Title: Children per Woman Correlations
Kelsey Spicer
Justin Tagle
Brennen Zinkgraf
fertilityofwomen.blogspot.com
By 2050, the Earth’s population will have reached 9.6 billion. This spike in population is not evenly distributed across the globe; contribution to population growth varies regionally as the standard number of children each woman has is different in many areas of the world. The different averages of the amount of children women have correlates with many other important global indicators. Main Goal: The primary objective of this project is to demonstrate the average number of children per woman (the fertility rate) globally, as well to make evident the correlations that accompany this indicator. The indicators for each country that will be compared to the fertility rates are: the percentage of women in parliament, infant mortality rate, life expectancy, population density, literacy, and gross domestic product per capita.
Problem statement: There is a dramatic difference in the average number of children that women bear in the regions of the world. Justification: Being aware of the average number of children per woman could bestow important insight into future population trends, such as what age the majority of a population would be in the future. Problem statement: Unfortunately, areas with the highest fertility rates correlate with many problematic issues. Justification: It is important to become aware of these issues, so that they can be addressed. This is accomplished by identifying where certain problems originate and what correlates with them. Finding these correlations can initiate awareness, diagnose, identify areas where improvements can be made, and showcase what can be done to mitigate these problems.
Scope: All countries will be taken into account when analyzing the data; 246 locations, both countries and territories. Characteristics: The children per woman data set will be compared to the percentage of women in parliament, infant mortality rate, life expectancy, population density, literacy, and gross domestic product per capita.
Objectives for accomplishing the main goal: The objective of this project is to create a visual representation of the average amount of children per woman across the world. Another objective is to demonstrate a correlation between the factors of the the percentage of women in parliament, infant mortality rate, life expectancy, population density, literacy, and gross domestic product per capita. Criteria: These standards were chosen using preliminary research done using the website GapMinder, where comparisons of data, can be plotted in order to observe possible correlations.
Methodology
Describe the analysis process: We agreed that the average amount of children per woman could be correlated with many other considerations, however specifically what exactly did correlate was unknown before initiating research. Gapminder.com was a crucial resource in comparing factors to the average number of children per women. This tool allowed us to observe correlations through visual linear representations of many factors as we compared them to the average amount of children per women. It was then decided that criteria for our selection would be: the percentage of women in parliament, infant mortality rate, life expectancy, population density, women in government, literacy, and GDP.
Describe ArcGIS tools applied to solve the problem: After creating our own data set to be used for the fertility rate shapefiles, we were able to join our data supplied by the UN site to several of the other shapefiles provided as part of the Geospatial Data Library (which the entire class worked on compiling). From here, each joined dataset was individually exported, cleaned up, and edited for any errors. Then, we arranged the layout in a way that could be easily understood, and saved as a layer file. This was done as many times as needed, in order to get an idea of what indications could be predicted using the fertility rate indicator.
Describe specific values (variables) that you used: We used all different data provided by the work that our class did during the Data Library set up. We created our own Fertility Rates shapefile, and used the Women in Government, Life Expectancy, Infant Mortality, Population Density, CO2 Emissions, and Female Literacy shapefiles created by others in the class.
Results and Discussions:
Below is the basic visual representation of the average number of children per woman worldwide.
Gapminder.com allowed us to preview certain correlations with the amount of children Gapminder.com allowed us to preview certain correlations with the amount of children per
women. The following are some of the graphs that influenced our decisions regarding which factors we chose, along with our ensuing ARCmap results.
Each dot represents a country, and is color coded to its according continent. Figure 2: The dark blue dot furthest to the right represents Niger, a country in Africa. Niger has the highest average amount of children per woman of 7.6. Niger also averages 114 child deaths per every 1,000 children born. Sierra Leone is the highest blue dot. It averages 4.8 children per woman with an average of 182 children deaths every 1,000 born. Figure 3: The lowest light blue dot represents Afghanistan. The average number of children per woman is 5.4. Only 13% of women are literate, ages 15 and above who can read or write. The 2nd to lowest dot, which it dark blue is Mali, a country in Sub-Saharan Africa. Mali has an average number of children of 6.9, with a literacy rate of 35% of women 15 and up. Closely following Mali is another Sub-Saharan country, Chad. Chad also has a literacy rate of 25%, with an average of 6.5 children per woman. Regarding Figures 2-5, it is very evident that African countries have the highest average number of children per women. These countries are also rank highest in infant mortality, lowest in life expectancy, GDP, and literacy of females. These graphs also demonstrate how high numbers of children per woman correlate with the percentage of women in parliament, infant mortality rate, life expectancy, population density, literacy, and gross domestic product per capita.
General results of our project are as follows: The lower the infant mortality rate, the lower the amount of children per women. The higher the life expectancy, the lower the amount of children per woman. A lower life expectancy correlates with more children. The higher the degree of education and GDP per capita of human population, the fewer children are born. Interestingly, a richer population could support more children. If more women were to become literate and GDP improved, thus improving health care, lengthening lives and reducing infant mortality, would the average number of children per women decrease? These correlations are inherently linked. Economic development of a country can lead to demographic transition from high birth and death rates to low birth and death rates. Poverty is a driving factor and if this was addressed, it appears it would correlate with lower birth and lower death rates, meaning a smaller average number of children.
Conclusions:
Observing the world visually through GIS opens up opportunities to discover and recognize different aspects that may not be recognizable or observable otherwise. This allows us the contingency to view the world in different ways. Correlations of low life expectancy and high infant mortality to a higher amount of children that each woman has, as well as as a lower literacy percentage and a low GDP accentuate the areas and locations where social progress could be important. If you desire to learn more about the subject, we have a blog hosting this paper, as well as relevant links that can point you in the direction of additional information that can be found here.