The temporal order of fluctuations in atopic disease symptoms and attention-deficit/hyperactivity disorder symptoms: a time-series study in ADHD patients.
Jurjen van der SchansQi CaoElisabeth H BosG Ingrid J G RoursPieter J HoekstraEelko HakTjalling W de VriesPublished in: European child & adolescent psychiatry (2019)
In a recent meta-analysis, we found that atopic diseases, like asthma and allergic rhinitis, occur more frequently prior to the onset of attention-deficit/hyperactivity disorder (ADHD). Our aim was to determine the temporal order of the association between daily fluctuations in atopic disease symptoms and in ADHD symptoms in individual participants. In this observational study among 21 participants, age 7-16 years, we performed a replicated time-series analysis of symptom fluctuations in asthma and/or allergic rhinitis and ADHD. Data were collected through parents who filled in a daily online questionnaire during up to 50 days. In each individual, we investigated the temporal order of fluctuations in atopic disease symptoms and ADHD symptoms using a vector autoregressive (VAR) model while using sleep problems and medication use as covariates. For 16 out of 21 participants, we constructed a VAR model. For a majority of the participants, significant associations were detected between atopic disease symptoms and ADHD symptoms. The results were heterogeneous; the direction, sign, and timing of the relationship between ADHD, atopy, sleep problems, and medication use varied between individuals. This study provides additional evidence that the symptom expression of atopy and ADHD are related. However, the connection between both diseases in children is found to be heterogeneous within our study population.
Keyphrases
- attention deficit hyperactivity disorder
- autism spectrum disorder
- allergic rhinitis
- sleep quality
- working memory
- systematic review
- physical activity
- young adults
- mental health
- chronic obstructive pulmonary disease
- newly diagnosed
- ejection fraction
- randomized controlled trial
- big data
- electronic health record
- prognostic factors
- single molecule
- high speed
- artificial intelligence
- data analysis