Figure 1 below summarises the literature search process method. The PubMed search identified 152 papers; however, only 16 were relevant to this study. Three of these papers (letters to the editor etc.) related to other papers which are all discussed in this review and offered no additional relevant information and were thus excluded. No extra relevant studies were identified among the 47 papers identified in the ERIC search. Initial grey literature search identified three more studies, while snowball search of the 16 relevant records identified six additional studies not identified by the PubMed or ERIC searches, leaving a total of 22 studies for inclusion.

Of these 22 studies, 19 explored the relationship between late birthdate within school intake cohorts and ADHD diagnosis. Of the 19 studies, 15 reported medication use and only nine reported diagnosis rates. Three other studies explored related topics (season of birth and ADHD, birthdate and adult ADHD symptomology). The diversity of methodologies in the studies meant that it was not appropriate to undertake a meta‐analysis. Instead the 19 studies (conducted in 13 countries) are discussed separately.

A total of 17 studies – five in the USA, two in Spain and one each in Canada, Finland, Germany, Holland, Iceland, Israel, Norway, Sweden, Taiwan and Australia – found that children who were the youngest in their school year were more likely than their classmates to be medicated for, and/or diagnosed with, ADHD. Two Danish studies found a weak or no late birthdate effect. These 19 studies have a combined total population of over 15,400,000 children (approximate medication rate of 2.4% among the 15 studies that reported medication use). They are discussed below, and summarised in Appendix S1, with studies from the same country grouped together in descending order of the total number of children in the largest study in a country.

Large studies investigating the late birthdate effect for ADHD

Ten of the largest eleven studies are population‐wide studies in nine countries that each cover at least 310,000 children, with a minimum 5,900 medicated or diagnosed. The remaining smaller studies each had a total population of less than 35,000 children, with fewer than 2,000 medicated. As discussed below, the two large scale studies from Denmark (Dalsgaard, Humlum, Nielsen, & Simonsen, 2014; Pottegard, Hallas, Hernandez, & Zoega, 2014) have significant cohort overlap, with the larger of the two (Pottegard et al., 2014) having a more robust methodology. The key measures (mean medication rate and late birthdate effect) of nine of these 10 large‐scale studies (Dalsgaard et al., 2014 is not included) are plotted in Figure 2. Following this, another large scale study (Boland, Shahn, Madigan, Hripcsak, & Tatonetti, 2015) that reviewed the relationship between date of birth and a range of diseases and eight smaller studies that investigate the ADHD late birthdate effect, and then three other related studies are discussed.

Figure 2 Open in figure viewer PowerPoint Relative medication use risk (youngest vs. oldest) against per capita medication use rate [Colour figure can be viewed at wileyonlinelibrary.com

The largest of the studies is a German study (Schwandt & Wuppermann, 2016) that reviewed the health insurance records from 2008 to 2011 of roughly 7.2 million children (approximately 90% of all German children aged 9–13 in this period). A number of children – most of whom were out of their recommended age group school cohort (primarily entry delayed for a year) – were excluded, so the final number analysed was 6,585,039. The proportion of 9–13 year‐olds reported as receiving medication over the 4 years was 2.7%, with 3.8% reported as having been diagnosed with ADHD. The study reviewed records from 16 German states with different school entry cut‐off dates. Among children aged 9–13 at any time between 2008 and 2011, researchers found large increases in ADHD rates around cut‐off dates, amounting to a 22% increased risk for the youngest children in an age cohort (born the last month before the cut‐off) compared with children born just after them who were the oldest (first month) in the next age cohort. These changes occurred ‘at different months across [German] states in accordance with the different cut‐off dates’.

The late birthdate effects demonstrated in the study were weaker in the first two grades and peaked in fourth and fifth grade, before moderating in later grades. One factor identified as a possible explanation for this trend was that academic performance becomes important in third and particularly fourth grade, and new ADHD diagnoses of relatively young children may occur then as a response to age‐related differences in academic performance (Schwandt & Wuppermann, 2016).

The Swedish study (Halldner et al., 2014) reviewed the records of all people born from 1940 onwards, and residing in Sweden during July 2005 to December 2009. This included 1,821,939 children aged 6–17 years, of whom 17,565 (0.96%) received medication (calculated from Halldner et al., 2014 table 1, p. 899). Children born in November and December had a 39% higher risk of being medicated and a 30% higher risk of being diagnosed than their oldest classmates (born the previous January and February). This late birthdate effect was strongest in children aged 6–7 (70% increased medication use risk) and decreased progressively among older children (20% increased medication use risk among adolescents aged 16 and 17). The late birthdate effect tapered further in early adulthood, so that after age 35 there was no discernible difference. The study also reviewed diagnosis status, and similar patterns were displayed. Despite the relative age differences, the authors found no differences in parent or self‐reported ADHD symptoms by birth month. This was one of only two studies that reported the relationship between month of birth and parent‐reported ADHD symptoms.

