INTRODUCTION
Problem statement
Child malnutrition is a critical global issue, particularly prevalent in low-income countries like Vietnam, where the poorest quintile of children experiences the highest rates of malnutrition.
Malnutrition occurs when there is an imbalance in nutrient intake, either insufficient or excessive It can significantly impact children's health, leading to issues such as a weakened immune system, increased susceptibility to infections, cognitive impairments, and a heightened risk of developmental delays, including conditions like HIV/AIDS.
Inadequate maternal nutrition can significantly harm children's development, leading to long-term stunting even after recovery Over 200 million children under the age of five in developing countries lack the necessary environment to achieve their full developmental potential (Grantham-McGregor et al., 2007).
Many countries are actively seeking solutions to reduce the number of malnourished children, a critical issue for national security and economic stability This problem is particularly severe in developing nations, with significant variations observed across regions such as South and Southeast Asia, Latin America, and Sub-Saharan Africa.
Many countries aim to identify the factors influencing child health, focusing on health and nutritional inputs, access to medicines and medical care, and the quality of household drinking water and sanitation facilities Additionally, they consider other hygienic conditions, household assets, parental education, and community economic and health-related characteristics (Glewwe, 1999).
Numerous studies highlight the significant impact of parental education, particularly that of mothers, on child health and nutrition Increased maternal education is linked to improved child health outcomes, as educated mothers are better equipped to create a safer environment and provide nutritious food This education empowers mothers to adopt healthier habits, ultimately enhancing their children's nutritional status.
The relationship between a mother's education and child health varies significantly across countries due to substantial socio-economic differentials, as highlighted by Hobcraft et al (1984) in their analysis of 28 World Fertility Surveys In many developing nations, higher maternal education is crucial for enhancing child survival rates The study indicates that socio-economic disparities impact child survival from ages one to five, with increased child age correlating with these differences Additionally, both parents' education levels, particularly the father's, significantly influence child survival, with even minor improvements in paternal education contributing positively to child health outcomes.
Mensch et al (1985) conducted a study across 15 countries, yielding results consistent with those of Hobcraft et al (1984) They noted that significant socio-economic disparities weakened the association between maternal education and child survival in sub-Saharan Africa compared to Asia and Latin America Additionally, Mensch et al (1985) indicated that the relationship between maternal education and child survival remained consistent across different regions, including both rural and urban areas.
In Bangladesh, research by Lindenbaum (1990) indicated that educated women maintain higher cleanliness standards, which correlates with lower child mortality rates and fewer diarrhoeal episodes Cleland (1990) further supported this by linking international data on diarrhoeal incidents to maternal education, suggesting that education significantly enhances health knowledge This increased knowledge fosters a more innovative mindset among women, providing them with greater opportunities to gain valuable experiences through schooling.
When comparing Bolivia, Egypt and Kenya, Stewart and Sommerfelt
A study conducted in 1991, analyzing data from 25 Demographic and Health Surveys, revealed that a woman's educational level significantly influences prenatal care In Bolivia and Egypt, the impact of maternal education was more pronounced in urban areas compared to rural ones Conversely, in Kenya, this relationship was only weakly significant after accounting for factors such as urban-rural residence, possessions index, father's education, age, number of births, mother's education, and family planning use Notably, in Kenya, the urban-rural residence variable showed a strong significance.
Malnutrition among children under five is a significant concern in Vietnam, particularly in low-income areas According to UNICEF, 50 percent of Vietnamese children in this age group experience stunting, which is characterized by abnormally low height for their age.
1993 In 2005, this figure has been improved with 25 percent of children (UNICEF, 2006) because of economic growth and sustained investment in primary healthcare
Haughton et al (1997) highlighted significant disparities in child malnutrition across various regions and ethnic groups in Vietnam, with higher rates observed among families in northern areas, rural households, and ethnic minorities According to the National Institute of Nutrition and UNICEF (2011), the prevalence of stunting in children under five was approximately 29.3 percent, with an average annual reduction of 1.3 percentage points from 1995 to 2010.
Approximately 60% of neonatal deaths occur in children under five, with one-third of this age group experiencing stunting, malnutrition, and anemia Additionally, the prevalence of overweight children is rising annually, while children over one year old frequently face fatal risks from drowning and traffic accidents.
