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Maternal Education and Child Nutritional Status in Bangladesh: Evidence from Demographic and Health Survey Data

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The objective of present study is to determine the effect of maternal education on child nutritional status in Bangladesh. The study has used 2007 Bangladesh Demographic and Health Survey (BDHS) data for the analysis. The study has employed various pathway measures linking maternal education and child nutritional status in Bangladesh. Logistic regression results explain that maternal education has significant effect on child better nutritional status. Socioeconomic status and attitude towards modern health care services are the most important pathways linking the both. Health knowledge and reproductive behavior describe some of the effect of mother’s education on child nutrition. Only women empowerment appears to be the weakest pathway in our analysis.
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Pak. j.
life soc. Sci. (201
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ISSN: 2221
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Pakistan Journal of Life and Social Sciences
www.pjlss.edu.pk
RESEARCH ARTICLE
Maternal Education and Child Nutritional Status in Bangladesh: Evidence
from Demographic and Health Survey Data
Sofi a An war1 , *, Samia N asre en1, Zahra B atoo l2and Zakir Husain1
1Depa rtme nt o f Ec onomics, Go vern ment Col lege University, Faisalab ad, Pak ista n
2Depa rtme nt o f So ciology, Univer sity of Agri culture, Faisalabad, Pa kist an
ARTICLE INFO
ABSTRACT
Received:
Accepted:
Online:
Jan 18, 2013
Mar 11, 2013
Mar 17, 2013
The objective of present study is to determine the effect of maternal education on
child nutritional status in Bangladesh. The study has used 2007 Bangladesh
Demographic and Health Survey (BDHS) data for the analysis. The study has
employed various pathway measures linking maternal education and child
nutritional status in Bangladesh. Logistic regression results explain that maternal
education has significant effect on child better nutritional status. Socioeconomic
status and attitude towards modern health care services are the most important
pathways linking the both. Health knowledge and reproductive behavior describe
some of the effect of mother’s education on child nutrition. Only women
empowerment appears to be the weakest pathway in our analysis.
Keywords
Bangladesh
Child nutrition
Health knowledge
Maternal education
Socioeconomic status
*Corresponding Author:
Sofia_ageconomist@yahoo.com
INTRODUCTION
Socioeconomic development and quality of life of
masses; living in any country is determined through
child health and infant mortality rate. Children are the
hope for this world. Development is not obtained only
with physical capital in form of bricks, wheels,
computers rather the actual capital is human itself. A
healthy, intelligent and honest human force is the ardent
energy to utilize the bricks and run the wheels. This is
the reason that every developing country is striving
hard to convert its population into human capital. It is
one of the Millennium Development Goals (MDGs) to
reduce infant mortality rate by two-third till 2015.
Nourished children not only perform better in education
rather grow into healthier adults, become active labour
force and hence are able to give their own children a
better life. In Bangladesh, under-five mortality rate is
estimated as 65 deaths per 1000 child birth are reported
Neonatal deaths are estimated at 57 percent of under-
five death rate (BDHS, 2007).
Whatever are the cultural and economic setups; at
household level mothers are considered the main
catalyst in better nutrition, health and education of
children. Higher years of mother’s schooling are
considered to lower the child mortality rate as education
provides information relating to child nutrition, their
proper treatment during illness and information relating
to vaccination. According to World Bank (1993),
mother education is necessary for improving child
health status and lowering infant mortality rate. Various
studies on health confirm the significant association
between motherly learning and child health and use of
health facilities than father education (Mondal et al.,
2009; Frost et al., 2005; Young et al., 1983). Maternal
education can improve child health and reduce infant
mortality through various ways like women
empowerment, enhanced use of modern health care
services, small family size, better health knowledge,
and increased family income (Glewwe, 1999; Castro
and Juarez, 1995; Caldwell and Caldwell, 1993;
Schultz, 1993; Cleland, 1990; Mason, 1984). Caldwell
(1979) was the first to conclude that children of
educated mothers have better health than uneducated
mothers. Some studies on cross-country comparison
demonstrated negative relationship between mother’s
years of education and children death rate (Bicego and
Boerma, 1991; Mensch et al., 1985; Ware, 1984).
Glowwe (1999) explained that health knowledge is the
most significant factor explaining the relationship
Anwar et al
78
between mothers’ education and child health. However,
there are some studies that failed to explain strong
causal relationship between maternal education and
child health (Kunstadter, 1995; Desai and Alva, 1995;
Cleland and Ginneken, 1988).
Socioeconomic status is one of the most important
pathways explaining the link between maternal
education and child nutritional status (Frost et al., 2005;
Desai and Alva 1998; Caldwell, 1994). Education and
socioeconomic status not only improves mothers’
knowledge relating to health but also change their
attitude and behavior, which in turn positively affect the
nutritional status of their children (Cleland, 1990).
Children health depends upon educational attainment of
mothers and their capacity to purchase those goods and
services which are necessary for maintaining better
health status of their children (Frost et al., 2005; Defo,
1997; Cleland and Ginneken, 1988). Higher years of
education provide woman with more opportunities to
find a better job and increase their family income
(Barrette and Brown, 1996). Moreover, educated
women prefer to marry highly educated men, with
sound earnings (Cleland and Ginneken, 1988).
