Investigation Regarding the Correlation Between HDI and ...
[Pages:12]HL Biology IA
Anthony Hans
Jan 2016
Investigation Regarding the Correlation Between HDI and Mortality Rates due to Stroke
Research Question
What is the correlation between HDI and mortality rate due to stroke (measured in number of deaths per 100,000 of population), in countries with a HDI of above 0.75?
Background Research
Stroke is a cardiovascular disease that involves a lack of blood flow to the brain (National Stroke Association, n.d.). This can occur in several ways: hemorrhagic strokes occur when a weak blood vessel in the brain leaks, or if an aneurysm (a localized swelling of a blood vessel) bursts inside the brain; an embolic stroke occurs if a plaque or clot fragment formed elsewhere in the body, travels up the brain and blocks a small blood vessel there; and a thrombotic stroke is caused by a clot that formed inside one of the brain's blood vessel. All deprive sections of the brain from receiving sufficient oxygen, resulting in the death of the brain's neurons. Collectively, all of the different types of strokes kill six million individuals per year worldwide (World Heart Foundation, 2016).
Figure 1: Diagram showing a hemorrhagic stroke involving an aneurysm
Stroke, and other diseases such as coronary heart disease and Alzheimer's disease, are noncommunicable; that is, they are not transmitted from person to person, as infectious diseases carried by viruses or bacteria are (World Health Organization, 2015). Instead, they are caused due to risk factors, such physical inactivity or smoking. For this reason, advances technology and civil engineering which has helped in preventing and curing transmissible diseases (examples being vaccines limiting the effect of bacterial/viral diseases, and proper sewage treatment improving public hygiene and therefore health)
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may not necessarily work to slow the growing prevalence of non-communicable diseases, which are not caused by transmissions.
In this investigation, HDI (human development index) will be used as the metric by which development is measured. This is an index incorporating education, GNI per capita, and healthcare, using various indicators to measure each component and therefore the overall HDI (Human Development Report, 2015). An HDI value of 0.75 or higher can therefore be a reasonable indicator of a developed country.
Although certainly not as prominent as other non-communicable diseases, such as coronary heart disease or cancer ? both of which are the leading causes of death in most developed countries ? stroke is by no means insignificant. Even if a stroke attack does not claim the lives of its victims, the devastation it so often causes to the afflicted and their families are hugely paralyzing. Therefore, I have devoted this investigation to the study of stroke's prevalence, in hopes of better understanding it in the larger picture.
Therefore, this research aims to determine the impact of human development on the number of mortalities caused by strokes; where human development is measured by HDI, and the number of mortalities is taken per annum and per 100,000.
Hypothesis
It can be predicted there is a negative correlation between the HDI of a country and the number of lethal stroke cases there.
This is because when very high HDI countries are concerned, strokes are more easily treatable with advanced healthcare, allowing stroke patients a higher recovery rate. Therefore, despite a higher life expectancy and more people suffering from strokes, highly developed countries might be able to treat strokes more easily than other diseases such as cancer or coronary heart disease, hence reducing the mortality rate due to strokes
Therefore, the hypotheses for statistical testing are as follows:
Null Hypothesis: HDI has no impact on the mortality rate due to stroke. Alternative Hypothesis: HDI will have a negative correlation on the mortality rate due to stroke
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Materials
l Microsoft Excel (used for all calculations and data processing) l HDI database (for this, the Human Development Reports published by the UN will be used, which
may be found in this link: ) l WHO database on mortalities due to cerebrovascular diseases (may be found in this link:
, note that the death estimates for 2000 and 2012 is used) l World Bank database on total population (may be found in this link: ) Data from these sources are chosen for two reasons: reliability (as the UN and World Bank can be considered as reliable and trustworthy sources for such data due to the nature of their organization), and a lack of other databases.
Methodology & Trial Investigation
The following trial investigation was conducted with a selection of seven nations, which can also be used to demonstrate the methodology of this investigation. These countries are: Austria, Denmark, Germany, Greece, Hungary, Portugal, and Spain. These countries are chosen as they are all European OECD nations, and therefore should have reasonably similar cultural and economic status, reducing the possible impact of unrelated outside factors such as lifestyle habits or dietary preferences. The correlation should therefore be reasonably strong, demonstrating that this investigation will work.
