n p r nt nd nt n t l r t l z t nn B n l d hB l t H n, h d . H
The Journal of Developing Areas, Volume 49, Number 2, Spring 2015,pp. 109-124 (Article)
P bl h d b T nn t t n v r t ll f B nDOI: 10.1353/jda.2015.0045
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T h e J o u r n a l o f D e v e l o p i n g A r e a s
Volume 49 No. 2 Spring 2015
WOMEN EMPOWERMENT AND ANTENATAL
CARE UTILIZATION IN BANGLADESH1
Belayet Hossain
Thompson Rivers University, Canada
Ahmed A. Hoque
University of Victoria, Canada
ABSTRACT
This study attempts to examine the role of women empowerment in the utilization of antenatal care
in Bangladesh. Four dimensions are considered to measure the women empowerment: the highest
level of education, freedom of choice/movement, power in the household decision making process
and involvement in economic activities. Factor analysis technique is employed to construct the last
three dimensions. The probit and the zero-inflated negative binomial regression models are
specified and estimated using the 2011 Bangladesh Demographic and Health Survey data. Results
show that all four dimensions of women empowerment contribute positively and significantly to
the decision and intensity of utilization of antenatal care in Bangladesh. Findings of the study have
a number of policy implications on this issue for a developing country like Bangladesh.
JEL Classifications: O20; I10; C25
Keywords: Women Empowerment, Antenatal care, Probit Model, Zero-Inflated Negative Binomial
Model, Bangladesh
Corresponding Author’s Email Address: [email protected]
INTRODUCTION
The risk of infant and maternal mortalities is often high in most of the developing
countries. Adequate antenatal care is necessary to improve the health status of a country
as it contributes to the reduction of infant and maternal mortalities. Studies (Hong and
Ruiz-Beltran, 2007; Halim, Bohara and Ruan, 2011; Mcdonagh, 1996; and Habibov,
2011) show that antenatal care is negatively related to both infant and maternal
mortalities. Women receiving adequate antenatal care usually have better opportunity to
learn more about their health during pregnancy, child birth and parenting; and have their
health problems diagnosed and treated early. These cares result in higher chances of
normal delivery with better health for both newborn baby and the mother, which may
lead to lower infant and maternal mortalities.
There is a healthy body of literature on the determinants of antenatal care.
Simkhada et al. (2008) and Say and Raine (2007) have done a systematic review and
summarized most of the studies on this issue. The former examine 28 peer-reviewed
studies published since 1990, while the later examine 30 for the same period. These
studies identify and analyze main factors affecting the utilization of antenatal care in
developing countries. The major determinants of antenatal care utilization in developing
countries are divided into four categories: (1) women socio-demographic characteristics
110
(e.g., age, education and age at birth); (2) current pregnancy characteristics (e.g., birth
order, gender of the child, multiple births and wanting the last child or current
pregnancy); (3) affordability (e.g., socio-economic status such as spouse’s education,
household wealth/income and insurance coverage); and (4) accessibility to the services
(e.g., place of residence such as rural/urban and region, travel time to health facilities and
public/private facilities). Other factors such as ethnicity, religion and culture are also
found to be significant determinants of antenatal care utilization.
Women empowerment is believed to be an important factor in determining the
utilization of antenatal care. Duflo (2012) highlights three dimensions of women
empowerment: (i) education; (ii) participation in the decision making process; and (iii)
involvement in economic activities. She refers education as the first and most important
dimension of empowerment followed by other two.
Higher the level of education of a woman, better the chance that she would be
enlightened and be more conscious; and therefore can make better decisions for herself as
well as for her family. Educated women can easily comprehend the benefits of antenatal
care and thus expected to utilize antenatal care more effectively. They may also be better
informed about how the healthcare system functions and hence can get better access to it.
Furthermore, educated women can easily interact and communicate with the health
service providers to get required cares (Bloom et al., 2001).
In many developing countries, where a man is typically the head of a household
makes most of the household decisions and the wife experiences no equity in this process
(Holland and Hogg, 2001). For instance, men often control the financial matters no
matter who earns the cash and make decisions regarding major household purchases. This
translates into financial vulnerability and lack of autonomy of a woman and more
dependent on her spouse. In such cases, a woman who needs antenatal care has to rely on
her husband’s judgment and willingness to spend money on such cares. So, we
hypothesize that the higher the participation in the household decisions making process
by a woman, the higher is the likelihood that she would utilize the antenatal care in the
developing countries.
In a developing country like Bangladesh, the opportunity of women involvement
in economic activities is limited. Microcredit organizations increase the scope of being
involved in economic activities for women as most of their members are women in
Bangladesh (Microcredit Regulatory Authority, 2013). When a woman is involved in
economic activities outside home, it improves the financial stability of the family and
uplifts her social status and self-confidence. It directly contributes to her power in any
household decision making process, including the decision to receive health care. It
makes sense to presume that such a woman would receive more antenatal care.
