| Spend the least amount of time analyzing
trends in the Crude Death Rate. Quite possibly the Crude Death Rate,
since it is so greatly influenced by the age structure of a population,
will give you a false impression of mortality conditions in your two
populations. It is also an especially problematic "comparative" measure of
the force of mortality since oftentimes a young population with worse
mortality conditions will have a lower crude death rate than an
older population with better mortality conditions. |
|
| Spend more time analyzing trends in the
Infant Mortality Rate. The Infant Mortality Rate is a very sensitive
measure of not only the health conditions of infants but also of the
general health conditions of a population. In many populations it has
undergone dramatic changes over the last 55 years. |
|
| Spend the most time analyzing trends in
life expectancy. Life expectancy at birth is our best measure of
mortality; you can use it to directly compare the mortality levels of two
populations. It is also easy to understand. A female life expectancy
of 62 years means that the age-sex specific death rates in effect in a
particular year imply that a woman experiencing these rates would live to
be 62. It is also our best single comparative measure of mortality. You
can directly compare the life expectancies of two populations to determine
how much higher mortality is in one population than the other. If the
male life expectancy of one population is 50 and that of another
population is
75, then the mortality of the second population is really 50% higher than the
first. Analyzing changes in life expectancy over time is an easy way
of tracking the general mortality trends. |
|
| In your
analysis of life expectancy be sure to note if one population is "catching
up" with the other population with respect to LE. Looking at
the "Life Expectancy and Ratio between Life Expectancy Chart" is an easy
way of doing that. Is the "ratio" (left scale of chart) getting closer to
1? |
|
| Examine the "Annual Rate of Change, Life
Expectancy by Sex" charts for both populations. See if there is a
clear pattern of change, especially over the last ten to fifteen years.
You will need this analysis when it comes times for you to think about the
future course of mortality in each population. |
|
| Also look for gender differences in the
"Annual Rate of Change, Life Expectancy by Sex" charts for both
populations. See if both sexes are experiencing the same rate of
improvement or retrogression. |
|
| In analyzing the Gender Difference in Life
Expectancy Chart, your interest is in the sex differences in life
expectancy trends. Look at the "gap" between the female and male lines.
There "should be" (probably for biological reasons) a significant female
advantage. Focus on the time period from 1950 to 2005. What has happened
to that gap over time? |
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