Firstly, data regarding the population, human development index, and population will be obtained from their respective databases for the years 2000 and 2012 (the only years when the WHO has presented data regarding causes of mortality on their website):
Table 1: Raw data showing the estimated death counts due to stroke, population and the HDI of selected countries in the specified years
Country
Austria Denmark Germany Greece Hungary Portugal
Spain
Human Development Index
2000 0.836 0.862 0.855 0.799 0.769 0.782 0.827
2012 0.884 0.921 0.915 0.865 0.823 0.827 0.874
Estimated death counts due to
stroke (in '000s of deaths)
2000
2012
8.8
5
5.2
3.6
82.4
59.9
22.9
20.7
18.8
13.3
22.8
12.8
36.6
29.6
Population
2000
2012
8,011,566 8,429,991
5,339,616 5,591,572
82,211,508 80,425,823
10,805,808 11,045,011
10,210,971 9,920,362
10,289,898 10,514,844
40,263,216 46,773,055
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To calculate death rates, the estimated death counts due to stroke can be divided by the population. This is the death rate due to stroke per person; to find the more conventional death rate per 100,000 population, the number can be multiplied by 100,000.
Sample calculations: Austria's death rate due to stroke per 100,000 population in 2000
=
8.8 = 8011566 = 0.001098412
100,000 = ? 100,000 = 0.001098412 ? 100,000 = 109.8 (Note that the final result is in 1 decimal place, as the data found on death counts is also in 1 decimal place.)
Table 2: Processed data showing the mortality rates caused due to strokes
Country
Mortality rates due to stroke per person
Mortality rates due to stroke per 100,000 population
2000
2012
2000
2012
Austria
0.001098412
0.000593120
109.8
59.3
Denmark
0.000973853
0.000643826
97.4
64.4
Germany
0.001002293
0.000744786
100.2
74.5
Greece
0.002119231
0.001874149
211.9
187.4
Hungary
0.001841157
0.001340677
184.1
134.1
Portugal
0.002215765
0.001217327
221.6
121.7
Spain
0.000909018
0.000632843
90.9
63.3
From here, it is a simple matter of averaging the death rates and HDI for both years, then comparing the two values for correlation:
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Table 3: Average mortality rates per 100,000
population due to stroke and HDI of selected
countries of during the years 2000 and 2012
Country
Average human development index
Average mortality rate due to stroke
per 100,000 population
Austria
0.860
84.6
Denmark
0.891
80.9
Germany
0.885
87.4
Greece
0.832
199.7
Hungary
0.796
159.1
Portugal
0.804
171.7
Spain
0.851
77.1
Chart 1: the relationship between HDI and mortality rates due to stroke per 100,000
population in trial nations
250.0
Death rate due to stroke per 100,000 population
200.0
150.0
100.0
50.0
0.0 0.780
0.800
0.820
0.840
0.860
Human development index
0.880
5 0.900
The investigation will follow exactly the same method, except with a larger number of countries.
Investigation and Results
The database used in obtaining HDI information divides countries based on four categories: very high HDI countries (countries with a HDI above 0.8 as of 2014), high HDI countries (between 0.7 to 0.8), medium HDI countries (between 0.55 to 0.7) and low HDI countries (below 0.55). Therefore, the
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countries categorized as having a "very high HDI" will be used in this investigation, as relatively few of them have a HDI below 0.75 during 2000 (which is the minimum HDI used for this investigation, as stated in the research question). As there are relatively few countries in this category ? only 49 ? and a few of them either lack data (such as Liechtenstein) or have a population that is relatively small (such as Singapore or Hong Kong), random sampling is not necessary; only 18 of these countries have sufficient data, an HDI that is consistently above 0.75 and a population size greater than 10 million since 2000, so these 18 countries shall be used.
