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      Association of Social Determinants of Health and Vaccinations With Child Mental Health During the COVID-19 Pandemic in the US

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      , PhD 1 , , , PhD 2 , 3 , , PhD 1 , , MD 4 , 5 , 6
      JAMA Psychiatry
      American Medical Association

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          Abstract

          This cohort study investigates the association of individual and structural social determinants of health and vaccinations with child mental health during the COVID-19 pandemic in the US.

          Key Points

          Question

          To what extent are individual and structural social determinants of health (SDoH) and vaccinations associated with child mental health during the COVID-19 pandemic?

          Findings

          In this cohort study of 8493 US children, pandemic-related food insecurity, parental unemployment, disrupted mental health treatment, living in neighborhoods with higher shares of adults working full-time, and living in states lagging in vaccination rates were associated with increased trajectories of perceived stress, sadness, and COVID-19–related worry. Associations between SDoH and these mental health outcomes were more common among Asian, Black, and Hispanic children more than White children.

          Meaning

          Supporting children’s mental health requires multifaceted policies that address SDoH and structural barriers to food, health services, employment protection, and vaccination.

          Abstract

          Importance

          The COVID-19 pandemic disproportionately affected mental health in socioeconomically disadvantaged children in the US. However, little is known about the relationship of preexisting and time-varying social determinants of health (SDoH) at individual and structural levels, vaccination eligibility/rates, and the racial and ethnic differences to trajectories of child mental health during the COVID-19 pandemic.

          Objective

          To estimate the association of trajectories of child mental health to multilevel SDoH and vaccination eligibility/rates.

          Design, Setting, and Participants

          This prospective longitudinal cohort study, conducted from May 16, 2020, to March 2, 2021, integrated structural-level, pandemic-related data with the Adolescent Brain Cognitive Development (ABCD) cohort data (release 4.0). The ABCD study recruited 11 878 children (baseline) and conducted 6 COVID-19 rapid response surveys across 21 US sites (in 17 states) from May 16, 2020, to March 2, 2021.

          Exposures

          Preexisting individual (eg, household income) and structural (area deprivation) SDoH and time-varying individual (eg, food insecurity, unemployment) and structural (eg, social distancing, vaccination eligibility/rates) SDoH.

          Main Outcomes and Measures

          Perceived Stress Scale, the National Institutes of Health–Toolbox emotion measures, and COVID-19–related worry.

          Results

          The longitudinal sample included 8493 children (mean [SD] age, 9.93 [0.63] years; 5011 girls [47.89%]; 245 Asian [2.34%], 1213 Black [11.59%], 2029 Hispanic [19.39%], 5851 White [55.93%], and 1124 children of other/multiracial ethnicity [10.74%]). Trajectories of stress, sadness, and COVID-19–related worry decreased after adult vaccination rollout. Compared with younger children, boys, White children, or those living with married parents, those who reported greater perceived stress included older children aged 12 to 15 years (β = 0.26; 95% CI, 0.12-0.41; P < .001); girls (β = 0.75; 95% CI, 0.61-0.89; P < .001); Hispanic children (β = 0.24; 95% CI, 0.01-0.47; P = .04); children living with separated parents (β = 0.50; 95% CI, 0.03-0.96; P = .04); children experiencing disrupted medical health care access (β = 0.19; 95% CI, 0.01-0.36; P = .04); children living in economically deprived neighborhoods (β = 0.28; 95% CI, 0.05-0.51; P = .02); children living in areas with more full-time working-class adults who were unable to social distance (β = 1.35; 95% CI, 0.13-2.67; P = .04); and children living in states with fewer fully vaccinated adults (β = 0.59; 95% CI, 0.16-1.02; P = .007). COVID-19 pandemic–related worry was higher among Asian children (β = 0.22; 95% CI, 0.08-0.37; P = .003), Black children (β = 0.33; 95% CI, 0.22-0.43; P < .001), children of other/multiracial ethnicity (β = 0.17; 95% CI, 0.09-0.25; P < .001), and children with disrupted medical health care (β = 0.15; 95% CI, 0.09-0.21) and disrupted mental health treatment (β = 0.11; 95% CI, 0.06-0.16). Inability to afford food was associated with increased sadness (β = 1.50; 95% CI, 0.06-2.93; P = .04). States with later vaccination eligibility dates for all adults were associated with greater COVID-19–related worry (β = 0.16; 95% CI, 0.01-0.31; P = .03) and decreased positive affect (β = −1.78; 95% CI, −3.39 to −0.18; P = .03) among children.

          Conclusions and Relevance

          Results of this study suggest a disproportionately adverse association of the COVID-19 pandemic with child mental health among racial and ethnic minority groups, which may be improved by addressing modifiable individual (food insecurity, unemployment, health services, parental supervision) and structural (area deprivation, job protection, vaccination) SDoH.

