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Prevalence and comorbidity of attention deficit hyperactivity disorder in Chinese school-attending students aged 6–16: a national survey

Annals of General Psychiatry volume 24, Article number: 23 (2025) Cite this article

Abstract

Background

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Despite its significance, no large-scale epidemiological study assessing ADHD, and its associated comorbidities in children and adolescents has been conducted in China.

Methods

Within a national epidemiological survey of 73,992 children and adolescents aged between 6 and 16 in China, we used the CBCL, MINI-KID, and DSM-IV to identify ADHD and its comorbid conditions. Chi-square tests were utilized to compare the prevalence estimates across varied age and sex groups.

Results

The overall ADHD prevalence was estimated at 6.4% (95% CI: 6.2–7.0%). Broken down by subtypes, ADHD-I had a prevalence of 3.9%, ADHD-C was at 1.7%, and ADHD-H was at 0.9%. Boys and the younger age bracket recorded higher prevalence rates for ADHD and its subtypes (p < 0.001). Among ADHD-diagnosed individuals, 53% exhibited at least one comorbid psychiatric disorder. Oppositional defiant disorder/conduct disorder (ODD/CD) was the most prevalent comorbidity for ADHD-C and ADHD-H, at 58%, while anxiety disorders, at 17%, were predominant among ADHD-I cases. ODD/CD was notably higher among younger subjects (p < 0.001). In contrast, anxiety disorders were more frequent in older children and in girls (p < 0.001). Tic disorders showed a higher prevalence in younger boys, whereas mood and substance use disorders were more common in older boys (p < 0.001).

Conclusions

ADHD is a common neurodevelopmental disorder with high comorbidity rates that vary substantially across subtypes, age, and sex. These clinical heterogeneities complicate management and highlight the need for tailored interventions.

Introduction

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder, characterized by developmentally inappropriate and impairing symptoms of inattention, motor hyperactivity, and impulsivity [1]. The manifestations of ADHD are typically pronounced in school-aged children. ADHD appears more frequently in boys than in girls and often persists into adulthood [2]. Based on the predominant symptoms, ADHD can be categorized into three subtypes: predominantly inattentive (ADHD-I), predominantly hyperactive-impulsive (ADHD-H), and combined (ADHD-C) [3]. ADHD profoundly impacts various domains of health-related quality of life in affected children and adolescents [4]. Children with ADHD, compared with those without, were found to be impaired in psychosocial, educational, and neuropsychological functioning [5]. ADHD also places a serious economic burden on families and societies [6].

In a meta-analysis of 175 studies (including 1,023,071 subjects over 36 years), the estimated pooled prevalence of ADHD was 7.2% (95% CI: 6.7 to 7.8) worldwide [7]. However, the prevalence of ADHD as reported in various studies can vary, depending on the diagnostic criteria used and the specific populations being studied. It is noteworthy that the prevalence of ADHD in the United States was often reported to be higher than that in European countries [7]. Furthermore, a marked rise has been reported in ADHD diagnoses in the United States over the last years. Specifically, the estimated prevalence surged from 6.1% in 1997–1998 to 10.2% in 2015–2016 [8]. In Asian countries, recent studies have identified an ADHD prevalence of 8.5% among Korean children aged 7–12 in a community population [9], and 4% among Iranian children and adolescents aged between 6 and 18 years [10]. While definitive data about ADHD prevalence among children and adolescents in China remains elusive, several regional surveys have been undertaken. In Sichuan Province, a study of 20,752 students aged 6–16 found an ADHD prevalence of 5.37%, with subtype distributions as followed: ADHD-I at 3.20%, ADHD-H at 0.75%, and ADHD-C at 1.43% [11]; Another study in Hunan Province, which assessed 17,071 students of the same age range, reported an ADHD prevalence of 4.96% [12]. A meta-analysis consolidating 67 studies deduced an overall ADHD prevalence of 6.26% (95% CI: 5.36–7.22%) among children and adolescents in China, with ADHD-I emerging as the predominant subtype. Notably, the above mentioned results exhibited significant heterogeneity, attributable in part to geographic factors and information sources [13].

