Discussion Question

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European Child & Adolescent Psychiatry (2018) 27:1171–1180 https://doi.org/10.1007/s00787-018-1180-6

O R I G I N A L CO N T R I B U T I O N

Age level vs grade level for the diagnosis of ADHD and neurodevelopmental disorders

Maurizio Bonati1  · Massimo Cartabia1 · Michele Zanetti1 · Laura Reale1 · Anna Didoni2 · Maria Antonella Costantino2 · the Lombardy ADHD Group

Received: 22 February 2018 / Accepted: 4 June 2018 / Published online: 6 June 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018

Abstract A number of worldwide studies have demonstrated that children born later in the school year are more likely to receive an ADHD diagnosis than their same school-year peers. There is, however, variation in findings between countries. We aimed to confirm whether relative age is associated with ADHD diagnosis, with or without comorbidities, and to investigate whether relative age is associated with ADHD type and severity, and if this age relationship is in common with other neurodevelop- mental disorder. We used the Lombardy Region’s ADHD registry. Data on children aged 6 years and older from September 1, 2011 to December 31, 2017 were considered. We calculated incidence ratios to assess the inter-relations between relative age within the school year, using age at diagnosis of ADHD or of other psychiatric disorder, year of diagnosis, and total number of children born in Lombardy during the corresponding timeframe. Data on ADHD type, severity of diagnosed disorder clinical global impressions–severity scale, and repetition of a school-grade were also considered. 4081 children, 2856 of whom with ADHD, were identified. We confirmed that the cumulative incidence of ADHD diagnosis was greatest for younger children, in particular for boys, for whom the prevalence is greater. The relative age effect was not accounted for by ADHD comorbid disorders, ADHD of combined type or severity. The relative age effect was also observed for children with other neurodevelopmental disorders (without ADHD), with a similar profile as ADHD children: the incidence ratio was 1.78 (95% CI 1.07–2.97; p < 0.0247) for boys diagnosed before age ten. The findings have a potential implication for diagnostic and therapeutic practice, educational advice, and policies, besides to better plan and organize service systems and appropriately inform parents, children, and citizens.

Keywords Attention-deficit hyperactivity disorder · Age factors · Children · School · Italy · Epidemiology

Introduction

Attention-deficit hyperactivity disorder (ADHD) is a neurobiological condition characterized by developmen- tally inappropriate and impairing patterns of inattention,

hyperactivity, and impulsivity [1]. ADHD symptoms usu- ally become more evident in school-aged children, are more frequent in boys than girls, and tend to persist into adulthood [2]. The reported range in prevalence is very wide (from 0.2 to 34.5%), and heterogeneity in the methodological approaches used contributes to these differences [3]. ADHD diagnosis in children is a multiple-step process based on clinical evaluation, teacher ratings of behavior and perfor- mance in school, and parental rating [4]. Evidence of clini- cally significant impairment in social and school functioning is required for an appropriate diagnosis.1

As for other psychiatric disorders occurring during the developmental age, the categorical and relatively simple symptomatological core of ADHD often does not appear alone. Frequently, a wide variety of concurrent psychiatric disorders contribute to the psychopathological status of chil- dren and adolescents with ADHD, with a well-established

The list of participants, in addition to the authors, is part of the Lombardy ADHD Group and is reported in the acknowledgements.

* Maurizio Bonati [email protected]

1 Laboratory for Mother and Child Health, Department of Public Health, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Via Giuseppe La Masa 19, 20156 Milan, Italy

2 Child and Adolescent Neuropsychiatric Service, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy

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consensus among authors that the presence of overlapping psychiatric disorders is more likely to be the rule than the exception [4–6]. The overall prevalence of psychiatric dis- orders associated with ADHD in children and adolescents ranges from about 40–80% depending on the sample [7–9], with higher rates in clinically referred ADHD children (67–87%) [5].

