Stella T Lartey1, Lei Si2, Barbara de Graaff1, Costan G Magnussen3, Hasnat Ahmad1, Julie Campbell1, Richard Berko Biritwum4, Nadia Minicuci5, Paul Kowal6, Andrew J Palmer7. 1. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia. 2. The George Institute for Global Health, University of New South Wales, Kensington, Australia. 3. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland. 4. Department of Community Health, University of Ghana, Accra, Ghana. 5. National Research Council, Neuroscience Institute, Padova, Italy. 6. World Health Organization, Geneva, Switzerland; University of Newcastle Research Centre for Generational Health and Ageing, Newcastle, Australia. 7. Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia. Electronic address: andrew.palmer@utas.edu.au.
Abstract
BACKGROUND: Obesity is a major public health challenge and its prevalence has increased across the age spectrum from 1980 to date in most parts of the world including sub-Saharan Africa. Studies that derive health state utilities (HSUs) stratified by weight status to support the conduct of economic evaluations and prioritization of cost-effective weight management interventions are lacking in sub-Saharan Africa. OBJECTIVES: To estimate age- and sex-specific HSUs for Ghana, along with HSUs by weight status. Associations between HSUs and overweight and obesity will be examined. STUDY DESIGN: Cross-sectional survey of the Ghanaian population. METHODS: Data were sourced from the World Health Organization Study of Global AGEing and Adult Health (WHO SAGE), 2014 to 2015. Using a "judgment-based mapping" method, responses to items from the World Health Organization Quality-of-Life (WHOQOL-100) used in the WHO SAGE were mapped to EQ-5D-5L profiles, and the Zimbabwe value set was applied to calculate HSUs. Poststratified sampling weights were applied to estimate mean HSUs, and a multivariable linear regression model was used to examine associations between HSUs and overweight or obesity. RESULTS: Responses from 3966 adults aged 18 to 110 years were analyzed. The mean (95% confidence interval) HSU was 0.856 (95% CI: 0.850, 0.863) for the population, 0.866 (95% CI: 0.857, 0.875) for men, and 0.849 (95% CI: 0.841, 0.856) for women. Lower mean HSUs were observed for obese individuals and with older ages. Multivariable regression analysis showed that HSUs were negatively associated with obesity (-0.024; 95% CI: -0.037, -0.011), female sex (-0.011; 95% CI: -0.020, -0.003), and older age groups in the population. CONCLUSIONS: The study provides HSUs by sex, age, and body mass index (BMI) categories for the Ghanaian population and examines associations between HSU and high BMI. Obesity was negatively associated with health state utility in the population. These data can be used in future economic evaluations for Ghana and sub-Saharan African populations.
BACKGROUND: Obesity is a major public health challenge and its prevalence has increased across the age spectrum from 1980 to date in most parts of the world including sub-Saharan Africa. Studies that derive health state utilities (HSUs) stratified by weight status to support the conduct of economic evaluations and prioritization of cost-effective weight management interventions are lacking in sub-Saharan Africa. OBJECTIVES: To estimate age- and sex-specific HSUs for Ghana, along with HSUs by weight status. Associations between HSUs and overweight and obesity will be examined. STUDY DESIGN: Cross-sectional survey of the Ghanaian population. METHODS: Data were sourced from the World Health Organization Study of Global AGEing and Adult Health (WHO SAGE), 2014 to 2015. Using a "judgment-based mapping" method, responses to items from the World Health Organization Quality-of-Life (WHOQOL-100) used in the WHO SAGE were mapped to EQ-5D-5L profiles, and the Zimbabwe value set was applied to calculate HSUs. Poststratified sampling weights were applied to estimate mean HSUs, and a multivariable linear regression model was used to examine associations between HSUs and overweight or obesity. RESULTS: Responses from 3966 adults aged 18 to 110 years were analyzed. The mean (95% confidence interval) HSU was 0.856 (95% CI: 0.850, 0.863) for the population, 0.866 (95% CI: 0.857, 0.875) for men, and 0.849 (95% CI: 0.841, 0.856) for women. Lower mean HSUs were observed for obese individuals and with older ages. Multivariable regression analysis showed that HSUs were negatively associated with obesity (-0.024; 95% CI: -0.037, -0.011), female sex (-0.011; 95% CI: -0.020, -0.003), and older age groups in the population. CONCLUSIONS: The study provides HSUs by sex, age, and body mass index (BMI) categories for the Ghanaian population and examines associations between HSU and high BMI. Obesity was negatively associated with health state utility in the population. These data can be used in future economic evaluations for Ghana and sub-Saharan African populations.
Authors: Stella Lartey; Lei Si; Thomas Lung; Costan G Magnussen; Godfred O Boateng; Nadia Minicuci; Paul Kowal; Alison Hayes; Barbara de Graaff; Leigh Blizzard; Andrew J Palmer Journal: BMJ Glob Health Date: 2020-09