to October 2019. The research protocol was approved by the ethics committee of XXXXX University, and the study was conducted in accordance with the Declaration of Helsinki. Participants between the ages of 6 and 18 who met the DSM-5 criteria for ADHD through clinical evaluation were included in the study. Sociodemographic and clinical information were collected from personal background records and the results of specific scales found in the patients’ files. Internalizing and externalizing disorders that developed during the follow-up period from the first admission were determined by psychiatric examination and recorded chronologically (1st, 2nd, 3rd and 4th comorbidities) in the patients’ files. The Conners’ Parent and Teacher Rating Scales/Revised Long Forms used when diagnosing ADHD were included in the analysis.

Measures

The Sociodemographic and Clinical Data Form (SCDF) was utilized to systematically collect information, including age, sex, number of siblings, maternal age and educational status, paternal age and educational status, ADHD subtypes, age at notification of ADHD symptoms (years), age at diagnosis of ADHD (years), age at initiation of ADHD medication (years), psychiatric comorbidities (neurodevelopmental disorders, internalizing and externalizing disorders), history of physical illness, first-line ADHD treatments, drug forms and doses, and familial medical and psychiatric history, from the patients’ files.

The Wechsler Intelligence Scale for Children-Revised (WISC-R) was employed to assess the cognitive abilities of children with adequate speech and language skills, aged 6 to 16. Developed by Wechsler in 1949 and revised in 1974, the WISC-R is an intelligence test consisting of 12 subtests that evaluate verbal and performance skills (Wechsler, 1974). Savaşır and Şahin conducted a validity and reliability study to adapt the WISC-R to the Turkish culture (Savaşır & Şahin, 1995). Based on the results of these subtests, verbal, performance, and total intelligence scores are calculated. Intelligence scores recorded in the patients’ files were included in the analysis.

Parents and teachers were administered the Conners’ Parent and Teacher Rating Scales/Revised Long Forms (CPRS/RLF and CTRS/RLF) to assess the core symptoms of ADHD, the ADHD index, and the global index in children with ADHD. Developed by Conners et al., both versions involve rating ADHD symptoms and related problematic behaviors in children and adolescents aged 6 to 18 years using a Likert scale ranging from 0 (not at all/never) to 3 (very much/very frequently) (Conners, 1997; Conners et al., 1998a, b). Kaner et al. conducted the Turkish standardization of the CPRS/RLF, which includes 7 subscales (total of 57 items) such as oppositional, cognitive problems/inattention, hyperactivity, anxious-shy, perfectionism, social problems, and psychosomatic symptoms (Kaner et al., 2011a). The Turkish version of the CTRS/RLF was also validated by Kaner et al. and consists of 28 items with six subscales: oppositional, cognitive problems/inattention, hyperactivity, anxious-shy, perfectionism, and social problems (Kaner et al., 2011b). The Cronbach’s alpha coefficients for both versions ranged from 0.55 to 0.90. These scales provide users with two global problem indexes (restless-impulsive and emotional liability) as well as a composite ADHD index.

Data Analysis

Statistical analyses were performed using the SPSS software version 23.0. The variables were investigated using visual (histograms, probability plots) and analytical methods (Kolmogorov-Smirnov test) to determine whether or not they are normally distributed. Descriptive analyzes were presented using the mean and standard deviation values for normally distributed variables, and the median, 1st and 3rd quartiles for non-normally distributed variables. Categorical variables were expressed as frequency (n) and percentage (%). Correlation coefficients and statistical significance were calculated using the Spearman test, while investigating the relationships between variables, at least one of which was not normally distributed. Normally distributed parameters were compared between groups using Student’s t test. Non-normally distributed ones were compared between groups using Mann-Whitney U test. Comparisons between categorical variables were made using either the Chi-square test or Fisher’s exact test (when the chi-square assumptions did not hold due to low expected cell counts). Also, the exact test was used for table structures larger than 2x2 (when the chi-square assumptions were not met). In order to explore additional factors potentially linked to the age at the first diagnosis of internalization or externalization comorbidity in children diagnosed with ADHD, logistic regression analysis was conducted. The study participants were categorized into two groups based on whether their first diagnosis occurred before the age of 10 or after (Mohammadi et al., 2021). Following univariate analyses and careful consideration of variables deemed clinically relevant, the variables included in the regression model were age, specific learning disorders (SLD) diagnosis, age at notification of ADHD symptoms, and the CTRS/RLF Conners’ global index-total score. A p-value of less than 0.05 was considered to show a statistically significant result.

