Cemetery lab, Human Demography
This laboratory exercise is adapted from the one created Nancy Flood and tested and presented by Charles N Horn for the project Experiments to Teach Ecology (1993, edited by J.M. Beiswenger), sponsored by the Ecological Society of America. The original laboratory exercise is available at http://tiee.ecoed.net/ under “Teaching” It may also be downloaded from the Course Materials section of our course page. You should read the original exercise for general background information and this adaptation for specific instructions.
See the original Introduction and Objectives in Flood (1993).
Methods – Data Collection
1. Select a cemetery in your community that you can visit to collect data. If it is not possible for you to visit a cemetery in person, please notify the instructor to obtain a dataset for analysis.
2. When visiting the cemetery, be aware and respectful of local customs. Obtain permission if necessary, and do not disturb persons who may be visiting the graves of relatives. Avoid areas where a service is being held.
3. Choose two cohorts you can compare. Depending on the cemetery, you may immediately be able to identify two cohorts of interest. For example, perhaps one section of the cemetery has graves from an earlier time period, or maybe people of different ethnic groups were traditionally buried in different sections of the cemetery. Here are some possible examples of cohorts:
a. Persons born 1801-1820, versus persons born 1871-1890
b. Persons who died 1861-1870, versus persons who died 1916-1925
c. Persons buried in a traditional European-American cemetery 1851-1900, versus persons buried in a traditional African-American cemetery 1851-1900
d. Think of another example that is applicable to the cemetery you are studying
4. Use Table 1 from Flood (1993) to collect the following information from at least 100 tombstones: Birth Year, Death Year, Age at Death, Sex
a. Many tombstones will list the Birth Year and Death Year. Calculate Age at Death as (Death Year) – (Birth Year). For purposes of this project, ignore the month and day of birth; just use years. An infant who was born and died in the same year will have an Age at Death of zero. You don’t have to do your calculations while in the cemetery- as long as you collect Birth Year and Death Year, you can calculate Age at Death later.
b. Some tombstones will list Age at Death and either Birth Year or Death Year. Calculate Birth Year as (Death Year) – (Age at Death). Calculate Death Year as (Birth Year) + (Age at Death).
c. If the tombstone doesn’t list enough information for you to determine both Birth Year and Age at Death, go on to the next tombstone. You need to have at least 100 tombstones for which you have both Birth Year and Age at Death.
d. Determine sex from the name if reasonably obvious; Sarah and Mary are probably females, and Thomas and William are probably males. If the name is used for both males and females (Tracy, Kimberly, Kelly, Cameron, etc), look for clues on the epithet, such as “husband of …”, “daughter of …” If you are not reasonably sure of the sex of the person, go on to the next tombstone.
5. Try to get about half of your samples from each of the cohorts you will be comparing. For example, if you are comparing persons born 1801-1850 with persons born 1851-1900, get about 50 from each group.
Table A – See instructions following Table B, under “Methods”
Name of cemetery: ____________________________________
Town/city of cemetery: ________________________________
County of cemetery: __________________________________
State/province of cemetery: ____________________________
Country of cemetery: _______________________________
Cohort 1: __________________________________________
Cohort 2: __________________________________________
Cohort 1 Cohort 2
Age class Age at start x dx nx lx Log10(1000*lx) dx nx lx Log10(1000*lx)
0-9 0 0
10-19 10 1
20-29 20 2
30-39 30 3
40-49 40 4
50-59 50 5
60-69 60 6
70-79 70 7
80-89 80 8
90-99 90 9
100-109 100 10
110-119 110 11
120+ 120 12
Total
Additional background information about the cemetery: _________________________
Table B – An example of a life table based on cemetery data
Data from the burial records of Trinity Church, an Episcopalian parish in St. Mary’s City, Maryland (http://ftp.rootsweb.com/pub/usgenweb/md/stmary/cemeteries/trinity.txt)
Born 1801-1850 Females Males
Age class Age at start x dx nx lx Log10(1000*lx) dx nx lx Log10(1000*lx)
0-9 0 0 4 83 1 3 9 92 1 3
10-19 10 1 1 79 0.9518 2.978549 1 83 0.902 2.95529027
20-29 20 2 7 78 0.9398 2.97301651 7 82 0.891 2.95002603
30-39 30 3 4 71 0.8554 2.93218026 6 75 0.815 2.91127344
40-49 40 4 4 67 0.8072 2.90699671 10 69 0.75 2.87506126
50-59
50 5 7 63 0.759 2.88026246 11 59 0.641 2.80706418
60-69 60 6 14 56 0.6747 2.82910993 20 48 0.522 2.71745341
70-79 70 7 24 42 0.506 2.7041712 16 28 0.304 2.4833702
80-89 80 8 14
18
0.2169 2.33619441 11 12 0.13 2.11539342
90-99 90 9 4 4
0.0482 1.6829819 1 1 0.011 1.03621217
100-109 100 10 0 0 0 #NUM! 0 0 0 #NUM!
110-119 110 11 0 0 0 #NUM! 0 0 0 #NUM!
120+ 120 12 0 0 0 #NUM! 0 0 0 #NUM!
