Determining frailty index thresholds for older people across multiple countries in sub-Saharan Africa

Gideon Dzando; Paul R Ward; Lillian Mwanri; Richard K Moussa; Justice Moses K Aheto; Rachel C Ambagtsheer

doi:10.1038/s43856-025-00952-1

Determining frailty index thresholds for older people across multiple countries in sub-Saharan Africa

Commun Med (Lond). 2025 Jun 17;5(1):237. doi: 10.1038/s43856-025-00952-1.

Authors

Gideon Dzando¹, Paul R Ward², Lillian Mwanri², Richard K Moussa³, Justice Moses K Aheto^{4

5}, Rachel C Ambagtsheer²

Affiliations

¹ Research Centre for Public Health, Equity and Human Flourishing, Torrens University Australia, Wakefield Campus, Adelaide, Australia. Gideon.Dzando@torrens.edu.au.
² Research Centre for Public Health, Equity and Human Flourishing, Torrens University Australia, Wakefield Campus, Adelaide, Australia.
³ Ecole Nationale Supérieure de Statistique et d'Economie Appliquée (ENSEA), Abidjan, Côte d'Ivoire.
⁴ Department of Biostatistics, School of Public Health, University of Ghana, Accra, Ghana.
⁵ WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.

Abstract

Background: Despite the increasing attention on frailty as a global public health concern, frailty screening among older people in Sub-Saharan Africa (SSA) continues to rely on instruments and thresholds from high-income countries. These instruments and thresholds may not be useful in SSA due to contextual differences. We explored the development of a frailty threshold for older people in SSA.

Methods: We utilized pooled cross-sectional data from four SSA countries (Kenya, Ghana, Uganda and Côte d'Ivoire) to determine a frailty index threshold for 5527 older people (50 years and above) using a two-step approach. The mean ages of the participants ranged from 62.13 (SD: 9.60) to 74.00 (SD: 9.40) years. The participants were mostly females across the four countries, ranging from 50.1% in Côte d'Ivoire to 65.3% in Kenya. Country-specific frailty thresholds were developed using the Receiver Operating Characteristics (ROC) method. The primary thresholds were further combined into a single threshold using random effects meta-analysis. Subgroup analyses and meta-regression were conducted to explore potential sources of heterogeneity in the pooled frailty threshold.

Results: Here we show the Area Under the Curves from the ROC analyses ranging between 0.91 (CI: 0.89, 0.93) and 0.94 (CI: 0.92, 0.97), with sensitivities ranging from 0.83 to 0.94 and specificities from 0.72 to 0.87. An overall threshold of 0.29 (95% CI: 0.25, 0.33) was obtained after pooled analysis of the country-specific thresholds.

Conclusions: This work demonstrates that using context-specific data can yield valuable insights into frailty thresholds among older people in SSA, enabling more culturally relevant interventions. Effective frailty screening must account for population-level differences, including demographic, health, and socio-cultural factors.

Plain language summary

Frailty is a common problem which makes older people weak and unable to carry out daily activities. While this has been well researched in high-income countries, there is limited evidence about frailty among older people in Sub-Saharan Africa, where the older population is increasing quickly. Most studies conducted in sub-Saharan Africa rely on thresholds developed and validated in high-income countries, which may not capture the important things that contribute to frailty in Sub-Saharan Africa. We developed a frailty threshold by combining data from four African countries. Our results show that it is possible to develop thresholds that reflect the realities of older people in Sub-Saharan Africa, though attention to each population’s aging profile is still required for effective frailty screening.