According to Desai and Alva (1998) introduction of
socioeconomic variables in the model reduce the
strength of relationship between mother education and
child health. On the contrary, Frost et al. (2005)
considered the socioeconomic status as the most
important variable explaining the relationship between
mothers’ education and child nutritional status.
Similarly, Cleland and Ginneken (1988) found that
nearly half of the bearing of mothers’ education on
child nutrition is explained by socioeconomic status.
Attainment of formal education makes women
knowledgeable relating to wide range of health issues
like causes and symptoms of diseases, precautionary
measures, proper nutrition during disease and greater
exposure to health related messages and suggestions
through different sources like mass media (Benta et al.,
2011; Casterline, 2001; Defo 1997; Streatfield et al.,
1990; Cleland and Ginneken 1988). The relationship
between knowledge and child health implies that
knowledge about conditions and cognitive measures for
maintaining better health directly change previous
behavior relating to health. According to Defo (1997)
health knowledge can reduce the risk of infectious
disease through improved hygiene, nutritious food and
greater access to health products. Further, education
leads to better income generating activities enabling the
provision of improved housing. Enjoying these
facilities in household environment means that theses
family members are less unhygienic on average (Frost
et al., 2005).
Education not only has direct and significant effect
rather can shift negative attitude, traditional practices
and beliefs relating to health towards the adoption of
modern ideas and medicated practices (Benta, et al.,
2011; Frost et al., 2005; Defo 1997; Barrette and Brown
1996).Therefore, it is believed that educated mothers
are less likely to believe in the supernatural reasoning
of their child disease rather use modern medicine and
preventive measures for the cure of disease (Heaton et
al., 2005). Educated mothers’ can take early decision
regarding the health problem of their children (Frost et
al., 2005; Jejeebhoy, 1995) and their family size and
birth interval (Benta et al., 2011; Levin et al., 1994).
Women greater control on family income can improve
the nutritional status of children particularly female
child (Saraswathi, 1992) and children survival rate
(Kishor, 1995).
The relationship between maternal age and child health
status is also found in many studies. Benta et al. (2011)
found that child health increases with mother age.
However, Sommerfelt and Stewart (1994) found no
systematic relationship between child health and
mothers’ age. An inverse relationship existed between
years of education, fertility and early age marriage
(Cleland and Ginneken, 1988). Early age marriage is
the main cause for increase in infant mortality rate
(Tagoe-Dark, 1995).
The present study signifies the impact of maternal
education on child nutritional status (assessed by
stunting/ height for age) in Bangladesh using
Demographic and Health Survey (DHS, 2007) data.
According to BDHS (2007) stunting is the result of
inadequate nutrition to children that affect child
population over a long period of time. In Bangladesh,
national estimates reveal that 43 percent children are
stunted while 16 percent are severely stunted. This
study provides the answer of the question;Whether
maternal education significantly affects child nutritional
status in Bangladesh?
MATERIALS AND METHODS
Bangladesh Demography and Health Survey (BDHS,
2007) collected separate estimates of major indicators
for each of the six divisions of the country including
Barisal, Chittagong, Dhaka, Khulna Rajshahi and
Sylhet. The present study is limited to the sample set of
ever married women having at least one alive child. The
purpose of present study is to describe the effect of
maternal education on child nutritional status through
various parameters such as socio-economic status,
health knowledge, attitude towards the utilization of
health care services, women empowerment and
reproductive variables. Height for age is an
anthropometric index that is used as a proxy to measure
the child nutritional status. According to WHO
International Growth Conference, “the children who are
below 2, standard deviations on the height for age
growth curve are classified as stunted” (Benta et al.,
Maternal education and child nutritional status in Bangladesh
79
2011; Dibley et al., 1987). This variable is treated as
dependent variables in our analysis in the form of
binary variable. Child’s height for age =1 for those
children who are below negative 2 standard deviation of
the median population and “0” otherwise following the
Heaton et al. (2005).
Mothers education is the main explanatory variable and
is classified into three categories: illiterate/ no
education, primary, secondary and above. Using
various measures, indices are constructed to
operationalize the effect of selected pathways on child
health. Before constructing these indices, different
variables are selected that properly measure each
pathway. Then, a factor analysis is performed to
determine how well each set of variables factored
together, omitting obvious outliers. Table 1 presents
scores of factor analysis and Cronbach’s alpha for each
of the selected variables to show that every index is
formulated from correlated variables. After this, the
indices are constructed in simple additive form.
Socioeconomic status is measured by two additive
indices: household wealth and household environment.
Both indices range from 1 to 5. Household
environment index is measured by the availability of
following four basic facilities: (1) piped drinking water
(2) flush toilet facility (3) non-dirt floor and (4)
electricity. Household wealth index is measured by the
availability of following four durables: (1) radio (2)
television (3) refrigerator and (4) telephone. Various
proxy variables are used to measure knowledge, attitude
and empowerment because their direct measures are not
available in survey data. Health knowledge index is
constructed based on the knowledge about four
indicators; (1) oral rehydration therapy (2) AIDS (3)
tuberculosis and (4) modern methods of contraception.