Youth with ADHD experience greater academic impair- ment, including lower grades, grade repetition, and school dropout than their peers, and medication efficacy in improv- ing academic outcomes needs further evidence [10–16]. Fur- thermore, the association between relative age and ADHD has been reported, with the youngest children in the school year having 1.2–2.0 times increased risk of receiving an ADHD diagnosis or prescription [17, 18]. Relative age effects have been reported strong for learning disabilities but not for other disabilities [19], although attention and learn- ing problems are on a continuum (and not simply present or absent) and usually coexist [20]. This relative age effect was shown consistently in countries with high prescribing rates for ADHD, resulting in concerns that ADHD might be over- diagnosed or misdiagnosed [16, 21]. This association and the risk of academic impairment may thus have an impact on maturity differences in the classroom and how they are evaluated and handled, and on the long-lasting negative effects on personal achievements and health outcomes [22, 23]. A large Finnish study spanning a 14-year period showed the association between relative age and age at ADHD diag- nosis, in particular in children diagnosed with ADHD before the age of ten, and showed for the first time that the associa- tion was not accounted for by comorbid disorders such as conduct disorder, oppositional defiant disorder (ODD), or learning disorder (LD) [24].

Younger children in a school year are at a slightly greater psychiatric risk than older children, not only of ADHD, but of different disorders [22], but interest has been growing in the influence of young relative age within the school year towards the diagnosis of ADHD [25]. Different countries use different cut-off dates for school entry, comparisons so between countries are illuminating. The matter is important because of the potential implications for diagnostic practice and educational advice and policies.

We, therefore, aimed to confirm the association between relative age (defined as the child’s age within their school year) and ADHD in a different additional national context: if it is stronger at the younger end of the school-age range, if comorbid disorders have a role, and if such an association is specific to ADHD with and without comorbidities or if it is present also with other mental disorders without ADHD.

Methods

This study was designed as a review of patient medi- cal records identified from the regional ADHD Registry database. Written informed consent was obtained for all patients before collection data in the Registry. Data were anonymised prior to use for research purposes. Formal eth- ical review board approval was not required for the present analysis of the data. The present research was approved by the Institutional Review Board of the IRCCS Istituto di Ricerche Farmacologiche “Mario Negri” in Milan, Italy.

Data collection and participants

In June 2011, the official regional ADHD Registry was activated in Lombardy and was designed as a disease-ori- ented registry collecting information not only on ADHD patients treated with pharmacological therapy, but also on all patients who access ADHD centers for a diagnosis of suspected ADHD. Italian legislation [26] requires data on all ADHD patients receiving methylphenidate or atomox- etine treatment (the only two drugs licensed for ADHD in Italy) to be reported in the Registry. The regional Registry is part of a more general project aimed to ensure appro- priate ADHD management for every child and adolescent once the disorder is suspected and reported, and includes commonly acknowledged diagnostic and therapeutic pro- cedures as well as educational initiatives for health care workers (child neuropsychiatrists and psychologists) of the Lombardy Region’s health care system who provide assistance to ADHD patients and their families [27–29].

The regional ADHD Registry represents a distinctive tool, internationally, aimed to ensure the appropriate care of, and the safety of drug use in, ADHD children [27–29]. All collected data, i.e., those concerning the diagnostic evaluation and the systematic monitoring assessments described, were analyzed monthly, and the findings were reported and periodically discussed with all 18 ADHD centers belonging to the Lombardy ADHD Group. This is a clinical multicenter study, in which all patients received a rigorous diagnostic assessment (according to national and international guidelines) [30, 31], approved by all involved clinicians and monitored by a registry-based data collection method.

In Italy, primary school enrolment begins during the calendar year in which a child turns 6 years old, with the school year starting in mid-September. The eldest chil- dren in a school year are, therefore, born in January (aged 6 years and 8 months) and the youngest children are born in December (aged 5 years and 8 months). Because the aim of our study was to investigate the effect of relative

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age after starting school, we included children diagnosed with ADHD from age 6 years onwards. Seven mandatory steps were applied at the time of diagnostic evaluation: (1) the clinical anamnestic and psychiatric interview; (2) the neurological examination; (3) the evaluation of cogni- tive level by Wechsler Scales; (4) the Schedule for affec- tive disorders and schizophrenia for school-age children (K-SADS) for a complete psychopathology overview and comorbidity assessment; (5) the child behavior checklist (CBCL) and/or the conners’ parent rating scale-revised (CPRS-R) rated by parents; (6) the conners’ teacher rat- ing scale-revised (CTRS-R) rated by teachers; and (7) the clinical global impressions–severity scale (CGI-S) to quantify symptom severity. This diagnostic pathway was agreed on, approved, and shared by all participating ADHD centers [5].

