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Multilingualism protects against accelerated aging in cross-sectional and longitudinal analyses of 27 European countries

Nature Aging volume 5, pages 2340–2354 (2025)Cite this article

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Abstract

Aging trajectories are influenced by modifiable risk factors, and prior evidence has hinted that multilingualism may have protective potential. However, reliance on suboptimal health markers, small samples, inadequate confounder control and a focus on clinical cohorts led to mixed findings and limited applicability to healthy populations. Here, we developed biobehavioral age gaps, quantifying delayed or accelerated aging in 86,149 participants across 27 European countries. National surveys provided individual-level positive (functional ability, education, cognition) and adverse (cardiometabolic conditions, female sex, sensory impairments) factors, while country-level multilingualism served as an aggregate exposure. Biobehavioral factors predicted age (R2 = 0.24, r = 0.49, root mean squared error = 8.61), with positive factors linked to delayed aging and adverse factors to accelerated aging. Multilingualism emerged as a protective factor in cross-sectional (odds ratio = 0.46) and longitudinal (relative risk = 0.70) analyses, whereas monolingualism increased risk of accelerated aging (odds ratio = 2.11; relative risk = 1.43). Effects persisted after adjusting for linguistic, physical, social and sociopolitical exposomes. These results underscore the protective role of multilingualism and its broad applicability for global health initiatives.

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Fig. 1: Study design and analytical workflow.
Fig. 2: BAG results and epidemiological associations.
Fig. 3: Validation of the biobehavioral age prediction model and derived BAGs.
Fig. 4: Epidemiological outcomes after covariate adjustments.

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Data availability

All databases used in this study are publicly accessible. Indicators of GDP, air quality, socioeconomic inequality (Gini index) and migration were obtained from the World Bank’s platform (https://databank.worldbank.org/). Country-level gender inequality indexes (GII) are available on the WHO’s website (https://www.who.int/data/nutrition/nlis/info/gender-inequality-index-(gii)/. Sociopolitical exposome indicators are available through the Global State of Democracy Indices (https://www.idea.int/democracytracker/dataset-resources/). Country-level percentages of foreign-speaking languages are sourced from the Eurostat database covering 2007, 2011, 2016 and 2022 waves (https://ec.europa.eu/eurostat/statistics-explained/index.php?/title=Foreign_language_skills_statistics/). Linguistic exposome indicators for the number of stable and institutional languages per European country are available from Ethnologue (https://www.ethnologue.com/). The two most spoken languages per country are sourced from the ‘Europeans and their languages’ Eurobarometer survey by the European Commission (https://languageknowledge.eu/countries-list/). The typological distance between languages was estimated using the Perplexity metric available at https://github.com/gamallo/Perplexity/.

Code availability

Analysis code (https://github.com/euroladbrainlat/Biobehavioral-age-gaps-Multilingualism/tree/main/scripts/) and preprocessed data containing individual BAG estimates (https://github.com/euroladbrainlat/Biobehavioral-age-gaps-Multilingualism/tree/main/scripts/main/data/) are freely available on GitHub.

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Acknowledgements

L.A. is supported by the Spanish Ministry of Science and Innovation under the program Ramón y Cajal (RYC2022-035514-I). H.H. is supported by Davos Alzheimer’s Collaborative. A.I. is supported by grants from the multi-partner consortium to expand dementia research in Latin America (ReDLat, supported by Fogarty International Center (FIC), National Institutes of Health (NIH), National Institutes of Aging (R01 AG057234, R01 AG075775, R01 AG21051, R01 AG083799, CARDS-NIH), Alzheimer’s Association (SG-20-725707), Rainwater Charitable Foundation – The Bluefield project to cure FTD, and Global Brain Health Institute)); ANID/FONDECYT Regular (1210195 and 1210176 and 1220995); ANID/PIA/ANILLOS ACT210096; FONDEF ID20I10152 and ANID/FONDAP 15150012. A.M.G. is supported by the NIH, National Institutes of Aging (R01 AG075775, R01 AG083799, 2P01AG019724); ANID/FONDECYT Regular (1250317 and 1250091); DICYT-USACH (032351MA); and Agencia Nacional de Promoción Científica y Tecnológica (01-PICTE-2022-05-00103). C.D.-A. is supported by ANID/FONDECYT Regular 1210622, ANID/PIA/ANILLOS ACT210096, Alzheimer’s Association (AARGD-24- 1310017), ANID/FOVI240065 and ANID/Proyecto Exploración 13240170. H.S.-G. is supported by NIH R01 (‘Social epigenetics of Alzheimer’s disease and related dementias in Latin American countries’, no. 1R01AG082056-01A1), Global Brain Health Institute and Alzheimer Association (‘Brain health in individuals with exposition to high violence in Colombia’, no. GBHI ALZ UK-23-971135”). S.B. is supported by the Global Brain Health Institute, Alzheimer’s Association, Alzheimer’s Society UK and Pilot Awards for Global Brain Health Leaders (grant no. GBHI ALZ UK- 25-1289623). Additionally, research reported in this publication was supported by the Fogarty International Center of the NIH under award number D43TW012455. J.M. and C.C.-O. are supported by postdoctoral fellowships granted by the multi-partner consortium to expand dementia research in Latin America (ReDLat), and the Atlantic Fellows for Equity in Brain Health program. The contents of this publication are solely the responsibility of the authors and do not represent the official views of these institutions. This paper uses data from SHARE Waves 1, 2, 3, 4, 5, 6, 7, 8 and 9 (DOIs: https://doi.org/10.6103/SHARE.w1.900; https://doi.org/10.6103/SHARE.w2.900; https://doi.org/10.6103/SHARE.w3.900; https://doi.org/10.6103/SHARE.w4.900; https://doi.org/10.6103/SHARE.w5.900; https://doi.org/10.6103/SHARE.w6.900; https://doi.org/10.6103/SHARE.w6.DBS.100; https://doi.org/10.6103/SHARE.w7.900; https://doi.org/10.6103/SHARE.w8.900; https://doi.org/10.6103/SHARE.w8ca.900; https://doi.org/10.6103/SHARE.w9.900; https://doi.org/10.6103/SHARE.w9ca.900; https://doi.org/10.6103/SHARE.HCAP1.100). The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211909, SHARE-LEAP: GA N°227822, SHARE M4: GA N°261982, DASISH: GA N°283646) and Horizon 2020 (SHARE-DEV3: GA N°676536, SHARE-COHESION: GA N°870628, SERISS: GA N°654221, SSHOC: GA N°823782, SHARE-COVID19: GA N°101015924) and by DG Employment, Social Affairs and Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, VS 2020/0313, SHARE-EUCOV: GA N°101052589 and EUCOVII: GA N°101102412. Additional funding from the German Federal Ministry of Education and Research (01UW1301, 01UW1801, 01UW2202), the Max Planck Society for the Advancement of Science, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, BSR12-04, R01_AG052527-02, R01_AG056329-02, R01_AG063944, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see www.share-eric.eu).