Women empowerment is measured through two proxy
variables. Reproductive variables included are (1)
mother’s age (2) birth interval and (3) birth
order/parity. Interval between two births is given in
months. Birth order/parity is further classified into four
categories ;(1)1st birth (2)2nd-3rd birth (3) 4th-6th birth (4)
above 6th birth. Mother’s age is given in complete year.
Source of information is measured by the access to (1)
newspaper (2) radio (3) television. Access to each of
the sources is coded by a dummy variable. In addition
to these variables, division of residence, rural/urban
disparity and husband education are treated as control
variables.
Analytical framework
In our analysis, predicted variable: child height for age
has two categories. So, our model was estimated by
following binary logistic regression equation.
(
1
Pr( 1) Pr( _ )
ln ln ( ) ..............(1)
Pr( 0) Pr( )
J
j ij
j
Y Y chld stunt
Y Z
Y Y Nostunt
Where;
α is the constant and β is the slope coefficient of the
estimated parameter, P/1-P is the odd ratio of the
occurring of an event given the value of the predictor
variable. Here a flow chart diagram is also added to
explain the relationship of variables.
Fig. 1: Relationship between maternal education
and child nutritional status
The estimated coefficients are interpreted on the basis
of their significance level. Finally, exponential log of
estimated coefficients is taken to find out odd ratios
(Bronte and Dejong, 2005). Odd ratios explain the
effect of explanatory and control variables on the
probability of child stunting.
RESULTS AND DISCUSSION
It was alarming to know that approximately 65 percent
of children were stunted in Bangladesh (Table 2).
Maternal education attainment level was not
satisfactory in Bangladesh as 71 percent of mothers
were either illiterate or having less than primary
education. Socioeconomic status of women; measured
by household wealth index and environmental index,
indicated that wealth status of women was not
satisfactory in Bangladesh. The average score of wealth
index was less than 2.5 out of total score of 5 and
environmental index was less than 3.5 out of total score
of 5 showing a better sign. Results demonstrated that
mother’s knowledge relating to health was not
satisfactory, showing an average score of 2.78 out of a
total score of 6. Average score for health care
utilization index was 2.72 out of total score of 6.
Women empowerment index showed a moderate score
of 2.11 out of a total score of 4.
Reproductive variables show that approximately 34
percent of children were born within the birth interval
of 0 to 24 months, 47 percent within the 25 to 45
months and only 19 percent of children were having
birth interval greater than 45 months. The average age
of mothers at the time of 1st birth interval was
approximately 17 years. Father’s education attainment
Anwar et al
80
Table 1: Results of Factor Analysis of Variables
included in Indices
Indices/Variables Factor
analysis Reliability
Analysis (α)
Household Wealth Index
Own a TV 0.772
Own a Radio 0.464 0.789
Own a refrigerator 0.574
Own a telephone 0.684
Household Environment Index
(better environment conditions)
Electricity available in house 0.736
Piped water provided in house 0.651 0.668
Flush toilet avail be in house 0.485
Non
-dirt floor type 0.624
Knowledge index
(improved
knowledge)
heard of oral rehydration therapy 0.447
heard of modern method of
contraception 0.642 0.752
Has heard of tuberculosis 0.588
Has heard of HIV/AIDs 0.707
Health care utilization
( Healthy
lifestyle)
Received pre-natal care from
doctor 0.636
Doctor attended birth 0.825 0.724
Received tetanus injection before
birth 0.537
Has used modern method of
contraception 0.489
Women empowerment
Decision for spending money in
household 0.621 0.710
Decision relating to family
planning 0.697
level was also low. About 36 percent of father’s were
illiterate, 45 percent were having primary education and
only 19 percent of men reported secondary and higher
level of education. About 70 percent of women were
living in rural areas. Majority of women lived in
Chittagong division (22 percent) followed by Dhaka
(21 percent). Surprisingly, most commonly used source
of information in Bangladesh was television, as 45
percent of women were watching television to get
information relating to child health.
The results of logistic regression are reported in Table
3. Model 1 shows that educated mothers significantly
decrease the likelihood of having a stunted child by 14
percent (1- exponent of the log odds) and 60 percent
respectively as compared to illiterate mothers. In model
2, when place of residence and division of residence
was added in model; educated mothers were again less
likely to have stunted child meaning have lower.
