Cardiovascular Diseases an The Coerlation Between The Human Development Index and The Age Standardized Death Rate

Relationship between the Human Development Index of countries and the Age Standardized Death Rate caused by Cardiovascular Diseases.

Background Information

Cardiovascular diseases (CVD) are non communicable diseases within a class of diseases that include the heart or blood vessels (WHO, 2010). A few of the most common cardiovascular diseases are coronary artery disease, heart failure, and myocardial infarction (commonly referred to as a heart attack) (Mayo Clinic Staff, 2014). It is estimated that approximately 90% of cardiovascular diseases are preventable and can be treated with healthy lifestyle changes (McGill, 2008). These diseases are caused by a multitude of risk factors including but not limited to, lack of exercise, significant alcohol intake, tobacco use, and unhealthy eating (McGill, 2008). Cardiovascular diseases are the main cause of death globally and are constantly becoming more common and leading to more deaths every year. In 1990, they resulted in 12.3 million deaths or 25.8% of all deaths globally (WHO, 2010). Meanwhile, in 2013, they caused 17.3 million deaths or 31.5% of the global population (WHO, 2010). Taking into consideration the significant increase in negative lifestyle habits, which are risks factors for cardiovascular diseases, it is no surprise that the numbers are rising.

Coronary artery disease is the most common of the cardiovascular diseases. It takes place when the arteries that provide blood to the heart muscle begin to harden and narrow (Mayo Clinic Staff, 2014). This is caused by an accumulation of cholesterol on the artery’s inner walls, called atherosclerosis (Mayo Clinic Staff, 2014). As this plaque continues to increase, the amount of blood that can flow through the arteries decreases (Mayo Clinic Staff, 2014). When this happens, the heart muscle can not receive the blood and oxygen that it needs (Mayo Clinic Staff, 2014). In extreme cases where the heart’s blood supply is suddenly cut off (usually due to a blood clot), this can cause a heart attack (Mayo Clinic Staff, 2014). Over an extended period of time, coronary artery disease can also weaken the heart muscle, leading to heart failure or arrhythmias (Mayo Clinic Staff, 2014). Since coronary artery disease develops over years, many do not notice problems until they have significant symptoms or a heart attack. Symptoms include chest pain, shortness of breath, indigestion, nausea, lightheadedness, or sweating (Mayo Clinic Staff, 2014). A healthy lifestyle is essential to both preventing and treating the disease. In conjunction with a healthy lifestyle, cholesterol-modifying medications, aspirin, beta blockers, nitroglycerin, angiotensin-converting enzyme inhibitors, and angiotensin II receptor blockers can be taken to treat coronary artery disease (World Heart Federation, 2017). In cases where more aggressive treatment is necessary, angioplasty and stent placement or coronary artery bypass surgery are treatment options (World Heart Federation, 2017).

Cardiovascular diseases have had a large impact on my life. Family members on both sides of my family have suffered from cardiovascular diseases. However, I have noticed that, based on where they live, there is a large difference in the ways that cardiovascular diseases affect them. For instance, my great aunt and grandmother were both impacted by the same form of cardiovascular diseases, coronary artery disease. Both women grew up in the same household under the same living conditions and only had a two year age difference. Yet, my great aunt who lived in Serbia died ten years ago while my grandmother, who lives in the United States of America, is still living an active lifestyle. This deviation inspired me to investigate the relationship between cardiovascular diseases in highly developed nations versus less developed nations.

In order to determine how “developed” a nation is, I will be using the Human Development Index (HDI). The Human Development Index is a statistical analysis of the quality of human life in a country. The calculations are done by the United Nations Development Programme and they use four categories; Life expectancy at birth, mean years of schooling, expected years of schooling, and the gross national income per capita (United Nations Development Programme, 2014). The data is displayed on a 1.0 scale, where countries that rank the highest are closest to 1.0 and vise versa. For the purpose of this research, I will consider the Human Development Index my raw data since I am simply reproducing the data from the United Nations database. Additionally, I will be using the World Health Organization’s (WHO) databases in order to indicate the amount of people who die from cardiovascular diseases. The World Health Organization presents the number of people who die from cardiovascular diseases per 100,000 (WHO, 2010). They further organize their data in an age standardized format which is based upon the weighted means of age-specific rates and the weights are taken from a standard population (WHO, 2010).

