Medication use for depression and anxiety: data collected from 28/29 year-old offspring in the Avon Longitudinal Study of Parents and Children

Holly Fraser, Gail White, Sarah Matthews, Dheeraj Rai, Brit Davidson, Rebecca Pearson, Ryan McConville, Alex Kwong

Research output: Contribution to journalArticlepeer-review

Abstract

Patterns of mental health have been well characterised in the Avon Longitudinal Study of Parents and Children (ALSPAC), but there is a paucity of longitudinal medication data for depression and anxiety within the ALSPAC study. Understanding types and usage of pharmacological treatment allows for a deeper understanding of mental health in the ALSPAC study and key factors influencing illness outcomes, such as access to service provision. Enhanced understanding of the types of medication people have used to manage depression and anxiety could also give insight into which treatments work for individuals over the life course. This data note describes data collection on medication for depression and anxiety in the offspring (ALSPAC-G1) at ages 28-29 (born 1991/1992). Data were collected through a questionnaire deployed between December 2020 and April 2021. First, we highlight the variables collected as part of the questionnaire, specifically on medication use for depression and anxiety. We then outline how we have derived antidepressant variables including type of antidepressants, length of time used, and treatment phenotypes such as ‘remission’ and ‘non remission’. Finally, we also report associations between longitudinal mental health variables and reported use of medication and antidepressant variables to validate these new measures. Considerations for how the data collected can be used for researchers is also summarised.
Original languageEnglish
JournalWellcome Open Research
Early online date9 Jun 2023
DOIs
Publication statusPublished - 9 Jun 2023

Bibliographical note

Grant Information: The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and HF and ASFK will serve as guarantors for the contents of this paper. The lead author is supported by the EPSRC Digital Health and Care Centre for Doctoral Training (CDT) at the University of Bristol (UKRI Grant No. EP/S023704/1). This work was also supported by the Elizabeth Blackwell Institute, University of Bristol, the Wellcome Trust Institutional Strategic Support Fund and the Rosetrees Trust (Grant ref: 204813/Z/16/Z).

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