Examining Frailty Phenotype Dimensions in the Oldest Old

Sara Alves; Laetitia Teixeira; Oscar Ribeiro; Constança Paúl

doi:10.3389/fpsyg.2020.00434

Examining Frailty Phenotype Dimensions in the Oldest Old

Front Psychol. 2020 Mar 26:11:434. doi: 10.3389/fpsyg.2020.00434. eCollection 2020.

Authors

Sara Alves^{1

2}, Laetitia Teixeira^{1

2}, Oscar Ribeiro^{3

4}, Constança Paúl^{1

2}

Affiliations

¹ Abel Salazar Institute of Biomedical Sciences-University of Porto (ICBAS.UP), Porto, Portugal.
² Center for Health Technology and Services Research (CINTESIS.ICBAS), Porto, Portugal.
³ Center for Health Technology and Services Research (CINTESIS.UA), University of Aveiro, Aveiro, Portugal.
⁴ Department of Education and Psychology, University of Aveiro, Aveiro, Portugal.

Abstract

Introduction: Frailty has been studied among the old population due to its association with negative outcomes. Presently there is no gold standard for measuring frailty, but several studies have used the frailty phenotype of Fried consisting of five components (weakness, slowness, unintentional weight loss, exhaustion, and low physical activity) that classify individuals as robust, pre-frail, or frail, depending on the number of components affected, respectively, zero, one or two, and three or more. This study aims to explore the specific contribution of each of these components to the frailty phenotype in a sample of oldest old community-dwelling individuals.

Materials and methods: Individuals aged 80+ years old living in the community (N = 142) participated in this study. Sociodemographic data (age, sex, educational level, and marital status) and Fried's frailty phenotype were collected. Descriptive analysis summarized sociodemographic information and the frailty components. Multiple correspondence analysis (MCA) was performed to detect and explore relationships between frailty's five components.

Results: Participants had a mean age of 88.07 years (SD = 5.30 years) and were mainly women (73.9%). The majority of the sample were considered frail (71.8%) and pre-frail (24.7%), and the most recurrent component for both groups was slowness. From the MCA analysis, a two-dimension solution was considered the most adequate, with 53.47% of variance explained. Dimension 1 (32.21% of variance explained) showed weakness as the most discriminant component; dimension 2 (21.26% of variance explained) showed unintentional weight loss as the most discriminant component.

Discussion: Results revealed a high number of pre-frail and frail participants. MCA proved to add an important understanding in examining the frailty phenotype; it revealed weakness as the most discriminant component for dimension 1, suggesting a high association with the frailty phenotype. MCA also identified two main features of frailty: one related with physical features (motor behavioral and grip strength) including weakness, low physical activity, and slowness; and the second related with intrinsic conditions (unintentional weight loss and exhaustion).

Conclusion: This study corroborates the need of a differentiated approach to the frailty phenotype among very old individuals, bringing for consideration the specific influence of its components.

Keywords: Fried phenotype of frailty; frailty dimensions; oldest old; phenotype components; physical frailty.