Several studies (Adamu and Salihu, 2002; Pallikadavath et al., 2004; Matsumura
and Gubhaju, 2001 and Mumtaz and Salway, 2005) suggest that the lack of women
autonomy is one of the reasons for under-utilization of the antenatal care. They show that
women autonomy is positively related to the antenatal care utilization. Ahmed et al.
(2010) find that economic status, education and empowerment (called as the 3Es) are
significantly associated with the utilization of maternal health services. They compare
two groups of women for each factor using data from 33 developing countries and
demonstrate inequality in maternal healthcare services utilization. However, the study
shows only the association between factors not the causality - it controls neither the other
111
the relevant variables nor the heterogeneity across countries. Most of these studies are
either regional in nature or fail to address the women empowerment broadly using
representative national level data The present study is an attempt to examine the role of
different dimensions of women empowerment on the antenatal care utilization in
Bangladesh to void the gap in the literature.
Over the last thirty years, Bangladesh has emerged as one of the success stories
worldwide in healthcare achievements despite of high population density, low per capital
income, widespread poverty and low per capita expenditure on healthcare, corruption and
political fragmentation. Since 1980, the maternal mortality has dropped by more than 75
percent, while the infant mortality has dropped by more than half since 19902. Maternal
and child under five mortality rates are estimated to be 2.4 and 48 per 1000 in 2010
respectively (WHO, 2013). As a result, life expectancy at birth climbs to 70 years in 2011
(WHO, 2013). Women empowerment is considered as one of the key factors behind the
success of healthcare in Bangladesh. Appropriate education policy targeting girls and
access to microcredits institutions which provide credit, healthcare services and education
have increased the women empowerment remarkably in Bangladesh (World Bank, 2013).
Given the prevailing situation in Bangladesh, it is of interest to examine the role of
women empowerment in the utilization of antenatal care.
The reminder of the paper is organized as follows. The next section presents a
discussion on data and methodology. Results and Discussion section presents the findings
and their interpretations of the study and concluding remarks and policy
recommendations are made in the Summary and Policy Implications section.
METHODOLOGY AND DATA
Data and Weights
The data used in this study are from the 2011 Bangladesh Demographic and Health
Survey (BDHS), a nationally representative sample survey. The 2011 BDHS contains
information of all ever-married women aged 12-49 residing in the selected households. A
sample of size 7,318 women, those who have given birth in last five years has been
selected. The BDHS provides useful statistics that can be used to determine changes in
key areas of development in Bangladesh including maternal and child health, women
involvement in economic activities, education and poverty reduction (see, NIPORT et al.,
2013). The survey is conducted through the collaboration between the National Institute
of Population Research and Training (NIPORT) of the Ministry of Health and Family
Welfare, ICF International/Macro International/ORC Macro, and Mitra and Associates.
The BDHS samples are collected using stratified multi-stage cluster sampling.
Hence the sample data is not an identical and independently distributed (iid) sample and
observations are selected using non-simple random sampling technique. Non-simple
random sampling, which is well known as complex survey sampling, consists of various
probabilities of selections at different levels. The weight assigned to each observation is
inversely proportional to the probability of selection. Sampling weights that come with
the survey data are used in estimation, instead of simple random sampling weight. The
weight series is rescaled following the BDHS manual and normalized such that the sum
of all normalized weights is equal to one.
112
Measuring Women Empowerment
The BDHS contains a number of variables that can be used to measure different
dimensions of women empowerment. Besides education, other dimensions of
empowerment are constructed using factor analysis technique. In the survey, respondents
were asked about who makes particular decisions, e.g., major household purchases,
respondent’s own healthcare and use of contraception. Four options were offered to each
question in the survey: a) respondent alone; b) respondent and spouse jointly; c) husband
alone; and d) someone else. Binary response variables are created by merging categories
a) and b) to be “1” to denote that the respondent participates in decision making; and c)
and d) to be “0” to denote that the respondent does not participate in the decision making
process. Nine variables included in the factor analysis are: choosing contraceptive
method, deciding the use of contraception, decision about respondent’s own health,
participation in major household purchases, visiting families and relatives, involvement
in microcredit organizations, decision about child healthcare, freedom of going to heath
center alone, and freedom of going to health center with a young child.
Using the principal component analysis for the above variables, three factors are
extracted that represent three dimensions of women empowerment. These dimensions are
named as freedom of choice and movement, decision making power in the household and
involvement in economic activities outside home. Table 1 presents the summary of factor
analysis, where three factors together account for more than 63 percent of the variations
in the sample data. Adding respondent’s level of education to these three factors, we
have four indicators to measure four dimensions of women empowerment.
