HEAT MORTALITY VERSUS COLD MORTALITY a Study of Conflicting Databases in the United States

HEAT MORTALITY VERSUS COLD MORTALITY A Study of Conflicting Databases in the United States

BY P. G. DIXON, D. M. BROMMER, B. C. HEDQUIST, A.J. KALKSTEIN, G. B. GOODRICH, J. C. WALTER, C. C. DICKERSON IV, S. J. PENNY, AND R. S. CERVENY

Studies of heat- and cold-related mortality in the United States produce widely ranging results due to inconsistent data sources, and this paper describes the methods, assets, and limitations of the most common temperature-related mortality sources.

hen set against the backdrop of the massive by weather sources of information (e.g., National death toll associated with the August 2003 heat Climatic Data Center) and by medical authorities Wwave in Europe, weather-related mortality and (e.g., Centers for Disease Control and Preventions the comparison of the various causes is important National Center for Health Statistics). Such com- in regard to preparation, policy determination, and parisons set the number of heat stroke victims, and the allocation of resources. However, discussion of other sources of life-ending heat-related conditions, cross-disciplinary statistics is difficult due to the lack against hypothermia and other sources of life-ending of knowledge and communication between different cold-related conditions. The adequate allocation of areas of interest. Even in a country such as the United medical resources, formulation of advance warning States, where substantial documentation of mortal- and prediction systems, and other policy decisions are ity exists, significant errors and marked differences fundamentally linked to questions of the following can occur. A classic case is the number of fatalities type: "Do more people die from heat than die from associated with "excessive cold" or "excessive heat," cold?" and even more basically, "How many people where statistics have been independently compiled die due to heat or cold?" Interestingly, depending on the database used and the compiling U.S. agency, completely different

AFFILIATIONS: DIXON, BROMMER, HEDQUIST, KALKSTEIN, results can be obtained. Several studies show that GOODRICH, WALTER, DICKERSON, PENNY, AND CERVENY—Office heat-related deaths outnumber cold-related deaths, of Climatology, Department of Geography, Arizona State while other studies conclude the exact opposite. University, Tempe, Arizona We are not suggesting that any particular study is CORRESPONDING AUTHOR: Randy Cerveny, Depart- consistently inferior to another, but, rather, that it is ment of Geography, Arizona State University, P.O. Box absolutely critical to identify the exact data source, as 870101, Tempe, AZ 85287-0104 E-mail: [email protected] well as the benefits and limitations of the database, DOI: 10.1175/BAMS-86-7-937 used in these studies.

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC Control and Prevention's (CDC's) National Center TABLE 1. Selected categories of various for Health Statistics (NCHS) maintains electronic databases containing weather-related records for identified causes of death. Each state is mortality. responsible for compiling their death certificates and entering the information into a series of computer Selected major Selected weather programs—such as the Automated Classification categories of the categories from of Medical Entities (ACME); Translation of Axis, ICD-9 NCDC's Storm Data (TRANSAX); Mortality Medical Indexing, Classi- Excessive heat Drought fication, and Retrieval system (MICAR); and Super MICAR. Such programs scan for common terms and Excessive cold Dust storm then code the data based on keywords. In some cases, however, such as those with multiple causes of death, High and low air human review may be necessary. Additionally, in a pressure and changes in air pressure Fog few cases, human evaluation under strict regulations might reorder the cause of death as stated on the Hunger, thirst, exposure, death certificate and override the examining doctor's and neglect Hail diagnosis of ultimate cause of death. To quote a practicing physician, "death certificates Lightning Hurricane/tropical storm are pretty straightforward." Much like any other Cataclysmic storms, official paperwork, the death certificate consists of and floods resulting a series of blanks that must be filled with specific in- from storms Lightning formation regarding the deceased. The forms tend to vary by state and are meant to record the fundamental Cataclysmic Earth cause of death, as well as unambiguously identify the surface movements and person in question. The space on the certificate that is eruptions Tornado provided to state the cause of death is not particularly Accidental drowning large. Rather, there is generally a single blank for the and submersion Wild/forest fire "immediate cause," as well as another small space used to list any underlying causes that may have led to Struck accidentally by the immediate cause. There may also be a small space falling object Ocean/lake surf for the explanation of other contributing factors (e.g., Exposure to radiation Precipitation substance abuse, disease, smoking, etc.) that were not related to the immediate cause. However, each Overexertion and of these spaces is separate, and mortality compila- strenuous movements Snow/ice tions based on the immediate cause usually exclude information about underlying or complicating fac- Other and unspecified tors. Unfortunately, for most users the acquisition environmental and accidental causes Temperature extremes of death certificate copies is cost prohibitive, and the use of a secondary dataset, a codified analysis of Late effects of accidental Thunderstorms and high death certificates such as the Compressed Mortality injury winds Index, is necessary. Consequently, the CDC NCHS maintains a database that is structured on the cause of death as the ICD-9 classification scheme include "excessive denoted by the deceased's death certificate. Deaths heat," "excessive cold," "lightning," and "high and are classified as to the underlying cause, using the low air pressure and changes in air pressure" (Table International Classification of Disease (ICD) [ninth 1) among others. Most of the excessive cold and ex- edition for 1979-98 (ICD-9) and tenth edition for cessive heat mortality studies presented in the CDC's 1999-present]. The World Health Organization publication Morbidity and Mortality Weekly Report (1992) defines the underlying cause of death as "the employ this database (Donoghue et al. 2003; Grey et disease or injury that initiated the train of events al. 2002; Mirchandani et al. 2003; Sathyavagiswaran leading directly to death, or the circumstances of the et al. 2001). accident or violence, which produced the fatal injury." Kalkstein (1991) proposed the use of standardized Weather-related mortality categories according to gross mortality values as a method to determine the