The sociodemographic and clinical characteristics of the study participants were presented in Tables 1 and 2. The average age of the sample was 12.5 years with a standard deviation of 2.8, and 45.3% (n = 146) of the participants were male. Females were found to be statistically significantly younger than males (p = .037). There was also a significant difference in the distribution of father’s educational status between females and males (p = .020). However, apart from these differences, the sociodemographic characteristics of females and males in the sample were similar. There was a significant difference in the distribution of ADHD subtypes between females and males (p < .001). The mean age at which ADHD symptoms were first noticed was 7.3 years (± 2.2) for females and 6.7 years (± 2.1) for males, showing a statistically significant difference (p = .015). Males had significantly higher scores than females in all WISC-R scores (p < .001). The CPRS subscale scores were similar between males and females. However, according to the CTRS, teachers rated males significantly higher than females on the oppositional and hyperactive/impulsive subscales (p = .049 and p = .015, respectively). The Conners’ global index-restless/impulsive was also higher in males compared to females according to the CTRS (p = .024). While atomoxetine was preferred more frequently in females than in males as first-line treatment, psychostimulants (mostly extended-release forms) were used in higher doses in males than in females (p = .035 and p = .050, respectively).

Table 1

Sociodemographic characteristics of children with ADHD
		Females		Males		Total Sample
		n	% ^a	n	% ^a	n	% ^a	p
Sex
	Female	176	57.7			176	57.7
	Male			146	45.3	146	45.3
Age (years)
	Median	12		13		12		.037^b
	1st and 3rd quartiles	10–14		11–15		10–15		.037^b
Number of siblings
	Median	2		2		2		.811^b
	1st and 3rd quartiles	1–2		1–2		1–2		.811^b
Mother’s age (years)
	Median	39		40		40		.205^b
	1st and 3rd quartiles	35–43		35–44		35-43.5		.205^b
Father’s age (years)
	Median	42		43		43		.543^b
	1st and 3rd quartiles	39–48		38–48		38–48		.543^b
Mother’s education
	None	4	2.4	1	0.7	5	1.6	.122^c
	Primary school	51	30	33	22.6	84	26.6
	Middle school	37	21.8	24	16.4	61	19.3
	High school	51	30	58	39.7	109	34.5
	Graduate	27	15.9	30	20.5	57	18
Father’s education
	None	2	1.2	1	0.7	3	0.9	.020^c
	Primary school	47	27.6	19	13.0	66	20.9
	Middle school	31	18.2	27	18.5	58	18.4
	High school	56	32.9	60	41.1	116	36.7
	Graduate	34	20.0	39	26.7	73	23.1
^a: Column percentage ^b: Mann-Whitney U test ^c: Exact test

