1. Ispra meeting June 15-16, 2009 Lennart Sjöberg
Perceived risks of chemicals in consumer products in the European Union: Clothing textiles
Ispra meeting
June 15-16, 2009
Lennart Sjöberg
Lennart Sjöberg June 2009 Ispra meeting

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Background
”Chemicals” found to be perceived as very risky in previous, now dated, research
Study was conducted to update knowledge about risk perception of chemicals in consumer products
Respondents from all member states in the EU
Lennart Sjöberg June 2009 Ispra meeting

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Table 1. Mean percentage of cases where a product category was stated to be risky, across all countries and respondents.
Product category
Mean percentage
Pesticides or herbicides 74
Bleach and heavy duty cleaners 68
Bathroom cleaners 49
Hair dyes 44
Interior paints 40
Timber preservatives 39
Laundry or dishwashing detergents 30
Washing powder 28
Fabrics: Synthetic fibers 25
Sunscreens 19
Hair shampoo 13
Fabrics: Wool cotton or linen 12
Toothpaste 9
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Comments
Very large differences among product types
”Chemicals” per se do not seem to be uniquely risky
Synthetic fabrics somewhat risky
Natural fabrics clearly less risky, supporting the importance of ”naturalness” for risk perception
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Comments
Three clusters of countries:
Nordic countries and Germany (both East and West)
Southern and Baltic countries (Italy, France, Romania and Baltic countries)
Central and Eastern Europe
Unclear reasons for some of the placements
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Comments
Multi-modal distribution
Many respondents saw no or very few risks
A minority (about 10 percent) appeared to be alarmed
Results agree with previous work showing most people unconcerned about risks
See Sjöberg, L. (2006). Rational risk perception: Utopia or dystopia? Journal of Risk Research, 9(6),
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Comments
Effects of education opposite to expectation
Possible reason: Question asked about knowledge, not belief or perceived risk
Interesting topic for further research
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More demographics
Leftist political orientation was associated with checking more items as risky
In larger households more items were checked as risky
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Table 3. Proportion of between-countries variation remaining after controlling for over-all level of tendency to check items as risky.
Product category
Proportion remaining
Pesticides or herbicides
0.39
Bleach and heavy duty cleaners
0.40
Bathroom cleaners
0.23
Hair dyes
Interior paints
0.71
Timber preservatives
0.58
Laundry or dishwashing detergents
0.51
Washing powder
0.45
Fabrics: Synthetic fibers
0.27
Sunscreens
0.13
Hair shampoo
0.26
Fabrics: Wool cotton or linen
0.60
Toothpaste
0.31
Mean
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Comments
Most variation among countries – 60 % - is on the average due to the level of responding
In some cases there is additional variation among contries:
Interior paints
Timber preservatives
Laundry or dishwashing detergents
Fabrics of wool, cotton or linen
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Summary Question 1
The items seen as most risky were pesticides/herbicides and cleaners, while toothpaste, fabrics and sunscreens were relatively seldom checked as risky
There were large differences among countries in level of perceived riskiness, but strong intercorrelations implying very similar rank orders, and a tendency towards three clusters of nations
The distribution of the index of perceived risk was multimodal, with most people checking no or very few items and a subgroup checking many items
Women had a higher level of perceived risk than men, but women and men had similar rank orders of items with regard to risk
The youngest and oldest age groups had a lower level of perceived risk than others
Higher education was associated with perceiving more items as risky, especially among women
Leftist political preferences were associated with checking more items as risky
In households with more children, more items were checked as risky
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Comments
Gender differences as expected
Personal risk smaller than general risk, expected
Age effects similar but weaker compared to Question 1 results
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Table 9. Results of fitting regression models to the perceived risk of fabrics, standardized regression weights and adjusted proportion of variance accounted for.
Regression weights
Adjusted R2
Gender
Age
Worry
Trust
Risk sensitivity
Wool, cotton, linen
-0.016
-0.029
0.214
0.043
0.325
0.215
Synthetic fibers
0.031
0.029
0.316
-0.073
0.350
0.332
Labelled as safe
-0.006
0.019
0.114
0.490
0.313
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25. Correlation between risk and trust Hair dyes, general risk -0.098
Table 6. Correlations between trust and perceived risk at the individual level.
Risk
Correlation between risk and trust
Hair dyes, general risk
-0.098
Fabrics, general risk
-0.089
Sunscreens, general risk
-0.092
Cleaning products, general risk
-0.124
Hair dayes, personal risk
-0.054
Fabrics, personal risk
-0.074
Sunscreens, personal risk
-0.064
Cleaning products, personal risk
-0.110
Wool, cotton or linen textiles, personal risk
-0.008
Synthetic fibers, personal risk
-0.091
Fabrics with quality labels, personal risk
-0.057
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Table 7. Response distributions in percent, all respondents, to statements about he quality of information about chemical substances in consumer products. (DK answers deleted).
1 = Totally dis-agree 2 3 4 5 6
7 = Totally agree
Instructions and labels are hard to understand 9 11 13 17 18 19
The industry is doing everything to inform clearly and precisely 20 15 7
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Discussion 1
The concept of chemicals
Natural vs man-made
Smell and taste
Known to be poisonous
Familiarity
Health promoting
Media interest
Environmental impact
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Discussion 2
Personal risk vs general risk: control?
Level of education unexpected results, note the wording of Question 1: ”according to what you know”…
Models of risk perception suggest that several factors were not covered
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Discussion 3
Dissatisfaction with available information
Suspicion towards industry, but low social trust over-all
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Further research
The risk perception models indicate that more independent variables are needed
Data on epistemic, not only social trust
Data on perceived control: can you protect yourself from some or all chemical risks by means of prudent behaviour?
More direct measurement of beliefs about the dose-response relationship (intuitive toxicology)
Exploring the concept of “chemicals”: what are they, how can they affect your body and your health, with different types of consumer products, and what are the pertinent risk dimensions (such as interfering with Nature)?
More data on policy attitudes: not only blame and responsibility but also demand for mitigation
More data on emotional reactions, both negative and positive
Consideration of the need for more and more accessible information: what do people really want and how can they use it?
Data on a few other types of risk in order to get a “benchmark” to compare with and get some idea about the level of perceived risk in relation to other “typical” risks
A focus on practical application to risk communication would be helped by information about the problems of risk communication regarding chemicals in consumer products: what is the experience of practitioners in industry and government, what previous attempts (successful or failures) have been documented in research or otherwise?
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Further information about my research can be found at
Lennart Sjöberg June 2009 Ispra meeting