We identified the number of children born in each month during the study period from the regional database that con- tains the demographic information of the population and which is routinely updated.

Type of ADHD (according to the the items of the DSM- IV-TR) and CGI-Severity scale score (for all diagnosed chil- dren) were considered for the present investigation, as well as the cases of school rejection.

Procedures

We compared all children diagnosed with ADHD to chil- dren with other diagnosed disorders except ADHD (“without ADHD” group) for the association with relative age. ADHD subtype was also evaluated. To assess the possible contri- bution of comorbid disorders to the association between relative age and diagnosed disorder, we then stratified cases according to the presence of ADHD.

Statistical analyses

We estimated the cumulative incidence of ADHD (and corresponding 95% CIs) with a Poisson-regression model, assuming a Poisson error distribution. We initially calcu- lated the cumulative incidence of ADHD and of other men- tal disorders without ADHD per 1000 births, in the total sample and, separately, for boys and girls, for each month of birth and by blocks of 4  months (i.e., January–April, May–August, and September–December). The numerator was the number of children with ADHD and without ADHD born in a specific period and the denominator was the total number of children born in Lombardy during the corre- sponding timeframe. Next, to assess whether a possible rela- tive age effect was a function of the presence of a comorbid disorder, we estimated the cumulative incidence for children with and without comorbidity. We estimated incidence ratios of ADHD or other mental disorders separately for boys and

girls, for each birth month, and we compared every month with births in January. To improve the precision of these estimates and better reflect the way in which adults might think of children within a school year (i.e., as one of the eldest or one of the youngest in the class), we estimated inci- dence ratios for children born within 4-month periods (Janu- ary–April, May–August, and September–December), and compared the two younger periods with the eldest group of children (i.e., those born in January–April). Furthermore, to assess whether any relative age effect was affected by actual age at diagnosis (with a greater effect at the younger end of the school-age range), we stratified the sample on median age at diagnosis (age 9 years) as either age 7–9 years or age 10 years or older. We estimated incidence ratios of ADHD and disorders without ADHD by comparing the youngest and middle groups, by relative age, with those born during January–April. Children diagnosed between 1998 and 2003 who were aged 7–9 years at diagnosis were born between 1991 and 1996, whereas those aged 10 years or older were born between 1991 and 1993. Cross tabulations with Chi square, when appropriate, were made to explore the univari- ate associations. We performed statistical analyses with SAS version 9.4.

Results

Between September 1, 2011, and December 31, 2017, 4081 children from the 18 ADHD regional centers were evaluated for ADHD. 11 children with severe or profound intellectual disability (eight with ADHD) were excluded, resulting in a sample of 4070 children (M: 3439, 85%; F: 631, 15%).

2856 of 4070 subjects evaluated (70%) met the diagnostic criteria for ADHD (M: 2458, 86%; F: 398, 14%). The mean age at ADHD diagnosis in the sample was 9.3 years (SD 2.5, range 6–17). 1669 of 2856 ADHD patients (58%) had ADHD of combined type (ADHD-C), 934 (33%) of inatten- tive type (ADHD-I), and 253 (9%) of hyperactive/impulsive type (ADHD-H).

Incidence ratios for ADHD diagnosis among children born later in the year were generally higher than those for children born earlier in the year (Table 1). Compared with boys born in January, incidence ratios increased from 1.11 (95% CI 0.57–2.16) for those born in February to 2.25 (1.21–4.19; p < 0.009) for births in December. Among girls, similar increased incidence ratios were noted although not statistically significant. Figure 1 provides a visual presenta- tion of the cumulative trend of ADHD incidence among boys and girls, by birth month.

Similar features were observed for the 1214 children (M: 981, 80%; F: 233, 20%; mean age at diagnosis in the sample was 9.7 years, SD 2.4, range 6–17) without ADHD or with subthreshold ADHD (Table 2; Fig. 1), in particular for boys.

