Wealth and Freedoms of the World

For my honor’s project I wanted to do something that had to do with my interest in freedoms and wealth. Throughout the world is this idea that the wealthier a nation, the more advanced or able to care for its people, but I do not believe that this is the case. I wanted to prove that the freer, more democratic a country, the more accessible and prevalent health services -- not based on wealth or GDP. 

In my first honor’s class based in statistics, my research question was: How much can democracy affect the reproductive health care available for women? In this study, the expectation was that the more free (or democratic) a country is, the more legally accessible services for women’s reproductive health will be. Using Freedom House data, World Value Surveys, and United Nations’ data, I was able to determine if that is true. I hypothesized that the more free a country, health care will be more accessible and legally obtainable. My null hypothesis was there would be no difference in health care accessibility because of states’ GDP or Freedom House score.  

This analysis used data from the United Nations Population Fund’s study of women’s reproductive health worldwide on the question of what percentage of births are attended by skilled health personnel.  I compared the countries with the highest GDP and the countries with the lowest GDP for one test. Secondly, I looked into countries’ Freedom House scores and compared the statistics from the UNPFA of the ten highest scoring countries and the ten lowest scoring countries. Data on GDP was from statisticstimes.com from April 2017 and the World Bank. I used the statistical equation of difference of two means to perform this test.

I found that there was not a significant difference between the poorest and richest countries' percentages of health personnel at birth, only a -.288 difference between the two which did not exceed the degree of freedom of 2.447 on a two-tailed test. In regard to the most free and least free countries, there was a significant difference between the presence of healthcare personnel at the time of birth. The degree of freedom was 2.447 and the result was -3.039 showing that the least free countries were less likely to have someone at the time of birth trained in healthcare. 

For my honor’s project for Spring 2020, I theorized that the freer the state, the more accessible immunization (using HEP B as the example), public education, and professionals at time of birth would be. The wealth of a nation would not be impactful in its ability to provide public health and education. I used a regression test -- a test of means that looked at independent variables -- freedom and wealth in freest/least free and richest/poorest countries and compared them to determine which (freedom or wealth) impacted access to education, immunizations, and healthcare most. I hoped my hypothesis would find all of them to be most impacted by freedom. For this test, I needed probability to be less than .05 to prove that this independent variable affected the outcome. 

For early education, P>[t] for GDP is .458 – which means there is a .458 chance you are saying a country’s GDP affects the percentage of kids in early education in a country, but because we want it to be .05 or less -- it proves that it is not important enough to affect outcome. P>[t] for Freedom is .136 – which means there is a .136 chance you are saying a country’s Freedom Score affects the percentage of kids in early education in a country -- proving my hypothesis to not be void. 

For immunization, I used WHO data about the use of HEP B immunizations across the world, but focusing strictly on the ten richest/poorest and ten free/least free nations. P>[t] for GDP is .373 – which means there is a .373 chance you are saying a country’s GDP affects the percentage of people who have HEP B immunizations in a country -- proving there to be a standard error that does not exceed the standard deviation; however, P>[t] for Freedom is .011 – which means there is a .011 chance you are saying a country’s Freedom score affects the percentage of people who have HEP B immunizations in a country proves that freedom score does impact the prevalence of HEP B immunizations. 

For births attended by a health personnel, from the WHO, P>[t] for GDP is .643 – which again means there is a .643 chance you are saying a country’s GDP affects the percentage of people who have births attended in a country proving GDP does not make it more or less likely to have a healthcare professional at birth, but P>[t] for Freedom is .001 – which means there is a .001 chance you are saying a country’s Freedom does impact the amount of births attended by healthcare professionals.

My hypothesis proved correct for two -- births attended by healthcare professionals and HEP B immunizations, and it did not for early education. I am glad that my hypothesis came out correctly, but I think it is important to note that most of the freest countries are also the whitest, least diverse countries. This is important to note because often because of their nation state-like status, they are more capable of having working industries that cater to homogenous persons. Interestingly (to me), many of the poorest countries are free states, while not free states are more likely to be intermediately wealthy (worth a few billion dollars). 

All of the “poorest” countries are also some of the smallest, less known islands in Oceania, East Africa, and Central Africa. If I do this test again, I will surely make sure to compare poor countries and rich countries with similar population sizes because I think that is really what I should have been comparing. It is definitely different to compare a country with 211,000 people (Sao Tome and Principe) and 328,000,000 like the United States. 

If I continue this work, I will definitely be more cognizant of the issues with population size, demographic makeup, and where information is accessed. I believe the data from WHO, World Bank, and the United Nations is reputable, but I would have liked to be able to read information and data from actual citizens from states to determine how they feel about their healthcare and education systems. In the end, I am happy with the results -- showing the GDP does not have such a heavy impact on these factors. The most politically active, with social liberties are more likely to have access to healthcare, education, and immunizations which, during a time when I’m doing my project at home because of a global pandemic, is not a small deal. 

Bertrand, Natasha. “The 15 Least Free Countries in the World.” Business Insider, Business 

Insider, 29 Jan. 2015. www.businessinsider.com/the-15-least-free-countries-in-the-world-2015-1#eritrea-13.

“Freedom House.” Championing Democracy, freedomhouse.org/.

Roser, Max et al.“Global Extreme Poverty,” https://ourworldindata.org/extreme-poverty. 

“Global Health Observatory data repository,” WHO, https://apps.who.int/gho/data/node.main.A828?lang=en. 

“List of Countries by Projected GDP.” Countries by Projected GDP 2019 - StatisticsTimes.com, 

statisticstimes.com/economy/countries-by-projected-gdp.php.

“These Are the Freest Countries in the World.” U.S. News & World Report, U.S. News & World 

Report,www.usnews.com/news/best-countries/articles/2016-11-29/these-are-the-freest-co

Untries-in-the-world.

“United States.” OECD, www.oecd.org/unitedstates/. 

“World Population Dashboard.” United Nations Population Fund, 

www.unfpa.org/data/world-population-dashboard#.

WVS Database, www.worldvaluessurvey.org/wvs.jsp.