Table 2: Descriptive Statistics of households (N=5382)
Stunted =1 65.4%
Not stunted = 0
34.6%
Mother’s education
No education
34.3%
Primary 36.6%
Secondary and higher 29.1%
Socio economic status Range, Mean, SD
Household Wealth Index 1-5, 2.34, 1.106
Household Environment Index 1-5, 3.26, 1.210
Knowledge index 1-6, 2.78, 1.66
Health care utilization Index 1-6 2.72, 1.776
Women empowerment 1-4, 2.11, 1.735
Reproductive Variables
Mother age at 1
st
birth 17.39, 2.936
Birth order
1
st
birth 18.1%
2-3 birth 25.4%
4-6 birth 39.3%
Above 6 birth 17.2%
Birth interval
0-24 months 33.8 %
25-45 months 46.8 %
Above 45 months 19.5 %
Control Variables
Partner’s education ,
Illiterate(no. education) 35.9 %
Primary 44.7 %
Secondary and higher 19.5 %
Place & type of residence
Rural 70.5 %
Urban 29.5 %
Division of residence
Barisal 15.1 %
Chittagong 22.6 %
Dhaka 21.1 %
Khulna 08.7 %
Rajshahi 14.0 %
Sylhet 18.5 %
Source of Information
Listen to radio 20.8 %
Watch TV 44.8 %
Read News Paper 15.9 %
In model 3 on addition of mother age and partner
educational level, maternal education again confirmed to
have less probability of stunted or poor nutrition child
but education of child’s father (partner education)
indicated higher probability for having stunted child.
This explains for the more promising effect of mother
education on child health and nutrition than his father
education.
However, after controlling for wealth index, household
environmental index, health knowledge index, health
care utilization index and women empowerment index
Maternal education and child nutritional status in Bangladesh
81
Table 3: Effects of Maternal Education and Intervening Mechanisms on Likelihood of Stunting of children in
households of Bangladesh
Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
Maternal Education (uneducated , reference category)
Primary education 0.862**
(-0.15) 0.883***
(-0.12) 0.875
(-0.13) 0.877
(-0.13) 0.902
(-0.10) 0.920
(-0.08) 0.911
(-0.09) 1.226
(0.20) 1.215
(0.19)
Secondary /above 0.403*
(-0.90) 0.426*
(-0.85) 0.574*
(-0.55) 0.575*
(-0.55) 0.628*
(-0.46) 0.669*
(-0.40) 0.664*
(-0.41) 0.612**
(-0.49) 0.652*
(-0.43)
Place of residence (Rural, reference category)
Urban 0.758*
(-0.27) 0.750*
(-0.29) 0.752*
(-0.28) 0.859***
(-0.15) 0.876
(-0.13) 0.886
(-0.12) 0.986
(-0.014) 0.989
(-0.011)
Region of residence (Barisal, reference category)
Chittagong 0.981
(-0.02) 0.841
(-0.17) 0.839
(-0.17) 0.905
(-0.09) 0.899
(-0.10) 0.893
(-0.11) 0.773
(-0.25) 0.775
(-0.25)
Dhaka 0.822**
(-0.19) 0.717**
(-0.33) 0.715**
(-0.33) 0.791***
(-0.23) 0.815***
(-0.20) 0.80***
(-0.22) 0.570
(-0.562) 0.572
(-0.55)
Khulna 0.592*
(-0.52) 0.516*
(-0.66) 0.514*
(-0.66) 0.549*
(-0.59) 0.573*
(-0.56) 0.573*
(-0.55) 0.082*
(-2.501) 0.089*
(-2.42)
Rajshahi 0.682*
(-0.38) 0.626*
(-0.46) 0.624*
(-0.47) 0.659*
(-0.14) 0.668*
(-0.40) 0.664*
(-0.41) 0.48***
(-0733) 0.489***
(-0.71)
Sylhet 0.802**
(-0.22) 0.683*
(-0.38) 0.681*
(-0.38) 0.74**
(-0.30) 0.73**
(-0.31) 0.71**
(-0.43) 0.410**
(-0.891) 0.414**
(-0.88)
Mother’s Age at 1
st
birth 0.999
(-0.001) 0.999
(-0.001) 1.004
(0.004) 1.008
(0.008) 1.009
(0.009) 0.993
(-0.007) 0.994
(-0.006)
Partner’s education (uneducated , reference category)
Primary education 1.500*
(0.40) 1.551*
(0.44) 1.322*
(0.28) 1.222*
(0.200) 1.204*
(0.18) 1.207*
(0.19) 1.211**
(0.19)
Secondary education 1.591*
(0.46) 1.791*
(058) 1.699*
(0.53) 1.647*
(0.49) 1.663*
(0.509) 1.665
(0.509) 1.666
(051)
Socioeconomic Stutus
Wealth index 0.993*
(-0.007) 0.971*
(-0.03) 0.929*
(-0.07) 0.982*
(-0.02) 0.975*
(-0.025) 0.99*
(-0.01)
Better Environment
index 0.883*
(-0.12) 0.844*
(-0.17) 0.772*
(-0.26) 0.793*
(-0.23) 0.789**
(-0.24)
Improved Knowledge
index 0.850***
(-0.16) 0.871
(-0.14) 0.890
(-0.11) 0.898
(-0.10)
Healthy life style
(Health care Index) 0.923*
(-0.08) 0.922*
(-0.08) 0.981*
(-0.02) 0.983*
(-0.02)
Women
empowerment 0.930
(-0.04) 0.921
(-0.08) 0.925
(-0.07)
Birth order (Above 6 birth , reference category )
1
st
birth 0.472**
(-0.75) 0.491**
(-0.71)
2-3 birth 0.741***
(-0.30) 0.778***
(-0.25)
4-6 birth 1.197
(0.18) 1.185
(0.17)
Birth interval (Above 45 months, reference category)
0-24 months 1.46**
(0.38) 1.48**
(0.39)
25-45 months 0.901
(-0.10) 0.902
(-0.10)
Source of Information (No,reference)
Listen to radio 1.215
(0.19)
Watch TV 0.663***
(-0.41)
Read News Paper 0.438
(-0.82)
-2 Log likelihood 6739.90 6686.83 6126.37 6127.18 6109.99 6100.51 6095.12 5890.98 5862.54
Note: coefficient values are reported below the odd ratios. *P<0.001, ** P<0.05, *** P<0.01.