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The small numbers, although respect a monthly increas- ing trend during the year, limit the statistical significance. Overall, LD (57%), anxiety disorders (17%), sleep disorders (14%), and ODD (10%) were the most frequent disorders in subjects without ADHD. The small numbers limit further stratified analyses.

Table  3 shows incidence ratios of ADHD among boys and girls by 4-month periods (Januar y–April, May–August, and September–December). Compared with the oldest boys in each school year (i.e., those born January–April), the incidence ratio of ADHD diagnosis for the youngest boys in the school year (i.e., those born

Table 1 Incidence ratios of ADHD per 1000 births by month of birth, in girls and boys

ADHD attention-deficit hyperactivity disorder

Boys (N = 2458) Girls (N = 398)

Cases (%) Incidence ratio (95% CI) p Cases (%) Incidence ratio (95% CI) p

January 170 (7) Reference 25 (6) Reference February 159 (6) 1.11 (0.57–2.16) 0.7594 21 (5) 1.06 (0.24–4.62) 0.9367 March 163 (7) 0.6 (0.49–1.90) 0.9162 22 (6) 1.06 (0.25–4.53) > 0.9999 April 169 (7) 1.07 (0.54–2.08) 0.8547 29 (7) 0.99 (0.22–4.47) > 0.9999 May 194 (8) 1.24 (0.66–2.34) 0.5008 33 (8) 1.26 (0.32–4.98) 0.8580 June 203 (8) 1.16 (0.60–2.23) 0.6663 28 (7) 1.43 (0.36–5.67) 0.6926 July 211 (9) 1.06 (0.55–2.04) 0.8544 31 (8) 1.19 (0.30–4.80) > 0.9999 August 231 (9) 1.30 (0.70–2.43) 0.4099 45 (11) 1.77 (0.49–6.44) 0.7768 September 225 (9) 1.39 (0.75–2.57) 0.2911 38 (10) 1.54 (0.41–5.87) 0.9816 October 228 (9) 1.44 (0.78–2.65) 0.2455 41 (10) 1.24 (0.31–4.94) 0.7982 November 246 (10) 1.55 (0.84–2.87) 0.1619 49 (12) 2.12 (0.59–7.57) 0.2375 December 259 (11) 2.25 (1.21–4.19) 0.0087 36 (9) 2.01 (0.50–8.06) 0.3138

Fig. 1 Cumulative incidence of ADHD and other psychiatric disorders, by month of birth and sex. Data points depict the cumulative incidence per 1000 births, and error bars represent the 95% CI. ADHD attention- deficit hyperactivity disorder

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September–December) was 1.54 (95% CI 1.13–2.09; p < 0.0058). The corresponding incidence ratio for girls was 1.64 (0.84–3.22). A similar picture was observed for non-ADHD diagnosed children. Concerning the type of ADHD, the incidence ratio of ADHD diagnosis for the youngest boys in the school year (i.e., those born Sep- tember–December) compared with the oldest children was 1.58 (95% CI 1.10–2.29; p < 0.0139) for children with a disorder of combined type (ADHD-C). No statistical sig- nificance was observed for the other two types of ADHD, as well as no relative age effect in ADHD risk according to CGI-S score (less or ≥ 5) was noted.

A relative age effect was noted among children who received a diagnosis of ADHD at age 6–9 years (Table 4). No increase in the incidence ratio for ADHD diagnosis was recorded, however, among children diagnosed at a later age

(10 years or older). A similar trend was also observed for the group of children with other diagnosed disorders.

Of 2856 ADHD children, 834 (29%) received a diagnosis of ADHD only, while 2022 (71%) had at least one comor- bid psychiatric disorder (OR 1.67, IC 1.46–1.93). Comor- bid psychiatric disorders were more frequent in patients with ADHD-C subtype (OR 1.36, IC 1.16–1.60), and in ADHD patients with a CGI-S score equal to or greater than 5 than patients with only ADHD or non-ADHD (χ2 222, p < 0.0001).

