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Does Mother’s education affect antenatal care visits in Bangladesh?
Result from 2007 Bangladesh Demographic and Health Survey (2007 BDHS)
Author: Md.Ruhul Kabir
Name of supervisor: Dr. Joacim Rocklöv
Department of Public Health and Clinical Medicine
Epidemiology and Global Health
Umeå University, Sweden
2012
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Acknowledgement
I would like to thank and show my gratitude to my supervisor Joacim Rocklöv for the
constructive guidance throughout the process, for fruitful discussions and helpful feedbacks
to the thesis.
I would also like to take the opportunity to thank Sabina Bergsten, Kjerstin Dahlblom and all
the teachers and administrative staffs for their support and assistance throughout the entire
program.
My sincere appreciation, gratitude and thanks are offered to my brother Mr.Sanjib Saha, PhD
student, Lund University, for his valuable suggestions, meticulous guidance of the thesis and
continuous support for my studies and stay in Sweden.
My heartfelt thanks goes to Hassan Al Mammon and Tasmia Islam for their continuing
inspiration and belief on me and making my stay memorable here in Umea. I would also like
to thank Koushik, Mahmud bhai, Masum bhai, Sham bhai and all my friends in Sweden for
their support and love. Moreover, I am delighted to acknowledge the contribution of some of
my friends (Masud, Saif, Tazul, Tamal, Mamun, Sajib, Shohag, Nasir and many more) in my
studies as well as in my life and would like to show my gratitude for their inspiration, love
and support they have provided me over the years.
Finally, I am grateful to my beloved parents and family members for their blessings,
motivation and support. Without their unconditional love and affection nothing would have
been possible. Anything I do which is meaningful, credit belongs to them.
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Abstract
Background
Bangladesh has achieved significant progress in the health sector in last few decades;
however, despite of recent progress, maternal mortality ratio (MMR) remains still one of the
highest in the world around 240 per 100,000 live births in 2010 according to WHO’2012.
Proper antenatal care (ANC) services can potentially reduce maternal morbidity and
mortality, acknowledged by the Millennium Development Goals Report 2012. Despite of the
importance of ANC in the reduction of maternal morbidity and mortality, utilization of ANC
services remains very low in Bangladesh and several factors contributing to the low
utilization of antenatal care. One such is women's education which may have effects on
health seeking behaviors, therefore, the study aimed to assess how maternal education
influences the number of ANC visits in Bangladesh by considering other socioeconomic
factors contributing to the association.
Methods and Materials
The 2007 Bangladesh Demographic and Health Survey (2007 BDHS) data were used for the
study, which is nationally representative. The study considered ever married women aged 15-
49 years who had at least one child in the last five years preceding the survey. A total of 6,150
women fulfilled study eligibility criteria and considered for analysis. To evaluate the effect of
mother’s education on number of antenatal care (ANC) visits, the outcome variable was
categorized into three groups where two groups were compared with the arbitrary reference
group. In addition to descriptive statistics, chi-square test was performed to test the
difference between groups. Univariate multinomial logistic regression was used to estimate
the effect of predictor variables on the outcome variable. To control for potential confounding
effects, multivariate multinomial logistic regression was used. Three models have been
established in multivariate analysis to assess the effect of potential confounding factors in the
association. Moreover, predicted probability of ANC visits in relation to mother’s education
was estimated from the logistic regression model. Multicollinearity was done to cancel out
collinearity and a sensitivity analysis was also performed to test the sensitivity of the result.
Result
The result revealed that around 60% of women received ANC at least once , but only 23.1% of
women made recommended (4 or more) number of visits for ANC. Moreover, less than 10%
of the illiterate mothers made recommended number of visits, whereas, around 40% of
mothers who had completed secondary or higher education made recommended number of
visits. The logistic regression analysis showed that mother’s education level was a strong
determinant for the number of ANC visits by mothers. Multivariate multinomial logistic
regression estimated that, in comparison with the mothers who made 4 or more visits, the
chances of having no ANC visit were almost 4 [OR= 4.21; 95% CI: 3.05-5.87] times higher for
illiterate mothers compared to the mothers who had secondary or higher education.
However, for mothers who had primary education, the likelihood of having no ANC visit was
around 2 [OR= 2.34; 95% CI: 1.84-2.99] times higher compared to the mothers with
secondary school or higher education level, after adjusting for other predictors considered for
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the study. In addition to mother’s education level, household wealth status, partner’s
education level, partner’s occupation level, area of residence & birth order were also found to
be significant determinants for the number of ANC visits in Bangladesh.
Conclusion
The study characterized and estimated that maternal education had strong influence on the
utilization of antenatal care service; therefore, emphasis should be given more on educating
women in addition to improving maternal health care services. By considering the necessity
of having ANC service which provides interventions and information during pregnancy
government should act deliberately to address the factors responsible for the low utilization
of ANC service in Bangladesh.
Key words: Antenal care, maternal mortality, women's education, Bangladesh.
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Abbreviations and acronyms
AIDS Acquired Immune Deficiency Virus
ANC Antenatal care
BDHS Bangladesh Demographic and Health Survey
DHS Demographic and Health survey
EmOC Emergency Obstetric Care
EA Enumeration Area
FSSAP Female Secondary School Assistance Project
GNI Gross National Income
HDI Human Development Index
HH Household
HIV Human Immunodeficiency Virus
HPNSDP Health, Population and Nutrition Sector Development Program
MDG 5 Millennium Development Goal 5 (Improving maternal health)
MMR Maternal Mortality Ratio
MNCH Maternal, Nutrition and Child Health Care
MOHFW Ministry of Health and Family Welfare
NGO Non Government Organization
NIPORT National Institute for Population Research and Training
UHC Upazila (sub-district) Health Complex
UNESCO United Nations Educational, Scientific and Cultural Organizations
UNICEF United Nations Children’s Fund
USAID U.S. Agency for International Development
VS. Versus
WHO World Health Organization
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Content
Acknowledgement .......................................................................................................................ii
Abstract ......................................................................................................................................iii
Abbreviations ..............................................................................................................................v
Content .......................................................................................................................................vi
Introduction..........................................................................................................................….....1
Maternal mortality overview …………………………….………………………….……………..........1
Antenatal care (ANC)......................................................................................................2
Importance of mother’s education on ANC......................... …………………….……………..4
Bangladesh Overview ...…………………………………….……………………………………………….4
Maternal health care service in Bangladesh ............................................…...................6
Antenatal care service in Bangladesh .............................................................................8
Women education in Bangladesh ...................................................................................8
Research question......................................................................................................................10
Aims.............................................................................................................................................11
Methodology...............................................................................................................................12
Data source................................................................................................................12
Demographic and Health Surveys (DHS).....................................................12
Bangladesh Demographic and Health Survey 2007 (2007 BDHS)..............12
Study design ..........................…………………………………………………..…………………….13
Data processing ….......................................................................................................13
Variables of the study ................................................................................................15
Dependant variable........…................…………….…… ……………………………….15
Independent variables…………………...............…………………….………………….15
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Data analysis...............................................................................................................17
Multinomial logistic regression.............……………………..…………………………18
Sensitivity analysis.....................................................................….................19
Multicollinearity ............................................................................................19
Results…..……………………………………………………………….………………………………………….……...20
Background characteristics of study population..................................................20
Antenatal care visit according to background characteristics….................……….22
Univariate multinomial logistic regression………............................………………….24
Effect of mother’s education on ANC visit.......................…………………...24
Effect of other factors on ANC visit.........................................................24
Multivariate multinomial logistic regression........................................................26
Result of calculation of predicted probability of ANC visit……….……...........…….28
Sensitivity analysis................................................................….............................30
Discussion ..................................................................................................................................31
Policy implications ....................................................................................................................34
Conclusion .................................................................................................................................35
References .................................................................................................................................36
Appendix ...................................................................................................................................40
Appendix I: ANC visits according to background variables including missing
values..........................................................................................................................................41
Appendix II: Sensitivity Analysis...............................................................................................42
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List of tables
Table 1: Important statistics for Bangladesh………………………………………………….……………......6
Table2: Maternal health care facilities in Bangladesh.................................................................7
Table 3: Dependant variable.......................................................................................................15
Table 4: Independent variables……………………………………….......……………………………….……...16
Table 5: Background characteristics of study population.........................................................21
Table 6: ANC visit according to background characteristics....................................................23
Table 8: Univariate multinomial logistic regression of ANC visits according to different
variables.....................................................................................................................................25
Table 9: Multivariate multinomial logistic regression of ANC visits........................................27
List of figures
Figure 1: Location of Bangladesh in world map..........................................................................5
Figure 2: Flowchart of data generation process.......................................................................14
Figure 3: Predicted probability of use of ANC services in relation to mother’s education......30
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Introduction
Maternal mortality overview
Maternal mortality still remains as a major burden in many developing countries though
significant progress has been made globally in the last two decades (1). According to
WHO’2012, around 287,000 maternal deaths occurred in 2010 globally at a staggering rate
of around 210 deaths per 100,000 live births. Though MMR declined from 400 to 210 per
100,000 live births between 1990 and 2010, however, the figure remains unacceptably high.
Moreover, Sub-Saharan Africa and Sothern Asia account for more than 85% of all maternal
deaths where half of the deaths occur in Africa and one third in Southern Asia (2).
