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Clinical biomarker-based biological age predicts deaths in Brazilian adults: the ELSA-Brasil study

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Abstract

Biological age is a construct that seeks to evaluate the biological wear and tear process of the organism that cannot be observed by chronological age. We estimate individuals’ biological age based on biomarkers from multiple systems and validate it through its association with mortality from natural causes. Biological age was estimated in 12,109 participants (6621 women and 5488 men) from the first visit of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) who had valid data for the biomarkers used in the analyses. Biological age was estimated using the Klemera and Doubal method. The difference between chronological age and biological age (Δage) was computed. Cox proportional hazard models stratified by sex were used to assess whether Δage was associated with mortality risk after a median follow-up of 9.1 years. The accuracy of the models was estimated by the area under the curve (AUC). Δage had equal mean for men and women, with greater variability for men. Cox models showed that every 1-year increase in Δage was associated with increased mortality in men (HR (95% CI) 1.21; 1.17–1.25) and women (HR (95% CI) 1.24; 1.15–1.34), independently of chronological age. Results of the AUC demonstrated that the predictive power of models that only included chronological age (AUC chronological age = 0.7396) or Δage (AUC Δage = 0.6842) was lower than those that included both, chronological age and Δage (AUC chronological age + Δage = 0.802), in men. This difference was not observed in women. We demonstrate that biological age is strongly related to mortality in both genders and is a valid predictor of death in Brazilian adults, especially among men.

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Data Availability

Data are available on reasonable request. The data used in this study are available for research proposal on request to the ELSA’s Datacenter and to the ELSA’s Publications Committee (publiELSA). Additional information can be obtained from the ELSA’s Datacenter (estatisticaelsa@ufrgs.br) and from the ELSA Coordinator from the Research Center of Minas Gerais (sbarreto@medicina.ufmg.br).

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Acknowledgements

We thank all ELSA-Brasil participants for their invaluable contribution to this study.

Funding

This work was supported by the Brazilian Ministry of Health (Department of Science and Technology) and the Brazilian Ministry of Science, Technology and Innovation (FINEP, Financiadora de Estudos e Projetos and CNPq, National Research Council), Grant No 01 06 0010.00, 01 06 0212.00, 01 06 0300.00, 01 06 0278.00, 01 06 0115.00 and 01 06 0071.00. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES) Finance Code 001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. Postgraduate Program in Public Health, School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Amanda Viana Machado

  2. Department of Epidemiology and Center for Social Epidemiology and Population Health, University of Michigan, Ann Arbor, USA

    Amanda Viana Machado & Belinda L. Needham

  3. Center of Data Integration and Knowledge for Healthcare, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil

    Juliana Freitas de Mello e Silva

  4. Department of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Enrico Antônio Colosimo

  5. Department of Clinic Pathology, School of Medicine, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Chams Bicalho Maluf

  6. School of Medicine & Clinical Hospital, Universidade Federal de Minas Gerais, Avenida Professor, Alfredo Balena, 190, Belo Horizonte, Minas Gerais, CEP, 30130-100, Brazil

    Luana Giatti, Lidyane V. Camelo & Sandhi Maria Barreto

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  1. Amanda Viana Machado
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Correspondence to Sandhi Maria Barreto.

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ELSA-Brasil research protocol was approved by the Research Ethics Committee of Universidade de São Paulo (USP), Research Ethics Committee of Universidade Federal de Minas Gerais (UFMG), Research Ethics Committee of Fundação Oswaldo Cruz (FIOCRUZ), Research Ethics Committee of Universidade Federal do Espírito Santo (UFES), Research Ethics Committee of Universidade Federal da Bahia (UFBA), Research Ethics Committee of Universidade Federal do Rio Grande do Sul (UFRGS), and also by the National Research Ethics Committee (CONEP).

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Machado, A.V., Silva, J.F., Colosimo, E.A. et al. Clinical biomarker-based biological age predicts deaths in Brazilian adults: the ELSA-Brasil study. GeroScience (2024). https://doi.org/10.1007/s11357-024-01186-0

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