Geography of medication reimbursements in Belgium: an exploratory analysis
As part of a broader multidisciplinary research project dealing with the association between health and green/blue environments, this paper aims at exploring the spatial variation of medication reimbursements within Belgium. These data were potentially and a priori considered as a proxy for health. ...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | DE EN FR IT PT |
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Unité Mixte de Recherche 8504 Géographie-cités
2021
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| Acceso en línea: | https://doaj.org/article/d0bc0191000a428281bec47ba3a0485c |
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| Sumario: | As part of a broader multidisciplinary research project dealing with the association between health and green/blue environments, this paper aims at exploring the spatial variation of medication reimbursements within Belgium. These data were potentially and a priori considered as a proxy for health. This paper is purely exploratory: statistical maps, correlations, PCAs and cluster analyses corroborate the results. Five groups of medications prescribed for health disorders associated with the environment have been selected. We show that – at the level of the municipalities – the spatial distributions of the five medication groups are positively correlated to each other (medication consumption co-vary positively in space, whatever their type), but are independent of the environmental and socio-economic conditions measured. Against our expectation, they prove to be negatively correlated to air pollution and green spaces. Strikingly, the spatial distribution of medication prescriptions follows the linguistic border between Flanders and Wallonia. This implies that the observed differences are mainly due to administrative/political regional differences in terms of health policies, medical schools, pharmaceutical commercial activities, etc. that are hard to quantify (no data, diversity of actors) but should be taken into account in any further explanatory model. Medication reimbursements data correspond to a new type of data, and despite their potential attractiveness for health analyses, extreme care has to be taken when interpreting their spatial variation and their link to health. |
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