Most SDG-inequality indices rely on a unidimensional design which cannot reflect how a given health outcome is distributed along the socio-economic spectrum. The concentration index can overcome this limitation. With an application to adult excess weight data, the concentration index was illustrated along with a decomposition method which allowed for key predictors to be identified. An Erreyger's concentration index and Shapley decomposition-based approach provide a relatively simple analytical tool to the monitoring of socio-economic inequalities in health. Such analytical approach should be considered as a monitoring tool by public managers to inform SDG policy and budgetary decisions.
Accounting for socio-economic inequalities in health to inform SDG decision making: a proof-of-concept study / Candio, Paolo. - In: SUSTAINABLE FUTURES. - ISSN 2666-1888. - 2024, 8:(2024), p. 100321. [10.1016/j.sftr.2024.100321]
Accounting for socio-economic inequalities in health to inform SDG decision making: a proof-of-concept study
Candio, Paolo
2024-01-01
Abstract
Most SDG-inequality indices rely on a unidimensional design which cannot reflect how a given health outcome is distributed along the socio-economic spectrum. The concentration index can overcome this limitation. With an application to adult excess weight data, the concentration index was illustrated along with a decomposition method which allowed for key predictors to be identified. An Erreyger's concentration index and Shapley decomposition-based approach provide a relatively simple analytical tool to the monitoring of socio-economic inequalities in health. Such analytical approach should be considered as a monitoring tool by public managers to inform SDG policy and budgetary decisions.File | Dimensione | Formato | |
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