Volume 5, Number 2
October 1999

Women's Status, Women's Education and Child Nutrition in Developing Countries

The main question Smith and Haddad set out to answer is, What are the causes of child malnutrition? Researchers tend to hold two contrasting views on this question. Economists blame slow GDP (gross domestic product) growth and low incomes. But nutritionists point to insufficient calories or protein, poor nutrition knowledge, micronutrient deficiencies, and infection.

The study does not draw a sharp distinction between these viewpoints, though it does focus more directly on nutritional goals. It has four objectives: (1) to determine whether women's education and women's status have an impact on child nutrition in developing countries; (2) to estimate the strength of that impact; (3) to estimate the contribution women's education has made to reductions in child malnutrition from 1970 to 1995; and (4) to determine what level of priority should be given to women's education and status in strategies for reducing child malnutrition.

The study considers four explanatory variables for children's nutritional status: 1) national food availability, measured as per capita dietary energy supply; 2) women's education, measured as gross female secondary enrollment rates; 3) women's status relative to men, measured by the ratio of female life expectancy male life expectancy; and 4) access to safe water, measured as the percentage of a country's population with access. The study uses the best available child malnutrition data (mostly from the World Health Organization) and applies statistical techniques designed to yield estimations that are more accurate than in other such studies. The national-level data used in the study cover 63 countries (88 percent of the developing- country population) for the period 1970-96.

Smith presented the findings for each of the studies.

1. The empirical analysis shows that all four variables have a statistically significant and negative association with child malnutrition. So, for example, when women's status relative to men increases, child malnutrition can be expected to decrease.

2. The study found all four variables have strong impacts on child malnutrition. To determine the relative impact of each variable, Smith and Haddad estimated the percentage each variable would have to increase to reduce child malnutrition by 1 percentage point. By this measure, women’s education has the greatest impact on child malnutrition. Food availability comes in second, followed by women’s status and safe water access.

3. Regression estimates show that the four variables together reduced underweight prevalence by 15.8 percentage points during 1970-95. Increases in women's education and women's status reduced child malnutrition by 43 and 12 percent, respectively. Together these two variables accounted for more than half of the reduction in child malnutrition. Improvements in food availability and safe water access also made significant contributions: 26 and 20 percent, respectively.

4. Smith and Haddad used two criteria to determine future priorities for each developing region (not taking cost-effectiveness into account): (1) the relative impact of each variable and (2) the scope for increasing each variable to desirable levels. By these criteria, women’s education and food availability should be top priorities in South Asia and Sub-Saharan Africa--the regions with the highest rates of child malnutrition. A secondary priority in South Asia would be to improve women's status. Women's education is also a top priority in East Asia, in the Near East and North Africa, and in Latin America and the Caribbean. Women's status would be a secondary priority in these three regions. An additional secondary priority in East Asia would be food availability; in Latin America and the Caribbean, health environment improvements. With regards to the Asian enigma hypothesis, the study found that women's low status relative to men in South Asia partially contributes to the region's higher rate of child malnutrition. But country-specific factors that do not change quickly over time--possibly the monsoon climates and cultural norms surrounding child care practices--contribute much to the higher rates of malnutrition.

An initial impact of the study is its use in formulating priorities for the U.S. Plan of Action for World Food Security (World Food Summit country action plan). And the Poverty Reduction and Economic Management (PREM) Network of the World Bank has also shown interest in this work.

The next step in this research involves the use of household-to level rather than national-level data to further explore the Asian Enigma. An IFPRI/ Emory University study along these lines is being funded by the Swedish International Development Agency.

A questioner began the discussion by asking what the relationship was between the food availability variable and GDP growth. The authors said that GDP growth is indeed one of the factors explaining increases in all of the explanatory variables. It lies at a deeper level of causality than the factors considered in the study.

Several participants stressed the need to disaggregate the data for female and male children, because the determinants of malnutrition probably differ for each. Smith and Haddad agreed that this should be done. A microlevel study will look into this.

An audience member wondered if the educational variable should include the primary level along with the secondary level. Data for both levels would lead to more informed choices before investing limited resources. The authors agreed but said that they used data only for secondary enrollments because those for primary enrollments were not as good.

Was it possible to determine the effect of education on child malnutrition when enrollment generally has been increasing, a participant asked? Are the data points well-spaced enough to see the effect? The authors noted that the data points are 13 years apart on average. The timing of data points is different for each country. However, no data points spaced less than three years apart were used.

Another audience member wanted to know if male education would have the same effect on child malnutrition as female education. Smith and Haddad said that they have not tested for male education. Female education probably has more direct effects on child care quality, and male education more indirect effects, for example through income.

A questioner wondered what role low birth weight plays in the Asian Enigma. The authors replied that low birth weight certainly contributes to malnutrition; in turn low female status contributes to the prevalence of low birth weight in South Asia.