Volume
8: No. 6, November 2011
Liesbeth Claassen, PhD; Lidewij Henneman, PhD; Giel Nijpels, MD, PhD; Jacqueline Dekker, PhD; Theresa Marteau, PhD; Danielle Timmermans, PhD
Suggested citation for this article: Claassen L, Henneman L, Nijpels G, Dekker J, Marteau T, Timmermans D.
Causal beliefs and perceptions of risk for diabetes and cardiovascular
disease, the Netherlands, 2007. Prev Chronic Dis 2011;8(6):A130.
http://www.cdc.gov/pcd/issues/2011/nov/10_0276.htm. Accessed [date].
PEER REVIEWED
Abstract
Introduction
Understanding people’s perceptions of disease risk and how these
perceptions compare with actual risk models may improve the effectiveness of risk communication. This study examined perceived disease risk and causal beliefs
for type 2 diabetes and cardiovascular disease (CVD), the relationship between self-reported risk factors and perceived disease risk, and the influence of causal beliefs on perceived disease risk in people at increased risk.
Methods
The sample (n = 255) consisted of people who were at increased risk for diabetes and CVD (aged 57-79 y). Participants completed a postal questionnaire assessing risk factors, perceived risk, and causal beliefs
for diabetes and CVD. We used regression analyses to examine the relationship between risk factors and perceived disease risk and to explore how causal beliefs affect the relationship between risk factors and perceived disease risk.
Results
Associations between risk factors and perceived diabetes and CVD risks were weak. Perceived risk, causal beliefs, and explained variance of risk factors on perceived risk were lower for diabetes than for CVD. Stronger beliefs concerning 1) overweight as a cause of diabetes and 2) smoking as a cause of CVD strengthened the association between
these risk factors and perceived disease risk.
Conclusion
Although participants seemed to have some understanding of disease causation, they only partially translated
their risk factors into accurate perceptions of risk. To improve understanding of risk information, health professionals may need to educate patients on how personal risk factors can contribute to the development of diabetes and CVD.
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Introduction
Epidemiological models indicate that several factors contribute to the development of diabetes and
cardiovascular disease (CVD). Many patients who develop diabetes or CVD have a history of physiological characteristics associated with a disordered metabolism such as insulin resistance, cholesterol abnormalities, hypertension, and abdominal obesity (1,2). These metabolic abnormalities increase with age and are mostly caused by a combination of genetic and behavioral factors (ie, unhealthy eating habits,
physical inactivity, and smoking). Reflecting the consequences of interactions among multiple genetic and behavioral factors, a family disease history is a strong and independent risk factor for diabetes (3,4) and CVD (5-7),
and having diabetes increases the risk of CVD by 2 to 4 times (2).
Some researchers have argued that perceptions of disease risk are based on matching personal risk factor information with beliefs about risk factors and causes of disease (8-11). If a
risk factor does not fit within beliefs about disease causation, it is unlikely to increase perceived risk. For example, smoking may only be associated with higher risk of a disease if it is considered an important cause of the disease.
The few studies on causal beliefs for diabetes and CVD show that most people believe that both lifestyle factors and genetic factors could cause these diseases (12-14). However, these studies did not examine the role of causal beliefs in perceived disease risk or make comparisons
between diseases. To improve the effectiveness of disease risk communication, a better understanding
of how people perceive their risk of developing a disease is needed.
The objective of this study was to examine the extent to which causal beliefs
about diabetes and CVD affected the relationship between self-reported risk factors and perceived disease risk. We examined how people perceive their risk of diabetes and CVD in relation to
their actual risk according to epidemiological models.
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Methods
Design, sample, and procedure
We used data from a cross-sectional study performed in 2007. The sample was recruited from a database of a population-based screening program to identify people with undiagnosed diabetes among inhabitants of a semirural region of the Netherlands, carried out from 1998 through 2000 (15). Participants in this program first filled out a Symptom Risk Questionnaire, which included questions about age, family history of diabetes, and body mass
index (BMI). Participants who screened positive (scores ≥6) were subsequently biochemically tested for diabetes. High scores indicated a high risk
for diabetes and CVD (16). We randomly selected a subset (n = 319) of all people who screened positive and who did not have diabetes at the time of testing
and mailed them a letter, describing this study. The letters included study information and informed consent forms. Participants who reported not having diabetes and who signed and returned the informed consent form were sent a postal questionnaire (participation rate was 80%, n = 255). The VU University Medical Center ethical
committee in Amsterdam approved the study protocol. Participants provided data
on age, sex, marital status, and educational level.