The risk of maternal death is about 15 times lower in developed countries in comparison
with developing countries. In Southern Asia, MMR was around 220 per 100,000 live births
in 2010 though maternal deaths declined around 64% between 1990 and 2010. The lifetime
risk of maternal deaths in Southern Asia is almost 1 in 160, whereas, in developed countries
the figure is around 1 in 3800 women (2). As the fifth MDG targets to improve maternal
health and reduce maternal death by three quarters between 1990 and 2015, it requires 5.5%
annual decline from 1990 to reach the target in 2015 [4]. For Southern Asia MMR declined
4.9% annually between 1990 and 2010 which means South Asia is making progress (2).
Complications during pregnancy, childbirth or the six weeks following delivery are the major
causes of maternal death around the world. WHO defines maternal death as (3):
“The death of a woman while pregnant or within 42 days of termination of pregnancy,
irrespective of the duration and site of the pregnancy, from any cause related to or aggravated
by the pregnancy or its management but not from accidental or incidental causes.”
Maternal deaths could happen from direct or indirect causes. Direct obstetric complications
like obstetric hemorrhage, infections, eclampsia, prolonged or obstructed labour and unsafe
abortion followed by indirect causes like anemia, malaria and HIV aggravate the hemorrhagic
condition further (4). However, according to The Millennium Development Goals report of
2011, the vast majority of maternal deaths are avoidable (1) and many health problems
among pregnant women are preventable, detectable or treatable through visits with trained
health workers before child birth. Reproductive health care services, antenatal care, skilled
health workers assisting at birth and access to emergency obstetric care can reduce
complications and deaths (5). Although maternal mortality still remains a major challenge,
effective interventions have been applied in different regions of the world to prevent
disabilities and avoidable maternal deaths (2). All the deaths occur during pregnancy or child
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birth intensified the importance of having health care service during pregnancy and delivery
period through which maternal morbidity and mortality can be minimized to a great extent
(13).
Antenatal care
“Antenatal care (ANC) means “care before birth”, and includes education, counselling,
screening and treatment to monitor and to promote the well-being of the mother and foetus”
(6).
Antenatal care provides preventive interventions and information which are vital for
detecting and managing complications during pregnancy and childbirth (1). According to
The Millennium Development Goals report of 2012, ANC is an important intervention which
can reduce maternal morbidity and mortality (11). ANC aims to provide regular medical and
nursing care during pregnancy by the medically trained health care providers. It includes
providing health information about pregnancy complications and dangerous sign, symptoms
and risks of labour and delivery, importance of seeking medical care and deliver with the
assistance of skilled health care provider etc. (7). In addition, reduction of adverse health
outcomes like preterm birth, low birth weight and small for gestational age has been
associated with ANC (8). Safe delivery can be attributed by ANC (9) as interventions
provided through ANC can help women to recognize and react to signs and symptoms which
can lead them to potential adverse conditions (10).
ANC also provides information about fetal growth and development and its relationship to
the mother’s health and promotes healthy lifestyle. Immunization, malaria and sexually
transmitted infection prevention and treatment, management of anemia etc. can significantly
improve maternal health and fetal outcomes and ANC can contribute to ensure this (6,7).
According to The Millennium Development Goals report of 2011, the percentage of women
receiving ANC from skilled health care personnel has increased significantly in the last two
decades. The percentage of women made at least one ANC visit increased from 64% in 1990
to 81% in 2009 across all developing regions. In Southern Asia the percentage of women that
made at least one ANC visit increased from 51% in 1990 to 70% in 2009, lowest among all
regions (1). In 2005, ANC utilization in the developing countries was low (65%) compared to
developed countries (97%) (12). Insufficient ANC and lack of utilization of maternal health
services during pregnancy and delivery could turn into potential risk factors for maternal
mortality (13, 14). However, it has already been recognized that the presence of medically
trained health care provider during delivery reduces the risk of maternal mortality (15, 16).
Moreover, ANC has a large effect on ensuring professional assistance at delivery, especially
for increasing institutional delivery (17).
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The effectiveness of ANC mostly depends on the continuation of the receiving care from first
trimester to throughout pregnancy according to the standards of periodicity. ANC has the
potential to reduce the morbidity and mortality as it focuses on identifying complications and
treating them in addition to addressing behavioral factors (18). The activities which comprise
the basic components of ANC includes: screening and treatment of health issues, providing
beneficial therapeutic interventions and educating pregnant women to plan for safe birth and
potential crisis which may arise during pregnancy and delivery and the best possible way to
tackle them (19).
By reviewing the effectiveness of different models of ANC, WHO recommends minimum four
antenatal visits for the uncomplicated pregnancies (routine ANC) and more visits for
complicated cases (special care) based on requirement. However, because of the differences
in training of health care professionals in different countries and difficulties of standardizing
the definition of skilled providers it is recommended to visit at least once to the medically
trained providers (doctor, nurse, midwife etc.) and four or more visits to any providers (
medically or non-medically trained) . Recommended number of ANC visits increase the
likelihood of receiving effective maternal health interventions as receiving ANC doesn’t
always guarantee the receipt of effective ANC (20). Therefore, WHO guidelines are important
to follow as it specified the timing and content of ANC according to gestational age. The
guidelines focused on the issue that the examinations and tests which are beneficial and have
immediate purpose should be performed which includes: routine weight and height
measurement (optional), blood measurement, tetanus immunization, screening and
management (prevention and treatment) of malaria, anemia, sexually transmitted diseases,
syphilis and urinary tract infections like bacteriuria & proteinuria in addition to necessary
advices required (7,19). Moreover, ANC services also provides important health messages
about personal hygiene, importance of having balanced diet, eating nutritious food, infant
and newborn care, breastfeeding practice, family planning overall provides education on how
to take care of herself. It also provides knowledge to the husband and other family members
of the family about their responsibilities and how to support mothers psychologically during
the critical period of time.
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Importance of mother’s education on ANC service
Maternal morbidity and mortality has reduced significantly in developed countries in last few
decades, however, the situation is different in developing regions of the world where most of
the death occurs (61). According to a worldwide survey study, maternal mortality rate tend to
be higher in countries where female literacy rate is lower than their male counterparts. The
study also revealed women's education as a moderately powerful indicator of maternal
mortality and women's education can provide the knowledge to demand and seek proper
health care important to negate complications (21). Woman’s health seeking behaviors is
highly influenced by her education status and preventive health care services are used to a
greater extent by mothers with higher education than their less educated counterparts.
Moreover, the influence of maternal education persists even after controlling the effect of
other socioeconomic factors (22). Education increases awareness of causes and deleterious
effects of bad health which in turn increases the demand and utilization of health care (23).
Several studies have explored that higher educational attainment of both women and their
husbands had positive influences on the utilization of ANC (24, 25, 26).
Improved educational status of women may help them to empower and improve their ability
to manipulate their surroundings as well as to have control over their own health. Education
may also help them to have economic power, decrease feeling of shyness for childbirth,
expanded support and communication with husband and other family members which all
can contribute in increased number of ANC visits. Moreover, education can minimize the
effect of distance to health care centers and time to reach their as educated mothers
prioritizes her own and babies health and safety first (27). Several other studies also support
that women's autonomy and decision making power over their own health influences the
utilization of ANC services and education can help them to overcome these limitations (28,
29). A study in India performed to find out the relation between maternal eduction and
maternal health care utilization recommended that in a setting where illiteracy is high,
improving access to health facilities should go hand in hand with educating women as female
education have an impact on factors that reduce maternal mortality (22).
Bangladesh overview
Bangladesh is a densely populated country located in South Asia (Figure 1), has land area of
around 147,570 square km. The religion for the majority of the people is Islam (around 90%)
and the rest of the people is hindu, Christian or others. Bangladesh got independence in 1971
from Pakistan and the mother tongue is Bangla.
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Figure 1: Location of Bangladesh in the world map.
(Source:http://www.mapsofworld.com/bangladesh/bangladesh-location-map.html)
Bangladesh is a parliamentary democratic country. Bangladesh has a tropical monsoon
climate with frequent visit of natural calamities like flood, cyclones, river erosions,
landslides, droughts etc. (31).
The economy of the country is mainly based on agriculture production and around 72% of
people lives in rural areas. According to the 2011 Human Development Report, Bangladesh
falls in the low human development category ranked 146th among 187 countries. Human
Development Index (HDI) measures human development by considering a long and healthy
life, access to knowledge and a decent standard of living. Bangladesh’s HDI value increased
from 0.30 in 1980 to 0.50 in 2011 (Table 1), almost 65% increase at an average annual
increase of 1.6% (32). More than 80% of people live below $2 a day (38) which shows the
overspreading gulp of poverty across the country. Despite of relentless effort from
government and other development organizations, adult literacy rate is still revolving around
50-60% though situation is improving day by day. Government spends around 2.2% of total
GDP in the education sector in 2010 and around 3.4% of total GDP in the health sector where
only 3 physicians are available per 10,000 people. The percentage of nurses and midwives are
even lower, representing the scarcity of medically trained providers across the country.
