Jorge ; Arana

Quantitative Methods, D62 -Externalities < D6 -Welfare Economics < D -Microeconomics, Q51 -Valuation of Environmental Effects < Q5 -Environmental Economics < Q -Agricultural and Natural Resource Economics

Keywords: Environmental risks, Probability neglect, Embedding, Anchoring Anchoring vignettes, Environmental risks, Embedding, Probability neglect, Measurement scales, Money, Willingness to pay

The valuation of environmental risks is commonly approached with the utilization of stated preference methods such as contingent valuation. In these methods, money is utilized as the scale that reflects the individual's underlying utility function. However, this scale can vary across individuals due to different perceptions on what are the right or appropriate bounds for willingness to pay. In this paper we test for scale perception bias and propose a correction method based on the utilization of anchoring vignettes that define different degrees of preference for the non-market good. The proposed method is applied to study the commonly found anomaly "probability neglect", which is defined by the insensitivity to the probability levels in the valuation of environmental risks. The results show that probability neglect disappears when willingness to pay responses are corrected for self-perception bias through the utilization of the anchoring vignettes approach.

Introduction

The measurement of environmental benefits is commonly approached with stated preference methods, such as contingent valuation (CVM). This method is based on the utilization of structured survey questionnaires to elicit from individuals their maximum willingness to pay (WTP) for some policy proposal about a well defined environmental good (e.g. [START_REF] Bateman | Valuing Environmental Preferences: theory and practice of the contingent valuation method in the US, EU, and developing countries[END_REF]). The central element of stated preference methods is the utilization of money as the utility measurement rod under the assumption that it should reflect the underlying change in individual's utility.

However, some authors such as [START_REF] Kahneman | Fairness as a Constraint on Profit Seeking: Entitlements in the Market. Elgar Reference Collection[END_REF] and [START_REF] Kahneman | Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias. Elgar Reference Collection[END_REF] have pointed out that the reliance on money to approximate subjective utility raises some problems, because answers based on money might be subject to potential biases (e.g. the scope insensitivity effect, anchoring effects, warm glow), which could lead to unreliable results. The cumulative set of anomalies and potential mishaps performed by CVM led [START_REF] Kahneman | Experienced utility as a standard of policy evaluation[END_REF] to conclude that contingent valuation questions tend to elicit attitudes rather than preferences. The main difference between preferences and attitudes lies in the fact that while the logic of preference assumes extensionality, the logic of attitudes do not 1 . These authors argue that CVM responses are made without a "modulus" 2 or a standard, and it is the absence of modulus what induce unreliable responses and anomalies such as the anchoring effects found by [START_REF] Ariely | Coherent Arbitrariness: Stable Demand Curves Without Stable Preferences[END_REF] by recalling the social security number on respondents.

1 More concisesly, [START_REF] Kahneman | Experienced utility as a standard of policy evaluation[END_REF] claim that "we have attitudes to many things that we don't have any reason to have preferences about because they are not choices that we could ever have to make". Therefore, these authors claim that this is problematic for the use of contingent valuation to inform public policy, since some of the common anomalies that are found in responses to contingent valuation surveys (i.e. framing and context effects) can be attributed to the fact that the logic of preferences assumes extensibility while the logic of attitudes do not guarantee such property. 2 A "modulus" in a scale development can be formally defined as a certain value that is clearly identified and considered as the reference point to relatively place (i.e. valuate) any objet in the scale. See [START_REF] Hsee | Sun and Water: On a Modulus-Based Measurement of Happiness[END_REF] for a nice review. The absence of a "modulus" or standard in CVM responses could lead to the fact that the monetary measurement scale can be subjectively interpreted across groups of individuals. It is well known that respondents to contingent valuation surveys often understand the same survey question differently. That may be especially true for the more abstract concepts of interest to environmental economists, such as sustainable development or environmental quality perception. A policy that clearly leads to "average environmental quality" to one respondent could lead to "very high environmental quality" to another and "poor environmental quality" to a third. This inter-personal incomparability potentially poses a non-trivial threat to the conclusions drawn from survey questions applied in heterogeneous populations. Seemingly important inter-group differences in survey responses could, in fact, reflect differences in question interpretation. The implication is that it would be useful to correct for these differences in the perception of the monetary scale, in order to harmonise answers across respondents. In this paper we propose a method for correcting individual heterogeneity in the perception of the monetary scale.

