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VIETNAM – THE NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
THE ROLE OF MATERNAL EDUCATION IN
CHILD HEALTH: EVIDENCE FROM CHINA
BY
NGUYEN THI HONG CAM
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
HO CHI MINH CITY, December 2017
UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM
ERASMUS UNIVERSITY ROTTERDAM
INSTITUTE OF SOCIAL STUDIES
THE NETHERLANDS
UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM
INSTITUTE OF SOCIAL STUDIES
THE HAGUE
THE NETHERLANDS
VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
THE ROLE OF MATERNAL EDUCATION IN
CHILD HEALTH: EVIDENCE FROM CHINA
A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
By
NGUYEN THI HONG CAM
Academic Supervisor:
VO TAT THANG
HO CHI MINH CITY, December 2017
i
DECLARATION
“I certify the content of this dissertation has not already been submitted for any degree
and is not being currently submitted for any other degrees. I certify that, to the best of my
knowledge, any help received in preparing this dissertation and all source used, have been
acknowledged in this dissertation.”
Signature
Nguyen Thi Hong Cam
Date: 1 January, 2018
ii
ACKNOWLEDGEMENT
Foremost, I would like to express my sincere gratitude to my supervisor Dr. Vo
Tat Thang, for his patience, motivation, enthusiasm, sympathy, immense knowledge,
and for giving me valuable advice. His guidance helped me at all the time of research
and writing of this thesis.
In addition, I would like to thank Prof. Nguyen Trong Hoai, Dr. Pham Khanh
Nam and Dr. Nguyen Luu Bao Doan who have their expertise view with me, the
valuable experience in research, and Dr. Truong Dang Thuy who has provided the
practical econometric technique, a valuable knowledge in research.
Furthermore, I would also like to thank all lecturers and staff at the Vietnam
Netherlands Program who already supported me wholeheartedly during my studying
time in there.
In particular, I would like to express my gratitude and affection towards my
family for providing me with unfailing support and continuous encouragement
throughout my years of study. My sincere thanks to all members in K22, who always
devotes all love and all the best interest for me. I am grateful for my best friends in
encouraging me to start the thesis, persevere with it and finally to complete it. They
always beside by me during difficult moment and sharing ups and downs with me and
making my burdens lighter.
Finally, I take this opportunity to express gratitude to Dr. Bach Nguyen. I am
extremely thankful and indebted to him for sharing expertise, and sincere and valuable
guidance and encouragement extended to me.
iii
ABSTRACT
Children healthcare and gender discrimination are a real challenge to China in the
process of achieving its Millennium Development Goals (MDGs). In this study, we
investigate the influence of mothers’ education on the health status of their children in the
context of China. The data are derived from the China Family Panel Studies (CFPS) which
comprises information from 16,000 households and individuals collected from 25 provinces
across China except for autonomous zones. The result shows that maternal education strength
affects children’s health, and household wealth as well as gender and living area slightly
impact on child health. The study is one of the first research to estimate the influence of
maternal education on child health by quantile regression while the historical papers used
OLS or fixed effect to research those influences. Quantile regression is employed to analyze
the impacts of mothers’ education on child health under different quantiles of the child’s
body index variable.
JEL classification: I14, I24
Keywords: Child health, maternal education, household wealth, BMI, China.
iv
TABLE OF CONTENTS
DECLARATION i
ACKNOWLEDGEMENT ii
ABSTRACT iii
TABLE OF CONTENTS iv
LIST OF TABLES vi
LIST OF FIGURES vii
CHAPTER 1. INTRODUCTION 8
1.1. Research problem 8
1.2. Research objective 10
1.3. Scope of the study 11
1.4. Contributions 11
1.5. Thesis structure 11
CHAPTER 2. LITERATURE REVIEW 12
2.1. Theoretical background 12
2.2. Empirical reviews 15
2.2.1. The impact of maternal education on child health 15
2.2.2. The role of household wealth 19
2.2.3. The effect of development economic on health 20
2.3. Summary 21
CHAPTER 3. RESEARCH METHODOLOGY and DATA RESOURCES 22
3.1. Analytical framework 22
3.2. Econometric models 23
3.3. The constructed model 25
3.4. Data descriptions 28
3.4.1. The background of data set 28
3.4.2. Characteristics 28
3.4.3. Core module 29
v
3.4.4. Process 29
CHAPTER 4. EMPIRICAL RESULTS 31
4.1. Data description 31
4.2. Empirical results 33
4.2.1. Maternal education 33
4.2.2. Household wealth 34
4.2.3. Gender and living area 34
CHAPTER 5. CONCLUSIONS AND POLICY IMPLICATIONS 41
5.1. Conclusions 41
5.2. Policy implications 42
5.3. Limits of the study 42
REFERENCES 44
APPENDIX 47
List of variables using in data set 47
vi
LIST OF TABLES
Table 1: Descriptive variables 32
Table 2: Correlation within variables 35
Table 3: OLS estimates of determinants of child weight and height 37
Table 4: Quantile regression for Child Weight and Height 38
Table 5:Simultaneous quantile regression results of Child BMI 39
Table 6:Simultaneous quantile regression of child weight for age on all covariates 40
Table 7: Quantile regression for Child BMI 48
vii
LIST OF FIGURES
Figure 1: Bronfenbrenner’s Ecological systems theory 12
Figure 2: The linkage between maternal education and child health (UNICEF, 1998) 22
8
CHAPTER 1. INTRODUCTION
1.1. Research problem
Nowadays, improving women and children healthcare is the goal of
development for global economies. In assessing the level of children development, the
health of child is used as a major indicator for child development (WHO, 2004), thus
indirectly imposing child health as a key factor to determine the level of economic
development.
Women education plays an important role in child health, especially in
developing countries. Caldwell (1979) supported that maternal education is the most
crucial factor in different child health outcomes. The recent trend in governmental
policy making is to use resources (generated by economic development) to invest in
education. When the level of education is improved, parental care-giving is advanced
which shall indirectly lead to an improvement in child health.
However, education is not the only factor impacting parenting and child health.
Child health is affected by other determinants such as paternal education, health
service availability, and socioeconomic status (Trussell et al. 1983 and Edmonston et
al., 1983). (Dong et al., 2010) indicated that the relation between economic growth
and household wealth is positive, thus implying that the maternal health and parental
care-giving can be improved through resources and services. It can be concluded that
wealth production is the pathway through which economic development can leave
positive effect on parental care-giving and child health.
Developing countries tend to have a concave association between child health
and household wealth. Evidences from developing countries have shown that
household wealth and child health tend to have a concave association since the
diminishing returns to life expectancy is linked to the growth of income (Belli et al.,
2002). Both household wealth and maternal education are the pathways for economic
development process and child health benefits (Stewart et al., 2000). Furthermore,
many of these strategies are interdependent so researchers can analyze the influence of
9
each variable on child health to find out the magnitude of each strategy toward child
health and women’s education policy within the host country.
