Population aging is a global health challenge, with accelerated aging linked to cognitive decline and neurodegenerative disorders.1,2 Recent research published in Nature Aging (November 2025) provides compelling evidence that multilingualism—defined as the regular use of more than one language—acts as a protective factor against accelerated aging.3 Using biobehavioral age gaps (BAGs) as a direct marker of healthy versus unhealthy aging2, the study analyzed data from 86,149 participants across 27 European countries. Findings reveal that multilingual individuals exhibit delayed aging trajectories compared to monolinguals, with protective effects increasing alongside the number of languages spoken. These associations remained robust after adjusting for linguistic, physical, social, and sociopolitical confounders, underscoring the potential of multilingualism as a population-wide intervention for healthy aging.3
The demographic shift toward older populations worldwide has intensified the urgency to identify modifiable factors that promote healthy aging. Aging is associated with structural and functional brain changes, leading to cognitive decline and increased vulnerability to dementia.1 While lifestyle factors such as physical activity and education are well-established contributors to healthy aging, emerging evidence suggests that multilingualism may offer unique cognitive and functional benefits.4,5
Previous studies have linked bilingualism to delayed onset of dementia and enhanced cognitive reserve.4,6 However, these findings were often limited to clinical cohorts, small sample sizes, and indirect proxies of aging, resulting in mixed conclusions.4,5,7,8 The recent study by Amoruso et al. addresses these gaps by leveraging large-scale, multi-country data and introducing biobehavioral age gaps (BAGs) as a direct measure of aging trajectories.3
The analysis included 86,149 participants aged 51–90 years from the Survey of Health, Ageing and Retirement in Europe (SHARE).9 Individuals with dementia diagnoses were excluded to ensure generalizability to healthy populations. Data harmonization protocols ensured consistency across countries.2
BAGs were computed as the difference between predicted age—based on positive and adverse biobehavioral factors—and chronological age.10 Negative BAG values indicate delayed aging, while positive values reflect accelerated aging. Predictors included:3
A gradient-boosting regression model predicted chronological age using these factors, validated through nested cross-validation and leave-one-country-out strategies to ensure robustness.3,11
Multilingualism was assessed at the country level using Eurostat data, categorizing individuals as monolingual or speaking one, two, or three or more additional languages.3 Cross-sectional analyses estimated odds ratios (ORs) for accelerated aging, while longitudinal analyses calculated relative risks (RRs) over time.3
The model explained 24% of age variance (R2 = 0.24), with functional ability emerging as the strongest predictor. Positive factors correlated with delayed aging, while adverse factors were linked to accelerated aging.3
In cross-sectional analyses, monolinguals were 2.11 times more likely to experience accelerated aging (OR = 2.11, 95% CI: 1.98–2.24). Conversely, speaking at least one additional language reduced this risk by more than half (OR = 0.46, 95% CI: 0.43–0.49). Protective effects scaled with the number of languages (Figure 1):3
Figure 1: ORs from the cross-sectional analysis3
Longitudinal findings mirrored these results. Monolinguals had a 43% higher risk of accelerated aging over time (RR = 1.43), while multilinguals exhibited progressively lower risks:
Adjusting for linguistic, physical, social, and sociopolitical exposomes—including migration, gender equality, air quality, and institutional language policies—did not substantially alter the protective effect of multilingualism. Exceptions included diminished significance for speaking three additional languages after controlling for migration and for one additional language after adjusting for gender inequality.3
Protective effects persisted across age cohorts (51–64, 65–77, 78–90 years). However, benefits of speaking only one additional language weakened in older groups, while speaking two or more languages conferred stronger protection with advancing age.3
This study provides robust, population-level evidence that multilingualism delays aging trajectories, as reflected by lower BAGs and reduced risk of accelerated aging. The dose-dependent nature of the effect suggests cumulative cognitive benefits from managing multiple languages, consistent with theories of experience-dependent neuroplasticity.12 Continuous engagement in multilingual contexts likely strengthens executive and attentional networks, which are critical for cognitive resilience.13
Importantly, these findings remained significant after accounting for macro-level factors, reinforcing the domain-independent protective role of multilingualism. Nonetheless, certain conditions—such as migration-related stress or structural inequalities—may attenuate benefits, highlighting the interplay between individual and societal factors.
The strengths of this study include the large, diverse sample, multi-country design, and use of BAGs as direct aging markers. The limitations involve reliance on country-level multilingualism estimates rather than individual metrics, potential cohort effects, and geographic restriction to Europe. Future research should incorporate individual-level language profiles, explore causal mechanisms through experimental designs, and extend analyses to non-European populations.
Multilingualism emerges as a powerful, scalable protective factor against accelerated aging, comparable to other lifestyle interventions emphasized in public health guidelines. By promoting functional ability and cognitive reserve, multilingualism offers a promising avenue for global healthy aging strategies. Integrating language learning into educational and public health frameworks could enhance resilience against age-related decline, reduce health disparities, and improve quality of life across the lifespan.
References
1. Fang M, et al. Nat Med. 2025;31: 772–6. 2. Hernández H, et al. Nat Med. 2025; 31, 3089–100. 3. Amoruso L, et al. Nat Aging. 2025; 5: 2340–54. 4. Bialystok E. Trends Cogn Sci. 2021;25, 355–64. 5. Venugopal A, et al. Alzheimers Dement. 2024;20: 2620–31. 6. Alladi S, et al. Neurology. 2013;81:1938–44. 7. Mukadam N, et al. J Alzheimer’s Dis. 2017;58: 45–54. 8. Brini S, et al. Neuropsychol Rev. 2020; 30: 1–24. 9. Bergmann M, et al. Survey participation in the Survey of Health, Ageing and Retirement in Europe (SHARE), Wave 1–7. Based on Release 7.0.0. SHARE Working Paper Series 41–2019 (MEA, Max Planck Institute for Social Law and Social Policy. 2019). 10. Ibanez A, et al. Nat Aging. 2024;4:1153–65. 11. Jeong CU, et al. JMIR Aging. 2025;8:e64473. 12. Pliatsikas C. Biling Lang Cogn. 2020;23: 459–71. 13. Rothman J. Biling Lang Cogn. 2024;28: 793–801.