Comorbidities are common among ADHD patients, complicating diagnosis and management [14]. In a multicenter observational study, two-thirds of ADHD patients had at least one concurrent psychiatric disorder, such as learning disorders (56%), sleep disorders (23%), oppositional defiant disorder (ODD) (20%), and anxiety disorders (12%) [15]. Other prevalent comorbidities with ADHD included conduct disorder (CD), mood disorders, substance use disorders, and tic disorders [16]. Regional Chinese surveys similarly identified ODD, CD, and anxiety disorders as frequent comorbidities [11, 12]. Particularly, those diagnosed with ADHD-C or with severe impairments were more likely to present comorbid conditions [15]. However, the pattern of comorbidities of different ADHD subtypes is still unclear. Furthermore, comorbidities might be influenced by demographic factors such as age and sex [17]. Thus, a nationwide survey is needed to present the comorbid conditions of ADHD and its subtypes.

Utilizing a nationwide epidemiological survey that aimed to research psychiatric disorders (ADHD included) in children and adolescents in China, our team has reported an overall prevalence of ADHD of 6.4% (95% CI: 6.2–7.0). The purpose of this study was to further investigate the prevalence and comorbidities of ADHD and its subtypes, meanwhile exploring the effect of age and sex.

Methods

Samples and procedure

This study was part of a national survey among Chinese school (including primary school and middle school) students aged 6–16 years. The national survey utilized a multistage cluster stratified random sampling approach. According to the level of gross domestic product (GDP), a total of five areas, including Beijing city (BJ), which is representative of a developed area, and the other 4 provinces, including Liaoning Province (LN), Jiangsu Province (JS), Sichuan Province (SC), and Hunan Province (HN), are representative of developing areas. Every 2–4 prefecture divisions were randomly selected from the above areas, and a total of 15 divisions were enrolled. Then, 169 schools (81 primary schools and 88 middle schools) were randomly picked, and in each grade, classes 2–5 were randomly chosen. Finally, a total of 73,992 students in 1764 classes were enrolled in this survey (See Fig. 1).

Fig. 1
figure 1

The flowchart for the procedures of the survey

Note: CBCL: Child Behavior Checklist; MINI-Kid: Mini International Neuropsychiatric Interview for Children and Adolescents; ADHD: Attention deficit hyperactivity disorder; ADHD-I: the predominantly inattentive type; ADHD-H: the predominantly hyperactive-impulsive type; ADHD-C: the combined type

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The current study has two stages. In the first stage, the Achenbach’s Child Behavior Checklist (CBCL) was adopted as a screening tool. Participants with scores of all total problem in CBCL above 35 were identified as high-risk individuals in mental disorders. The second stage involved the administration of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) and the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV). The participants in this stage included high-risk individuals as well as 5% nonhigh-risk individuals. Participants first completed the MINI-KID, and only those with a positive result were subsequently evaluated by trained psychiatrists using DSM-IV criteria. In the rare cases where DSM-IV criteria were not met, the diagnosis was not confirmed. A diagnosis was considered valid only when both MINI-KID and DSM-IV criteria were satisfied.

The cutoff for the total problem score in the CBCL was set at 35, following Liu et al.’s suggestion [18], and it was the 90th percentile of the CBCL Total Problems score for the entire sample. The cutoff was also reported to have the overall correct classification rate of 88%, with a sensitivity of 86% and specificity of 89% for ADHD [18]. In addition, the 5% of the CBCL negative participants were selected to assess the false negative rate of CBCL, and these individuals were selected by simple random selection [19]. In our dataset, among these negative participants, only 5.5% were diagnosed with at least one mental disorder (Li et al., 2021) [19].