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Table1 : Important socio-demographic statistics for Bangladesh
Indicators Statistics
Location South Asia
Total population (thousands) (2010)˟ 148,692
Total fertility rate (births per women) (2009) ˟ 2.3
Population living in rural areas (%) ˟ (2010) 72%
Life expectancy at birth (years) (2009) ˟ 68, Male:66, Female:71
Adult literacy rate˟˟ (2010) 56, Male:62, Female:52
Poverty (% of pop.on less than $2 a day) (2005) ˟ 81
Gross National Income (GNI) per capita (PPP int. $)˟ 1810
Human Development Index (HDI) (2011)˟ ˟˟ 0.5 (Low human development)
Public expenditure on education (2010) ˟
As % of GDP
As % of total government expenditure
2.2
14.1
Total expenditure on health as % of GDP (2009) ˟˟ 3.4
Health workforce Per 10,000˟˟ (2010)
Physicians
Nurses & midwives
3
2.7
MMR (per 100, 000 live births) ˟˟ (2010) 240
˟Reference 35, ˟˟ Reference 38, ˟˟˟ Reference 32
Bangladesh is a least developed country facing daunting challenge of development issues like
deep-ridden poverty and hunger, increasing social and economic disparities etc. followed by
man made and natural calamities like political unrest, natural disasters etc (31). In spite of
these challenges, Bangladesh has made good progress in achieving MDG2, MDG4 and MDG5
thanks to the contribution of different NGO’s and developmental organizations for helping
government to some extent.
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Maternal health care service in Bangladesh
According to WHO, the progress towards improving maternal health is “on tract” for
Bangladesh for achieving MDG 5 within stipulated period as between 1990 and 2010 MMR
declined from 800 to 240/100,000 live births i.e. 5.9% annually. The lifetime risk of
maternal death is still staggering though, 1 in 172 despite of progressive success (2).
The ministry of Health and Family Welfare (MOHFW) is responsible for providing maternal
health care in Bangladesh as most of the health infrastructure and health service system are
controlled by the Government. To accelerate progress in the reduction of MMR, MOHFW has
undertaken Health, Population and Nutrition Sector Development Program (HPNSDP) for a
period of five years from 2011 to 2016 and more emphasis has given for strengthening
maternal health service delivery. In addition to various targets, the program aims to expand
the access and quality of maternal, nutrition and child health care (MNCH) services focusing
on ANC, assisted delivery, postnatal and neonatal health care (33). The government provides
maternal health care services in primary, secondary and tertiary level (Table 2). The primary
health care services deliver services in three tiers: upazila, union and the community with
linkages to the district.
Table 2 : Maternal health care facilities in Bangladesh
Level of care Administrative unit Health care facility
Primary level Upazila Upazila health complex (UHC)
Union Union health and family welfare
centers (UHFWC)
Ward Community clinics (CCs)
Secondary level District District hospital, Maternal and
child welfare centers (MCWCs)
Tertiary level Division or national/capital Divisional level hospitals,
medical college hospitals,
specialized hospitals.
Source: Ministry of Health and Family Welfare, Bangladesh
The Upazila health complex (UHC) is the first inpatient facility in the network that works at
sub district level (30-50 beds) and delivers primary as well as secondary level of services.
Emergency obstetric care (EmOC) provided here by medical doctors, nurses and family
welfare assistant (FWA). UHFWC provides maternal health care services (with or without
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beds) and it has few sub-centers at the lowest administrative level with field facilities. At the
field level, health assistants, family welfare assistants and community skilled birth attendants
provide preventive health care services. The CCs, a new concept not fully applied yet, in
primary level will represent the first entry and contact point to the health referral system and
patients would be referred from there according to the condition. Districts hospitals (50-150
beds) and maternal child welfare center (10-20 beds) provide care at secondary level.
Divisional level hospitals, medical college hospitals and specialized hospitals deliver maternal
care at tertiary level (33). District hospitals and UHC are supposed to provide 24-hour EmOC
services, however, due to lack of trained personnel and other supporting facilities many
hospitals are not providing 24-hr EmOC services. As Bangladesh is densely populated and
lack of trained personnel, inaccessibility of quality services in government facilities in
different administrative levels, mothers are sometimes forced to go for expensive private
services. Besides the public sector, many private hospitals and non-government
organizations (NGOs) are providing maternal health care services in Bangladesh. NGO’s
mostly provide primary health care services both in rural and urban areas.
Antenatal care service in Bangladesh
Antenatal care services are provided in all the three administrative levels in Bangladesh. At
primary level ANC services are delivered free of charges, however, in hospital level, a small
amount of user fees are applied (generally around 10-20 BDT, $0.1-$ 0.2). Though ANC and
emergency obstetric care (EmOC) are normally free of charge, hence, sometimes families
have to pay a considerable amount of out-of-pocket money to get the service on time (60).
Antenatal care visit by mothers are very low in Bangladesh even in comparison with other
developing countries in the world. The proportion of women attended by professional health
care personnel at least once during pregnancy was 81% in 2009 (1) in all developing regions
in the world, whereas, in Bangladesh only 55% women were attended by professionals in
2011 (34). The proportion of women attended by health professionals at least once during
pregnancy has increased from 52% in 2007(36) to 55% in 2011(34). However, only 23% of
mothers made the recommended number of visits i.e. 4 or more times to the ANC providers
in 2010 where the regional (South-East Asia) average was 52% (35). According to 2007
BDHS report, the likelihood of receiving ANC from medically trained providers increases
with mothers education and household wealth. The urban-rural differentials in ANC coverage
were also large, only 46% of rural women received ANC compared with 71% urban women. A
majority of women who have not received ANC responded that ANC was not needed, many of
them don’t know about benefit of receiving ANC and some of them replied service was
expensive, health care center too far, religious regions or they did not have permission to
leave house (36).
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Women's education in Bangladesh
The present education system in Bangladesh is divided into primary, secondary and
higher/tertiary education. Primary education comprised of 5 years of formal schooling (class
1-5), secondary education comprised of 7 years of schooling where first 3 years referred as
junior secondary and next 2 years as secondary and final 2 years as higher secondary. Higher
secondary education is then followed by college/university level education (37). In addition
to the general education system, there are madrasah and technical-vocational education
system as well. Primary education is free for all and compulsory, however, Government has
initiated Female Secondary School Assistance Project (FSSAP) with The World Bank to
support female education up to completion of secondary level. The project aims to promote
female education by reducing gender disparities in secondary level which will enable them to
contribute in the economic and social development of the country. The projects support
female education by providing a stipend and tuition fees in addition to improving quality of
education and management. In 2010, according to UNESCO, female literacy rate was about
52%, whereas, male literacy rate was about 62%. However, encouraging news is that youth
(15-24) literacy rate for female was about 79% compared to male literacy rate which was 76%
(38). Apart from that many NGOs and development organizations are working to promote
female literacy in Bangladesh. However, despite of efforts the secondary school enrollment
ratio (net) for female was around 43% in secondary level which was almost 93% in primary
level in 2010 (39).
Education is very important for the empowerment of women and an important tool for
achieving equality in the society. Bangladesh has made significant progress in accessing
primary education in recent years. Though gender parity has improved in primary and lower
secondary schooling, however, large disparities still exists in the upper level of secondary
schooling as well as in higher education. It could be because of gender based budgetary
initiatives has not been considered yet in higher education level resulting in high drop out
rate (40). Moreover, the culture, tradition, religion, common mentality, perception of lesser
value and limited roles of women, lack of female teachers, unfriendly school environment,
and violence against women, limited options and gender based division of work in the
household are among the reasons hinders the education of women in Bangladesh.
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Research question
Bangladesh is experiencing one of the highest MMR in the world despite of recent progress.
As per MDG 5 which targets reduction of MMR by 75% between 1990 and 2015, Bangladesh
is still struggling to reduce the MMR below the danger level. Complications during pregnancy
and delivery not attended by skilled health professional are important reasons for the
maternal mortality in developing countries (41) like Bangladesh. Utilization of maternal
health care services and recommended number of ANC visits to skilled health care personnel
is still very low. Though Government, NGO’s and different international organizations trying
hard to reduce MMR, satisfactory decline in MMR still far away. Therefore, it is time to look
at the fundamental causes of high MMR and work on these issues more. Emphasis should be
given more on women's education as educated women understand the importance of seeking
health care services during pregnancy period. ANC can play a major part as it is regarded as
an important component of maternal health care (42). ANC services contribute indirectly to
mothers and baby's survival as it helps to detect and treat pregnancy and delivery related
complications and provide important health messages to women and their families (41,43,
44). ANC can ensure the presence of skilled birth attendance during delivery (16) important
for survival of mothers and infant. However, realization of the importance of seeking ANC
varies according to the educational status of mothers. Educated mothers may be well aware
about their health during the critical pregnancy and delivery period, seek for the medical
assistance more frequently and earlier than their non-educated counterparts (30). Therefore,
the present study aims to know, “Does mother’s education affects antenatal care visits in
Bangladesh?
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Aims
The aim of the thesis was to evaluate the effect of mother’s education on antenatal care
(ANC) visits in Bangladesh. The specific aims were:
To describe current ANC practices by women during pregnancy.
To study if there was any difference in ANC visit with respect to women’s education.
To estimate the extent of contribution mother’s education have on the utilization of ANC
services after adjusting for potential confounding factors.
To study other sociodemographic factors associated with ANC visit beside education.
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Methodology
Data source
Demographic and Health Surveys (DHS)
Demographic and Health Surveys (DHS) are nationally-representative household surveys
typically conducted about every 5 years (Standard DHS Surveys) in many countries. It
provides data for a wide range of monitoring and impact evaluation indicators in the area of
population, health and nutrition to allow comparisons over time. DHS has worldwide
reputation for collecting and disseminating nationally representative and accurate data on
fertility, family planning, maternal and child health, gender, HIV/AIDS, malaria and
nutrition. Standard DHS Surveys generally have large sample size (usually between 5,000 to
30,000 households). The Measure DHS project is funded by the U.S. Agency for
International Development (USAID) with contribution from other interested donors and
participating countries. The aim of the measure DHS is to institutionalize the appropriate
collection and use of data by host countries to use in policy formation, program planning as
well as for monitoring and evaluation (45).
