1. CONCLUSIONS AND DISCUSSION
Risk perception and water fluoridation support and opposition in Australia
Jason M. Armfield1 and Harry F. Akers2
1 Australian Research Centre for Population Oral Health, School of Dentistry, University of Adelaide, South Australia, 2 University of Queensland, Queensland
Table 1. Twenty outrage factors identified by Sandman
ABSTRACT
1. Voluntariness
2. Naturalness
3. Familiarity
4. Media attention
5. Delayed effects
6. Dread
7. Uncertainty
8. Fairness
9. Controllability
10. Trust
11. Secrecy
12. Arrogance
13. Personal stake
14. Reversibility
15. Understanding
16. Benefits
17. Ethical/moral nature
18. Catastrophic potential
19. Effects on children
20. Accident history
Background: Despite water fluoridation enjoying reasonably strong support in Australia, a sizeable minority of people are opposed to this important public health measure and it is not uncommon for the introduction of water fluoridation to be voted down at public referendums. It is therefore important to better understand individual-level factors related to support for or opposition to water fluoridation. Aims: To provide preliminary support for Sandman's influential model of risk perception which states that the general public’s perception of risk is based on socially defined ‘outrage‘ factors. It was hypothesised that a number of identifiable outrage factors would be significantly associated with level of water fluoridation support and opposition. Methods: A cross-sectional survey design was used to obtain questionnaire data from a stratified national sample of 460 Australian adults (response rate = 32%) aged 18 to 92 years of age. Data were weighted to reflect estimated state and territory adult resident populations by age and sex. Results: An estimated 70% of Australians supported water fluoridation, 16% opposed water fluoridation to some extent, while 14% were neutral. Sixteen of the 20 measured outrage factors were significantly associated with support for water fluoridation in the direction predicted by Sandman's theory. The significant items were combined into a single Outrage Index which accounted for 62% of the variance in water fluoridation support strength in a bivariate regression model and was a strong and statistically significant predictor of water fluoridation support strength after controlling for socio-demographic characteristics, having children, socio-economic status, beliefs related to benefits and harm, and self-rated knowledge. Conclusion: Risk perception was an independent correlate of water fluoridation support and opposition. Being able to communicate risks to the general public by addressing known outrage factors may reduce public outrage and aid efforts in extending water fluoridation into currently non-fluoridated areas. Acknowledgements: This study was supported by the Australian Dental Research Foundation.
Figure 2. Boxplots showing univariate distribution of measures of support strength and outrage
Dependent variables
Water fluoridation stance was assessed by the question “…how supportive or opposed are you in relation to water fluoridation?” on a 7-point scale (response range: –3 to +3. Commitment to that stance was assessed by the question “do you think you would change your…[stance] on the basis of new information or research?” (response range: 1 to 4). Responses to the two questions were multiplied together to obtain a measure of support strength ranging from –12 (committed strong opposition) to +12 (committed strong support).
INTRODUCTION
Water fluoridation has long been the backbone of public health initiatives to reduce dental caries1.
Public support is often essential for the introduction or continuation of water fluoridation.
The reasons behind an individual’s support of, or opposition to, water fluoridation have received little empirical or theoretical inquiry.
Sandman has proposed a general risk perception model in which he argues that whereas ‘experts’ see risk in terms of quantifiable hazards, the public perception of risk reflects various outrage factors such as voluntariness, control, responsiveness, fairness, perceived secrecy and dread2,3.
Sandman spoke in 1990 at the National Oral Health Conference in California, USA on the public perception of fluoridation risks4. However, the application of his risk perception model to water fluoridation has not been tested empirically.
Figure 3. Scatterplot of association between water fluoridation support strength and outrage
RESULTS
A total of 460 adults (response rate = 32.1%), aged 18–92 years old, returned completed questionnaires.
An estimated 70.2% of Australians supported and 16.1% opposed water fluoridation to some extent, while 13.6% were neutral (Figure 1).
Multivariate general linear modeling controlling for the participants’ age in years (18–39, 40–64, 65+), sex, child age (0–11, 12–17, 18+, no children), highest level of education completed (Up to Year 10, High School, Diploma or Certificate, University, missing), household income (<$30K, >$30K–$60K, >$60K–$100K, >$100K, missing), self-rated knowledge, perceived dental benefits to adults and to children, and perceived harm (Yes, No/Don’t know), found that outrage remained a statistically significant predictor of support strength (Table 3). Outrage had a stronger relationship with support strength (β = -4.79) than did perceived harm (β = -3.46).
70.2%
16.1%
AIMS
Table 3. Multivariate linear regression results
To determine the level of fluoridation support among Australian adults.
