Effect of the COVID-19 pandemic on the well-being of middle-aged and older Europeans.
COVID-19 pandemic
Elderly
Latent score change
Longitudinal study
SHARE
Well-being
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
28 10 2024
28 10 2024
Historique:
received:
12
03
2024
accepted:
26
09
2024
medline:
29
10
2024
pubmed:
29
10
2024
entrez:
29
10
2024
Statut:
epublish
Résumé
The COVID-19 pandemic has been associated with a general decline in well-being. However, there is limited evidence on the effect of the pandemic on the general population, and especially among the ageing population. We assessed the overall impact of the pandemic on the well-being of middle-aged and older adults residing in 27 European countries, focusing on the time-period before summer 2021. We used a sample of 46,209 respondents from the two population-based longitudinal Corona Surveys collected during summer 2020 and summer 2021. To test our hypotheses, we used latent change score models. All analyses were stratified by sex. The COVID-19 pandemic affected middle-aged and older Europeans' well-being irrespective of their sex. Being infected by the COVID-19 virus at the start of the pandemic had a negative impact on well-being. As expected, adults with Long COVID experienced the most pronounced decline in well-being. A novel finding was the decline in the level of well-being among adults not infected by the COVID-19 virus. Support should be provided at community levels with specific attention towards individuals with Long COVID symptoms and those infected with COVID-19 at earlier stages of the pandemic.
Identifiants
pubmed: 39468090
doi: 10.1038/s41598-024-74429-x
pii: 10.1038/s41598-024-74429-x
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
25796Informations de copyright
© 2024. The Author(s).
Références
COVID-19 statistics for the European Region. [ https://www.who.int/europe/data ]
Wilk, P. et al. The role of multimorbidity and socio-economic characteristics as potential risk factors for Long Covid: evidence from the multilevel analysis of the Survey of Health, Ageing and Retirement in Europe’s corona surveys (2020–2021). Age Ageing 52(12), afad225 (2023).
Wilding, S. et al. Probable COVID-19 infection is associated with subsequent poorer mental health and greater loneliness in the UK COVID-19 Mental Health and Wellbeing study. Sci. Rep. 12, 20795 (2022).
pubmed: 36460665
pmcid: 9718764
doi: 10.1038/s41598-022-24240-3
Magnúsdóttir, I. et al. Acute COVID-19 severity and mental health morbidity trajectories in patient populations of six nations: an observational study. Lancet Public. Health. 7, e406–e416 (2022).
pubmed: 35298894
pmcid: 8920517
doi: 10.1016/S2468-2667(22)00042-1
Taquet, M., Luciano, S., Geddes, J.R., Harrison, P.J. Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA. Lancet Psychiatry 8, 130–140 (2021).
Folayan, M. O. et al. Fear of contagion, emotional stress and coping strategies used by adults during the first wave of the COVID-19 pandemic in Nigeria. BMC Psychiatry. 22, 732 (2022).
pubmed: 36424567
pmcid: 9694852
doi: 10.1186/s12888-022-04360-w
Koçak, O., Koçak, Ö. E. & Younis, M. Z. The psychological consequences of COVID-19 fear and the moderator effects of individuals’ underlying illness and witnessing infected friends and family. Int. J. Environ. Res. Public. Health 18(4), 1836 (2021).
Shafran, R., Rachman, S., Whittal, M., Radomsky, A. & Coughtrey, A. Fear and anxiety in COVID-19: preexisting anxiety disorders. Cogn. Behav. Pract. 28, 459–467 (2021).
Grace, M. K. COVID-19 bereavement, depressive symptoms, and binge drinking. SSM Ment Health. 1, 100041 (2021).
pubmed: 34841376
pmcid: 8606021
doi: 10.1016/j.ssmmh.2021.100041
Han, N. et al. Impacts of the COVID-19 pandemic on the Bereaved: a study of Bereaved Weibo users. Healthc. (Basel) 9. (2021).
Figueiredo, E., Margaça, C., Hernández-Sánchez, B. & Sánchez-García, J. C. Teleworking effects on mental health-a systematic review and a research agenda. Int. J. Environ. Res. Public. Health. 21. (2024).
Shim, R. S. Mental Health inequities in the Context of COVID-19. JAMA Netw. Open. 3, e2020104–e2020104 (2020).
