PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya
Version 1
: Received: 14 September 2020 / Approved: 18 September 2020 / Online: 18 September 2020 (03:52:59 CEST)
How to cite:
Mwenda, N.; Nduati, R.; Kosgey, M.; Kerich, G. Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya . Preprints2020, 2020090412. https://doi.org/10.20944/preprints202009.0412.v1
Mwenda, N.; Nduati, R.; Kosgey, M.; Kerich, G. Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya . Preprints 2020, 2020090412. https://doi.org/10.20944/preprints202009.0412.v1
Mwenda, N.; Nduati, R.; Kosgey, M.; Kerich, G. Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya . Preprints2020, 2020090412. https://doi.org/10.20944/preprints202009.0412.v1
APA Style
Mwenda, N., Nduati, R., Kosgey, M., & Kerich, G. (2020). Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya <strong> </strong>. Preprints. https://doi.org/10.20944/preprints202009.0412.v1
Chicago/Turabian Style
Mwenda, N., Mathew Kosgey and Gregory Kerich. 2020 "Differences in Household size, Employment Status and Ability to pay for the service, are Associated with Distance Travelled for Inpatient Care in Kenya <strong> </strong>" Preprints. https://doi.org/10.20944/preprints202009.0412.v1
Abstract
Background: Distance to a health facility for inpatient care in developing countries has been a huge hindrance towards the achievement of the Sustainable Development Goal three. The United Nation encourages countries to research on access to inpatient care, so as to form health policies based on data. Methods: Data on four hundred and eighty-one participants of all ages from forty-seven counties in Kenya who sought inpatient care in Kenya in 2018 were analyzed. Distance to a health facility was captured as a continuous variable and was self-reported by the respondent. The response exhibited a discrete mass at zero and continuous characteristic, therefore a Tweedie distribution was adopted for modelling. Due to the correlation nature of clustered data, we embraced the Generalized Estimating Equations approach with an exchangeable correlation. Since no standard software was available to analyze this problem, we developed an R functions. We assessed the best model fit using the QICu and criteria, in which the lowest value for the former and the highest for the later are preferred.Findings: Differences in employment, ability to pay for the service and household size are associated with the distance covered to access government facilities. Interpretation: Poor people tend to have large households and are more likely to live in rural areas and slums, thus are forced to travel for long distance to access inpatient care. Compared to unemployed, the employed could have better socio-economic status and possibly live within reach of the inpatient health facilities, therefore travel less distances to access. Longer distances are associated with high payments, signifying some form of specialized treatment care due to the complexity of the medical cases, that are expensive to treat.
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
