Introduction
In most subpopulations, heart disease incidence is higher than cancer incidence,1 yet laypeople may think the reverse given extensive cancer exposure2 such as the “pink ribbon” campaign and celebrity deaths (e.g., Peter Jennings3). People often overestimate their own cancer risk4 and thus may also overestimate its relative prevalence. Such misperceptions could promote underuse of preventive interventions for cardiovascular disease and overuse of cancer risk reduction strategies.
Concomitantly, laypeople perceive cancer messages as highly ambiguous (defined in decision science as lacking in reliability, credibility, or adequacy5) and fatalistic. In one study,6 72% of U.S. citizens believed there were too many cancer prevention recommendations and 47% agreed that everything causes cancer. These beliefs are associated with greater perceived risk and cancer worry.7 We used a nationally representative sample to assess whether such beliefs are related to misperceptions about relative prevalence. We also explored how these misperceptions might be related to demographics and risk-related behavior.
Methods
Data were collected from 3,376 U.S. adults in 2012–2013 via the National Cancer Institute Health Information National Trends Survey (HINTS) and analyzed in 2013. The sample included 51% women, 75% whites, 41% with high school education or less, 58% never smokers, and 75% with own or family cancer history.
Questionnaires were randomly mailed to residential addresses and completed by the adult with the next birthday. Relative prevalence perceptions were assessed with: How much do you agree or disagree with the following statement: In adults, cancer is more common than heart disease (1=strongly agree through 4=strongly disagree). Perceptions of ambiguity and fatalism were assessed on the same scale with How much do you agree or disagree with each of the following statements: It seems like everything causes cancer, There’s not much you can do to lower your chances of getting cancer, and There are so many recommendations about preventing cancer, it’s hard to know which ones to follow. Standard measures assessed sample demographics; personal cancer risk perceptions; cancer experience; health behaviors; cancer information seeking (including frustration when doing so); and numeracy (HINTS downloadable at hints.cancer.gov/docs/HINTS_4_Cycle_2_English.pdf).
Results
To control for bias in variance estimates due to the complex sampling design, jackknife replicate weights were employed. Univariate logistic regressions identified significant predictors of perceived prevalence. Significant univariate predictors (p<0.05) were entered simultaneously in a final multivariable regression model (Table 1).
Table 1.
Results from univariate and final logistic regressions predicting the belief that cancer is more common than heart disease
| Univariate logistic regression |
Final logistic regression | |||
|---|---|---|---|---|
| Predictora | OR (95% CI OR) | p | OR (95% CI OR) | p |
| Gender (51% women) | 1.09 (0.70, 1.69) | 0.694 | ||
| Age (M=46.64, SD=16.64) | 1.00 (0.99, 1.01) | 0.886 | ||
| Less than HS (13%) versus college (29%) | 1.82 (1.18, 2.80) | 0.007 | 3.34 (1.61, 6.93) | 0.002 |
| HS (28%) versus college (29%) | 1.96 (1.46, 2.61) | 0.000 | 1.15 (0.69, 1.91) | 0.584 |
| Some college (30%) versus college (29%) | 1.29 (0.92, 1.81) | 0.134 | 1.26 (0.75, 2.12) | 0.383 |
| White (76%) | 1.00 (0.95, 1.06) | 0.991 | ||
| Smoker (19%) versus never smoker (59%) | 0.83 (0.55, 1.24) | 0.348 | ||
| Former smoker (23%) versus never smoker (59%) | 0.81 (0.62, 1.05) | 0.105 | ||
| Cancer diagnosis (8%) | 0.89 (0.69, 1.14) | 0.337 | ||
| Family members with cancer (67%) | 0.97 (0.82, 1.16) | 0.747 | ||
| Numeracy (1–4, M=1.10, SD=0.31) | 1.07 (0.75, 1.52) | 0.716 | ||
| Lifetime cancer risk (absolute risk) (1–5, M=2.73, SD=0.83) | 1.09 (0.96, 1.24) | 0.197 | ||
| Lifetime cancer risk (comparative risk) (1–5, M=2.79, SD=0.88) | 1.02 (0.84, 1.23) | 0.852 | ||
| It seems like everything causes cancer (1–4, M=2.27, SD=0.96) | 0.80 (0.71, 0.90) | 0.000 | 0.70 (0.58, 0.85) | 0.001 |
| There are so many different recommendations about preventing cancer it’s hard to know which ones to follow (1–4, M=2.07, SD=0.87) | 0.72 (0.62, 0.84) | 0.000 | 0.78 (0.59, 1.04) | 0.091 |