Anwar et al
82
(model 4 to 7) secondary education has significant
effect on child nutritional status while primary
education of mothers has less effect on child health. In
model 8, when birth parity and child birth interval are
controlled for and source of information was included
(model 9) as a proxy for awareness, secondary school
and above level of mother education decreases the
likelihood of stunting by approximately 35 percent
compared to those mother having no educational status.
However, the effect of mothers’ primary education and
child nutritional status got weaker and insignificant
after controlling for source of information (model 9).
Household wealth index and better environment index
are main contributing factors in explaining child health
status. These results support the findings of Benta et al.
(2011), Frost et al. (2005) and Desi and Alva (1998).
Socio-economic status is the primary pathway
explaining the effect of maternal education on child
nutritional status, but modern health care utilization
services and health knowledge also explain the effect of
maternal education on child health. In reproductive
behavior, birth order and birth interval has some
influence on child health status. Watching television is
connected with less likelihood of children being
stunted. This means that watching television is an
important source for broadcasting public health
campaign in Bangladesh. On the basis of our result we
can conclude that maternal education not only improve
socioeconomic condition but also transform behavior
from traditional and fatalistic view of health care to the
acceptance and utilization of modern health care
services. Still in our final model, maternal secondary
education has significant influence on child nutritional
status.
We find insignificant effect of mothers’ empowerment
on child health status. This result supports the findings
of Benta et al. (2011). The reason for insignificance
effect of women empowerment on child health status is
the lack of direct measures of this variable in BHDS
dataset. Further this variable requires other household
conditions like better socioeconomic conditions, wealth
and better education of child father to facilitate these
facilities as being traditional developing country this is
important in south Asian culture. This result is totally in
contradiction to Gupta (1990) who pointed out those
personality characteristics and abilities of mother
influence child health status are independent of
education and wealth status. She also said that mothers
with strong will and decision making power in
household matters have children with better health
status. Simon et al. (2002) concluded that mothers
having greater power in household matters can better
utilize the resources to meet the nutritional needs of
their children.
Conclusions
In this study, we used the Bangladesh Demography and
Health Survey (BDHS) data to estimate the effect of
maternal education on child nutritional status (measured
by stunting/ height for age) through various pathways
like socioeconomic status, health knowledge, and
attitude toward modern health care services, women
autonomy and reproductive behavior. Results estimated
by applying Binary Logistic regression models
explained that socioeconomic status, attitude toward
modern health care and health knowledge are important
pathways in explaining the effect of maternal education
on child health. In reproductive behavior birth interval
(25-45 months) has significant effect on child health
status. Estimated results overall suggest that maternal
education can influence child nutritional status by
improving health knowledge, reproductive behavior and
using modern health care services.
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... Senarath et al. (2012) highlighted the significance of feeding in young children. The importance of maternal education and its linkage with child's nutrition status was discussed by Anwar et al. (2013). ...
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The bright future of any society is always associated with its upcoming genera- tion. Children are the future prosperity of any nation as they are productive workers of tomorrow. The main objective of this study is to estimate the opportunities avail- able for children under age of 5 years and their mothers for different regions of Paki- stan and Bangladesh. The core idea of this study is to access and compare Pakistan with Bangladesh as it was previously a poor and struggling part of it. Data of this study are gathered from Bangladesh Demographic Health Survey and Pakistan Demographic Health Survey for the year 2017–18. The overall comparison of Pakistan and Bangladesh had put Pakistan in a situation where it lagged in every aspect of health-related facili- ties provided to its citizen. Governments should focus on providing economic oppor- tunities, Health, education, and nutrition to enhance regional and area-level living standards. Further, rural areas should be more focused, especially by the Government of Pakistan.
... Furthermore, the results indicate that a mother's low educational attainment increases her child's probability of being underweight. Children of educated women have significantly lower risks of being underweight due to their access to better career and good payment benefits [54], [55]. This has significant ramifications for undernutrition in children and emphasizes the necessity of raising women's educational attainment to improve child health outcomes in underdeveloped nations [56], [57]. ...