To attempt to ameliorate this problem, researchers have developed the technique of anchoring vignettes [START_REF] King | Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research[END_REF][START_REF] King | Comparing Incomparable Survey Responses: New Tools for Anchoring Vignettes[END_REF][START_REF] Wand | Credible Comparisons Using Interpersonally Incomparable Data: Ranking Self-Evaluations Relative to Anchoring Vignettes or Other Common Survey Questions[END_REF], Soest et al. 2007). After a standard willingness to pay question, the survey respondent learns about hypothetical individuals through brief vignettes and is asked to place those individuals on the same response scale. Variation in vignette responses across individuals reveals interpersonal incomparability and enables researchers to use one of several statistical techniques to rescale the respondent's own willingness to pay. As it has been shown in previous literature, when applied correctly, the technique can greatly increase the comparability in survey responses (Grzymala-Busse 2007, Kristensen and Johansson, Buckley 2008, Kapteyn, Smith, and Soest 2007, Soest et al. 2007[START_REF] King | Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research[END_REF], Salomon, Tan-don, and Murray 2004[START_REF] Damacena | Perception of Health State and the Use of Vignettes to Calibrate for Socioeconomic Status: Results of the World Health Survey in Brazil, 2003[END_REF][START_REF] Javaras | An 'Unfolding' Latent Variable Model for Likert Attitude Data: Drawing Inferences Adjusted for Response Style[END_REF][START_REF] Hsee | Sun and Water: On a Modulus-Based Measurement of Happiness[END_REF][START_REF] Javaras | Co-occurrence of Binge Eating Disorder with Psychiatric and Medical Disorders[END_REF], Datta Gupta et al., 2010, Vonkova and Hullegie, 2010, Baggo D'Uva et. al, 2007, among many others).

Following the approach developed by [START_REF] King | Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research[END_REF] for qualitative survey responses, a normalization of the WTP responses across individuals can be obtained by questioning them about hypothetical anchoring vignettes or profiles, which are intended to obtain the implicit anchors of the potential range of the WTP responses. The idea behind this method is that respondents, in addition to stating how much are they willing to pay for an specific environmental policy, are asked to evaluate, on the same scale, how much they think that a set of hypothetical persons (vignettes) are willing to pay for the same policy. This information is then used to rescale individuals' evaluation of the environmental policy at hand, using a joint model for the willingness to pay questions and the vignettes. Thus, if one particular subgroup of the population, systematically gives higher valuations of hypothetical vignettes compared to other subgroups that rank the exact same hypothetical vignettes, this would indicate that differences in willingness to pay are due to cultural differences in evaluating such subjective questions and not due to stronger preferences for the policy project under study.

On the other hand, it is important to notice that scale perception bias is not simply reflecting heterogeneity in respondents' preferences. Moreover, it does consider heterogeneity in the definition of the appropriate scale of the money metric across This type of bias could be related to other anomalies commonly encountered with monetary scales, such as the anchoring effects or the scope bias.

Thus, the scale-perception of what would be the right scale range and intensity for the measurement rod utilized in the valuation of environmental goods, could lead to individual responses which are not directly comparable, unless some corrections are made for the anchor or scale effects. For instance, for some individuals the maximum WTP of an individual with a strong preference for an environmental policy -given income and other socioeconomic parameters-could be 1000 €, and for other individuals this could be 300 €. Thus, each subject could base her responses on a different monetary scale leading to a scale-perception or assessment bias that could be corrected by deriving a homogeneous scale across individuals.

The main finding of this research is the fact that probability neglect disappears when the scale perception bias is accounted for. In other words, the correction for monetary scale perception bias leads to a more accurate approximation to individual utility, and provides a new way to challenge the potential anomalies commonly encountered in CVM, such as the scope effect. This type of effect is due to the fact that subjects might not be sensitive to the dimensions of the good to be valued. In this paper, we focus on a particular type of scope effect that might be found in the valuation of environmental risks, in what is also named "probability neglect" [START_REF] Sunstein | Terrorism and Probability Neglect[END_REF]). This follows from the fact that individuals might not be sensitive to the level of risks (e.g. [START_REF] Kunreuther | Making Low Probabilities Useful[END_REF], [START_REF] Loewenstein | Collateral Damage[END_REF], [START_REF] Slovic | Rational Actors or Rational Fools: Implications of the Affect Heuristic for Behavioral Economics[END_REF]). For instance, if some measure is undertaken to reduce the health risks across the population, then subjects could respond the same monetary quantity regarding the extent of risk reduction. There can be various reasons for this response, for example, just because any small amount of risk is considered unacceptable, or because respondents are unable to discriminate between different risk levels in monetary terms. In any case, the amount of risk posed to the subject does not have an impact on the monetary scale although she might value different levels of risk reduction differently, according to her underlying and informed preferences.

