Intrinsic Capacity and Its Biological Basis: A Scoping Review.

BACKGROUND

In 2015, the World Health Organization (WHO) introduced the concept of intrinsic capacity (IC) to define healthy aging based on functional capacity. In this scoping review, we summarized available evidence on the development and validation of IC index scores, the association of IC with health-related factors, and its biological basis. The review specifically focused on identifying current research gaps, proposed strategies to leverage biobank datasets, and opportunities to study the genetic mechanisms and gene-environment interactions underlying IC.

METHODS

The literature search was conducted across six databases, including PubMed, CINAHL, Web of Science, Scopus, AgeLine, and PsycINFO, using keywords related to IC.

RESULTS

This review included 84 articles, and most of them (n=38) adopted the 5-domains approach to operationalize IC, utilizing correlated five factors or bifactor structures. Intrinsic capacity has consistently shown significant associations with socio-demographic and health-related outcomes, including age, sex, wealth index, nutrition, exercise, smoking, alcohol use, ADL, IADL, frailty, multimorbidity, and mortality. While studies on the biological basis of the composite IC are limited, with only one study finding a significant association with the ApoE gene variants, studies on specific IC domains - locomotor, vitality, cognitive, psychological, and sensory suggest a heritability of 20-85% of IC and several genetic variants associated with these subdomains have been identified. However, evidence on how genetic and environmental factors influence IC is still lacking, with no available study to date.

CONCLUSION

Our review found that there was inconsistency in the use of standardized IC measurement tools and indicators, but the IC indices had shown good construct and predictive validity. Research into the genetic and gene-to-environment interactions underlying IC is still lacking, which calls for the use of resources from large biobank datasets in the future.