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Childhood undernutrition remains a critical global health challenge with far-reaching consequences. This study developed and compare predictive models for three key indicators of under-five child undernutrition in Nigeria: stunting, wasting, and underweight. By leveraging various machine learning (ML) algorithms, we identified the most significant socio-demographic determinants of these nutritional outcomes. The study utilizes data from the Nigerian Multiple Indicator Cluster Survey (MICS6) 2021, a comprehensive nationwide survey. Four ML algorithms were employed to predict the risk factors for the under-5 child nutritional status: k-nearest neighbors (KNN), random forest (RF), decision tree (DT), and logistic regression (LR). These models were evaluated and compared based on their predictive performance. The study encompasses households across Nigeria, providing a broad representation of the country's diverse population. Preliminary analysis reveals significant regional disparities in the prevalence of stunting, wasting, and underweight among Nigerian children. Among the four ML algorithms tested, the KNN model demonstrated superior predictive capability across all evaluation metrics, including accuracy (89.65%, 95.00%, 80.04%), precision (91.02%, 87.79%, 93.53), recall (99.98%, 100%, 100%), and F1-score (94.44%, 98.83%, 88.60%). This outperformance was consistent for all three undernutrition indicators. The KNN model, identified as the most effective predictor, highlighted several key determinants of childhood undernutrition. These factors varied somewhat across the three outcomes but commonly included: household wealth index, geopolitical zone, source of drinking water, child age, birth size, mother's education level, and residential area (urban/rural) among others. This study demonstrates the efficacy of machine learning approaches, particularly the KNN algorithm, in predicting and understanding the determinants of children undernutrition in Nigeria. The findings provide valuable insights for targeted interventions and policy formulation. These results can inform evidence-based decision-making and resource allocation in Nigeria's efforts to improve child nutrition and achieve related Sustainable Development Goals.
... Among the 56 studies included in this review, the largest proportion of studies were conducted in Bangladesh (n = 20 studies) (Akram et al., 2018;Anwar et al., 2013;Bhowmik & Das, 2017Das & Hossain, 2008;Das & Rahman, 2011;Das et al., 2020;Goyal & Canning, 2018;Huda et al., 2018;Islam & Biswas, 2020;Kamal & Moniruzzaman, 2021a;Khan & Gulshan, 2020;Khan & Raza, 2014;Khan et al., 2021;Mozumder et al., 2000;Rayhan & Khan, 2006;Siddiqi et al., 2011;Sultana et al., 2019;Talukder, 2017;Talukder et al., 2018). ...
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... All of these elements work together to establish the relationship between parents' education and the nutritional status of their children. The present study uses the conceptual framework (with some additions and amendments) of Anwar et al. (2013) as a base for its analysis. ...
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... Result also shows that due to a change in the composition from the illiterate level to the higher level may play important role. Previous studies confirm our finding that the educational level of the mother is significantly associated with child undernutrition [21,22]. It may be due to the reason that educated mothers have sufficient knowledge about child care, and are empowered to make better health decisions for their children. ...
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... As such, Africa is lagging in improving child nutrition due to many factors including inadequate healthcare (Salm et al., 2021), and illiteracy (Kumeh et al., 2020). Given the bond between a mother and a child, which suggests that maternal characteristics can affect childhood health conditions, extant studies have shown that a mother's education has a positive effect on child health and in reducing the rate of child malnutrition globally (Abuya et al., 2012;Anwar et al., 2013;Fadare et al., 2019;Iftikhar et al., 2017;Makoka, 2013). Low maternal education may result in child wasting, stunting, and overweight or underweight among African children (Akombi et al., 2017). ...
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Aim: This study examined the nexus between mother's education and nutritional status and their relationships with child stunting, wasting, underweight, and overweight. Methods: The data of 34,193 under-five (U-5) children from the 2018 Nigeria Demographic and Health Survey (NDHS) were analyzed using descriptive statistics, and binary and complementary log-logistic regression models. Results: The prevalence of child stunting, wasting, underweight, and overweight were 36.51%, 6.92%, 21.73%, and 2.05%, respectively. Compared to children born to mothers with at least secondary education, uneducated women's children (odds ratio (OR) = 1.55; 95% confidence interval (CI) = 1.32–1.82) and those of women with primary education (OR = 1.49; 95% CI = 1.28–1.72) were more likely to be stunted. Similarly, children born to uneducated women (OR = 1.51; 95% CI = 1.24–1.83) were more likely to be underweight than women with at least secondary education. The likelihood of child underweight (OR = 1.71; 95% CI = 1.45–2.01) and wasting (rate ratio (RR) = 1.82; 95% CI = 1.47–2.26) were higher among underweight mothers, respectively, than those with normal body mass index (BMI). The likelihood of child stunting (OR = 0.75; 95% CI = 0.67–0.84) and underweight (OR = 0.66; 95% CI = 0.57–0.77) were lower among obese/overweight mothers compared to those with normal BMI, but their children were more likely to be overweight (RR = 1.77; 95% CI = 1.27–2.48). Conclusion: Attainment of higher education by mothers should be promoted to prevent childhood nutritional imbalances, and sensitization on healthy dietary habits and lifestyles should be promoted among women, especially the overweight/obese, to reduce their risk of having overweight children.
... This association remained strong even after adjusting for other woman-and household-level characteristics including wealth. The positive impact of women's education on acceptance and utilization of nutrition, hygiene, and other health services has also been reported in many studies across multiple contexts [63][64][65][66][67][68]. In our study population, a higher level of education might help women understand the importance of safe food hygiene practices for their children's health and thus to adopt promoted behaviors. ...