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC number of people dying from heat-related events. Using this method, total daily mortality within a metropolitan area is standardized first for population change, and then for time of year, because more deaths occur during the winter months (Fig. 1). A residual is then computed from the difference of the specific date/year of mortality and its standardized counterpart. It has been shown that heat waves exhibit an increased number of deaths over the standardized values (excess deaths), and this excess will be more FIG. I. Gross mortality (in percentage of annual deaths) reflective of the actual number of heat-related deaths for 12 cities across the United States for 1975-98. (Kalkstein 1991). It is important to note that the gross mortality method takes all causes of death into account, and evidence has shown that overall mortality In contrast to CDC reports, the operation manual rates of numerous causes, such as heart attack and for NCDC's Storm Data (Mandt 2002) includes de- stroke, increase during heat waves. Thus, there is no tailed instructions on how to categorize direct and need for stratification by cause of death. indirect causes for dozens of weather-related deaths. Regardless of the type of weather event, the manual Storm Data index. Storm Data, maintained by the clearly indicates that only deaths caused directly by National Climatic Data Center (NCDC), lists mortal- the given weather event can be entered into the Storm ity values that are compiled (based on reports from Data archive. Any death that is indirectly caused by trained spotters, law enforcement agents, emergency a weather event will be noted in the narrative that managers, and various media sources) by local Na- accompanies each entry, but will not be entered into tional Weather Service (NWS) offices. Storm Data the database. publications are easily accessible online through For excessive heat to be considered the direct cause the NCDC Web site for 1994-present. However, of a death in Storm Data, there must be a "fatality a search function allows users to query the Storm where heat-related or heat stress was the primary, sec- Events Database for certain weather phenomena ondary, or major contributing factor as determined back to 1950, with more detailed information from by a medical examiner or coroner" (Mandt 2002). Storm Data comprising all of the years since 1993. Hypothermia and cold-related deaths must meet Included in both the online Storm Data publications similar criteria. The weather event itself must also and the Storm Events Database is the number of achieve locally established values for heat or cold for direct weather-related casualties, injuries, and prop- the death to be considered direct. Deaths due solely erty damage, including the location and date of each to exposure to excessive temperatures are found in event. Also included for significant weather events are the "temperature extremes" category. Another cat- narratives that provide detailed information regard- egory in Storm Data that can include excessive cold ing casualties, weather records, and other anecdotal deaths is "snow and ice." If the death was the result information. The Storm Events Database is updated of excessive cold and there were other weather condi- monthly and generally lags 90-120 days behind the tions that led to the disorientation of the individual current month. The coupling of online data with the (such as blowing snow or icy roads), the death is not relatively quick updates makes Storm Data a very ac- counted under the temperature extremes category cessible data source. An example of a study based on and is, instead, listed under the category of snow and Storm Data information is Curran et al.'s (2000) study ice, which includes deaths by blizzards, heavy snow, on lightning deaths across the United States. and winter storms. For example, if the individual dies Because the source of each event is not given in of exposure to cold after a traffic accident, the death the database, users of Storm Data must be cautious. is counted as a direct cause under snow and ice, but The NWS cannot verify the accuracy and validity of not temperature extremes. all events. Once data from the various NWS offices Indirect deaths that are related to excessive cold are compiled, they are categorized by weather event and heat include those due to man-made heat or cold type (Table 1). While data regarding tornadoes, or, for example, when an individual dies of a heart at- thunderstorm winds, and hail are available from the tack while shoveling snow. Also included as indirect 1950s, all other weather events in Table 1 are only deaths are those related to excessive cold and heat available since 1993. that occur when the ambient weather conditions do

