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Keywords:

  • health knowledge;
  • attitudes;
  • practice;
  • health education;
  • patient education;
  • neoplasms;
  • attitude to health

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

BACKGROUND.

Inaccurate beliefs about cancer risk may contribute to unhealthy lifestyle behaviors and poor adherence to recommended screening and prevention guidelines. To address this issue the current study assessed the prevalence and sociodemographic correlates of scientifically unsubstantiated beliefs about cancer risk in a representative sample of the US population.

METHODS.

Nine hundred fifty-seven US adults with no history of cancer were surveyed by telephone. The survey included 12 statements about cancer risk, risk factors, and prevention that were framed to be contrary to the consensus of current scientific evidence.

RESULTS.

Participants were inconsistent in their ability to identify the statements as false, and appraisal accuracy was associated with several sociodemographic characteristics. Five of the 12 misconceptions were endorsed as true by at least a quarter of the respondents, and uncertainty was higher than 15% for 7 statements. At the same time, more than two-thirds of the participants were able to identify 7 statements as false and, on average, respondents endorsed fewer than 3 statements as true. Respondents who were male, older, non-White, less educated, and of lower income were most likely to hold inaccurate beliefs.

CONCLUSIONS.

A notable percentage of the participants in this study hold beliefs about cancer risk at odds with the prevailing scientific evidence. Because the population segments with the least accurate knowledge also bear the greatest burden of cancer, areas for public education and intervention efforts are identified. Cancer 2007. © 2007 American Cancer Society.

Numerous social theoretical frameworks have been advanced to explain and predict health-related behaviors.1–4 Although such health-behavior theories may differ with respect to their fundamental constructs, most include consideration of beliefs regarding one's susceptibility to disease, knowledge of potential risk factors, and understanding of the associations between health-related behaviors and health outcomes. Such theories hold that engaging in a healthy lifestyle is partially predicated on an accurate assessment of risk factors and understanding the relation between such risks and one's behaviors. Applied to cancer, limited awareness of proven cancer risk factors represents an obstacle to positive health outcomes.5–7 Without awareness of such risk factors, individuals may engage in unhealthy lifestyles and may not adhere to recommended cancer screening guidelines. Others may hold inaccurate beliefs about factors that have little or no scientific evidence supporting their relevance to cancer risk. Previous research suggests that undue concern regarding such factors may distract some individuals' attention from documented risk factors and result in lifestyle behavior decisions detrimental to their health.8, 9 Thus, educating individuals about factors that increase cancer risk has been a goal of cancer prevention programs in the US.10 To address these issues, we undertook a study to assess the accuracy of the public's beliefs regarding cancer risk, risk factors, and prevention, and to identify the sociodemographic factors associated with these beliefs.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

In late 2002 the American Cancer Society (ACS), Prevention magazine (published by Rodale Press), Discovery Health Channel, and Princeton Survey Research Associates collaboratively designed and conducted a survey of cancer-related beliefs that was intended to further research in the area as well as identify topics for public education projects and programming. A previous publication reported results concerning beliefs about cancer treatment and the survey methods are described in detail in that article.9

The survey instrument included standard demographic questions as well as statements about cancer risk, screening, diagnosis, and treatment. The intention was to construct survey items that represented common misconceptions about cancer. Thus, each statement was framed to be contrary to the available scientific evidence. Survey items were developed with input from healthcare professionals and educators, including staff associated with the ACS National Cancer Information Center, based on their experience with the public's attitudes and beliefs about cancer.

The current analyses focus on the 12 survey items (Table 1) concerning overall cancer risk, specific risk factors for cancer, and cancer prevention. Respondents could agree, disagree, or express uncertainty about the truth of each statement by choosing 1 of 3 response options: “true,” “false,” or “don't know.” Although a comprehensive review of the relevant epidemiological literature is beyond the scope of this article, Table 1 includes citations to key references relevant to each statement.

Table 1. Distribution of Responses to Statements About Cancer Risk: Cancer Myths and Cancer Facts Survey 2002
Statements% General publicNo. of cancer epidemiologists
TrueNot trueDon't knowTrueTrue only in rare circumstancesDifficult to evaluate; likely trueDifficult to evaluate; likely falseFalseNot familiar with this topic
1. The risk of dying from cancer in the United States is increasing.11–1367.722.59.80000100
2. Living in a polluted city is a greater risk for lung cancer than smoking a pack of cigarettes a day.17, 1838.742.518.80000100
3. Some injuries can cause cancer later in life.32, 3337.241.920.9010054
4. Electronic devices, like cell phones can cause cancer in the people who use them.3429.745.724.7000811
5. What someone does as a young adult has little effect on their chance of getting cancer later in life.3524.868.27.1000190
6. Long-time smokers cannot reduce their cancer risk by quitting smoking.1716.278.15.70000100
7. People who smoke low-tar cigarettes have less chance of developing lung cancer than people who smoke regular cigarettes.1814.774.510.8000181
8. Personal hygiene products, like shampoo, deodorant, and antiperspirants, can cause cancer.3613.771.015.3000541
9. Getting a mammogram, or using a special X-ray machine to detect breast cancer, can cause cancer of the breast.26, 3710.273.816.1020152
10. Getting a base tan or base coat at a tanning salon will provide protection from skin cancer when you go outside in the sun.388.478.413.2000073
11. Underwire bras can cause breast cancer.396.262.930.9000190
12. You cannot get skin cancer from using a tanning booth.386.275.518.3000361

Recognizing that some survey items in this study had not been the subject of conclusive scientific study, the authors conducted a survey of 10 cancer epidemiologists at the American Cancer Society to assess their views regarding the evidence for each statement. To characterize their views more precisely, the response options for the epidemiologists differed from those offered to the study participants. The epidemiologists' response categories were “true,” “true only in rare circumstances,” “difficult to evaluate because of absent or limited data but likely to be true,” “difficult to evaluate because of absent or limited data but likely to be false,” “false,” and “I'm not familiar enough with this topic to answer this question.” After each epidemiologist returned the survey follow-up interviews explored their responses.