Of the 3574 patients with at least one psychiatric disorder, 834 (23%) were diagnosed only with ADHD and 523 (15%) only with one other psychiatric disorder, while 2217 (62%) had two or more mental disorders (of whom 2022 also had ADHD). The rate of ODD (16 vs 10%; p < 0.0001) was sig- nificantly higher in ADHD patients, while an inverse data

Table 2 Incidence ratios of without ADHD per 1000 births by month of birth, in girls and boys

Boys (N = 981) Girls (N = 233)

Cases (%) Incidence ratio (95% CI) p Cases (%) Incidence ratio (95% CI) p

January 67 (7) Reference 20 (9) Reference February 49 (5) 0.78 (0.29–2.07) 0.6173 12 (5) 0.78 (0.15–4.09) 0.8377 March 67 (7) 1.01 (0.41–2.46) 0.9902 18 (8) 0.79 (0.16–4.03) > 0.9999 April 65 (7) 1.04 (0.42–2.56) 0.9325 12 (5) 0.99 (0.21–4.71) > 0.9999 May 79 (8) 1.16 (0.49–2.73) 0.7407 18 (8) 0.74 (0.14–3.75) > 0.9999 June 86 (9) 1.37 (0.59–3.18) 0.4656 16 (7) 0.88 (0.18–4.39) > 0.9999 July 95 (10) 1.34 (0.58–3.05) 0.4906 22 (9) 1.06 (0.24–4.66) > 0.9999 August 110 (11) 1.57 (0.70–3.50) 0.2676 18 (8) 0.88 (0.19–4.21) > 0.9999 September 78 (8) 1.10 (0.46–2.61) 0.8259 21 (9) 1.07 (0.24–4.78) 0.9328 October 86 (9) 1.24 (0.53–2.88) 0.6200 22 (9) 1.28 (0.31–5.31) > 0.9999 November 108 (11) 1.72 (0.77–3.86) 0.1797 28 (12) 1.30 (0.30–5.55) > 0.9999 December 91 (9) 2.21 (0.96–5.07) 0.0564 26 (11) 2.08 (0.50–8.65) 0.6680

Table 3 Incidence ratios of ADHD and without ADHD per 1000 births by month of birth, in girls and boys

Month of birth was categorized into three groups of relative age ADHD attention-deficit hyperactivity disorder

ADHD

Boys (N = 2458) Girls (N = 398)

Cases (%) Incidence ratio (95% CI) p Cases (%) Incidence ratio (95% CI) p

January–April 661 (27) Reference 97 (24) Reference May–August 839 (34) 1.15 (0.84–1.59) 0.3858 137 (34) 1.37 (0.69–2.72) 0.3593 September–December 958 (39) 1.54 (1.13–2.09) 0.0058 164 (41) 1.64 (0.84–3.22) 0.1441

Without ADHD

Boys (N = 981) Girls (N = 233)

January–April 248 (25) Reference 62 (27) Reference May–August 370 (38) 1.42 (0.93–2.17) 0.1056 74 (32) 1.00 (0.44–2.25) 0.9971 September–December 363 (37) 1.55 (1.01–2.38) 0.0418 97 (42) 1.53 (0.72–3.28) 0.2670

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proportion was observed for LD (40 vs 57%; p < 0.0001), and anxiety disorders (7 vs 17%; p = < 0.0001). Similar rates (14%) between the two groups were observed for sleep disorders.

Figure  2 shows the cumulative incidence of ADHD among children with and without comorbid or other

psychiatric disorders by birth month. For all six groups of children, the cumulative incidence of diagnosis increased for those born later in the year, with the highest propor- tion noted among those born in December. Compared with the oldest boys in each school year (i.e., those born Janu- ary–April), the incidence ratio of ADHD diagnosis for the

Table 4 Incidence ratios of ADHD and without ADHD by year of diagnosis, age at first diagnosis, and month of birth

Age at diagnosis splits into age 6–9 and age ≥ 10 years. Month of birth was categorized into three groups of relative age ADHD attention-deficit hyperactivity disorder

ADHD

Age 6–9 years (N = 1715) Age 10–17 years (N = 1141)

Cases (%) Incidence ratio (95% CI) p Cases (%) Incidence ratio (95% CI) p

January–April 442 (26) Reference 316 (28) Reference May–August 549 (32) 1.20 (0.82–1.75) 0.3404 427 (37) 1.17 (0.77–1.76) 0.4668 September–December 724 (42) 1.69 (1.18– 2.43) 0.0038 398 (35) 1.28 (0.85–1.94) 0.2354

without ADHD

Age 6–9 years (N = 650) Age 10–17 years (N = 564)

