- Data, Statistics and AI for Well-Being of People and Organisations
- A cura di Luigi Fabbris, Alberto Franci, Pietro Renzi
Depression, biomarkers and the Covid-19 outbreak
- Omar Paccagnella
- © 2026 Author(s) |
- CC BY 4.0
- DOI: 10.36253/979-12-215-1062-1.53
The COVID-19 disease and individual depression share a common pathophysiological framework: the disease causes an increase of proinflammatory cytokines, that can be responsible for inducing the development of depressive disorders. This work aims to investigate the relationship between depression among European elderly after the Covid-19 pandemic and an objective measure of the health, such as the C-reactive protein (CRP), collected in some SHARE countries through blood biomarkers in 2015. The final sample is composed of 3,223 men and 4,788 women with a valid CRP measure. Exploiting the answers to the EURO-D depression scale in the eighth and ninth wave of SHARE (collected before and after the COVID-19 pandemic, respectively), two different types of variables identifying a depression worsening and one variable defining the stability of the depression status were constructed. A large set of individual covariates and events related to the COVID-19 pandemic experience (i.e., contagion, hospitalisations or deaths due to the virus, or vaccination behaviours) is introduced. Logistic models with robust standard errors are estimated and Average Marginal Effects are calculated, separately by gender. Investigating both definitions of depression deterioration, CRP does not play any role in explaining changes in depression, both for men and women. Modelling stability of depression, the estimated models show better fits and a large number of statistically significant variables; CRP measures are statistically significant among men, but not among women. Inflammatory markers are not easy to collect, but they are nowadays recognised as an important underlying condition in many common diseases and can provide powerful objective measures of individual health conditions. Their application could overcome the use of several health indicators, such as self-reported measures, which are easier to collect, but risk suffering from serious measurement errors, as any subjective assessment is typically characterised.
- Keywords:
- Ageing,
- Biomarkers,
- Covid-19,
- Gender differences,
- Mental health,
University of Padua, Italy - ORCID: 0000-0002-6961-3839
- Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S., Zuber, S. (2013). Data resource profile: The Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology, 42(4), pp. 992–1001. DOI: 10.1093/ije/dyt088
- Börsch-Supan, M., Andersen-Ranberg, K., Borbye-Lorenzen, N., Cofferen, J., Groh, R., Horton, H.M., Kerschner, E., Minh Kha, T., Potter, A.J., Schmidutz, D., Skogstrand, K., Sun, A., Weiss, L., Wener, M.H., Börsch-Supan, A. (2024). Biomarkers in SHARE: Documentation of Implementation, Collection, and Analysis of Dried Blood Spot (DBS) Samples 2015 – 2023. SHARE-ERIC. DOI: 10.3386/w32764
- da Silva Lopes, L., Silva, R.O., de Sousa Lima, G., de Araùjo Costa, A.C., Barros, D.F., Silva-Néto, R.P. (2021). Is there a common pathophysiological mechanism between COVID-19 and depression? Acta Neurologica Belgica, 121(5), pp. 1117–1122. DOI: 10.1007/s13760-021-01748-5
- Dewey, M., Prince, M. (2005). Mental health. In A. Börsch-Supan, A. Brugiavini, H. Jürges, J. Mackenbach, J. Siegrist, G. Weber (eds.). Health, Ageing and Retirement in Europe. First Results from the Survey of Health, Ageing and Retirement in Europe. Mannheim: Mannheim Research Institute for the Economics of Aging (MEA), pp. 108-117.
- Elbakary, N., Al-Khuzaei, N., Hussain, T., Karawia, A., Smida, M., Abu-Rahma, N., Akel, F., Mahmoud, S.E., Currie, J., Khoodoruth, M.A.S., Ouanes, S. (2025). Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study. Journal of Affective Disorders, 387, 119545. DOI: 10.1016/j.jad.2025.119545
- Eklund, C.M. (2009). Proinflammatory cytokines in CRP baseline regulation. Advances in Clinical Chemistry, 48, pp. 111-136. DOI: 10.1016/s0065-2423(09)48005-3
- Grolli, R.E., Mingoti, M.E.D., Bertollo, A.G., Luzardo, A.R., Quevedo, J., Réus, G.Z., Ignácio, Z.M. (2021). Impact of COVID-19 in the mental health in elderly: Psychological and biological updates. Molecular Neurobiology, 58(5), pp. 1905–1916. DOI: 10.1007/s12035-020-02249-x
- Markiewicz-Gospodarek, A., Górska, A., Markiewicz, R., Chilimoniuk, Z., Czeczelewski, M., Baj, J., Maciejewski, R., Masiak, J. (2022). The relationship between mental disorders and the COVID-19 pandemic-course, risk factors, and potential consequences. International Journal of Environmental Research and Public Health, 19(15), 9573. DOI: 10.3390/ijerph19159573
- Mood, C. (2010). Logistic regression: Why we cannot do what we think we can do, and what we can do about it. European Sociological Review, 26(1), pp. 67–82. DOI: 10.1093/esr/jcp006
- Nolen-Hoeksema, S. (1990). Sex Differences in Depression. , Stanford, CA: Stanford University Press. DOI: 10.1515/9781503621640
- Prince, M., Reischies, F., Beekman, A., Fuhrer, R., Jonker, S., Kivelä C., Lawlor B., Lobo A., Magnusson H., Fichter I., van Oyen H., Roelands M., Skoog I., Turrina C., Copeland J. (1999). Development of the EURO-D scale - a European Union initiative to compare symptoms of depression in 14 European centres. British Journal of Psychiatry, 174(4), pp. 330–338. DOI: 10.1192/bjp.174.4.330
- SHARE-ERIC (2024a). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 6. SHARE Dried Blood Spots. Release version: 1.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w6.DBS.100. DOI: 10.6103/SHARE.w6.DBS.100
- SHARE-ERIC (2024b). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. Release version: 9.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w8.900. DOI: 10.6103/SHARE.w8.900
- SHARE-ERIC (2024c). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 8. COVID-19 Survey 1. Release version: 9.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w8ca.900. DOI: 10.6103/SHARE.w8ca.900
- SHARE-ERIC (2024d). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 9. Release version: 9.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w9.900. DOI: 10.6103/SHARE.w9.900
- SHARE-ERIC (2024e). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 9. COVID-19 Survey 2. Release version: 9.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w9ca.900. DOI: 10.6103/SHARE.w9ca.900
Informazioni sul capitolo
Titolo del capitolo
Depression, biomarkers and the Covid-19 outbreak
Autori
Omar Paccagnella
Lingua
Inglese
DOI
10.36253/979-12-215-1062-1.53
Opera sottoposta a peer review
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Informazioni bibliografiche
Titolo del libro
Data, Statistics and AI for Well-Being of People and Organisations
Curatori
Luigi Fabbris, Alberto Franci, Pietro Renzi
Opera sottoposta a peer review
Numero di pagine
420
Anno di pubblicazione
2026
Copyright
© 2026 Author(s)
Licenza d'uso
Licenza dei metadati
Editore
Firenze University Press
DOI
10.36253/979-12-215-1062-1
ISBN Print
979-12-215-1061-4
eISBN (pdf)
979-12-215-1062-1
eISBN (xml)
979-12-215-1063-8
Collana
Applied Statistics Series