Evidence map›Paper›PMID 39187800›Full record

ArticleBMC public health2024

Parental domestic violence and abuse, mental ill-health, and substance misuse and the impact on child mental health: a secondary data analysis using the UK Millennium Cohort Study.

Kate Allen, G J Melendez-Torres, Tamsin Ford, Chris Bonell, Vashti Berry

Abstract read
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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Kate AllenUniversity of Exeter, South Cloisters, St Luke's Campus, College Road, Exeter, EX1 1TE, UK. kate.allen@exeter.ac.uk.ORCID 0000-0002-0870-7209
G J Melendez-TorresUniversity of Exeter, South Cloisters, St Luke's Campus, College Road, Exeter, EX1 1TE, UK.ORCID 0000-0002-9823-4790
Tamsin FordDepartment of Psychiatry, University of Cambridge, Herchel Smith Building, Forvie Site, Robinson Way, Cambridge, CB2 0SZ, UK.ORCID 0000-0001-5295-4904
Chris BonellLondon School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK.ORCID 0000-0002-6253-6498
Vashti BerryUniversity of Exeter, South Cloisters, St Luke's Campus, College Road, Exeter, EX1 1TE, UK.ORCID 0000-0001-6438-3731

Funding

National Institute for Health Research Applied Research Collaboration South West Peninsula NIHR200167
6 · The paper itself

Abstract

backgroundParental domestic violence and abuse (DVA), mental ill-health (MH), and substance misuse (SU) can have a negative impact on both parents and children. However, it remains unclear if and how parental DVA, MH, and SU cluster and the impacts this clustering might have. We examined how parental DVA, MH, and SU cluster during early childhood, the demographic/contextual profiles of these clusters, and how these clusters relate to child MH trajectories.

methodsWe examined data from 15,377 families in the UK Millennium Cohort Study. We used: (1) latent class analysis to create groups differentially exposed to parental DVA, MH, and SU at age three; (2) latent growth curve modelling to create latent trajectories of child MH from ages 3-17; and (3) a case-weight approach to relate latent classes to child MH trajectories.

resultsWe identified three latent classes: high-frequency alcohol use (11.9%), elevated adversity (3.5%), and low-level adversity (84.6%). Children in the elevated adversity class had higher probabilities of being from low-socioeconomic backgrounds and having White, younger parents. Children exposed to elevated adversity displayed worse MH at age three (intercept = 2.274; p < 0.001) compared the low-level adversity (intercept = 2.228; p < 0.001) and high-frequency alcohol use class (intercept = 2.068; p < 0.001). However, latent growth factors (linear and quadratic terms) of child MH did not differ by latent class.

conclusionsParental DVA, MH, and SU cluster during early childhood and this has a negative impact on children's MH at age three, leading to similar levels of poor MH across time. Intervening early to prevent the initial deterioration, using a syndemic-approach is essential.

Indexed as

Domestic ViolenceMental DisordersSubstance-Related DisordersAdolescentChildChild, PreschoolCohort StudiesData AnalysisFemaleHumansLatent Class AnalysisMaleMental HealthParentsSecondary Data AnalysisUnited KingdomAdverse childhood experiencesChild mental healthDomestic violence and abuseLatent variable mixture modellingMental ill-healthSubstance misuse

Identifiers

PMID39187800
PMCPMC11346203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.