Jeriček Klanšček, H. & Furman, L. Socioeconomic deprivation and inequalities in Mental Well-Being during the COVID-19 pandemic among adolescents. Int. J. Environ. Res. Public. Health 20(13), 6233 (2023).
Lombardo, C. et al. Inequalities and mental health during the Coronavirus pandemic in the UK: a mixed-methods exploration. BMC Public. Health. 23, 1830 (2023).
Sudre, C. H. et al. Attributes and predictors of long COVID. Nat. Med. 27, 626–631 (2021).
Daly, M. & Robinson, E. Longitudinal changes in psychological distress in the UK from 2019 to September 2020 during the COVID-19 pandemic: evidence from a large nationally representative study. Psychiatry Res. 300, 113920 (2021).
Alzueta, E. et al. How the COVID-19 pandemic has changed our lives: a study of psychological correlates across 59 countries. J. Clin. Psychol. 77, 556–570 (2021).
Zaninotto, P., Iob, E., Demakakos, P. & Steptoe, A. Immediate and longer-term changes in the Mental Health and Well-being of older adults in England during the COVID-19 pandemic. JAMA Psychiatry. 79, 151–159 (2022).
Kilani, H. A. et al. Healthy lifestyle behaviors are major predictors of mental wellbeing during COVID-19 pandemic confinement: a study on adult arabs in higher educational institutions. PLoS One. 15, e0243524 (2020).
pubmed: 33315880
pmcid: 7735567
doi: 10.1371/journal.pone.0243524
De Pue, S. et al. The impact of the COVID-19 pandemic on wellbeing and cognitive functioning of older adults. Sci. Rep. 11, 4636 (2021).
pubmed: 33633303
pmcid: 7907111
doi: 10.1038/s41598-021-84127-7
Dal Santo, T. et al. Systematic review of mental health symptom changes by sex or gender in early-COVID-19 compared to pre-pandemic. Sci. Rep. 12, 11417 (2022).
pubmed: 35794116
pmcid: 9258011
doi: 10.1038/s41598-022-14746-1
Kwong, A. S. F. et al. Mental health before and during the COVID-19 pandemic in two longitudinal UK population cohorts. Br. J. Psychiatry. 218, 334–343 (2021).
pubmed: 33228822
doi: 10.1192/bjp.2020.242
Pierce, M. et al. Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry. 7, 883–892 (2020).
pubmed: 32707037
pmcid: 7373389
doi: 10.1016/S2215-0366(20)30308-4
The Lancet Regional Health – E. Securing the future of Europe’s ageing population by 2050. Lancet Reg. Health – Europe 35, 100807 (2023).
Ruggeri, K., Garcia-Garzon, E., Maguire, Á., Matz, S. & Huppert, F. A. Well-being is more than happiness and life satisfaction: a multidimensional analysis of 21 countries. Health Qual. Life Outcomes. 18, 192 (2020).
pubmed: 32560725
pmcid: 7304199
doi: 10.1186/s12955-020-01423-y
Chen, C. et al. Global prevalence of Post-coronavirus Disease 2019 (COVID-19) Condition or Long COVID: a Meta-analysis and systematic review. J. Infect. Dis. 226, 1593–1607 (2022).
pubmed: 35429399
doi: 10.1093/infdis/jiac136
Han, Q., Zheng, B., Daines, L. & Sheikh, A. Long-term sequelae of COVID-19: a systematic review and meta-analysis of one-year follow-up studies on post-COVID symptoms. Pathogens 11, 269 (2022).
Kharroubi, S. A. & Diab-El-Harake, M. Sex-differences in COVID-19 diagnosis, risk factors and disease comorbidities: a large US-based cohort study. Front. Public. Health. 10, 1029190 (2022).
pubmed: 36466473
pmcid: 9714345
doi: 10.3389/fpubh.2022.1029190
Abate, B. B., Kassie, A. M., Kassaw, M. W., Aragie, T. G. & Masresha, S. A. Sex difference in coronavirus disease (COVID-19): a systematic review and meta-analysis. BMJ Open. 10, e040129 (2020).