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          Most cited references71

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
            • Record: found
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            A Global Measure of Perceived Stress

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              Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population

              Summary Background The potential impact of the COVID-19 pandemic on population mental health is of increasing global concern. We examine changes in adult mental health in the UK population before and during the lockdown. Methods In this secondary analysis of a national, longitudinal cohort study, households that took part in Waves 8 or 9 of the UK Household Longitudinal Study (UKHLS) panel, including all members aged 16 or older in April, 2020, were invited to complete the COVID-19 web survey on April 23–30, 2020. Participants who were unable to make an informed decision as a result of incapacity, or who had unknown postal addresses or addresses abroad were excluded. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). Repeated cross-sectional analyses were done to examine temporal trends. Fixed-effects regression models were fitted to identify within-person change compared with preceding trends. Findings Waves 6–9 of the UKHLS had 53 351 participants. Eligible participants for the COVID-19 web survey were from households that took part in Waves 8 or 9, and 17 452 (41·2%) of 42 330 eligible people participated in the web survey. Population prevalence of clinically significant levels of mental distress rose from 18·9% (95% CI 17·8–20·0) in 2018–19 to 27·3% (26·3–28·2) in April, 2020, one month into UK lockdown. Mean GHQ-12 score also increased over this time, from 11·5 (95% CI 11·3–11·6) in 2018–19, to 12·6 (12·5–12·8) in April, 2020. This was 0·48 (95% CI 0·07–0·90) points higher than expected when accounting for previous upward trends between 2014 and 2018. Comparing GHQ-12 scores within individuals, adjusting for time trends and significant predictors of change, increases were greatest in 18–24-year-olds (2·69 points, 95% CI 1·89–3·48), 25–34-year-olds (1·57, 0·96–2·18), women (0·92, 0·50–1·35), and people living with young children (1·45, 0·79–2·12). People employed before the pandemic also averaged a notable increase in GHQ-12 score (0·63, 95% CI 0·20–1·06). Interpretation By late April, 2020, mental health in the UK had deteriorated compared with pre-COVID-19 trends. Policies emphasising the needs of women, young people, and those with preschool aged children are likely to play an important part in preventing future mental illness. Funding None.

                Author and article information

                Journal
                JAMA Psychiatry
                JAMA Psychiatry
                JAMA Psychiatry
                American Medical Association
                2168-622X
                2168-6238
                27 April 2022
                June 2022
                27 April 2022
                : 79
                : 6
                : 610-621
                Affiliations
                [1 ]Department of Population Health Sciences, Weill Cornell Medicine, New York–Presbyterian, New York
                [2 ]Hong Kong Jockey Club Centre for Suicide Research and Prevention, The University of Hong Kong, Hong Kong
                [3 ]Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong
                [4 ]Department of Psychiatry, Columbia University Irving Medical Center, Columbia University, New York, New York
                [5 ]Department of Radiology, Columbia University Irving Medical Center, Columbia University, New York, New York
                [6 ]Division of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, New York
                Author notes
                Article Information
                Accepted for Publication: March 1, 2022.
                Published Online: April 27, 2022. doi:10.1001/jamapsychiatry.2022.0818
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Xiao Y et al. JAMA Psychiatry.
                Corresponding Author: Yunyu Xiao, PhD, Department of Population Health Sciences, Weill Cornell Medicine, New York–Presbyterian, Division 306, 425 E 61 St, New York, NY 10065 ( yux4008@ 123456med.cornell.edu ).
                Author Contributions: Dr Xiao had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: All authors.
                Acquisition, analysis, or interpretation of data: Xiao, Pathak, Mann.
                Drafting of the manuscript: Xiao, Pathak.
                Critical revision of the manuscript for important intellectual content: All authors.
                Statistical analysis: Xiao, Yip.
                Obtained funding: Xiao.
                Administrative, technical, or material support: Xiao, Pathak.
                Supervision: Pathak, Mann.
                Conflict of Interest Disclosures: Dr Xiao reported receiving grants from the Bill & Melinda Gates Foundation during the conduct of the study. Dr Mann reported receiving royalties for commercial use of the Columbia Suicide Severity Rating Scale paid from the Research Foundation for Mental Hygiene. No other disclosures were reported.
                Funding/Support: This research is supported by grant CORONAVIRUSHUB-D-21-00125 from the Bill & Melinda Gates Foundation and a Research Grants Council Collaborative Research Fund grant (C7151-20G) from the University Grants Committee of Hong Kong.
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Article
                yoi220022
                10.1001/jamapsychiatry.2022.0818
                9047762
                35475851
                33d8cb83-82bb-48d5-9094-dfd94c8379d6
                Copyright 2022 Xiao Y et al. JAMA Psychiatry.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 22 November 2021
                : 1 March 2022
                Funding
                Funded by: Bill & Melinda Gates Foundation
                Funded by: University Grants Committee of Hong Kong
                Categories
                Research
                Research
                Original Investigation
                Online First
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