On the other hand, many studies concerned about the effect of environment and
social contexts on child health. For example, local health environment has significant
contribution toward child health (Glewwe, 1999). However, the relation between
household wealth and child health was less evident by current research. In 2000,
Wagstaff estimated the levels of household consumption related with child mortality.
The result shows that three over nine developing countries have no relationship
between five levels of household exhaustion and mortality. In addition, political
context is another important factor that impacts child health. Based on evidence from
22 developing economies, the analysis concluded that the relationship between
maternal education and child height for age is significant in cross-national
discrepancies (Desai and Alva, 1998).
However, developing countries are still facing other vital issues such as
inequality in income as well as unbalanced healthcare and poor living conditions in
rural areas. Many recent research evaluated the relation between maternal education
and child health in developing countries because of difficult challenge in development
progress. The important issue in developing countries is gender discrimination
(Pearson, 1995), regional diversity result in health inequality (Dong et al., 2010).
Gender discrimination is the most critical issue that effect parental care-giving,
especially in China. Male members can earn more money in compare to their female
counterparts; thus, the rights of women within the household are misappropriated
(Anker and Hein, 1985) even though many evidences show that women also
contributed to the labor force. In addition, parental education has strong effect on
child health, but the impact of maternal education is greater than the effect of father’s
education (Peng et al., 2006).
China is considered the world’s most populated and the second largest
developing country. As a result, the Chinese government faces many difficulties and
challenges on its developing process. One of the first challenges for the Chinese
government is to improve child health and woman health progress, which have
10
achieved more significant achievements over the past decades in China. The gap in
infant and maternal mortality ratios between urban and rural areas is still large
although these rates have been reduced to lower levels in recent years. Looking at the
case of Western China, the most important law in the West of China is that the
qualities of the human population must always be increased. That is the reason the
Chinese authorities distributes teaching role and management for each level based on
a hierarchical network of maternal and child health services.
The second development challenge for China is the unbalanced gender ratio
and inequality household income. In China, the number of women employed in
fulltime jobs could be limited because the employers prefer male employees than by
women (due to their child-care obligations). Many rural Chinese households are stem
families, in which three generations live under the same roof. The adult-to-child ratio
in these families is quite large since Chinese birth control policies in the past limit the
number of children for each couple to one. In addition, gender discrimination is one of
the the most critical issues in urban China (Feng et al., 1992).
The larger the size of the production market, the more competitive between
firms to attain skilled and experienced workers. A greater number of private and
collective firms instead of state-owned firms indicates a greater population of
companies competing with one another for resources. As the result, labor markets will
be more developed in regions and localities that have more developed commodity and
production markets. It could be argued that labor markets for non-agricultural work
are simply a functional level of industrialization, since in the absence of industry the
only source of employment for rural people is agriculture and small-scale commerce.
As a result, the Chinese society created the household income inequality.
1.2. Research objective
This dissertation focuses on analyzing the influence of the level of women
education (mother) on child health, with controlling the effect of economic growth,
household wealth and father’s educational level as well as heredity factors and
children gender.
Consequently, the main objectives are considered consist of:
11
First, analyzing the relation between body mass index of both children and
their parent and parent’s education level.
Second, estimating the household wealth association with child health.
Third, evaluating how the influence of gender discrimination as well as
economy of living area.
1.3. Scope of the study
The thesis analyses the interaction between mother’s education and child
health, which is measured by the children’s body mass index (BMI) is calculated by
the ratio of height of age and the weight of age. Moreover, the study controls external
factors consist of environment, household income, the educational father, heredity
factors, age and gender of children. The research in term of 25 provinces in China in
2014.
1.4. Contributions
The role of maternal education in child health is the important empirical
results.
The study uses China Family Panel Studies (CFPS) data while the lack of
papers used that data set.
The thesis is the first study to estimate the effect of maternal education on child
health using quantile regression. A number of recent researches examined those
influence by multilevel modelling (Boyle et al., 2006), fixed-effect and random-effect
(Desai and Alva, 1998).
The body mass index for the analysis was objectively measured, reducing
possible misclassification, although there a number of papers examined the child
health through either the weight of age or the height of age of children.
1.5. Thesis structure
The paper is organized as follows. Chapter II is Empirical studies which briefly
reviewed the recent literature. Then, details estimation strategy in chapter III. After
that, chapter IV will analyze the current the data and determine the empirical results.
Finally, conclusion and implication policy are included in chapter V.
12
CHAPTER 2. LITERATURE REVIEW
2.1. Theoretical background
Children health is a part of children development researches. The thesis based
on two theoretical frameworks.
Ecological systems theory: This theory looks at a child’s development within
the context of the system of relationships that form his or her environment.
Bronfenbrenner’s theory defines complex “layers” of environment, each having an
effect on a child’s development. This theory has recently been renamed “bioecological
systems theory” to emphasize that a child’s own biology is a primary environment
fueling their development. The interaction between factors in the child’s maturing
biology, their immediate family or community environment, and the societal
landscape fuels and steers its development. Changes or conflict in any one layer will
ripple throughout other layers. To study a child’s development then, we must look not
only at the child and her immediate environment, but also at the interaction of the
larger environment as well.
Figure 1: Bronfenbrenner’s Ecological systems theory
Chronosystem
Macrosystem
Exosystem
Mesosystem
Microsystem
Child
13
Bronfenbrenner’s theory includes the following layers:
First, the microsystem is the layer closest to the child and contains the
structures with which the child has direct contact. The microsystem encompasses the
relationships and interactions a child has with her immediate surroundings (Berk,
2000). Structures in the microsystem include family, school, neighborhood, or
childcare environments. At this level, relationships have impact in two directions -
both away from the child and toward the child. For example, a child’s parents may
affect his beliefs and behavior; however, the child also affects the behavior and beliefs
of the parent. Bronfenbrenner calls these bi-directional influences, and he shows how
they occur among all levels of environment. The interaction of structures within a
layer and interactions of structures between layers is key to this theory. At the
microsystem level, bi-directional influences are strongest and have the greatest impact
on the child. However, interactions at outer levels can still impact the inner structures.
Second, the mesosystem is the layer provides the connection between the
structures of the child’s microsystem (Berk, 2000). Examples: the connection between
the child’s teacher and his parents, between his church and his neighborhood, etc.
Third, the exosystem is the layer defines the larger social system in which the
child does not function directly. The structures in this layer impact the child’s
development by interacting with some structure in her microsystem (Berk, 2000).
Parent workplace schedules or community-based family resources are examples. The
child may not be directly involved at this level, but he does feel the positive or
negative force involved with the interaction with his own system.