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Background Microbial food contamination, although a known contributor to diarrheal disease and highly prevalent in low-income settings, has received relatively little attention in nutrition programs. Therefore, to address the critical pathway from food contamination to infection to child undernutrition, we adapted and integrated an innovative food hygiene intervention into a large-scale nutrition-sensitive agriculture trial in rural Bangladesh. In this article, we describe the intervention, analyze participation and uptake of the promoted food hygiene behaviors among intervention households, and examine the underlying determinants of behavior adoption. Methods The food hygiene intervention employed emotional drivers, engaging group activities, and household visits to improve six feeding and food hygiene behaviors. The program centered on an ‘ideal family’ competition. Households’ attendance in each food hygiene session was documented. Uptake of promoted behaviors was assessed by project staff on seven ‘ideal family’ indicators using direct observations of practices and spot checks of household hygiene conditions during household visits. We used descriptive analysis and mixed-effect logistic regression to examine changes in household food hygiene practices and to identify determinants of uptake. Results Participation in the food hygiene intervention was high with more than 75% attendance at each session. Hygiene behavior practices increased from pre-intervention with success varying by behavior. Safe storage and fresh preparation or reheating of leftover foods were frequently practiced, while handwashing and cleaning of utensils was practiced by fewer participants. In total, 496 of 1275 participating households (39%) adopted at least 5 of 7 selected practices in all three assessment rounds and were awarded ‘ideal family’ titles at the end of the intervention. Being an ‘ideal family’ winner was associated with high participation in intervention activities [adjusted odds ratio (AOR): 11.4, 95% CI: 5.2–24.9], highest household wealth [AOR: 2.3, 95% CI: 1.4–3.6] and secondary education of participating women [AOR: 2.2, 95% CI: 1.4–3.4]. Conclusion This intervention is an example of successful integration of a behavior change food hygiene component into an existing large-scale trial and achieved satisfactory coverage. Future analysis will show if the intervention was able to sustain improved behaviors over time and decrease food contamination and infection.
... We study whether the health system has a strengthening/weakening effect on the association of maternal education with child health outcomes in the Indian context, where the health system is still in a transitioning phase of improvement. In line with the existing literature, we find that mother's education has a positive impact on child death and child anaemia (Abuya et al., 2011;Emina et al., 2011;Kamal, 2012;Anwar et al., 2013;Gunes, 2015;Onsomu et al., 2015;Forshaw et al., 2017;Mandal et al., 2019). A better health care system helps to improve child health (Fay et al., 2005;Datar et al., 2007;Kuhnt and Vollmer, 2017). ...
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Global evidence suggests that maternal education is a crucial determinant of a child's health. The health system moderates the maternal education and child health relationship. However, there is sparse evidence on which direction health system moderates this relationship, especially in developing nations because of limited data availability. In order to address this gap in the evidence, we study this question in the Indian context, where the health system is still in a transitioning phase. We use two nationally representative surveys, the fourth round of the National Family Health Survey (2015–16) and the fourth round of the District Level Health Survey data (2012–13), to estimate the effects of maternal education and the health care system on child death and child anaemia. We map district-level data on health infrastructure and human resources information with individual-level information on health outcome, insurance, and antenatal care coverage along with other socio-economic characteristics. In accordance with global evidence, we find that maternal education remains an important determinant of child health outcomes in India too. However, the association between maternal education and child health outcomes weakens in the presence of a poor health care system. Health system improvement first benefits the already privileged in the Indian context. Yet, it should not hinder the policy focus either on the improvement of women's education or the medical care system.
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According to data from Demographic and Health Surveys for nine Latin American countries, women with no education have large families of 6-7 children, whereas better educated women have family sizes of 2-3 children, analogous to those of women in the developed world. Despite these wide differentials in actual fertility desired family size is surprisingly homogeneous through-out the educational spectrum. While the least educated and the best educated women share the small family norm, the gap in contraceptive prevalence between the two groups ranges from 20-50 percentage points. Better educated women have broader knowledge, higher socioeconomic status and less fatalistic attitudes toward reproduction than do less educated women: Results of a regression analysis indicate that these cognitive, economic and attitudinal assets mediate the influence of schooling on reproductive behavior and partly explain the wide fertility gap between educational strata.
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In this paper the behavioural factors which make for continuing high levels of child mortality in rural Punjab, despite favourable conditions in terms of nutrition, income, women's literacy and health care facilities are examined. A major factor is that inadequate attention has been paid to improved health care practices within the home. Women's autonomy, social class, and mothers' education significantly influence child survival. One of the pathways by which mothers' education affects child survival is through improved child care. In this society, a woman's autonomy is lowest during that part of her life-cycle which also contains her peak childbearing years: this perverse overlap raises child mortality. The risk of dying is distributed very unevenly amongst children, as the majority of child deaths are clustered amongst a small proportion of the families. The death-clustering variable remained significant even after several possible biological and socio-economic reasons for clustering had been controlled. It is argued that this clustering of deaths is partly due to the poor basic abilities of some mothers and other carers.