Measures
Coding of self-reported risk factors. We used 4 measures to assess physiological risk factors associated with a disordered metabolism. Participants were asked if they had been diagnosed with high cholesterol
or blood pressure. For both items, we coded “yes” responses as 1 and
“no” responses as 0. With self-reported weight (in kg) and height (in m), we calculated BMI.
Normal weight (BMI <25.0 kg/m2) was coded as 0, overweight (BMI 25.0-29.9 kg/m2) as 1,
and obese (BMI ≥30.0 kg/m2) as 2.
We collected data on 3 behavioral risk factors: 1) unhealthy diet and eating habits, 2) lack of physical activity, and 3) smoking. The first 2 behaviors were assessed by the extent of agreement with the statements, “I attend to my diet and see to it that I eat healthy every day” and “I see to it that I am sufficiently physically active every day” (explained in the instructions to participants as eating food with little saturated fat and at least 2 pieces
of fruit and 200 g of vegetables every day and at least half an hour of moderately intense physical activity, such as walking, biking, swimming
or gardening, 5 d/wk); responses ranged from 1 (completely disagree) to 5 (completely agree). For both statements, responses were dichotomized: 1, 2, and 3 were recoded as 1, and categories 4 and 5 were coded as 0. Participants also indicated which category best described their smoking behavior (response categories: “I am a smoker,” “I
stopped smoking less than 2 years ago,” “I stopped smoking more than 2 years ago,” and “I have never smoked [with any regularity]).” Nonsmokers and ex-smokers were assigned a score of 0, and current smokers were assigned a score of 1. Participants also provided information on how many (0, 1,
or ≥2) and which of their 1st-degree family members (parents and siblings) were affected by diabetes and CVD, respectively.
Perceived disease risk. With 2 items for diabetes and CVD, we assessed perceived disease risk: “How likely do you think it is that you will get diabetes
[or CVD] within the next 10 years?” (1 [very unlikely] to 7 [very likely]),
“Based on your feelings, what is the chance that you will develop diabetes
[or CVD] within the next 10 years?” (1 [very low] to 7 [very high]). Reliability (Spearman-Brown coefficient) of this measure was
rsh =. 93 for both diabetes and CVD.
Causal beliefs. In a list of possible causes of diabetes (or CVD),
taken from the revised Illness Perception Questionnaire (17), participants
indicated for each cause the extent to which they believed it could be a cause
of diabetes (or CVD). For this present study, we selected the causes associated
with established risk factors: “advancing age,” “unhealthy diet or eating
habits,” “lack of physical activity,” “smoking,” and “hereditary, diabetes [CVD]
runs in the family.” In addition, participants indicated the extent to which
they believed “being overweight” could be a cause of diabetes and the extent to
which they believed “raised cholesterol levels,” “raised blood pressure,” and
“having diabetes” could increase the risk of CVD. Responses for all items were
assessed on 5-point rating scales from 1 (definitely not) to 5 (definitely).
Statistical analyses
Data analyses were performed by using SPSS 15.0 (SPSS, Inc, Chicago, Illinois). To describe the characteristics of the sample and perceived disease risk and causal beliefs
for diabetes and CVD, we generated means, standard deviations, and frequencies. Cases with missing values were
deleted pairwise from the subsequent analyses. Simple and multiple regression analyses were
used to examine the predictive value of the 9 risk factors on perceived risk of diabetes and CVD. To explore the moderating role of causal beliefs on
perceptions of disease risk, we performed a series of separate hierarchical multiple regression analyses for each risk factor. In the first step, we entered the risk factor and the associated causal belief in the regression; in the second step, we added an interaction term (product of risk factor and causal belief) to the regression. A moderator effect is present if the interaction term explains a significant amount of variance in perceived risk
(P <.05). To compare across diseases, we performed paired-samples t tests to assess the difference between perceived risk of diabetes and of CVD and differences in causal beliefs.