Pelà, G. et al. Sex-related differences in Long-COVID-19 syndrome. J. Womens Health (Larchmt). 31, 620–630 (2022).
pubmed: 35333613
doi: 10.1089/jwh.2021.0411
Sylvester, S. V. et al. Sex differences in sequelae from COVID-19 infection and in long COVID syndrome: a review. Curr. Med. Res. Opin. 38, 1391–1399 (2022).
pubmed: 35726132
doi: 10.1080/03007995.2022.2081454
Bai, F. et al. Female gender is associated with long COVID syndrome: a prospective cohort study. Clin. Microbiol. Infect. 28, 611.e619-611.e616. (2022).
Thompson, E. J. et al. Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records. Nat. Commun. 13, 3528 (2022).
Wilk, P. & Cuschieri, S. Does pre-existing Diabetes Correlate with Long Covid in Europe? Evidence from the Analysis of the Survey of Health, Ageing and Retirement in Europe¿s Corona Surveys (Diabetology & Metabolic Syndrome, 2023).
Cuschieri, S. & Wilk, P. Does pre-existing diabetes correlate with long COVID-19 in Europe? Evidence from the analysis of the survey of health, ageing and retirement in Europe’s corona surveys. J Diabetes Res 2024:7459628. (2024).
Hirschtick, J. L. et al. Population-based estimates of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) prevalence and characteristics. Clin. Infect. Dis. 73, 2055–2064 (2021).
pubmed: 34007978
doi: 10.1093/cid/ciab408
Fernandez-de-Las-Penas, C. et al. Long-term post-COVID symptoms and associated risk factors in previously hospitalized patients: a multicenter study. J. Infect. 83, 237–279 (2021).
pubmed: 33984399
pmcid: 8110627
Phu, D. H. et al. Prevalence and factors associated with long COVID and mental health status among recovered COVID-19 patients in southern Thailand. PLoS One. 18, e0289382 (2023).
pubmed: 37523396
pmcid: 10389739
doi: 10.1371/journal.pone.0289382
Molani, S. et al. Risk factors for severe COVID-19 differ by age for hospitalized adults. Sci. Rep. 12, 6568 (2022).
pubmed: 35484176
pmcid: 9050669
doi: 10.1038/s41598-022-10344-3
D’ascanio, M. et al. Age is not the only risk factor in COVID-19: the role of comorbidities and of long staying in residential care homes. BMC Geriatr. 21, 63 (2021).
pubmed: 33451296
pmcid: 7809533
doi: 10.1186/s12877-021-02013-3
Whitaker, M. et al. Persistent COVID-19 symptoms in a community study of 606,434 people in England. Nat Commun 13, 1957 (2022).
Ziauddeen, N. et al. Characteristics and impact of Long Covid: findings from an online survey. PLoS One. 17, e0264331 (2022).
pubmed: 35259179
pmcid: 8903286
doi: 10.1371/journal.pone.0264331
Hawkins, R. B., Charles, E. J. & Mehaffey, J. H. Socio-economic status and COVID-19-related cases and fatalities. Public. Health. 189, 129–134 (2020).
pubmed: 33227595
doi: 10.1016/j.puhe.2020.09.016
Tang, I. W., Vieira, V. M. & Shearer, E. Effect of socioeconomic factors during the early COVID-19 pandemic: a spatial analysis. BMC Public. Health. 22, 1212 (2022).
pubmed: 35715743
pmcid: 9205762
doi: 10.1186/s12889-022-13618-7
Koffman, J., Gross, J., Etkind, S. N. & Selman, L. Uncertainty and COVID-19: how are we to respond? J. R Soc. Med. 113, 211–216 (2020).
pubmed: 32521198
pmcid: 7439590
doi: 10.1177/0141076820930665
Bohn, M. K. et al. Pathophysiology of COVID-19: mechanisms underlying Disease Severity and Progression. Physiology. 35, 288–301 (2020).
pubmed: 32783610
pmcid: 7426542
doi: 10.1152/physiol.00019.2020
Msemburi, W. et al. The WHO estimates of excess mortality associated with the COVID-19 pandemic. Nature. 613, 130–137 (2023).
pubmed: 36517599
doi: 10.1038/s41586-022-05522-2
Mohammadi, F. et al. The mental health crises of the families of COVID-19 victims: a qualitative study. BMC Fam. Pract. 22, 94 (2021).
pubmed: 33992079
pmcid: 8123094
doi: 10.1186/s12875-021-01442-8
Tracker, O. C. G. R. Facial Coverings (OxBSG) [dataset]. (Data OWi ed. (Blavatnik School of Government, University of Oxford, 2024).