Cases (%) Incidence ratio (95% CI) p Cases (%) Incidence ratio (95% CI) p

January–April 157 (24) Reference 153 (27) Reference May–August 218 (34) 1.26 (0.74–2.15) 0.3974 226 (40) 1.34 (0.78–2.28) 0.2872 September–December 275 (42) 1.78 (1.07– 2.97) 0.0247 185 (33) 1.27 (0.73–2.22) 0.3914

Fig. 2 Cumulative incidence of ADHD in children with and without comorbid or other psychiatric disorders, by month of birth and sex. Data points depict the cumulative incidence per 1000 births, and error bars represent the 95% CI. ADHD attention-deficit hyperactivity disorder

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youngest boys in the school year (i.e., those born Septem- ber–December) was 1.55 (95% CI 1.08–2.23; p < 0.0163) for boys with ADHD and psychiatric comorbidity, and 1.80 (95% CI 1.02–3.18; p < 0.0399) for boys with only other psychiatric disorders. For both boys with only ADHD and for all girls, the noted relative age effect was not statistically significant. Similar results were seen among the youngest boys with ADHD and a LD (the most frequent disorder in the studied population) with an incidence ratio of 1.71 (95% CI 1.06–2.75; p < 0.0254).

More ADHD-C patients received drug prescription treat- ments (methylphenidate) at the time of the diagnosis than ADHD-I or ADHD-H patients (29% vs 12%; incidence ratio of 2.98, 95% CI 2.43–3.66; p < 0.0001), but no association with younger relative age in the school year was found (Chi-square test, p = 0.9645). Similarly, the incidence ratio of ADHD patients with a CGI-S score equal to or greater than five than patients with a lower score receiving drug prescriptions was 6.61 (95% CI 5.42–8.07; p < 0.0001), but no association was observed with patient’s relative age at school (Chi-square test, p = 0.9019).

3747 of the 4070 subjects considered had completed at least their first year of school at the time of evaluation, and 5.7% had repeated a grade. The rate was double for patients diagnosed with other psychiatric disorders alone (7.2%) or with ADHD (6.5%) compared to children who received a diagnosis of ADHD only (3.4%) or no psychiatric diagnosis (3.6%). The incidence of grade repetition for the youngest children (i.e., those born September–December) was slightly higher than those born in January–April for both children with (0.34 vs 0.25) and without (0.28 vs 0.21) ADHD, although the small numbers limit statistical significance.

Discussion

In both boys and girls, the cumulative incidence of clini- cally diagnosed ADHD or other developmental disorders is greater among children within the school year, and the strength of the association is greater for children born dur- ing September–December. The association is independent of type of ADHD, presence of comorbidities, ADHD severity, and pharmacological prescription at the end of the diag- nostic assessment. Furthermore, a risk that needs additional confirmation was observed for repeating a grade for the younger children.

Thus, our study findings confirm an association between younger relative age in the school year and diagnosis of ADHD, and that the findings are not affected by the pres- ence of comorbidities in agreement with what was reported in other countries, in particular by the most recent and large study [24]. Furthermore, our study findings show that the association is not exclusive to ADHD, but can be observed

for other developmental disorders in children without ADHD. Thus, recent findings from a country with low diag- nosis and prescribing rates for ADHD [27], and with 1-year early primary school enrolment than in other countries [24], not only add weight to the cumulative evidence in favour of a relative age effect for ADHD diagnosis, but add that such an effect is common for developmental disorders that appear at school, with the affected children directed for evaluation at the child psychiatric services.