Table 2

Clinical characteristics of children with ADHD
			Females			Males			Total Sample
			n	% ^a		n		% ^a	n	% ^a		p
ADHD subtypes
	Combined		87	49.4		112		76.7	199	61.8		< .001^b
	Predominantly inattentive		87	49.4		31		21.2	118	36.6
	Predominantly hyperactive/impulsive		2	1.1		3		2.1	5	1.6
Age at notification of ADHD symptoms (years)
	Median		7			7			7			.015^c
	1st and 3rd quartiles		6–8			5.5-8			6–8			.015^c
Age at diagnosis of ADHD (years)
	Median		7.5			7			7			.363^c
	1st and 3rd quartiles		7–9			7–9			7–9			.363^c
Age at initiation of ADHD medication (years)
	Median		8			7			8			.251^c
	1st and 3rd quartiles		7–9			7–9			7–9			.251^c
History of physical illness
	Yes		39	22.5		22		15.1	61	19.1		.091^b
	No		134	77.5		124		84.9	258	80.9		.091^b
Family history of psychiatric disorders
	Yes		41	24		38		26	79	24.9		.674^b
	No		130	76		108		74	238	75.1		.674^b
WISC-R verbal scores
	Median		80.5			92.5			87			< .001^c
	1st and 3rd quartiles		67–92			80.5–104			72–98			< .001^c
WISC-R performance scores
	Median		92			103.5			99			< .001^c
	1st and 3rd quartiles		78–105			91–113			84–108			< .001^c
WISC-R total scores
	Mean		85			96			89.5			< .001^d
	Standard deviation		19.6			17.9			19.6			< .001^d
First-line treatments
	Psychostimulants		150		86.7	137	93.8		287		90	.035^b
	Atomoxetine		23		13.3	9	6.2		32		10
Psychostimulant doses
	Mean		29.2			32.4			30.7			.050^d
	Standard deviation		13.2			14.7			14
Psychostimulant forms
	Immediate-release tablets		25		16.7	11	8		36		12.5	.027^b
	Extended-release tablets/capsules		125		83.3	126	92		251		87.5
Atomoxetine doses
	Mean		41.8			46.2			43.2			.655^d
	Standard deviation		20.9			28.7			23.3
Body weight
	Median		42			47			45			.057^c
	1st and 3rd quartiles		34–55			35–64			34-57.5
Conners’ Parent Rating Scale/Revised Long Form
Oppositional subscale scores		Median	10			11			11			.607^c
Oppositional subscale scores		1st and 3rd quartiles	7–15			7–15			7–15			.607^c
Cognitive problems subscale scores		Mean	18.6			18			18.4			.683^d
Cognitive problems subscale scores		Standard deviation	8.5			8.2			8.3			.683^d
Hyperactive/impulsive subscale scores		Median	11			12			11			.200^c
Hyperactive/impulsive subscale scores		1st and 3rd quartiles	6–15			7–18			7–16			.200^c
ADHD index		Median	20			20.5			20			.832^c
ADHD index		1st and 3rd quartiles	14–27			15–24			15–26			.832^c
Conners’ global index-restless/impulsive		Median	9.5			9			9			.328^c
Conners’ global index-restless/impulsive		1st and 3rd quartiles	6–13			8–13			6–13			.328^c
Conners’ global index-emotional lability		Median	3			4			4			.616^c
Conners’ global index-emotional lability		1st and 3rd quartiles	2–5			2–5			2–5			.616^c
Conners’ global index-total		Median	13			14			13			.308^c
Conners’ global index-total		1st and 3rd quartiles	9–18			9.5–18.5			9–18			.308^c
Conners’ Teacher Rating Scale/Revised Long Form
Oppositional subscale scores		Median	1			3			2			.049^c
Oppositional subscale scores		1st and 3rd quartiles	0–6			0–7			0–7			.049^c
Cognitive problems subscale scores		Median	10			11			11			.384^c
Cognitive problems subscale scores		1st and 3rd quartiles	7–15			8–14			7–14			.384^c
Hyperactive/impulsive subscale scores		Median	6			10			8			.015^c
Hyperactive/impulsive subscale scores		1st and 3rd quartiles	2–12			5–14			3-13.5			.015^c
ADHD index		Median	15			17.5			16			.091^c
ADHD index		1st and 3rd quartiles	9–22			12–24			10–23			.091^c
Conners’ global index-restless/impulsive		Median	6			9			7			.024^c
Conners’ global index-restless/impulsive		1st and 3rd quartiles	4–11			6–12			5–12			.024^c
Conners’ global index-emotional lability		Median	3			4			3			.350^c
Conners’ global index-emotional lability		1st and 3rd quartiles	1–7			2–7			1–7			.350^c
Conners’ global index-total		Median	8			11.5			10			.080^c
Conners’ global index-total		1st and 3rd quartiles	5–17			7–17			6–17			.080^c
ADHD: Attention deficit hyperactivity disorder ^a: Column percentage ^b: Chi-square test ^c: Mann-Whitney U test ^d: Independent groups t-test

Table 3 presents the data on psychiatric comorbidities of the participants. The rate of psychiatric comorbidity in females was 83.5% (n = 147), which was significantly different from males, indicating that females had a significantly higher number of psychiatric comorbidities (p < .001). Among neurodevelopmental disorders, ID (21%, n = 37) and speech disorders (18.2%, n = 32) were significantly more common in females (p < .001 and p = .028, respectively). When considering internalizing and externalizing disorders in general, anxiety disorders were the most common first and second comorbid disorders in both sexes (See Table 3). However, when examining the distributions of the first and second comorbidities individually, statistically significant differences were observed between males and females (p < .001 and p < .001, respectively). Among internalizing and externalizing disorders, the first comorbidities to occur in males were predominantly conduct disorder, oppositional defiant disorder, and specific phobias, while in females, they were depressive disorder, social phobia, and conduct disorder, respectively (See Table 3). The second comorbidities were generally similar to the first comorbidities in females, with the addition of performance anxiety replacing social phobia. In males, depressive disorder and social phobia were added to the first comorbidities of conduct disorder and specific phobias (See Table 3).