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Results
The mean age of participants was 66 years (standard deviation [SD] 5, range 57-79). Most participants were either married or living together, education level was generally low, and a high percentage of participants were overweight
(Table 1).
Perceived disease risk and predictive value of risk factors
Mean scores of both measures of perceived risk measures were below the scale
midpoint
(Table 2). Mean scores for perceived risk of diabetes were significantly lower than means scores for perceived risk of CVD.
A positive family history of diabetes and lack of physical activity were positively associated with perceived diabetes risk, and being 65 years or older was negatively associated with perceived diabetes risk
(Table 2). Raised cholesterol levels, family history of CVD, unhealthy diet and eating habits, and lack of physical activity were positively associated with perceived CVD risk; being 65 years or older and having a family history of diabetes were negatively associated with perceived CVD risk.
Taken together, self-reported risk factors accounted for 11% of the variance in perceived risk of diabetes and 18% of the variance in perceived risk of CVD (Table 2).
Causal beliefs and the relationship between risk factors and perceived
disease risk
Causal beliefs concerning behavioral factors (unhealthy diet, lack of physical activity, and smoking) were weaker for diabetes than for CVD (Figure). Mean scores for causal beliefs about diabetes ranged from 2.9 (SD, 1.2) for “smoking” to 4.0 (SD, 1.0) for “being overweight” (Figure). Mean scores for beliefs about CVD were
at least ≥4.0, except for “advancing age” (mean, 3.7; SD,
0.9) and “having diabetes” (mean, 3.4; SD, 1.1).
Figure. Causal beliefs for diabetes and cardiovascular disease,
the Netherlands, 2007 (n = 255). Participants indicated on a scale of 1 to 5 for each cause the extent to which they
believed it could be a cause (or risk factor) of diabetes or cardiovascular disease.
[A tabular version of this figure is also available.]
For diabetes, we found significant interaction effects between risk factors
and causal beliefs for advancing age and being overweight (Table 3a). For advanced age, explained variance in perceived risk of diabetes increased from 3% for age category alone to 6% when the interaction term, the risk factor causal belief, was added; for being overweight, explained variance in perceived risk of diabetes increased from 0% to 3%. For CVD, we found significant risk factor causal belief interaction effects for smoking and heredity (Table 3b). For smoking, explained variance in perceived risk of CVD increased from 0% to 3% and for family history, explained variance increased from
3% to 8%. Other causal beliefs for diabetes and CVD did not significantly moderate the relationship between risk factor and perceived disease risk.
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Discussion
Participants in this sample of older adults at risk for CVD and diabetes only partially translated self-reported risk factor information into perceptions of risk. They seemed to have a somewhat better understanding of the association between risk factors and CVD risk than between risk factors and diabetes risk. Although for some risk factors, causal beliefs strengthened the association between self-reported risk factor and perceived disease risk (ie, for perceived risk of diabetes, association between advancing
age and being overweight, and for perceived risk of CVD, association between smoking and heredity), for other risk factors, no moderator effects of causal beliefs were found.
These results support earlier findings that family disease history is associated with perceived risk of diabetes (18-21) and CVD (22-24). We found that believing more strongly that heredity could be a cause of disease strengthened the association between family history of CVD and perceived CVD risk but not between family history of diabetes and perceived diabetes risk.
It is possible that the association between family history and perceived risk of diabetes
is best explained by the salience of diabetes in memory, which increases with the number of and closeness to people they know with diabetes, rather than family history and heritability of diabetes per se (13).
There was an unexpected negative association between family history of diabetes and perceived CVD risk. Any explanation is highly speculative and further studies are needed to determine the exact
relationship between family history of diabetes and perceptions of CVD risk.
Similar to other studies conducted in the Netherlands (20,24) and the United States (18,21), we found that people
older than 65
years had lower perceptions of risk than younger people. Considering that this age group has a higher objective risk of diabetes (17) and CVD (25), their lower risk perceptions may be viewed as misconceptions. In addition, the negative relationship between age and perceived diabetes risk was even more pronounced in participants who viewed advancing age as an
important cause of diabetes. One explanation is that after a certain age, people may think that if they were likely to develop a disease, they would already have developed the disease. People may also minimize their risk as a defensive mechanism.