The present study has several strengths. First, use of the same approach as a recent and well performed study [24] that also made the point about available evidence, i.e., to confirm the results and go further. Second, use of a specific ADHD register collecting information on an evidence-based and shared strategy for diagnostic evaluation and monitoring of the disorder among the 18 participating ADHD centers [27]. The use of an ad hoc clinical registry allows us to use more appropriate data without having to resort to proxies or face to many limitations as in the previous studies using administrative databases [27–29]. Third, since the data were collected as part of the monitoring of ADHD patients’ care, information on educational characteristics and academic achievement was available. It was, therefore, possible to consider grade repetition as one of the potential adverse outcomes related to early access to school of these patients. In other studies, this was not adequately taken into account [24]. Furthermore, the potential misclassification of the pre- vious studies [24] due to the fact that it was not known that young children had been held back a year at school has been overcome.

Our study also has some limitations. Since we have ana- lyzed the cases from the regional ADHD registry database, there was no general population comparison in the present study. Although the registry on ADHD care collects infor- mation on children referred to all the 18 public, free regional ADHD centers, it misses those who were diagnosed, treated, and followed only in private practice. However, these cases should be a rarity, at least for ADHD diagnosis in Lom- bardy. Even if a third [32] or a fourth [33, 34] of referrals to child and adolescent mental health services are turn away, the regional ADHD project (and registry) is long lasting and represents a specific challenge, but also an opportunity, for the Healthcare Directorate of the Lombardy Region, involving all the child and adolescent mental health units of the health system. However, registry collects information only on patients who access ADHD centers for a diagno- sis or treated with pharmacological therapy (in a country, where prescribing rates for ADHD are very low), this affects the absolute cumulative incidence rates that were low than those in other countries [24]. Second, even if the size of the population is one of the larger published studies, as is the large amount of information available, the evaluation of potential outcomes related to the association between

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neurodevelopmental disorders and younger relative age in the school year needs further data collection, as well as dif- ferent research approaches.

Our findings confirm [24] that the relative age effect was affected by a child’s actual age, particular among the young- est children (aged 6–9 years), suggesting that relative age has a greater effect on clinical diagnosis in younger chil- dren attending school. Moreover, the effect also seemed to decline with age supporting the immaturity hypothesis of ADHD [18], known as the “maturational lag” [35] and sup- ported by a series of neuroanatomical and functional stud- ies [36, 37]. Younger children are less mature in terms of self-regulation, and teachers are, therefore, more likely to raise concerns about these children to their parents, which could lead parents to seek an assessment [38]. The devel- opmental immaturity hypothesis could also be extended to explain the relative age effect here reported associated also to other mental disorders (in children without ADHD, and other mental disorders). However, further studies are needed as done in regard for ADHD, and caution is necessary as long as findings of further investigations show that relative age hypothesis may be applied in other mental disorders in children.

Children with ADHD show significant academic undera- chievement, poor academic performance, and educational problems [39]. Children with ADHD are more likely to be expelled, suspended, or repeat a grade compared to con- trols [12, 13]. Teachers and parents should thus be aware of a child’s relative age to prevent or reduce these adverse outcomes.

Findings indicate that developmental immaturity is mis- labelled as a mental disorder and this is risk of unnecessary medication, since overdiagnosis induces overmedication [17–19].

Teachers’ and parents’ formal evaluations (conners’ teacher and parent rating scale-revised) and not their impres- sions are essential for the clinical diagnosis of ADHD [5], as guaranteed by the Lombardy registry’s procedures. Since the study took into account only children who arrived at a service (ADHD center), however, we do not know if there is a lower referral by both teachers and parents for older chil- dren with suspected ADHD. A systematic underdiagnosis due to teachers’ and parents’ perceptions, concerns, or atti- tudes may, therefore, exist. Because it is not only a specific, potential limitation for ADHD care detection, but also for other neurodevelopmental disorders, as shown in the present study more efforts and initiatives are needed such as formal teacher training to help recognize and properly refer children with suspected neurodevelopmental disorders.

Younger children may be at a greater educational disad- vantage than their older school-year peers due to ADHD or other psychiatric disorders. There is evidence that ADHD symptoms, necessary for diagnosis, can appear before

school-entry age [30, 31]. In this case, the association between school-year relative age and ADHD diagnosis is, therefore, an expression of delated diagnosis in chil- dren with neurodevelopmental immaturity with access school early. Relatively young children would struggle more than their older peers to meet the behavioral expec- tations of the classroom, but it could be that early access to school makes a latent disorder, even though it would have appeared anyway a year later [40]. In such a context, the need to diagnose mental disorders early, to refer, and to treat appropriately is well known, regardless of patient age [38]. In our study, we do not have information on children from disadvantaged backgrounds at preschool and early school. These children start school with a higher preva- lence of mental health difficulties, compared with their more advantaged peers [41]. These children need extra support in the preschool and early years to help narrow these inequalities. The relation between disadvantaged backgrounds and relative age is unknown, as its poten- tial implications for health and education of children, and should be explored in the future research.

