Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Apr 22;24(1):355.
doi: 10.1186/s12877-024-04948-9.

Assessing the relationship between multimorbidity, NCD configurations, frailty phenotypes, and mortality risk in older adults

Rafael Ogaz-González  1   2 , Eva Corpeleijn  2 , Rosa Estela García-Chanes  3 , Luis Miguel Gutierréz-Robledo  3 , Ricardo Antonio Escamilla-Santiago  1 , Malaquías López-Cervantes  4
Affiliations

Assessing the relationship between multimorbidity, NCD configurations, frailty phenotypes, and mortality risk in older adults

Rafael Ogaz-González et al. BMC Geriatr. .

Abstract

Background: Older adults are increasingly susceptible to prolonged illness, multiple chronic diseases, and disabilities, which can lead to the coexistence of multimorbidity and frailty. Multimorbidity may result in various noncommunicable disease (NCD) patterns or configurations that could be associated with frailty and death. Mortality risk may vary depending on the presence of specific chronic diseases configurations or frailty.

Methods: The aim was to examine the impact of NCD configurations on mortality risk among older adults with distinct frailty phenotypes. The population was analyzed from the Costa Rican Longevity and Healthy Aging Study Cohort (CRELES). A total of 2,662 adults aged 60 or older were included and followed for 5 years. Exploratory factor analysis and various clustering techniques were utilized to identify NCD configurations. The frequency of NCD accumulation was also assessed for a multimorbidity definition. Frailty phenotypes were set according to Fried et al. criteria. Kaplan‒Meier survival analyses, mortality rates, and Cox proportional hazards models were estimated.

Results: Four different types of patterns were identified: 'Neuro-psychiatric', 'Metabolic', 'Cardiovascular', and 'Mixt' configurations. These configurations showed a higher mortality risk than the mere accumulation of NCDs [Cardiovascular HR:1.65 (1.07-2.57); 'Mixt' HR:1.49 (1.00-2.22); ≥3 NCDs HR:1.31 (1.09-1.58)]. Frailty exhibited a high and constant mortality risk, irrespective of the presence of any NCD configuration or multimorbidity definition. However, HRs decreased and lost statistical significance when phenotypes were considered in the Cox models [frailty + 'Cardiovascular' HR:1.56 (1.00-2.42); frailty + 'Mixt':1.42 (0.95-2.11); and frailty + ≥ 3 NCDs HR:1.23 (1.02-1.49)].

Conclusions: Frailty accompanying multimorbidity emerges as a more crucial indicator of mortality risk than multimorbidity alone. Therefore, studying NCD configurations is worthwhile as they may offer improved risk profiles for mortality as alternatives to straightforward counts.

Keywords: Clusters; Frailty; Mortality; Multimorbidity; Older adults; Patterns.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Cohort follow-up procession: exclusion, inclusion, and follow-up of subjects with phenotype criteria throughout the time in the CRELES Cohort
Fig. 2
Fig. 2
Prevalence of Non-communicable diseases over the basal period (n = 2,662)
Fig. 3
Fig. 3
NCD’s accumulation by frailty phenotype (N = 2,603)
See this image and copyright information in PMC

References

    1. Hogan DB. Models, definitions, and criteria for frailty. In: Ram JL, Conn PM, editors. Conn’s handbook of models for human aging. Academic; 2018. pp. 35–44.
    1. Brivio P, Paladini MS, Racagni G, Riva MA, Calabrese F, Molteni R. From healthy aging to Frailty: in search of the underlying mechanisms. Curr Med Chem. 2019;26(20):3685–701. doi: 10.2174/0929867326666190717152739. - DOI - PubMed
    1. Xia S, Zhang X, Zheng S, Khanabdali R, Kalionis B, Wu J et al. An update on inflamm-aging: mechanisms, prevention, and treatment. J Immunol Res. 2016;2016. - PMC - PubMed
    1. Dodig S, Čepelak I, Pavić I. Hallmarks of senescence and aging. Biochem Med (Zagreb). 2019;29(3). - PMC - PubMed
    1. Kennedy BK, Berger SL, Brunet A, Campisi J, Cuervo AM, Epel ES, et al. Geroscience: linking aging to Chronic Disease. Cell. 2014;159(4):709–13. doi: 10.1016/j.cell.2014.10.039. - DOI - PMC - PubMed

Publication types

LinkOut - more resources