In general, associations between risk factors and perceived disease risk were weak. Confirming the findings of previous studies (20,21), we found that
neither being overweight nor smoking were associated with higher perceived risk of diabetes. Contrary to previous findings, we also found that perceived risk of CVD was not primarily associated with being a smoker (24,26). However, most participants indicated that they believed being overweight could cause diabetes, and
smoking could cause CVD. One explanation for this apparent paradox may be that in general, people show an optimistic bias when considering their own health risk (27). People believe that they are healthier than others not because they have inaccurate knowledge about the causes of disease but because they do not correctly apply this knowledge to themselves. In particular, they may believe their actions contributing to risk (eg, smoking) are outweighed by their actions to prevent
risk (eg, engaging in sufficient physical activity). Notably, being overweight and believing that overweight could be a cause of diabetes was associated with higher perceptions of diabetes risk. Similarly, being a smoker and believing that smoking could be a cause of CVD was associated with higher perceptions of CVD risk.
For other risk factors, causal beliefs did not strengthen the associations between risk factor and perceived risk. One explanation may be that causal beliefs were assessed with closed questions, which tend to overestimate actual knowledge of disease causation (12). The absence of a moderator effect for causal beliefs concerning
unhealthy diet and eating habits and lack of physical activity may also be explained by the phrasing of the items assessing these factors. Participants were
not asked to report on their behavior as such, but to provide qualitative judgments. Responses included, “I attend to my diet and see to it that I eat healthy every day,” and “I see to it that I am sufficiently
physically active every day.” Disagreement with these items already indicates some awareness of a causal link
between self-reported behavior and health risk.
Previous studies comparing perceived risk of diabetes and CVD show inconsistent results. Although DiLorenzo et al (28) found that people perceive their risk of developing CVD as higher than the risk of developing diabetes, Wang et al (29) found no difference in perceived risk between diabetes and CVD.
In our study, we found that participants perceived their risk for CVD as higher than for diabetes. Furthermore, self-reported risk factors explained more variance in perceived CVD
risk than in perceived diabetes risk. Participants also demonstrated a better knowledge about the causes of CVD risk than about the causes of diabetes risk. The
general public is probably better informed about risk factors and causes for CVD because it is the leading cause of death in the Netherlands and is more prevalent than diabetes.
Notably, having diabetes was not generally understood as a risk factor for CVD. Other studies also show that even among people diagnosed with diabetes, the
link between having diabetes and higher risk of CVD is not clearly understood (24,26).
This study has some limitations. First, it presents cross-sectional data and therefore, does not show the dynamic relationship between risk factors, perceived disease risk, and causal beliefs. If a personal risk factor is seen as increasing disease risk or as an important cause of disease, then a person may be motivated to engage in preventive behavior, which in turn may reduce the number of risk factors.
Second, people may not accurately report on risk factors. Third, the representativeness of the study population
is unknown. The sample participated in a population-based diabetes screening program some years earlier; therefore, their understanding of diabetes risk might have been better than that of the average at-risk population.
On the other hand, being tested for diabetes and not having diabetes could have minimized the belief that the risk factors had any personal relevance and
might have reduced the moderating
effect of causal beliefs.
Our results confirm that people’s understanding of their risk of developing diabetes and CVD is limited. In general, people have some knowledge of disease causation, in particular of CVD, but only partially use this knowledge to link personal risk factors to an increased risk. To address misconceptions and improve understanding of risk information, health professionals may need to educate
patients on the causes of disease and how personal risk factors can contribute to the
development of diabetes and CVD.
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Acknowledgments
This study was conducted as part of a research project funded by the Societal Component of Genomics Research of the Netherlands Organization for Scientific Research (grant no. 050-32-022).
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Author Information
Corresponding author: Liesbeth Claassen, PhD, Department of Public and
Occupational Health, EMGO Institute for Health and Care Research,
VU University Medical Center, PO Box 7057, 1007 MB Amsterdam,
the Netherlands. Telephone: +31 (0)20-4449619. E-mail:
liesbeth.claassen@vumc.nl.
Author Information: Lidewij Henneman, Danielle Timmermans, Giel Nijpels, Jacqueline Dekker, EMGO Institute for Health and Care Research, VU University Medical Center,
Amsterdam, the Netherlands; Theresa Marteau, Health Psychology Section (at Guy’s), King’s College, London, United Kingdom.
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