Tables

• Table B.1: Annual Risk of Death in the United States
• Table B.2: Annual Risk of Death in the United States
• Table B.3: Risk Comparisons (Involuntary Risks Only)
• Table B.4: Estimated Loss of Life Expectancy Due to Various Causes
• Table B.5: Risks Estimated to Increase the Probability of Death in Any Year by One Chance in a Million
• Table B.6: Average Risk of Death to an Individual from Various Natural and Human-caused Accidents
• Table B.7: Average Risk of Death from Various Human-caused and Natural Accidents
• Table B.8: Ranking of Possible Cancer Risks from Common Substances

Figures

• Figure B.1: Health Risk Ladder   Annual Number of Deaths per Million People
• Figure B.2: Upper Bound Estimates of Deaths for Different Energy Systems
• Figure B.3: Comparisons of Different Sources of Radiation Exposure
• Figure B.4: The Causes of Cancer: Quantitative Estimates of the Avoidable Risk of Cancer in the U.S.
• Figure B.5: Radon Risk Charts

WARNING NOTES:

1. Since the data in these tables and figures have been calculated or assembled by others, their technical accuracy cannot be guaranteed. CMA makes no representations or warranties concerning their accuracy.

2. Some of the data are old and need to be updated. For some risks, this can make a significant difference, either because the risk itself has changed significantly or because its measurement has improved. In general, rates (e.g., number of deaths per million population) tend to change less over time than fatalities (counts).

3. It is not always clear what is included in the specific risk entries. For example, do deaths from smoking include cardiovascular disease and emphysema or just lung cancers? What is included in the categories “falling objects” or “toxic gas”? When in doubt, do not use the statistic.

4. Most tables of risk comparisons in the literature contain a hodgepodge of risks characterized by different levels of uncertainty. For risks such as driving, where fatalities can be counted, the number is likely to be reliable. But for risks such as radiation or food additives — based not on counting and actuarial statistics but on theoretical modeling and extrapolation — the number is likely to be highly uncertain. In general, data based on theoretical models and extrapolation are more likely to be a target for debate and criticism than data based on counts and actuarial statistics.

5. Most risk comparison tables offer only single number risk estimates, with no range or error term.

6. Most tables of risk comparisons in the literature have been developed to make a particular point. No matter how often the table has been reprinted, it is important to be sensitive to biases in the calculation of risks.

7. A careful risk comparison requires a good deal of background information about data sources, assumptions, and other qualifiers. Just because a risk statistic is published does not mean it is reliable. Published data often take on a life of their own. The original publication may discuss a number of qualifying uncertainties but these may be left out by the next person who reproduces the statistic. This may make the data look more certain, but in fact it makes them far less reliable. Keep in mind, however, that even if a risk estimate in a table is slightly off, it still could prove useful for comparisons in which risks differ by factors of 10, 100 or more.

8. The tables are often neither clear nor consistent about the population used to calculate the risk. Within the same table, some risk estimates are based on the entire population (e.g., the United States), while others are based only on the population that is exposed (e.g., only people who hunt or live in tornado-prone regions). Every risk looks more risky if only the most exposed population is considered, less risky if lots of unexposed people are considered.

9. Even if the risk comparison data are carefully and accurately reported, they can be misleading. For example, the risk calculation for driving includes many different driving situations. Yet speeding home from a party just before dawn is two orders of magnitude more dangerous than driving to the supermarket. Similarly, the risk of being hit by lightning for people who remain on a golf course during a thunderstorm is much higher than the risk for the U.S. population provided in these tables.

10. Risk comparisons raise all the same framing issues as risk quantification generally. That is, there are many different ways to express risk comparison data. Each of these expressions is likely to have a somewhat different impact on the audience.

11. The primary intent of these cautionary statements is to warn against casual acceptance of data in comparison tables, to emphasize the importance of acting fairly and responsibly in constructing comparisons, and to indicate the advisability of having someone carefully cross-check the comparison data. Whenever possible, avoid the use of secondary data sources. Track down the original source of the statistic and, if it seems accurate and appropriate, use that number.

12. Remember that a useful risk comparison must be accurate and appropriate. Comparing chemical plant risks to voluntary lifestyle choices such as smoking or driving without a seatbelt is seldom appropriate or successful, even if the comparison is technically accurate.

2002 Note: Several numbers were incorrect in the original CMA publication and have been corrected here.

Notes: (*) These items assume that all U.S. power is nuclear. UCS stands for the Union of Concerned Scientists, a leading critic of nuclear power. NRC stands for the U.S. Nuclear Regulatory Commission.

Note: These data are based on simple extrapolations from population averages. Some data are based on actuarial statistics (e.g., coal mine accidents) and others are based on theoretical models (e.g., cancers from chlorinated water).

Figure B.1: Health Risk Ladder
Annual Number of Deaths per Million People

Figure B.3: Comparisons of Different Sources
of Radiation Exposure

Figure B.4: The Causes of Cancer: Quantitative Estimates of the Avoidable Risk of Cancer in the U.S.

Source: Adapted from Doll, R. and Peto, R. (1981), “The Causes of Cancer: Quantitative Estimates of the Avoidable Risk of Cancer in the U.S. Today.” Journal of the National Cancer Institute, 1981, Vol. 66, 1191–1308.

Introduction and Index       I . Effectively Communicating Risk Information       II. Guidelines for Presenting and Explaining Risk-Related Numbers and Statistics       III. Guidelines for Providing and Explaining Risk Comparisons       IV. Concrete Examples of Risk Comparisons       V. Anticipating Objections to Explanations of Chemical Risks       Conclusion       Acknowledgements       Appendix A: Concentration and Quantity Comparisons       Appendix B: Risk Comparison Tables And Figures       Appendix C: Risk Perception Factors       Selected Bibiliography on Risk Communication

Peter M. Sandman 59 Ridgeview Rd. Princeton NJ 08540-7601	Phone: 1-609-683-4073 Fax: 1-609-683-0566 Email: peter@psandman.com
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