The sample of US adults was drawn using standard list-assisted random digit dialing method. Of the 3338 working telephone numbers (excluding fax, business, and nonworking phones) called, 2497 were successfully reached (contact rate = 75%), and 1254 individuals agreed to participate (cooperation rate = 50%). Of the 1254 respondents, 1070 were eligible (adults without language barriers), and 1002 completed the telephone survey (completion rate = 94%). The overall response rate of 35% was calculated as the product of the contact rate (75%), the cooperation rate (50%), and the survey completion rate (94%). Of the 1002 respondents, 45 reported a previous cancer diagnosis. Because this study focused on cancer risk beliefs among the general population, individuals with a personal history of cancer were removed from the analyses, leaving a sample of 957 US residents with no history of cancer. The sample was then weighted to match national parameters (obtained from the March 2001 Current Population Survey) for sex, age, education, race, Hispanic origin, and census region. Because of the complex sampling design, we used a design effect (=1.10) to adjust the standard error for tests of statistical significance.

To create an indicator of overall health literacy regarding cancer risk, we calculated a combined endorsement score by summing responses for all 12 statements. Each false response was assigned a zero value, and each true response was assigned a value of 1; don't know and refused responses were considered missing and not included in the calculation of this score. Thus, each participant's score is an integer that could vary from 0 (responded false to all 12 statements) to 12 (responded true to all 12 statements), with higher scores corresponding to lower cancer risk health literacy. Mean values were calculated for participants in various sociodemographic categories (gender, race, education, etc), and multivariate linear regressions examined associations between the combined endorsement score and sociodemographic characteristics. Multivariate logistic regressions examined associations between responses to each of the 12 statements and sociodemographic variables. Confidence intervals were adjusted by the design effect. As with the computation of the combined endorsement score, don't know and refused responses were considered missing and not included in these analyses.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Sample Characteristics

As presented in Table 2, 54.1% of the weighted sample consisted of individuals between 35 and 64 years old, 72.6% were non-Hispanic White, 51.4% were female, 86.3% had at least a high school education, and 56.2% reported a positive family history of cancer. The vast majority of participants said they were very or somewhat informed about cancer.

Table 2. Association Between Sociodemographic Characteristics and Combined Endorsement Score
CharacteristicCount%*Mean endorsement scoreMultivariate model design effect: 1.10
BetaAdjusted std errt testP
  • *

    Percentages may not sum to 100 because of nondisplayed unknown/refused category.

  • Unknown/refused responses to each statement were excluded in the analyses.

  • P values adjusted for design effect.

Total957 2.74    
Sex
 Women48351.52.50Referent  Referent
 Men47448.53.000.63130.11425.53<.001
Race
 White72772.62.53Referent  Referent
 Black9310.93.120.46030.19102.41<.05
 Hispanic8510.73.530.92330.19184.81<.001
 Other394.53.570.93430.27793.36<.01
Age
 <3529530.92.81Referent  Referent
 35–6452054.12.65−0.03800.1303−0.29 
 65+13314.22.970.07440.19220.39 
Education
 <High school8013.43.730.63210.18233.47<.001
 High school graduate35937.02.96Referent  Referent
 Some college20424.22.46−0.44680.1494−2.99<.01
 College graduate31125.22.16−0.66240.1540−4.30<.001
Income
 <$30,00025929.73.190.38400.17142.24<.05
 $30–50,00017318.32.56Referent  Referent
 $50–100,00026526.62.42−0.00530.1716−0.03 
 $100,000+1029.42.31−0.03220.2313−0.13 
Family history of cancer
 Yes54556.22.59Referent  Referent
 No40342.82.930.18000.11701.53 
Cancer knowledge
 Very informed33433.82.89Referent  Referent
 Somewhat informed50953.12.63−0.30450.1240−2.45<.05
 Not very informed9110.52.79−0.47540.2014−2.36<.05
 Not at all informed151.63.36−0.01470.4791−0.03 
Census region
 South32935.82.94Referent  Referent
 Northeast17319.72.69−0.04980.1619−0.31 
 Midwest25623.22.53−0.19630.1532−1.28 
 West19921.32.69−0.12390.1577−0.79 

Endorsement of Cancer Risk Statements

The average combined endorsement score for the sample overall and by each sociodemographic variable is presented in Table 2. Multivariate linear regression analyses indicated that the combined endorsement score (mean of 2.74 for all participants combined) differed by several sociodemographic characteristics. Characteristics associated with lower health literacy (higher combined endorsement scores) included male gender, non-White race, Hispanic ethnicity, income less than $30,000, and less than a high school education. Paradoxically, compared with respondents who considered themselves “very informed” about cancer, respondents rating themselves as “somewhat informed” or “not very informed” had lower combined endorsement scores (Table 2).