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The main purpose of this study is to observe the influencing factors on infant and child mortality of suburban and rural areas of Rajshahi District, Bangladesh. Primary data have been used to examine the differential patterns of infant and child mortality. A multivariate technique is employed to investigate the effects of those variables both socioeconomic and demographic on infant and child mortality. The study results reveal that several socioeconomic, demographic and health related variables affect on infant and child mortality. Multivariate analysis results indicate that the most significant predictors of neonatal, post-neonatal, and child mortality levels are immunization, ever breastfeeding, mother's age at birth and birth interval. Again, the risk of child mortality is 78.20% lower among the immunized child than never immunized child and also the risk of neonatal mortality is 57.70% lower after a birth interval of 36 months and above than under 18 months. Parents' education, toilet facilities and treatment places are significant predictors during neonatal and childhood period but father's occupation is significant at post-neonatal periods. For instance, risk of neonatal mortality is 31.40% lower among the women having primary education and 52.30% lower among the women having secondary and higher education than those having no education. It is observed that the risk of child mortality 32.00% lower among the household having hygienic toilet facility than those who have not such facilities. Similarly, risk of child mortality decreased with increased female education and wider access to safe treatment places. So, attention should be given to female education and expansion of public health system for reducing the risk of infant and child mortality.
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It is known that women who have been to school lose fewer of their children in childhood and infancy than their unschooled peers. It is not known why this should be so either in terms of the impact of education on women's behavior in general or in terms of their specific contribution to their children's health. The relationship between women's economic and other roles and the survival of their children remains even more uncertain. What is needed is much more pragmatic investigation of the intermediate factors involved, for it is these factors that are most amenable to policy intervention in the short and medium term. Finally, while there is an urgent need for information on the exact nature of the maternal behaviours associated with increased child survival, attributing the blame for high mortality levels directly to mothers should be warily considered.-from Author
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The debate between those who see economic development and those who regard advances in medical technology as bearing major responsibility for mortality decline usually gives little attention to different stages of social change when economic or medical conditions are fixed. However, Nigerian statistics analyzed here show that very different levels of child survivorship result from different levels of maternal education in an otherwise similar socio-economic context and when there is equal access to the use of medical facilities. Indeed, maternal education in Nigeria appears to be the single most powerful determinant of the level of child mortality. The statistics come from two surveys undertaken in 1973: one of 6,606 women in Ibadan city, and the other of 1,499 women in a large area of south-west Nigeria. Proportions of children surviving are compounded into an index of child mortality to increase the frequencies in individual cells and standardize maternal age when child survivorship is correlated with a range of factors, and two component indices are also constructed to detect change over time. It is concluded that women's education in societies like that of the Yoruba in Nigeria can produce profound changes in family structure and relationships, which in their turn may influence both mortality and fertility levels. Education may well play a major role in the demographic transition and this role may help to explain the close timing of mortality and fertility transitions.
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The study aimed at identifying the crucial psycho-social factors in the child's immediate environment in the poverty context, that influence child survival and health. Secondary data on 200 infants (0-36 months) and their families were analysed. The data base included information on 51 environmental, familial, maternal and child related factors and 3 dependent variables, namely, child mortality, infant morbidity and nutritional status. Data on infant morbidity and nutritional status were analysed by age and gender. The analyses involved step-wise multiple regression and formulation and testing of the best fit predictor equation. Factors associated with child mortality presented the clearest picture in terms of maximum amount of variance explained with a minimum set of predictor variables (74 per cent of the variance explained by 11 variables). The crucial variables associated with child mortality and infant morbidity were related to feeding practices, family composition, mother's education or highest education in the family and immunisation.
Book
Women's access to education has been recognized as a fundamental right. At the national level, educating women results in improved productivity, income, and economic development, as well as a better quality of life, notably a healthier and better nourished population. It is important for all kinds of demographic behaviour, affecting mortality, health, fertility, and contraception, The personal benefits that women attach to education vary widely according to region, culture, and level of devlopment, but it is clear that educaiton empowers women, providing them with increased autonomy and resulting in almost every context in fewer children. Beyond these few general assertions, however, there is little consensus on such issues as how much education is required before changes in autonomy or reproductive behaviour occur; whether the education-autonomy relationship exists in all cultural contexts, at all times, and at all levels of development; and which aspects of autonomy are important in the relationship between education and fertility. It is in the need to address these fundamental issues that this book took shape. The author reviews the considerable evidence about education and fertility in the developing world that has emerged over the last twenty years, and then passes beyond the limits of previous studies to address three major questions: BL Does increased education always lead to a decrease in the number of children, or is there a threshold level of education that a woman must achieve before this inverse relationship becomes apparent? BL What are the critical pathways influencing the relationship of women's education to fertility? Is fertility affected because education leads to changes in the duration of breast-feeding? Because it raises the age at marriage? Because it increases the practice of contraception? Or because education reduces women's preferences for large numbers of children? BL Do improvements in education empower women in other areas of life, such as their improving exposure to information, decision-making, control of resources, or confidence in dealing with family and the outside world? Supported by full documentation of the available survey data, this study concludes that such contextual factors as the overall level of socio-economic development and the situation of women in traditional kinship structures complicate the general assumptions about the interrelationships between education, fertility, and female autonomy. It lays out the policy implications of these findings and fruitful directions for future research.