After that, the macrosystem is layer may be considered the outermost layer in
the child’s environment. While not being a specific framework, this layer is comprised
of cultural values, customs, and laws (Berk, 2000). The effects of larger principles
defined by the macrosystem have a cascading influence throughout the interactions of
all other layers. For example, if it is the belief of the culture that parents should be
solely responsible for raising their children, that culture is less likely to provide
resources to help parents. This, in turn, affects the structures in which the parents
14
function. The parents’ ability or inability to carry out that responsibility toward their
child within the context of the child’s microsystem is likewise affected.
Finally, the chronosystem which is a system encompasses the dimension of
time as it relates to a child’s environments. Elements within this system can be either
external, such as the timing of a parent’s death, or internal, such as the physiological
changes that occur with the aging of a child. As children get older, they may react
differently to environmental changes and may be more able to determine more how
that change will influence them.
From Bronfenbrenner’s (1986) ecological theory, these factors include
maternal education (microsystem level), maternal and family involvement in
children’s home activities (microsystem level), maternal and family involvement in
children’s school activities (mesosystem level), and the social support (exosystem
level).
Also, the ecological theory views child outcomes as dependent upon the
characteristics of the child, parent, family, school, community, and larger society, as
well as the interactions among these variables. However, some researchers have
argued that this traditional ecological framework is limited because it does not
adequately consider variables such as social position (e.g., social class, ethnicity, race,
and gender), social stratification (e.g., racism, prejudice, discrimination, and
segregation), and adaptive culture (e.g., traditions and cultural legacies, migration and
acculturation, economic and political histories) experienced by family members of
color who are born in the United States or other countries. To address this problem,
Garcia Coll et al. (1996) proposed an integrative model to study the development of
competence in children of color, by considering both social position and social
stratification constructs at the core rather than at the periphery of a theoretical
formulation of children’s development. In this model, the researchers address some
important factors omitted or neglected in mainstream ecological models, such as
experiences of racism and segregation, intragroup variability and diversity within
minority group families, and the effects of social stratification and acculturation on the
developmental competencies of minority group children.
15
Children inhabit both families and child-care microsystems, and these systems
are linked. Parents select particular types of child care, of varying quality, for children
of different ages—and these decisions vary with family structure, parental
characteristics, geographical location, and other factors. Singer, Fuller, Keiley, and
Wolf (1998) argued that child-care researchers must consider these selection effects if
they are to accurately model the impact of child care on children’s development over
time. In the research, the authors refer to the effects of family-level and community-
level factors on child-care.
In this study, the main hypothesis is that maternal education may affect
children health at least in the following two ways. First, women with more years of
education have higher production and allocation efficiencies in their children’s health
production (Grossman, 2006). Production efficiency means better health condition
with given health production input, while allocation efficiency means optimal
combination of different health inputs with given budget. Maternal education can raise
both production and allocation efficiencies, and thus improve children’s health.
Second, higher maternal education can also affect the amount of inputs of children’s
health production. More educated women have higher labor market income (labor
market effect) and “match” with better educated and higher income husbands
(assortative mating effect), while more family resources and better family
environment contribute to children’s health human capital accumulation (McCrary
and Royer, 2011).
2.2. Empirical reviews
2.2.1. The impact of maternal education on child health
The mother’s education in most of papers are measured by the number of year
of schooling.
The relation between mother’s education and child health has long been
supported by many evidences. Barrera (1990) researched the impact of mother’s
education on child health in which the indicator for good or bad child health is
determined by height – for – age scores. The regression result shows a positive effect
16
of maternal education on child nutritional outcomes. Also, mother’s education
improves children’s height – for – age.
Similarly, the effect of maternal education on three markers of child health is
examined in 22 developing countries (Desai and Alva, 1998). The markers of child
health consist of the probability of infant death, children’s height – for – age, and
immunization status. The ranking of level educational mother includes 2 levels,
mother not educated and secondary educational level. The result indicates that there is
a consistent association between mother’s education and infant mortality. Meanwhile,
the correlation between maternal education and children’s height – for – age is
positive and significant. Although the coefficient correlation of mother’s education on
immunization status is small, this effect is statistically significant in sample countries.
Moreover, the effect of mother’s schooling on child health is can also be seen
in the case of Morocco (Glewwe, 1999). The study also suggests that there is a
positive relationship between education and child health. However, in this case, the
evidences indicated that it is not only education but also the effect of household
wealth that leave an impact on child health.
The association of maternal education with child health may arise because
educated mothers are considered more efficient “producers” of good child health
(“productive efficiency”) by adopting better child-care practices or superior hygiene
standards. Alternatively, it could be because they choose health input mixes that
generate more health output (“allocative efficiency”) than selected by less-educated
mother.
Another studies used natural experiments to identify mother’s education-child
health relationship. Breierova and Duflo (2004) used the 1995 intercensal survey of
Indonesia and school data from the Sekolah Dasar program to investigate the impact
of parents’ education on fertility and child mortality. The results show a positive and
significant effect of the school program on parents’ education and a negative effect on
fertility. Both father’s and mother’s education were found to reduce child mortality.
The authors found little evidence to support the intuition that the mother’s education
effect is stronger than the father’s. Similarly, using a natural experiment from Taiwan
17
(a new compulsory education law), Chou et. al. found evidence of a causal
relationship between parents’ education and child health, but contrary to the previous
study, mother’s education was found to be stronger effect than father’s education. No
pathway investigation was attempted in either study.
Maternal education in child health functions may therefore be affected by
different factors (at the level education of the father, household welfare and place
where child born). A study by (Thomas, Strauss et al., 1990) in Brazil analyses the
role of income, mother’s literacy and information processing, and the interaction of
maternal schooling with community services. The authors find that for most of time
all the impact of maternal schooling on child height can be explained through
mother’s access to information (i.e. exposure to media).
Besides, some authors have found a significant effect of maternal education on
child health status while others argue that there is little or no evidence of a causal
relationship. For instance, Frongillo, de Onis, and Hanson (1997) ran cross-country
OLS regressions of child height-for-age (stunting) and weight-for-height (wasting) on
education variables, food security, geographic region and other variables. They found
that the female literacy rate had a significantly negative effect on stunting. The main
shortcoming of this study is that it did not address the heterogeneity in child health
endowment and did not use instrumental variables methods to address the endogeneity
of female literacy rate. While Martorell, Leslie, and Moock (1984) found no evidence
of an impact of parents’ education on child health outcomes. Baya (1998), using data
from a town in Burkina Faso, found that after controlling for father’s education, the
effect of mother’s education on child survival loses significance. He concludes that
studies on parents’ education and child health status should not focus on mother’s
education.