TABLE 1. FACTOR ANALYSIS RESULTS FOR WOMEN EMPOWERMENT
VARIABLES
Factor/Dimension Eigen
value
Explained
Variance
(in proportion)
Cumulative
proportion
of variance
Factor 1:
Freedom of choice/ movement
Factor 2:
Power in household decisions
Factor 3:
Involve in economic activity
2.89
1.79
1.03
0.3026
0.2123
0.1198
0.3026
0.5149
0.6347
Models and Variables
Two models have been used to examine the influence of women empowerment along
with other variables that determine the decision of receiving and frequency of antenatal
care. A discrete choice model, with the dependent variable being a binary outcome of
whether a woman, who has given a birth in last five years has received any antenatal care
from health professionals or not, can be estimated by logit or probit regression model.
This study uses a probit model, as given below, to estimate the probability of receiving
antenatal care:
113
( | ) ∫ ( )
( )
where is the probability of receiving antenatal care by a woman i. if antenatal
care is received from health professionals and , otherwise.
To examine the impact of women empowerment on the frequency of antenatal
care visits, the Zero-Inflated Negative Binomial (ZINB) regression model has been
specified. In ZINB model the count response variable is with
probability for zero count and ( ) with probability
( ) for non-zero cunt so that
( ) ( )( )
( ) ( ) (
)
( ) (
)( )
where is the mean of the underlying negative binomial distribution and is the over-
dispersed parameter. The parameter is modeled as = exp( ) where is the
( ) vector of unknown parameters associated with the known covariates
( ) where is the number of covariates.
The ZINB model appears to be appropriate when dependent variable is a count
variable, number of nonnegative counts of an event has extra-Poisson variation (over-
dispersion)3 and there exists excessive zero values of dependent variable (Yau, Wang and
Lee, 2003). The distribution of the frequency of antenatal care visits (the dependent
variable) as presented in Figure 1 shows a high zero value frequency, which supports the
use of ZINB model4.
In our model, there are four categories of covariates. First category includes four
dimensions of women empowerment (highest level of education, power in household
decision making process, freedom of choice/movement and involvement in economic
activities). The specification of all variables included in empowerment category is
presented in Table 2.
In second category of covariates, individual characteristics of the respondent other
than education, such as age of the respondent, if pregnancy wanted, experience from
previous child birth and age at first birth are included. Third category includes household
characteristics, such as household’s economic condition, spouse’s level of education and
occupation, and if the household has a television or/and radio to access information.
Geographical location (e.g., town, city or country side) of residence of the respondent is
included in the final category. Table 3 presents the list of all explanatory variables and
their specifications under category 2, 3 and 4.
114
FIGURE 1: DISTRIBUTION OF THE ANTENATAL CARE VISITS
Source: Bangladesh Demographic and Health Survey, 2011.
The estimated coefficients of probit and ZINB models provide the signs of the
partial effects of each of the explanatory variables on the response probability
(Wooldridge 2002, p. 465). For instance, the sign of an estimated coefficient in probit
model determines whether the variable has a positive or negative effect on the probability
of receiving antenatal care of by a woman. But to get the magnitude of the impact, the
marginal effect has to be calculated. Using STATA software commands we estimate
marginal effects of all covariates separately for both models.
RESULTS AND DISCUSSIONS
Descriptive Statistics
Table 2 presents descriptive statistics of explanatory variables related to women
empowerment, while descriptive statistics of other explanatory variables are presented in
Table 3. Sixty seven percent of the total respondents (7,318) receive antenatal care from
the health professionals with a mean visit of 3.59. The WHO guideline (WHO, 2003)
recommends that every expecting mother should have at least four antenatal care visits
per pregnancy period. The survey data (NIPORT, 2013) shows that about 40% of the
pregnant women who received antenatal care have four or more visits with a mean of
6.06. Other 60% have visits between 1 and 3 with a mean of 1.96.
The utilization of antenatal care increases significantly with the increase in
respondent’s level of education. Among the respondents, 30% have primary, 43% have
secondary and 8.5% have post-secondary education. Fifty eight percent of the
respondents having primary education received such cares with a mean visit of 2.95. On
the other hand, 96% of the respondents having post-secondary education received
antenatal care with mean of 5.5 visits. Similarly, empowered women, when measured by
other indices also show higher utilization of antenatal care (Table 3).
Of the total respondents, 62%, 21% and 3% belong to 20-29, 30-39 and 40-49
age groups respectively. The percentage of respondents receiving antenatal care as well
01
02
03
04
0
Pe
rcen
t
0 5 10 15 20antcarefr
Number of Antenatal Care Visits
Mean: 2.39
Variance: 7.22
115
TABLE 2. SPECIFICATION AND DESCRIPTIVE STATISTICS OF VARIABLES
MEASURING WOMEN EMPOWERMENT
Variables
Description of variable
No. of
Obs.
