Computation and Measurement of Risk - Mathematics and Statistics for the Environment - page 201

8.4.4 p roportionate m ortality
Proportionate mortality describes the proportion of deaths in a specified population over a period
of time attributable to different causes. Each cause is expressed as a percentage of all deaths, and
the sum of the causes must add to 100%. These proportions are not mortality rates, because the
denominator is all deaths rather than the population in which the deaths occurred.

8.4.4.1 Method for Calculating Proportionate Mortality
For a specified population over a specified period,

Deaths causedbyaparticular cause
Deaths fromall causes

×100

The distribution of primary causes of death in the United States in 2003 for the entire population
(all ages) and for persons ages 25 to 44 years are provided in Table 8.1. As illustrated in that table,
accidents (unintentional injuries) accounted for 4.3% of all deaths but 21.6% of deaths among 25- to
44-year-olds (WISQARS, 2012).
Sometimes, particularly in occupational environmental health, proportionate mortality is used
to compare deaths in a population of interest (say, a workplace) with the proportionate mortality
in the broader population. This comparison of two proportionate mortalities is referred to as a
proportionate mortality ratio , or PMR for short. A PMR greater than 1.0 indicates that a par-
ticular cause accounts for a greater proportion of deaths in the population of interest than might
be expected; for example, construction workers may be more likely to die of injuries than the
general population. PMRs can be misleading, though, because they are not based on mortality
rates. A low cause-specific mortality rate in the population of interest can elevate the proportion-
ate mortalities of all of the other causes, because they must add up to 100%. Those workers with
a high injury-related proportionate mortality very likely have lower proportionate mortalities for
chronic or disabling conditions that keep people out of the workforce. In other words, people who
work are more likely to be healthier than the population as a whole—this is known as the healthy
worker effect .

■ EXAMPLE 8.19
Problem: Using the data in Table 8.7, calculate the missing proportionate mortalities for persons
ages 25-44 years for diseases of the heart and assaults (homicide).

Solution:

Proportionate mortality for diseases of the heart, 25- to 44-year-olds

= Number of deaths fromdiseases of theheart
Number of deaths fromall causes

× 100

( ) ×=

= 16 , 83 128 294 , 100 12 6 . %

Proportionate mortality for assaults (homicide), 25- to 44-year-olds

= Number of deaths fromassaults (homicides)
Number of deaths fromall causes

× 100

( ) ×=

= 7367 128 294 , 100 57 . %