The associations between sociodemographic characteristics and each cancer risk statement are displayed in Tables 3 through 5. In general, the pattern was consistent across statements and in line with associations noted between sociodemographic variables and the combined endorsement score, although some variability across statements was observed. For example, although lower income was generally associated with greater likelihood of endorsing statements as true, an exception was found for the belief that underwire bras cause cancer. Similarly, those with a college education were more likely than high school graduates to believe that low tar cigarettes are safer, although lower education was generally associated with higher endorsement of other statements.

Table 3. Association Between Sociodemographic Characteristics and Beliefs About Cancer Risk
 Statement 1*,Statement 2*,Statement 3*,Statement 4*,
Risk of dying increasingCity pollution worse than smokingInjuries cause cancerElectronic devices cause cancer
%OR (CI)§%OR (CI)§%OR (CI)§%OR (CI)§
  • OR indicates odds ratio; CI, confidence interval.

  • *

    Statements are fully defined in Table 1.

  • Unknown and/or refused responses to each statement were excluded in the analyses.

  • Percentage of participants who endorsed the statement as true.

  • §

    Odds ratio for multivariate analysis adjusted for sociodemographic characteristics; 95% confidence intervals are adjusted for design effect.

Sex
 Women75.61.00 (referent)47.41.00 (referent)41.31.00 (referent)35.71.00 (referent)
 Men74.31.03 (0.80–1.32)47.91.16 (0.92–1.46)52.81.85 (1.46–2.34)42.81.37 (1.07–1.75)
Race
 White73.01.00 (referent)46.11.00 (referent)44.11.00 (referent)36.31.00 (referent)
 African American79.31.01 (0.66–1.56)47.70.96 (0.66–1.40)54.21.74 (1.19–2.54)43.81.23 (0.82–1.85)
 Hispanic84.01.52 (0.94–2.44)51.41.21 (0.82–1.78)63.62.62 (1.75–3.93)53.21.73 (1.17–2.57)
 Other76.41.06 (0.57–1.96)60.51.74 (0.97–3.12)36.70.85 (0.47–1.56)43.61.30 (0.71–2.36)
Age
 <3579.71.00 (referent)41.01.00 (referent)42.61.00 (referent)45.01.00 (referent)
 35–6472.60.74 (0.55–1.00)49.31.42 (1.09–1.85)47.21.44 (1.10–1.89)39.70.87 (0.66–1.13)
 65+73.00.50 (0.32–0.77)56.11.52 (1.03–2.23)56.82.15 (1.44–3.21)21.90.36 (0.23–0.58)
Education
 <High school85.01.34 (0.84–2.13)67.11.99 (1.37–2.90)58.01.29 (0.89–1.86)48.41.47 (0.98–2.22)
 High school graduate81.11.00 (referent)50.61.00 (referent)47.01.00 (referent)41.31.00 (referent)
 Some college70.20.51 (0.37–0.71)41.60.73 (0.54–0.99)47.81.08 (0.79–1.46)38.40.84 (0.61–1.15)
 College graduate64.30.51 (0.37–0.72)38.30.66 (0.48–0.90)39.50.78 (0.57–1.08)32.90.66 (0.47–0.91)
Income
 <$30,00082.81.12 (0.80–1.58)56.41.31 (0.93–1.85)52.51.45 (1.02–2.06)39.81.02 (0.71–1.47)
 $30–49,99976.61.00 (referent)45.51.00 (referent)40.91.00 (referent)38.61.00 (referent)
 $50–99,99969.30.74 (0.51–1.07)46.11.03(0.72–1.46)43.51.37 (0.96–1.96)43.41.32 (0.92–1.90)
 ≥$100,00057.90.48 (0.30–0.77)33.10.61 (0.37–0.98)44.01.41 (0.88–2.26)29.60.78 (0.47–1.28)
Family history
 Yes74.91.00 (referent)44.61.00 (referent)48.31.00 (referent)38.81.00 (referent)
 No74.90.99 (0.76–1.28)51.31.37 (1.08–1.73)45.00.75 (0.59–0.96)40.51.04 (0.81–1.34)
Cancer knowledge
 Very informed74.31.00 (referent)53.81.00 (referent)47.81.00 (referent)35.21.00 (referent)
 Somewhat informed75.91.11 (0.85–1.47)46.10.73 (0.57–0.94)44.40.90 (0.70–1.16)41.61.31 (1.00–1.72)
 Not very informed73.60.70 (0.44–1.10)37.60.45 (0.30–0.68)53.41.20 (0.81–1.79)44.01.14 (0.75–1.74)
 Not at all informed77.71.02 (0.34–3.05)29.60.30 (0.11–0.85)57.41.27 (0.49–3.30)32.20.84 (0.75–1.74)
Census region
 South81.31.00 (referent)50.81.00 (referent)50.91.00 (referent)42.01.00 (referent)
 Northeast69.60.59 (0.41–0.85)49.81.06 (0.76–1.47)44.50.84 (0.60–1.16)42.91.10 (0.78–1.54)
 Midwest70.10.56 (0.40–0.79)44.10.86 (0.63–1.17)42.80.79 (0.57–1.08)34.60.77 (0.56–1.07)
 West74.20.76 (0.53–1.09)44.30.90 (0.65–1.24)47.10.88 (0.63–1.21)37.60.82 (0.58–1.15)
Table 4. Association Between Sociodemographic Characteristics and Beliefs About Cancer Risk
 Statement 5*,Statement 6*,Statement 7*,Statement 8*,
Young adult behaviorsSmokers can't reduce their riskLow tar cigarettes are saferHygiene products cause cancer
%OR (CI)§%OR (CI)§%OR (CI)§%OR (CI)§
  • OR indicates odds ratio; CI, confidence interval.