(%)
Women with
any ant. care
Women with
1-3 ant. care
visits
Women with
4 ant. care
visits
No. of
women
(%)
Aver.
visits
No. of
women
(%)
Aver.
visits
No. of
women
(%)
Aver.
visit
Number of women received
antenatal care
4873
(67%)
4873
(67%)
3.59 2940
(60%)
1.96 1933
(40%)
6.06
Dimension 1: Education
Level of Education: Respondent’s highest level of education (default: no education)
Primary
If the highest level education is primary then 1, else 0
2191 (29.9%)
1265 (58%)
2.95 898
(41%) 1.87
367 (17%)
5.6
Secondary If the highest level education
is secondary then 1, else 0
3171
(43.3%)
2475
(78%) 3.64
1450
(46%) 2.01
1025
(32%)
5.94 Post-
Secondary
If the highest level education is
post-secondary then 1, else 0 624
(8.5%)
601
(96%) 5.5
179
(29%) 2.27
422
(68%)
6.86
Other dimensions of women empowerment: Contraception
Decision
If respondent has say on the
use of contraception then
1,else 0
4489 (61.3%)
3082 (69%)
3.67 1833
(41%) 2
1249 (28%)
6.12
Contraception
Method
If respondent can 4choose a
method then 1, else 0
4875
(66.6%)
3339
(68%) 3.66
1991
(.41%) 2
1348
(27%)
6.11
Own Health If respondent has say about seeking own healthcare then 1,
else 0 otherwise
4460
(61%)
3065
(69%) 3.71
1795
(40%) 2
1270
(29%)
6.11
Major HH Purchase
If respondent has say on major household purchase then 1,
else 0
4062
(55.5%)
2795
(69%) 3.78
1595
(39%) 2
1200
(30%
6.15
Visiting Families
If respondent has freedom over visiting family members
then 1, else 0
4282
(58.5%)
2958
(69%) 3.77
1707
(40%) 2
1251
(29%)
6.18
Children
Health
If respondent has say about
seeking children’s healthcare
then 1, else 0
5098 (70%)
3499 (68%)
3.74 2030
(40%) 2
1469 (29%)
6.15
Going Alone to
Health Centre
If respondent has freedom to
go to health centre alone then
1, else 0
4637 (63%)
3161 (68%)
3.68 1849
(40%) 1.98
1312 (28%)
6.1
Going to
Health Centre with a Young
Child
If respondent has freedom to
go to health centre with a young child then 1, else 0
2458 (33.6%)
1664 (68%)
3.53 1022
(42%) 1.93
642 (26%)
6.1
Association with Micro-
Credit Inst.
If respondent associates with microcredit institutions then 1,
else 0
2555
(34.9%)
1632
(64%) 3.43
1008
(39%) 1.97
624
(24%)
5.78
Source: Bangladesh Demographic and Health Survey, 2011.
116
TABLE 3. SPECIFICATION AND SUMMARY STATISTICS OF OTHER
VARIABLES IN THE STUDY
Variables
Description of variable
No. of
women
(%)
Women with any ant. care
Women with 1-3 ant. care
visits
Women with
4 ant. care visits
No. of
women (%)
Aver.
visits
No. of
women (%)
Aver.
visits
No. of
women (%)
Aver.
visits
Respondent’s other characteristics
Age group
Age1:
If respondent belongs to age group 20-29 then 1; else 0
(Default group: 12-19)
4523
(62%)
3095
(68%) 5.58
1963
(41%) 1.98
1232
(27%) 6.0
Age2 If respondent belongs to age group 30-39 then 1; else 0
1544 (21%)
936 (61%)
3.94 544
(35%) 1.96
392 (26%)
6.45
Age3 If respondent belongs to age
group 40-49 then 1; else 0
218
(3%)
95
(44%) 2.91
72
(33%) 1.81
23
(11%) 6.35
Pregnancy
wanted
If pregnancy wanted then 1;
else 0
5188
(71%)
3585
(69%) 3.65
2121
(41%) 1.98
1464
(28%) 6.07
No. of births in last 5 years
A count variable Mean: 1.2; Sd=0.43; Max 4 and Min 1
Age at first
birth
Respondent’s age at first birth:
continuous variable Mean: 18.084; Sd=3.29; Max 40 years and Min. 12 years
Household Characteristics
Poor
If a respondent belongs to
wealth index 2 then 1; else 0 (default: wealth index 1,
poorest)
1408
(19%)
924
(66%)
3.09
625
(44%)
1.88
299
(21%)
5.61
Middle If respondent belongs to wealth index group 3 then 1;
else 0
1473
(20%)
1122
(76%) 3.45
697
(47%) 2
425
(29%) 5.83
Rich
If respondent belongs to
wealth index group 4 then 1;
else 0
1513
(21%)
1382
(91%) 4.85
542
(36%) 2.17
840
(56%) 6.58
Spouse education
A continuous variable indicating years of schooling
5.45; Sd=4.68; Max18 and Min 0
Spouse
occupation
If spouse occupation is agri.
