Abstract
Introduction
Like in most neurodevelopmental disorder, there is a male preponderance in autism spectrum disorder (ASD). A recent systematic review and meta-analysis by Loomes and colleagues (2017) summarized the prevalence studies on autism and reported a large variability across studies with an overall male-to-female ratio of 4.2:1 in children aged 0–18 years. Intelligence quotient (IQ) has most consistently been associated with the sex difference in autism (Rivet & Matson, 2011), with the proportion of males increasing among participants with higher IQ (Volkmar & Szatmari, 1993). Another factor is the age of participants, in the meta-analysis of Loomes et al. (2017), the male-to-female ratio was higher in the age group over 6 years than under 6 years. Researchers have also related the disparity to differences in genetic background, hormonal status, and neurocognitive development, but with mixed results (May et al., 2019; Rivet & Matson, 2011). Recently, social and cultural factors that might contribute to underidentification of autism in females have been put forward. More specifically, a steep increase is seen in the number of publications on the hypothesis of a “female autistic phenotype” and “camouflaged” autism symptoms in females diagnosed later in life (adolescence or afterwards) (e.g. Bargiela et al., 2016; Hull et al., 2020). Central to this idea is that that there is a female-specific manifestation of autism symptoms and co-occurring traits. Compared to boys/men, girls/women with autism are believed to show relatively higher social motivation, a greater capacity for traditional friendships, fewer repetitive and stereotyped behaviors, less-externalizing behaviors (hyperactivity/impulsivity and conduct problems), yet more internalizing problems (anxiety, depression, and eating disorders) (Bargiela et al., 2016; Hull et al., 2020). Furthermore, girls/women are believed to be inclined, more than boys/men, to hide their autistic behavior by masking and using compensatory strategies (“camouflaging”) to navigate the social world (Lai et al., 2020). As a consequence, girls/females with autism may more often be misdiagnosed (foremost with internalizing and/or personality disorders) or late-diagnosed compared to boys/males with autism. This seems to be especially the case in girls/females at the milder end of the autism spectrum (Lai et al., 2017), in which group, the autistic symptoms are harder to discern from other forms of psychopathology or extremes of normotypic behavior. Despite the apparent clinical validity of this theory, studies on this topic have been mainly conducted with small convenience samples that lack a proper longitudinal case–control design (Fombonne, 2020). One of the alternative explanations for the reported subjective sensations of “pretending” in late-diagnosed females with autism may be social anxiety (Fombonne, 2020).
Consequently, to increase our understanding of sex differences in autism, it is important to have detailed information on these differences in prevalence and course of autistic and comorbid psychopathological symptomatology (i.e. co-occurring internalizing and externalizing symptoms) in autistic persons, while at present, only coarse information is available. Autism has a multifaceted presentation, and it is plausible that sex differences differ along these problem domains within autism; therefore, an analysis of multidomain sex differences is relevant. In addition, a reference sample of same-aged individuals without autism is needed in order to determine if potential sex differences in psychopathology in persons with autism reflect normative (i.e. similar sex differences as in typically developing peers) or autism-specific developmental patterns (i.e. different sex differences compared to typically developing peers). A recent study by Demetriou and colleagues (2021), in which sex differences in cognitive performance shown not to be specific to the autistic group, underlines the importance of the inclusion of a normative group.
In this study, we will focus on sex differences in the development of autism, internalizing (anxiety and depression), attention-deficit/hyperactivity disorder (ADHD) and externalizing (aggression) symptoms in persons with and without a clinical diagnosis of autism from late childhood to early adulthood. In the next paragraph, we will summarize what is already known about sex differences in the developmental course of autism, internalizing, ADHD, and externalizing symptomatology in autistic persons, as well as in the general population.
The course of autistic symptoms during adolescence in males and females
Studies on the developmental course of autistic traits in adolescents in the general population are confined to the social-communicative problem domain of autism. Overall, the literature suggests that boys score higher than girls in early adolescence (Mandy et al., 2018; Robinson et al., 2011); however, the study by Mandy et al. showed an increase in scores in girls from 10 to 16 years that was steeper than in boys. As a result, the sex difference in scores at age 10 disappeared during adolescence. Results on sex differences in autistic symptoms in persons with autism come from cross-sectional studies and are somewhat inconsistent due to a large variability in IQ, age, and autism severity (Fountain et al., 2012; Louwerse et al. 2015; Simonoff et al., 2019; Woodman et al., 2016). In a systematic review and meta-analysis of cross-sectional studies that reported on sex and age differences in symptom severity in the core triad of autism problem domains as measured by—mainly parent report—standardized instruments (in toddlers and pre-schoolers, children, adolescents and adults), Van Wijngaarden-Cremers et al. (2014) reported no sex differences in social behavior and communication problems, but more repetitive and stereotyped behaviors in boys than girls aged 6–18. Kaat et al. (2021) combined several databases to create a large sample of girls and boys with an autism diagnosis to evaluate sex differences in scores on standardized measures of autism symptoms. When matched for age, IQ, and language level, they found minimal sex differences (effect sizes < .20); boys received more severe scores on parent-reported and clinician-administered measures of restricted repetitive behavior. A meta-analysis by Mahendiran et al. (2019) of studies that included a normative comparison group on sex differences in social and communication symptoms in children and adolescents with autism again reported no significant differences between males and females but noted significant heterogeneity in the reviewed studies. Wood-Downie and colleagues (2021) conducted a systematic review and meta-analysis of gender differences on narrow construct domains like social attention and peer relationships and found that autistic females had better social interaction and communication skills than autistic males; for non-autistic individuals, similar gender differences were found. Groups were not matched for IQ. They concluded that standardized measures that are based on broad constructs might not capture these differences which potentially contribute to under recognition of autism in females.
