HUMAN DEVELOPMENT INDEX
HOW DO WE
Geographers agree that the most effective tool to measure quality of life around
the world is the Human Development Index (HDI). Every year, the UN gathers
data from its member countries and ranks their HDI scores. In each country,
it considers indicators in three key areas of human development:
• longevity: the average life expectancy of the people in a country
• knowledge: the average number of years that adults have attended school,
and the expected years of schooling that a child just entering school will
complete
• country’s income: the total income of a country in one year, divided by
the number of people (Gross National Income [GNI] per person)
Together, the indicators give a “snapshot” of the quality of life of the
people in each country.
A country with top marks for every indicator would have an HDI score
of 1.000. In the 2014 Human Development Report, the world HDI was 0.702.
Compare this to the scores of the countries listed in Figure 5.14. For
example, Qatar’s GNI is well above Canada’s and yet Canada has a higher
HDI ranking. What kind of questions does this make you ask?
COMPARE
QUALITY OF LIFE?
Country
Rank
HDI Score
Human Development
Index (HDI) the results
of an annual evaluation of
countries made by looking at
life expectancy, literacy,
and income
Gross National Income (GNI)
per person the total, or gross,
income of a country in one
year, divided by the number
of people
Life
Expectancy
(years)
Adult
Schooling
(years)
Expected Child
Schooling
(years)
Average Income
per Person
($)
Very High HDI (0.800 to 1.000)
Many people compare their quality of life with the quality of life of others
living within their country. They also compare the overall quality of life
in their country to the overall quality of life of other countries. Country
leaders also compare. This can help them to decide on priorities and set
goals for developing their country and improving the quality of life for their
citizens. For example, they may prioritize healthcare or increased economic
development. Some leaders aim to bring their people freedom from unjust
treatment. In South Africa, decades of widespread racism affected the
quality of life of the majority of its Black citizens. In 1994, Nelson Mandela
ran for president to promote equality and freedom and encourage change.
He won the election (Figure 5.13).
FIGURE 5.13 For decades,
Nelson Mandela struggled to end
South Africa’s racist policies, even
from prison. In the 1994 election,
all citizens were allowed to vote
for the first time. Mandela was
elected president.
150
UNIT 2: Global Inequalities: Economic Development and Quality of Life
1
0.944
81.5
12.6
17.6
63 909
Canada
8
0.902
81.5
12.3
15.9
41 887
Qatar
31
0.851
78.4
9.1
13.8
119 029
High HDI (0.700 to 0.799)
Uruguay
50
0.790
77.2
8.4
15.5
18 108
Malaysia
62
0.773
75.0
9.5
12.7
21 824
China
91
0.719
75.3
7.5
12.9
11 477
WORLD
I wonder what changed in
South Africa so that a
person who was once in jail
could become president?
0.702
Medium HDI (0.550 to 0.699)
USING INDEXES TO MEASURE
QUALITY OF LIFE
Indexes help us understand development on a global scale. An index
summarizes data made from a set of observations. Examples of indexes
created to measure quality of life are the Human Development Index, the
Happy Planet Index, the World Happiness Report, and the Gross National
Happiness Index. Each index focuses on different factors and indicators.
Norway
Maldives
103
0.698
77.9
5.8
12.7
10 074
Vietnam
121
0.638
75.9
5.5
11.9
4 892
Bangladesh
142
0.558
70.7
5.1
10.0
2 713
Low HDI (0.000 to 0.549)
How can an
index help us to identify
geographic patterns in
quality of life?
Nepal
145
0.540
68.4
3.2
12.4
2 194
Sudan
166
0.473
62.1
3.1
7.3
3 428
Niger
187
0.337
58.4
1.4
5.4
873
FIGURE 5.14 This table lists some values for the HDI and its components from the Human
Development Report 2014. The HDI data was collected in 2013.
NEL
NEL
CHAPTER 5: Understanding Quality of Life
151
SCATTER GRAPHS
Country
A scatter graph shows a relationship between two sets of data.
Geographers use scatter graphs to analyze data about many themes,
including quality of life.
Each axis on a scatter graph represents a different set of data. So when
you read a scatter graph, you first check to see what the two sets of data
are. The points on the graph are where the values from each set of data
intersect. Check to see if the data form a pattern. If there is a pattern, you
know there is a relationship between the two sets of data.
Look at the scatter graphs in Figure 5.15. Figure 5.15A shows a positive
pattern—the data increases along the x axis and the y axis. Figure 5.15B
shows a negative pattern—as one set of data increases (x axis), the other
set decreases ( y axis). There is no pattern in Figure 5.15C. If a graph has
no pattern, referred to as a random pattern, there is no connection
between the two sets of data.