The second stage was taken approximately 2 weeks after the first stage. The duration of data collection was from October 2014 to March 2015. The detailed procedure and study protocol are provided in our previous study [19, 20].

Screening scales

CBCL: The CBCL is accepted as an excellent instrument for mental health problem in children [21], which has 118 items, providing scores for three broad-band scales: internalizing (sum of withdrawn, somatic complaints, and anxious/depressed subscales), externalizing (sum of attention problems and aggressive and delinquent behavior subscales), and total behavior problems. Each item is scored on a three-point Likert scale (0 = not true, 1 = somewhat or sometimes true, or 2 = very true or often true) [22, 23]. The higher score indicated more severe mental problems. Our study used the Chinese version CBCL revised by Shanghai Mental Health Center, suitable for children aged 4–16 [24], The Chinese version of the CBCL has been shown to have good reliability and validity [24, 25]. The parents or other caregivers of the enrolled children or adolescents completed the CBCL. The age groups in the previous studies related to CBCL were 6–11 and 12–16 years [18, 20, 26], and we used these age group settings in the analysis throughout the study.

MINI-KID: The MINI-KID is a structured instrument for assessing the presence of psychiatric disorders in children and adolescents 6–17 years old and was developed by Sheehan and his colleagues in 1998 [27].The assessment tool, divided into diagnostic sections or modules, must be applied by trained psychiatrists. Twenty-four psychiatric disorders (based on DSM-IV and International Classification of Diseases-10) and suicidality were included in the interview. Each disorder is screened by answering 2 to 4 questions. Other symptoms will be asked only if the screening questions are positively answered. All the questions are only answered by “yes” or “no”. The parent version of the MINI-KID (MINI-KID-P) was also adopted as an additional reference. The parent or caregiver and the child both present the interview at the same time. The Chinese version of the MINI-KID-P and MINI-KID were used in this survey, translated from MINI-KID English version 5.0 [28, 29]. The concordance of MINI-KID-P and MINI-KID was good. The MINI-KID and MINI-KID–P both have good reliability and validity for assessing psychiatric disorders in children and adolescents, high concordance with DSM-IV assessment by psychiatrists [27]. Potential diagnoses were considered present when they met the criteria on either the parent or child version. The psychiatric disorders in MINI-KID are divided into 5 categories: attention-deficit and disruptive disorders (including ADHD, ODD and CD), anxiety disorders, tic disorders (including Tourette’s syndrome, chronic motor tic disorder, chronic vocal tic disorder, and transient tic disorder), mood disorders, substance use disorders and other mental disorders (including bulimia nervosa, anorexia nervosa, adjustment disorder, psychotic disorders, and pervasive developmental disorder).

Statistical analysis

First, the distribution of the sample in terms of sex, age, region, and screening stages was described. Second, based on all participants included in this study, the point prevalence rates of ADHD (including ADHD-I/ADHD-H/ADHD-C) were estimated. Sex and age’s effects on the prevalence rates of ADHD (including ADHD-I/ADHD-H/ADHD-C) were then calculated using chi-square tests. Third, the proportions of comorbidities for ADHD (including ADHD-I/ADHD-H/ADHD-C) were estimated. The differences in the proportions of comorbidities by sex and age groups were also calculated using chi-square tests. When sex and age groups were analyzed as binary variables, the degrees of freedom of the chi-square test were all 1. And when the age groups were analyzed as 11 categorical variables, the degrees of freedom of the chi-square test were 10. All statistical tests were conducted using the two-tailed approach with a significance level of 0.05. Data analyses were performed using JMP Pro 17.0 in this study.

Results

Sample description

A total of 73,992 participants aged 6–16 years were enrolled by cluster sampling and screened by CBCL in the first stage. Among them, 36,893(49.9%) were males, 33,875(45.8%) aged 6-11years, and 10,549(14.3%) resided in developed area. However, 1885 participants refused to attend the interview. A total of 72,107 completed the CBCL in the first stage. In addition, 178 participants were excluded because the CBCL was completed by themselves or their teachers instead of their caregivers. We found missing data with a proportion of 0.35% (less than 0.5%) in the whole sample of 73,992, which were excluded from further analyses.