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC of the total (17) snow-and-ice-related deaths during TABLE 2. Total number of heat-related deaths January/February 1995. reported by the media (Chicago Sun-Times) for the Chicago 1995 heat wave event. Media reports. Media accounts of heat- or cold-related Total deaths deaths are primarily comprised of mortality numbers Date reported obtained from pertinent authorities and, given the nature of the media, are obtained quickly after, or 13 Jul 1995 20 even during, a given event. For example, the media- 15 Jul 1995 56 reported mortality numbers during the Chicago, Illinois, heat wave of 1995 were primarily made up 16 Jul 1995 116 of daily reports from the Cook County Chief Medi- cal Examiner. During that event, the media reported 17 Jul 1995 179 daily heat-related death statistics (Table 2). In addi- 18 Jul 1995 376 tion to medical examiners, the media also garnered death statistics from personal interviews with local 19 Jul 1995 402 funeral homes. A common problem with the use of weather-relat- 20 Jul 1995 456 ed death totals as reported in the media is that major 21 Jul 1995 457 events are often underreported and rarely revised after publication. Further, because the media use 22 Jul 1995 466 county medical examiners as primary information sources, it should be noted that a medical examiner 23 Jul 1995 468 generally is involved only with deaths of an unknown

25 Jul 1995 484 cause or of a suspicious nature. Consequently, many heat-related deaths are not sent for collaboration to 27 Jul 1995 529 the medical examiner. Also, as with other methods, media reports can be taken out of context and tend 3 Aug 1995 549 to lack reliable evidence of direct or indirect causes of

10 Aug 1995 562 death. See Changnon et al. (1996) for a comprehensive discussion of media reporting on the Chicago 1995 30 Aug 1995 568 heat wave.

COMPARISON OF DATABASES FOR HOT/ not surpass the locally established thresholds for an COLD DEATHS. Compressed Mortality Index. Us- excessive cold or heat event. Storm Data also consid- ing CDC NCHS's compressed mortality database ers deaths from snow- or ice-related traffic accidents during the 21-yr period of 1979-99 (the most recent where exposure to excessive cold is not a factor in years for which national data are available), a total of the death to be indirectly caused by weather, and, 8015 deaths in the United States were heat related (Fig. thus, they are not counted in the database. Therefore, 2). Of that total, 3829 (47.8%) were "due to weather defined criteria for death by heat or cold must be conditions," while 3809 (47.5%) were "of unspecified considered before data selection can begin. origin" and 377 (4.7%) were "of man-made origins" Unfortunately, even with a well-defined standard (e.g., heat generated in vehicles, kitchens, boiler for classifying direct and indirect causes of death, it rooms, furnace rooms, and factories) (Donoghue et is possible for problems to occur. There are several al. 2003; Sathyavagiswaran et al. 2001). Consequently, instances in Storm Data where traffic-related deaths the CDC NCHS dataset s category of "excessive heat were classified as directly caused by weather in con- resulting from weather conditions" creates an average trast to the official guidelines. A random sample of of 182 deaths per year. two months from early 1995 snow and ice deaths Conversely, again using the compressed mortality shows that three deaths in January in Kentucky, two database during the 21-yr period of 1979-99, a total in February in Pennsylvania, and six in February in of 13,970 deaths were attributed to hypothermia (ex- Texas were all from traffic accidents where exposure cluding anthropogenic cold deaths) (Grey et al. 2002; to excessive cold was not a factor in the death. These Mirchandani et al. 2003) (Fig. 2). In 1999, exposure 11 incorrectly labeled deaths make up more than half to excessive natural cold was listed as the underlying

