Valuing lives saved from safer food--a cautionary tale revisited.

Number of People) Twice every week (1 in 10 people) Once every month (1 in 100 people) Once every year (1 in 1,000 people) Once every 10 years (1 in 10,000 people) Once every 100 years (1 in 100,000 people) Once every 1,000 years (1 in 1,000,000 people) Once every 10,000 years (1 in 10,000,000 people) Once every 100,000 years (1 in 100,000,000 people)

Q22. Please mark the point that you think best represents how frequently YOU can be expected to suffer a food-borne illness in any given year. How Often Frequency (In Terms of

Number of People) Twice every week (1 in 10 people) Once every month (1 in 100 people) Once every year (1 in 1,000 people) Once every 10 years (1 in 10,000 people) Once every 100 years (1 in 100,000 people) Once every 1,000 years (1 in 1,000,000 people) Once every 10,000 years (1 in 10,000,000 people) Once every 100,000 years (1 in 100,000,000 people)

Implementation of Survey

Knowledge Networks (KN) implemented the survey, which was funded by the U.S. Department of Agriculture through the Economic Research Service. The study design consisted of three waves of data collection with two interventions between the three waves. Each wave of data collection lasted for fourteen days. In these fourteen days, respondents were instructed to collect their household's grocery shopping receipts. In Wave I, 1,274 surveys were fielded with 923 completed--a 72% response rate. After the first wave of data collection, respondents were sent the first intervention survey. Respondents were instructed to visit a website about the ten least-wanted bacteria present in foods (see http://www.fightbac.org/10least.cfm). In Wave II, 905 surveys were fielded, with 800 completed--a 88% response rate. The second wave took place next. After the second wave, respondents were sent the second intervention survey. They were instructed to visit a different website about food safety (see http://www.thebody.com/fda/fsebac.html). Finally, in Wave III, 774 surveys were fielded, with 703 completed--a 91% response rate.

The sample of the study was restricted to the overlapping panelists between KN's web-enabled panel and the National Shopper Lab (NSL) panel. This sample design was intended to allow analysis of UPC data collected at grocery stores where respondents used their NSL card to shop. (2) The survey instrument averaged approximately 19 minutes. Each respondent was awarded 5,000 bonus points (an equivalent of $5) for their participation in each survey and for the collection of their household's grocery store receipts.

Wave I Results

We created six indexes that summarize a subject's responses to related sets of questions and three measures of risk perception. First, we created a health index, HI. Several questions pertain to the respondents' health and susceptibility to illness. We converted the answers to numeric values. For instance, if the answer to question 1 was "yes," we defined q1 - 1, whereas q1 = -1 if the answer was "no." If the question was not answered, we defined q1 = 0. The corresponding was done with questions 2-5, 12, and 18. Based on these numerical responses, the health index, HI, was:

HI = q1 + q2 + q3 + q4 + q5 + q12 + q18. (1)

The questions were formulated so "yes" implied poor health or higher susceptibility to illness. Higher values of the health index indicate greater sensitivity to health risk.

Second, the survey respondents reported their height and weight in questions 13 and 14, which we combine into the body mass index, BMI:

BMI = weight/height (2) (2)

where the weight is measured in kilograms and the height in meters.

Third, we created a measure of the respondent's effort in self-protection through various activities that reduce risk. We had two questions that already required quantitative responses, namely the two sub-questions in question 6 that asked how many times, out of ten times, the respondent wore a seat belt and adhered to the speed limit when driving or riding in a car. The risk index, RI, was calculated as

RI = q6_wear/10 - q6_drive/10 + q7 + q8 + q9 + q10 + q11 + q20 + Q24 (3)

where Q24 = 1 if the response to question 24 was greater than 0 and Q24 = 0 otherwise. The first two terms in the expressions on the right-hand side of (3) indicate that we use the fraction of times the respondent wore a seatbelt and adhered to the speed limit, as components of the index.

Fourth, we created a food preparation index from the responses to question 33. This question inquired about numerous activities carried out before, during, and after food preparation that may have influenced the heath risks posed by the prepared food. The food preparation index (FPI) was calculated as the sum of the reported number of times, out of ten meal preparations, the specific activity was carried out:

FPI = q33a + q33b + ... + q33t. (4)

Fifth, the survey asks how effective various activities were perceived to be in reducing food-borne health risks posed by three categories of food: beef, pork, and chicken. We created from the responses the following self-protection effectiveness index (SPEI):

SPEI = q43_beef + q43_pork + q43_chicken + ... + q46_beef + q46_pork + q46_chicken. (5)

Questions 43-46 are formulated so that the lowest response, 1, indicated that the activity is very effective. Larger values of SPEI thus corresponded to less effectiveness of self-protection.

Sixth, questions 48 through 51 asked about the change in health risk that would result if the respondent changes the activity level for specific activities. From these responses, we created an index that measures the perceived incremental risk reduction (IRR) from doubling, or cutting in half (two treatments), the number of times the risk reduction activity is carried out. The variable amount equals 1 if the "cut in half" treatment was given, and amount = 2 if the "double" treatment was given. The responses to the questions range from 1 = "large decrease," through 6 = "no change," to 11 = "large increase" in risk due to the halving/doubling of the activity We combined the responses to the questions into the index IRR as follows:

IRRI = ((q48_beef-6) + (q48_pork-6) + ... + (q51_chicken-6)) x (2 x amount - 1). (6)

The index is thus calculated so that it takes on negative values if doubling (halving) the activity level is associated with decreased (increased) risk, and positive values if doubling (halving) the activity level is associated with increased (decreased) risk.

Finally questions 21 and 22 provide three risk perception variables: (3)

(7) Personalrisk = q21

(8) Baserisk = q22

(9) Relativerisk = Personalrisk/Baserisk

Table 1 provides descriptive statistics about the respondents and their responses to the questions as summarized by the indexes defined above. Table 2 reports the significant correlations between the variables.

Several key points arise in the correlation matrix. First, a strong relationship exists between the health index and the body mass index. This is to be expected since both indexes are based on questions about facts, and there likely is a factual relationship between health and body mass. Second, a significant correlation exists between some pairings of the indexes. The risk index (RI) is correlated with the food preparation index (FPI). Respondents with high levels of self-protection in food preparation also report more caution in other activities, such as driving. They also report that self-protection is more effective (SPEI). Also, respondents who believe self-protection is more effective (low SPEI) believe in a greater reduction of risk associated with an increase in self-protection (low IRRI). Given the strong similarity of the underlying perceptions asked about in the set of Q43-46 (SPEI) and Q48-51 (IRRI), we find it troublesome that the correlation between the two indexes is no more than 0.115. The adjusted-[R.sup.2] is only 1.2% in a regression between SPEI and IRRI.

Third, and perhaps most notably, no evidence of correlation exists between either of the two health status indexes, HI and BMI, and any of the other indexes. HI and BMI are based on questions with strong factual basis, such as a person's weight, height, smoking, and pregnancy. The risk index, RI, and to a lesser degree the food preparation index, FPI, are based in part on factual information. Some of the component questions have a weaker factual basis, such as the questions about how often, out of ten times, a person engages in a certain behavior. The "facts" underlying such questions may be poorly remembered and may suffer from reporting errors and perhaps reporting biases. Finally, the factual underpinnings for SPEI and IRRI are probably most complex of all, and are most susceptible to reporting errors and biases.