  • *

    Statements are fully defined in Table 1.

  • Unknown/refused response to each statement were excluded in the analyses.

  • Percent of participants who endorsed the statement as true.

  • §

    Odds ratio for multivariate analysis adjusted for sociodemographic characteristics; 95% confidence intervals are adjusted for design effect.

Sex
 Women24.81.00 (referent)17.11.00 (referent)13.61.00 (referent)11.41.00 (referent)
 Men28.61.47 (1.14–1.90)17.31.13 (0.85–1.50)19.51.65 (1.23–2.23)21.32.02 (1.48–2.77)
Race
 White23.41.00 (referent)14.91.00 (referent)15.11.00 (referent)15.11.00 (referent)
 African American32.01.57 (1.05–2.34)20.71.45 (0.92–2.28)17.01.29 (0.78–2.13)11.00.80 (0.45–1.44)
 Hispanic37.42.46 (1.65–3.68)23.71.81 (1.17–2.79)23.11.91 (1.23–2.98)19.41.30 (0.81–2.10)
 Other51.95.33 (2.91–9.79)35.63.94 (2.18–7.10)20.91.47 (0.74–2.91)34.22.07 (1.08–3.96)
Age, y
 <3521.21.00 (referent)17.11.00 (referent)12.51.00 (referent)18.41.00 (referent)
 35–6426.81.69 (1.26–2.28)15.50.97 (0.70–1.34)17.11.56 (1.09–2.22)14.60.65 (0.46–0.92)
 65+40.12.87 (1.89–4.33)25.01.54 (0.98–2.42)24.92.47 (1.52–4.02)15.50.59 (0.35–0.99)
Education
 <High school49.02.04 (1.43–2.93)25.61.20 (0.79–1.81)25.31.64 (1.06–2.54)24.32.04 (1.29–3.24)
 High school graduate28.61.00 (referent)20.61.00 (referent)14.11.00 (referent)15.41.00 (referent)
 Some college23.10.77 (0.56–1.07)15.60.82 (0.57–1.18)12.20.95 (0.62–1.44)12.60.72 (0.47–1.10)
 College graduate15.90.49 (0.34–0.70)9.80.56 (0.37–0.85)19.81.75 (1.17–2.61)16.50.91 (0.60–1.38)
Income
 <$30,00033.61.14 (0.79–1.63)22.91.23 (0.82–1.85)18.31.34 (0.85–2.12)13.60.92 (0.56–1.49)
 $30–49,99924.81.00 (referent)17.01.00 (referent)14.31.00 (referent)13.71.00 (referent)
 $50–99,99922.71.03 (0.71–1.50)12.70.79 (0.50–1.23)14.40.98 (0.61–1.56)15.31.17 (0.73–1.89)
 ≥$100,00019.00.86 (0.51–1.47)6.80.43 (0.21–0.91)16.81.03 (0.56–1.86)19.81.46 (0.79–2.69)
Family history
 Yes24.91.00 (referent)13.71.00 (referent)13.11.00 (referent)14.31.00 (referent)
 No29.11.05 (0.81–1.35)21.31.47 (1.10–1.97)20.51.59 (1.17–2.15)18.81.36 (0.99–1.87)
Cancer knowledge
 Very informed28.21.00 (referent)18.61.00 (referent)18.21.00 (referent)19.61.00 (referent)
 Somewhat informed25.70.87 (0.66–1.13)15.80.76 (0.56–1.03)14.40.72 (0.52–0.99)14.50.68 (0.49–0.94)
 Not very informed23.60.64 (0.41–1.02)15.40.67 (0.39–1.13)21.51.14 (0.71–1.85)12.70.46 (0.26–0.81)
 Not at all informed43.41.45 (0.55–3.80)20.30.87 (0.28–2.74)14.60.74 (0.19–2.79)25.81.00 (0.32–3.11)
Census region
 South31.11.00 (referent)16.61.00 (referent)17.21.00 (referent)15.21.00 (referent)
 Northeast26.20.93 (0.66–1.32)16.51.18 (0.78–1.79)18.71.13 (0.75–1.69)14.60.89 (0.57–1.39)
 Midwest23.40.83 (0.59–1.16)19.71.48 (1.02–2.15)19.70.89 (0.59–1.34)14.21.11 (0.74–1.68)
 West23.00.71 (0.50–1.01)16.01.00 (0.67–1.50)15.80.90 (0.60–1.36)18.11.26 (0.83–1.93)
Table 5. Association Between Sociodemographic Characteristics and Statements About Cancer Risk
 Statement 9*,Statement 10*,Statement 11*,Statement 12*,
Mammograms cause cancerBase tans are protectiveUnderwire bras cause cancerNo cancer from tanning booths
%OR (CI)§%OR (CI)§%OR (CI)§%OR (CI)§
  • OR indicates odds ratio; CI, confidence interval.

  • *

    Statements are fully defined in Table 1.

