Predictors of skilled attendance at delivery among antenatal clinic attendants in Ghana: a cross-sectional study of population data
Identifieur interne : 000291 ( Main/Exploration ); précédent : 000290; suivant : 000292Predictors of skilled attendance at delivery among antenatal clinic attendants in Ghana: a cross-sectional study of population data
Auteurs : Mary Amoakoh-Coleman [Pays-Bas, Ghana] ; Evelyn K. Ansah [Ghana] ; Irene Akua Agyepong [Ghana] ; Diederick E. Grobbee [Pays-Bas] ; Gbenga A. Kayode [Pays-Bas] ; Kerstin Klipstein-Grobusch [Pays-Bas, Afrique du Sud]Source :
- BMJ Open [ 2044-6055 ] ; 2015.
Abstract
To identify demographic, maternal and community predictors of skilled attendance at delivery among women who attend antenatal clinic at least once during their pregnancy in Ghana.
A cross-sectional study using the 2008 Ghana Demographic and Health Survey (DHS) data. We used frequencies for descriptive analysis, χ2 test for associations and logistic regression to identify significant predictors. Predictive models were built with estimation of area under the receiver operating characteristic curves (AUC).
Ghana.
A total of 2041 women who had a live birth in the 5 years preceding the survey, and attended an antenatal clinic having a skilled provider, at least once, during the pregnancy.
Skilled attendance at delivery.
Overall, 60.5% (1235/2041) of women in our study sample reported skilled attendance at delivery. Significant positive associations existed between skilled attendance at delivery and the variables such as maternal educational level, wealth status class, ever use of contraception, previous pregnancy complications and health insurance coverage (p<0.001). Significant predictors of skilled attendance were wealth status class, residency, previous delivery complication, health insurance coverage and religion in a model with AUC (95% CI) of 0.85 (0.83 to 0.88).
Women less likely to have skilled attendance at delivery can be identified during antenatal care by using data on wealth status class, health insurance coverage, residence, history of previous birth complications and religion, and targeted with interventions to improve skilled attendance at delivery.
Url:
DOI: 10.1136/bmjopen-2015-007810
PubMed: 25991459
PubMed Central: 4442247
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Objective</title>
<p>To identify demographic, maternal and community predictors of skilled attendance at delivery among women who attend antenatal clinic at least once during their pregnancy in Ghana.</p>
</sec>
<sec><title>Design</title>
<p>A cross-sectional study using the 2008 Ghana Demographic and Health Survey (DHS) data. We used frequencies for descriptive analysis, χ<sup>2</sup>
test for associations and logistic regression to identify significant predictors. Predictive models were built with estimation of area under the receiver operating characteristic curves (AUC).</p>
</sec>
<sec><title>Setting</title>
<p>Ghana.</p>
</sec>
<sec><title>Participants</title>
<p>A total of 2041 women who had a live birth in the 5 years preceding the survey, and attended an antenatal clinic having a skilled provider, at least once, during the pregnancy.</p>
</sec>
<sec><title>Outcome</title>
<p>Skilled attendance at delivery.</p>
</sec>
<sec><title>Results</title>
<p>Overall, 60.5% (1235/2041) of women in our study sample reported skilled attendance at delivery. Significant positive associations existed between skilled attendance at delivery and the variables such as maternal educational level, wealth status class, ever use of contraception, previous pregnancy complications and health insurance coverage (p<0.001). Significant predictors of skilled attendance were wealth status class, residency, previous delivery complication, health insurance coverage and religion in a model with AUC (95% CI) of 0.85 (0.83 to 0.88).</p>
</sec>
<sec><title>Conclusions</title>
<p>Women less likely to have skilled attendance at delivery can be identified during antenatal care by using data on wealth status class, health insurance coverage, residence, history of previous birth complications and religion, and targeted with interventions to improve skilled attendance at delivery.</p>
</sec>
</div>
</front>
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<name sortKey="Grobbee, Diederick E" sort="Grobbee, Diederick E" uniqKey="Grobbee D" first="Diederick E" last="Grobbee">Diederick E. Grobbee</name>
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<name sortKey="Klipstein Grobusch, Kerstin" sort="Klipstein Grobusch, Kerstin" uniqKey="Klipstein Grobusch K" first="Kerstin" last="Klipstein-Grobusch">Kerstin Klipstein-Grobusch</name>
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<country name="Ghana"><noRegion><name sortKey="Amoakoh Coleman, Mary" sort="Amoakoh Coleman, Mary" uniqKey="Amoakoh Coleman M" first="Mary" last="Amoakoh-Coleman">Mary Amoakoh-Coleman</name>
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<name sortKey="Ansah, Evelyn K" sort="Ansah, Evelyn K" uniqKey="Ansah E" first="Evelyn K" last="Ansah">Evelyn K. Ansah</name>
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