Bangladesh Demographic Health Survey 2007 (2007 BDHS)
The data used for this report was obtained from Bangladesh Demographic and Health Survey
2007 (2007 BDHS). The 2007 BDHS survey was conducted under the authority of the
National Institute for Population Research and Training (NIPORT) of the Ministry of Health
and Family Welfare, Government of the People’s Republic of Bangladesh. It was the fifth
nationally representative sample survey designed to provide information on basic national
indicators of social progress which includes fertility, childhood mortality, contraceptive
knowledge and use, maternal and child health, nutritional status of mothers and children,
awareness of AIDS, and domestic violence. The main objective of this periodic survey is to
serve population and health data for policy makers, program managers, and the research
community as well as monitor the progress in those sectors (36).
The sample was collected from six administrative divisions: Barisal, Chittagong, Dhaka,
Khulna, Rajshahi and Sylhet. These divisions are further subdivided into zilas (district) and
each zilas into upazilas (sub-district). About 100 households from an upazila (sub-district)
were considered as enumeration areas (EA). These EAs were used as the primary sampling
units (PSUs) for the survey. The 2007 BDHS survey was based on two-staged stratified &
clustered sample of households. In the first stage, 361 PSUs (227 rural PSUs and 134 urban
PSUs) were selected and all the households from PSUs were listed. In the second stage, 30
- 13 -
households were selected from the list by using equal probability systematic sampling
technique. This leads to 30 households in each PSU, on average, resulting in 10,819
households in the sample. Of the 10, 819 HH, interview was successfully completed in 10,400
HH which comprised 10,996 ever married women aged 15-49 years and 3,771 men aged 15-54
years (36).
All these individuals were interviewed by well-trained staffs using structured and validated
questionnaires. Information was collected about background characteristics of all the family
members including age, residential history, education, religion, marital status, employment
status, reproductive history, family planning, antenatal, delivery, postnatal, newborn care,
breastfeeding practices, vaccinations, childhood illness, awareness of AIDS, knowledge of
tuberculosis, domestic violence etc. To obtain and get access to DHS data one has to submit
request to DHS MACRO, citing the purpose of accessing the data set. To perform the present
study maternal, infant and household data in spss format were accessed from Measure DHS
(Demographic and Health Surveys) website after getting proper permission.
Study design
The 2007 Bangladesh Demographic and Health Survey (2007 BDHS) data were used for
analysis. The study was limited to the ever married women aged 15-49 years who had at least
one birth in the last five years preceding the survey. If the woman had more than one child in
the last five years prior to the interview, information about the most recent live birth was
considered. To investigate the association between antenatal care (ANC) visit and mother’s
education level, socioeconomic and demographic characteristics was analyzed.
Data Processing
A total of 6150 women fulfilled the study eligibility criteria and considered for analysis
(Figure 2). The final data set consist information about mother’s antenatal care visits,
maternal characteristics ( mother’s age at conception, educational level), partner’s
characteristics (partner’s occupation and education level), household characteristics (
household wealth status) and community characteristics ( area of residence, religion) etc.
- 14 -
A flowchart featuring the data generation process has given below:
Interview completed
Interview: Women Interview: Men
Fulfilled study eligibility criteria
Data preparation for analysis
Figure 2: Flowchart of data generation process
Total 10,819 Household (HH)
Interview: 10,400 HH
10,996 ever married
women aged 15-49 years
3,771 men aged 15-54
years
6,150 women who had at least one
child last five years preceding the
survey
Total 6,150 women considered for
analysis
- 15 -
Variables of the study
Dependent variable
As the purpose of the study was to evaluate the effect of mother’s education on ANCl visits,
the outcome variable was number of antenatal care (ANC) visits (Table 3). Mothers who
visited any ANC provider (medically trained or non-medically trained) was considered to
have received ANC. Medically trained providers include qualified doctor, nurse, midwife,
paramedic, family welfare visitor (FWV), community skilled birth attendant (CSBA), medical
assistant (MA), or sub-assistant community medical officer (SACMO) and non-medically
trained providers include health assistant (HA), family welfare assistant (FWA), trained and
untrained birth attendants and other providers. Traditional birth attendants and other
practitioners have not been considered as skilled providers because they are not part of the
formal health care system (7). The number of antenatal visits was categorized into three
groups:0, 1-3 and ≥4 (Table 3). The reason for selecting three categories was that women who
visited for ANC would generally get more benefit compared to the women who never visited.
Though WHO recommends 4 or more antenatal visits, therefore, it assumes to be optimal.
Whereas, women who visited 1-3 times may get some benefit than women who never visited
for antenatal care.
Table 3: Dependant variable
Variable Definition Measurement
Antenatal care
(ANC)visits
Woman who visited/consulted
ANC providers during pregnancy
period was considered to have
used antenatal care.
Categorized into three groups: No
ANC visit, ANC visit 1-3 times,
ANC visit ≥4 times
Independent variables
The main independent variable in the study was mother’s level of education. Primary
education completion is defined as completing grade 5 and secondary school completion is
defined as grade 10. Other independent variables were place of the residence of the mothers,
education and occupational status of their partners, wealth index, birth order and age of the
mother’s at conception and religion (Table 4).
- 16 -
Table 4: Independent variables
Variables Definition Measurement
Mother’s
education level
Highest education level attained by
mother
Categorized into three groups: no education;
primary education; and secondary education or
higher education. Secondary and higher
education was merged together because of very
few cases of higher educated mothers.
Place of
residence
Place of residence of the women at
the time of the interview
Dichotomous variable in nominal scale and
categories were rural and urban.
Partner’s
education level
Highest education level attained by
partner/husband
Categorized into four groups: no education;
primary; secondary and higher.
Partner’s
occupation
level
Occupation of the partner Categorized into three groups: day laborer
(landowners, farmers, agricultural workers,
fishermen, poultry, cattle raising, home based
manufacturing, rickshaw pullers, brick-breakers,
domestic servants, factory workers, semi skilled
labor, unemployed, student), professional and
business (Small and large).
Wealth index The wealth index was constructed
by BDHS from data on household
assets, including ownership of
durable goods (such as televisions
and bicycles) and dwelling
characteristics (such as source of
drinking water, sanitation facilities,
and construction materials) (36).
Categorized into five quintiles by BDHS: poorest,
poorer, middle, richer and richest.
Birth Order Rank of the child Categorized into three groups: Birth order 1, 2-3
and ≥4.
Mother’s age at
conception
Mother’s age at conception =
(Mothers current age- age of last
child) – 1
Categorized into three groups: mother’s age <20
years, 20-34 years and 35-49 years.
Religion Religion Categorized into two groups: Islam and others
- 17 -
Data analysis
The data were analyzed using the statistical software SPSS version 20. For descriptive
statistics of categorical data, frequency distribution and percentages were used to describe
the data. In descriptive analysis, frequency and percent distributions of different variables
and associations with ANC visits were also calculated. It allowed to find out ANC practice by
mothers as well as the educational status of women in Bangladesh. To find out if there was
any significant difference in ANC visit with respect to women’s education, chi-square test was
performed.
As the outcome variable had three unordered categories (0, 1-3 and ≥4 ANC visits),
multinomial logistic regression was used to assess the effect of mothers' education on ANC
visit. Four or more ANC visits (≥4) were chosen as a reference group for comparison. Two
comparisons were possible: 1) ≥4 ANC visits vs. no ANC visit; and 2) ≥4 ANC visits vs. 1-3
ANC visits. Moreover, mother’s education (independent variable) was also categorized into
three groups. For this variable the last category (secondary or higher education) was
considered also as the reference category.
Univariate logistic regression analysis was performed to estimate the association between
independent variables and ANC visits in Bangladesh. Furthermore, to control the effect of
other predictor variables in the association of mother’s education level and ANC visits,
multivariate analysis was done. In multivariate analysis, three models were established to
control the effects of factors which may confound the association. The aim to generate three
models was to provide a clearer idea about how different factors influenced the association.
Multivariate multinomial logistic regression also allowed to calculate predicted probabilities
of ANC visits in Bangladesh in relation to the educational status of mothers while adjusting
for other factors.
Odds Ratios (OR) with 95% confidence interval was included in the table to estimate the
effect of the independent variable on the outcome variable and p-values less than 0.05 were
considered for statistical significance. Sensitivity analysis was done to test the sensitivity of
the result. Test of multicollinearity was also performed to cancel out numerical problems
arising from collinearity.
Dealing with missing values:
Regression analysis in SPSS does not consider missing cases in the analysis and excludes the
entire case from the analysis by default (list wise deletion of missing data). In the collected
data the outcome variable had almost 20% of missing cases, but fewer missing cases in the
- 18 -
independent variables. An analysis of the missing values was done and presented in
Appendix I. The percentage distribution of missing values in different categories was
analyzed using crosstabulations and Chi2-test.
Multinomial logistic regression
Multinomial logistic regression allows each category of an unordered response variable to be
compared to an arbitrary reference category providing a number of logistic regression
models. It is used when outcome variable has more than two categories which are unordered
and predictors are of any type: nominal, ordinal or interval/ratio (numeric). The multinomial
logistic regression model allows the effects of the explanatory variables to be assessed across
all the logit models and provides estimates of the overall significance (i.e., for all comparisons
rather than each individual comparison). A general multinomial logistic regression model is
shown in equation below (46):
Log Pr (Y=j)/Pr (Y= j′) = α + β1X1 + β2X2 + …. + βkXk
Where, where j is the identified response category and j' is the reference response category.