Children's health in Vietnam faces significant challenges, particularly in mountainous regions where healthcare services are limited Key issues include neonatal conditions, stunting, malnutrition, anemia, drowning, and traffic accidents, as highlighted by the World Health Organization in their 2010 fact sheet on child health in Vietnam.
Numerous studies across different countries have identified various factors influencing child health However, Vietnamese reports provide limited insights into the impact of maternal education on child health outcomes This raises the question of whether this relationship holds true in Vietnam To explore this, we will apply the aforementioned factors to gain a detailed understanding of their effects.
Research objectives
This study intents to: Evaluate the relationship between mother’s education and child health in Vietnam.
Research scope and data
The article discusses various factors affecting child health in Vietnam, including the height-for-age z-score, household income categorized by wealth index quintiles, and health environment indicators such as access to drinking water and flushing toilets, based on data from MICS4.
The structure of this study
Except the introduction and the references chapter, this study is divided into 4 chapters as follows:
LITERATURE REVIEW
The relationship between mother’s education on child health
Research has highlighted the significant role of a mother's education in influencing children's health and nutrition, particularly in developing countries Studies consistently demonstrate that increased schooling for women leads to improved outcomes for their children.
Grossman M (1972) concluded that an individual's knowledge stock enhances their ability to process information about fertility options and healthy pregnancy behaviors Specifically, higher education levels can lead to better health choices through improved wage rates This highlights the impact of knowledge on estimating the opportunity cost of time However, education alone may not suffice for ensuring child health, raising further questions about the roles of parental education, household income, housing options, and behaviors affecting child health.
Willis J.R (1973) examined the impact of mothers' income on child quality and services, using individual data on the number of children born in America The study highlights that higher education and health among women contribute to an increase in their permanent income, enabling them to make optimal choices in child-rearing Consequently, this rise in mothers' income enhances the demand for child quality, which in turn boosts the supply of child services, illustrating the strong link between education, income, and child care.
Research indicates that mothers significantly influence their children's well-being According to Case (2000), a mother's education and employment can enhance her children's health through better nutrition and reduced stress in caregiving This analysis underscores the importance of government policies aimed at improving maternal education, which can lead to better health, education, and productivity outcomes for children throughout their lives.
Children's health is crucial as it significantly influences their academic performance and long-term well-being Research by Currie and Stabile (2003) using panel data on Canadian children indicates that health shocks adversely affect test scores and future health outcomes Consequently, understanding the factors that impact the health of future generations is essential for fostering their development.
Currie & Moretti (2003) analyzed Vital Statistics Natality data from 1970 to 1999 and discovered that higher maternal education significantly enhances infant health, as indicated by improved birth weight and gestational age They posited that educated mothers are more likely to access better healthcare, adopt healthier behaviors, and increase family income, potentially by marrying highly educated partners.
Berhman & Wolfe (1987) discovered that while a mother's education did not directly improve children's health outcomes, it positively influenced their nutrition This finding contrasts with standard estimates derived from cross-sectional data in Nicaragua, suggesting that maternal education typically enhances child health Additionally, they provided evidence of an indirect effect of maternal schooling on children's health through improved nutrition, particularly in relation to the duration of breastfeeding.
Research has examined the health disparities between biological and adopted children A study by Y Chen and Li (2009) indicated that a mother's education significantly influences child health through nurturing, while genetic factors may not play a crucial role Their sensitivity tests and subsequent analyses failed to provide evidence supporting significant differences in health outcomes between adopted children and those born to the parents.
Sacerdote (2000) utilized three extensive long-term panel data sets, including adopted children, their adoptive parents, and biological parents, sourced from the British National Child Development Survey, the Colorado Adoption Project, and the National Longitudinal Survey of Youth (NLSY79) to investigate the issue at hand.
Research indicates a significant correlation between the education and income of adoptive parents and the developmental potential of their children Specifically, the educational background and financial resources of adoptive parents greatly influence their children's future outcomes, including college attendance, marital status, and earning potential.
According to Plug and Vijverberg (2003, 2004) and Plug (2005), their estimations were not influenced by variables related to adoptees and biological children It is believed that adopted children's health benefits from a nurturing effect, highlighting the significant role of maternal education in their well-being This suggests that educated mothers are better equipped to care for their children Even after accounting for factors such as income, number of siblings, health environment, and other socio-economic variables, the influence of women's education on both adoptees and biological children remains consistent Consequently, there is no discernible difference in the impact of maternal education on these two groups However, there are concerns regarding the ability of parents to select among abandoned children, which may affect the circumstances of their upbringing.
