A
proximate determinant of an outcome (or event) is a variable (or factor) that
produces a direct effect on that outcome. It can act as an intermediary
variable through which other variables (or factors) which have indirect effects
on the same outcome variable operate to exhibit their effects. Socioeconomic,
demographic and cultural factors (also called background or underlying factors)
are known to have indirect effects on whether or not a pregnant woman would
choose to deliver her baby in a healthcare facility. The background or
underlying factors of the women can also determine if they will attend or not
attend antenatal clinic during pregnancy. However, antenatal clinic attendance
also has direct effect on a woman’s use of healthcare facility to deliver her
baby.
In this
study we examined whether or not antenatal clinic attendance is a major
proximate determinant of use of healthcare facility for delivery by Nigerian
women. However, the study shows that antenatal care visits had a very strong
direct effect on mothers’ delivery in healthcare facilities. The study used
quantitative data from the 2008 Nigeria Demographic and Health Surveys
(NDHS).Mothers were asked to indicate where they delivered their last babies
(i.e., in Healthcare Facility or outside the healthcare facility)and also the
number of antenatal visits they attended during the pregnancy. A mother that
had four or more visits during the pregnancy was considered to have had
adequate number of visits and those who did not attend at all or attended for
less than four times were considered not to have had adequate attendance.
Information was also collected on the socio-economic and demographic characteristics
of the women.
The data
analyzed consisted of 17,635 women aged 15-49 years who had a live birth within the five years preceding
the survey Stata 12 computer software was used to carry
outdataanalyses.Data analyses wereatunivariate, bivariate andmultivariate
levels. Due to the dichotomous nature of the outcome variable (i.e., whether a
child was delivered in a healthcare facility or not; coded as (1, 0)), the multivariate analyses technique used is
Binary Logistic Regression, and Likelihood Ratio (LR) statistical test of
significance was applied.
Results
from bivariate analysis indicated that the background (underlying) factors of
the women (i.e., age, children ever born, region of residence, educational
level, wealth index status, and religion)
all have significant association with the number of antenatal visits
made by mothers during their last pregnancy (P < 0.001). Similarly,
antenatal clinic attendance has significant relationship with delivery in
healthcare facility (P < 0.001).
The binary
logistic regression which includes all the six background variables and
antennal clinic attendance (i.e., the proximate determinant) indicated a highly
significant contribution to the model chi-square statistic. Women who had adequate number of antenatal clinic visits were about four
times more likely to deliver their babies in healthcare facility than mothers
who did not (OR = 4.4, P < 0.001). The likelihood Ratio (LR) test to determine
the extent to which antenatal clinic attendance helped to explain the effect of
the background variables on delivery in healthcare facilities also gave a
highly significant result (chi-square = 891 on 1 degree of freedom, P <
0.001). This means that antenatal clinic attendance is an important proximate
determinant through which socioeconomic, demographic and cultural factors
influence Nigerian women delivery in healthcare facilities.
We
conclude therefore that policies and programs targeted at encouraging Nigerian
pregnant women to attend adequately antenatal clinics will also increase the
prevalence of their delivery in healthcare facilities, thereby reducing the
risk of maternal and infant mortality.
Underlying Factors Antenatal Clinic Attendance Proximate Determinants Healthcare Facility Delivery Nigeria
Journal Section | Articles |
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Authors | |
Publication Date | August 31, 2017 |
Submission Date | August 30, 2017 |
Published in Issue | Year 2017 |
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