Many of the medicines and procedures necessary to treat cardiovascular diseases require a great deal of money. As a result, countries in lower human development categories generally have a more difficult time accessing treatment. This investigation will exemplify whether there is a significant relationship between access to expensive treatments and a prolonged survival rate. Human Development Index is a good indication of a country’s wealth and technological advancements. Therefore, this exploration will demonstrate whether (by 2008), new treatments have made a significant difference in decreasing the mortality rates caused by cardiovascular diseases. If the treatments have made a significant difference, then countries with a higher Human Development Index will generally have lower death rates due to cardiovascular diseases.

Research Question

Is there a relationship between the Human Development Index of countries and the Age Standardized Death Rate caused by cardiovascular diseases?

Hypothesis

If I examine the relationship between countries’ Age Standardized Death Rate due to cardiovascular diseases while utilizing a range of Human Development Indexes then, there will be a negative correlation because, countries with a higher Human Development Index will typically have better access to treatment for cardiovascular diseases.

Dependent Variable

The mortality rates as a result of cardiovascular diseases. This raw data will be derived from the World Health Organization’s Global Status Report on noncommunicable diseases 2010.

Independent Variable

The Human Development Index of a given country. This raw data will be derived from the United Nations Development Programme’s Human Development Reports.

Control Variables Why How

The database from which I derived the raw data regarding Human Development Index Reports. Obtaining data from a variety of sources could lead to incorrect or falsified data. The data will be collected from a reliable primary source which created the Human Development Index and recalculates it every year, the United Nations Development Programme.

The database from which I derived the raw data regarding mortality rates due to Cardiovascular Diseases. Obtaining data from a secondary source which could have estimated the data or have analyzed it using unreliable methods, could lead to incorrect or falsified data. The data will be collected from a reliable primary source, the health sector of the United Nations, the World Health Organization.

Time period of data collection Following 2008, the World Health Organization did not continue their annual collection of data regarding the mortality rates of cardiovascular diseases. In order to guarantee reliability, I will pair the “latest year of data” provided in the World Health Organization’s database with the Human Development Index ranking. Additionally, when selecting which countries I will use in my exploration, I will give priority to those with the most recent year available. The World Health Organization’s estimates, or those with “no data” will be a final resort.

Grouping of countries within the Human Development Index Inconstant grouping of the Human Development Index ranks would lead to incorrect data. The 2010 United Nations Human Development Index dictates how the countries are grouped.

Materials

• Logger Pro
• Unlited Natlions Development Programme’s Human Development Reports
• “Table 1: Human Development lindex and lits components”
• World Health Organlizatlion’s Global Status Report on noncommunlicable dliseases 2010
• “Country estlimates of NCD mortallity and selected rlisk factors, 2008”

Methodology

The United Nations Development Programme groups the Human Development Index into four distinct categories. Rankings 1-49 are “Very High Human Development”, 50-105 are “High Human Development, 106-143 are “Medium Human Development”, and 145-188 are “Low Human Development” (United Nations Development Programme, 2014). I selected 8 countries from each category to use as my sample data to test the relationship between mortality from cardiovascular diseases and Human Development Index. Within each category, I gave priority to those with the most recent data available and those with “no data” were a final resort because they are the World Health Organization’s estimated values. Estimated values (compared to calculated values) lead to a higher degree of inaccuracy and I therefore attempted to avoid using them when possible. I was successfully able to select countries with the most recent year calculated in the first three categories, but in the final category (Low Human Development) all of the countries had “no data” as their listed value. I chose to analyze 32 countries because it provided a large range with which I could explore countries from a large variety of regions.