In the second stage, a total of 17,524 individuals were included, which was consistent with the 14,653 high-risk individuals in mental disorders by CBCL and a randomly selected group of 2871 non-high-risk individuals (5.0% of the entire sample) for distributional difference. Finally, a total of 13,030 patients were diagnosed with at least one disorder after the MINI-KID screening and psychiatrists diagnosed according to the DSM-IV. A total of 4574 individuals were diagnosed with ADHD (including 2761 with ADHD-I, 623 with ADHD-I, and 1190 with ADHD-C) (See Fig. 1).

Point prevalence of ADHD and its subtypes

The point prevalence of ADHD was 6.4% (95% CI: 6.2-7.0). The point prevalence of ADHD-I, ADHD-H and ADHD-C were 3.9%, 0.9% and 1.7%, respectively.

Sex effects on the prevalence of ADHD and its subtypes

Given the high prevalence of ADHD, we further investigated relevant factors of ADHD, namely, sex and age. Table 1 shows the prevalence rates of ADHD and its subtypes in girls and boys. For boys, the prevalence rate of ADHD was 8.08%, which was higher than that for girls at 4.57%. The difference in ADHD between boys and girls was statistically significant (χ2 = 15960.31, p < 0.001). An analogous analysis on the prevalence of its subtypes revealed a similar conclusion. We found that all subtypes appeared to be significantly more prominent in the boys’ group than in the girls’ group (ADHD-I: boys 4.75% versus girls 2.90%, χ2 = 167.52, p < 0.001; ADHD-H: boys 1.25% versus girls 0.47%, χ2 = 130.20, p < 0.001; ADHD-C: boys 2.08% versus girls 1.21%, χ2 = 85.12, p < 0.001;).

Table 1 Sex difference in the prevalence of ADHD and its subtypes
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Age effects on the prevalence of ADHD and its subtypes

Concerning the age differences, our results on the prevalence of ADHD and its subtypes among children and adolescent groups can be seen in Table 2. We found that the prevalence of ADHD in children was prominently higher than that in adolescents (children aged 6–11 years old: 8.09% versus adolescent aged 12–16 years: 4.84%, χ2 = 318.29, p < 0.001). Similarly, the prevalence of all subtypes was significantly higher in the children group (ADHD-I: children 4.47% versus adolescent 3.28%, χ2 = 68.37, p < 0.001; ADHD-H: children 1.00% versus adolescent 0.74%, χ2 = 14.36, p < 0.001; ADHD-C: children 2.62% versus adolescent 0.82%, χ2 = 358.15, p < 0.001;).

Table 2 Age difference in the prevalence of ADHD and its subtypes
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The prevalence rates of ADHD and its subtypes at each age point are illustrated in Fig. 2 and Table S1. The highest point prevalence rates of ADHD, ADHD-I and ADHD-C were all found to be 8 years old. However, the highest point prevalence rate of ADHD-H was 6 years old.

Fig. 2
figure 2

The trend with age for the prevalence of ADHD and its subtypes

Note: ADHD: attention deficit hyperactivity disorder; ADHD-I: the predominantly inattentive type; ADHD-H: the predominantly hyperactive-impulsive type; ADHD-C: the combined type

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Comorbidities of ADHD and its subtypes

ADHD patients have comorbidity rates of 52.95% with at least one psychiatric disorder. ADHD-I, ADHD-H, ADHD-C have comorbidity rates of 33.54%, 87.16%,and 80.08%, respectively.