The model above provides estimates for the effect that each explanatory variable has on the
response. For example, a dependant variable (DV) has j categories and one category of DV is
designated as the reference category. The multinomial model generates j-1 sets of parameter
estimates, one for each category relative to the reference category, to explain the relationship
between the DV and the IVs. If for instance DV has three unordered categories (A,B &C), two
logit models should be computed; one comparing A with reference category C and one
comparing B with reference category C. The logit models will be (46):
Log Pr (Y=A)/Pr (Y= C) = α + β1X1 + β2X2 + …. + βkXk
Log Pr (Y=B)/Pr (Y= C) = α + β1X1 + β2X2 + …. + βkXk
- 19 -
Sensitivity analysis
Sensitivity analysis reveals how different values of a predictor variable will influence a certain
outcome variable under a given set of assumptions. It is often used to predict the outcome of
a decision if a situation turns out to be different compared to the key predictions. Sensitivity
analysis allows assessing the impact of changes of certain parameters will have on the
model’s conclusion (47). In the present study, sensitivity analysis was done to test the
variability in the association of mother’s education and ANC visit by excluding the data who
have responded distance to health care centers as the reason for not seeking ANC. As it was
related to the problem of accessing health care service, therefore, sensitivity analysis enabled
to estimate the difference of outcome by cancelling out the effect of distance of the health
care center on the association.
Multicollinearity
Multicollinearity happens when two or more of the covariates in a multiple regression are
highly correlated in the model. Multicollinearity leads to misleading results as the regression
coefficients could be biased due to multicollinearity . One way to compute multicollinearity
is by computing correlation between covariates of the model and if they seem highly
correlated then it is useful to remove the redundant variables which are not providing extra
useful information (59). However, the reliable ways to examine multicollinearity are
measuring variance inflation factors (VIF) or tolerance value. Tolerance value is the
proportion of variance in the independent variable that is not related to the other
independent variable in the model. So,
Tolerance = 1- Ri2
VIF = 1/1- Ri2, where Ri
2 is the proportion of variance in the ith independent variable that is
associated with other independent variables in the model. A VIF≥10 (tolerance ≤0.10)
indicates multicollinearity and VIF≥ 5 (tolerance ≤ 0.2) indicate possibilities of
multicollinearity (48). Variables which were considered in the analysis have not shown any
collinearity between them after checking correlations, VIF and tolerance value.
- 20 -
Results
Background characteristics of study population
Table 5 represents basic characteristics of the study population. According to the table, 37.8
% of mothers did not attend ANC, 39.1% made 1-3 visits and 23.1% made 4 or more visits.
Around 52% of women received ANC from medically trained providers at least once and 9.9%
received ANC care from non-medically trained providers. One out of four mothers were
illiterate (27.3%) and only around 40% of mothers had completed secondary or higher
education. However, if we consider partner’s education, it appeared that 34% had no
education and only 12% had higher education. Around half of the mothers were in the age
group of 20-34 years at conception and only 5.9% of mothers were in 35-49 years age group.
More than 65% of the mothers’ lived in rural areas and more than 40% (19.9+20.8) of
women were in the poorer and poorest wealth quintile group. Around 72% partners were day
laborer, only 4% were engaged in professional work and 22 % were engaged in business.
From the table it can be stated that, more than 30% of women were having their first child,
whereas, 40% of them were having their second or third child. More than 90% of the study
population were Muslims. More detailed account of missing values of different variables and
analysis has been attached to the Appendix I.
- 21 -
Table 5: Background characteristics of study population
Characteristics Number Valid Percent
Number of antenatal visits No ANC visit 1-3 visit ≥4 visits Missing
1861 1923 1136 1230
37.8 39.1 23.1
ANC visits according to providers ≥ 1 visit to medically trained providers ≥ 1 visit to non-medical providers Never visited to anyone Missing
2575 486 1861 1228
52.3 9.9 37.8
Mother’s education level No Primary Secondary or higher Missing
1676 1927 2544 3
27.3 31.3 41.4
Mother’s age (years) at conception <20 20-34 35-49 Missing
2455 3064 270 361
42.4 52.9 4.7
Area of residence Rural Urban
4043 2107
65.7 34.3
Wealth index Poorest Poorer Middle Richer Richest
1222 1282 1153 1146 1347
19.9 20.8 18.7 18.6 21.9
Partner’s education level No Primary Secondary Higher Missing
2094 1748 1570 731 7
34.1 28.5 25.5 11.9
Partner’s occupation level Day laborer Professional Business Missing
4444 252 1348 106
73.5 4.2 22.3
Birth order 1 2-3 4-5 6+
2033 2623 1016 472
33.2 42.7 16.5 7.6
Religion Islam Others Missing
5609 540 1
91.2 8.8
- 22 -
Antenatal care visits according to background characteristics
The table 6 depicts the number of times mother’s visited for antenatal care according to
background characteristics. It showed that, 62.1 % of illiterate mothers had never sought for
ANC, whereas, the percentages of receiving no ANC care for the women who completed
primary and secondary or higher education were 43.9% and 19.3% respectively. On the other
hand, only 30.8% mothers with no education made 1-3 visits, the percentage was 41.4% for
the mothers who completed secondary or higher education. According to the table, only 7.1%
of mothers with no education made recommended number of visits (i.e. 4 or more times),
however, 13.3% of mothers with primary education made 4 or more visits. A much better
condition was observed for mothers with secondary or higher education and around 40% of
mothers with secondary or higher education visited recommendation number of times for
ANC. The result showed that the percentages of receiving antenatal care increased with
mother’s education. The p-value (p<0.001) in chi-square test showed statistically significant
difference exists between different level of mothers' education and antenatal care visit.
On the other hand, only 15% of mothers living in rural areas made 4 or more visits, whereas,
38% mothers living in urban areas made recommended number of visits. The urban-rural
differentials seemed very large though the percentage was rather low for urban mothers also.
The p-value (<0.001) showed significant difference exists between rural and urban mothers
and ANC visit. From the table it appeared that receiving antenatal care also improves with
household wealth. Only 8% of women in the poorest wealth quintile made 4 or more visits,
whereas, almost 51% of women in the richest wealth quintile made 4 or more visits to the
ANC providers. Like the rural-urban differential, the poor-rich differential in antenatal
coverage was also significant (p<0.001) and seemed very large as well in Bangladesh. Around
60% of women made 4 or more visits whose partners had higher education. The figure was
not good for the women whose partners were illiterate or had primary education. A
significant difference (p<0.001) exists between partners education level and ANC care visit as
well. In contrast, only 8% of women made recommended numer of visits whose partners
were illiterate. A much better tendency to seek for ANC was observed for the women whose
partners were professional or businessman in comparison with the women whose partners
were day laborer. Moreover, the number of antenatal visits decreased significantly (p<0.001)
with the age of mother. Only 14% of mothers aged 35-49 years made 4 or more visits for ANC,
whereas, 24 % of mothers aged <20 years visited 4 or more times. The number of antenatal
visits also varied significantly (p<0.001) according to the birth order. The percentage of
mothers having their first child visited recommended number of times more often than
mothers who were not having their first child.
- 23 -
Table 6: Antenatal care visits according to background characteristics
Background characteristics ANC Visit Chi-square (p-value)
No visit Number (%)
1-3 visit Number (%)
≥4 visit Number (%)
Mother’s education level No Primary Secondary or higher
787 (62.1) 661 (43.9) 413 (19.3)
390 (30.8) 643 (42.8) 889 (41.4)
90 (7.1) 200 (13.3) 844 (39.3)
<0.001
Type of place of residence Urban Rural
424 (24.2) 1437 (45.2)
660 (37.8) 1263 (39.8)
662 (38.0) 478 (15.0)
<0.001
Wealth Index Poorest Poorer Middle Richer Richest
541 (57.7) 519 (52.6) 388 (42.6) 261 (27.7) 152 (13.3)
321 (34.3) 367 (37.2) 400 (44.0) 425 (45.1) 410 (35.7)
75 (8.0) 102 (10.2) 122 (13.4) 257 (27.3) 583 (51.0)
<0.001
Partner’s education level No Primary Secondary Higher
891 (56.2) 593 (43.0) 308 (23.4) 66 (10.4)
553 (34.9) 581 (42.1) 596 (45.2) 191 (30.2)
140 (8.8) 206 (14.9) 415 (31.5) 376 (59.4)
<0.001
Partner’s occupation level Day laborer Business Professional
1520 (43.2) 304 (27.7) 17 (7.8)
1392 (39.5) 428 (39.1) 62 (28.4)
609 (17.3) 364 (33.2) 139 (63.8)
<0.001
Mother’s age (years) at conception <20 20-34 35-49
646 (33.6) 1003 (38.6) 141 (56.2)
816 (42.4) 977 (37.6) 74 (29.5)
461 (24.0) 616 (23.8) 36 (14.3)
<0.001
Birth order 1 2-3 4-5 6+
369 (23.9) 795 (36.9) 442 (52.7) 255 (65.7)
659 (42.7) 853 (39.6) 306 (36.5) 105 (27.1)
515 (33.4) 508 (23.6) 91 (10.8) 28 (7.2)
<0.001
Religion Islam Others
1717 (38.4) 144 (31.9)
1742 (39.0) 181 (40)
1008 (22.6) 127 (28.1)
<0.007
Missing value analysis: Moreover, the same analysis including the missing values was done
(Appendix I) and percentage distribution of missing values in different categories showed
small variances of missing value distribution across the groups. Missing values appeared
little more in illiterate mothers (24.3) than secondary or higher educated mothers (15.6) (p
<0.001), rural mothers (21.4) than urban (17.0) (p<0.001), mother’s in poorest wealth
quintile (24.3) than richest group (14.8) (p<0.001)and so on.