1. Rank the countries from the World Health Organization’s dataset with their respective Human Development Index ranking.
2. Ascertain the Human Development Index category for each country.
3. Select 8 countries from each Human Development Index category.
4. Document the 32 selected countries along with their Human Development Index Rankings, Human Development Index value, Age Standardized Death Rate caused by cardiovascular diseases per 100,000 (females and males), and the Latest Year of Data.

Since my data is gathered from online databases, my exploration does not place any living being in harm’s way. Additionally, there are no notable ethical concerns since the raw data has previously been published on the internet from a humanitarian source.

Raw Data

The following tables organize the raw data for each four categories (Very High, High, Medium, and Low) of Human Development as determined by the United Nations Development Programme (United Nations Development Programme, 2014). In the “Age Standardized Death Rate” column, the data values are rounded to one decimal place because that is the form in which it is provided in the World Health Organization’s database (WHO, 2010). In the “HDI Value” column, the data values are rounded to three significant figures because that is the form in which it is provided in the United Nations Development Programme’s database (United Nations Development Programme, 2014).

Countries with Very High Human Development

Country Name HDI Rank HDI Value (out of 1.0) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Females) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males) Latest Year of Data

Norway 1 0.944 90.6 158.4 2008

United States of America 8 0.915 122.0 190.5 2007

Sweden 14 0.907 102.8 179.2 2008

France 22 0.888 69.2 128.3 2008

Greece 29 0.865 158.0 215.0 2008

Argentina 40 0.836 152.8 263.0 2008

Bahrain 45 0.824 311.3 357.0 2008

Montenegro 49 0.802 378.8 461.1 2008

Countries with High Human Development

Country Name HDI Rank HDI Value (out of 1.0) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Females) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males) Latest Year of Data

Russian Federation 50 0.798 414.3 771.7 2006

Barbados 57 0.785 173.9 293.2 2006

Malaysia 62 0.779 236.5 318.7 2006

Serbia 66 0.771 380.8 463.5 2008

Mexico 74 0.756 216.8 257.8 2008

China 90 0.727 259.6 311.5 2007

Colombia 97 0.720 166.7 205.9 2007

Maldives 104 0.706 220.7 184.3 2008

Countries with Medium Human Development

Country Name HDI Rank HDI Value (out of 1.0) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Females) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males) Latest Year of Data

Egypt 108 0.690 384.0 427.3 2008

Paraguay 112 0.679 227.9 269.3 2008

El Salvador 116 0.666 203.6 201.0 2008

South Africa 116 0.666 315.2 327.9 2007

Viet Nam 116 0.666 298.2 381.5 2008

Guyana 124 0.636 427.8 475.2 2006

Nicaragua 125 0.631 221.2 248.0 2006

Tajikistan 129 0.624 562.4 483.3 2005

Countries with Low Human Development

Country Name HDI Rank HDI Value (out of 1.0) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Females) Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males) Latest Year of Data

Kenya 145 0.548 326.4 401.1 No data

Swaziland 150 0.531 441.9 558.2 No data

Madagascar 154 0.510 384.4 367.0 No data

Yemen 160 0.498 445.7 541.8 No data

Uganda 163 0.483 383.7 561.6 No data

Afghanistan 171 0.465 578.2 765.2 No data

Democratic Republic of Congo 176 0.433 492.2 461.8 No data

Niger 188 0.348 412.0 350.7 No data

Processed Data

Levels of Human Development vs Mean Age Standardized Death Rate

Level of Human Development Mean Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males and Females) Mean HDI Value Range of HDI Values Standard Deviation of Age Standardized Death Rate caused by Cardiovascular Diseases per 100,000 (Males and Females)

Very High 208.6 0.873 0.142 114.4

High 304.7 0.755 0.092 151.8

Medium 340.9 0.657 0.066 111.9

Low 467.0 0.477 0.200 112.6

Graph 1

32 countries with average standardized death rates for male and females

Country HDI Value ASDR per 100,000 (Males and Females) Range for ASDR per 100,000 between genders Country HDI Value ASDR per 100,000 (Males and Females) Range for ASDR per 100,000 between genders

