Univariate and multivariate spatial models of health facility utilisation for childhood fevers in an area on the coast of Kenya
In: International Journal of Health Geographics, Jg. 16 (2017), Heft 1, S. 1-8
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Background Precise quantification of health service utilisation is important for the estimation of disease burden and allocation of health resources. Current approaches to mapping health facility utilisation rely on spatial accessibility alone as the predictor. However, other spatially varying social, demographic and economic factors may affect the use of health services. The exclusion of these factors can lead to the inaccurate estimation of health facility utilisation. Here, we compare the accuracy of a univariate spatial model, developed only from estimated travel time, to a multivariate model that also includes relevant social, demographic and economic factors. Methods A theoretical surface of travel time to the nearest public health facility was developed. These were assigned to each child reported to have had fever in the Kenya demographic and health survey of 2014 (KDHS 2014). The relationship of child treatment seeking for fever with travel time, household and individual factors from the KDHS2014 were determined using multilevel mixed modelling. Bayesian information criterion (BIC) and likelihood ratio test (LRT) tests were carried out to measure how selected factors improve parsimony and goodness of fit of the time model. Using the mixed model, a univariate spatial model of health facility utilisation was fitted using travel time as the predictor. The mixed model was also used to compute a multivariate spatial model of utilisation, using travel time and modelled surfaces of selected household and individual factors as predictors. The univariate and multivariate spatial models were then compared using the receiver operating area under the curve (AUC) and a percent correct prediction (PCP) test. Results The best fitting multivariate model had travel time, household wealth index and number of children in household as the predictors. These factors reduced BIC of the time model from 4008 to 2959, a change which was confirmed by the LRT test. Although there was a high correlation of the two modelled .
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Univariate and multivariate spatial models of health facility utilisation for childhood fevers in an area on the coast of Kenya
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Autor/in / Beteiligte Person: | Ouma, Paul O. ; Agutu, Nathan O. ; Snow, Robert W. ; Noor, Abdisalan M. |
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Zeitschrift: | International Journal of Health Geographics, Jg. 16 (2017), Heft 1, S. 1-8 |
Veröffentlichung: | BMC ; BioMed Central, 2017 |
Medientyp: | academicJournal |
DOI: | 10.1186/s12942-017-0107-7 |
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