Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model

Abstract Background Prevention of Mother-to-Child HIV Transmission (PMTCT) coverage has been low in Ethiopia and the service has been implemented in a fragmented manner. Solutions to this problem have mainly been sought on the supply-side in the form of improved management and allocation of limited...

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Main Authors: Elias Asfaw Zegeye, Josue Mbonigaba, Zacharie Tsala Dimbuene
Format: Article
Language:English
Published: BMC 2018-11-01
Series:BMC Women's Health
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12905-018-0679-9
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spelling doaj-d33881c0349141a3ab3b91cc2c76bdcc2020-11-25T01:11:45ZengBMCBMC Women's Health1472-68742018-11-0118111110.1186/s12905-018-0679-9Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression modelElias Asfaw Zegeye0Josue Mbonigaba1Zacharie Tsala Dimbuene2School of Accounting, Economics and Finance, Economics Department, University of KwaZulu-NatalSchool of Accounting, Economics and Finance, Economics Department, University of KwaZulu-NatalAfrican Population and Health Research Center, Statistics and Survey UnitAbstract Background Prevention of Mother-to-Child HIV Transmission (PMTCT) coverage has been low in Ethiopia and the service has been implemented in a fragmented manner. Solutions to this problem have mainly been sought on the supply-side in the form of improved management and allocation of limited resources. However, this approach largely ignores the demand-side factors associated with low PMTCT coverage in the country. The study assesses the factors associated with the utilization of PMTCT services taking into consideration counts of visits to antenatal care (ANC) services in urban high-HIV prevalence and rural low-HIV prevalence settings in Ethiopia. Methods A multivariate regression model was employed to identify significant factors associated with PMTCT service utilization. Poisson and negative binomial regression models were applied, considering the number of ANC visits as a dependent variable. The explanatory variables were age; educational status; type of occupation; decision-making power in the household; living in proximity to educated people; a neighborhood with good welfare services; location (urban high-HIV prevalence and rural low-HIV prevalence); transportation accessibility; walking distance (in minutes); and household income status. The alpha dispersion test (a) was performed to measure the goodness-of-fit of the model. Significant results were reported at p-values of < 0.05 and < 0.001. Results Household income, socio-economic setting (urban high-HIV prevalence and rural low-HIV prevalence) and walking distance (in minutes) had a statistically significant relationship with the number of ANC visits by pregnant women (p < 0.05). A pregnant woman from an urban high-HIV prevalence setting would be expected to make 34% more ANC visits (counts) than her rural low-HIV prevalence counterparts (p < 0.05). Holding other variables constant, a unit increase in household income would increase the expected ANC visits by 0.004%. An increase in walking distance by a unit (a minute) would decrease the number of ANC visits by 0.001(p < 0.001). Conclusion Long walking distance, low household income and living in a rural setting are the significant factors associated with low PMTCT service utilization. The primary strategies for a holistic policy to improve ANC/PMTCT utilization should thus include improving the geographical accessibility of ANC/PMTCT services, expanding household welfare and paying more attention to remote rural areas.http://link.springer.com/article/10.1186/s12905-018-0679-9PMTCT serviceEthiopiaUrban-rural settingsCount regressionUtilization analysis
collection DOAJ
language English
format Article
sources DOAJ
author Elias Asfaw Zegeye
Josue Mbonigaba
Zacharie Tsala Dimbuene
spellingShingle Elias Asfaw Zegeye
Josue Mbonigaba
Zacharie Tsala Dimbuene
Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
BMC Women's Health
PMTCT service
Ethiopia
Urban-rural settings
Count regression
Utilization analysis
author_facet Elias Asfaw Zegeye
Josue Mbonigaba
Zacharie Tsala Dimbuene
author_sort Elias Asfaw Zegeye
title Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
title_short Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
title_full Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
title_fullStr Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
title_full_unstemmed Factors associated with the utilization of antenatal care and prevention of mother-to-child HIV transmission services in Ethiopia: applying a count regression model
title_sort factors associated with the utilization of antenatal care and prevention of mother-to-child hiv transmission services in ethiopia: applying a count regression model
publisher BMC
series BMC Women's Health
issn 1472-6874
publishDate 2018-11-01
description Abstract Background Prevention of Mother-to-Child HIV Transmission (PMTCT) coverage has been low in Ethiopia and the service has been implemented in a fragmented manner. Solutions to this problem have mainly been sought on the supply-side in the form of improved management and allocation of limited resources. However, this approach largely ignores the demand-side factors associated with low PMTCT coverage in the country. The study assesses the factors associated with the utilization of PMTCT services taking into consideration counts of visits to antenatal care (ANC) services in urban high-HIV prevalence and rural low-HIV prevalence settings in Ethiopia. Methods A multivariate regression model was employed to identify significant factors associated with PMTCT service utilization. Poisson and negative binomial regression models were applied, considering the number of ANC visits as a dependent variable. The explanatory variables were age; educational status; type of occupation; decision-making power in the household; living in proximity to educated people; a neighborhood with good welfare services; location (urban high-HIV prevalence and rural low-HIV prevalence); transportation accessibility; walking distance (in minutes); and household income status. The alpha dispersion test (a) was performed to measure the goodness-of-fit of the model. Significant results were reported at p-values of < 0.05 and < 0.001. Results Household income, socio-economic setting (urban high-HIV prevalence and rural low-HIV prevalence) and walking distance (in minutes) had a statistically significant relationship with the number of ANC visits by pregnant women (p < 0.05). A pregnant woman from an urban high-HIV prevalence setting would be expected to make 34% more ANC visits (counts) than her rural low-HIV prevalence counterparts (p < 0.05). Holding other variables constant, a unit increase in household income would increase the expected ANC visits by 0.004%. An increase in walking distance by a unit (a minute) would decrease the number of ANC visits by 0.001(p < 0.001). Conclusion Long walking distance, low household income and living in a rural setting are the significant factors associated with low PMTCT service utilization. The primary strategies for a holistic policy to improve ANC/PMTCT utilization should thus include improving the geographical accessibility of ANC/PMTCT services, expanding household welfare and paying more attention to remote rural areas.
topic PMTCT service
Ethiopia
Urban-rural settings
Count regression
Utilization analysis
url http://link.springer.com/article/10.1186/s12905-018-0679-9
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