A key question regarding child adoption is whether more educated mothers choose to adopt based on health considerations It is commonly understood that adopted children, particularly in China, often lack information about their birth parents and health history (Y Chen & Li, 2009) This situation is influenced by China's one-child policy, which has led many families to prioritize having male heirs for their next generation.
In China, the majority of abandoned children are girls, with around 90 percent of abandoned infants and 80 percent of adoptees being female, as parents tend to abandon disabled or ill boys Due to the illegality of abandonment, these children are often left in the first six months of life, limiting adoptive parents' ability to choose Furthermore, there is no evidence suggesting that parents prefer healthier children when adopting Consequently, the educational background of adoptive parents, particularly the mother's or father's education, becomes a significant factor in the adoption process.
The relationship between parental education and child health is a critical area of study Behrman (1997) posits that enhancing women's education significantly benefits children's well-being, often more so than increasing men's education He highlights that mothers with higher educational attainment, even with similar abilities, tend to create a more conducive environment for their children's development, leading to improved academic and labor-market outcomes.
Berhman & Rosenzweig (2002) found that an increase in women's education does not necessarily lead to higher educational attainment for their children, highlighting the challenge of influencing children's academic choices However, enhancing a mother's education within the same environment can positively affect children's outcomes, particularly in health.
In Vietnam, generally fathers have more opportunities to attain qualified education than mothers do, thus, father’s education can be an important variable
Y.Chen & Li (2009) covered their data in China and found that fathers have more education than mothers generally The tradition of China and Vietnam is similar
The impacts of all other factors
Numerous studies have suggested that health status is influenced by various socio-economic factors Gwatkin et al (2007) identified 120 indicators categorized into four groups: health status (such as child nutritional levels), utilization of basic health services (including antenatal care and treatment of common childhood illnesses), health-related behaviors (like smoking and alcohol consumption), and other determinants of health status (such as education) Additionally, factors like income, ethnicity, geographical location, gender, and assets, along with a range of social and economic circumstances, play a significant role Community factors, including the psychological state of caregivers, feeding practices, social norms affecting disease transmission, and the availability of essential trace minerals and vitamins in food and water, as well as vaccination coverage, are also critical to understanding health outcomes.
From above variables, O’Donnell et al (2008) suggested that income may play an important role in determining children health They covered data from the
The 1993 and 1998 Vietnam Living Standards Surveys were conducted to analyze the relationship between changes in child nutritional status, as measured by height distribution, and variations in income levels and distribution.
Their result showed that one-half of the 15-pong fall in the ratio of children malnutrition (stunted) can be explained by changes in the distributions of income
Income significantly influences children's health by enhancing access to essential resources Higher household income enables families to invest in healthcare, sanitation, nutritious food, and other critical factors that contribute to overall well-being.
Case et al (2002) highlighted that children's health is linked to household income, with evidence suggesting that this relationship is influenced by the presence and onset of chronic conditions.
Research indicates that children's health is significantly poorer in lower-income households compared to their higher-income counterparts Families with greater financial resources are better positioned to create a healthier environment, including access to clean water and sanitation This improved setting contributes to more effective child care, leading to better health outcomes, enhanced academic performance, and greater success in the labor market for their children.
Research indicates that the intergenerational transfer of socio-economic status starts early in life, even during pregnancy Consequently, numerous studies have sought to identify factors that positively influence children's health as part of this transfer process, as highlighted by Case et al.
(2002) showed out that the impact of parents’ income on children’s health c an explain a part of this issue by transferred their income to nutrition of their children
Research by Y Chen and Li (2009) indicates that a mother's education positively influences children's health Consequently, children's health is influenced by both household income and maternal education levels.
Pradhan et al (2003) emphasized the importance of examining health status determinants at both national and individual levels, as child health can be influenced by various factors At the national level, aspects such as healthcare systems and economic growth play a crucial role, while at the individual level, factors like household sanitation and income significantly impact health outcomes Understanding these indicators is essential for improving child health.
National incomes are influenced by health status, which encompasses health expenditures, social service infrastructure, education, and environmental factors O'Donnell et al (2008) emphasized that enhancing community infrastructure and mitigating negative public health externalities can lead to improved nutritional quality within communities.