  • Unknown/refused response to each statement were excluded in the analyses.

  • Percent of participants who endorsed the statement as true.

  • §

    Odds ratio for multivariate analysis adjusted for sociodemographic characteristics; 95% confidence intervals are adjusted for design effect.

  • Not estimable because of the low number of endorsements.

Sex
 Women7.41.00 (referent)7.61.00 (referent)5.91.00 (referent)7.41.00 (referent)
 Men17.43.32 (2.27–4.86)11.92.08 (1.40–3.08)12.92.14 (1.32–3.46)7.81.18 (0.76–1.83)
Race
 White9.81.00 (referent)7.41.00 (referent)7.41.00 (referent)6.11.00 (referent)
 African American21.22.16 (1.29–3.62)16.72.26 (1.26–4.06)9.61.39 (0.66–2.91)9.11.82 (0.85–3.91)
 Hispanic16.71.37 (0.79–2.38)15.42.47 (1.40–4.35)5.70.96 (0.38–2.43)17.43.23 (1.77–5.92)
 Other15.81.12 (0.49–2.60)20.32.95 (1.39–6.25)38.510.51 (4.69–23.6)9.31.62 (0.56–4.66)
Age
 <3515.11.00 (referent)10.41.00 (referent)12.51.00 (referent)7.91.00 (referent)
 35–6410.30.69 (0.46–1.02)7.30.80 (0.51–1.26)5.80.34 (0.20–0.59)6.80.96 (0.59–1.56)
 65+11.80.61 (0.34–1.10)17.91.78 (1.00–3.18)12.90.89 (0.43–1.86)10.71.27 (0.63–2.56)
Education
 <High school18.21.11 (0.67–1.86)15.30.86 (0.50–1.48)15.50.93 (0.48–1.77)17.82.54 (1.43–4.52)
 High school graduate15.61.00 (referent)11.91.00 (referent)12.01.00 (referent)7.61.00 (referent)
 Some college9.70.62 (0.38–1.00)5.60.48 (0.27–0.84)4.30.23 (0.11–0.49)8.31.17 (0.68–2.03)
 College graduate6.80.49 (0.29–0.84)7.30.91 (0.52–1.57)5.60.24 (0.11–0.49)2.50.36 (0.16–0.80)
Income
 <$30,00018.32.93 (1.67–5.14)13.93.06 (1.58–5.92)8.30.93 (0.46–1.88)11.62.12 (1.08–4.18)
 $30–49,9997.51.00 (referent)4.71.00 (referent)7.51.00 (referent)5.31.00 (referent)
 $50–99,9995.51.07 (0.54–2.12)4.51.11 (0.51–2.41)4.71.04 (0.46–2.32)3.40.82 (0.36–1.85)
 ≥$100,00013.72.63 (1.26–5.49)5.81.40 (0.53–3.67)16.46.29 (2.58–15.3)5.61.84 (0.68–4.95)
Family history of cancer
 Yes9.81.00 (referent)7.31.00 (referent)7.91.00 (referent)6.71.00 (referent)
 No14.81.42 (0.98–2.04)12.91.44 (0.97–2.14)10.50.88 (0.54–1.45)9.01.25 (0.80–1.94)
Cancer knowledge
 Very informed11.51.00 (referent)11.41.00 (referent)10.61.00 (referent)6.01.00 (referent)
 Somewhat informed10.90.96 (0.65–1.43)8.00.68 (0.45–1.04)6.70.59 (0.35–0.98)8.91.54 (0.94–2.55)
 Not very informed16.21.07 (0.59–1.95)11.70.75 (0.39–1.43)9.70.56 (0.24–1.30)7.40.81 (0.36–1.81)
 Not at all informed35.92.38 (0.86–6.62)20.61.31 (0.40–4.34)31.51.81 (0.52–6.25)NANA
Census region
 South14.71.00 (referent)12.41.00 (referent)9.61.00 (referent)7.41.00 (referent)
 Northeast8.30.62 (0.35–1.10)8.50.79 (0.59–2.07)10.01.13 (0.59–2.07)7.61.53 (0.82–2.85)
 Midwest17.00.59 (0.33–0.92)8.30.62 (0.36–1.08)7.70.85 (0.40–1.45)7.51.44 (0.80–2.61)
 West15.51.23 (0.80–1.95)8.50.63 (0.37–1.09)8.20.62 (0.26–1.08)8.11.35 (0.72–2.50)

Appraisal of each cancer risk statement for study participants is presented in Table 1. Five of the 12 statements were endorsed as true by more than 20% of the participants, with the most frequently endorsed misconception being “The risk of dying from cancer in the United States is increasing,” which was believed by almost 68% of the sample. Four statements were endorsed as true by 10% to 20% of the sample, and 3 statements were endorsed as true by less than 10% of the participants. With respect to refuting the statements, over two-thirds of the sample correctly identified 7 statements as false, and each of the remaining 5 statements was judged to be incorrect by at least 20% of the participants. Uncertainty was relatively high for several of the statements, with more than 15% of the sample responding don't know for seven statements, and 20% choosing this same option for 3 statements. Uncertainty was lower than 10% for 3 statements.

