Life Expectancy of Major League Baseball Umpires
Richard S. Cohen, MD; Celia A. Kamps, PhD; Stephen Kokoska, PhD; Erwin M. Segal, PhD; James B. Tucker, MD
THE PHYSICIAN AND SPORTSMEDICINE - VOL 28 - NO. 5 - MAY 2000
BACKGROUND: The on-field death 4 years ago of a veteran Major League Baseball (MLB) umpire raised questions regarding the mortality risks of this profession.
OBJECTIVE: To determine if the life expectancy of MLB umpires differs from that of the general population.
DESIGN: Ages of death of MLB umpires were determined, and the differences between the ages of death and age-adjusted life expectancies were calculated. T-score analysis was performed on these differences. Correlational analysis was also done on many different factors, including umpire debut year, debut age, life expectancy at debut, and length of career.
RESULTS: No significant difference was found between the age at death of MLB umpires and their age-adjusted life expectancy. Correlational analyses showed that only length of career correlated with age at death.
CONCLUSION: MLB umpiring is not associated with a shortened life expectancy. While this is most likely attributable to the profession having no inherent risk, it could also be explained by inherent risks being overcome by yet unidentified, unique factors.
Umpire John McSherry collapsed and died behind home plate at Riverfront Stadium in Cincinnati moments after the start of the opening game of the 1996 Major League Baseball (MLB) season. Several weeks later, Eric Gregg, another National League umpire, took a medical leave of absence to lose weight. These events, the obvious obesity of both men, and the relative lack of physical conditioning required for umpiring in MLB raised questions about the health risks of umpires. Baseball umpiring is a relatively sedentary officiating position, and baseball, unlike other sports, permits on-field hostility toward its officials, thus increasing the level of on-the-job stress. Significant travel, isolation, and other job stressors could also contribute to an increased health risk.
A literature search revealed that little empiric data exist on the morbidity or mortality risks of baseball umpiring and that existing work in this area has been unrelated to issues of umpire health (1-6). Some mortality studies related to athletics have been done, but these involve former athletes, rather than sports officials (7-17).
Sample and characteristics. A search list of 441 names was compiled using the National League and American League umpire rosters in Total Baseball: The Official Encyclopedia Of Major League Baseball (18). This reference contains birth and death dates for MLB players and managers but, unfortunately, does not include this information for umpires. The rosters are all-inclusive in that they list umpires who are still active, those alive but no longer working in the major leagues, and those deceased. Dates of birth and death were obtained from various sources, including the National Baseball Library in Cooperstown, New York; death certificate data, obituaries, personal correspondence with Larry Gerlach, PhD (professor of history at the University of Utah, founding chair of the Rules and Umpires Committee of the Society of American Baseball Research, and past president of that organization), and Pete Palmer, coeditor of Total Baseball (18), the umpire card file at The Sporting News, and an address list (19).
From the original list of 441 umpires, data were available for 227 who had died or had retired and were still living. Of these, dates of birth and death were available for 195 white men. Dates of birth and death for the remaining umpires were not found. (One black umpire was removed from the study because the available mortality data used were based on white men.) The sample spans the entire history of MLB up to 1995. The earliest date of birth in the sample was 1836, and the most recent was 1945. The earliest year of death was 1894 and the latest 1997. The youngest began umpiring in the major leagues at age 17, and the oldest debuted at age 50. Fifty-six (25%) umpires served in the major leagues only 1 year, and 1 umpire served for 37 years. Part-time and minor league umpires were not included in the study.
Calculations. Standard life tables were used to calculate age-adjusted life expectancy for each umpire based on his age when he began service in the major leagues. This age-adjusted life expectancy compares each umpire with his age-equivalent cohort alive at the time of the umpiring debut. These tables are based on decade (20) or greater-than-1-decade (21) information. Use of such life expectancy tables ensures stability of the actuarial data for comparison purposes. Life expectancy data within each period were interpolated to generate the life expectancy for each umpire.
The following data were examined: (1) actual or estimated age at death for each umpire (death age) and (2) life expectancy for each umpire at time of debut (predicted death age). The mean differences between death age and predicted death age were analyzed in several ways.
Deceased-umpire data analysis. The first analysis considered all umpires who had died (table 1-A). The average umpire in this group lived roughly one-half year less (-0.53 years) than expected according to the actuarial tables. Statistical analysis shows that this difference is not significant (t = -0.51, degrees of freedom [df] = 194, P > 0.50).
All-umpire data analysis. Living former umpires (with their calculated estimated death age based on current life expectancy as of January 1, 1998) were added to this set of data, and the analysis was repeated (table 1-B). Calculations reveal that the average umpire lived, or is expected to live, almost 1 year longer than predicted at his debut (t = 1.02, df = 226, P > 0.30), but this difference is not statistically significant.
Unbiased analysis. Those umpires who constitute the only unbiased sample are those for whom the entire cohort has already died. In this analysis, the umpires lived 1.8 years longer than predicted from the life expectancy tables (table 2-A). As in the previous analyses, the difference was not significant (t = 1.55, df = 152, P > 0.10).