The child’s relative age and individual needs should be kept in mind by teachers in their educational activities within the classroom, and they should be kept in mind by the clini- cians diagnosing and managing the care of children with neurodevelopmental disorders.

A number of studies examined the relative age effect on brief-run or long-run educational outcomes, lifelong earn- ing, success, self-esteem, well-being, and school sports, with divergent findings due also to the fact than the national school systems are different, including educational pro- grams, evaluations, and expectations [39]. However, children who are younger within their school year are more likely to have special educational needs, and for children with com- plex difficulties, being relatively young for their school year may be an additional stressor that may undermine mental health [40].

Future research should assess both teachers’ and parents’ perceptions of problematic behavior and thresholds for con- cern in children who are young for year level.

In practice, clinicians need to ensure they assess atten- tional capacity and impulse control relative to the child’s chronological age and overall developmental status, rather than age for year level for children with suspected ADHD [38]. The same assessment must be done, however, for any developmental disorder that affects performance and school attendance. Finally, also policymakers, in their planning and programming of services, should be aware that early access to school is a critical decision that can affect long-term out- comes, and not only educational ones. The decision should be personalized, involving parents and future teachers, also taking into account the socioeconomic and the health related quality of life settings. All this is valid not only for a more

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appropriate management of ADHD, but of all child psychi- atric disorders, and for all children.

Acknowledgements The study is part of the “Sharing diagnostic– therapeutic approaches for ADHD in Lombardy” project partially funded by the Healthcare Directorate of the Lombardy Region (D.G. sanità n.3798, 8/05/2014). The views expressed are those of the authors and not necessarily those of the regional Healthcare Directorate. We thank all the teams of the 18 participating ADHD centers who devoted. significant time and energy to this project, joining and animating the Lombardy ADHD Group, in addition to the authors: Stefano Conte, Valeria Renzetti, Laura Salvoni (Bergamo); Massimo Molteni, Sara Trabattoni (Bosisio Parini, LC); Paola Effedri, Elisa Fazzi, Elena Filippini, Elisabetta Pedercini, Edda Zanetti (Brescia); Nadia Fteita (Como); Daniele Arisi, Roberta Mapelli (Cremona); Simona Frassica, Simonetta Oriani, Christian Trevisan (Garbagnate Milanese, MI); Susanna Acquistapace, Ottaviano Martinelli, Davide Villani (Lecco); Emanuela Binaghi, Andrea Deriu, Gabriella Vasile (Legnano, MI); Ari- anna Borchia, Paola Morosini (Lodi); Maddalena Breviglieri, Giuseppe Capovilla, Roberto Segala (Mantova); Chiara Battaini, Claudio Bissoli, Maria Paola Canevini, Isabella Cropanese, Emiddio Fornaro, Gior- gio Leonardi, Silvia Merati, Monica Saccani, Roberto Vaccari, Vera Valenti (Milan); Umberto Balottin, Matteo Chiappedi, Elena Vlacos (Pavia); Corrado Meraviglia, Maria Grazia Palmieri, Gianpaolo Ruffoni (Sondrio); Francesco Rinaldi, Federica Soardi (Vallecamonica–Sebino, BS); Chiara Luoni, Giorgio Rossi (Varese). The authors would like to acknowledge Chiara Pandolfini and Daniela Miglio for manuscript language and technical editing.

Author contributions MB had the idea for the study, designed it, and drafted the initial report. MC and MZ managed and analyzed the data. LR, AD, and MAC drafted sections of the initial report. All authors participated in study design, contributed to interpretation of data, criti- cal review and revision of the report, and approved the final report as submitted. MB is guarantor for the study.

Compliance with ethical standards

Conflict of interests We declare no competing interests.

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