In contrast to all other studies that reported both diagnosis and medication rates, the diagnosis rate (0.6%) in the Swedish study (for children aged 6–17) was considerably lower than the medication rate (0.96%). However, this study reported the proportion of children with a diagnosis of hyperkinetic disorder as defined in ICD‐10. For many psychiatric disorders, including ADHD, diagnostic rates using DSM criteria are significantly higher than those using the equivalent disorder in ICD‐10 (Sorensen, Mors, & Thomsen, 2005). It may be that some Swedish children who met the broader diagnostic criteria for ADHD, but were not diagnosed with Hyperkinetic Disorder, received medication.

A Danish study (Pottegard et al., 2014) reviewed the records of 1,209,901 children aged 7–12, including 932,032 children in their recommended school year, of whom 10,932 (1.2%) received medication. Among children in their recommended school year across the period 2000–2011, there was an average 8% increased risk (95% CI: 1.04–1.12) for children born between October and December (the youngest) compared with their older classmates born between January and March (the oldest).

In Denmark, the recommended school year intake matches the calendar year. However, it is very common in Denmark for late‐born children to have delayed school entry, with 40% of children (boys 51%, girls 29%) born in October, November and December starting late, compared to only 4% of children born in January, February or March (Pottegard et al., 2014). The authors proposed that ‘the high proportion of relatively young children with delayed school entry in Denmark may play a role in the near absence of a relative age effect’.

Another large Danish study (Dalsgaard et al., 2014) with an overlapping sample, was published shortly before the research led by Pottegård. It included many of the same children, but the sample was only 35% of the size. It reviewed the records of all 418,396 children born between July 1990 and June 2001, of whom 8,720 (2.1%) children ‘purchased’ ADHD medication after the age of seven. The authors found no effect of ‘being born in the beginning of January compared to the end of December on the likelihood of having purchased ADHD medication’ (OR 1.0014, 95% CI: 0.9996–1.0031).

According to Dalsgaard et al. ‘In Denmark, school entry rules imply that children born in December are typically enrolled in school 1 year earlier than children born in January’. The paper makes no reference to the effect of the very common Danish practice of delayed entry for late‐born children, particularly boys. The lead author was contacted to confirm whether ‘the calculation of relative risk in your paper was based on the assumption that all children started school in line with these school entry rules’; but he did not respond. If, as appears likely, no adjustment was made for late starters, this would have hidden any late birthdate effect, because a disproportionate number of nominally young, late‐born children (born in December) would actually be among the oldest in their class. As Danish data from the more robust study led by Pottegard et al. (2014) are included in Figure 2, the results of this study are omitted there.

Elsewhere, Dalsgaard et al. have suggested that the lack of a late birthdate effect in Denmark may be due to diagnostic practices being less subjective because only specialists can diagnose ADHD (Dalsgaard, Humlumb, Nielsen, & Simonsen, 2012). However, in most other studies where a strong late birthdate effect exists, diagnosis is also restricted to specialists.

The Israeli study (Hoshen, Benis, Keyes, & Zoega, 2016) reviewed the records of 1,013,149 children aged between 6 and 17 years from 2006 to 2011, and found rising rates of ‘one‐year prevalence’ use of ADHD stimulant prescribing, from 2.6% in 2006 to 4.9% in 2011. The youngest third of children in class – born August to November – were more likely to use medication than the oldest third – born December to March – (risk ratio (RR) 1.17, 95% confidence interval (CI) 1.12–1.23) or the middle third (RR 1.06, 95% CI: 1.01–1.11). As in the Swedish study, the late birthdate effect ‘diminished as children were older in absolute age’ (Hoshen et al., 2016).

An important limitation of the Israeli study is that researchers could not identify children who had been ‘accelerated or delayed from the expected grade level’ (Hoshen et al., 2016). It is likely that the increasingly common Israeli practice of delayed entry for late‐born children partly explains why the late birthdate effect was not as strong as in other studies (Hoshen et al., 2016).

The Canadian study (Morrow et al., 2012) reviewed the records of 937,943 children in British Columbia, aged 6–12 years at any time between 1 December 1997 and 30 November 2008. Approximately 33,775 (3.6%) of these children received medication at some time (calculated from Morrow et al., 2012 table 1, p. 756). There was an increased risk of both being diagnosed (boys +30%, 95% CI: 1.23–1.37; girl s + 70%, 95% CI: 1.53–1.88) and taking medication (boys +41%, 95% CI: 1.33–1.50; girls +77%, 95% CI: 1.57–2.00) for the youngest children in a class (born in December) compared with the oldest (born the previous January).

The strength of the late birthdate effect remained relatively stable throughout the 11‐year study, despite increasing diagnosis and medication rates. The effect was present among all age groups of children but, as with the Swedish and Israeli studies, was weaker in older children. The risk for medication use rose month by month for both genders from January to September, and plateaued from September to December. The authors suggest this plateauing may occur because late‐born children (born in October to December) who show ADHD type behavioural problems may be held back a year, giving them more time to develop sociable behaviours.