| There’s not much you can do to lower your chances of getting cancer (1–4, M=2.94, SD=0.89) | 0.78 (0.68, 0.89) | 0.001 | 0.92 (0.74, 1.15) | 0.468 |
| Cancer information seeking, frustration (1–4, M=2.99, SD=0.97) | 0.82 (0.67, 1.00) | 0.046 | 0.97 (0.73, 1.31) | 0.864 |
| Cancer information seeking, easy to understand (1–4, M=3.00, SD=0.91) | 0.72 (0.60, 0.88) | 0.002 | 0.80 (0.59, 1.07) | 0.125 |
| Linear regressions | ||||
| Outcome | β | t | p | d |
| Exercise intentions (1–3, M=1.78, SD=0.85) | 0.04 | 2.85 | 0.006 | 0.10 |
| Soda consumption intentions (1–3, M=2.03, SD=0.89) | 0.05 | 0.33 | 0.746 | 0.01 |
| Vegetable consumption intentions (1–3, M=1.99, SD=0.84) | 0.04 | 0.53 | 0.596 | 0.02 |
| Fruit consumption intentions (1–3, M=2.12, SD=0.86) | 0.05 | 0.87 | 0.390 | 0.03 |
| Weight management intentions (1–3, M=2.01, SD=1.17) | 0.09 | 1.59 | 0.716 | 0.05 |
| Sunscreen use (1–5, M=3.45, SD=1.41) | 0.09 | 0.37 | 0.117 | 0.01 |
| Mammography (1–6, M=3.29, SD=2.13) | 0.04 | −0.26 | 0.792 | 0.01 |
For 1–4 scales, 1=strongly agree through 4=strongly disagree; for 1–5 scales, 1=very unlikely through 5=very likely; for exercise, vegetables, and fruit, 1=increase, 2=maintain, and 3=haven’t paid attention; for soda and weight, 1=decrease, 2=maintain, and 3=haven’t paid attention; for sunscreen, 1=never through 5=always; for mammography, 1=1 year ago or less, 2=more than 1, up to 2 years ago, 3=more than 2, up to 3 years ago, 4=more than 3, up to 5 years ago, 5=more than 5 years ago, and 6=never had a mammogram.
HS, high school
Approximately 44% agreed or strongly agreed that cancer was more common than heart disease. Higher perceived relative cancer prevalence was associated with lower education level but not age, race, smoking status, numeracy, personal risk perception, or cancer experience. The ambiguity and fatalism measures (and frustration in seeking cancer information) were significantly associated with believing that cancer is more prevalent. In multivariable analyses, the perception that everything causes cancer was the most predictive item. Misperceptions were related to exercise intentions but no other behaviors.
Discussion
Many U.S. citizens, including the highly educated, erroneously believe that cancer is more common than heart disease. Cancer experience and attitudes about personal risk appear unrelated to prevalence perceptions, as does age even though older individuals have more experience with both diseases. Individuals who perceived cancer as more prevalent were more likely to engage in exercise but not other behaviors related to both diseases such as healthy diet and physical activity.
Perceptions of cancer message ambiguity and fatalism may underlie misperceptions of cancer prevalence. Other work shows that people misunderstand the relative prevalence of different cancers, perhaps for similar reasons.8 Although more work is needed to establish causality, these findings suggest the need to design cancer messages not only to be less ambiguous but to explicitly present health risks in the context of other health risks—consistent with the finding that people are often more responsive to comparative than absolute information.9 Of course, such an approach would need to be tailored for subpopulations with higher cancer risk.
One limitation is that respondents may have focused on mortality rather than morbidity and may have used a narrow definition of heart disease. Although heart disease prevalence is higher across all adult age groups,1 cancer accounts for more deaths in those aged <85 years.10 Nevertheless, if the misperception about prevalence is pervasive, further research should consider whether it is consequential and how it might be addressed.
Footnotes
No financial disclosures were reported by the authors of this paper.
Contributor Information
William M.P. Klein, National Cancer Institute, NIH, Bethesda, Maryland.
Rebecca A. Ferrer, National Cancer Institute, NIH, Bethesda, Maryland.
Kaitlin A. Graff, National Cancer Institute, NIH, Bethesda, Maryland.
Annette R. Kaufman, National Cancer Institute, NIH, Bethesda, Maryland.
Paul K.J. Han, Email: kleinwm@mail.nih.gov, Maine Medical Center, Portland, Maine.
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