Shi, L. et al. Prevalence of and risk factors associated with mental health symptoms among the general population in China during the Coronavirus Disease 2019 Pandemic. JAMA Netw. Open. 3, e2014053 (2020).
pubmed: 32609353
pmcid: 7330717
doi: 10.1001/jamanetworkopen.2020.14053
Eisenstein, E. M. & Eisenstein, D. A behavioral homeostasis theory of habituation and sensitization: II. Further developments and predictions. Rev. Neurosci. 17, 533–557 (2006).
pubmed: 17180878
doi: 10.1515/REVNEURO.2006.17.5.533
Soriano, J. B., Murthy, S., Marshall, J. C., Relan, P. & Diaz, J. V. Condition WHOCCDWGoP-C-: a clinical case definition of post-COVID-19 condition by a Delphi consensus. Lancet Infect. Dis. 22, e102–e107 (2022).
pubmed: 34951953
doi: 10.1016/S1473-3099(21)00703-9
Aiyegbusi, O. L. et al. Symptoms, complications and management of long COVID: a review. J. R. Soc. Med. 114, 428–442 (2021).
pubmed: 34265229
pmcid: 8450986
doi: 10.1177/01410768211032850
Goodman, M. L., Molldrem, S., Elliott, A., Robertson, D. & Keiser, P. Long COVID and mental health correlates: a new chronic condition fits existing patterns. Health Psychol. Behav. Med. 11, 2164498 (2023).
pubmed: 36643576
pmcid: 9833408
doi: 10.1080/21642850.2022.2164498
Coelho, C. M., Suttiwan, P., Arato, N. & Zsido, A. N. On the nature of fear and anxiety triggered by COVID-19. Front. Psychol. 11, 581314 (2020).
Buecker, S. et al. Changes in daily loneliness for German residents during the first four weeks of the COVID-19 pandemic. Soc. Sci. Med. 265, 113541 (2020).
pubmed: 33248868
doi: 10.1016/j.socscimed.2020.113541
Leigh-Hunt, N. et al. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public. Health. 152, 157–171 (2017).
pubmed: 28915435
doi: 10.1016/j.puhe.2017.07.035
Abdul Rashid, M. R. et al. COVID-19 pandemic fatigue and its sociodemographic, mental health status, and perceived causes: a cross-sectional study nearing the transition to an endemic phase in Malaysia. Int. J. Environ. Res. Public. Health 20, 4476 (2023).
Zarowsky, Z. & Rashid, T. Resilience and wellbeing strategies for pandemic fatigue in Times of Covid-19. Int. J. Appl. Posit. Psychol. 8, 1–36 (2023).
pubmed: 36196257
Gupta, R. et al. Changes in sleep pattern and sleep quality during COVID-19 lockdown. Indian J. Psychiatry. 62, 370–378 (2020).
pubmed: 33165382
pmcid: 7597722
doi: 10.4103/psychiatry.IndianJPsychiatry_523_20
Penninx, B. W. J. H., Benros, M. E., Klein, R. S. & Vinkers, C. H. How COVID-19 shaped mental health: from infection to pandemic effects. Nat. Med. 28, 2027–2037 (2022).
Fleury, A. et al. Can COVID-19 pandemic worsen previous neurological/psychiatric diseases? Neurol. Perspect. 2, 143–150 (2022).
Menting, J., van Schelven, F., Aussems, C., Heijmans, M. & Boeije, H. Routine healthcare disruptions: a longitudinal study on changes in self-management behavior during the COVID-19 pandemic. BMC Health Serv. Res. 23, 196 (2023).
pubmed: 36829185
pmcid: 9951824
doi: 10.1186/s12913-023-09119-x
Cuschieri, S. et al. A case for Cross-border Governance? A comparative Trend Assessment of COVID-19 transmission, vaccination, and outcomes among 35 nations in Europe Across 18 months. Disaster Med. Public. Health Prep. 17, e196 (2022).
Steinert, J. I. et al. COVID-19 vaccine hesitancy in eight European countries: prevalence, determinants, and heterogeneity. Sci. Adv. 8, eabm9825 (2022).
Cadeddu, C. Vaccine hesitancy in Europe: the long and winding road. Eur. J. Pub. Health 33(Supply 2), ckad160.011 (2023).