The Finnish study (Sayal, Chudal, Hinkka‐Yli‐Salomaki, Joelsson, & Sourander, 2017) examined the birth month distribution of 870,695 children aged 7–19, of whom 6,136 (0.7%) were ever diagnosed with ADHD. The chances of a child being diagnosed before age 10 were 64% higher (95% CI: 1.48–1.81) for the youngest third in a class (born September to December) compared with their older classmates born from January to April. The effect was not as strong among older children. Across the entire 7–19 age range, boys born between September and December were 26% (95% CI: 1.18–1.35) more likely to be diagnosed than boys born from January to April. For girls aged 7–19, the increased risk was 31% (95% CI: 1.12–1.54). For both genders combined, there was a 27% increased risk of diagnosis (calculated from Sayal et al., 2017 table 2, p. 5).

The Norwegian study (Karlstad et al., 2016) reviewed the records of all Norwegian children born between 1998 and 2006 from their sixth birthday until 31 December 2014. In Norway, delayed (or early) enrolments are rare (Karlstad et al., 2016). Of the 509,827 children aged 6–16, 15,717 (3.1%) received ADHD medication at some time during this period and 3.4% were diagnosed. Boys born from October to December (the youngest children in a class) had a 41% (adjusted hazard ratio 1.4, 95% CI: 1.4–1.5) higher rate of medication and a 43% higher diagnosis rate than older boys born from January to March of the same year. For late‐born girls, the elevated medication risk was +79% (adjusted hazard ratio 1.8, 95% CI: 1.7–2.0), with an increased diagnosis rate of +75% (percentages calculated from Karlstad et al., 2016 table 1, p. 345). A supplementary analysis restricted to 17,017 siblings from 7,690 mothers, adjusted for gender and age, revealed a 70% greater risk of ADHD medication use for late‐born children (October to December) compared with their early‐born siblings (January to March).

Unlike most of the other studies, the late birthdate effect was most marked in higher grades. In Norway, the first testing of academic performance occurs late in grades four and five, coinciding with an increase in the strength of the late birthdate effect (Karlstad et al., 2016).

In the Taiwanese study (Chen et al., 2016), the total population of children was 378,881, of whom 6,062 (1.6%) received medication and 2.3% had ever been diagnosed. Among children aged 4–17, there was 65% (95% CI: 1.48–1.83) increased risk (boys +63%, girls +71%) of being diagnosed and a 73% (95% CI: 1.53–1.97) increased risk (boys +76%, girls +65%) of taking medication for the youngest children in a class (born in August) compared with the oldest (born the previous September). The late birthdate effect was stronger in early school years than in later school years.

The Australian study (Whitely, Lester, Phillimore, & Robinson, 2017) examined the birth month distribution of 311,384 Western Australian children aged 6–15, of whom 5,937 (1.9%) received medication (4,677 [2.9%] of 158,675 boys; 1,260 [0.8%] of 152,709 girls ‐ not reported in original study). There was a high degree of compliance with recommended age input (98%) and, to the limited extent that it occurs, most out‐of‐year children were late‐born children with delayed entry. For children aged 6–10, the youngest in a class (born in June) were approximately twice as likely (boys RR 1.93, 95% CI: 1.53–2.38; girls 2.11, 95% CI: 1.57–2.53) to take medication as the oldest (born the previous July). For children aged 11–15, those born in June were 30% more likely (boys 1.26, 95% CI: 1.30–1.52; girls 1.43, 95% CI: 1.15–1.76) to be medicated than those born the previous July. The increased risk for all children (both genders combined) was 57% (not reported in original study). Similar patterns were found when comparing children born in the first three (or six) months and the last three (or six) months of the school‐year intake.

Figure 2 (above) is a scatter diagram showing the medication rate (diagnosis rate for the Finnish study) versus relative risk for the nine countries in which large studies have been conducted. The smallest of these studies had a total population of over 310,000. The largest study with both population and diagnosis/medication data not included in the scatter diagram had a total population of less than 35,000 children.

All nine studies found a tendency for relatively young children to be medicated/diagnosed at a higher rate than their older classmates (ranging from 1.08 in Denmark through to 1.65 in Taiwan). However, there is no consistent relationship between the prescribing rate and the strength of the late birthdate effect. If anything, there is a weak inverse relationship (lower medication rate associated with a stronger effect), but there are differences in methodology – particularly diverse age ranges and the extent of unidentified delayed school entry – that make direct comparisons problematic. For example, the inclusion of 18 and 19 year‐olds in the Finnish study is likely to have reduced the strength of the reported late birthdate effect (based on diagnosis rather than prescribing). The most obvious conclusion that can be drawn from these nine studies is that the late birthdate effect occurs in both high and low prescribing/diagnosing jurisdictions.

Another very large study (Boland et al., 2015) reviewed a New York Medical Centre's records for 1,749,000 individuals born between 1990 and 2000, and examined the association between 1,688 diseases and birth month. It found a rising trend across the year for the diagnosis of ADHD, peaking in November. In New York the school intake year mirrors the calendar year, with the youngest children born in December. The study did not report absolute medication or diagnosis rates and therefore could not be plotted in Figure 2.