TABLE OF CONTENTS:
DATA AND METHODOLOGY
RESULTS AND DISCUSSION
Alternative Interesting Specifications and Discussion of Results
1. Results – including Hospital Births
2. Results – including Sanitation
Mothers play such a big role in raising and nurturing children and shaping their futures. They are essentially the first educators of children. But is this role a significant one? This paper seeks to answer the question: “What is the effect of education of women on the malnutrition rate of children?” If we can prove that education of women has a positive effect on the well-being of children, even small changes in the policies and economic foundations of underdeveloped and developing countries will have a huge impact on the well-being of children and consequently, in the sustenance of government institutions. It can have a substantial impact on the well-being of future generations.
In this paper, I will discuss applicable literature on the topic, collect data, analyze the data on a regression model, and discuss the results of my findings.
I expect to find a strong positive correlation between female education levels and malnutrition rate of children simply because of the fact that women are the primary caretakers of children. I predict that as the education level of women increases, the prevalence of malnutrition in children will decrease. I believe that the education of women will have a greater influence on the nutrition of children than the education of men because of the very fact that women are the primary educators of children. They are predominantly the ones that are raising the children, feeding them and looking after them. Educated women will have a greater awareness of nutrition and health and be more mindful of the types of food and nutrients they should be giving to their children to ensure a healthy and balanced diet. They will also have more knowledge on how to take care of their own selves and have more to offer the labour market. If they are able to go to work and earn income, they will assist and elevate the economic status of the household, helping to keep the family out of poverty. Hence, the education of women, I predict, will have the greatest influence in underdeveloped countries.
Economic theory would support my predictions, that as education level of women increases, children are better off. This is because increasing education increases human capital. Higher human capital leads to higher income and hence higher utility. Everyone in the family unit is happier and better off, including the children.
To reiterate, the purpose of my research is to determine what the effect of education of women is on the malnutrition rate of children. There are several academic papers that have analyzed related questions and come up with similar results.
In the Earthwatch Institute Journal, “Maternal and Child Healthcare in India”, a similar question is discussed. The article is predominantly a discussion about the experiences encountered by a group of people who went to India to gather information on maternal health. The study did not utilize a specific regression analysis to support its conclusions. The article explains how the state of malnutrition in India comes from not only the complex social systems present, but also from the lack of education. Specifically, it points out the lack of care in these systems for females. It discusses how educating women will lead to healthier pregnancies and to the birth of healthier babies. Giving birth to healthier babies instantly decreases the rate of malnutrition in children. Thus, confirming my hypothesis that education of women does have an direct effect on the malnutrition of children. In fact, the two are inversely related.
In Anna Milman’s paper, “Differential Improvement among Countries in Child Stunting is Associated with Long-Term Development and Specific Interventions”, Milman looks at the causes of stunting in children. Specifically, she looks at a number of variables including: food security (daily energy supply), maternal and child care (female literacy rate, females in the labour force), and health services and environment (access to safe water, immunization rate). In regards to the maternal and child care variables, factors included: social factors such as religion, prevalence of aids and urban population; political factors such as rights and civil liberties; economic factors such as debt, income distribution, health expenditures, assistance, and government consumption. Milman’s research was complex; she ran approximately 9 different regression models based on each group of these factors. The regression models were based on a wide range of data sources including WHO Global Database on Child Growth and Malnutrition and the UNICEF State of World’s Children data sets. The results of Milman’s regression models were that change in immunization rate, initial safe water rate, change in safe water rate, change in daily energy supply, and initial female literacy rate were the most important in explaining the stunting prevalence. This lead to the conclusion that an increase in immunization rates and high initial rates of female literacy are associated with improvement in the health of children.
Variables that account for the malnutrition of children was the centre of the research in “Risk factors for undernutrition of young children in a rural area of South Africa”. This paper looks at cross-sectional data across different districts in South Africa. The data was obtained by sending out questionnaires that asked for information about the status of the children in the household including age, birth weight and immunization status. Most of the variables that were looked at were related to infant feeding and caring practices performed by women and many of the same socio-economic, environmental and health factors were included such as mother’s education, literacy of mother, duration of breast-feeding and birth weight. The author, Mickey Chopra, uses a simple regression model to analyze the data. The results of his research showed that a number of factors did affect the malnutrition state of children, including average spending levels on food, absence of father, material of house, and the absence of toilet. Chopra states that children who start off with a low birth weight are over eight times more likely to be malnourished and/or stunted. However, he also concluded that the mother’s care has a significant effect on the health state of the child. The mother can educate herself to ensure her own proper nutrition when pregnant, to maintain health and disease-free status, and to prevent infection of the fetus. He goes on to conclude that the education of mothers is associated with childhood undernutrition even after controlling for socio-economic factors.
In a final paper, “Does intelligence account for the link between maternal literacy and child survival?”, Sandiford and Cassel look at the link between female education and the health of the children (ie. survival and risk of malnutrition rates). The methodology used is very similar to the methodology that I use in my research. One difference was in the way education was categorized. In my research, I categorize education into primary education, secondary education and tertiary education levels. However, in this paper, education is distinguished into two categories based on literacy rates: mothers that were educated exclusively as adults and mothers that were educated as children. The data used was individual level data collected on mothers in a single province. They obtained this data in the form of two questionnaires spaced about a year apart. These questionnaires not only asked about the health of their children, but also asked questions to determine literacy rates of the mothers. Unsurprisingly enough, this study also took into account a number of socio-economic factors including type of water supply, presence of sanitation facilities (ownership of a latrine), mother’s marital status, employment outside the home, child care arrangements, asset ownership (of a refrigerator or car), and house structure. The first questionnaire obtained data based on the children, and the second obtained more detailed data including literacy rates of the mother. The model regressed maternal literacy with child health controlling for the various socio-economic factors. A limitation to note in this research was the difficulty in measuring intelligence. This was evident by the large differences in intelligence scores between women in the illiterate group and those who became literate simply by attending primary schools. However, taking that into account, the study produced several conclusions. Firstly, the correlation between education of women and child health is significant and unexplainable by wealth and income. Secondly, education may have the greatest impact for mothers of relatively low-income countries. It can further be concluded that education offers the most benefit to women with the lowest literacy levels (intelligence level) and the highest rates of child mortality.
A common theme is apparent across the academic literature. They all consider education of women as either a main factor or an underlying factor in the health of children. They are also all in agreement that economic, social and environmental variables need to be accounted for when conducting any level of regression model. Although there is variation in the actual variable used to measure the health of children (ie. from malnutrition prevalence to stunting prevalence to infant mortality rates), the methodology used (ie. from a lack of a regression model to an extremely complex model consisting of 9 sub-models), and the data used (ie. questionnaires to available data), it does not make a large difference in the end. The results are all the same: that education of women has an effect on the health of the child, and that the greater the level of education the greater the well-being of the children.
 Earthwatch Institute Journal. “Maternal and Child Healthcare in India.” 2005 Research & Exploration Guide. 2005. 24(2): 35.
 Milman, Anna et al. “ Differential Improvement among Countries in Child Stunting Is Associated with Long-Term Development and Specific Interventions.” Journal of Nutrition. 2005. 135(6): 1415-1422.
 Chopra, Mickey . “Risk factors for undernutrition of young children in a rural area of South Africa.” Public Health Nutrition. 2003. 6(7): 645-653.
 Sandiford, P., Cassel, J. “Does intelligence account for the link between maternal literacy and child survival?” Social Science & Medicine. 1997. 45(8): 1231-1240.