Comorbidities of ADHD and its subtype are shown in Figs. 3. The proportions of ADHD comorbidities were as follows: ODD/CD(24.36%), anxiety disorders (15.57%), tic disorders (6.62%), substance use disorders (6.19%) and mood disorders (4.90%). The proportions of ADHD-I comorbidities were as follows: anxiety disorders (17.17%), tic disorders (7.32%), substance use disorders (6.30%), mood disorders (3.73%), ODD/CD (2.50%). The proportions of ADHD-H comorbidities were as follows: ODD/CD (58.11%), anxiety disorders (16.69%), tic disorders (10.75%), substance use disorders (8.83%), and mood disorders (4.49%). The proportions of ADHD-C comorbidities were as follows: ODD/CD (57.39%), anxiety disorders (11.26%), mood disorders (7.82%), substance use disorders (4.54%), and tic disorders (2.86%).

Fig. 3
figure 3

The comorbidity of ADHD and its subtypes

Note: ADHD: attention deficit hyperactivity disorder; ADHD-I: the predominantly inattentive type; ADHD-H: the predominantly hyperactive-impulsive type; ADHD-C: the combined type; ODD: oppositional defiant disorder; CD: conduct disorder

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Other mental disorders (bulimia nervosa, anorexia nervosa, adjustment disorder, psychotic disorders, and pervasive developmental disorder), were not found as ADHD comorbidities in our studies.

Considering the influence of gender on the comorbidities, tic disorders, substance use disorders and mood disorders were more common among boys than girls (8.37% vs. 3.49%, 7.72% vs. 3.43% and 5.95% vs. 3.00%, p < 0.001), but anxiety disorders had a higher rate among girls (22.71% vs. 11.60%, p < 0.001) (see Table 3).

Table 3 Sex difference in proportions of ADHD comorbidities
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It was also shown that age had a meaningful effect on the pattern of comorbidities. ODD/CD, and tic disorders were more prevalent among the younger group of participants (31.29% vs. 14.38%, and 9.01% vs. 3.20%, p < 0.001), but anxiety disorders, substance use disorders and mood disorders was more common among the older group of participants (21.04% vs.11.75%, 9.11% vs. 4.15% and 9.80% vs. 1.48%, p < 0.001) (see Table 4).

Table 4 Age difference in proportions of ADHD comorbidities
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Discussion

This study represents the first nationwide exploration into the prevalence of ADHD among school students aged 6–16 years in China. We found an ADHD prevalence of 6.4%. Among the subtypes, ADHD-I recorded the highest prevalence at 3.9%, followed by ADHD-C at 1.7%, and ADHD-H at 0.9%. Notably, ADHD was more prevalent among males and younger individuals. Moreover, we observed a significant comorbidity rate of 53% for ADHD patients, indicating they had at least one other psychiatric disorder. The most common comorbidities were ODD/CD and anxiety disorders, with prevalence rates of 24% and 16%, respectively. It is also worth noticing that comorbidity rates varied across different ADHD subtypes, age groups, and genders.

The ADHD prevalence found in our study aligned closely with findings from two recent meta-analyses in China, both of which reported a pooled prevalence of 6.3% for ADHD among children and adolescents [13, 30]. Furthermore, our findings resonated with global prevalence rates, which were estimated to be between 2.2% and 7.2% in previous meta-analyses [7, 31,32,33]. Overall, particularly when compared to some European countries, the prevalence of ADHD in China appears relatively higher.

This relatively higher prevalence in the Chinese population could be attributed to several factors. Firstly, methodological differences across regions may contribute to discrepancies in ADHD prevalence rates. For example, the DSM-IV diagnostic criteria used in our study are less stringent than those in the International Classification of Diseases, 10th Edition (ICD-10), potentially leading to higher reported rates [34]. Secondly, certain socio-cultural factors may influence ADHD prevalence [35]. The heightened academic pressures inherent in China’s competitive educational system may exacerbate the number of school-aged children and adolescents exhibiting ADHD symptoms [30]. Moreover, a longitudinal twin study suggested that genetic factors contributing to ADHD symptoms appear to be less significant in Chinese populations, while shared environmental influences are more pronounced compared to Western populations [36].