then 1; else 0
5391
(73.7%)
3860
(72%) 3.79
2200
(41%) 2
1660
(31%) 6.16
Access to
information
If household has TV and/or
Radio then 1; else 0
2978
(41%)
2385
(81%) 4.1
1223
(41%) 2.02
1162
(40%) 6.28
Religion If respondent’s religion is Islam then 1; else 0
6594 (90%)
4335 (66%)
3.54 2653
(40%) 1.96
1682 (26%)
6.03
Geographical location of residence
Place of residence (Default: country side/rural)
Town If respondent resides in small
city or town then 1; else 0
1573
(21.5%)
1233
(78%) 4.03
643
(41%) 2.07
590
(37%) 6.16
City If respondent resides in city then 1; else 0
751 (10.3%)
649 (86%)
4.9 240
(32%) 2.07
409 (54%)
6.56
Source: Bangladesh Demographic and Health Survey, 2011.
117
as the mean number of visits, decreases as the level of age group increases (Table 3). On
the other hand, the percent and mean number of visits gradually increases with the
increase in the wealth level. For example, 66% of the respondents belong to wealth index
2 receives antenatal care with a mean visits of 3.09, whereas for the wealth index 4, it is
91% with a mean visits of 4.85. More respondents residing in towns or cities receive
antenatal care with a higher mean number of visits compared to respondents residing in
country sides or rural areas (Table 3).
Results of the Probit Model
The probit model is estimated to determine how different indicators of women
empowerment influence the decision of receiving antenatal care. The results of the probit
model are presented in column 2 of Table 4. The Wald Statistic suggests that the data fit
the model very well. The signs of the coefficients of all explanatory variables meet our
prior expectations. Given that the probit regression model provides only the signs of the
coefficients, marginal effects of all covariates are estimated separately to observe the
magnitudes of the impacts. Marginal effects of the probit model are shown in column 3
of Table 4. Of the 21 explanatory variables, 15 are significant at 1% level, three are at 5%
level and three are at 10% level (column 2, Table 4). All factors representing four
dimensions of women empowerment used in the study are found positive and statistically
significant. Note that three categorical variables are used to see the effect of education on
the utilization of antenatal care. The marginal effects of primary, secondary and post-
secondary level of education are 0.086, 0.173 and 0.310 respectively (column 3, Table 4).
The marginal effect of 0.173 for the secondary education level, for instance, indicates that
respondents having secondary level of education have a 17% higher likelihood of
receiving antenatal care by health professionals compared to those who have no
education or other levels of education. Similarly, the likelihood of receiving antenatal
care is 31% higher for those who have post-secondary level of education compared to
others. It also indicates that a respondent with the post-secondary level of education has a
14% higher chance of receiving such cares compared to one who has secondary level of
education.
The estimated marginal effects of the variables representing the participation in
the household decision making process, freedom of choice/movement and involvement in
economic activities are 0.025, 0.025 and 0.022 respectively (column 3, Table 4). These
results imply that respondents, who participate in household decision making process,
have about three percent higher chance of receiving antenatal care compared to those,
who do not participate in such activities. Similarly those, who have more freedom of
choice in using contraception or going out alone have three percent and those who are
involve in economic activities have two percent higher chances of receiving antenatal
care. Note that the marginal effects of these three dimensions of women empowerment
are not very large individually. But if the combined effect of all four dimensions of
women empowerment is calculated, it is significantly large. For instance, an empowered
woman, defined by having secondary level of education, participates in household
decision making process, has freedom to choose her contraception use and method, and is
involved in economic activities, has a 24% percent higher likelihood to receive antenatal
care compared to one who has no education, and is not involved in those activities. Thus,
118
all four dimensions of women empowerment under study play a vital role in receiving
antenatal care in Bangladesh. Among the variables representing respondent’s other
characteristics, age and numbers of births in last five years are negatively related to
receiving antenatal care. Three dummy variables are specified to represent respondents’
age groups. The marginal effects of all age groups are negative and they increase
successively in absolute value (column 3, Table 4), meaning a respondent belongs to a
higher age group is less likely to receive antenatal care.