Author information

Author notes

  1. These authors contributed equally: Lucia Amoruso, Hernan Hernandez.

Authors and Affiliations

  1. Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain

    Lucia Amoruso

  2. Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina

    Lucia Amoruso, Sebastian Moguilner, Agustina Legaz, Manuel Carreiras, Marcelo Adrián Maito & Adolfo M. García

  3. Ikerbasque, Basque Foundation for Science, Bilbao, Spain

    Lucia Amoruso & Manuel Carreiras

  4. Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago de Chile, Chile

    Hernan Hernandez, Sebastian Moguilner, Agustina Legaz, Jhosmary Cuadros, Raul Gonzalez-Gomez, Joaquín Migeot, Carlos Coronel-Oliveros, Josephine Cruzat, Vicente Medel, Marcelo Adrián Maito, Claudia Duran-Aniotz, Enzo Tagliazucchi & Agustin Ibanez

  5. Pontificia Universidad Javeriana (PhD Program in Neuroscience) Bogotá, San Ignacio, Colombia

    Hernando Santamaria-Garcia & Agustin Ibanez

  6. Center of Memory and Cognition Intellectus, Hospital Universitario San Ignacio Bogotá, San Ignacio, Colombia

    Hernando Santamaria-Garcia

  7. Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Sebastian Moguilner

  8. Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago de Chile, Chile

    Pavel Prado

  9. Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal, Venezuela

    Jhosmary Cuadros

  10. Advanced Center for Electrical and Electronic Engineering, Universidad Técnica Federico Santa María, Valparaíso, Chile

    Jhosmary Cuadros

  11. Facultad de Ingeniería, Universidad de Concepción, Concepción, Chile

    Liset Gonzalez & Enzo Tagliazucchi

  12. Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, USA

    Joaquín Migeot, Carlos Coronel-Oliveros, Sandra Baez, Adolfo M. García & Agustin Ibanez

  13. Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland

    Joaquín Migeot, Carlos Coronel-Oliveros, Sandra Baez, Adolfo M. García & Agustin Ibanez

  14. Trinity College Dublin, The University of Dublin, Dublin, Ireland

    Carlos Coronel-Oliveros & Agustin Ibanez

  15. University of the Basque Country, UPV/EHU, Bilbao, Spain

    Manuel Carreiras

  16. Universidad de los Andes, Bogotá, Colombia

    Sandra Baez

  17. Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile

    Adolfo M. García

  18. Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey

    Agustin Ibanez

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  1. Lucia Amoruso
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  2. Hernan Hernandez
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  3. Hernando Santamaria-Garcia
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  20. Agustin Ibanez
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Contributions

Research design: A.I., H.H. and L.A.; Data collection, curation and analysis: H.H. and L.A.; BAG methods: H.H., H.S.M., S.B. and A.I.; multilingualism methods: L.A. and A.M.G.; writing—original draft: L.A., H.H., A.M.G. and A.I.; writing—reviewing and editing: all authors; project administration and funding: A.I.; accessed and verified data: H.H., L.A., S.B. and H.S.M.

Corresponding author

Correspondence to Agustin Ibanez.

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All authors declare no competing interests.

Peer review

Peer review information

Nature Aging thanks Jason Rothman, who co-reviewed with Federico Gallo; and Junhao Wen for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Stratified analysis by age group.

Associations between number of spoken languages and BAGs across age cohorts (n = 86,149 participants). A) Odds ratio (OR) estimates from the cross-sectional analysis and B) relative risk (RR) estimates from the longitudinal analysis, both stratified by age. Across designs, results show that risk of accelerated aging increases with age among monolinguals. For individuals speaking one additional language, the protective effect weakens with age. In contrast, speaking two or more additional languages is linked to progressively stronger protection with advancing age.

Supplementary information

Supplementary Information

Supplementary Note 1, Tables 1–6 and References

Reporting Summary

Source data

Source Data Fig. 1

Single Excel file containing statistical source data for all figures. No source data are provided for Fig. 1, as it is a descriptive schematic of the pipeline.

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Amoruso, L., Hernandez, H., Santamaria-Garcia, H. et al. Multilingualism protects against accelerated aging in cross-sectional and longitudinal analyses of 27 European countries. Nat Aging 5, 2340–2354 (2025). https://doi.org/10.1038/s43587-025-01000-2

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