When you construct a scatter graph, you choose two sets of data. You
refer to the range of each set of data to decide which intervals to mark.
For example, in Figure 5.16, healthcare spending data ranges from 3.49 to
11.18. One axis on your graph would need to include intervals between
0 and 12. You label each axis based on the information it will show.
A
B
Positive
y
C
Negative
y
Healthcare
Spending
(% of GDP)
12
11
Angola
3.49
51.9
Bulgaria
7.27
73.5
Canada
11.18
81.5
Iran
5.95
74.0
Mongolia
5.26
67.5
10.86
82.6
Switzerland
Healthcare Spending and Life Expectancy
in Selected Countries, 2014
Life
Expectancy
(years)
FIGURE 5.16 Percent of GDP spent on healthcare and
years of life expectancy in selected countries, 2014
Healthcare spending (% of GDP)
ANALYZING AND CREATING
FIGURE 5.17 Scatter graph showing percent of GDP
spent on healthcare and years of life expectancy in
selected countries, 2014
Switzerland
10
9
8
Bulgaria
7
6
Iran
Mongolia
5
4
Angola
3
0
50
x
0
Random
STEP 2
FIGURE 5.15 These scatter
graphs show three different
patterns: positive, negative,
and random.
x
0
Draw the y axis starting from 0 on the x axis.
Number the lines from 0 to 1.0 in intervals of 0.1.
Label the y axis “HDI score.”
Plot the data in Figure 5.18. Put a red dot where
the two values for each country intersect. Do not
join the dots. Beside each dot, print the name of
the country.
x
What is the relationship between the data? Use the
information you have read on page 145 to explain
any connection between the data.
152
STEP 1
Does the data show a positive, negative, or
random pattern?
STEP 3
UNIT 2: Global Inequalities: Economic Development and Quality of Life
Draw an x axis on graph paper. Number the lines
from 0 to 14 in intervals of 1. Label the x axis “Adult
schooling (years).”
Give your graph an appropriate title.
STEP 5
HOW TO ANALYZE A SCATTER GRAPH
STEP 2
90
STEP 3
STEP 6
Examine the data in Figure 5.16 and the scatter
graph in Figure 5.17, which was created from
this data. What are the two sets of data shown
on the graph? What does each dot on the
graph represent?
70
80
Life expectancy (years)
STEP 1
STEP 4
0
60
HOW TO CREATE A SCATTER GRAPH
Look at the data in Figure 5.18. What does the
data represent? What are the two sets of data that
are included?
y
Canada
What pattern is created by the dots? What does
this tell you about the connection between HDI
scores and the number of years that adults have
gone to school?
Norway
Canada
Qatar
Chile
Sri Lanka
Botswana
Vietnam
Ethiopia
HDI Score
0.944
0.902
0.851
0.822
0.750
0.683
0.638
0.435
Adult Schooling
(years)
12.6
12.3
9.1
9.8
10.8
8.2
5.5
2.4
FIGURE 5.18 HDI scores and years of adult schooling in selected countries, 2014
NEL
NEL
CHAPTER 5: Understanding Quality of Life
153
HAPPINESS INDEXES
FOCUS ON
INTERPRET AND ANALYZE
As you continue your geographic education, you
need to develop certain skills. These skills include
interpreting and analyzing geographic data.
Geographers use tools such as tables, graphs,
diagrams, and maps to describe and organize
data. This makes it easier to look for patterns and
analyze trends, issues, and perspectives.
TRY IT
INTERPRETING AND ANALYZING A TABLE
When interpreting and analyzing a table, ask
yourself the following questions:
• What is the source of the data? Why was the
data created?
• What is the title of the table, and what are the
headings? What does the data represent?
• What significant patterns or differences can
you see for each category? What are your best
guesses based on the evidence?
1. In Figure 5.19, a high score is considered good for
life expectancy and HPI score. Explain whether this
is true for ecological footprint and for experienced
well-being, and explain why.
2. Use a graphic organizer, such as a web, to interpret
and analyze the information in Figure 5.19. In
the centre of your organizer, write the table’s
title. For each of the table’s three categories,
summarize what you see. For example, [country]
has the highest life expectancy and [country] has
the lowest. Note the connections to the HPI. For
example, [country] has high life expectancy and
high experienced well-being, but a low HPI.
3. Select two countries that seem to have a
disconnect between their HPI scores and the three
other factors. Explain this disconnect using the
data in the table.