It is believed that the older women are more experienced and utilize their
experience to stay well during their pregnancy periods instead of going out to receive
antenatal care from the health professionals. Similarly, if a respondent has given multiple
births in the last five years, she is less likely to receive antenatal care. On the other hand,
the marginal effect of the variable indicating age at first birth is positive. When a woman
becomes pregnant at older age, she is expecting more complications and thus she will be
more inclined to receive antenatal care.
Among household characteristics, the marginal effects of spouse’s level of
education, wealth and access to information (TV/Radio) are positive, as expected. The
spouse’s level of education is measured in number of years of schooling. So, the
estimated marginal effect of this variable 0.007 indicates that the likelihood of receiving
antenatal care rises by 0.7% for the woman for every additional year of schooling of her
spouse.
Economic status, represented by three wealth indices, is an important predictor
of receiving antenatal care. The marginal effects of all three wealth indices increase
successively, implying that higher the level of wealth the more likely to receive the
antenatal care. Access to information is represented by owning TV and/or Radio. The
marginal effect of this variable is significant at 10% level. This may be because of the
multicollinearity issue as the BDHS constructs the wealth index taking TV/Radio as one
of the financial assets into account. The marginal effects of agriculture being spouse
occupation and household being Muslim are negative. Women belong to Muslim families
are expected to be more conservative and less likely to go outside to receive antenatal
care from health professionals.
In Bangladesh, the accessibility to health care depends on the geographical
location as well, as more healthcare facilities are located in towns and cities compared to
the country sides. Thus, location of a household influences the probability of using
antenatal care. Two dummy variables for town and city are specified to represent three
locations. The marginal effects of these two dummies are positive and statistically
significant suggesting that a respondent who lives in a city has the largest probability of
receiving antenatal care than one who lives in a town or a country side.
Results of the Zero-Inflated Negative Binomial (ZINB) Regression Model
Upon estimating the probit model, which predicts the probability of receiving antenatal
care, we examine the intensity of the use of antenatal care in Bangladesh based on the
same set of explanatory variables. Intensity of care is measured by the frequency of
antenatal care. The ZINB model is estimated to examine the effects of women
empowerment on the frequency of using antenatal care. The estimated coefficients and
marginal effects of covariates in the ZINB are presented in columns 4 and 6 of Table 4
119
respectively. The data fits the negative binomial regression model even better than that of
the probit model as shown by the Wald Statistic. The Vuong test shows that ZINB model
is more appropriate than standard Negative Binomial regression model. All explanatory
variables of the ZINB model meet a priori expectation. Out of 21 variables, 11 are
statistically significant at less than 1% level, two are at 5% level, three are at 10% level
and five are not significant at an acceptable level. The marginal effects of all women
empowering variables are positive and have large magnitudes, reflecting the importance
of women empowerment on the intensity of using antenatal care. The marginal effects of
three dummy variables representing respondent’s level of education which are 0.42, 0.89
and 1.95 respectively (column 6, Table 4), suggest that the impact of the level of
education on the frequency of visiting health professionals for antenatal care. For
instance, the marginal effect of 1.95 for post-secondary level of education implies that a
respondent having post-secondary level of education is expected to have on average two
more visits compared to one who does not have the post-secondary level of education.
We also observe that that the respondent’s level of education is the largest contributing
factor in explaining the intensity of receiving antenatal care in Bangladesh.
Positive marginal effects of 0.21 and 0.20 suggest that women who participate in
the household decision making and are involved in economic activities respectively are
expected to visit health professionals more often. However, the coefficient with the
variable representing the freedom of choice and movement is found not significant at an
acceptable level. This may be because of multicollinearity problem. Thus, most of the
women empowering factors appear to play an important role in determining the
frequency of antenatal care visit. Further, an empowered woman having post-secondary
education, who participates in household decision making process and is involved in
economic activities is expected to have at least two more (2.3) antenatal care visits
compared to the woman having no empowering factors. Note that the coefficients of all
of the variables representing women empowerment in the inflated model are negative;
indicating that an empowered woman is less likely to have zero antenatal care visits.
Among other characteristics of a respondent, age and number of births in the last
five years negatively influence the frequency of visiting health professionals. The
marginal effects of the age groups suggest that as age of a respondent increases the
number of visits to a health professional declines. This finding is consistent with the
previously found lower probability of receiving antenatal care by an older woman.
