Data Sources

We analyzed data from the Truven Health MarketScan Research Database, a large health insurance claims database that contains deidentified, individual-level information on more than 80 million enrollees in all U.S. states from approximately 100 commercial payers and self-insured corporations, not including Medicaid claims. The database has been described previously.15,16 Cutoff dates for kindergarten entry for each state were obtained from the Education Commission of the States17 and the National Center for Education Statistics.18 The study was approved by the institutional review board at Harvard Medical School.

Study Population

The study population was restricted to children born from 2007 through 2009, which meant that all children completed at least 1 year of elementary school by 2015, the last year of data collection. Children were linked to parents within the database, and the location of the family was recorded as the last state in which the family was insured. Children were linked by state to cutoff dates for kindergarten entry in the respective state. Children and their parents were matched with all outpatient, inpatient, and drug claims for all years included in the analyses.

Study Measures

We sought to determine whether, in the 18 states that use the September 1 cutoff for school entry, the rate of ADHD diagnosis among children born in August (who are the youngest in their grade cohort) was higher than the rate among those born in September (who are the oldest in their grade cohort). Data from children in other states, which either use different cutoffs statewide or allow local jurisdictions to decide cutoff dates for school entry, were used in sensitivity analyses. The primary outcome was a diagnosis of ADHD, defined on the basis of International Classification of Diseases, 9th Revision (ICD-9), code 314.01 (attention deficit disorder with hyperactivity) or 314.00 (attention deficit disorder without hyperactivity) or on the basis of any prescription filled for a stimulant (either an amphetamine or another type) in any insurance claim for a health care encounter between the child’s date of birth and the end of the study period. The second criterion was added to account for potential undercoding of ICD-9 ADHD codes in claims data. Details regarding diagnosis and classification are provided in the Supplementary Appendix, available with the full text of this article at NEJM.org. A secondary outcome was treatment for ADHD. We also assessed the intensity of treatment among children who received ADHD medication by determining the total number of days of ADHD medication supplied to each child throughout all years of the study period.

For children in a birth-year cohort who were born before September 1, we excluded diagnoses from 2015 so that children with August birthdays, who entered kindergarten at a younger age than their peers, would have the same number of school years to potentially receive a diagnosis of ADHD as those with September birthdays, who entered kindergarten at an older age than their peers. This ensured that any difference in diagnosis rates between children born in August and children born in September was due to relative age within the child’s grade rather than to August-born children having spent more years in school, which would have provided a longer period during which the diagnosis could be given.

Statistical Analysis

For our primary analysis, we used multivariable linear regression to compare the rate of ADHD diagnosis among children born in August with the rate among children born in September, and we evaluated statistical differences with t-tests. This analysis relied on the assumption that children born in August and September were similar both in known demographic and clinical characteristics and in unobserved factors that could influence rates of ADHD diagnosis, given that the September 1 cutoff is arbitrary, and parents most likely do not systematically plan births to occur in a particular month in preference to another. To validate this assumption, we compared rates of childhood health conditions other than ADHD among August-born and September-born children and assessed the characteristics of the parents of children born in August and the parents of children born in September with chi-square and t-tests where appropriate; all these variables should have been similar in these two groups. We also plotted birth months to ensure an even distribution of children in each month; an uneven distribution would suggest unobserved differences between groups.

In addition to comparing rates of ADHD diagnosis between children born in August and those born in September, we investigated the age at which the difference in ADHD diagnosis between August-born and September-born children appeared, using outcome variables indicating ADHD diagnosis in 1-year age groups from ages 4 through 7. We compared these age-specific rates of ADHD diagnosis and treatment with the use of methods similar to those used in our analyses of overall rates of diagnosis and treatment; we hypothesized that there would be no difference in ADHD diagnosis between August-born and September-born children by age 4 (before the start of kindergarten) but that there would be a difference by age 7 (after school entry).

We investigated differences in the intensity of ADHD treatment between children born in August and children born in September to determine whether the August-born children who received a diagnosis of ADHD but who may not have received this diagnosis if they had been born in September (and therefore would have started school later) received less intensive treatment, which would have occurred if the diagnosis had been less certain for these children. A finding that August-born children received fewer days of medication than September-born children would indicate that these children at the margin for ADHD diagnosis and treatment may receive treatment of lesser duration than those born in September; this might occur if children born in August have symptoms that resolve with age, which would lead to earlier discontinuation of therapy.

We conducted several additional analyses to ensure that differences in ADHD diagnosis rates between August-born and September-born children were not spurious. First, we compared differences in diagnosis rates between other consecutive birth months (e.g., between January and February and between February and March), expecting no between-month differences in diagnosis rates.19 Second, we assessed ADHD diagnosis rates among children who lived in states without a September 1 cutoff, expecting no difference in diagnosis rates between August-born and September-born children. Third, we compared rates of asthma, diabetes, and obesity among August-born and September-born children in an additional sensitivity analysis; these rates should not have been affected by birth in August as compared with birth in September because the diagnosis of those conditions is not influenced by the relative behavior of a child within a class.20 Fourth, we modified our baseline analysis with the use of a multivariable linear-regression model, with adjustment for a detailed set of covariates, including the sex of the child, the age of each insured parent, and the Charlson comorbidity index for each parent. (The Charlson comorbidity index includes 19 conditions and is used to predict 10-year mortality; values range from 0 to 37, with higher values indicating more coexisting conditions.21) We also adjusted for indicator variables for status with respect to asthma, anxiety, depression, obsessive–compulsive disorder, bipolar disorder, obesity, and diabetes in children and parents. Fixed effects for the year of birth and state of residence of each child were also included. Finally, we performed a regression-discontinuity analysis (see the Supplementary Appendix). Analyses were performed with Stata software, version 15 (StataCorp). The 95% confidence interval around the reported estimates reflects an alpha level of 0.025 in each tail (or P≤0.05). P values were calculated with the use of t-tests of the coefficients from linear-regression models.