Handa (1999) examined six pathways through which mother’s education might
affect child health outcomes: income effects, interactions with household
characteristics, interactions with community services, information processing,
18
unobserved household heterogeneity1
, and intrahousehold bargaining power. Using
data from Jamaica, Handa found that information processing is found to be a pathway
through which mother’s education affects child health outcomes. Handa argued that he
was able to control for unobserved household heterogeneity. He used the fact that in
Jamaican households there are usually children from different mothers, and women in
the same household care for all children whether the children are their own or not.
This is questionable because there is likely to be mother heterogeneity. The other
limitations of this study include treating parents’ education as exogenous, and using
unobserved household heterogeneity as a pathway; it is really an estimation problem,
not a pathway.
Webb and Block (2004), using household survey data from Central Java,
Indonesia, found that a mother’s nutritional knowledge is a determinant of child short-
term nutritional status (weight-for-height) whereas her schooling is a determinant of
long-term nutritional status (height-for-age). These authors could not find plausible
instrumental variables for maternal nutritional knowledge and household
expenditures, so they used proxy variables to estimate reduced form equations for
child nutritional status. Webb and Block did not account for the possibility of omitted
variable bias that would result from the heterogeneity of child health endowment.
Appoh and Krekling (2005), using data from the Volta Region in Ghana, found that
mother’s nutritional knowledge is more important than mother’s schooling in
determining child weight–for-age. However, these authors accounted neither for the
simultaneity of inputs choices, nor the endogeneity of mother’s health knowledge.
After all, recent research on the relationship between maternal schooling and
child health has moved towards underpinning the ‘pathways’ in which mother’s
education translates into the improvement in child health. While a majority of the
evidence has not directly controlled for the endogeneity of maternal schooling,
introducing different ‘pathways’ is one way of isolating the ‘true’ impact of maternal
education from the effect of confounding factors. In a recent study, (Glewwe, 1999)
1
Correlation between mother’s education and unobserved household characteristics. Possible sources
of unobserved household heterogeneity: food preparation methods, knowledge of symptoms of ill health,
different minimum levels of acceptable sanitation and cleanliness, and different tastes for child health.
19
identifies three channels: 1) direct acquisition of basic health knowledge in school, 2)
literacy and numeracy skills learned in school and 3) exposure to modern society. The
study finds that mother’s health knowledge alone impacts child health outcomes.
According to (Boyle Racine et al., 2006), the linkages between maternal
education and child health is cross-national difference; child health risks are reduced
at higher levels of household wealth despite the unbalanced relationship between child
health and levels of education with the pattern of household wealth. However, this
research has some limitations, including the model is distributed with some
unnecessary variables for improving on policies in population health; the limited
regression for variation.
2.2.2. The role of household wealth
Household wealth plays an important role in child health. (Filmer and Pritchett,
1999) The construction of household wealth index includes the following indicators:
first, consumer durables (family owns a radio, television, bike or motorbike or car,
etc); second, drinking water sources; third, type of toilet; fourth, household has
electricity or not; fifth, the number of bed room; sixth, type of material for floor in
house. Some factors are used as control variables to analyze the effect of other factors
such as maternal education (Boyle, Racine et al., 2006)
Meanwhile, household wealth is measured by net worth, values of businesses
and private accounts (Shanks, 2007). The result shows that wealth is a relevant factor
associated with child development.
The effect of household wealth on child health is similar to the impact of
economic development level on child health. It can be explained that improving the
material status of the family and purchasing goods and services can lead to better
health. It can be considered that poverty is an important determinant of mortality and
poor health in all countries (Wagstaff, 2002). Furthermore, the evidence advocates
that there are likely to be positive monotonic relationships between household wealth
and child health in most developing countries (Gwatkin, 2000).
20
2.2.3. The effect of development economic on health
Following a number of previous studies, the level of regional economy is
measured by the income of a nation, particularly by GDP per capita based on
purchasing power parity. In some countries, there would be a negative relation
between life expectancy and income inequality (Preston, 1975). Surprisingly,
mortality rate in Jamaica is better than Brazil even though the country’s GDP per
capita is lower, which has mortality worse than expectation (Filmer and Pritchett,
1999).
The region inequality in health system was demonstrated in Lorenz curve and
Kuznets hypothesis (Fang Dong et al., 2010). The Lorenz curve shows that regional
health inequality in China is related to socioeconomic factors and health system. Also,
the Kuznets hypothesis to test the influence of GDP per capita on health distribution.
The result of testing of Kuznets hypothesis indicated that health inequality had not
reached its peak, meaning that China is still laying on the left side of the Kuznets
curve.
Deaton (2003) captured evidences for the association between national income
and health. The results indicate that GDP per capita is significantly related to the
probability of death in developed countries. Besides, the effect of income inequality
on health in developing countries is bigger than in developed countries. This study
used National Health Interview Survey (NHIS) with observation sample of
approximately 50,000 households in every year, the National Health and Nutritional
Examination Survey (NHANES) which surveyed more than 14,000 people in the first
round between 1971 and 1975, and the Panel Study of Income Dynamics (PSID)
which has followed around 5,000 households (and their children and split-offs) since
1968. The author used all data to find out the interaction among mortality, income,
and income inequality. A logit model was applied to estimate the log odds of death
during the ten-year follow up as a linear function of age including dummy variables
for each of the seven income groups. These logits are estimated for white males and
females separately, using data only for those aged 18 to 75 at the time of first
interview. (The log odds of mortality are approximately linear in age over this range.)
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21
In order to conduct a state-level analysis, each of these models is fitted to data for a
single state, thus allowing inequality or any other state-level produce an unrestricted
effect on the relationship between mortality and income. In findings, income
inequality becomes relatively more important as a cause of death at higher income
levels.
2.3. Summary
From the recent researches, the weight of age and the height of age are only
measured method for the health of children. However, I suggest BMI is an accuracy
health measurement to determine the child health.
In this study, the model organizes contexts of child health into 3 levels of
external influence, including the family impact the child health directly, the
environment elements and the physiological indirect affect child health.
A major factor affecting the limited research in China is the lack of papers
examining that issue. Furthermore, the study contributes to the literature as one of the
first research employing CFPS dataset. The availability of rich recent data from CFPS
allows us to overcome this gap in the literature.
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22
CHAPTER 3. RESEARCH METHODOLOGY and
DATA RESOURCES
3.1. Analytical framework
Figure 2: The linkage between maternal education and child health (UNICEF, 1998)
The conceptual framework guiding this study is based on the linkage between
maternal schooling, childcare, and the health of children. Above figure shows the
possible linkages between maternal education and child health that this study explores.
The possible pathway through which maternal education can affect the health of
children is through skill acquisition that leads to improved knowledge about
healthcare and parental knowledge. Therefore, it is expected that women with more
education are more aware of the benefits of feeding children at the appropriate times
and in right quantities, and preventing the BMI ‘s child overweight. These practices
can improve child health.