Overall, sex differences in social and communication symptoms as measured by standardized diagnostic instruments in autistic persons seem to be absent. Sex differences found on some subdomains of social interaction, and communication seem to be alike in autistic and non-autistic persons. More repetitive and stereotyped behavior has been reported in males than in females with autism; however, with regard to this symptom domain, we did not find a study which included a normative comparison group.
The course of internalizing, ADHD, and externalizing symptoms during adolescence in males and females
Multiple studies that examined the course of internalizing problems throughout adolescence in the general population have shown that these increase in early adolescence, peak in mid-adolescence and decrease into young adulthood (e.g. Petersen et al., 2018). Females developed higher levels of depressive and anxiety symptoms than males around the onset of puberty (Hankin et al., 1998; Lewinsohn et al., 1998). Distinct gender-specific developmental trajectories of anxiety and depression during adolescence have been identified. With regard to anxiety, females exhibited a slight decrease in symptoms and males exhibited a stable course from mid-to-late adolescence (Legerstee et al., 2013; Ohannessian et al., 2017; Van Oort et al., 2009). A sex difference in the course of depressive symptoms emerged early in adolescence when girls’ symptoms accelerated, whereas boys’ symptoms accelerated later in adolescence, but did not reach female levels of symptoms indicating a stable higher female-to-male preponderance of depressive symptoms (Hankin et al., 2015; Salk et al., 2016). Thus, sex differences in internalizing problems increase during adolescence and this seems to be driven predominantly by depressive problems.
ADHD symptoms on average decline from approximately age 12, with inattention remaining relatively stable or declining at a modest rate, and hyperactivity/impulsivity waning more strongly and remitting more abruptly (Hartman et al., 2016; Vos et al., 2021). Studies on sex-specific ADHD trajectories through adolescence are scarce and showed contradictory results (e.g. Malone et al., 2010; Murray et al., 2019). The developmental course of ADHD symptoms leads to a decline over time in the sex ratio of ADHD (male-to-female ratio of 3:1 in childhood, closer to 1:1 in adulthood; Huang et al., 2016).
Most studies on the course of externalizing problems (aggression and oppositional behavior) in childhood and adolescence have also demonstrated a decline of symptoms with age (e.g. Bongers et al., 2004; Roskam, 2019). With regard to sex differences in externalizing problems in adolescents, Fernandez et al. (2014) found that boys showed higher levels of externalizing symptoms than girls in a large sample from the general population. These symptoms decreased in both groups from age 11 to 15, indicating stable higher externalizing problems in males than females. Other studies converge on this pattern (Bongers et al., 2004; Karriker-Jaffe et al., 2008) and show that higher aggression in males than females is still present in young adulthood (Boyd et al., 2015).