Table 3

Data on psychiatric comorbidities of children with ADHD
		Females		Males		Total Sample
		n	%^a	n	% ^a	n	% ^a	p
Comorbidity
	Yes	147	83.5	67	45.9	214	66.5	< .001^b
	No	29	16.5	79	54.1	108	33.5	< .001^b
Number of comorbidities
	Median	2		0		1		< .001^c
	1st and 3rd quartiles	1–3		0–2		0–2		< .001^c
Neurodevelopmental disorders
Intellectual disability
	Yes	37	21	8	5.5	45	14	< .001^b
	No	139	79	138	94.5	277	86	< .001^b
Autism spectrum disorder
	Yes	2	1.1	2	1.4	4	1.2	1.000^d
	No	174	98.9	144	98.6	318	98.8	1.000^d
Specific learning disorders
	Yes	65	36.9	40	27.4	105	32.6	.069^b
	No	111	63.1	106	72.6	217	67.4	.069^b
Speech disorders
	Yes	32	18.2	14	9.6	46	14.3	.028^b
	No	144	81.8	132	90.4	276	85.7	.028^b
Tic disorders
	Yes	1	0.6	2	1.4	3	0.9	1.000^d
	No	175	99.4	144	98.6	319	99.1	1.000^d
Internalizing and externalizing disorders
1st comorbidity
	None	70	40	104	72.2	174	54.5	< .001^d
	Depressive disorder	21	12	5	3.5	26	8.1
	Social phobia	18	10.3	4	2.7	22	6.9
	Conduct disorder	14	8	8	5.5	22	6.9
	Enuresis	13	7.4	5	3.5	18	5.6
	Performance anxiety	12	6.9	2	1.4	14	4.4
	Generalized anxiety disorder	8	4.6	3	2.1	11	3.4
	Oppositional defiant disorder	6	3.4	6	4.2	12	3.8
	Specific phobias	4	2.3	6	4.2	10	3.1
	Separation anxiety disorder	2	1.1	0	0	2	0.6
	Obsessive compulsive disorder	2	1.1	1	0.7	3	0.9
	Post-traumatic stress disorder	2	1.1	0	0	2	0.6
	Panic disorder	1	0.6	0	0	1	0.3
	Encopresis	1	0.6	0	0	1	0.3
	Other	1	0.6	0	0	1	0.3
2nd comorbidity
	None	122	69.3	131	89.7	253	78.6	< .001^d
	Depressive disorder	14	8.0	2	1.4	16	5.0
	Performance anxiety	12	6.8	1	0.7	13	4.0
	Conduct disorder	9	5.1	3	2.1	12	3.7
	Social phobia	4	2.3	2	1.4	6	1.9
	Encopresis	4	2.3	0	0.0	4	1.2
	Oppositional defiant disorder	2	1.1	0	0.0	2	0.6
	Panic disorder	1	0.6	0	0.0	1	0.3
	Specific phobias	1	0.6	3	2.1	4	1.2
	Generalized anxiety disorder	1	0.6	1	0.7	2	0.6
	Obsessive compulsive disorder	1	0.6	1	0.7	2	0.6
	Enuresis	1	0.6	1	0.7	2	0.6
	Post-traumatic stress disorder	1	0.6	0	0.0	1	0.3
	Other	3	1.7	1	0.7	4	1.2
3rd comorbidity
	None	152	87.4	140	95.9	292	91.3	.060^d
	Depressive disorder	7	4.0	1	0.7	8	2.5
	Enuresis	3	1.7	0	0	3	0.9
	Performance anxiety	3	1.7	0	0	3	0.9
	Social phobia	2	1.1	0	0	2	0.6
	Obsessive compulsive disorder	2	1.1	1	0.7	3	0.9
	Specific phobias	1	0.6	1	0.7	2	0.6
	Conduct disorder	1	0.6	2	1.4	3	0.9
	Post-traumatic stress disorder	1	0.6	0	0	1	0.3
	Psychotic disorder	0	0.0	1	0.7	1	0.3
	Other	2	1.1	0	0	2	0.6
4th comorbidity
	None	166	95.4	145	99.3	311	97.2	.135^d
	Depressive disorder	2	1.1	0	0	2	0.6
	Social phobia	1	0.6	0	0	1	0.3
	Generalized anxiety disorder	1	0.6	0	0	1	0.3
	Oppositional defiant disorder	1	0.6	0	0	1	0.3
	Performance anxiety	0	0	1	0.7	1	0.3
	Other	3	1.7	0	0	3	0.9
Ages at diagnosis of internalization and externalization comorbidities (months)
1st comorbidity
	Mean	121.9		113.3		119.5		.184^e
	Standard deviation	35.5		33.3		35		.184^e
2nd comorbidity
	Mean	143.8		125.2		139.7		.086^e
	Standard deviation	37.4		32.3		36.9		.086^e
3rd comorbidity
	Mean	155.2		139.7		151.8		.386^e
	Standard deviation	40.1		28.9		38		.386^e
4th comorbidity
	Median	188		164		176		.827^c
	1st and 3rd quartiles	155–210		164–164		156.5-207.5		.827^c
^a: Column percentage ^b: Chi-square test ^c: Mann-Whitney U test ^d: Exact test ^e: Independent groups t-test