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC by the CDC NCHS for the years 1975-98. The data are organized by age group, and daily mortality is broken down into those younger than 65 and those 65 and older. A simple linear regression was conducted for each of the metropolitan areas to adjust for any changes in population. One of the key points regarding total, or gross, mortality is the prevalence of higher deaths in the winter months (Fig. 3). Such deaths cannot be solely linked to atmospheric conditions (i.e., cold) and are a function of socioeconomic conditions, psychologi- FIG. 2. CDC NCHS Compressed Mortality Index. Total cal state, influenza, etc. (Kalkstein 1991). Therefore, deaths by excessive heat (gray bars) and total deaths before performing analyses of mortality associated by excessive cold (black bars) for 1968-99. with abnormal hot/cold conditions, gross mortality numbers must be detrended to account for population cause of death for 598 persons in the United States, change and a strong seasonal cycle. and hypothermia was listed as a "nature" of injury For this study, gross mortality numbers were (i.e., an injury that occurred to the deceased) in 1139 detrended using two methods. The first is based on deaths. Totaling these numbers, the database lists a computing the residual of the actual day's mortality total of 15,707 people who have died from extreme for a specific year from its long-term mean mortality. cold from 1979 to 1999. Therefore, this dataset's cat- For example, to calculate the residual for 1 January egory of "excessive cold resulting from weather condi- 1975, its mortality is subtracted from the average tions" lists an average of 748 persons killed per year. mortality value for every 1 January from 1975 to 1998. The second method utilizes a first-order harmonic Storm Data. Temperature extreme deaths listed in wave fitted to the annual mortality data and computes NCDC's Storm Data are skewed heavily toward heat- the residual of the actual day's mortality for a specific related deaths (Fig. 3). Even when snow and ice events year from the harmonic. are combined with cold temperature extremes, the Once detrended, excess heat- or cold-related deaths number of heat-related deaths far outweighs cold-re - can be analyzed more effectively, and specific heat lated deaths during the period 1993-2003 by a 3-to-l waves and cold events between 1975 and 1998 were margin. Of course, the data are heavily linked to two examined for each of the cities. Severe heat waves often specific heat-wave events in 1995 and 1999. If these produce large "spikes" in mortality, especially during events are removed from the list, the numbers of hot the 1995 heat wave across the Midwest. However, and cold extreme deaths are nearly equal. abnormally cold conditions have little effect on the standardized daily mortality. For example, February Gross mortality. Daily gross mortality data from 12 1996, a cold period across much of the United States, cities (Fig. 4) across the United States were provided produced no spikes in winter mortality levels.

FIG. 3. NCDC Storm Data. Total deaths by excessive heat (gray bars) and total deaths by excessive cold FIG. 4. Twelve cities for which gross mortality data (see (black bars) for the period of 1993-2003. Fig. I) were used in this study.

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC Overall. It is apparent from the numbers shown above Index, the total number of reported deaths due to that these databases have different degrees of "cor- "excessive heat" in Cook County, Illinois for all of rectness," and this is likely due to multiple method- 1995 was only 85. ological differences. For example, Storm Data, which When gross mortality values are examined in is often based on media reports, tends to be biased Cook County for the period associated with the 1995 to the media's (and consequently the public's) over- heat wave, a tremendous spike in daily mortality all awareness of the event. As such, weather-related is indeed apparent (Fig. 5). While the background catastrophic "group kills" rather than "individual "baseline" mortality for that time of year is around kills" are more likely to be included in Storm Data. 120 deaths per day, the daily total mortality greatly Therefore, this may tend to give more complete num- exceeds that baseline value for five days (14-18 July) bers for weather-related categories, such as tornadoes, by approximately 840 individuals. hurricanes, or heat waves, than for deaths from winter Certainly, if such a wide range of values exists cold, and the multiple categories for excessive cold for a single event in a single city, compiled mortal- deaths can also introduce an underreporting of cold ity databases are more likely to have even greater deaths. However, Storm Data is updated each month, and consequently, information on a given weather event is added into the database fairly quickly after its occurrence. The CDC NCHS's Compressed Mortality Database is, in general, a more comprehensive database. As such, it would more likely include weather-related "single kills" than would Storm Data. However, the Compressed Mortality Database is limited by the medical personnel's actual determination of the "weather relatedness" of death, and the database often runs years behind current events. The latest mortality values that are used in recent medical studies are from 1999 (Donoghue et al. 2003; Grey et al. FIG. 5. Gross mortality (number of deaths) for July 1995 2002; Mirchandani et al. 2003; Sathyavagiswaran et in Chicago, IL. (Adapted from Whitman et al. 1997.) al. 2001). The calculation of deviations from the daily norm disparity. Fundamentally, the vast differences in in gross mortality does not suffer from many of the these mortality numbers exist because of the various subjective death determinations associated with other sources on which the mortality databases rely. For datasets. However, it can be problematic to classify example, mortality numbers coming from a medical the causes of death using these data. In addition, examiner are limited to only the cases in which that gross mortality data are generally available only for medical examiner was involved. The markedly low metropolitan areas and are not easily obtainable on number of deaths reported by the CDC NCHS also a daily time scale for large regions. suggests that, on many death certificates, the cause of death was likely determined not to be directly CHICAGO 1995 HEAT WAVE. As an example heat related. of the disparity between datasets, we review the wide range of mortality numbers reported for the Chicago CONCLUSIONS. Depending on the compila- 1995 major heat-wave event. By 27 July 1995, the tion nature of the dataset, the numbers of heat- or media (Chicago Sun-Times) reported 529 heat-related cold-related mortality are quite divergent. Con- deaths in the Chicago metropolitan area (Table 2). sequently, in general, these separate mortality Storm Data lists 583 heat-related deaths in Illinois datasets should not be combined or compared in for the entire month of July 1995 (heat-related deaths policy determination, and the specific dataset used from Chicago are erroneously placed under the state in a given study should be clearly identified. All of of Idaho in the online NCDC database). However, a the datasets suffer from some major limitations, subsequent NOAA natural disaster survey report lists such as the potential incompleteness of source in- 465 heat-related deaths for Chicago for the period formation, long compilation time, limited quality 11-27 July (NOAA Disaster Survey Team 1995). Yet, control, and subjective determination of the direct according to the CDC NCHS Compressed Mortality versus indirect cause of death. These factors must