CASE STUDY: HAPPY PLANET INDEX
The United Kingdom’s New Economics
Foundation (NEF) researches the
connections among the economy, the
environment, and a society’s well-being.
The NEF created the Happy Planet
Index (HPI) to measure three factors:
life expectancy, ecological footprint,
and people’s views of their experienced
well-being. Ecological footprint is the
amount of land needed by a country
to support a citizen’s daily living on
Earth. The experienced well-being data
reflects people’s responses to a survey
asking how satisfied they are with their
daily lives. Connecting well-being to
the use of natural resources allows an
overall look at a country’s sustainability
and also the planet’s sustainability.
The data in the 2012 HPI report
showed that no country comes close to
a high degree of sustainability. Why is
this? Mainly, people are using too many
natural resources.
154
Happy Planet Index Data and Scores
for Several Countries, 2012
Life
Expectancy
Ecological
Footprint
Experienced
Well-Being
(out of 10)
HPI Score
(out
of 100)
Costa Rica (1)
79.3
2.5
7.3
64.0
Vietnam (2)
75.2
1.4
5.8
60.0
Colombia (3)
73.7
1.8
6.4
59.8
Pakistan (15)
65.4
0.8
5.3
54.1
India (32)
65.4
0.9
5.0
50.9
China (60)
73.5
2.1
4.7
44.7
Canada (65)
81.0
6.4
7.7
43.6
Singapore
(90)
81.1
6.1
6.5
39.8
United States
(105)
78.5
7.2
7.2
37.3
Qatar (149)
78.4
11.7
6.6
25.2
Country
(rank out
of 151)
You read about the Happy Planet Index on page 154. The World Happiness
Report, created by the UN, also considers more than economic factors when
assessing quality of life. It suggests that six factors seem to be responsible for
differences in happiness: healthy life expectancy, having someone to count
on, freedom to make life choices, fair treatment in society, generosity of fellow
citizens, and household income. In 2013, the top six countries deemed to
be happy were Denmark, Norway, Switzerland, the Netherlands, Sweden,
and Canada.
Bhutan created the Gross National Happiness Index (Figure 5.20) as
another way to measure quality of life. It surveys its people to assess their
spiritual, physical, and social well-being, and it measures the health of the
natural environment. The survey divides happiness into four categories:
unhappy, narrowly happy (slightly happy), extensively happy (happy in many
areas), and deeply happy (very happy). In 2010, the results showed that
10.4 percent of the people were unhappy; 47.8 percent were narrowly happy;
32.6 percent were extensively happy; and 8.3 percent were deeply happy.
The results also showed that men were happier than women, and urban
dwellers were generally happier than rural dwellers. The country uses the
results of the data to try to develop policies to increase happiness.
MEASURING INEQUALITIES
Currently there are no indexes that measure all aspects of quality of life.
Also, many indexes, such as the HDI, create a score for a whole country.
They do not measure levels of inequality within a country. For example,
life expectancy of Aboriginal peoples in Canada is six to nine years below
the Canadian average, and income is about 30 percent lower. However,
the UN’s Inequality-adjusted Human Development Index (IHDI) does
measure inequalities within a country. When Canada is measured by the
IHDI, its HDI ranking drops. In 2013, Canada’s HDI was 0.902 but its IHDI
was lower at 0.833. Aboriginal peoples are working hard to narrow the
gaps between their quality of life and the Canadian average. Changes are
slowly happening.
How would I try to calculate
happiness in my country?
Inequality-adjusted
Human Development Index
(IHDI) the results of
an annual evaluation of
countries made by looking
at life expectancy, income,
and literacy, and how these
are distributed among the
population
CHECK-IN
1. EVALUATE AND DRAW CONCLUSIONS Some people
argue that the HDI is not a good tool for
measuring quality of life. They say that it does
not examine conditions that affect people’s
satisfaction with their life or their overall
happiness. Evaluate this argument with a partner
and arrive at a conclusion together.
FIGURE 5.19 This table shows the data used to calculate the results for
several countries on the 2012 Happy Planet Index. The life expectancy data
is from the Human Development Report 2011.
UNIT 2: Global Inequalities: Economic Development and Quality of Life
FIGURE 5.20 Bhutan created
the Gross National Happiness
Index to measure the quality
of life of its citizens. Spiritual
well-being of its people and
health of the natural environment
are measured on the index.
NEL
NEL
2.
INTERRELATIONSHIPS Create a graphic organizer to
identify connections between all of these three
sets of indicators:
• life expectancy and gross national income per
person
• gross national income per person and average
years of adult schooling
• average years of adult schooling and life
expectancy
CHAPTER 5: Understanding Quality of Life
155