When examining the relationships between the timing of internalizing and externalizing comorbidities and clinical features, several findings were observed (See Table 4). The timing of most comorbidities showed a moderate positive association with the age of children with ADHD, the age at notification of ADHD symptoms, the age at diagnosis of ADHD, and the age at initiation of ADHD medication. This suggests that as the age of the child increases, the likelihood of developing comorbidities also increases. However, there was a mild negative association between the timing of the first and second comorbidities and SLD, indicating that children with SLD tend to develop comorbidities at an earlier age compared to those without SLD. Scale scores based on parental reporting did not show significant associations with the timing of comorbidities. On the other hand, the oppositional and hyperactive/impulsive subscale scores of the CTRS were mildly negatively correlated with the timing of the first comorbidity. This suggests that higher levels of oppositional and hyperactive/impulsive symptoms may be associated with an earlier onset of comorbidities. Furthermore, all indexes calculated based on the CTRS, such as the ADHD index and Conners’ global indexes (restless/impulsive, emotional lability, and total indexes), were mildly negatively associated with the timing of the first comorbidity. This indicates that higher symptom severity on the CTRS may be related to an earlier occurrence of comorbidities. Additionally, the timing of the first, second, and third comorbidities showed a high positive correlation with each other, suggesting that the timing of comorbidities tends to be consistent across multiple comorbid conditions.

Table 4

The relationships between the timing of internalization and externalization comorbidities and clinical features
		Ages at diagnosis of internalization and externalization comorbidities
		1st comorbidity	2nd comorbidity	3rd comorbidity	4th comorbidity
Age	rho	0.486	0.445	0.336	0.927
Age	p	< .001	< .001	.086	.001
Age at notification of ADHD symptoms	rho	0.469	0.319	0.583	0.683
Age at notification of ADHD symptoms	p	< .001	.008	.001	.062
Age at diagnosis of ADHD	rho	0.557	0.331	0.526	0.682
Age at diagnosis of ADHD	p	< .001	.006	.005	.062
Age at initiation of ADHD medication	rho	0.571	0.346	0.456	0.562
Age at initiation of ADHD medication	p	< .001	.004	.017	.147
Specific learning disorders	rho	-0.259	-0.264	-0.152	-0.109
Specific learning disorders	p	.002	.030	.448	.797
Conners’ Teacher Rating Scale/Revised Long Form
Oppositional subscale scores	rho	-0.212	-0.205	-0.075	-0.400
Oppositional subscale scores	p	.049	.193	.784	.600
Cognitive problems subscale scores	rho	-0.011	0.101	-0.077	0.500
Cognitive problems subscale scores	p	.922	.558	.785	.667
Hyperactive/impulsive subscale scores	rho	-0.316	-0.289	-0.370	-0.600
Hyperactive/impulsive subscale scores	p	.003	.063	.159	.400
ADHD index	rho	-0.240	-0.006	-0.343	-0.800
ADHD index	p	.026	.971	.194	.200
Conners’ global index-restless/impulsive	rho	-0.248	-0.133	-0.388	-0.800
Conners’ global index-restless/impulsive	p	.020	.408	.138	.200
Conners’ global index-emotional lability	rho	-0.223	-0.161	-0.209	-0.316
Conners’ global index-emotional lability	p	.038	.310	.437	.684
Conners’ global index-total	rho	-0.274	-0.148	-0.321	-0.400
Conners’ global index-total	p	.011	.357	.226	.600
4th comorbidity	rho	0.683	0.643	0.571
4th comorbidity	p	.062	.086	.139
3rd comorbidity	rho	0.732	0.765
3rd comorbidity	p	< .001	< .001
2nd comorbidity	rho	0.798
2nd comorbidity	p	< .001
ADHD: Attention deficit hyperactivity disorder

