Review articleRisk and protective factors for mental disorders with onset in childhood/adolescence: An umbrella review of published meta-analyses of observational longitudinal studies
Introduction
It is commonly recognized that a large portion of mental disorders have their onset before age 18 (Paus et al., 2008). However, some of them have an even earlier onset. Mental disorders with onset in childhood are grouped differently in the 10th and 11th versions of the International Classification of Diseases ((ICD)-10 (WHO, 2019a) and ICD-11 (WHO, 2019b), respectively). In ICD-10, they are classified under “V - Mental and behavioural disorders”, “F80-F89 Disorders of psychological development”, and “F90-F98 Behavioural and emotional disorders with onset usually occurring in childhood and adolescence”, while in the ICD-11 they are grouped under “06 - Mental, behavioural or neurodevelopmental disorders”, “Neurodevelopmental disorders”, and “Disruptive behaviour or dissocial disorders”. Despite being defined as individual categorical entities, or even being clustered in different blocks within and across ICD-10 and ICD-11, the above listed disorders are characterised by their onset, which is typically in childhood. Importantly, in terms of clinical presentation, there is a high degree of overlap among some of these disorders, which provides a strong rationale for considering them together when exploring their putative patho-etiology (Thapar et al., 2017). These childhood-onset disorders present complex and heterogeneous patho-etiology, and, although highly heritable (Lord et al., 2018; Yousaf et al., 2020; Demontis et al., 2019; Lichtenstein et al., 2010), their aetiology is typically multifactorial (with the exception of cases with single major causes, such as patients with fetal alcohol syndrome or specific genetic syndromes). Several putative environmental risk and protective factors have been proposed and assessed in several meta-analyses, with conflicting results. Gaining insight on credible risk or protective factors for neurodevelopmental disorders is a crucial initial step to illuminate the development of preventative strategies for these disorders aimed at reducing the significant financial and societal burden related to mental disorders with onset in childhood (Arim et al., 2017; Arango et al., 2018). While two recent umbrella reviews (Kim et al., 2019, 2020) have graded the available evidence from meta-analyses of observational studies on risk factors for autism-spectrum disorder (ASD) (Kim et al., 2019), and attention-deficit/hyperactivity disorder (ADHD), Kim et al., 2020) respectively, the credibility of the claimed associations between putative risk factors for other neurodevelopmental disorders and disorders with onset in childhood remains unknown. To fill this gap in the literature, we conducted an umbrella review focused on environmental risk and protective factors for disorders with onset in childhood other than ADHD or ASD. Of note, we endeavoured to address possible methodological issues when assessing putative risk factors. Indeed, as shown in several previous umbrella reviews on risk factors for mental disorders or obesity, (Kim et al., 2019; Solmi et al., 2020; Köhler et al., 2018; Bortolato et al., 2017; Solmi et al., 2018a) several sources of bias are present across studies, which individually or altogether can contribute to over- or underestimate the associations between socio-demographic, health, environmental, and other risk factors and disorders. Additionally, when medications are considered as potential risk factors, confounding by indication can affect several false positive claimed associations between medications and disorders’ onset (Solmi et al., 2018b). Therefore, the aim of this umbrella review was to grade the evidence from meta-analyses of cohort and case-control studies on protective and risk factors for the most important mental disorders with onset in childhood accounting for several sources of bias and applying established quantitative criteria.
Section snippets
Methods
This study was conducted according to state-of-the-art methods of previously published umbrella reviews (Kim et al., 2019; Dragioti et al., 2019, 2017; Bellou et al., 2017; Belbasis et al., 2015; Radua et al., 2018). The study followed an a-priori protocol uploaded in Center for Open Science (https://osf.io/ejrfs/?view_only = 41603e4db20d40538b32d542010bb79c). The Meta-analysis of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and
Search results
We initially identified 6581 possibly relevant articles, screened 272 full-text articles, and eventually included ten articles in this umbrella review (Fig. 1; Table 2) (Lee et al., 2018; Papola et al., 2019; Lee et al., 2018; Poels et al., 2018; Radke et al., 2020; Rochelle and Talcott, 2006; Ruisch et al., 2018; Sanchez et al., 2018; Thompson et al., 2018; Yew and O’Kearney, 2013; Zhang et al., 2019; Birks et al., 2017). Reasons for exclusion for each reference for which full text was checked
Discussion
To our knowledge, this is the first umbrella review assessing systematic reviews with meta-analysis on risk or protective factors for mental disorders with onset in childhood (other than ASD and ADHD), exclusively focusing on case-control and retrospective/prospective cohort studies. This umbrella review shows that no convincing nor highly suggestive evidence supports any risk or protective factor, that the only risk factor supported by suggestive evidence is affected by confounding by
Declaration of Competing Interest
MS, ED, EO, FCS, PM, LM, JR, SC have no conflict of interest to declare.
CA has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda.
CUC has been a consultant and/or advisor to or have received honoraria from: Alkermes, Allergan, Angelini, Boehringer-Ingelheim, Gedeon Richter, Gerson Lehrman Group, Indivior,
Acknowledgements
No funding supported the present study
CA is supported by the Spanish Ministry of Science and Innovation. Instituto de Salud Carlos III (SAM16PE07CP1,PI16/02012,PI19/024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds. European Union H2020 Program under the Innovative Medicines Initiative 2 Joint Undertaking (grant agreement No 115916, Project PRISM, and grant
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