Total 83 92
Born 1851-1900 Females Males
Age class Age at start x dx nx lx Log10(1000*lx) dx nx lx Log10(1000*lx)
0-9 0 0 13 157 1 3 17 142 1 3
10-19 10 1 4 144 0.9172 2.96246284 4 125 0.88 2.94462167
20-29 20 2 7 140 0.8917 2.95022838 9 121 0.852 2.93049703
30-39 30 3 6 133 0.8471 2.92795199 5 112 0.789 2.89692968
40-49 40 4 6 127 0.8089 2.90790407 4 107 0.754 2.87709543
50-59 50 5 11 121 0.7707 2.88688572 14 103 0.725 2.86054888
60-69 60 6 23 110 0.7006 2.84549303 22 89 0.627 2.79710166
70-79 70 7 35 87 0.5541 2.7436196 35 67 0.472 2.67378646
80-89 80 8 35 52 0.3312 2.52010369 26 32 0.225 2.35286163
90-99 90 9 15 17 0.1083 2.03454927 6 6 0.042 1.62586291
100-109 100 10 2 2 0.0127 1.10513034 0 0 0 #NUM!
110-119 110 11 0 0 0 #NUM! 0 0 0 #NUM!
120+ 120 12 0 0 0 #NUM! 0 0 0 #NUM!
Total 157 142
The cemetery contains one site dating from the 1600s, the grave of the first royal governor of Maryland, but most of the tombstones transcribed in the online database date from the 1800s and 1900s.
Graph accompanying the life table examples in Table B:
Survivorship curves by sex, for individuals born 1801-1850 and 1851-1900
Methods – Data Analysis
1. Complete any remaining calculations, so that you have both Birth Year and Age at Death for all individuals.
2. If you are comfortable with spreadsheets, you will probably find it simple to enter your data as follows. You can then use the spreadsheet sort function to easily tabulate your data. Alternatively, you could tabulate the data by hand.
Sex Birth Year Death Year Age at Death
m 1648 1693 45
f 1740 1816 76
f 1756 1833 77
etc
3. In Table A within this exercise, provide some background information about the cemetery and cohorts you chose to study.
4. Summarize your data by filling in Table A, with each cohort in its own section. Follow the example in Table B. Please note that dx refers to the number of individuals who die within each of the specified age intervals. For example, if 4 persons died when between ages 0-9 at time of death, enter 4 in that cell. The total number of deaths should equal the total number of tombstones you counted.
5. The column labeled nx is for the number of persons alive at the start of each interval. For the first interval (ages 0-9), all of the persons are alive at the start, so that number is equal to the total number of tombstones. For this column, it is easiest to start from the bottom and work up. If you have any individuals 120 years or older at death, that number would go in the bottom row. The row above (for individuals 110-119 years of age) would be equal to the sum of nx for the row below plus dx for the same row. For example, to calculate nx for age interval x=11 (ages 110-119), calculate n11 = n12 + d11
6. Please note that nx as calculated above corresponds to lx as listed in Flood (1993). We are using a more conventional notation.
7. For each row, calculate lx as the proportion surviving to start age interval x. For each row, this would be equal to the number alive at the start of that interval (nx) divided by the total number of persons in the cohort. Please note that the lx you calculate is not the same as the lx calculated in Flood (1993); we are using the more conventional notation.
8. For graphing, calculate the log10 of each lx multiplied by 1000. In effect, you are first calculating the number of persons out of a starting 1000 who would survive to start each age interval. You then place it on a log scale so you can see the pattern more clearly in a graph. Note that the base 10 logarithm of zero is undefined; we will graph that value as zero. Most calculators have a log10 key, shown simply as log. If your calculator does not have a log key, you can go to the Calculator tools (under Accessories on a Windows computer) and choose the Scientific view. Macintosh and Linux have similar scientific calculator tools. The spreadsheet demgraph.xls will perform the calculations for you.
9. Graph the log10(1000*lx) on the y-axis and the age at the start of each interval on the x axis. You may produce the graph by hand using the axes on the next page, scan the picture, and copy the picture file into this document. Alternatively, you may produce a graph using the spreadsheet demgraph.xls on the course website and copy the graph here.
Description of cohort 1: _____________________________________
Description of cohort 2: _____________________________________
Plot the data for cohorts 1 and 2, using different colors/symbols/line styles for the two cohorts. For example, plot cohort 1 with pink circles and connect with a solid line, and plot cohort 2 with blue triangles and connect with a dashed line. Please include a legend to identify which line refers to which cohort. If you are copying a graph from Excel or another program, you can delete the graph template below and paste in the graph you produced in Excel.
Questions
1. Do the survivorship curves for your two cohorts differ from one another? Describe and explain any differences. If there are no discernable differences, explain why this may be the case.
2. Examine the survivorship curves provided with Table B. These depict males and females separately for two cohorts of persons buried in a church cemetery in St. Mary’s County, Maryland. One cohort consists of persons born 1801-1850, and persons in the other cohort were born 1851-1900. What differences do you notice between the male and female curves for the 1801-1850 cohort? Do you see a similar pattern in the 1851-1900 cohort? Is the pattern consistent with what you know about male and female life expectancies in the USA today? Do you observe a similar pattern in your own data set? If you have enough males and females in your dataset, you may graph the male-female data to help you answer the question. The spreadsheet demgraph.xls has a worksheet (template- 4 lines on graph) that will help you.
3. When examining a birth cohort (such as was done with the example in Table B), it is important to follow the cohort through the death of the last individual. How would your survivorship curves be affected if you were to study a later birth cohort, such as persons born 1901-1950?
4. When examining a death cohort (a hypothetical example might be persons who died between 1916-1925), how would your data be affected if the cemetery were a relatively new one?
5. In your data, do you see any evidence of events causing a large number of deaths, such as wars or the influenza pandemic? Why or why not?
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