Risk factors associated with newly diagnosed attention-deficit/hyperactivity disorder in adults: a retrospective case-control study
Bibliographic record
Abstract
BACKGROUND: Knowledge of risk factors for attention-deficit/hyperactivity disorder (ADHD) may facilitate early diagnosis; however, studies examining a broad range of potential risk factors for ADHD in adults are limited. This study aimed to identify risk factors associated with newly diagnosed ADHD among adults in the United States (US). METHODS: Eligible adults from the IQVIA PharMetrics® Plus database (10/01/2015-09/30/2021) were classified into the ADHD cohort if they had ≥ 2 ADHD diagnoses (index date: first ADHD diagnosis) and into the non-ADHD cohort if they had no observed ADHD diagnosis (index date: random date) with a 1:3 case-to-control ratio. Risk factors for newly diagnosed ADHD were assessed during the 12-month baseline period; logistic regression with stepwise variable selection was used to assess statistically significant association. The combined impact of selected risk factors was explored using common patient profiles. RESULTS: A total of 337,034 patients were included in the ADHD cohort (mean age 35.2 years; 54.5% female) and 1,011,102 in the non-ADHD cohort (mean age 44.0 years; 52.4% female). During the baseline period, the most frequent mental health comorbidities in the ADHD and non-ADHD cohorts were anxiety disorders (34.4% and 11.1%) and depressive disorders (27.9% and 7.8%). Accordingly, a higher proportion of patients in the ADHD cohort received antianxiety agents (20.6% and 8.3%) and antidepressants (40.9% and 15.8%). Key risk factors associated with a significantly increased probability of ADHD included the number of mental health comorbidities (odds ratio [OR] for 1 comorbidity: 1.41; ≥2 comorbidities: 1.45), along with certain mental health comorbidities (e.g., feeding and eating disorders [OR: 1.88], bipolar disorders [OR: 1.50], depressive disorders [OR: 1.37], trauma- and stressor-related disorders [OR: 1.27], anxiety disorders [OR: 1.24]), use of antidepressants (OR: 1.87) and antianxiety agents (OR: 1.40), and having ≥ 1 psychotherapy visit (OR: 1.70), ≥ 1 specialist visit (OR: 1.30), and ≥ 10 outpatient visits (OR: 1.51) (all p < 0.05). The predicted risk of ADHD for patients with treated anxiety and depressive disorders was 81.9%. CONCLUSIONS: Mental health comorbidities and related treatments are significantly associated with newly diagnosed ADHD in US adults. Screening for patients with risk factors for ADHD may allow early diagnosis and appropriate management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".