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Unauthenticated | Downloaded 09/28/21 07:33 AM UTC be considered if the data are used in policy deter- Donoghue, E. R., M. Nelson, G. Rudis, R. I. Sabogal, mination or resource allocation. J. T. Watson, G. Huhn, and G. Luber, 2003: Heat- Of the datasets identified in this study, the one related deaths—Chicago, Illinois, 1996-2001, and that appears to be least influenced by the above United States, 1979-1999. Morbid. Mortal Weekly limitations is gross mortality. However, the gross Rep., 52, 610-613. mortality data must be detrended in order to remove Grey, T. C., R. Rolfs, M. A. Chambers, and A. S. Niskar, a persistent winter-dominant death maximum. 2002: Hypothermia-related deaths—Utah, 2000, and Another major limitation of gross mortality is in United States, 1979-1998. Morbid. Mortal Weekly obtaining regional daily mortality as opposed to Rep., 51, 76-78. only daily mortality for metropolitan areas. There- Kalkstein, L. S., 1991: A new approach to evaluate the fore, any users of weather-related mortality data impact of climate on human mortality. Environ. must determine which source is most suitable for Health Perspectives, 96, 145-150. their needs, and they should fully understand the Mandt, G. A., 2002: Storm Data preparation. National Weath- limitations associated with the data. er Service, National Oceanic and Atmospheric Admin- istration, Department of Commerce, National Weather ACKNOWLEDGMENTS. We greatly appreciate the Service Instruction 10-1605, NWSFD 10-16,79 pp. information and comments provided by Dr. Edmund R. Mirchandani, H., C. Johnson, C. Newbern, and C. Can- Donoghue, Dr. R. C. Patel, Dr. David Berglund, D. Kenneth chez, 2003: Hypothermia-related deaths—Philadel- Kochanek, Pamela Monroe, and Charles J. Dastych. phia, 2001, and United States, 1999. Morbid. Mortal Weekly Rep., 52, 86-87. NOAA Disaster Survey Team, 1995: July 1995 Heat Wave. Natural Disaster Survey Report, 52 pp. REFERENCES Sathyavagiswaran, L., J. E. Fielding, and D. Dassy, 2001: Changnon, S. A., K. E. Kunkel, and B. C. Reinke, 1996: Heat-related deaths—Los Angeles County, Cali- Impacts and responses to the 1995 heat wave: A call fornia, 1999-2000, and United States, 1979-1998. to action. Bull Amer. Meteor. Soc., 77, 1497-1506. Morbid. Mortal Weekly Rep., 50, 623-626. Curran, E. G., R. L. Holle, and R. E. Lopez, 2000: Light- World Health Organization, 1992: International Sta- ning casualties and damages in the United States tistical Classification of Diseases and Related Health from 1959 to 1994. /. Climate, 13, 3448-3464. Problems. World Health Organization, 1243 pp.

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