In addition to showing the appraisal of each statement by the study participants, Table 1 also displays the tabulation of responses to our survey of 10 cancer epidemiologists. Examination of these data shows that none of the 12 statements were endorsed as true by any of the epidemiologists. For the most part, the epidemiologists identified the statements as false or as likely to be false (but difficult to evaluate because of absent or limited data), although the “true, but only in rare circumstances” response was used 3 times. For 7 of the statements 1 or more of the epidemiologists reported that they were not familiar with this topic.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

This study assessed the prevalence of belief in or uncertainty regarding several scientifically unsubstantiated statements about cancer risk in a sample of 975 US adults with no personal history of cancer. Overall, the results indicate that the participants in this study were able to identify several incorrect statements about cancer risk as being false. Specifically, the overall endorsement score across all 12 statements—the mean of the individual scores of all respondents—was less than 3. This suggests that, on average, participants in this study believed less than a quarter of these cancer risk statements to be true, which may be encouraging for health educators. Indeed, endorsement rates for most statements were relatively low, providing further evidence that the general public is able to correctly refute many erroneous cancer risk beliefs. At the same time, however, endorsement rates for several statements were relatively high, and belief in some of these statements could adversely affect health behaviors. For example, almost 4 in 10 believed that “living in a polluted city is a greater risk for lung cancer than smoking a pack of cigarettes a day.” This belief could affect smoking behaviors by reducing concern about the risk associated with tobacco. Statements such as this, which have higher levels of endorsement and relate directly to unhealthy behaviors, should be addressed by public health education. In addition, several sociodemographic characteristics (gender, race, education, and income) were associated with greater likelihood of endorsement (both in terms of the overall mean endorsement score and across individual items), suggesting avenues for developing targeted messages for particular at-risk populations.

Notably, the 2 most commonly endorsed statements were also among the statements that were unanimously identified as false by all 10 epidemiologists. Specifically, 68% of the respondents believed that the risk of dying from cancer in the US is increasing. This statement is clearly false, as the age-standardized cancer death rate has been decreasing since the early 1990s,11, 12 and the 5-year relative survival rate for all cancers combined has improved steadily over the last 30 years.13 Although these trends clearly reflect the decline in the cancer death rate, at the time of this survey the actual number of deaths from cancer had been steadily increasing over several decades because of the growth and aging of the US population.11 Thus, some respondents might have based their answer on the absolute number of cancer deaths, as opposed to either relative survival rates or age-standardized death rates. The second most commonly endorsed statement—that living in a polluted city is a greater risk for lung cancer than smoking a pack of cigarettes a day—was believed by 39% of the respondents, with an additional 19% uncertain. Despite frequent public education messages about risk associated with tobacco use, media coverage of carcinogenic environmental exposures such as pollution may impact the public's attitude about relative risks associated with these factors. Another possible explanation for this belief may lie with personal responsibility for the exposure. Although smoking behavior was not examined in the present study, our results are consistent with studies demonstrating that individuals who engage in behaviors like smoking or unprotected sun exposure tend to underestimate their own health risks associated with these choices despite knowledge of the risk in general, a phenomenon described as self-exempting optimistic bias.14–16

Two other misconceptions about smoking, each endorsed by about 15% of the respondents, are that there is little reduction in cancer risk when long-term smokers quit, and that low tar cigarettes are less dangerous than regular cigarettes. On the contrary, studies have found that quitting smoking is indeed associated with a reduced risk of lung cancer, even among long-term smokers,17 and research has not demonstrated any significant difference in cancer risk between smokers of regular and low-tar cigarettes.18 These misconceptions could have an obvious impact on behavioral choices, with significant health implications. Future public education and smoking cessation programs should include attempts to dispel such inaccurate beliefs. Although such misconceptions are of obvious concern, the remaining 6 misconceptions in this study were endorsed as true by less than 15% of the sample, and of these 6, 3 were endorsed by less than 10% of the respondents. This finding offers the encouraging suggestion that belief in these misconceptions is relatively low and may not require significant public education efforts.

In addition to noting substantial belief in several statements for the sample as a whole, we also found associations between certain sociodemographic variables and the combined endorsement score. When examining the endorsement of each statement individually, a consistent finding was that males were more likely to believe the statements to be true than were females, as noted for 8 misconceptions. Some research indicates that males may be less attentive to and less likely to seek medical information than are females19, 20 and thus may be less well informed, as suggested by these data. Lower educational levels were also significantly associated with higher combined endorsement scores, which is consistent with most prior studies of health literacy and with endorsement of 10 of the 12 statements.21–23 These findings suggest that public education and community intervention projects may be most effective and efficient if targeted to the groups with the most misconceptions about cancer risk.

One surprising result was that those claiming to be “very informed” about cancer were significantly more likely to endorse 4 of the statements, compared with those rating themselves as having lower cancer literacy. This finding is consistent with previous research demonstrating that people tend to overrate their own abilities and reach judgments with too much confidence.16 The practical implication for health education is that individuals who feel confident about their cancer knowledge may not ask relevant questions of their healthcare providers, and may therefore miss opportunities to obtain accurate information.