- 24 -
Univariate multinomial Logistic Regression
The table 7 depicts the result of univariate analysis which shows the effect of different
independent variables on the antenatal care visit.
Effect of mother’s education on ANC visit
The univariate analysis shows that in comparison with the mother’s who made 4 or more
visits, mothers with no education had OR of 17. 7 (95% CI: 13.8-22.6) and it was highly
statistically significant. That means women with no education were 17.25 times more likely to
have no antenatal visit compared to the women who completed secondary or higher
education. In contrast, for mothers who completed primary education, the chances of getting
no antenatal visit was 6.6 (OR) (95% CI: 5.4-8.1) times higher than women who finished
secondary or higher secondary education. Again for the women who made 1-3 visit in
comparison to the women made 4 or more visits, women with no education might be 4.0
(OR) (95% CI: 3.1-5.2) times less likely to have 1-3 times antenatal visit compared to the
women with secondary or higher education. Furthermore, for the women with primary
education, the chances of having 1-3 visits were 3.0 (OR) (95% CI: 2.5-3.6) times less than
the women finished secondary or higher education. These figures entails that the tendency of
getting ANC visit largely influenced by mother’s education level and increased educational
status of mothers increases the likelihood of getting ANC visit.
Effect of other factors on ANC visit
From the table 7 it can be stated that, in comparison with the women who made 4 or more
visits, the chances of having no ANC visit was around 27 times higher for the women in the
poorest wealth quintile compared to the women in richest wealth quintile. Moreover, for the
women who made1-3 visits compared to the reference group, women in poorest wealth
quintile group were almost 6 times less likely to get 1-3 visit. The difference between richest
and poorest wealth quintile were quite high and the likelihood of getting ANC visits increased
with improved wealth status. Partner’s educational status was also an important factor for
ANC visits according to the result. In comparison with the reference group, women whose
partner were uneducated were almost 36 times more likely to get no ANC visit compared to
women whose partner was highly educated. Moreover, comparison between women with no
ANC visit and reference group revealed that, women whose partner was day laborer were 2.9
times less likely to have ANC visit compared to the women whose partner was engaged in
professional work. The difference between rural and urban dwelling also had significant
effect on ANC visits. Rural women had 2.61 times higher chance of not getting any ANC visit
compared to the urban women when compared to ≥4 ANC visits vs. no ANC visit.
- 25 -
Table 7: Univariate multinomial logistic regression of ANC visits according to different variables
Variables Univariate multinomial logistic regression of ANC visits
No ANC Visit OR (95% CI)
1-3 visits OR (95% CI)
Mother’s education level No Primary Secondary or higher
17.7 (13.8-22.6) ˟ 6.6 (5.4-8.1) ˟
1
4.0 (3.1-5.2) ˟ 3.0 (2.5-3.6) ˟
1
Wealth index Poorest Poorer Middle Richer Richest
27.8 (20.5-37.5) ˟ 19.6 (14.8- 25.6) ˟ 12.2 (9.3-16.5) ˟ 3.91 (3.05-5.01) ˟ 1
6.1 (4.6-8.1) ˟ 5.1 (3.9-6.6) ˟ 4.6 (3.6-5.9) ˟ 2.3 (1.9-2.8) ˟ 1
Partner’s education level No Primary Secondary Higher
36.2 (24.3-49.7) ˟ 16.5 (12.1-22.3) ˟ 4.2 (3.1-5.7) ˟
1
7.7 (6.0-10.1) ˟ 5.5 (4.4-7.0) ˟ 2.8 (2.3-3.5) ˟
1
Partner’s occupation level Day laborer Business Professional
2.9 (2.4-3.5) ˟ 0.1 (0.8-0.2) ˟
1
1.9 (1.6-2.3) ˟ 0.3 (0.27-0.53) ˟
1
Place of residence Rural Urban
2.6 (2.2-3.0) ˟
1
4.7 (4.0-5.5) ˟
1
Birth order 1 2-3 4-5 6+
1 2.1 (1.8-2.5) ˟ 6.7 (5.2-8.8) ˟ 12.7 (8.4-19.2) ˟
1 1.3 (1.1-1.5) ˟ 2.6 (2.0-3.4) ˟ 2.93 (1.9-4.5) ˟
Mother’s age at conception <20 years 20-34 years 35-49 years
1 1.1(.9-1.3) 2.7 (1.9-4.1) ˟
1 0.8 (0.7-1.0) 1.1 (0.7-1.7)
Religion Islam Others
1.5 (1.2-1.9) ˟
1
1.2 (0.9-1.5) 1
The reference category: ≥4 ANC visits, ˟ = Significant at 0.05 levels, 1 = Reference category within groups .
Birth order also had significant effects on ANC visits where women having child number 6 or
more were almost 12 times less likely to visit ANC compared to the women who were having
their first child. In comparison with ≥4 ANC visits vs. no ANC visit, women who aged more
than 35 years had 2.7 times less chance to visit for ANC compared to the women who were
<2o years. So, the likelihood of visits for ANC decreases with the age of the mother and birth
order. Mother’s age at conception and religion had small effect on ANC visits as statistical
significance varied across the group.
- 26 -
Multivariate multinomial logistic regression
To control the effect of other factors in the association of mother’s education level and ANC
visits, multivariate multinomial logistic regression was performed and multivariate analysis
involved three models (Table 8):
Model 1: In the 1st model of analysis mother’s education, wealth index and area of residence
was included (the -2 log likelihood = 345.66, chi-square = 1449.11, p<0.001) where the
potential confounding effect of household wealth status and area of residence in the
association between mother’s education and ANC visit were controlled.
Model 2: To control for the effect of other predictor variables which may confound the study,
in the 2nd model partner’s education level and partner’s occupation level was also considered
in addition to the 1st model (the -2 log likelihood = 1410.79, chi-square = 1548.06 p<0.001).
Model 3: In the 3rd model, all the predictors including mother’s age at conception, birth order
& religion in addition of the previous two models were included in an attempt to control for
their effect in the study ( the -2 log likelihood = 3896.3, chi-square = 1615.8 p<0.001).
Moreover, log likelihood ratio test confirmed the significant differences between models and
adding more predictor variables to the different models makes statistically significant
improvements to the model fit. In model 3 where the effect of all predictor variables
controlled was regarded as adjusted model and OR3 considered as adjusted OR. The odds
ration obtained through univarite analysis of mother’s education on ANC visit was
considered as crude effect of mother’s education on ANC visit (ORc). The crude effect of
mother’s education on ANC visits has already been discussed in univariate section. The
purpose of building three models was to show how different predictors affect the association
of mother’s education and ANC visit.
In the 1st model of multivariate analysis, after adjustments for household wealth status and
area of residence, in comparison with the women who made 4 or more visits and had
secondary or higher education, uneducated women were 9.6 (OR1) (95% CI: 7.3-12.5) times
more likely not to visit for ANC and primary school educated women were 4.2(OR1) (95% CI:
3.4-5.2) times more likely not to visit for ANC. On the other hand, women who made 1-3
visits compared to reference group, uneducated women were 2.8 (OR1) (95% CI: 2.19-3.7)
times more likely not to visit for ANC compared to the secondary or highly educated women.
- 27 -
Table 8: Multivariate multinomial logistic regression of ANC visits
In the 2nd model, after controlling for partner’s occupation and education level in addition to
1st model, it can be observed that, in comparison with the reference group, uneducated
women were 5.6 (OR2) (95% CI: 4.2-7.6) times more likely not to visit for ANC. In contrast,
women who made 1-3 visits compared to the reference group, uneducated women had almost
2 times higher chance of not getting 1-3 times compared to the secondary or highly educated
women.
In the 3rd model which was considered as adjusted model, it can be stated that in comparison
with the women who made 4 or more visits, uneducated women were 4.2 (OR3) (95% CI: 3.0-
5.8) times more likely not to visit for ANC and primary school educated women were 2.34
(OR3) (95% CI: 1.8-2.9) times more likely not to visit for ANC compared to the secondary or
highly educated women. Moreover, women who made 1-3 visits compared to the reference
group, uneducated women were 1.8 times (OR3) (95% CI: 1.3-2.4) more likely not to visit for
Univariate logistic regression
Multivariate multinomial logistic regression (reference category:≥ 4 ANC visits)
Mother’s Education Level
ANC visits Model 1 adjusted for wealth index and place of residence
Model 2 adjusted for wealth index, place of residence, partners education & occupation level
Model 3 (Adjusted for all variables i.e. wealth index, place of residence, partners education, partner’s occupation, mother’s age at conception, birth order & religion)
No ANC visit
1-3 ANC visits
No ANC visit
1-3 ANC visits
No ANC visit
1-3 ANC visits
No ANC visit
1-3 ANC visits
ORC (95% CI)
ORC (95% CI)
OR1 (95% CI)
OR1 (95% CI)
OR2(95% CI)
OR2 (95% CI)
OR3 (95% CI)
OR3
(95%CI)
No Education
17.7˟˟˟ (13.8-22.6)
4.0 ˟˟˟ (3.1-5.2)
9.6˟˟˟ (7.3-12.5)
2.8˟˟˟ (2.1-3.7)
5.6˟˟˟ (4.2-7.6)
2.0˟˟˟ (1.5-2.6)
4.2˟˟˟ (3.0-5.8)
1.8˟˟˟ (1.3-2.4)
Primary Education
6.6˟˟˟ (5.4-8.1)
3.0 ˟˟˟ (2.5-3.6)
4.2˟˟˟ (3.4-5.2)
2.3˟˟˟ (1.9-2.8)
2.7˟˟˟ (2.2-3.5)
1.7˟˟˟ (1.4-2.1)
2.3˟˟˟ (1.8-2.9)
1.6˟˟˟ (1.3-2.0)
Secondary or Higher Education
1 1 1 1 1 1 1 1
The Reference Category: ≥4 ANC visits; 1 = reference category within groups for comparison; ORC = Crude
Odds Ratio; OR123 = Adjusted Odds Ratio ;˟˟˟ = Significant at <0.001 level
- 28 -
1-3 times compared to the secondary or highly educated women. On the contrary, wome with
priamry education were 1.6 (OR3) (95% CI: 1.3-2.0) times less likely to visit for 1-3 times
compared to the women who completed secondary or higher education.