The results of the logistic regression analysis revealed that the age (in months) at the first diagnosis of internalization or externalization comorbidity in children with ADHD was significantly predicted by two variables: age and SLD (See Table 5). The predictor variable age had a positive effect (β = 0.332, p = .004, 95% CI: 1.112–1.747), indicating that older age was associated with a later onset of comorbidity. On the other hand, the presence of SLD had a negative effect (β=-2.003, p = .001, 95% CI: 0.043–0.419), suggesting that children with ADHD and SLD were more likely to experience an earlier onset of comorbidity. Other variables included in the analysis did not show statistically significant associations with the timing of comorbidity diagnosis. These findings indicate that age and the presence of SLD are important predictors for the age at which children with ADHD develop comorbid psychiatric disorders.

Table 5

Additional factors potentially linked to the age at the first diagnosis of internalization or externalization comorbidity in children diagnosed with ADHD by using logistic regression analysis
							95% CI Exp(B)
	B	SE	Wald	df	p	Exp(B)	Lower	Upper
Age	0.332	0.115	8.324	1	.004	1.394	1.112	1.747
Specific learning disorders	-2.003	0.579	11.986	1	.001	0.135	0.043	0.419
Age at notification of ADHD symptoms	0.082	0.137	0.355	1	.551	1.085	0.829	1.421
CTRS/RLF Conners’ global index-total	-0.001	0.039	< 0.001	1	.984	0.999	0.926	1.078
ADHD: Attention deficit hyperactivity disorder CTRS/RLF: Conners’ Teacher Rating Scale/Revised Long Form SE: Standard error

We compared the sociodemographic and clinical characteristics, the rates of psychiatric comorbidities, the rates of other accompanying neurodevelopmental disorders, distribution and occurrence time of internalizing and externalizing comorbidities among boys and girls with ADHD. We also investigated additional factors potentially linked to the age at the first diagnosis of internalization or externalization comorbidity in children diagnosed with ADHD. These can help clinicians provide a more personalized treatment modality using age and sex-related comorbidity profiles and associated clinical variables.