Norway 0.944 124.5 67.8 Egypt 0.690 405.7 43.3

United States of America 0.915 156.3 68.5 Paraguay 0.679 248.6 41.4

Sweden 0.907 141.0 76.4 El Salvador 0.666 202.3 2.6

France 0.888 98.8 59.1 South Africa 0.666 321.6 12.7

Greece 0.865 186.5 57.0 Viet Nam 0.666 339.9 83.3

Argentina 0.836 207.9 110.2 Guyana 0.636 451.5 47.4

Bahrain 0.824 334.2 45.7 Nicaragua 0.631 234.6 26.8

Montenegro 0.802 420.0 82.3 Tajikistan 0.624 522.9 79.1

Russian Federation 0.798 593.0 357.4 Kenya 0.548 363.8 74.7

Barbados 0.785 233.6 119.3 Swaziland 0.531 500.1 116.3

Malaysia 0.779 277.6 82.2 Madagascar 0.510 375.7 17.4

Serbia 0.771 422.2 82.7 Yemen 0.498 493.8 96.1

Mexico 0.756 237.3 41.0 Uganda 0.483 472.7 177.9

China 0.727 285.6 51.9 Afghanistan 0.465 671.7 187.0

Colombia 0.720 186.3 39.2 Democratic Republic of Congo 0.433 477.0 30.4

Maldives 0.706 202.5 36.4 Niger 0.348 381.4 61.3

Graph 2

Evaluation

Fundamentally, my statistical analysis supported my hypothesis. The Age standardized death rate due to cardiovascular diseases and the Human Development Index have a negative correlation. The negative correlation is strong since the data from Graph 2 rejects the Null Hypothesis.

Both of the databases that I used, the United Nations Development Programme and the World Health Organization, were relative and appropriate for my exploration. The Human Development Index, my independent variable, was started by the United Nations Development Programme (United Nations Development Programme, 2014). The World Health Organization is a sector within the United Nations, an internationally recognized organization (WHO, 2010). Since both of my sources are from a widely recognized organization, they are highly reliable. Additionally since they were published by the same organization, I know that the data is compatible.

One improvement that would have enhanced my exploration would have been to focus on a specific region. By exploring the relationship between the Human development Index and mortality caused by cardiovascular diseases world wide, I sacrificed the precision of my data. Had I chosen a region with a variety of Human Development categories (such as Europe), I could have reached a more accurate conclusion. Additionally, had I chosen a specific region, I could have explored all of the countries within that region. This would have eliminated the need for random selection when choosing which countries to include in my exploration.

Another improvement that would increase the accuracy of my results would be to place more significance on the Human Development Index value rather than the Human Development category. While the Human Development category is a valid generalization, it leaves a lot of room for inaccuracy. Meanwhile, by utilizing the Human Development Index, there would be a higher degree of precision in my exploration. One instance in which I could implement this improvement would be when I grouped the countries into their respective Human Development categories. Rather than doing this, I should have categorized the countries in respect to their Human Development Index.

A limitation to my exploration was the fact that my raw data from the World Health Organization’s database was not representative of the same year. The data ranged from 2005 to 2008 (with countries in the low human development category having no data available) (WHO, 2010). Within the span of these three years, there could have been a statistical change in the way that the Human Development Index was calculated. This uncertainty ultimately decreased the reliability of the data. Nevertheless, there were no available United Nations databases with a consistent annual collection of cardiovascular diseases mortality rates that included data from all four human development categories. Although I tried to mimic such a database by pairing the cardiovascular diseases mortality rates with the Human Development Index of their particular year, having all of the raw data derived from one primary source would have led to a higher level of accuracy.

Although the Human Development Index incorporates a wide variety of factors that determine the quality of life within a country, it does not specifically take into consideration a person’s exercise regimens, alcohol intake, tobacco use, or eating habits, all highly significant factors that lead to the development of cardiovascular diseases.