However, it is difficult to estimate the association of health care systems and health of each child in each family
Skoufias (1998) analyzed cross-sectional household data from the 1994 Integrated Household Survey of Romania to estimate the impact of socioeconomic, demographic, and environmental factors on the growth of preschool children aged 0-5 years The study concluded that national income does not influence child health in urban areas during Romania's economic transition, indicating that child health cannot be solely explained by national income across different regions Consequently, it is essential to explore other monetary variables to better understand this relationship.
After using from household survey data from 12 countries and data on malnutrition rates in a cross-section of countries from the 1970s, Haddahs el al
(2003) also found that it is required to have 6% growth in incomes per capita for
Over the past 20 years, efforts to reduce the stunting rate among children aged 5 have led to a 15 percentage point decrease in stunting, aligning closely with growth forecasts While improvements in growth rates can indicate a reduction in malnutrition, economic growth alone cannot fully account for this issue Therefore, nutrition programs and targets must consider factors beyond just economic growth to effectively address malnutrition.
Household income is a crucial factor influencing child health and malnutrition, as higher family incomes enable greater investment in food, clean water, and hygiene practices.
As a result, those can help parents to afford better child care arrangements (Haddahs et al 2003)
O’Donnell et al (2008) found that household income accounted for 15% of the decrease in the stunting ratio among children When incorporating variables related to safe drinking water and sanitation, this figure increased to 35% This indicates that malnutrition is influenced more by factors like household income and community infrastructure, rather than solely by GDP Consequently, child health is significantly affected by variables such as access to clean water, sanitation, drug availability, and the education levels of household members.
Sahn and Alderman (1997) analyzed data from Maputo, Mozambique, to assess the influence of household resources on health outcomes Their findings revealed two key insights: firstly, a mother's education significantly correlates with the nutritional status of children aged two years and younger; secondly, an increase in household income positively impacts the health of children older than two years.
Research indicates that the relationship between a mother's education and children's health varies across countries, yet there is a consistent trend in this association This study aims to explore the connection between maternal education and child health in Vietnam, utilizing data from MICS4.
RESEARCH METHODOLOGY
Model and Data
This article explores the impact of maternal education, water and sanitation conditions, and household income on child health, specifically through the lens of the Height-for-Age Z-score (HAZ z-score) It highlights that the HAZ z-score is influenced by factors such as the mother's level of education, access to safe drinking water, the presence of a flushing toilet, and the household's wealth index quintiles.
The standard model currently lacks alternative frameworks for this issue, with coefficients represented by the vectors β₀, β₁, β₂, β₃, β₄, β₅, β₆, β₇, and β₈, while ε denotes the residual To address this, I decomposed the standard function into components associated with the relevant variables This study employs the model proposed by Y Chen & Li (2009) to analyze the impact of maternal education on child health.
The equation for HAZ is expressed as follows: HAZ i = β o + β 1 melevel 1i + β 2 melevel 2i + β 3 wiq 1i + β 4 wiq 2i + β 5 wiq 3i + β 6 wiq 4i + β 7 dtoilet i + β 8 dwater i + ε i This model incorporates various factors, including multiple levels of measurement and specific indicators related to water and sanitation For further insights and the latest updates, please refer to the full thesis available for download.
Table 1: Variables of the study
HAZ Height-for-age z-score (WHO) of child i
Melevel 1i melevel 1i = 1 if level of mother i ’s education is upper secondary
Melevel2 i melevel 1i = 1 if mother i studies teritarty level
Wiq i wiq 1i = 1 if the wealth index quintiles of household i is second
Wiq i wiq 2i = 1 if the wealth index quintiles of household i is middle
Wiq i wiq 3i = 1 if the wealth index quintiles of household i is fourth
Wiq i wiq 4i = 1 if the wealth index quintiles of household i is richest
Dtoilet i dtoilet i = 1 if household i uses a flushing toilet
Dwater i dwater i = 1 if household i uses safe water
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The above variables in Table 1 are explained in detail:
Pradhan et al (2003) highlighted the challenges in comparing income and socio-economic variables to health status across different times and locations, particularly in poorer countries where constructing income and expenditure measures is complex They emphasized the importance of using standardized height as a health indicator, as it mitigates the measurement issues associated with other health metrics like morbidity, mortality, and life expectancy, as well as the complications of monetary variables Consequently, the height-for-age z-score (HAZ) is recommended as a widely accepted health indicator, ensuring the appropriateness of health measures for quantitative analysis (O'Donnell, Nicolas, & Doorslaer, 2008).