In contrast, the prevalence observed in our study is lower than the 10.2% reported in the United States, which can potentially be explained by two factors [8]. First, the U.S. study relied on parent-reported diagnoses, whereas our findings are based on clinical evaluations. Second, compared to China, the higher rates of ADHD diagnosis in the U.S. may reflect greater public awareness, improved access to healthcare services, and supportive policies that promote early identification and diagnosis, including tailored educational resources for students with ADHD.

In line with previous research, ADHD-I emerged as the most prevalent subtype in our sample, followed by ADHD-C, and then ADHD-H [13, 32]. However, individuals with the ADHD-C subtype exhibited greater global functional impairment and were thus more likely to be referred for clinical assessment [15]. As a result, ADHD-C emerged as the subtype clinicians diagnosed most frequently [32]. Alarmingly, fewer than half of the children with ADHD received a diagnosis and appropriate treatment [37]. This pattern hints at the possibility that the primary reason for the low consultation rate, especially concerning ADHD-I, might stem from a lack of understanding or awareness about the disorder among parents and educators [38].

Previous studies consistently indicated significant disparities in ADHD prevalence based on gender. Several studies have reported that ADHD was two to three times more prevalent in boys than in girls [39]. Our study corroborated this trend, revealing a notably higher prevalence of ADHD in boys than in girls (8.08% vs. 4.57%). Explanations for this discrepancy are twofold. Firstly, evidence suggested that ADHD followed a polygenic inheritance pattern [40]. Given that girls may possess a higher genetic predisposition threshold compared to boys, they typically manifest behavioral symptoms only when a larger set of relevant genes come into play [41]. Additionally, boys might inherently display greater impulsivity and heightened externalizing issues, traits that were more readily noticed by parents and teachers. This made it more probable for boys exhibiting ADHD symptoms to be recognized than their female counterparts [20, 42, 43]. The gender disparity was even more pronounced in clinical samples, where the sex ratio was more skewed [39]. Such patterns hint at a potential under-diagnosis of ADHD in girls, complicating timely referrals and diagnosis for affected females.

Previous research has indicated noticeable differences in the prevalence of ADHD depending on the age of participants, a finding also consistent with our study. A recent meta-analysis revealed that 7.6% of children between 3 and 12 years of age were diagnosed with ADHD, while 5.6% of teenagers aged 12 to 18 years had the disorder [44]. Furthermore, another meta-analysis that examined ADHD’s global prevalence among individuals aged 5 to 19 found the highest prevalence at 9 years of age [33]. The above results closely aligned with our findings, as illustrated in Fig. 2, which indicated the peak prevalence of ADHD at 8 years of age. Examining the subtypes further, we found that the highest prevalence for ADHD-H was at 6 years of age. However, the decline in ADHD-I prevalence posted that the age of 8 might not be as pronounced as that of ADHD-C. It supported that inattention symptoms remain fairly stable throughout development, while hyperactivity-impulsivity symptoms tended to decrease with age. Consequently, children initially diagnosed with ADHD-C during early childhood might transition to ADHD-I as they mature, especially if their hyperactivity-impulsivity symptoms fall below the diagnostic benchmark [45]. Future longitudinal studies utilizing population-based samples will offer a clearer validation of this hypothesis. However, another peak in the prevalence of ADHD and the ADHD-I subtype was observed at age 13, though this phenomenon was not found in ADHD-H or ADHD-C subtypes. This additional peak in ADHD prevalence at age 13 aligned with recent research from Iran [10]. A possible explanation is that age 13 often marks the transition from primary to secondary school, a period when academic demands increase and parents’ expectations for their children’s academic abilities become higher. This shift may make attention-related issues more noticeable.