In our clinical sample, which included a nearly equal number of females, females diagnosed with ADHD were younger than males. However, in a community-based sample where males outnumbered females (79.4% males vs. 20.6% females), it was found that males with ADHD were younger (Jensen & Steinhausen, 2015a, 2015b). In a different clinical study with a male-to-female ratio of 3 to 1, girls and boys with ADHD showed similar ages (Ghanizadeh, 2009). This finding may be attributed to the specific characteristics of the sample used in the study. According to Slobodin and Davidovitch (2019), some authors have concluded that the clinical correlates of ADHD do not seem to be influenced by sex in non-referred children. This implies that the observed differences between boys and girls with ADHD may arise from the process of being clinic-referred for clinical evaluation rather than inherent sex-related variations in ADHD characteristics (Slobodin & Davidovitch, 2019). The authors suggest that differences may exist between girls with ADHD in outpatient clinics and those in community samples regarding ADHD subtypes, intelligence level, rates of ID, speech disorders, and comorbid psychiatric disorders. These disparities may indicate that girls facing more significant functional impairments associated with clinical features are more likely to be referred to outpatient clinics at an earlier stage. Therefore, it is not surprising that in our study, contrary to epidemiological studies, the most common subtype in both sexes was found to be the combined type (Mowlem et al., 2019). Similarly, girls with ADHD tended to have lower IQ scores than boys, consistent with the literature (De Rossi et al., 2022; Gaub & Carlson, 1997). Our results may be attributed to the use of an outdated assessment tool such as the WISC-R rather than reflecting the current situation. It has been suggested that the WISC-R norm indicates that males generally perform better than females on most subtests (Reynolds & Jensen, 1983). Therefore, it is crucial to utilize modern IQ measures (WISC-V, DAS-II, etc.) to provide a more accurate and fair assessment of intelligence across sexes. One study reported that no differences were found in terms of ADHD and comorbid psychiatric disorders according to IQ levels (Katusic et al., 2011). The examination of sex differences in teacher reports, but not parents’, using the Conners rating scales, revealed that boys exhibited higher levels of oppositional, and hyperactive/impulsive symptoms compared to girls. Unlike our results, the results of previous studies revealed that among clinic-referred children, girls demonstrated higher levels of inattention symptoms compared to boys. However, there were no significant differences between boys and girls when it came to impulsivity and hyperactivity; both sexes were equally impaired in these aspects (Slobodin & Davidovitch, 2019). Contrary to others suggesting that sex differences on ADHD-related symptoms may arise from referral sources (eg, clinic-referred versus community-referred), research has demonstrated that endophenotypes such as cognitive features could be the cause of these differences (Arnett et al., 2015). Because the girls in our sample were younger than the boys, differences in boys may be related to an endophenotype associated with the trait of impulsivity rather than delay in girls’ referral. Whether sex differences in ADHD symptoms are due to genetics and impulsivity predispositions should be investigated in the future (Kerekes et al., 2013).

Based on our findings, 66.5% of children with ADHD had at least one comorbid psychiatric disorder. We also showed that 83.5% and 45.9% of females and males with ADHD, respectively, had at least one comorbid disorder, and that females had more comorbidities than males. Although females’ rate was almost twice that of males, all comorbidity rates in our sample were close to those in previous studies (Mohammadi et al., 2021; Tung et al., 2016). Contrary to studies indicating that there is no difference in comorbidity rates according to sex, our finding in favor of girls can be attributed to the frequent occurrence of other neurodevelopmental disorders along with ADHD in the girls in our sample (Pingali & Sunderajan, 2014; Takeda et al., 2012). When the frequency of other neurodevelopmental disorders in the sample was examined, it was seen that the most common learning disorders were followed by speech disorders and ID. Comorbidity between ADHD and specific learning disorders, such as other neurodevelopmental disorders, may be attributed to shared genes with pleiotropic effects. Additionally, this connection might be influenced by factors related to slow processing speed (Tistarelli et al., 2020). Although it was stated that this relationship was more pronounced in males than in females, we did not find any difference in the rates of learning disabilities between girls and boys with ADHD (Willcutt & Pennington, 2000). When assessed by sex, speech disorders and ID were significantly more prevalent in girls, similar to the findings of Ottosen et al. (Ottosen et al., 2019). The higher rates of comorbidity between ADHD symptoms and ID in girls may be explained by phenotypic overlap. In a population-based sample study investigating the comorbidities of ADHD, the prevalence of each neurodevelopmental disorder was notably lower than the rates we identified, with a clear bias favoring males (Mohammadi et al., 2021). In clinical samples where girls are represented at least as much as boys, ADHD may be accompanied by other neurodevelopmental disorders at high rates in both girls and boys. Among the first developing comorbidities (at 119.5 months), anxiety disorders and behavioral disorders with prevalences of 18.7% and 10.7% were the most prevalent group of comorbidities, respectively, and depressive disorder with 8.1% was the first rank comorbid disorder. When both groups and each were evaluated, it was seen that the rankings of the second developing comorbidities (at 139.7 months) were similar. In parallel with the literature suggesting an increase in internalizing disorders with age, depressive disorder also consistently ranked first among the third and fourth comorbidities, developing at 151.8 and 176 months, respectively (Mohammadi et al., 2021). Both sexes exhibited a similar temporal sequence in the development of comorbidities. Contrary to the general belief in the literature, both internalizing and externalizing disorders were significantly more common in girls than boys. Comorbidities between ADHD and internalizing/externalizing disorders, such as depression, social phobia (performance anxiety) and conduct disorder, may be the result of common genetic and non-shared environmental influences (Tistarelli et al., 2020). The investigation of the overlap between ADHD and psychiatric comorbidities using candidate endophenotypes in girls should be the focal point of future research.

