ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis

Guilherme V Polanczyk, Erik G Willcutt, Giovanni A Salum, Christian Kieling, Luis A Rohde, Guilherme V Polanczyk, Erik G Willcutt, Giovanni A Salum, Christian Kieling, Luis A Rohde

Abstract

Background: Previous studies have identified significant variability in attention-deficit / hyperactivity disorder (ADHD) prevalence estimates worldwide, largely explained by methodological procedures. However, increasing rates of ADHD diagnosis and treatment throughout the past few decades have fuelled concerns about whether the true prevalence of the disorder has increased over time.

Methods: We updated the two most comprehensive systematic reviews on ADHD prevalence available in the literature. Meta-regression analyses were conducted to test the effect of year of study in the context of both methodological variables that determined variability in ADHD prevalence (diagnostic criteria, impairment criterion and source of information), and the geographical location of studies.

Results: We identified 154 original studies and included 135 in the multivariate analysis. Methodological procedures investigated were significantly associated with heterogeneity of studies. Geographical location and year of study were not associated with variability in ADHD prevalence estimates.

Conclusions: Confirming previous findings, variability in ADHD prevalence estimates is mostly explained by methodological characteristics of the studies. In the past three decades, there has been no evidence to suggest an increase in the number of children in the community who meet criteria for ADHD when standardized diagnostic procedures are followed.

Keywords: ADHD; cross-cultural; epidemiology; methodology; prevalence; time.

Figures

Figure 1.
Figure 1.
ADHD prevalence estimates as a function of year of study publication. The point sizes are drawn proportional to the inverse of the standard errors. The predicted average prevalence estimate rate based on a mixed-effects model is added to the plot (with corresponding 95% confidence interval bounds).
Figure 2.
Figure 2.
ADHD prevalence estimates over time, as a function of diagnostic criteria (A) and geographical location of studies (B).

Source: PubMed

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