# Defining frailty using a modified Fried’s Frailty Phenotype in a Southern African context

## TL;DR

This study adapts the Fried’s Frailty Phenotype to better identify frailty in a Southern African population by adjusting criteria for local conditions.

## Contribution

The study proposes region-specific modifications to the Fried’s Frailty Phenotype for improved frailty diagnosis in Southern Africa.

## Key findings

- Using the lowest quintile of BMI missed 15.2% of overweight and obese participants who reported weight loss.
- Grip strength correlated better with age than BMI, leading to the use of sex-specific thresholds for grip strength.
- The modified SDOC threshold identified slow walking speed in 85.8% of participants, indicating non-differentiality.

## Abstract

Frailty leads to disability, morbidity, and mortality in older persons. The Fried’s Frailty Phenotype (FFP), derived in the American Cardiovascular Health Study (CHS), is widely used around the world to define frailty, but lacks adaptation in African populations.

To derive a modified FFP definition which best identifies frailty in a Southern African context.

A population-based cross-sectional study of adults aged ≥40 years collected data from questionnaires and physical assessments. Original CHS, population-dependent, European Working Group on Sarcopenia in Older People2 (EWGSOP2) and Sarcopenia Definitions and Outcomes Consortium (SDOC) and independent thresholds were all applied to the five FFP criteria (weight loss, exhaustion, low physical activity [PA], low grip strength [GS] and slow walking speed [WS]) to assess non-differentiality, internal consistency, and plausibility.

The 919 participants had a median age of 59 years [IQR 50–70], 53.3% were female. Self-reported exhaustion was reported by 37.5%nd self-reported weight loss by 34.9%. Using the lowest quintile of body mass index (BMI), missed 15.2% of overweight and obese participants who reported weight loss. Using CHS thresholds, low PA was present in 36.7%. Grip strength correlated better with age (r = −0.45) than BMI (r = −0.19). Therefore, the sex-specific tenth percentile of the 40–49-years-age band of the study population was used rather than the CHS approach. The modified SDOC threshold identified slow WS in almost all (85.8%) and was therefore non-differential. The EWGSOP2 and CHS thresholds identified slow WS in 52.9% and 22.9%, respectively, compared to 34.5% using the study population’s lowest quintile.

Culture and language sensitive questions for self-reported exhaustion and weight loss, CHS thresholds for low PA, and population dependent thresholds for GS and WS were the most suitable modifications in a Southern African setting, highlighting the need for region-specific adaptations when diagnosing frailty.