Result of calculation of predicted probability of ANC visits
The figure 3 below depicts the predicted influence of mother education on ANC visits in
Bangladesh. The figure was constructed from the results of the probability calculation. The
predicted probability of ANC care utilization was plotted in relation to the main independent
variable i.e. mother’s education which showed strong association in the multinomial logistic
regression model. The basic formual for probability calculation of each outcome category was
as follows:
Logit (probability of ANC visits) = α + β1X1 + β2X2 + β3X3+ β4X4+ β5X5+ β6X6+ β7X7+ β8X8
Probability (p) = e (α + β1X1+.....+ βnXn ) / 1+ e (α + β1X1+.....+ βnXn )
Where, α = intercept, X1 = mother’s education level, X2 = area of residence, X3 = wealth
index, X4 = parter’s education level, X5 = partner’s occupation level, X6 = mother’s age at
conception, X7 = birth order and X8 = religion & βnXn= coefficient*variable . The β
coefficients for each variable were taken from multivariate logistic regression model.
From the figure 3 it can be stated that, the probability of using ANC services increased with
the improvement of mother’s education. The line which represents no ANC shows that the
chance of having no ANC visits reduced dramatically with the increased of mother’s
education level. The line which represents ANC 1-3 times depicts that the chances of getting
1-3 times ANC visits also increased with education level. The line which representing ANC
visit 4 or more time shows that women with no education had very low chance of having 4 or
more ANC visits, whereas, the probability of getting 4 or more ANC visits increased sharply
for secondary or highly educated mothers in comparison with the mothers who had no or
primary education.
- 29 -
Figure 3: Predicted probability of use of ANC services in relation to mother’s education.
Sensitivity Analysis
According to the various reviews of literature and results from different studies indicate
distance of health care center/medical territory from a woman's house is an important factor
for number of antenatal visits (49, 50, 51). The 2007 BDHS data included distance as one of
the reasons for not seeking antenatal care with other reasons. For doing sensitivity analysis,
women who responded distance of health care centers as the reason for not seeking antenatal
visit was excluded from the data set to see the variability of the result. Hence, women who
have not responded distance as the reason for not seeking antenatal care was assumed to live
near the health care center. After sensitivity analysis (i.e. excluding the data) the results did
not show much variability in comparison with the actual result. Therefore, it can be stated
that the effect of distance was small in the association of mother’s education and ANC visit.
The sensitivity analysis result has been attached to the Appendix II.
- 30 -
Discussion
The study examined the utilization of antenatal care services according to the different level
of mother’s educational status. The study compared mother’s who made recommended
number of visits for ANC with the mothers who never visited for ANC and who made 1-3
visits. The reason for the segmentation of ANC visits was that mothers who made 1-3 visits,
supposed to get less benefit from mothers who made 4 or more visits but must get some
benefits compared to the mothers who have not received any ANC. Therefore, the study tried
to estimate the difference in accordance with different level of mothers educational status.
As health care is vitally important for detecting and managing conditions during pregnancy
and childbirth, basic ANC provides women a package of preventive interventions (1). The risk
of maternal mortality and morbidity as well as neonatal deaths can be reduced substantially
through regular and proper antenatal care check-up and delivery under safe and hygienic
conditions (2, 44). However, if mothers are not conscious and educated enough to know the
importance of seeking health care services during these critical periods of pregnancy and
delivery, could be deleterious for both mother and infant survival. Despite of continuous
effort of Govt. and other organizations, ANC service utilization remains very low in
Bangladesh. From the result it appeared that, only 23.1% of mothers made recommended
number of visits (4 or more times) for ANC. Around 60% of mothers received ANC care at
least once (39.1% visited 1-3 times + 23.1 visited 4 or more times), among them 52.3% visited
to medically trained providers. ANC from a medically trained provider just increased slightly
in comparison with 2004 BDHS report when the figure was 49% (52). According to
Millennium Development Goals Report of 2011, in all developing regions of the world, the
proportion of women receiving recommended number of visits was 51% (1). Bangladesh is
still far behind even in comparison with other developing regions of the world.
Furthermore, early detection of risks during pregnancy through appropriate ANC at
community level and the timely availability of referral facilities are important requirements
for reduction of maternal mortality (10, 42,53). Women's education can make a difference
here as educated women should be able to recognize the importance of using ANC services
early and timely to prevent unwanted pregnancy outcomes (54). The study also showed that
only around 42% of mothers had completed secondary or higher education, that means,
around 60% of mothers were either illiterate or had primary education. Less than 8% of
illiterate mothers made recommended number of visits for ANC, whereas, around 40% of
mothers who had secondary or higher education made recommended number of visits. A
study in Laos explored that low level of education, lack of knowledge and poor attitude
towards ANC along with misconception were important factors for the low utilization of ANC
- 31 -
services (49). A worldwide survey on female education and maternal mortality confirmed
that maternal mortality is tend to be higher where maternal educational staus is poor (21).
Therefore, it can be stated the low female education may attribute to the lower utilization of
ANC services in Bangladesh as more than half of the mothers do not have traditional school
education.
Univariate and multivariate analysis showed strong associations between mother’s education
and utilization of ANC services. The result revealed that mother’s education was an
important determinant for the utilization of maternal health services after controlling for
other related predictors like household wealth status, area of residence, partner’s education,
partner’s occupation, birth order of child, mother’s age at conception & religion. The result
showed that, in comparison with the women who made 4 or more visits, the chances of
having no ANC visit were almost 4 times higher for illiterate mothers compared to the
mothers with secondary or higher education, after adjusted for other predictors. However,
for mothers who had primary education, the likelihood of having no ANC visit was almost 2
times higher compared to the mothers who had secondary or higher education. On the other
hand, comparison between ≥4 ANC visits vs. no ANC visit showed that, uneducated mothers
were almost 1.8 times less likely to have 1-3 times visit compared to the mothers who had
secondary or higher education. However, women with primary education were almost 1.6
times less likely to visit 1-3 times in comparison with the women with secondary or higher
education. Overall, the result showed that secondary or highly educated mothers had better
chance of having recommended number of ANC visits compared to the mothers who had no
or primary education. The predicted probabilities of ANC utilization also revealed that the
probability of using ANC care increased with mother’s education. It depicted that women's
education was very strong determinant for the utilization of ANC in Bangladesh.
Several studies have found that women’s education is one of the best predictors for ANC
visits (22, 24, 28, 30, 49, 50, 51, 55, 56, 57) which supports the present study findings. A
study in Nepal found that a mother with primary education used professional ANC nearly
twice in comparison with uneducated mothers. Moreover, mothers with secondary and
higher education used ANC almost five and 35 times higher than their non-educated
counterparts respectively(30). Another study in India explored that educated women with at
least middle schooling (high school) were almost 8 times and women with less than middle
schooling were 3 times more likely to seek for ANC compared with the women with no
education (22).
- 32 -
According to WHO, in addition to improved health system, increased female education and
physical accessibility to health facilities are the two important factors for the decline in
maternal mortality in different regions of the world (2). Several studies based on Bangladesh
Demographic and Health Survey data showed that the proportion of mothers who received
ANC from medically trained providers increased steadily with an increase in the education
level of the mothers both in the urban and rural areas of Bangladesh (23, 58). A study which
analyzed the levels, patterns and trends of ANC service utilization in Bangladesh added that
mother’s education increases perceived seriousness about pregnancy related complications
followed by improving health care seeking behaviors (58). The study confiremd that the
influence of maternal education on ANC visits prevailed even when other socioeconomic
factors were taken into account.
In addition to mother’s education, household wealth status, partner’s education, partner’s
occupation status, area of residence & birth order were significant influencing factors for
seeking ANC services in Bangladesh. The univariate analysis revealed that woman whose
partner was highly educated and engaged in professional work received ANC more often and
frequently than woman whose partner was less educated and not engaged in professional
work. Moreover, women in richest household wealth quintile made more ANC visit than
women in poorest household wealth quintile group and the rich-poor diffence on receiving
ANC was huge. Besides, women who were having there first child received ANC more often
than women having a child with different birth order. The likelihood of receiving of ANC also
decreased with mother's age. The three models in multivariate multinomial logistic
regression showed the effect of these factors on the association of mother’s education and
ANC visit.