Children and adolescents diagnosed with ADHD often exhibit a high comorbidity rate of 53% with at least one other psychiatric disorder. This rate was even more pronounced in the ADHD-C and ADHD-H subtypes. This pattern of frequent co-occurrence was corroborated by other studies. For instance, national mental disorder surveys conducted in Denmark [46], Italy [15], Iran [10] and the US [47] have documented ADHD co-occurrence rates of 52%, 66%, 61%, and 67% respectively. The underlying mechanism driving this high comorbidity rate between ADHD and other psychiatric disorders remains unclear. One possible reason might be that many other disorders have symptoms of inattention and impulsivity, which can be collocated on the symptom spectrums of ADHD [48]. Clinicians should take these high prevalence rates into account during ADHD diagnosis and treatment. Core ADHD symptoms in children and adolescents were obscured by coexisting conditions, complicating the diagnostic process. Additionally, comorbid disorders significantly shaped the therapeutic approach, long-term prognosis, and eventual outcomes in ADHD cases [15].

Our research indicated that disruptive behavioral disorders (like ODD/CD) and anxiety disorders ranked as the most frequent comorbidities alongside ADHD. In contrast, tic disorders, substance use disorders, and mood disorders manifested at considerably lower frequencies. Examining the ADHD subtypes, ODD/CD emerged as the principal comorbid disorder for ADHD-C and ADHD-H at 58%, while anxiety disorders topped the list for ADHD-I at 17%. This distribution mirrored findings from earlier studies [10, 49]. The symptoms of ADHD-C/ADHD-H and ODD/CD were found to be correlated and changed concurrently [50]. It has also been suggested that ADHD shared dysfunctional brain regions and gene with CD, ODD [51, 52]. ADHD-anxiety comorbidity may develop in part because early symptoms of ADHD contribute to the development of anxiety symptoms [53].

Our analysis has identified significant age and gender effects on comorbidity patterns. ODD/CD and tic disorders were more prevalent in younger participants, aligning with previous research that emphasized a higher incidence of ODD/CD and tic disorders among younger populations [19]. Conversely, anxiety disorders, mood disorders, and substance use disorders were more widespread in older participants. This age-related trend concurred with past research, suggesting that other psychiatric conditions might either be long-term ramifications of ADHD or outcomes stemming from the mistreatment of ADHD-affected children [10, 46]. Gender-wise, tic disorders, mood disorders, and substance use disorders predominantly afflicted boys, whereas anxiety disorders were more prevalent among girls. This gender effect on comorbidity patterns has been highlighted in prior studies, which associated male gender with a heightened risk of neuropsychiatric disorders, while females exhibited a predilection for internalizing disorders [10, 46]. The observed gender-based variability in comorbidity rates could be attributed to differences in epidemiological methods and study populations [54]. Consequently, tailored strategies might be essential when managing ADHD-affected children across different ages and genders.

Strengths and limitations

The current study possesses several strengths. First and foremost, it marks the first nationwide investigation in China into the prevalence and comorbidity of ADHD among children and adolescents. Second, the use of community-based data offers a broad perspective on ADHD prevalence and characteristics in the general population, avoiding the referral bias often seen in hospital-based studies. Additionally, we conducted a detailed analysis of both the prevalence and comorbid traits across various subtypes, segmented by different age and sex groups, a perspective relatively seldom emphasized in prior studies.

However, this study also has its limitations. First, our focus was primarily on students from mainstream schools, inadvertently excluding those in special schools or those who had dropped out. This could lead to an underreporting of ADHD comorbidities, especially in cases where ADHD is accompanied by more severe mental health conditions, including psychotic disorders. We also did not collect data on whether participants were receiving or had previously received treatment for ADHD, which could have influenced the results. Furthermore, the preschool-aged demographic, wherein ADHD prevalence is notably significant [55], was excluded from our research parameters. These exclusions suggested that our results might not encapsulate the entire spectrum of children and adolescents. Moreover, while our study included a large sample size, it was limited to children and adolescents from only five regions in China, leading to within-cluster homogeneity that could introduce additional bias into our results.