In children and adolescents with autism, higher levels of depressive and anxiety symptoms than in peers in the general population or peers with other developmental disabilities have been reported (Gotham et al., 2015; Kim et al., 2000; Verheij et al., 2015; Woodman et al., 2016). Sex differences in comorbid psychopathology in autistic adolescents have not been investigated thoroughly, with the findings so far summarized mostly based on cross-sectional data, which were heterogeneous in terms of age, intelligence, and autism severity, and with inconsistent results (Holtmann et al., 2007; Nasca et al., 2019; Oswald et al., 2016; Pisula et al., 2017). In a longitudinal study, Gotham and colleagues (2015) compared trajectories of depressive and anxiety symptoms in participants with autism (
Aims and hypotheses of this study
This study aimed to determine if sex differences in developmental trajectories of psychopathology in persons with milder forms of autism differ from normative sex-specific developmental trajectories of psychopathology. To this end, we documented sex-specific developmental trajectories of autistic and non-autistic symptoms from childhood through young adulthood in persons with a
Methods
Sample
The study is based on data from persons with a clinical
Matching
We matched an equally sized subsample of the TRAILS general population sample (normative sample) to the sample of autistic persons on characteristics potentially linked to autism which may confound conclusions: that is, sex, IQ, and SES. To this end, we first ensured that we had an equal number of male and female participants in the clinical and normative sample. IQ was a matching variable given its well-known association with severity of autism and comorbid psychiatric problems. Furthermore, we used SES as a matching variable, as family and social characteristics have been implicated in influencing symptom manifestation as well as clinical interpretation of such symptoms in autistic girls (Kreiser et al., 2014), although few studies have specifically investigated SES in this connection, and its association with symptom severity of autism is currently not clear (Mahendiran et al., 2019). Finally, since TRAILS is a homogeneous age cohort, and followed up at same age-intervals over time, age matching was not a priori necessary, although we checked if the two samples were comparable on age, after matching. We first matched the clinical and normative samples on IQ such that the IQ of the matching participant from the normative sample was within 2 IQ points of the IQ of the autistic participant. Next, of those participants who met this criterion, the participant who had the SES closest to the autistic participant was selected. After matching, mean IQ in the clinical sample was 100.15 (
Demographic characteristics of persons with and without ASD, comparing males and females at T1
a
(mean (
ASD: autism spectrum disorder; IQ: intelligence quotient; SES: socioeconomic status;
Sample size at different waves: T2:
Instruments
To assess cognitive ability, the Vocabulary and Block Design subtests of the
To capture the heterogeneity of problems of children and adolescents with autism, we used the Children’s Social Behavior Questionnaire (CSBQ; Hartman et al., 2006; Luteijn et al., 2000). The parent-reported, 49-item CSBQ is a quantitative measure of autistic traits, with subscales that allow a differentiated description of multitype autistic problems. We report on the four subscales which are the most characteristic of autism as well as two additional subscales: (1)
Internalizing (depression and anxiety), ADHD and externalizing (conduct disorder) symptoms were measured with the
The CSBQ, CBCL, and YSR were administered at T1 (mean age 11.13 years), T2 (mean age 13.12 years), and T3 (mean age 16.02 years). At T4 (mean age 19.05 years), the CSBQ and ASR were administered, and at T5 (mean age 22.06 years) the ABCL.
Data analysis
CSBQ, CBCL, ABCL, YSR, and ASR scores were analyzed using linear mixed modeling (Gardiner et al., 2009). Models contained a random intercept and random slope for age and fixed effects for age at assessment, autism status, sex, and all possible interactions between these variables. The covariance between the random intercept and slope was freely estimated. Age at assessment was continuous and the normative group and males served as reference categories in all models.
In a post hoc analysis, we added IQ as a covariate to adjust for the lower IQ difference that was found to be present between in autistic females compared to autistic males (and through matching also in males and females without ASD). All models were estimated in SPSS, version 26, using maximum likelihood estimation (West, 2009).
To enhance interpretation, we standardized all CSBQ, CBCL, ABCL, YSR, and ASR subdomain scores and mean-centered age.
There was no community involvement in the reported study.
Results
Table 2 provides model estimated means of autistic symptoms, and Figure 1 plots the sex differences in persons with and without ASD. Supplementary Table ST1 provides the regression model estimates and Supplementary Figure SF1 the estimated means separately for males and females with and without ASD. No sex differences for the subscales
Model-estimated means of CSBQ domains in standardized scores of males and females with and without ASD between childhood and young adulthood.
CSBQ: Children’s Social Behavior Questionnaire; ASD: autism spectrum disorder.

Model-estimated CSBQ female versus male differences in standard deviations using linear mixed modeling between childhood and young adulthood in persons with and without ASD.
Internalizing symptoms
Table 3 provides model-estimated means of internalizing, ADHD, and externalizing symptoms, and Figure 2 plots the sex differences in persons with and without ASD. Supplementary Table ST2 provides the regression model estimates, and Supplementary Figure SF2 provides the estimated means separately for males and females with and without ASD. During adolescence, as indicated by two-way sex-by-age interaction effects, self-reported affective and anxiety symptoms increased in females, but decreased in males (Table 3, Figure 2(a) and (b), ST2, and SF2a/b). There were no three-way interaction effects between diagnostic group, sex, and age on either of these two internalizing subscales indicating that these sex differences were not specific for ASD. The parent ratings of affective and anxiety symptoms yielded similar findings (Table 3, Figure 2(e) and (f), ST2, and SF2e/f).
Model-estimated means of YSR and CBCL domains in standardized scores of males and females with and without ASD between childhood and young adulthood.
The YSR/ASR were assessed at waves 1–4 and the CBCL/ACBL at waves 1, 2, 3, and 5. YSR: youth self report; ASR: adult self report; CBCL: Child Behavior Checklist; ABCL: Adult Behavior Checklist; ADHD: attention-deficit/hyperactivity disorder.