Hou, Z. et al. Mental health symptoms and sleep quality of asymptomatic/mild SARS-CoV-2 infected individuals during the Omicron wave of the COVID-19 pandemic in Shanghai China. Brain Behav. 12, e2803 (2022).
pubmed: 36326125
pmcid: 9759130
doi: 10.1002/brb3.2803
Connor, J. et al. Health risks and outcomes that disproportionately affect women during the Covid-19 pandemic: a review. Soc. Sci. Med. 266, 113364 (2020).
pubmed: 32950924
pmcid: 7487147
doi: 10.1016/j.socscimed.2020.113364
Hassan MFb, Hassan, N. M., Kassim, E. S. & Said, Y. B. U. Financial Wellbeing and Mental Health: A Systematic Review (Studies of Applied Economics, 2021).
Börsch-Supan, A. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. COVID-19 Survey 1. Release version: 8.0.0. SHARE-ERIC. (2022).
Börsch-Supan, A. Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 9. COVID-19 Survey 2. Release version: 8.0.0. SHARE-ERIC. (2022).
Borsch-Supan, A. et al. Data resource profile: the Survey of Health, Ageing and Retirement in Europe (SHARE). Int. J. Epidemiol. 42, 992–1001 (2013).
pubmed: 23778574
pmcid: 3780997
doi: 10.1093/ije/dyt088
Börsch-Supan, A. & Jürges, H. The Survey of Health, Ageing and Retirement in Europe – Methodology (MEA, 2005).
Hawkley, L. C. & Cacioppo, J. T. Loneliness matters: a theoretical and empirical review of consequences and mechanisms. Ann. Behav. Med. 40, 218–227 (2010).
Masoumi, M. et al. Sleep duration as the Main Indicator of Self-Rated Wellness and Health among Healthcare Workers Involved in the COVID-19 pandemic. Int. J. Environ. Res. Public. Health 19(1), 136 (2021).
Clayborne, Z. M. et al. Associations of sleep duration and sleep quality with indicators of mental health among youth and adults: findings from the 2015 Canadian Community Health Survey. Health Promot Chronic Dis. Prev. Can. 43, 243–259 (2023).
Diesfeldt, H. F. [Indicators of emotional well-being in psychogeriatric care]. Tijdschr Gerontol. Geriatr. 46, 137–151 (2015).
pubmed: 25475410
doi: 10.1007/s12439-014-0107-z
McArdle, J. J. & Hamagami, F. Latent difference score structural models for linear dynamic analyses with incomplete longitudinal data. In New methods for the analysis of change. Edited by Collins L, Sayer A: American Psychological Association; : 139–175 (2001).
McArdle, J. & Nesselroade, J. Using multivariate data to structure developmental change. In Life-span developmental psychology: Methodological contributions Edited by Cohen S, Reese H: Lawrence Erlbaum Associates, Inc.; : 223–267 (1994).
Muthén, L. K. & Muthén, B. O. Mplus: Statistical Analysis with Latent Variables: User’s Guide (Version 8) (Muthén & Muthén, 2024).
Brown, T. Confirmatory Factor Analysis for Applied Research (The Guilford Press, 2015).
Beauducel, A. & Herzberg, P. Y. On the performance of Maximum Likelihood Versus means and Variance Adjusted weighted least squares estimation in CFA. Struct. Equation Modeling: Multidisciplinary J. 13, 186–203 (2006).
doi: 10.1207/s15328007sem1302_2
Hu Lt, Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equation Modeling: Multidisciplinary J. 6, 1–55 (1999).
doi: 10.1080/10705519909540118
Meade, A. W., Johnson, E. C. & Braddy, P. W. Power and sensitivity of alternative fit indices in tests of measurement invariance. J. Appl. Psychol. 93, 568–592 (2008).
pubmed: 18457487
doi: 10.1037/0021-9010.93.3.568
Little, R. J. A. & Rubin, D. B. Statistical Analysis with Missing Data, 2nd Edition. New York: John Wiley & Sons; (2002).
Enders, C. K. A primer on maximum likelihood algorithms available for Use with Missing Data. Struct. Equation Modeling: Multidisciplinary J. 8, 128–141 (2001).
SAS-Institute. SAS 9.4 Help and Documentation. Cary, NC: SAS Institute Inc.; –2022. (2002).