It is known that accompanying externalizing and internalizing symptoms are associated with the age of onset and severity of ADHD clinical presentation (Connor et al., 2003). Our findings also indicate that as the age at follow-up, age at notification of ADHD symptoms, age at ADHD diagnosis, and age at initiation of ADHD medication increase, internalizing and externalizing problems emerge later. Therefore, it can be concluded that the onset of psychiatric comorbidities is also delayed when ADHD symptoms manifest later. Thus, as age increases, comorbidity rates may show an increase (Mohammadi et al., 2021). The occurrence of psychiatric comorbidities at earlier ages was linked to higher rates of teacher-reported child oppositionality, hyperactivity, and impulsive symptoms. Additionally, based on teachers’ reports, earlier ages of onset of psychiatric comorbidities were correlated with the severity of ADHD symptoms and emotional lability. Emotional lability is associated with an intensified expression of the core symptoms of ADHD, especially hyperactivity-impulsivity, and an augmented presence of comorbid psychopathological symptoms, including oppositional behaviors, affective symptoms, and substance abuse (Sobanski et al., 2010). We also suggest that internalizing and externalizing problems tend to emerge at an earlier stage when comorbid specific learning disorders are present. It is necessary to investigate whether the acceleration of the emergence of internalizing and externalizing problems in ADHD with comorbid specific learning disorders occurs in a shared etiopathogenesis linked to an endophenotypic feature, such as poor cognitive characteristics, in addition to environmental risk factors like social and emotional difficulties (Kamari & Bonti, 2023).

Limitations/ Future Directions

The study’s retrospective design, relying on historical data, introduces the potential for recall bias and limits the establishment of causation. Prospective longitudinal designs in future research could offer a clearer understanding of the temporal relationships between ADHD and comorbid psychiatric disorders. Additionally, the study’s focus on a specific age group (6–18 years) may restrict generalizability, prompting the suggestion for future investigations to encompass a more diverse age range to capture developmental nuances. Due to the naturalistic aspect of the study, children with neurodevelopmental disorders such as ID and speech disorders were not excluded. While the study highlights sex differences in comorbidity prevalence, further exploration into psychosocial and biological factors influencing these differences is necessary. The use of standardized assessment tools in the study could be complemented by incorporating additional measures, such as modern IQ measures, neuropsychological assessments or qualitative interviews, to provide a more comprehensive understanding of cognitive and behavioral aspects related to comorbidities. The study’s findings may be influenced by the sample’s sociodemographic characteristics, emphasizing the importance of including a more diverse participant pool for enhanced generalizability. Addressing these considerations in future research will contribute to a more nuanced understanding of comorbid psychiatric disorders in individuals with ADHD.

The results of this study provide important insights into sex differences, the frequency of comorbidities, and associated clinical features in children diagnosed with ADHD. Additionally, in each time frame, depression being the most commonly encountered comorbidity in both sexes, coupled with heightened impulsivity in this population, necessitates careful consideration for suicide risk during the assessment and treatment phases. These findings may shed light on understanding the impact of sex and chronological age on the clinical characteristics of ADHD and accompanying comorbidities, guiding future research.

Conflict of Interest

None of the authors have any conflicts of interest or financial ties to disclose.

Ethical Approval

The research protocol was approved by the ethics committee of Ankara University, and the study was conducted in accordance with the Declaration of Helsinki.

Funding

This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author Contribution

SDU: Project management, research design, data analysis, and leadership of the writing process.ZTK: Literature review, data collection and analysis, interpretation of results.RDT: Data collection, data analysis.MÇU: Data analysis, interpretation of results, writing and editing.EY: Literature review, writing and discussion of results.DBÖ: Writing and evaluation of results.TMB: Data collection, literature review.GYE: Data collection, writing.BGK: Project management, supervision.All authors have read and approved the final manuscript.

Acknowledgement

None

Data Availability

The data set used can be accessed by contacting the corresponding author.

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No competing interests reported.

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A Naturalistic Follow-up Study Focusing on Potential Sex Differences in Children and Adolescents with ADHD and Co-occurring Psychiatric Disorders

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