Evidence map›Paper›PMID 33761325›Full record

ArticleJournal of affective disorders2021

Socioeconomic inequality in child mental health during the COVID-19 pandemic: First evidence from China.

Wen Li, Zijing Wang, Guanghai Wang, Patrick Ip, Xiaoning Sun, Yanrui Jiang, Fan Jiang

Abstract read
In one paragraph

Article in Journal of affective disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 3 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Wen LiDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China.
Zijing WangDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China.
Guanghai WangDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China. Electronic address: wang-guanghai@163.com.
Patrick IpDepartment of Pediatric and Adolescent Medicine, The University of Hong Kong, Hong Kong SAR, China.
Xiaoning SunDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China.
Yanrui JiangDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China.
Fan JiangDepartment of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China. Electronic address: fanjiang@shsmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are increasing concerns that the coronavirus disease (COVID-19) pandemic will disproportionately affect socioeconomically disadvantaged children. However, there lacks empirical evidence on socioeconomic inequalities in child mental health and associated factors.

methodsWe conducted a population-based online survey in 21,526 children in China, when children were confined at home for nearly two months during the pandemic. We assessed child mental health problems with the Strengths and Difficulties Questionnaire (SDQ). Parental education level and provincial gross domestic product (GDP) per capita were treated as proxies for individual- and population-level socioeconomic status (SES), respectively. Lifestyle and family environment factors included sleep disturbances, physical activity, screen time, primary caregiver, parental mental health, and harsh parenting.

resultsOf the children, 32.31% demonstrated mental health problems. Parental education from the highest (undergraduate and above) to the lowest (middle school and below) increased the adjusted odds ratio(aOR) for child mental health problems by 42% (aOR, 1.42; 95% CI, 1.29-1.57); provincial GDP per capita (RMB) from the highest (>¥100K) to the lowest (≤¥70K) increased aOR by 41% (aOR, 1.41; 95% CI%, 1.28-1.55). Sleep disturbances, physical activity <1 h/day, media exposure ≥2 h/day, non-parental care, poor parental mental health, and harsh parenting were independently associated with increased child mental health problems, regardless of SES. LIMITATIONS: The potential sampling bias, subjective measures, and the cross-sectional design are the main limitations.

conclusionThe first evidence from China suggests socioeconomic inequality in child mental health during the pandemic. As unhealthy lifestyle and unfavorable family environment are contributory factors, prioritized interventions are needed to reduce socioeconomic inequality in child mental health problems.

Indexed as

CoronavirusCOVID-19ChildChinaCross-Sectional StudiesHumansMental HealthPandemicsSARS-CoV-2Socioeconomic FactorsSurveys and QuestionnairesChild mental healthChinaCOVID-19Family environmentLifestyleSocioeconomic inequality

Identifiers

PMID33761325
PMCPMC9754677

What OpenQuestion holds

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Registered trials

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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.