Mortality Rate Versus Age: An Historical Iowa City Human Population Study
This study is a microcosm of a global issue: human population trends. By conducting an historical analysis of the population of your town (in this example, Iowa City) complete with demographic data from three different time periods in the city's history and some background information from the library, students get a glimpse of local mortality and survivorship change that mirrors a worldwide trend. Ecologists divide populations into age classes and assign mortality rates to each class in order to gain insight into historical influences on birth and death rates, to make predictions
for future growth, and to generally better understand the ecology and evolution of life histories. By constructing life tables from local data, one can make insightful judgments about the demographics of mortality and local population trends, with direct application regionally and globally.
For the investigator interested in localized human population trends and demographics, the cemetery makes for an ideal data source. Here in Iowa City we have the Oakland Cemetery- with records dating back nearly 200 years, with over 30,000 citizens interred there. This setting provides a rich source of information for determining the birth dates, sexes, and death rates of Iowans over three different periods in Iowa City history. The accumulated data enable students to identify vulnerable age groups, differentiate the mortality rates of different periods, construct comparative graphs of survivorship, and make links to prevailing conditions in which people had lived. Additional sources of information should be provided for students to "fill in the details" as to significant contributors to mortality specific to each time period. Ultimately they should be able to paint a complete picture of not only the town's demographics with regard to mortality, age, and gender, but make predictions upon future mortality and survivorship based on this study.
Student | Instructor | Suggested Resources
- Sampling is conducted at a large cemetery. Be sure to procure permission from the manager so as not to interfere with funerals or maintenance duties.
- A map should be provided for cemetery layout.
- Cemeteries are often arranged whereby oldest graves are located near
the office, and progressively newer graves are found farther out from
- Prepare to gather four sets of data:
a) for those who had been born prior to 1850
b) those born between 1850 and 1900
c) those born between 1900 and 1950
d) those born after 1950
For each of the above sample groups, collect the following information:
Sex, date of birth, age at death
- A rich sample of data is required in order to establish trends and make inferences, so collect as many gravestone records as you can for each period.
- Set up four data tables in which you record the sex, birth year and death year for groups of individuals comprising each of the four time periods. Also include a column for calculating the mortality rate for each age group (see example below). Note: total number column is to include all the deceased in your study who survived beyond a particular age group.
- Sampling tip: results of the study may be skewed if all your data on a particular birth-year group are collected from graves in close proximity. Your sampling scheme should involve establishing the geographical range of gravestones of interest, then collecting data from across the range.
- Graphically represent your data for identifying trends and for comparison. For example, generate a survivorship curve (line graph) by plotting age group vs. number of individuals (n). Also generate a mortality rate (M) vs. Age line graph for each of the three periods. Distinguish males from females on each graph.
- Comparisons of the survivorship curves and mortality rate vs. age graphs should yield insights characteristic of each time period. Consult literature to seek a complete explanation of events behind discrepancies seen between mortality and survivorship over the three time periods.Prepare to make predictions about survivorship and mortality for the future based upon your findings.