Although these data raise intriguing questions about the public's accuracy in judging cancer risk associated with certain factors, several limitations of this research should be noted. First, the degree to which these data can be considered representative of the US population is somewhat limited by the 35% response rate. However, the use of weights increased the concordance with national sociodemographic characteristics and a response rate in this range is consistent with other national studies from which conclusions about health behaviors are drawn.24

A second limitation relates to the lack of strong scientific evidence regarding some of the statements in this study. In support of including such statements, we assert that many important health decisions regarding risks and prevention are made by the general public in a context of limited or inconsistent evidence. In fact, research suggests that perceived ambiguity regarding cancer risk factors can increase worry about cancer and reduce perceived preventability.25 Although the 10 epidemiologists were not unanimous in conclusively rejecting all of the statements, none endorsed any of the statements as true. Furthermore, 10 of the 12 statements were rated as definitely false or likely to be false (but difficult to evaluate given current scientific knowledge) by the epidemiologists. The variation among the epidemiologists' responses, as assessed by qualitative follow-up interviews, concerned rare exceptions, the quality and quantity of available evidence, and the consistency of evidence. Because all 10 epidemiologists work together closely, their responses may not represent the full range of opinion within the epidemiologic community. It should be acknowledged that some evidence indicates that mammograms may actually result in a slight increase in the risk of developing breast cancer.26 Most experts, however, believe that the slight risk associated with mammography is more than offset by the considerable reduction in breast cancer mortality gained through early detection. Finally, the beliefs included in this survey were not selected based on estimates of the mortality attributed to related behaviors, but may still be useful as a proxy for cancer-related health literacy.

In sum, the key conclusions from this study are that beliefs in several scientifically unsubstantiated cancer risk statements are relatively common among the participants in this study, and that the prevalence of such beliefs varies by certain sociodemographic characteristics. Such beliefs may play a role in cancer disparities or influence actual health-related behaviors and adherence to screening guidelines, because previous research suggests that knowledge, attitudes, and beliefs about health and risk factors for disease contribute to the development and maintenance of disparities in heath outcomes.27, 28

Notwithstanding these results, it is important to recognize that individual beliefs are frequently not the most influential determinants of health behavior. For example, 1 of the most powerful predictors of cancer screening utilization is the healthcare provider's recommendation. Screening is also strongly influenced by healthcare access issues, such as having health insurance and a regular source of primary care.29 Likewise, the contribution of individual knowledge and beliefs to health disparities is influenced and often substantially limited by the broader socioeconomic context (eg, tobacco marketing targeting minority youths and the limited availability of healthful food choices and safe venues for physical activity in certain neighborhoods).30, 31 In addition, the extent to which beliefs about risk factors influence actual health behaviors is an important topic that should be addressed by future research. Public education programs and interventions to address and convincingly refute commonly held misconceptions regarding cancer risks might increase the adoption of healthy attitudes, beliefs, and, most important, behaviors. Such educational and intervention programs should be culturally informed and accessible to all individuals, with special attention placed on reaching the highest risk populations.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES

