DOI: 10.1177/17455057261476912 ISSN: 1745-5057

The monthly spectrum: Premenstrual symptoms across ADHD and autism

Annabeth P. Groenman, Lotte E. Welling, Sara Pieters

Background

Women with ADHD and autism experience elevated rates of premenstrual problems, yet no direct comparisons between these conditions exist in adults.

Objectives

This study examined premenstrual dysphoric disorder (PMDD) prevalence, symptoms, and impairment across ADHD, autism, and neurotypical women.

Design

Cross-sectional data from 199 women aged 20-40 without hormonal contraceptive use were analyzed across two samples.

Methods

Participants included 89 with ADHD, 39 with autism, and 71 controls. Premenstrual symptoms were assessed using the Premenstrual Symptoms Screening Tool (PSST), alongside measures of ADHD characteristics, autism traits, and sensory hypersensitivity.

Results

Both ADHD and autistic women showed significantly elevated provisional PMDD rates according to the PSST screening instrument compared to controls, with no significant difference between neurodivergent groups. Dimensional analyses revealed positive associations between premenstrual symptoms and neurodiverse traits, particularly inattention, hyperactivity-impulsivity, and social skills difficulties. The impact of premenstrual problems was similarly associated with these traits across diagnostic groups. Contrary to hypotheses, sensory hypersensitivity was not independently associated with premenstrual symptoms after controlling for ADHD and autism characteristics.

Conclusions

Premenstrual problems constitute a significant burden for both ADHD and autistic women, with dimensional associations suggesting that individuals with more severe neurodivergent traits face heightened risk. Yet our findings also demonstrate that prevalence estimates are only as reliable as the recruitment strategies behind them. Advancing this field requires both greater clinical attention to menstrual cycle-related difficulties in neurodivergent populations and recruitment strategies that yield dependable estimates.

More from our Archive