Numbers of studies have modeled the effects of maternal education on child
health outcomes through four non-excluded models: socioeconomic status, women
Maternal education
Maternal demographic
factors:
- Mother's education
- Mother's body index
- Time spending for child
Socioeconomic factors:
- Residence (urban or
rural)
- Household wealth index
- Husband's education
Child health factors:
- The weight of age
- The height of age
- The body mass index
Child demographic factors:
- Child sex
- Child age
6674506

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The role of maternal education in child health - evidence from China​.pdf

  • 1. VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE ROLE OF MATERNAL EDUCATION IN CHILD HEALTH: EVIDENCE FROM CHINA BY NGUYEN THI HONG CAM MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, December 2017 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ERASMUS UNIVERSITY ROTTERDAM INSTITUTE OF SOCIAL STUDIES THE NETHERLANDS
  • 2. UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE ROLE OF MATERNAL EDUCATION IN CHILD HEALTH: EVIDENCE FROM CHINA A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By NGUYEN THI HONG CAM Academic Supervisor: VO TAT THANG HO CHI MINH CITY, December 2017
  • 3. i DECLARATION “I certify the content of this dissertation has not already been submitted for any degree and is not being currently submitted for any other degrees. I certify that, to the best of my knowledge, any help received in preparing this dissertation and all source used, have been acknowledged in this dissertation.” Signature Nguyen Thi Hong Cam Date: 1 January, 2018
  • 4. ii ACKNOWLEDGEMENT Foremost, I would like to express my sincere gratitude to my supervisor Dr. Vo Tat Thang, for his patience, motivation, enthusiasm, sympathy, immense knowledge, and for giving me valuable advice. His guidance helped me at all the time of research and writing of this thesis. In addition, I would like to thank Prof. Nguyen Trong Hoai, Dr. Pham Khanh Nam and Dr. Nguyen Luu Bao Doan who have their expertise view with me, the valuable experience in research, and Dr. Truong Dang Thuy who has provided the practical econometric technique, a valuable knowledge in research. Furthermore, I would also like to thank all lecturers and staff at the Vietnam Netherlands Program who already supported me wholeheartedly during my studying time in there. In particular, I would like to express my gratitude and affection towards my family for providing me with unfailing support and continuous encouragement throughout my years of study. My sincere thanks to all members in K22, who always devotes all love and all the best interest for me. I am grateful for my best friends in encouraging me to start the thesis, persevere with it and finally to complete it. They always beside by me during difficult moment and sharing ups and downs with me and making my burdens lighter. Finally, I take this opportunity to express gratitude to Dr. Bach Nguyen. I am extremely thankful and indebted to him for sharing expertise, and sincere and valuable guidance and encouragement extended to me.
  • 5. iii ABSTRACT Children healthcare and gender discrimination are a real challenge to China in the process of achieving its Millennium Development Goals (MDGs). In this study, we investigate the influence of mothers’ education on the health status of their children in the context of China. The data are derived from the China Family Panel Studies (CFPS) which comprises information from 16,000 households and individuals collected from 25 provinces across China except for autonomous zones. The result shows that maternal education strength affects children’s health, and household wealth as well as gender and living area slightly impact on child health. The study is one of the first research to estimate the influence of maternal education on child health by quantile regression while the historical papers used OLS or fixed effect to research those influences. Quantile regression is employed to analyze the impacts of mothers’ education on child health under different quantiles of the child’s body index variable. JEL classification: I14, I24 Keywords: Child health, maternal education, household wealth, BMI, China.
  • 6. iv TABLE OF CONTENTS DECLARATION i ACKNOWLEDGEMENT ii ABSTRACT iii TABLE OF CONTENTS iv LIST OF TABLES vi LIST OF FIGURES vii CHAPTER 1. INTRODUCTION 8 1.1. Research problem 8 1.2. Research objective 10 1.3. Scope of the study 11 1.4. Contributions 11 1.5. Thesis structure 11 CHAPTER 2. LITERATURE REVIEW 12 2.1. Theoretical background 12 2.2. Empirical reviews 15 2.2.1. The impact of maternal education on child health 15 2.2.2. The role of household wealth 19 2.2.3. The effect of development economic on health 20 2.3. Summary 21 CHAPTER 3. RESEARCH METHODOLOGY and DATA RESOURCES 22 3.1. Analytical framework 22 3.2. Econometric models 23 3.3. The constructed model 25 3.4. Data descriptions 28 3.4.1. The background of data set 28 3.4.2. Characteristics 28 3.4.3. Core module 29
  • 7. v 3.4.4. Process 29 CHAPTER 4. EMPIRICAL RESULTS 31 4.1. Data description 31 4.2. Empirical results 33 4.2.1. Maternal education 33 4.2.2. Household wealth 34 4.2.3. Gender and living area 34 CHAPTER 5. CONCLUSIONS AND POLICY IMPLICATIONS 41 5.1. Conclusions 41 5.2. Policy implications 42 5.3. Limits of the study 42 REFERENCES 44 APPENDIX 47 List of variables using in data set 47
  • 8. vi LIST OF TABLES Table 1: Descriptive variables 32 Table 2: Correlation within variables 35 Table 3: OLS estimates of determinants of child weight and height 37 Table 4: Quantile regression for Child Weight and Height 38 Table 5:Simultaneous quantile regression results of Child BMI 39 Table 6:Simultaneous quantile regression of child weight for age on all covariates 40 Table 7: Quantile regression for Child BMI 48
  • 9. vii LIST OF FIGURES Figure 1: Bronfenbrenner’s Ecological systems theory 12 Figure 2: The linkage between maternal education and child health (UNICEF, 1998) 22
  • 10. 8 CHAPTER 1. INTRODUCTION 1.1. Research problem Nowadays, improving women and children healthcare is the goal of development for global economies. In assessing the level of children development, the health of child is used as a major indicator for child development (WHO, 2004), thus indirectly imposing child health as a key factor to determine the level of economic development. Women education plays an important role in child health, especially in developing countries. Caldwell (1979) supported that maternal education is the most crucial factor in different child health outcomes. The recent trend in governmental policy making is to use resources (generated by economic development) to invest in education. When the level of education is improved, parental care-giving is advanced which shall indirectly lead to an improvement in child health. However, education is not the only factor impacting parenting and child health. Child health is affected by other determinants such as paternal education, health service availability, and socioeconomic status (Trussell et al. 1983 and Edmonston et al., 1983). (Dong et al., 2010) indicated that the relation between economic growth and household wealth is positive, thus implying that the maternal health and parental care-giving can be improved through resources and services. It can be concluded that wealth production is the pathway through which economic development can leave positive effect on parental care-giving and child health. Developing countries tend to have a concave association between child health and household wealth. Evidences from developing countries have shown that household wealth and child health tend to have a concave association since the diminishing returns to life expectancy is linked to the growth of income (Belli et al., 2002). Both household wealth and maternal education are the pathways for economic development process and child health benefits (Stewart et al., 2000). Furthermore, many of these strategies are interdependent so researchers can analyze the influence of
  • 11. 9 each variable on child health to find out the magnitude of each strategy toward child health and women’s education policy within the host country. On the other hand, many studies concerned about the effect of environment and social contexts on child health. For example, local health environment has significant contribution toward child health (Glewwe, 1999). However, the relation between household wealth and child health was less evident by current research. In 2000, Wagstaff estimated the levels of household consumption related with child mortality. The result shows that three over nine developing countries have no relationship between five levels of household exhaustion and mortality. In addition, political context is another important factor that impacts child health. Based on evidence from 22 developing economies, the analysis concluded that the relationship between maternal education and child height for age is significant in cross-national discrepancies (Desai and Alva, 1998). However, developing countries are still facing other vital issues such as inequality in income as well as unbalanced healthcare and poor living conditions in rural areas. Many recent research evaluated the relation between maternal education and child health in developing countries because of difficult challenge in development progress. The important issue in developing countries is gender discrimination (Pearson, 1995), regional diversity result in health inequality (Dong et al., 2010). Gender discrimination is the most critical issue that effect parental care-giving, especially in China. Male members can earn more money in compare to their female counterparts; thus, the rights of women within the household are misappropriated (Anker and Hein, 1985) even though many evidences show that women also contributed to the labor force. In addition, parental education has strong effect on child health, but the impact of maternal education is greater than the effect of father’s education (Peng et al., 2006). China is considered the world’s most populated and the second largest developing country. As a result, the Chinese government faces many difficulties and challenges on its developing process. One of the first challenges for the Chinese government is to improve child health and woman health progress, which have