Other analyses. The set of umpires with at least one living cohort member, the next oldest group, was subjected to analysis. Table 2-B presents analysis of data from both living and deceased former umpires, all of whom were born after 1909 (the last year of birth for the cohort for whom there are no survivors). This analysis shows no significant difference from the life expectancy tables.
Correlational analysis. A correlational analysis was performed to assess several factors, including year of birth, year of death, age at death, predicted age at death, the difference between age at death and predicted age at death, debut year, debut age, life expectancy at debut, length of career, years as a player (if any), age at retirement, and years retired. Only length of career correlated with age at death.
The analyses relied on data from full-time MLB umpires, and statistical inferences apply only to that population. Part-time and minor league umpires may have mortality data different from the present analysis, and were thus not considered. Dale's study (2) revealed a difference in personality characteristics between major league umpires and lower level umpires, but did not examine the causes of death.
Deceased-umpire analysis and bias. No effort was made in this analysis to offset any statistical biases. If the data are unbiased and the life expectancies of umpires were essentially the same as that of the nonumpire cohort of the corresponding age, the average difference between these numbers would be close to zero. A mean difference as large as 0.53 years between actual age at death and expected age at death would occur more than half the time according to the calculated probability (see table 1-A). Thus the difference noted is most likely due to chance.
However, analysis of the entire cohort of deceased umpires does bias the results toward a finding that umpires have a shorter life than expected. Bias stems from the fact that if only deceased umpires are considered, all umpires still alive are eliminated from consideration, regardless of how old they may be when they die. Some of these umpires have already outlived their predicted age of death; many others might also.
All-umpire analysis. When living former umpires are added to the analysis, the result changes but still is not statistically significant (see table 1-B). In this case, such a difference would occur about 30% of the time even if the actual average life expectancies of umpires were identical to their predicted life expectancies. Thus, the addition of living former umpires only partially offsets the bias toward lower life expectancy inherent in the initial analysis of deceased umpires only (see table 1-A). Mortality biases still remain, however, since living active umpires have not been added to the set of data.
Unbiased analysis. Only one group of deceased umpires can be analyzed without any obvious selection bias—those for whom the entire umpire cohort has already died. The major limitation of this analysis is that this does not consider any umpires from the modern era.
Other analyses. The bias from such selection skews the results depending on the population selected. Analysis of only deceased umpires gives a decreased lifespan for umpires (-9.02 years; n = 42, t = -4.85, df = 41, P < 0.00001), and analysis of only living former umpires gives an equally strong bias in the other direction (+9.99 years; n = 32, t = 12.08, df = 31, P < 0. 00001). Although the biases in these analyses are obvious, they demonstrate that the analyses presented in table 1 contain unavoidable but clear biases.
Correlational analysis. As noted above, the correlation of length of career with age at death is plausible because of the healthy worker effect (22), which makes any group of individuals who are working appear to have a longer life expectancy than age-matched cohorts who are not working, regardless of occupation. No factors had any effect other than what might be expected independent of that variable.
These analyses indicate that the actual life expectancy of MLB umpires is no different from their predicted life expectancy. This leads to one of two possible conclusions.
The first (and most likely) conclusion is that the factors suspected of placing MLB umpires at risk are simply not at work. Regardless of the era, umpires may not be subjected to enough continuous stressors to incur any adverse impact from them. The overall length of time on the field in a workday is relatively short, usually no more than 4 hours, and an umpire is in charge of a game behind the plate in only one in every four games.
The second possible conclusion is that MLB umpires, even by living to their life expectancy, actually live longer than would be expected considering those factors working against them. Perhaps their personality makeup (2), in ways not currently understood, insulates them from work stressors and, therefore, from a premature death.
A Parting Word
MLB umpires have a career associated with a normal life span. While people die unexpectedly in all jobs and in all conditions, umpires do not die unexpectedly or early because of inherent risks in their profession. This normal life span demonstrates either that no significant inherent mortality risks exist, or that vocational risks have been overcome for unexplained reasons.
MLB umpires should be approached like all patients. Their medical risk factors and the stresses in their professional and personal lives should be identified and addressed. MLB can serve as a visible example to other employers by openly requiring regular comprehensive healthcare and risk-factor modification for these valuable employees.
The authors wish to thank the following for their assistance: Larry Gerlach, PhD, Pete Palmer, Joel Plotkin, William Grant, the staff at the National Baseball Library, and the staff at The Sporting News.
Dr Cohen is clinical assistant professor in the Department of Family Medicine and Dr Kamps is residency coordinator in the Department of Anesthesiology at Upstate Medical University in Syracuse, New York. Dr Kokoska is professor of mathematics in the Department of Mathematics and Computer Science at Bloomsburg University in Bloomsburg, Pennsylvania. Dr Segal is associate professor in the Department of Psychology and Center for Cognitive Science at the University at Buffalo, New York. Dr Tucker is director of the Family Practice Residency Program at St. Joseph's Hospital Health Center in Syracuse, New York. Address correspondence to Richard S. Cohen, MD, 52 Utica St, Hamilton, New York 13346; e-mail to [email protected].