Similar conclusion can be drawn for women, who have given multiple births in the last
five years. It is also found that when a respondent’s age at first birth is higher and
pregnancy is wanted, the expected number of visits rises. However, the marginal effect of
wanted pregnancy is not significant at an acceptable level. The economic condition of a
respondent’s household measured by the wealth index is the most important factor
determining the frequency of antenatal care visits. All three indices of wealth have
positive impacts on the intensity of visits and increase when the economic condition of
the household improves. Spouse’s level of education also influences such intensity
positively. The marginal effect of TV/Radio is positive which implies that a respondent
having more information is expected to make more antenatal care visits. On the other
hand, agriculture as being spouse occupation and the respondent being a Muslim
negatively affect the intensity. These findings are plausible. Because, for
120
TABLE 4. RESULTS OF THE PROBIT AND ZERO-INFLATED
NEGATIVE BINOMIAL REGRESSION MODELS
Covariates Probit Model Zero-Inflated Negative Binomial Model4
Coefficient Marginal
effect
Coefficient of
ZINB
Model
Coefficient of
Inflated model Marginal effect
of ZINB model
Women Empowerment
Education (Default no education)
Primary 0.282 (0.053)*** 0.086
(0.017)*** 0.117
(0.060)** -0.476
(0.126)***
0.425
(0.115)***
Secondary 0.581 (0.060)*** 0.173
(0.017)*** 0.231
(0.059)*** -1.109
(0.157***
0.887
(0.122)***
Post-secondary 1.142 (0.131)*** 0.310
(0.027)*** 0.415
(0.074)*** -5.211
(9.523)
1.946
(0.443)***
Power in HH decision 0.080
(0.038)** 0.025
(0.012)** 0.091
(0.029)*** -0.022
(0.100)
0.211
(0.062)***
Freedom of
choice/movement
0.082
(0.040)** 0.025
(0.013)** 0.003
(0.030)
-0.208
(0.101)**
0.078
(0.065)
Involvement in economic
activities
0.071
(0.040)* 0.022
(0.013)* 0.076
(0.032)*** -0.084
(0.102)
0.199
(0.068)***
Individual Characteristics
Age2:20-29 group -0.193
(0.056)*** -0.059
(0.017)*** -0.043
(0.039)
0.405
(0.160)***
-0.236
(0.090)***
Age3: 30-39 group -0.339
(0.070)*** -0.104
(0.021)*** -0.095
(0.052)* 0.678
(0.188)***
-0.444
(0.119)***
Age4: 40-49 group -0.552
(0.130)*** -0.165
(0.037)*** -0.382
(0.119)*** 0.817
(0.330)***
-1.155
(0.272)***
Pregnancy wanted 0.073
(0.042)* 0.022
(0.013)* -0.010
(0.033)
-0.146
(0.108)
0.028
(0.071)
Birth in last 5 years -0.160
(0.044)*** -0.049
(0.013)*** -0.060
(0.036)* 0.289
(0.105)***
-0.232
(0.086)***
Age at first birth 0.023 (0.007)*** 0.007
(0.002)*** 0.014
(0.005)***
-0.027
(0.017)
0.041
(0.010)***
HH characteristics
Wealth index2 0.140 (0.053)*** 0.043
(0.016)*** -0.018
(0.047)
-0.343
(0.138)***
0.080
(0.096)
Wealth index3 0.350 (0.063)*** 0.107
(0.019)*** 0.063
(0.050)
-0.835
(0.190)***
0.423
(0.107)***
Wealth index4 0.728 (0.085)*** 0.213
(0.022)*** 0.260
(0.056)*** -1.776
(0.346)***
1.140
(0.149)***
Spouse education 0.022 (0.006)*** 0.007
(0.002)*** 0.019
(0.004)*** -0.029
(0.016)*
0.052
(0.010)***
Agri. being spouse
occupation
-0.10
(0.043)** -0.031
(0.013)** -0.070
(0.040)* 0.123
(0.111)
-0.198
(0.084)**
TV/Radio 0.079
(0.049)* 0.024
(0.015)* 0.067
(0.035)** -0.075
(0.140)
0.176
(0.077)**
Muslim -0.161
(0.064)*** -0.050
(0.019)*** -0.105
(0.042)*** 0.272
(0.172)
-0.328
(0.104)***
Geographic location
Town 0.180 (0.054)*** 0.055
(0.017)*** 0.144
(0.035)*** -0.302
(0.152)**
0.425
(0.085)***
City 0.218 (0.090)*** 0.067
(0.027)*** 0.247
(0.041)*** -0.203
(0.265)
0.626
(0.125)***
Wald Statistics 996.32 870.74
Vuong Test
14.9
(0.000)
Sample 7307 7318
Notes: Robust standard errors are reported in the parenthesis ***, ** and * denote that coefficient/marginal effects are significant at 1%, 5% and 10% level of
significant respectively
121
instance, if a respondent belongs to a Muslim family she is expected to visit less for
antenatal care as Muslim women in general are more conservative. The marginal effects
of two dummy variables (town and city) are positive and their impact increases
successively, suggesting that respondents living in towns are likely to make more visits
compared to those who live in country sides. Similarly, respondents living in cities are
likely to have more visits compared to their counterparts who live in towns.
