Gideon Dzando, Paul R Ward, Lillian Mwanri, Richard K Moussa, Justice Moses K Aheto, Rachel C Ambagtsheer
{"title":"Determining frailty index thresholds for older people across multiple countries in sub-Saharan Africa.","authors":"Gideon Dzando, Paul R Ward, Lillian Mwanri, Richard K Moussa, Justice Moses K Aheto, Rachel C Ambagtsheer","doi":"10.1038/s43856-025-00952-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"237"},"PeriodicalIF":5.4000,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12174359/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43856-025-00952-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
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.