Additionally, the MINI-KID assessment did not cover diagnoses such as autism spectrum disorder (ASD), learning disorders, and sleep disorders, so we did not evaluate these conditions despite their known correlation with ADHD in younger populations [15, 46]. Although the MINI-KID assessed the prevalence of PDD, conceptually similar to ASD, we could not evaluate ADHD-ASD comorbidity, as PDD was excluded in the DSM-IV criteria for an ADHD diagnosis. Moreover, we did not record cases where the MINI was positive but did not meet DSM-IV criteria, or vice versa, so diagnoses relied solely on cases meeting both criteria. Lastly, data collection began in 2014 using DSM-IV criteria, as the DSM-V translated into Chinese in 2015, when DSM-V was not yet widely adopted in China. This choice may have affected our results. Compared to the DSM-IV, the DSM-V raised the age of onset to 12 years and replaced subtypes with presentation specifiers, and more children might be diagnosed with ADHD according to the new criteria [44].

Conclusions

The prevalence of ADHD in Chinese school-attending students aged 6–16 years was 6.4%, with ADHD-I identified as the predominant subtype. A clear gender and age predisposition was observed, with significantly higher ADHD prevalence among males and younger children. Notably, over half of ADHD patients exhibited comorbidity with at least one psychiatric disorder, with ODD/CD (24%) and anxiety disorders (16%) being the most common comorbidities. Comorbidity rates varied substantially across subtypes, age groups, and genders. Our findings reinforce that ADHD is not only a prevalent neurodevelopmental disorder but also highly intertwined with comorbid conditions. The elevated comorbidity rates substantially complicate ADHD management, underscoring the necessity for intervention strategies tailored to subtypes, age groups, and genders.

Data availability

The data involved in this study can be obtained by contacting corresponding authors.

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Acknowledgements

We thank all respondents and staff who participated in this research.

Funding

1. This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 82171538, 82001445, 82301731 and the Natural Science Foundation of Beijing Municipality under Grant No. 7212035, 7232057, Beijing Hospitals Authority Youth Programme Grant No. QML20211203.

2. This study was funded by National Commission of Health, the National Twelfth Five-Year Plan for Science and Technology Support of the Chinese Ministry of Science and Technology (2012BAI01B02) and research on prevention and control of major chronic noncommunicable diseases in the Ministry of Science and Technology (2016YFC1306100).

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Authors and Affiliations

  1. Department of Psychiatry, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

    Jingran Liu, Zhongliang Jiang, Yonghua Cui & Ying Li

  2. Key Lab of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China

    Fenghua Li

  3. Department of pediatrics, Beijing Anding Hospital, Capital Medical University, Beijing, China

    Yi Zheng

  4. Big Data Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

    Hui Xu

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  1. Jingran Liu
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Contributions

Jingran Liu was responsible for data collection, data analysis, data interpretation, conceptualisation, visualisation, writing - original draft and writing - editing. Zhongliang Jiang, Fenghua Li, Yi Zheng, Ying Li was responsible for conceptualisation, validation and writing - review. Yonghua Cui and Hui Xu was responsible for project administration, supervision, validation and writing - review&editing.

Corresponding authors

Correspondence to Yonghua Cui or Hui Xu.

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All participants and their parents provided informed consent prior to participation in the study. The study adhered to the principles of the Declaration of Helsinki and received approval from the Ethics Committee of Anding Hospital, Capital Medical University (Project identification code: 2012BAI01B02).

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The authors declare no competing interests.

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Liu, J., Jiang, Z., Li, F. et al. Prevalence and comorbidity of attention deficit hyperactivity disorder in Chinese school-attending students aged 6–16: a national survey. Ann Gen Psychiatry 24, 23 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12991-025-00558-w

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Keywords

Annals of General Psychiatry

ISSN: 1744-859X