SUMMARY AND POLICY IMPLICATIONS
Bangladesh has achieved a remarkable success in health, evidenced by the fall in
maternal and infant mortalities and the rise in life expectancy. Antenatal care plays a key
role in reducing maternal and infant mortalities in Bangladesh. This study examines the
role of women empowerment in the utilization of antenatal care in Bangladesh using the
2011 Bangladesh Demographic and Health Survey (BDHS) – a nationally representative
survey sample. Following Duflo (2012) and using rotating factor analysis technique, four
dimensions of women empowerment have been constructed to examine their effects on
antenatal care utilization. They are (i) women’s highest level of education; (ii) decision
making power in the household; (iii) freedom of choice and movement; and (iv)
involvement in economic activities. Hypotheses have been tested to determine if these
dimensions of women empowerment contribute to the utilization of antenatal care in
Bangladesh.
The probit and the zero-inflated negative binomial regression models are
specified to see if women empowerment along with other variables plays any significant
role in the utilization of antenatal care. The probit model is used to determine factors
affecting the decision of receiving antenatal care, whereas the zero-inflated negative
binomial regression model is employed to determine the intensity of receiving such cares.
The intensity of care is measured by the frequency of receiving antenatal care.
The data fit both models very well. All explanatory variables in both models
meet our prior expectations. The results show that each dimension of the women
empowerment contributes positively to both the decision and frequency of using
antenatal care in Bangladesh. Of four dimensions, women education is found as the most
dominating factor in the utilization of antenatal care. This finding suggests that with an
increase in the level of empowerment through higher level of education, the likelihood of
antenatal care utilization increases substantially. The other three dimensions of
empowerment also contribute to the utilization of antenatal care positively.
Other important factors affecting the utilization of antenatal care are economic
condition (measured by wealth), spouse’s level of education, age of the respondent,
religion, location of the household and access to TV/Radio. With the increase in the level
of wealth which enhance the affordability, utilization of antenatal care increases.
Spouse’s level of education helps to realize the need for antenatal care. Accordingly, the
utilization of antenatal care rises with the rise in the level of spouse’s level of education.
Location of the household determines the accessibility of the healthcare facilities. More
healthcare facilities are available in cities and towns compared to country sides, therefore
respondents living in cities and towns are utilizing more antenatal care than those who are
living in the country sides. Older women are utilizing relatively less antenatal care
compared to younger women. It is believed that the older women are more experienced
122
and they feel that they need less antenatal care provided by health professionals. Owning
TV/Radio provides information and exposures, which may enlighten the respondents to
utilize more antenatal care.
The study has number of policy implications for all developing countries like
Bangladesh. First, women empowerment is one of the key factors in the utilization of
antenatal care, which subsequently contributes to the improvement of health status. All
efforts should be made to increase the women empowerment, particularly the girls’
education. Increase in women involvement in economic activities increases women
empowerment. For a developing country like Bangladesh, scopes and opportunities for
women employment are limited. The experience from Bangladesh shows that microcredit
institutions, which not only provide credits to members but also provide access to
information, education and health services, play an important role in increasing women
involvement in the economic activities.
Secondly, poverty emerges as one of the foremost obstacles in the utilization of
antenatal care. Respondents belong to poorer households cannot afford enough antenatal
care. Poverty eradication policy should be pursued effectively. In the short-run, special
programs targeting the poorest segment of the community should be undertaken to
provide adequate antenatal care. Thirdly, the findings of the study show that there exists a
disparity between rural and urban areas in antenatal care services utilization. To address
this disparity, the resource allocation should be taken into account based on the regional
need and degree of inequality. Finally, the study shows that TV/Radio can influence the
utilization of antenatal care, particularly the frequency of antenatal visits. This suggests
that more educated and informative programs and/or advertisement should be
broadcasted through TV/Radio aiming the target groups.
ENDNOTES
1 An earlier version of the paper was presented at the AABSS (Australian Academy of Business
and Social Sciences) conference held in Kuala Lumpur, Malaysia, August 25-26, 2014
2 The Guardian (2013) “Global Development”, http://www.theguardian.com/global-
development/2013/nov/21/bangladesh-healthcare-poverty-lancet-study. November 21, 2013.
Retrieved on February 20, 2014
3 The Negative Binomial model can accommodate overdispersion but not underdsipersion with
respect to the Poission model.
4 The ZINB assumes there are two distinct data generation processes. The result of a Bernoulli trial
is used to determine which of the two processes is used. For observation i, with probability the
only possible response of the first process is zero counts, and with probability of ( ) the
response of the second process is governed by a negative binomial with mean, . The zero counts
are generated from, both the first and second processes, where a probability is estimated for
whether zero counts are from the first or the second process. The overall probability of zero counts
is the combined probability of zeros from the two processes.
123
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