My study focuses on child mortality in Africa. According to UNICEF figures, the mortality rate among children under 5 years varies considerably from one country to another, and is amplified in certain countries. For this international organization whose responsibility is the protection of children, it is essential to know the causes of infant mortality, and implement projects to enable African children to reach adulthood. The economic aspects that I choose are the Gross National Income per capita, an indicator of poverty population, and health expenditure per capita, indicating whether the population can afford health care (vaccines, medical consultation etc).
UNICEF lists acute respiratory infections and malaria as the two major components of infant mortality in Africa. Currently, malaria is a disease which is difficult to control. For respiratory infections, the international organization recommends appropriate care of sick children. Solving these two major problems would bring about a decline in the number of deaths of children less than 5 years. I also recorded the number of children who are underweight and the percentage of people with access to potable water as factors that might explain the infant mortality rate.
Finally, the last but not least possible element: the HIV virus infection. Indeed, today more and more children are affected by the transmission of the virus from their mothers during pregnancy, childbirth or breastfeeding. Moreover, as HIV spreads, the number of child victims of the disease increases. After collecting data for the different variables and the removal of countries with missing data, my analysis focuses on 35 countries, mostly in Northern Africa. In the first part of the project, I will examine several variables that seem to be the causes of this phenomenon and determine which ones actually have a relationship with the rate of child mortality.
The mortality rate of under 5 is the ratio between the number of deaths before age 5 and the number of births for that year. It is expressed in 1000. It is a quantitative variable. UNICEF estimates that child mortality is the basic measure of the progress of a country. Source: UNICEF, 2004.
- Gross national income per capita, GNI: It expresses the country's wealth in dollars for 2004. Divided by the total population, it represents the average income of each person. We can assume that the economic difficulties of a country negatively affect the infant mortality rate. This is a quantitative variable. Source: UNICEF, 2004.
- Health expenditure per capita: This variable represents the total health expenditure per capita in dollars for 2002. Presumably, more the expenditure, the lower the risk of death is strong; this is a quantitative variable. Source: WHO, 2002
- Drinking Water: Expresses the percentage of population with access to safe drinking water. The consumption of unsafe water can lead to infections and increase the risk of death. Wider access to water sanitation facilities can result in improved living conditions for children; this, again, is a quantitative variable. Source: UNICEF, 2004;
Tags: Health expenditure per capita, UNICEF, Gross national income per capita
[...] On average of children suffer from respiratory infections. For half of the country of children at least suffer from this problem. Developments around the mean is low, the standard deviation is The correlation coefficient between the dependent variable and acute respiratory infections is - For some countries, the percentage of infected children is highly affected of risk of their death. In Côte d'Ivoire, where the number of sick children is the lowest mortality is stronger than Botswana, where the infection is most common among children less than 5 years. [...]
[...] Pneumonia (for bacterial infection) is the most serious disease that can cause. It is estimated that 60% of deaths attributable to them can be avoided if patients are given antibiotics. Quantitative variable. Source: UNICEF, 2004; - Malaria MALARIA This infection is the major cause of death among children in Africa today. This variable measures the percentage of children under 5 with fever receiving antimalarial drugs. This disease is a factor of severe anemia in children and one of the main causes of underweight. [...]
[...] Constraints are considered justified and validated. Wald Test: Equation: EQ02 Test Value df Probabil Statistic ity Null Hypothesis Summary: Normalized Restriction Value Std Restrictions are linear in coefficients. Test of nested models In the estimated model, the GNI impacts on the least significant endogenous variable. I then tested the model without this variable a 3 = 0 against H a 3 and I got: - The p.value is equal to 0.35 ; higher than 10%. We accept the hypothesis H 0. [...]
[...] This is a good indicator of the health and nutritional status of the child, as well as survival, growth and long- term health or even psychosocial development. In some developing countries, many infants are still not weighed at birth; the data are the best estimates available. Quantitative variable. Source: UNICEF, 2004; - ARI: ARI Percentage of children under 5 suffering from acute respiratory infections. Respiratory infections affect all areas of the respiratory tract (nose, ear, throat, larynx, trachea, and lungs). [...]
[...] The model is heteroscedastic. - White test The test is based on a significant relationship between the square of the residue and one or more variable explanation of the same regression equation: E ² t = a 0 + a 1 (INS_POND) i + b 1 (INS_POND) ² + a i 2 (MALARIA) + i b 2 (MALARIA) ² + v i t Test: H a 1 = b 1 = a 2 = b 2 = 0 → homoscedasticity of residuals H b 1 = a 1 = a 2 = b 2 0 → heteroscedasticity residues Lagrange multiplier test LM * = ~ χ ² ² nR = 2k χ ² 4 Chi-fractile Two: χ ² ( ) = 7.779 Decision rule: if LM χ ² 2k; 1-α we reject the null hypothesis, that is to say there heteroscedastic errors. [...]
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