Socio-economic determinants in selecting childhood diarrhoea treatment options in Sub-Saharan Africa: A multilevel model
Diarrhoea disease which has been attributed to poverty constitutes a major cause of morbidity and mortality in children aged five and below in most low-and-middle income countries. This study sought to examine the contribution of individual and neighbourhood socio-economic characteristics to caregiver's treatment choices for managing childhood diarrhoea at household level in sub-Saharan Africa.
Multilevel multinomial logistic regression analysis was applied to Demographic and Health Survey data conducted in 11 countries in sub-Saharan Africa. The unit of analysis were the 12,988 caregivers of children who were reported to have had diarrhoea two weeks prior to the survey period.
There were variability in selecting treatment options based on several socioeconomic characteristics. Multilevel-multinomial regression analysis indicated that higher level of education of both the caregiver and that of the partner, as well as caregivers occupation were associated with selection of medical centre, pharmacies and home care as compared to no treatment. In contrast, caregiver's partners' occupation was negatively associated with selection medical centre and home care for managing diarrhoea. In addition, a low-level of neighbourhood socio-economic disadvantage was significantly associated with selection of both medical centre and pharmacy stores and medicine vendors.
In the light of the findings from this study, intervention aimed at improving on care seeking for managing diarrhoea episode and other childhood infectious disease should jointly consider the influence of both individual SEP and the level of economic development of the communities in which caregivers of these children resides.
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- Socio-economic determinants in selecting childhood diarrhoea treatment options in Sub-Saharan Africa: A multilevel model
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Italian Journal of Pediatrics
- Online Date
- March 2011
- Online ISSN
- BioMed Central
- Additional Links
- Author Affiliations
- 1. Department of Public Health Sciences, Karolinska Institutet, SE, 17177, Stockholm, Sweden
- 2. Southampton Health Technology Assessment Centre, School of Medicine, University of Southampton, Southampton, SO16 7PX, UK
- 3. College of Medicine, University of Ibadan, Ibadan, Nigeria
- 5. Division of Epidemiology, The institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- 4. Departments of Medicine and Health Science, Centre for Health Technology Assessment, Linkoping University, Linkoping, Sweden