The cross sectional nature of the data was a limitation of the study which only provided a
snapshot view, therefore, it would be inappropriate to compare these findings to the present
situation. Therefore, causal (cause-effect) relationship may not be established between the
independent variables and utilization of Antenatal care (ANC). As the missing value analysis
showed variances in missing value distribution across groups (Appendix I), therefore, there
was a possibility that missing values could be “missing not at random (MNAR)” and the
findings may not possesss full external validity. Another disadvantage of the missing
observations was loss of data and reduced power although the sample size was quite large
even after omission of missing observations. Moreover, information on the distance to the
health facilities was not collected by 2007 BDHS. As most of the hospitals, clinics and
maternal health care services are situated in urban areas compared to the rural areas,
therefore, access to services can be a barrier for rural mothers. From univariate analysis, it
also appeared that mothers living in urban areas had higher odds of getting ANC services
- 33 -
compared to mothers living in rural areas. The effect of distance to access health care service
on the associationon of mother’s education and ANC visit was tried to adjust by proxy
measure of place of residence and by doing sensitivity analysis its effect had been estimated.
The sensitivity analysis result confirmed apparently to some extent that the effect of distance
to health care center was small (Appendix II) in the association. However, it was not possible
to conclude that the effect of access to health care service was minimized completely. The
study did not consider factors like quality of services, cultural barriers, attitude of providers
and related expenses which might have effect on accessing ANC services. In contrast to the
weak link, 2007 BDHS data were nationally representative, sample size was quite large and
well-established methodology and procedures including a variety of variables to understand
the actual association between mother’s education and ANC visits in Bangladesh were the
strength point.
Policy Implications
The study revealed that the utilization of maternal health care services greatly influenced by
education of mothers and some other important factors like household wealth status and
partner’s education. The study showed that maternal education, even at low level,
significantly increased the use of ANC. For the reduction of MMR and to ensure safe delivery
it is important to seek medical advice during pregnancy and have professional assistant
during delivery as unpredicted complications may arise any time. As receiving ANC from
medically trained providers increases the probability of having a skilled birth attendant
during delivery, therefore, the quality of ANC services should be improved and attention
should be given to providing appropriate advice on safe delivery which should be assisted by
professional health care providers. Though Health, Population and Nutrition Sector
Development Program (HPNSDP) introduced by Bangladesh government tend to provide
more focus on ANC, EmOC and delivery assisted by the professionals, priority should be
given to the implementation process. In addition to this, government should assess, monitor
and evaluate the factors responsible for accessing quality ANC services by doing quantitative
as as well as qualitative study so that proper progress and deficit can be measured. Additional
emphasis should be given on universal access to family planning and disadvantaged rural
areas where access of health care could be a major issue in addition to working on cultural
and traditional barriers about ANC.
The secondary school enrollment ration for the female is still very low in Bangladesh and
almost half of the women are illiterate; therefore, a large number of women do not aware
about the importance of having ANC and family planning. As the study explored that
secondary or higher education increased the likelihood of receiving ANC; therefore, priority
- 34 -
should be given on female education. The government should strengthen policy of female
education and it is necessary to make sure that girls complete at least secondary education.
Furthermore, According to Donnay F., there is clear association exists between low status of
women and the risk of maternal morbidity and mortality (61). However, educated women
may have more autonomy to their own life, can take decisions by herself and can also
contribute to the family as well as society. An integrated policy of health, education and social
welfare sectors which will focus on ensuring education of women, scaling up of ANC services
followed by assisting delivery by health professionals may reduce the complication as well as
contribute in the reduction of MMR, a burden and challenge for government to solve.
Initiatives should be also taken to encourage mothers to visit frequently for ANC by
improving the quality of services, improving the attitudes of ANC providers and reducing
out-of-pocket expenses implied by the staffs of health care center.
Government should also focus more on alleviating poverty, reducing the gap of accessing
health care facilities irrespective of wealth and geographic location, educating both female
and male members of the family to influence the utilization of maternal health care. Overall,
the integrated multi-sectoral approach to provide equity in health, education and other social
services could make important contributions to reducing MMR as well as for achieving
MDG5.
Conclusion
The study estimated the contribution of women's education on ANC which is important for
detecting, managing and treating complications during pregnancy potentially contributing to
maternal mortality. The study demonstrated that women with secondary or higher education
made recommended number of visits for ANC more often than uneducated and women with
primary education after adjusting the effect of other socioeconomic factors. Poor household
wealth status and low education level of partner’s along with other socioeconomic factors
aggravating the condition. Government, NGO’s and development organizations should work
combinely and deliberately to address factors responsible for the low utilization of ANC to
reduce preventable maternal morbidities and mortalities occurring in developing countries
like Bangladesh today.
- 35 -
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Appendix
Appendix I:
Table: ANC visits according to background variables including missing values
Background characteristics
ANC Visit Chi-square (p-value)
No visit Number (%)
1-3 visit Number (%)
≥4 visit Number (%)
Missing
Mother’s education level No Primary Secondary or higher
787 (47.0) 661 (34.3) 413 (16.2)
390 (23.3) 643 (33.4) 889 (34.9)
91 (5.4) 203 (10.5) 846 (33.3)
408 (24.3) 420 (21.8) 396 (15.6)
<0.001
Place of residence Urban Rural
424 (20.1) 1437 (35.5)
660 (31.3) 1263 (1263)
664 (31.6) 478 (11.8)
359 (17.0) 865 (21.4)
<0.001
Wealth Index Poorest Poorer Middle Richer Richest
541 (44.3) 519 (40.5) 388 (33.7) 261 (22.8) 152 (11.3)
321 (26.3) 367 (28.6) 400 (34.7) 425 (37.1) 410 (30.4)
75 (6.1) 102 (8) 122 (10.6) 257 (22.4) 586 (43.5)
285 (23.3) 294 (22.9) 243 (21.1) 203 (17.7) 199 (14.8)
<0.001
Partner’s education level No Primary Secondary Higher
891 (42.6) 593 (33.9) 308 (19.6) 66 (9.0)
553 (26.4) 581 (33.2) 596 (38) 191 (26.2)
141 (6.7) 206 (11.8) 415 (26.4) 379 (51.8)
509 (24.3) 368 (21.1) 251 (16.0) 95 (13.0)
<0.001
Partner’s occupation level Day laborer Business Professional
1520 (34.2) 304 (22.6) 17 (6.7)
1392 (31.3) 428 (31.8) 62 (24.6)
609 (13.7) 364 (27) 139 (55.2)
923 (20.8) 252 (18.7) 34 (13.5)
<0.001
Mother’s age (years) at conception <20 20-34 35-49
646 (26.3) 1003 (32.7) 141 (52.2)
816 (33.2) 977 (31.9) 74 (27.4)
461 (18.8) 620 (20.2) 36 (13.3)
532 (21.7) 464 (15.1) 19 (7.0)
<0.001
Birth order 1 2-3 4-5 6+
369 (18.1) 795 (30.3) 442 (43.5) 255 (54.0)
659 (32.3) 853 (32.5) 306 (30.1) 105 (22.5)
515 (25.3) 508 (19.4) 91 (9) 28 (5.9)
496 (24.3) 467 (17.8) 177 (17.4) 84 (17.8)
<0.001
Religion Islam Others
1717 (30.6) 144 (26.7)
1742 (31.1) 181 (33.5)
1014 (18.1) 127 (23.5)
1136 (20.3) 88 (16.3)
<0.002
- 41 -
Appendix II: Sensitivity Analysis
Table: Multinomial Logistic Regression Analysis for Antenatal Visit with respect to Mother’s Education
The table above showed sensitivity analysis result after removing the data of mother’s who
have responded distance of health care centre as the reason for not visiting ANC. The purpose
of the sensitivity analysis was to test the variability of the result by cancelling out the effect of
distance on the association of mother’s education and ANC visit. The results revealed that the
effect of distance of health care center was small in the association. The ORc for mothers with
no education and no ANC visit was 17.71 considering all data, whereas, after removing the
data who responded distance as a reason, the ORc was changed to 17.79 which seemed
negligible difference. The change for the rest of the cases seemed quite small as well. It
proved that distance has negligible effect on the association of mother’s education and ANC
visit.
Multinomial Logistic Regression Analysis for Antenatal Visit with respect to Mother’s Education
( Removing data who respond distance as the reason for not visiting for antenatal care in comparison with all data)
Mother’s Education
Univariate Analysis Multivariate Analysis
No Antenatal Visit Antenatal Visit 1-3 Times
No Antenatal Visit Antenatal Visit 1-3 Times
ORC (95% CI)˟˟˟
Previous value
ORC (95% CI)˟˟˟
Previous value
ORa (95% CI)˟˟˟
Previous value
ORa
(95%CI)˟˟˟ Previous value
No Education
17.79 (13.88-22.80)
17.71 (13.84-22.67)
4.07 (3.18-5.20)
4.07 (3.18-5.22)
4.36 (3.16-6.03)
4.33 (3.14-5.97)
1.83 (1.33-2.50)
1.83 (1.33-2.50)
Primary Education
6.65 (5.46-8.11)
6.67 (5.48-8.11
3.01 (2.50-3.62)
3.01 (2.52-3.62)
2.35 (1.84-2.99)
2.34 (1.84-2.99)
1.61 (1.29-2.01)
1.61 (1.29-2.01)
Secondary and Higher Education
1 1 1 1 1 1 1 1
The Reference Category : ≥4 visits; 1 =Rreference category within groups for comparison; ORC = Crude odds ratio;ORa = Adjusted odds ratio; ˟˟˟= Significant at <0.001 level