The results are as follows:
Table 4: Raw data showing the HDI, death counts due to stroke and total population of nations with HDIs above 0.75 on the years 2000 and 2012
Country
Human development index
Death count due to stroke (in '000s of
deaths)
Total population
2000
2012
2000
2012
2000
2012
Argentina
0.762
0.831
27.4
28.2
19,153,000 22,728,254
Australia
0.898
0.932
12.2
11.0
37,057,453 42,095,224
Belgium
0.874
0.889
8.6
7.4
10,251,250 11,128,246
Canada Chile
0.867 0.752
0.910 0.827
15.5 7.4
13.5 8.4
30,769,700 15,170,387
34,751,476 17,388,437
Czech Republic 0.821
0.867
16.9
10.4
10,255,063 10,510,785
France Germany
0.848 0.855
0.886 0.915
40.9 82.4
34.4 59.9
60,912,498 82,211,508
65,659,790 80,425,823
Greece Italy
0.799 0.829
0.865 0.872
22.9 67.3
20.7 58.7
10,805,808 56,942,108
11,045,011 59,539,717
Japan
0.857
0.888
132.1
120.6 126,843,000 127,561,489
Korea (Republic of) Netherlands
Poland
0.821
0.877 0.786
0.893
0.920 0.838
41.6
12.5 66.8
27.8
8.8 64.5
22,840,218
15,925,513 38,258,629
24,763,353
16,754,962 38,063,164
Portugal
0.782
0.827
22.8
12.8
10,289,898 10,514,844
Spain
0.827
0.874
36.6
29.6
40,263,216 46,773,055
United Kingdom
0.865
0.901
62.1
46.3
58,892,514 63,700,300
United States
0.883
0.912
169.3
133.6 282,162,411 314,102,623
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Table 5: Processed data showing the mortality rate caused by stroke in the selected nations in 2000 and 2012
Country
Mortality rate due to stroke per person
2000
2012
Mortality rate due to stroke per
100,000 population
2000
2012
Argentina
0.001432383
0.001241697
143.2
124.2
Australia
0.00032908
0.00026096
32.9
26.1
Belgium
0.000840013
0.000661172
84.0
66.1
Canada
0.000503748
0.000387472
50.4
38.7
Chile
0.000490413
0.000482589
49.0
48.3
Czech Republic
0.001647081
0.000988891
164.7
98.9
France
0.00067176
0.000524081
67.2
52.4
Germany
0.001002107
0.000744576
100.2
74.5
Greece
0.002114838
0.001870679
211.5
187.1
Italy
0.001182507
0.000985131
118.3
98.5
Japan
0.001041133
0.000945319
104.1
94.5
Korea (Republic of)
0.001819974
0.00112458
182.0
112.5
Netherlands
0.000787218
0.000522311
78.7
52.2
Poland
0.001745275
0.001693969
174.5
169.4
Portugal
0.00221199
0.001213221
221.2
121.3
Spain
0.000909327
0.000632348
90.9
63.2
United Kingdom
0.001054875
0.000726532
105.5
72.7
United States
0.000600084
0.000425269
60.0
42.5
Table 6: the average HDI and mortality rates due to stroke during the years 2000 and 2012
Country
Argentina
Average human development index
0.796
Mortality rate due to stroke per 100,000
population 133.7
Australia
0.915
29.5
Belgium
0.881
75.1
Canada
0.889
44.6
Chile
0.790
48.7
Czech Republic
0.844
131.8
France
0.867
59.8
Germany
0.885
87.3
Greece
0.832
199.3
Italy
0.850
108.4
Japan
0.872
99.3
Korea (Republic of)
0.857
147.2
Netherlands Poland
0.899 0.812
65.5 172.0
Portugal
0.804
171.3
Spain
0.850
77.1
United Kingdom
0.883
89.1
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Chart 2: Scatter graph showing the relationship between HDI and Mortality rate due to stroke in
countries with HDIs above 0.75
250.0
Mortality rate per 100,000 population caused by stroke
200.0
150.0
100.0
50.0
0.0 0.750
0.770
0.790
0.810
0.830
0.850
Human development index
0.870
0.890
0.910
y = -803.25x + 787.78 R? = 0.37128
Here we can observe that there is one outlier with a mortality rate of 48.7 per 100,000 due to stroke, and a HDI of 0.790 (the value found in the bottom left of the other data points on the graph); this belongs to Chile. If this is taken out of consideration, we can see that the scatter graph forms a loose linear correlation, as displayed on the graph. The linear correlation therefore allows the use of a Pearson's product-moment coefficient for statistical testing.
Statistical Testing
To conduct a Pearson's correlation test, some values must be assigned: the variable X can be the mortality rate due to stroke, whereas Y is the human development index, and N denotes the number of countries. The total sum of each column is then found. Then, new columns for the values of XY, X2, and Y2 is needed. The result is as follows:
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