Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2019
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2019
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

HEALTH FACILITY FACTORS AND INDIVIDUAL FACTORS AS PREDICTORS OF UPTAKE OF SKILLED BIRTH SERVICES IN LURAMBI SUB COUNTY, KENYA.

Authors: Mukaka, Victor Emali; Mukabana., Beatrice;

HEALTH FACILITY FACTORS AND INDIVIDUAL FACTORS AS PREDICTORS OF UPTAKE OF SKILLED BIRTH SERVICES IN LURAMBI SUB COUNTY, KENYA.

Abstract

Introduction: Factors determining maternity services utilization are diverse and yet interrelated. They can be grouped into five main factors namely socio cultural factors, Physical access, and economic access, past obstetric experience and perceived benefit or quality of care. Objective: To determine predictors of uptake of skilled birth services in Lurambi sub-County. Methodology: A descriptive cross-sectional study adopting Quantitative methods. The study was carried out in Kakamega County and Sampling frame consisting of all the 17 government facilities were used. A multistage stratified sampling strategy was used and Probability sampling technique of systematic sampling applied to select women seeking health facility delivery services in Lurambi sub county government facilities (n = 200). Data was analyzed through descriptive statistics, chi-square test and logistic regression. Results: The majority of the women were aged 20-35 years (70.5%) and 66% were married. About 40% had 1-2 children and majority had attained secondary education at 48.5% as the highest educational level. A majority of the women were business people at 25.5% and CHVs have a bigger role in deciding where the mothers deliver at 42%. Majority of the mothers 77.5% were less wealthy and a majority of them attended the ANC clinic at 98.5%. Chi square analysis showed that there was no statistically significant relationship between the skilled service delivery and age X2 (1, N=200) =0.22, p>0.05. Multinomial logistic regression was done, and the results showed people with one to two children were 1.7 times more likely (OR=1.17, 95% C.I, 0.4-3.8) to belong to the ?poor birth service? group than the ?good birth service? group compared to respondents who had seven children and above. With regards to marital status, respondents who were divorced from their spouses received good birth services (66.7%), while majority of the married people received poor birth services (55.6%). Results from chi square test showed that there was a statistically significant relationship between marital status and uptake of skilled birth service X2 (4, N=248) =39.109, p<0.05. Bivariate analysis on health facility related factors that are associated with uptake of skilled service delivery showed that there was a borderline significant relationship between delivery place and uptake of skilled birth service in the study area (OR: 0.8; 95% CI: 0.6 ? 1.2; p=0.02) Conclusion and Recommendation: Demographic factors like age, marital status, number of children and education level determine whether a woman would deliver in hospital or not.The factors are key players in women?s ability to uptake skilled birth services. It is recommended that sensitization of the elderly women and adolescent girls be done on importance of early access of antenatal clinic and hospital delivery through the community health volunteers.

Keywords

ANC skilled birth delivery Kakamega county individual factors health facility related factors nursing.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 5
    download downloads 4
  • 5
    views
    4
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
5
4
Green