  • 12. 10 achieved more significant achievements over the past decades in China. The gap in infant and maternal mortality ratios between urban and rural areas is still large although these rates have been reduced to lower levels in recent years. Looking at the case of Western China, the most important law in the West of China is that the qualities of the human population must always be increased. That is the reason the Chinese authorities distributes teaching role and management for each level based on a hierarchical network of maternal and child health services. The second development challenge for China is the unbalanced gender ratio and inequality household income. In China, the number of women employed in fulltime jobs could be limited because the employers prefer male employees than by women (due to their child-care obligations). Many rural Chinese households are stem families, in which three generations live under the same roof. The adult-to-child ratio in these families is quite large since Chinese birth control policies in the past limit the number of children for each couple to one. In addition, gender discrimination is one of the the most critical issues in urban China (Feng et al., 1992). The larger the size of the production market, the more competitive between firms to attain skilled and experienced workers. A greater number of private and collective firms instead of state-owned firms indicates a greater population of companies competing with one another for resources. As the result, labor markets will be more developed in regions and localities that have more developed commodity and production markets. It could be argued that labor markets for non-agricultural work are simply a functional level of industrialization, since in the absence of industry the only source of employment for rural people is agriculture and small-scale commerce. As a result, the Chinese society created the household income inequality. 1.2. Research objective This dissertation focuses on analyzing the influence of the level of women education (mother) on child health, with controlling the effect of economic growth, household wealth and father’s educational level as well as heredity factors and children gender. Consequently, the main objectives are considered consist of:
  • 13. 11 First, analyzing the relation between body mass index of both children and their parent and parent’s education level. Second, estimating the household wealth association with child health. Third, evaluating how the influence of gender discrimination as well as economy of living area. 1.3. Scope of the study The thesis analyses the interaction between mother’s education and child health, which is measured by the children’s body mass index (BMI) is calculated by the ratio of height of age and the weight of age. Moreover, the study controls external factors consist of environment, household income, the educational father, heredity factors, age and gender of children. The research in term of 25 provinces in China in 2014. 1.4. Contributions The role of maternal education in child health is the important empirical results. The study uses China Family Panel Studies (CFPS) data while the lack of papers used that data set. The thesis is the first study to estimate the effect of maternal education on child health using quantile regression. A number of recent researches examined those influence by multilevel modelling (Boyle et al., 2006), fixed-effect and random-effect (Desai and Alva, 1998). The body mass index for the analysis was objectively measured, reducing possible misclassification, although there a number of papers examined the child health through either the weight of age or the height of age of children. 1.5. Thesis structure The paper is organized as follows. Chapter II is Empirical studies which briefly reviewed the recent literature. Then, details estimation strategy in chapter III. After that, chapter IV will analyze the current the data and determine the empirical results. Finally, conclusion and implication policy are included in chapter V.
  • 14. 12 CHAPTER 2. LITERATURE REVIEW 2.1. Theoretical background Children health is a part of children development researches. The thesis based on two theoretical frameworks. Ecological systems theory: This theory looks at a child’s development within the context of the system of relationships that form his or her environment. Bronfenbrenner’s theory defines complex “layers” of environment, each having an effect on a child’s development. This theory has recently been renamed “bioecological systems theory” to emphasize that a child’s own biology is a primary environment fueling their development. The interaction between factors in the child’s maturing biology, their immediate family or community environment, and the societal landscape fuels and steers its development. Changes or conflict in any one layer will ripple throughout other layers. To study a child’s development then, we must look not only at the child and her immediate environment, but also at the interaction of the larger environment as well. Figure 1: Bronfenbrenner’s Ecological systems theory Chronosystem Macrosystem Exosystem Mesosystem Microsystem Child
  • 15. 13 Bronfenbrenner’s theory includes the following layers: First, the microsystem is the layer closest to the child and contains the structures with which the child has direct contact. The microsystem encompasses the relationships and interactions a child has with her immediate surroundings (Berk, 2000). Structures in the microsystem include family, school, neighborhood, or childcare environments. At this level, relationships have impact in two directions - both away from the child and toward the child. For example, a child’s parents may affect his beliefs and behavior; however, the child also affects the behavior and beliefs of the parent. Bronfenbrenner calls these bi-directional influences, and he shows how they occur among all levels of environment. The interaction of structures within a layer and interactions of structures between layers is key to this theory. At the microsystem level, bi-directional influences are strongest and have the greatest impact on the child. However, interactions at outer levels can still impact the inner structures. Second, the mesosystem is the layer provides the connection between the structures of the child’s microsystem (Berk, 2000). Examples: the connection between the child’s teacher and his parents, between his church and his neighborhood, etc. Third, the exosystem is the layer defines the larger social system in which the child does not function directly. The structures in this layer impact the child’s development by interacting with some structure in her microsystem (Berk, 2000). Parent workplace schedules or community-based family resources are examples. The child may not be directly involved at this level, but he does feel the positive or negative force involved with the interaction with his own system. After that, the macrosystem is layer may be considered the outermost layer in the child’s environment. While not being a specific framework, this layer is comprised of cultural values, customs, and laws (Berk, 2000). The effects of larger principles defined by the macrosystem have a cascading influence throughout the interactions of all other layers. For example, if it is the belief of the culture that parents should be solely responsible for raising their children, that culture is less likely to provide resources to help parents. This, in turn, affects the structures in which the parents
  • 16. 14 function. The parents’ ability or inability to carry out that responsibility toward their child within the context of the child’s microsystem is likewise affected. Finally, the chronosystem which is a system encompasses the dimension of time as it relates to a child’s environments. Elements within this system can be either external, such as the timing of a parent’s death, or internal, such as the physiological changes that occur with the aging of a child. As children get older, they may react differently to environmental changes and may be more able to determine more how that change will influence them. From Bronfenbrenner’s (1986) ecological theory, these factors include maternal education (microsystem level), maternal and family involvement in children’s home activities (microsystem level), maternal and family involvement in children’s school activities (mesosystem level), and the social support (exosystem level). Also, the ecological theory views child outcomes as dependent upon the characteristics of the child, parent, family, school, community, and larger society, as well as the interactions among these variables. However, some researchers have argued that this traditional ecological framework is limited because it does not adequately consider variables such as social position (e.g., social class, ethnicity, race, and gender), social stratification (e.g., racism, prejudice, discrimination, and segregation), and adaptive culture (e.g., traditions and cultural legacies, migration and acculturation, economic and political histories) experienced by family members of color who are born in the United States or other countries. To address this problem, Garcia Coll et al. (1996) proposed an integrative model to study the development of competence in children of color, by considering both social position and social stratification constructs at the core rather than at the periphery of a theoretical formulation of children’s development. In this model, the researchers address some important factors omitted or neglected in mainstream ecological models, such as experiences of racism and segregation, intragroup variability and diversity within minority group families, and the effects of social stratification and acculturation on the developmental competencies of minority group children.
