Leila Freidoony, Dina Goodman-Palmer, Fred Barker, Mamdou Bountogo, Pascal Geldsetzer, Guy Harling, Lisa R HIrschhorn, Jennifer Manne-Goehler, Mark J Siedner, Stefan T Trautmann, Yilong Xu, Miles Witham, Justine Davies
{"title":"The association between the value of a statistical life and frailty in Burkina Faso","authors":"Leila Freidoony, Dina Goodman-Palmer, Fred Barker, Mamdou Bountogo, Pascal Geldsetzer, Guy Harling, Lisa R HIrschhorn, Jennifer Manne-Goehler, Mark J Siedner, Stefan T Trautmann, Yilong Xu, Miles Witham, Justine Davies","doi":"10.1101/2024.02.10.24302634","DOIUrl":null,"url":null,"abstract":"Background: To ensure resources invested into services are commensurate with benefit, economists utilise various methods to assess value of life. Understanding the performance of these methods in older populations is crucial, particularly in low-and-middle-income countries (LMICs), where the majority of older people will live by 2030. Value of Statistical Life Years (VSLY) is widely used in cost-benefit analyses but rarely been in LMICs or in older people. Objective: This study aimed to investigate the hypothesis that frailty would be associated with a lower VSLY in participants in rural Burkina Faso, when controlling for factors found in other studies likely to affect VSLY, such as socio-demographics, multimorbidity, quality of life, and disability.\nMethods: The study included 3,988 adults aged 40 years and older from a population-representative household survey done in Nouna, Burkina Faso. Data were collected on sociodemographic characteristics, chronic medical conditions, quality of life, disability, physical performance, and VSLY. Frailty status was derived using Fried's frailty phenotype. Bivariate analyses investigated the association between quintiles of VSLY and frailty. To explore modification of associations by other variables, we built sequential binary logistic regression models comparing each quintile of VSLY with the first (lowest) quintile. Models included frailty category, age, sex, marital status, educational attainment, and wealth. We sequentially added quality of life, multimorbidity, and disability.\nResults: Of 2,761 survey participants included in this analysis, 51.4% were female. Average age was 54.5 years (with 70.0% aged 40-59 years), 24.8% of respondents reported being alone, and 84.5% had not completed education. In bivariate analyses, we found a significant negative association between higher VSLY and frailty, increasing age, disability, and quality of life. Conversely, being male, married, and educated were positively associated with higher VSLY. The negative association between VSLY and frailty remained significant after adjusting for age, gender, education, wealth, quality of life, disability, and multimorbidity (odds of being frail for VSLY quintile 5 vs quintile 1 was 0.48, 95% CI 0.37-0.64 for the fully adjusted model). Furthermore, effect of age, education, and wealth on VSLY became non-significant once frailty was included in the model.\nConclusion: There is a strong relationship between the value that older people place on their lives and their frailty status. Frailty status is important to consider when assessing VSLY, especially in LMICs in which there is a rapidly growing older population.","PeriodicalId":501072,"journal":{"name":"medRxiv - Health Economics","volume":"78 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.02.10.24302634","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: To ensure resources invested into services are commensurate with benefit, economists utilise various methods to assess value of life. Understanding the performance of these methods in older populations is crucial, particularly in low-and-middle-income countries (LMICs), where the majority of older people will live by 2030. Value of Statistical Life Years (VSLY) is widely used in cost-benefit analyses but rarely been in LMICs or in older people. Objective: This study aimed to investigate the hypothesis that frailty would be associated with a lower VSLY in participants in rural Burkina Faso, when controlling for factors found in other studies likely to affect VSLY, such as socio-demographics, multimorbidity, quality of life, and disability.
Methods: The study included 3,988 adults aged 40 years and older from a population-representative household survey done in Nouna, Burkina Faso. Data were collected on sociodemographic characteristics, chronic medical conditions, quality of life, disability, physical performance, and VSLY. Frailty status was derived using Fried's frailty phenotype. Bivariate analyses investigated the association between quintiles of VSLY and frailty. To explore modification of associations by other variables, we built sequential binary logistic regression models comparing each quintile of VSLY with the first (lowest) quintile. Models included frailty category, age, sex, marital status, educational attainment, and wealth. We sequentially added quality of life, multimorbidity, and disability.
Results: Of 2,761 survey participants included in this analysis, 51.4% were female. Average age was 54.5 years (with 70.0% aged 40-59 years), 24.8% of respondents reported being alone, and 84.5% had not completed education. In bivariate analyses, we found a significant negative association between higher VSLY and frailty, increasing age, disability, and quality of life. Conversely, being male, married, and educated were positively associated with higher VSLY. The negative association between VSLY and frailty remained significant after adjusting for age, gender, education, wealth, quality of life, disability, and multimorbidity (odds of being frail for VSLY quintile 5 vs quintile 1 was 0.48, 95% CI 0.37-0.64 for the fully adjusted model). Furthermore, effect of age, education, and wealth on VSLY became non-significant once frailty was included in the model.
Conclusion: There is a strong relationship between the value that older people place on their lives and their frailty status. Frailty status is important to consider when assessing VSLY, especially in LMICs in which there is a rapidly growing older population.