# data[].attributes.body
Analysis:

The highest percentage we see in all of the three countries is Malawi with a percentage of 14.4% (9.7 more than Canada’s 4.7% and 10.7 more than Spain’s 3.7%. This is followed by Canada with a percentage of 4.7% (9.7 less than Malawi’s 14.4%). Finally, Spain in third place is seen with a percentage of 3.7% (1 Less than Canada and 10.7 Less than Malawi).

# data[].attributes.body
Analysis:

The highest percentage within this data set of three countries is Spain with 10.3% (1.4 greater than Canada and 9.4 greater than Malawi). This is followed by Canada at 8.9% (1.4 less than Spain and 8 greater than Malawi. Finally, Malawi in third place has a percentage of 0.9% (8 Less than Canada and 9.4 less than Spain).

# data[].attributes.body
Definitions

1. Life expectancy

The total portion of the population where people are ages 75 and above. This is different from the measuring life expectancy of the average period that a person might live using statistics from all ages.

2. Birth rate

The total portion of the population where people are ages 0-4. This is different from birth rate calculated by dividing the number of live births in a population in a year by the midyear resident population.

3. Dependency load

The total portion of the population that is not in the workforce who are 14 and younger and 65 and older.

# data[].attributes.body
Analysis:

The highest total dependency load out of all three countries is Malawi at 43.2%. Second is Canada at 35.1% and third is Spain at 34%. Malawi, although having the highest total dependency load, contains a younger dependency load of 40.7% and only an older dependency load of 2.5%, the lowest dependency out of all countries. Spain, in comparison, has a smaller younger dependency than Malawi with it only being 13% but contains a higher older dependency with a dependency load of 21%. Finally, Canada has a slightly higher younger dependency than Spain with the dependency load being 15.1% but contains a slightly smaller older dependency than Spain with a dependency load of 20%.

# data[].attributes.body
Why do differences in life expectancy, birth rate and dependency load exist between countries?

Differences in life expectancy, birth rate, and dependency are certain to exist between countries through many factors influenced by many things. Some of the main factors in which countries can have differences in life expectancy are health care, housing, and quality of life. Access to affordable and quality healthcare can significantly impact the differences in countries as it increases life expectancy. Additionally, countries with safe, clean, and stable housing reduces exposure to diseases and injuries which contributes to the differences in life expectancy, birth rate, and dependency load of different countries. Finally, these reasons all combine together and create the differences between life expectancy, birth rate, and dependency load between different countries and is why we see differences in the charts that displays the data.

# data[].attributes.body
Why is it important or useful to look at this information now and in the future?

This information is important and useful to use now and in the near future as it allows us to collect projections for future planning. An example of planning can include governments and organizations using this data to ensure a balanced workforce that supports economic growth and deciding if healthcare and pension systems should improved to compensate for the dependency load. Using this data can also determine if there are higher birth rates which can indicate the need for more schools in the future while declining birth rates and aging populations highlight the importance of the dependency load.

Why is it important to understand that there are differences between life expectancies and birth rates between countries?

It is important to understand the differences between life expectancies and birth rates between countries as understanding these differences allows global issues like migration, resource allocation, and labour markets to be known. High birth rates in developing countries might indicate a need for improved family planning, while low birth rates in developed nations can result in aging populations and a need for policies to support the older dependency load. Additionally, awareness of these differences enables tailored healthcare, education, and policies to apply to specific regional challenges.