Understanding the relationship between income and mental health among 16- to 24-year-olds: Analysis of 10 waves (2009–2020) of Understanding Society to enable modelling of income interventions

Author:

Parra-Mujica Fiorella,Johnson ElliottORCID,Reed Howard,Cookson Richard,Johnson MatthewORCID

Abstract

A substantial body of evidence suggests that young people, including those at the crucial transition points between 16 and 24, now face severe mental health challenges. In this article, we analyse data from 10 waves of a major UK longitudinal household cohort study, Understanding Society, to examine the relationship between income and anxiety and depression among 16- to 24-year-olds. Using random effects logistic regression (Model 1) allowing for whether the individual was depressed in the previous period as well as sex, age, ethnicity, whether the individual was born in the UK, region, rurality, highest qualification, marital status, employment status and attrition, we find a significant and inversely monotonic adjusted association between average net equivalised household income quintiles and clinical threshold levels of depressive symptoms SF-12 Mental Component Summary (MCS score ≤45.6). This means that being in a higher income group is associated with a reduced likelihood of clinically significant depressive symptoms, allowing for observable confounding variables. Using a ‘within-between’ model (Model 2), we find that apart from among those with the very highest incomes, increases in average net equivalised household income over the course of childhood and adolescence are significantly associated with reduced symptoms of anxiety and depression as measured by a higher SF-12 MCS score. Compared with previous reviews, the data presented here provides an estimate of the magnitude of effect that helps facilitate microsimulation modelling of impact on anxiety and depression from changes in socioeconomic circumstances. This enables a more detailed and complete understanding of the types of socioeconomic intervention that might begin to address some of the causes of youth mental health problems.

Funder

Wellcome Trust

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference54 articles.

1. NatCen Social Research. Adult Psychiatric Morbidity Survey 2014, Chapter 2: Common Mental Disorders-Data Tables. Leeds: NHS Digital

2. 2016 [cited 2022 May 31]. https://digital.nhs.uk/data-and-information/publications/statistical/adult-psychiatric-morbidity-survey/adult-psychiatric-morbidity-survey-survey-of-mental-health-and-wellbeing-england-2014.

3. Clarke A, Pote I, Sorgenfrei M. Adolescent mental health evidence brief 1: Prevalence of disorders. London: Early Intervention Foundation; 2020 [cited 2022 May 31]. https://www.eif.org.uk/report/adolescent-mental-health-evidence-brief-1-prevalence-of-disorders.

4. NHS Digital. MHSDS Monthly: Performance February 2022 MHSDS Data File. Mental Health Services Monthly Statistics, Performance February, Provisional March 2022. 2022 [cited 2022 May 24]. https://digital.nhs.uk/data-and-information/publications/statistical/mental-health-services-monthly-statistics/performance-february-provisional-march-2022.

5. NHS Digital. MHSDS Monthly: End of Year Final February 2020 MHSDS Data File. Mental Health Services Monthly Statistics—Final February, Provisional March 2020. 2020 [cited 2022 May 24]. https://digital.nhs.uk/data-and-information/publications/statistical/mental-health-services-monthly-statistics/final-february-provisional-march-2020.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3