Supported by an Intramural funding of the American Cancer Society as well as outside funding from the Discovery Health Channel and Prevention Magazine.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. REFERENCES
  • 1
    Glanz K, Rimer BK. Theory at a Glance: A Guide for Health Promotion Practice. Bethesda, Md: US Dept. of Health & Human Services, Public Health Service, National Cancer Institute; 1997.
  • 2
    Rosenstock IM, Strecher VJ, Becker MH. Social learning theory and the Health Belief Model. Health Educ Q. 1988; 15: 175183.
  • 3
    Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall; 1986.
  • 4
    Prochaska JO, Redding CA, Evers KE. The transtheoretical model and stages of change. In: GlanzK, LewisFM, RimerBK, eds. Health Behavior and Health Education: Theory and Practice. San Francisco, Calif: Jossey-Bass; 1997: 6084.
  • 5
    Boulware LE, Cooper LA, Ratner LE, LaVeist TA, Powe NR. Race and trust in the health care system. Public Health Rep. 2003; 118: 358365.
  • 6
    Davis TC, Williams MV, Marin E, Parker RM, Glass J. Health literacy and cancer communication. CA Cancer J Clin. 2002; 52: 134149.
  • 7
    Nielsen-BohlmanL, PanzerAM, KindigDA, eds, for the Institute of Medicine Committee on Health Literacy. Health Literacy. A Prescription to End Confusion. Washington, DC: National Academies Press; 2004.
  • 8
    Breslow R, Sorkin J, Frey C, Kessler L. Americans' knowledge of cancer risk and survival. Prev Med. 1997; 26: 170177.
  • 9
    Gansler T, Henley SJ, Stein K, Nehl EJ, Smigal C, Slaughter E. Sociodemographic determinants of cancer treatment health literacy. Cancer. 2005; 104: 653660.
  • 10
    US Dept. of Health & Human Services. Healthy People 2010: Understanding and Improving Health. 2nd ed. Washington, DC: US Government Printing Office; 2000.
  • 11
    Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2007. CA Cancer J Clin. 2007; 57: 4366.
  • 12
    Ries LAG, Harkins D, Krapcho M, et al. SEER Cancer Statistics Review, 1975–2003. National Cancer Institute, Bethesda, Md. Updated 2006. Available at URL: http://seer.cancer.gov/csr/1975_2003/ Accessed on Nov. 26, 2006.
  • 13
    American Cancer Society. Cancer facts and figures, 2006. Atlanta, Ga: American Cancer Society; 2006.
  • 14
    Branstrom R, Kristjansson S, Ullen H. Risk perception, optimistic bias, and readiness to change sun related behaviour. Eur J Public Health. 2006; 16: 492497.
  • 15
    Weinstein ND, Marcus SE, Moser RP. Smokers' unrealistic optimism about their risk. Tob Control. 2005; 14: 5559.
  • 16
    Dunning D, Heath C, Suls JM. Flawed self-assessment. Implications for health, education, and the workplace. PsycholSci Public Interest. 2004; 5: 69106.
    Direct Link:
  • 17
    Taylor DHJr, Hasselblad V, Henley SJ, Thun MJ, Sloan FA. Benefits of smoking cessation for longevity. Am J Public Health. 2002; 92: 990996.
  • 18
    Harris JE, Thun MJ, Mondul AM, Calle EE. Cigarette tar yields in relation to mortality from lung cancer in the Cancer Prevention Study II prospective cohort, 1982–8. BMJ. 2004; 328: 7280.
  • 19
    Lorence DP, Park H, Fox S. Assessing health consumerism on the Web: a demographic profile of information-seeking behaviors. J Med Syst. 2006; 30: 251258.
  • 20
    Rutten LJ, Squiers L, Treiman K. Requests for information by family and friends of cancer patients calling the National Cancer Institute's Cancer Information Service. Psychooncology. 2006; 15: 664672.
  • 21
    Pohls UG, Fasching PA, Beck H, et al. Demographic and psychosocial factors associated with risk perception for breast cancer. Oncol Rep. 2005; 14: 16051613.
  • 22
    Ralston JD, Taylor VM, Yasui Y, Kuniyuki A, Jackson JC, Tu SP. Knowledge of cervical cancer risk factors among Chinese immigrants in Seattle. J Community Health. 2003; 28: 4157.
  • 23
    Viswanath K, Breen N, Meissner H, et al. Cancer knowledge and disparities in the information age. J Health Commun. 2006; 11( suppl 1): 117.
  • 24
    National Center for Chronic Disease Prevention and Health Promotion. Behavioral Risk Factor Surveillance System Summary Data Quality Report. Centers for Disease Control. Updated Aug. 25, 2006. Available at URL: http://www.cdc.gov/brfss/technical_infodata/quality.htm. Accessed on Oct. 24, 2006.
  • 25
    Han PK, Moser RP, Klein WM. Perceived ambiguity about cancer prevention recommendations: relationship to perceptions of cancer preventability, risk, and worry. J Health Commun. 2006; 11( suppl 1): 5169.
  • 26
    NCRP Scientific Committee 72 on Radiation Protection in Mammography. A Guide to Mammography and Other Breast Imaging Procedures:Recommendations of the National Council on Radiation Protection and Measurements. NCRP No. 149. Bethesda, Md: National Council on Radiation Protection and Measurements; 2004.
  • 27
    Coleman MP, Babb P, Sloggett A, Quinn M, De Stavola B. Socioeconomic inequalities in cancer survival in England and Wales. Cancer. 2001; 91( suppl): 208216.
  • 28
    House JS, Williams DR. Understanding and reducing socioeconomic and racial disparities in health. In: SmedleyBD, SymeSL, eds. Promoting Health: Intervention Strategies From Social and Behavioral Research. Washington, DC: National Academy Press; 2001: 81124.
  • 29
    Smith RA, Cokkinides V, Eyre HJ. American Cancer Society Guidelines for the Early Detection of Cancer, 2005. CA Cancer J Clin. 2005; 55: 3144.
  • 30
    Kushi LH, Byers T, Doyle C, et al. American Cancer Society guidelines on nutrition and physical activity for cancer prevention: reducing the risk of cancer with healthy food choices and physical activity. CA Cancer J Clin. 2006; 56: 254281.
  • 31
    Campaign for Tobacco Free Kids. Tobacco Company Marketing to African Americans. Campaign for Tobacco Free Kids. Updated 2006. Available at URL: www.tobaccofreekids.org/research/factsheets/pdf/0208.pdf. Accessed on Jan. 25, 2007.
  • 32
    Inskip PD, Mellemkjaer L, Gridley G, Olsen JH. Incidence of intracranial tumors following hospitalization for head injuries (Denmark). Cancer Causes Control. 1998; 9: 109116.
  • 33
    Merzenich H, Ahrens W, Stang A, et al. Sorting the hype from the facts in testicular cancer: is testicular cancer related to trauma? J Urol. 2000; 164: 21432144.
  • 34
    Schuz J, Jacobsen R, Olsen J, Boice JDJr, McLaughlin JK, Johansen C. Cellular telephone use and cancer risk: update of a nationwide Danish cohort. J Natl Cancer Inst. 2006; 98: 17071713.
  • 35
    Oliveria SA, Saraiya M, Geller AC, Heneghan MK, Jorgensen C. Sun exposure and risk of melanoma. Arch Dis Child. 2006; 91: 131138.
  • 36
    Mirick DK, Davis S, Thomas DB. Antiperspirant use and the risk of breast cancer. J Natl Cancer Inst. 2002; 94: 15781580.
  • 37
    Narod SA, Lubinski J, Ghadirian P, et al. Screening mammography and risk of breast cancer in BRCA1 and BRCA2 mutation carriers: a case-control study. Lancet Oncol. 2006; 7: 402406.
  • 38
    Gallagher RP, Spinelli JJ, Lee TK. Tanning beds, sunlamps, and risk of cutaneous malignant melanoma. Cancer Epidemiol Biomarkers Prev. 2005; 14: 562566.
  • 39
    Singer SR, Grismaijer S. Dressed to Kill. Pahoa, Hawaii: ISCD Press; 2005.