  • 17. 15 Children inhabit both families and child-care microsystems, and these systems are linked. Parents select particular types of child care, of varying quality, for children of different ages—and these decisions vary with family structure, parental characteristics, geographical location, and other factors. Singer, Fuller, Keiley, and Wolf (1998) argued that child-care researchers must consider these selection effects if they are to accurately model the impact of child care on children’s development over time. In the research, the authors refer to the effects of family-level and community- level factors on child-care. In this study, the main hypothesis is that maternal education may affect children health at least in the following two ways. First, women with more years of education have higher production and allocation efficiencies in their children’s health production (Grossman, 2006). Production efficiency means better health condition with given health production input, while allocation efficiency means optimal combination of different health inputs with given budget. Maternal education can raise both production and allocation efficiencies, and thus improve children’s health. Second, higher maternal education can also affect the amount of inputs of children’s health production. More educated women have higher labor market income (labor market effect) and “match” with better educated and higher income husbands (assortative mating effect), while more family resources and better family environment contribute to children’s health human capital accumulation (McCrary and Royer, 2011). 2.2. Empirical reviews 2.2.1. The impact of maternal education on child health The mother’s education in most of papers are measured by the number of year of schooling. The relation between mother’s education and child health has long been supported by many evidences. Barrera (1990) researched the impact of mother’s education on child health in which the indicator for good or bad child health is determined by height – for – age scores. The regression result shows a positive effect
  • 18. 16 of maternal education on child nutritional outcomes. Also, mother’s education improves children’s height – for – age. Similarly, the effect of maternal education on three markers of child health is examined in 22 developing countries (Desai and Alva, 1998). The markers of child health consist of the probability of infant death, children’s height – for – age, and immunization status. The ranking of level educational mother includes 2 levels, mother not educated and secondary educational level. The result indicates that there is a consistent association between mother’s education and infant mortality. Meanwhile, the correlation between maternal education and children’s height – for – age is positive and significant. Although the coefficient correlation of mother’s education on immunization status is small, this effect is statistically significant in sample countries. Moreover, the effect of mother’s schooling on child health is can also be seen in the case of Morocco (Glewwe, 1999). The study also suggests that there is a positive relationship between education and child health. However, in this case, the evidences indicated that it is not only education but also the effect of household wealth that leave an impact on child health. The association of maternal education with child health may arise because educated mothers are considered more efficient “producers” of good child health (“productive efficiency”) by adopting better child-care practices or superior hygiene standards. Alternatively, it could be because they choose health input mixes that generate more health output (“allocative efficiency”) than selected by less-educated mother. Another studies used natural experiments to identify mother’s education-child health relationship. Breierova and Duflo (2004) used the 1995 intercensal survey of Indonesia and school data from the Sekolah Dasar program to investigate the impact of parents’ education on fertility and child mortality. The results show a positive and significant effect of the school program on parents’ education and a negative effect on fertility. Both father’s and mother’s education were found to reduce child mortality. The authors found little evidence to support the intuition that the mother’s education effect is stronger than the father’s. Similarly, using a natural experiment from Taiwan
  • 19. 17 (a new compulsory education law), Chou et. al. found evidence of a causal relationship between parents’ education and child health, but contrary to the previous study, mother’s education was found to be stronger effect than father’s education. No pathway investigation was attempted in either study. Maternal education in child health functions may therefore be affected by different factors (at the level education of the father, household welfare and place where child born). A study by (Thomas, Strauss et al., 1990) in Brazil analyses the role of income, mother’s literacy and information processing, and the interaction of maternal schooling with community services. The authors find that for most of time all the impact of maternal schooling on child height can be explained through mother’s access to information (i.e. exposure to media). Besides, some authors have found a significant effect of maternal education on child health status while others argue that there is little or no evidence of a causal relationship. For instance, Frongillo, de Onis, and Hanson (1997) ran cross-country OLS regressions of child height-for-age (stunting) and weight-for-height (wasting) on education variables, food security, geographic region and other variables. They found that the female literacy rate had a significantly negative effect on stunting. The main shortcoming of this study is that it did not address the heterogeneity in child health endowment and did not use instrumental variables methods to address the endogeneity of female literacy rate. While Martorell, Leslie, and Moock (1984) found no evidence of an impact of parents’ education on child health outcomes. Baya (1998), using data from a town in Burkina Faso, found that after controlling for father’s education, the effect of mother’s education on child survival loses significance. He concludes that studies on parents’ education and child health status should not focus on mother’s education. Handa (1999) examined six pathways through which mother’s education might affect child health outcomes: income effects, interactions with household characteristics, interactions with community services, information processing,
  • 20. 18 unobserved household heterogeneity1 , and intrahousehold bargaining power. Using data from Jamaica, Handa found that information processing is found to be a pathway through which mother’s education affects child health outcomes. Handa argued that he was able to control for unobserved household heterogeneity. He used the fact that in Jamaican households there are usually children from different mothers, and women in the same household care for all children whether the children are their own or not. This is questionable because there is likely to be mother heterogeneity. The other limitations of this study include treating parents’ education as exogenous, and using unobserved household heterogeneity as a pathway; it is really an estimation problem, not a pathway. Webb and Block (2004), using household survey data from Central Java, Indonesia, found that a mother’s nutritional knowledge is a determinant of child short- term nutritional status (weight-for-height) whereas her schooling is a determinant of long-term nutritional status (height-for-age). These authors could not find plausible instrumental variables for maternal nutritional knowledge and household expenditures, so they used proxy variables to estimate reduced form equations for child nutritional status. Webb and Block did not account for the possibility of omitted variable bias that would result from the heterogeneity of child health endowment. Appoh and Krekling (2005), using data from the Volta Region in Ghana, found that mother’s nutritional knowledge is more important than mother’s schooling in determining child weight–for-age. However, these authors accounted neither for the simultaneity of inputs choices, nor the endogeneity of mother’s health knowledge. After all, recent research on the relationship between maternal schooling and child health has moved towards underpinning the ‘pathways’ in which mother’s education translates into the improvement in child health. While a majority of the evidence has not directly controlled for the endogeneity of maternal schooling, introducing different ‘pathways’ is one way of isolating the ‘true’ impact of maternal education from the effect of confounding factors. In a recent study, (Glewwe, 1999) 1 Correlation between mother’s education and unobserved household characteristics. Possible sources of unobserved household heterogeneity: food preparation methods, knowledge of symptoms of ill health, different minimum levels of acceptable sanitation and cleanliness, and different tastes for child health.