Other anthropometric indicators, including the weight-for-age z-score, weight-for-height z-score, and body mass index, can be utilized for regression estimation in this research However, these measures may not accurately reflect health status, as variations in weight do not necessarily correlate with better health outcomes Therefore, height is a more effective variable for explaining the model (Pradhan, E Sahn, &).
In their 2009 study, Y Chen and Li discovered that weight-for-age and weight-for-height (BMI) yielded comparable results in regression analysis They also highlighted that, even after accounting for income, health environment, and other socioeconomic factors, the mother's education remained a significant determinant of height-for-age z-scores (HAZ).
Height serves as an important indicator of both short-term and long-term health status O’Donnell, Nicolas, and Doorslaer (2008) analyzed data from the 1993 and 1998 Vietnam Living Standards Surveys, utilizing height-for-age z-scores (HAZ) to assess long-term nutritional status They posited that a child's nutritional status could be effectively explained by the complete distribution of HAZ Consequently, this paper focuses solely on the HAZ variable to evaluate child health, with further details provided in the Appendix.
The height-for-age z-score is defined:
: the observed height of child i in group k (child sex and the birth month);
: the median of the height in group j;
: the standard deviation of the height in group j
It is formed as the following categories
-1 < HAZ < 0 Normal -2 < HAZ < -1 Marginally stunted -3 < HAZ < -2 Moderately stunted HAZ < -3 Severely Stunted
Variable melevel is the mother’s education In previous parts, the study show out that the mother’s education can affect their children health
A dummy dwater is utilized to assess the safety of drinking water in households Water is deemed "safe for drinking" when it complies with the World Health Organization (WHO) guidelines and national standards for drinking water quality Safe sources include household connections, public standpipes, boreholes, protected dug wells, protected springs, and rainwater.
A dummy toilet is utilized to assess the presence of a flushing toilet in households, ensuring a clean and healthy living environment for both residents and their communities This includes connections to public sewers, septic systems, pour-flush latrines, simple pit latrines, and ventilated improved pit latrines, as outlined by the World Health Organization in their guidelines on health through safe drinking water and basic sanitation.
The wealth index quintile (wiq) serves as a valuable metric in this study, particularly in the context of Vietnam and other developing countries where collecting income and expenditure data poses challenges This index is thought to effectively predict a household's long-term asset potential However, it is important to note that the wealth index does not provide insights into absolute poverty or current income and expenditure levels.
(Vietnam: Multiple Indicator Cluster Survey 2011, 2011)
The wealth index quantifies a household's overall living standards by assessing ownership of various assets, including electricity, appliances, and vehicles Households are ranked based on their scores, which are then categorized into five quintiles: poorest, second, middle, fourth, and richest.
EMPIRICAL RESULTS
Descriptive statistics
This study utilized data from the Multiple Indicator Cluster Surveys (MICS) involving 3,559 children As shown in Table 2, the HAZ-score ranges from a minimum of -5.90 to a maximum of 5.54, but the focus is primarily on four categories: severely stunted (HAZ < -3), moderately stunted (-3 < HAZ < -2), and marginally stunted to normal (-2 < HAZ < 0) The mean HAZ-score is -1.092 with a standard deviation of 1.38, indicating that most children in the MICS data exhibit good health.
Mean Std.deviation Minimum Maximum
Table 2: Mean, Std.dev., minimum and maximum from MICS abour HAZ z-score
Table 3 also points out that haft of the number of children in MICS have better health In detail, there is 27 percent of children whose heath is normal (-1<
A significant portion of children, specifically 30 percent, are experiencing marginal stunting in their health, while 17 percent are moderately stunted and 7 percent are severely stunted, indicating a concerning overall health condition.
Table 3: Percent of HAZ z-score divided five parts
Table 4 illustrates the educational attainment of mothers, revealing that 38.0% have completed lower secondary education Additionally, 7.8% of mothers did not have the opportunity to attend school, while 18.4% achieved primary education The percentages for mothers with upper secondary and tertiary education are closely aligned, at 17.7% and 18.0%, respectively.
Table 4: Percent of mother's education level
HAZ