Model-estimated YSR and CBCL female versus male differences in standard deviations using linear mixed modeling between childhood and young adulthood in persons with and without ASD.
ADHD symptoms
There were no sex differences in self- or parent-reported scores of ADHD symptoms (Table 3, Figure 2(c) and (g), ST2, and SF2c/g).
Externalizing symptoms
No sex differences were found in self-reported conduct problems as shown in Table 3, Figure 2(d), ST2, and SF2d. The parent ratings yielded the same conclusion (Table 3, Figure 2(h), ST2, and SF2h).
Post hoc analyses
Adding IQ as a covariate in post hoc analyses did not alter any of the conclusions drawn from the findings of our main analyses (see the regression model estimates in ST3 and ST4 as compared to the estimates in ST1 and ST2, respectively).
Discussion
The aim of this study was to identify possible sex-specific manifestations of autism during the course of adolescence and determine if these differed from normative sex-specific developmental trajectories of psychopathology.
Sex differences specific for autism were only found in the autism domain of restrictive repetitive behavior (
In recent years, the notion of a specific female autistic symptom profile has been developed in the literature (e.g. Hull et al., 2020; Mandy et al., 2012) which has received much attention both in the scientific and in the lay press. Although the first delineations of this female phenotype assumed subtle sex differences in behavior (more restricted repetitive behavior in males, more internalizing problems in females, more externalizing problems in males, superior motor skills in females (Mandy et al., 2012), more recent publications presume a broader set of typical female autistic characteristics, also including social-communicative behavior (Hull et al., 2020). Our results clearly support the former, more limited female autistic symptom profile: sex differences in severity and course of social-communicative behavior were not confirmed in our present analyses. Our results are in line with previous findings that autistic males demonstrate more restricted repetitive behavior than autistic females in adolescence. In addition, we found a sex-specific course through adolescence of the
Males had a somewhat higher IQ than females in our autism group (and therefore also in our matched normative group) which was not accounted for in our main analysis. The difference in IQ identified in our samples is in line with the literature showing that autistic females are overrepresented at the lower end of IQ and underrepresented at the higher end (Kaat et al., 2021). This may have likewise played a role in previous studies on sex differences in autism that have for the most part not studied potential confounding by IQ (Mahendiran et al., 2019). To further explore this, we performed post hoc analysis, and showed that the results regarding sex differences did not differ when adjusted for the IQ differences between males and females (Supplementary Table S3–S4)). Note that in our sample with an average IQ of around 100, the diagnostic barriers for autistic girls such as being more successful at camouflaging their problems as suggested in the literature (Hull et al., 2020) may have led to underdiagnosis of female participants. As a consequence, we cannot fully rule out that when more women with a higher IQ had been present in our autism group, the results regarding sex differences would have been more in line with findings in other studies that suggested a more pronounced female autism phenotype. That said, the composition of our autism group and our findings give a good representation of the sex differences we encounter in clinical practice, including females with lower IQ.
The parallel increase in
An important limitation of this study is that the initial autism diagnosis was made clinically and assessment was not systematically confirmed by us at inclusion in the study using standardized diagnostic measures. The quality of diagnostic information on autism in TRAILS depends on clinical diagnostic practice, which in the Netherlands accords with the national clinical guideline stating that a best-estimate clinical diagnosis should be based on integrated information from different sources such as anamnesis, hetero-anamnesis, and observation (Kan et al., 2013). The around-to-above threshold-levels of SCQ scores for autism at the time of inclusion in the study at age 11 reported in our previous study appears to confirm the presence of significant autistic behavior in the autism group, although almost all received a clinical diagnosis of PDD-NOS (Horwitz et al., 2020). Nonetheless, in particular in light of the current higher threshold for diagnosing autism in
Another limitation relates to the possibility of a diagnostic bias against girls, particularly among those without intellectual disability who score high on autistic symptoms but fail to meet the diagnostic criteria for autism (Loomes et al., 2017; Ratto et al., 2018). According to the female autistic phenotype/camouflaging hypothesis, girls with a female-specific autism presentation are likely to be missed out on a timely diagnosis. In our study, we cannot rule out that a female autism group with a more “masculine” autism presentation was included. However, as mentioned, participants with autism were on the milder part of the autism spectrum in our sample, which diminishes chances of having missed substantial numbers of autistic females. In general, it holds that only if diagnostic criteria—that are characteristic for both sexes—are agreed upon and assessment instruments are changed accordingly this situation of potential underdiagnosis in autistic females can be improved.
We conclude that in adolescents with milder forms of autism and an average IQ subtle sex differences are found that are not present in the normative sample: higher scores on the
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Footnotes
References
Supplementary Material
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