Stronger association of perceived health with socio-economic inequality during COVID-19 pandemic than pre-pandemic era
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yun, Je-Yeon | - |
dc.contributor.author | Sim, Jin-Ah | - |
dc.contributor.author | Lee, Sujee | - |
dc.contributor.author | Yun, Young Ho | - |
dc.date.accessioned | 2023-03-23T06:40:07Z | - |
dc.date.available | 2023-03-23T06:40:07Z | - |
dc.date.created | 2023-02-27 | - |
dc.date.issued | 2022-09 | - |
dc.identifier.issn | 1471-2458 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/43489 | - |
dc.description.abstract | Objective The COVID-19 pandemic has changed peoples' routine of daily living and posed major risks to global health and economy. Few studies have examined differential impacts of economic factors on health during pandemic compared to pre-pandemic. We aimed to compare the strength of associations between perceived health and socioeconomic position (household income, educational attainment, and employment) estimated before and during the pandemic. Methods Two waves of nationwide survey [on 2018(T1;n = 1200) and 2021(T2;n = 1000)] were done for 2200 community adults. A balanced distribution of confounders (demographics and socioeconomic position) were achieved across the T2 and T1 by use of the inverse probability of treatment weighting. Distributions of perceived health [= (excellent or very good)/(bad, fair, or good)] for physical-mental-social-spiritual subdomains were compared between T1 and T2. Odds of bad/fair/good health for demographics and socioeconomic position were obtained by univariate logistic regression. Adjusted odds (aOR) of bad/fair/good health in lower household income(< 3000 U.S. dollars/month) were retrieved using the multiple hierarchical logistic regression models of T1 and T2. Results Perceived health of excellent/very good at T2 was higher than T1 for physical(T1 = 36.05%, T2 = 39.13%; P = 0.04), but were lower for mental(T1 = 38.71%, T2 = 35.17%; P = 0.01) and social(T1 = 42.48%, T2 = 35.17%; P < 0.001) subdomains. Odds of bad/fair/good health were significantly increased at T2 than T1 for household income (physical-mental-social; all Ps < 0.001) and educational attainment (social; P = 0.04) but not for employment (all Ps > 0.05). AORs of bad/fair/good health in lower household income were stronger in T2 than T1, for mental [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.82(P < 0.001)], physical [aOR (95% CI) = 2.64(2.05-3.41) in T2, 1.50(1.18-1.90) in T1; aOR difference = 1.14(P < 0.001)] and social [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.35(P = 0.049)] subdomains. Conclusions Risks of perceived health worsening for mental and social subdomains in people with lower monthly household income or lower educational attainment became stronger during the COVID-19 pandemic compared to pre-pandemic era. In consideration of the prolonged pandemic as of mid-2022, policies aiming not only to sustain the monthly household income and compulsory education but also to actively enhance the perceived mental-social health status have to be executed and maintained. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | BMC | - |
dc.relation.isPartOf | BMC PUBLIC HEALTH | - |
dc.title | Stronger association of perceived health with socio-economic inequality during COVID-19 pandemic than pre-pandemic era | - |
dc.type | Article | - |
dc.identifier.doi | 10.1186/s12889-022-14176-8 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | BMC PUBLIC HEALTH, v.22, no.1 | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000854508200006 | - |
dc.identifier.scopusid | 2-s2.0-85138143897 | - |
dc.citation.number | 1 | - |
dc.citation.title | BMC PUBLIC HEALTH | - |
dc.citation.volume | 22 | - |
dc.contributor.affiliatedAuthor | Lee, Sujee | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.subject.keywordAuthor | COVID-19 | - |
dc.subject.keywordAuthor | perceived health | - |
dc.subject.keywordAuthor | socioeconomic position | - |
dc.subject.keywordAuthor | Physical health | - |
dc.subject.keywordAuthor | Mental health | - |
dc.subject.keywordAuthor | Social health | - |
dc.subject.keywordAuthor | Logistic regression model | - |
dc.subject.keywordPlus | PROPENSITY SCORE METHODS | - |
dc.subject.keywordPlus | FINANCIAL DIFFICULTIES | - |
dc.subject.keywordPlus | CARE UTILIZATION | - |
dc.subject.keywordPlus | OUTCOMES | - |
dc.subject.keywordPlus | INCOME | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Soongsil University Library 369 Sangdo-Ro, Dongjak-Gu, Seoul, Korea (06978)02-820-0733
COPYRIGHT ⓒ SOONGSIL UNIVERSITY, ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.