You’ve probably heard the quote—"there are three kinds of lies: lies, damned lies, and statistics.” The line is so widespread, and its attributions so many, that it has a Wikipedia page dedicated just to listing all the people who are said to have first said it. The sentiment is plain enough—statistical data gets a bad rap, especially in politics and economics. As much as it might be intended to represent hard data, it can also be presented to mislead, or miscalculated, or gathered incompletely, and suggest correlations that are far from true—or much more distantly related. A classic example of the latter: graphing monthly ice cream sales and monthly shark attacks shows an extremely close correlation, which has a great deal more to do with summer weather and beach trips than dessert-loving chondrichthyans. On the other hand, of course, statistical analyses form the basis for a large part of modern medicine—it takes a huge number of cases to conclude anything about the human body overall. If the scale is even bigger, the necessity of statistical analysis is guaranteed.
When dealing with death records, statistical analysis may be the most important reason they’re compiled. Vital statistics have earned their name, and from outbreaks of Ebola to the hazards of smoking to the discovery of asbestosis, they are still very vital to human health.
They also have an intriguing history—after all, we haven’t always kept records of deaths or their causes. There had to be a few pioneering statisticians, once those records began to be kept, who first wondered what we could learn from the numbers.
One of the very first of those was, oddly enough, not a physician, a scientist, a politician, or a mathematician—he was a haberdasher, selling sewing supplies in London in the mid-1600’s. This was during the collection and publication of the London Bills of Mortality, which listed the weekly deaths in each of London’s districts, grouped by cause, and had been started to document the progress of the Plague. The Bills of Mortality collected very little beyond a tally next to a rudimentary diagnosis, and the diagnoses were determined at the time by Searchers of the Dead, whose usual qualifications were being unmarried older women who needed money, and had nothing to do with medical training. Names, sexes, and ages were not included—but John Graunt, a haberdasher and the son of a draper, armed with a statistical approach and a fascination with the possibilities of those tallies, took that data and was able to produce critiques on the diagnostic system, an estimate of London’s population and its rate of change, projections of spread, increase, and mortality of various forms of disease, and even the very first table of average life expectancies—what proportion of male or female citizens of London died in infancy, childhood, adolescence, and adulthood, based entirely on extrapolations from those contextless causes of death.
He recorded his process, his tables, and his conclusions in a book called Natural and Political Observations Made Upon the Bills of Mortality, published first in 1662 and then reprinted in 1663 and several more times thereafter, with one notable change between them—after the first printing, the author was no longer listed as simply “John Graunt, Citizen of London”, a concerned and curious sewing-shop supplier. In the reprinted editions, he is given as “John Graunt, Fellow of the Royal Society”—after presenting his book to them, the scientists and physicians of the Royal Society of London accepted him as a member, with the direct endorsement of King Charles II, based on the significance of his work. He is still regarded as one of the first epidemiologists, and one of the founders of the modern study of demographic analysis.
That was the first of many uses of records of deaths, but it set the stage and set the tone for many more to follow him—a few more unexpected pioneers of death statistics will be explored in a companion to this article, including one more familiar for the celestial body that bears his name; and one best-known for his role in the Salem witch trials, and little remembered for his interest in public health statistics.