To confirm the hypothesised associations between risk perceptions, based on Sandman’s various identified outrage factors, and support for, and opposition to, water fluoridation. F
Sig.
Partial Eta
Age
2.01
n.s.
.011
Sex
0.58
.002
Child age/category
0.53
.004
Highest education
2.59
0.037
.028
Household income
4.15
0.003
.043
Perceived knowledge
1.68
.018
Benefit to adults
1.93
.021
Benefit to children
2.62
0.035
Perceived harm
31.94
<0.001
.080
Outrage
136.77
.272
Figure 1. Water fluoridation stance (support or opposition)
The association between water fluoridation stance and commitment to that stance was statistically significantly (Table 2). Those people strongly opposed to water fluoridation were most committed to their stance while those people a little opposed, neutral or a little or moderately supportive were most likely to change their opinion (‘Yes, definitely’ or ‘Yes, maybe’) if presented with new information (88.9%, 88.9%, 98.1%, and 89.5% respectively).
MATERIALS AND METHODS
Sampling and weighting
A stratified random sample of 1,500 Australian households was selected from the Electronic White Pages. Selection of an individual adult (18+ years) within a household was based on most recent birthday. Data for this study were weighted by age and sex estimated resident populations within each state and territory.
Independent variables
The questionnaire contained sections on participants’ socio-demographic characteristics, water fluoridation stance and their commitment to that stance, self-rated water fluoridation knowledge, beliefs of dental health benefits for children and adults, beliefs of harm (“Do you believe that drinking fluoridated water causes harmful diseases, disorders or illnesses?”), risk perceptions (which reflected various outrage factors), and socio-economic status.
Risk perceptions were assessed by operationalising 20 outrage factors regarded as important to risk perception2,5 (Table 1). As an example, voluntariness was assessed by the question: “To what extent do you see the drinking of fluoridated water as either voluntary or imposed upon people?” Responses were recorded on a 4-point scale ranging from 1 (least outrage) to 4 (most outrage). A general measure of perceived risk, the Outrage Index, was developed from the mean of the items.
n.s. = not significant; Model R2 = 0.712
CONCLUSIONS AND DISCUSSION
Water fluoridation support in Australia remains high but most people would change their stance on water fluoridation in the face of new information or research.
Consistent with Sandman’s model2,3, risk perceptions reflecting outrage factors had a strong association with water fluoridation support strength even after controlling for several other variables including perceived benefits and harms.
In terms of risk communication for low risk, high outrage issues such as water fluoridation, successful communication should be aimed at reducing outrage rather than denying hazards.
Table 2. Water fluoridation stance by commitment to stance
Likelihood of changing stance (row %s)
Water fluoridation stance
“Yes, definitely”
‘Yes, maybe”
“No, not likely”
“Definitely not”
Total n
Strongly opposed
6.8
20.5
31.8
40.9 44
Moderately opposed
7.7
69.2
23.1
0.0 13
A little opposed
16.7
72.2
11.1 18
Neutral
15.9
73.0 63
A little supportive
17.3
80.8
1.9 52
Moderately supportive
28.9
60.5
10.5
114
Strongly supportive
9.6
59.6
19.2
11.5
156
Fisher’s Exact Test = , p < 0.001
A series of bivariate analyses indicated that 16 of the 20 risk perception questions were significantly associated with support strength (p < 0.01) in the predicted direction (the non-selected items were numbers 3, 4, 5 and 15 shown in Table 1). The selected items were combined into an Outrage Index (Cronbach’s α = 0.90, mean inter-item correlaton = 0.36). The univariate distributions of both the Outrage Index and Support Strength are shown in Figure 2.
Bivariate linear regression modeling found that the Outrage Index accounted for 61.7% of the variance in water fluoridation support strength (Figure 3).
REFERENCES
Armfield JM. The extent of water fluoridation coverage in Australia. Aust NZ J Pub Health 2006;30:581–2.
Sandman PM. Risk communication: facing public outrage. EPA Journal 1987;13:21–2.
3. Sandman PM. Responding to community outrage: strategies for effective risk communication. American Industrial Hygiene Association, US; 1993.
4. Park B, Smith K, Malvitz D, Furman L. Hazard vs outrage: public perception of fluoridation risks. J Public Health Dent 1990;50:285–7.
5. Covello V, Sandman PM. Risk communication: evolution and revolution. In: A Wolbarst (Ed.), Solutions to an environment in peril (pp. 164–178). Baltimore: John Hopkins University Press; 2001.
ACKNOWLEDGEMENTS
This study was supported by a grant from the Australian Dental Research Foundation.