  • 21. 19 identifies three channels: 1) direct acquisition of basic health knowledge in school, 2) literacy and numeracy skills learned in school and 3) exposure to modern society. The study finds that mother’s health knowledge alone impacts child health outcomes. According to (Boyle Racine et al., 2006), the linkages between maternal education and child health is cross-national difference; child health risks are reduced at higher levels of household wealth despite the unbalanced relationship between child health and levels of education with the pattern of household wealth. However, this research has some limitations, including the model is distributed with some unnecessary variables for improving on policies in population health; the limited regression for variation. 2.2.2. The role of household wealth Household wealth plays an important role in child health. (Filmer and Pritchett, 1999) The construction of household wealth index includes the following indicators: first, consumer durables (family owns a radio, television, bike or motorbike or car, etc); second, drinking water sources; third, type of toilet; fourth, household has electricity or not; fifth, the number of bed room; sixth, type of material for floor in house. Some factors are used as control variables to analyze the effect of other factors such as maternal education (Boyle, Racine et al., 2006) Meanwhile, household wealth is measured by net worth, values of businesses and private accounts (Shanks, 2007). The result shows that wealth is a relevant factor associated with child development. The effect of household wealth on child health is similar to the impact of economic development level on child health. It can be explained that improving the material status of the family and purchasing goods and services can lead to better health. It can be considered that poverty is an important determinant of mortality and poor health in all countries (Wagstaff, 2002). Furthermore, the evidence advocates that there are likely to be positive monotonic relationships between household wealth and child health in most developing countries (Gwatkin, 2000).
  • 22. 20 2.2.3. The effect of development economic on health Following a number of previous studies, the level of regional economy is measured by the income of a nation, particularly by GDP per capita based on purchasing power parity. In some countries, there would be a negative relation between life expectancy and income inequality (Preston, 1975). Surprisingly, mortality rate in Jamaica is better than Brazil even though the country’s GDP per capita is lower, which has mortality worse than expectation (Filmer and Pritchett, 1999). The region inequality in health system was demonstrated in Lorenz curve and Kuznets hypothesis (Fang Dong et al., 2010). The Lorenz curve shows that regional health inequality in China is related to socioeconomic factors and health system. Also, the Kuznets hypothesis to test the influence of GDP per capita on health distribution. The result of testing of Kuznets hypothesis indicated that health inequality had not reached its peak, meaning that China is still laying on the left side of the Kuznets curve. Deaton (2003) captured evidences for the association between national income and health. The results indicate that GDP per capita is significantly related to the probability of death in developed countries. Besides, the effect of income inequality on health in developing countries is bigger than in developed countries. This study used National Health Interview Survey (NHIS) with observation sample of approximately 50,000 households in every year, the National Health and Nutritional Examination Survey (NHANES) which surveyed more than 14,000 people in the first round between 1971 and 1975, and the Panel Study of Income Dynamics (PSID) which has followed around 5,000 households (and their children and split-offs) since 1968. The author used all data to find out the interaction among mortality, income, and income inequality. A logit model was applied to estimate the log odds of death during the ten-year follow up as a linear function of age including dummy variables for each of the seven income groups. These logits are estimated for white males and females separately, using data only for those aged 18 to 75 at the time of first interview. (The log odds of mortality are approximately linear in age over this range.) Tải bản FULL (51 trang): https://bit.ly/415Xb3W Dự phòng: fb.com/TaiHo123doc.net
  • 23. 21 In order to conduct a state-level analysis, each of these models is fitted to data for a single state, thus allowing inequality or any other state-level produce an unrestricted effect on the relationship between mortality and income. In findings, income inequality becomes relatively more important as a cause of death at higher income levels. 2.3. Summary From the recent researches, the weight of age and the height of age are only measured method for the health of children. However, I suggest BMI is an accuracy health measurement to determine the child health. In this study, the model organizes contexts of child health into 3 levels of external influence, including the family impact the child health directly, the environment elements and the physiological indirect affect child health. A major factor affecting the limited research in China is the lack of papers examining that issue. Furthermore, the study contributes to the literature as one of the first research employing CFPS dataset. The availability of rich recent data from CFPS allows us to overcome this gap in the literature. Tải bản FULL (51 trang): https://bit.ly/415Xb3W Dự phòng: fb.com/TaiHo123doc.net
  • 24. 22 CHAPTER 3. RESEARCH METHODOLOGY and DATA RESOURCES 3.1. Analytical framework Figure 2: The linkage between maternal education and child health (UNICEF, 1998) The conceptual framework guiding this study is based on the linkage between maternal schooling, childcare, and the health of children. Above figure shows the possible linkages between maternal education and child health that this study explores. The possible pathway through which maternal education can affect the health of children is through skill acquisition that leads to improved knowledge about healthcare and parental knowledge. Therefore, it is expected that women with more education are more aware of the benefits of feeding children at the appropriate times and in right quantities, and preventing the BMI ‘s child overweight. These practices can improve child health. Numbers of studies have modeled the effects of maternal education on child health outcomes through four non-excluded models: socioeconomic status, women Maternal education Maternal demographic factors: - Mother's education - Mother's body index - Time spending for child Socioeconomic factors: - Residence (urban or rural) - Household wealth index - Husband's education Child health factors: - The weight of age - The height of age - The body mass index Child demographic factors: - Child sex - Child age 6674506