The paper is organized as follows. In the next section we present the application and the methods of anchoring vignettes utilized to elicit individuals valuations in the context of a CVM survey. The application focuses on the evaluation of the reduction in the environmental risks associated with the utilization of pesticides in agricultural products.

Section 3 presents the econometric approaches to model the normalization approach to rescaling the elicited individual values utilizing the methodology of anchoring vignettes presented in the previous section. Section 4 presents and discuses the results of the anchoring vignettes model, the correction of WTP for scale-perception bias and the test validity of the scope or probability neglect effect. Finally, section 5 presents the main conclusions and implications for future research. Individuals were posed with a policy proposal intended to enforce the adoption of sound management practices in agricultural production that would reduce the risks to environmental assets. It was remarked that agricultural production could cause several external effects on the environment because of the intensive use of pesticides and chemical fertilizers. The policy measures would reduce the amount of these substances towards a level that would reduce the risk of damage to soil and ecosystems.

Data and methods

F

The final sample included 525 subjects that were randomly selected from the sample population. The sample was representative of the population of the Canary Islands with a post sampling error of 4.3 %. In order to maximize sample representativeness, an ad hoc polietapic sampling design was implemented. This process was tested successfully in previous socioeconomic research for the same target population. The carefully designed random routes along islands, regions, cities and neighbourhoods were fixed by using sampling quotas for the most relevant demographic covariates. In order to test for the scope insensitivity effect or probability neglect, the final sample was split in three subsamples characterized by three alternative levels of risk reduction: 10%, 50% and 90%. Probability neglect would imply that WTP was insensitive to the amount of environmental risk reduction. In strict terms, this hypothesis could be attributed to the 8 fact that individuals would care only about the presence of risk but not about its magnitude. However, focus group results revealed that the amount of risk made a difference in subject's response to WTP as framed in a hypothetical market context. Thus, there might be a case for investigating the results with split samples in order to study if scope insensitivity is really an issue in the valuation of environmental risks.

The elicitation method was the dichotomous choice format. This involved a single binary yes/no WTP question to a bid price previously selected from a bid vector. The bid vector was designed following [START_REF] Cooper | Optimal bid selection for dichotomous contingent valuation surveys[END_REF] optimal bid design procedure for a pre-determined number of bids, and using information from the open ended results in the pre-test survey. Each subject received randomly one of the prices in the bid vector and was asked for a yes/no answer. 10% of subjects opted for declining any response because they did not know and could not formulate an answer, and were therefore excluded from the sample. Therefore, the response rate was of 90 %.

Each subject was asked about her own self-assessment and about the assessment of hypothetical profiles or anchoring vignettes. These vignettes were studied in focus groups and were defined by individuals with different degrees of preferences toward the policy proposal, and depending on specific characteristics3 . A crucial assumption of the anchoring vignettes model is the fact that there might be no "self-others gap", that is, responses to vignettes are evaluated under the same frame and preference structures as self-responses [START_REF] King | Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research[END_REF]. In other words, responses to vignettes should represent different values but from the same preferences distribution. In the preliminary studies of this research (focus groups, pre-tests, experts' interview, …) we observed that, for this F o r P e e r R e v i e w specific valuation scenario, after 4 vignettes respondents presented some fatigue and reported answers were less likely to come from the same distribution. For that reason, we decided to ask for 4 vignettes since, for our application at hand, they seem to provide the maximum amount of information to correct for scale bias that respondents may manage with average cognitive abilities. These four different profiles presented were described as follows:

[Ann] is very worried about the environment when taking shopping decisions. She always shops in organic foods markets and is very concerned about the production techniques involved in raising fruits and vegetables. She never eats food with artificial ingredients which could damage the environment.

[Michael] is just average worried about the environmental impact of agricultural food production. As much as he can, he avoids eating food with dubious origin, and although this is not a priority, in the weekends he uses to shop in ordinary markets where there is traceability of the agricultural products.

[Richard] does not believe all the predictions by experts about the impact of food production on the environment, and thinks that the benefits generated by those practices which are characterized as environmentally unfriendly techniques overcome the potential damages to environmental assets.

[John] is not concerned about environmental assets at all and does not think that food production in the current state is causing damage to the environment in any way. Even if damage is caused, he would not care about it. His main priority is cheap food since when he shops for food the most important issue is the price.

Following the description of each profile, each individual was asked to assess the potential response of the individual described in the hypothetical profile to the risk reduction policy measure using a binary response WTP question to a bid price randomly taken from a pre-designed bid vector. These bid price vectors for the hypothetical profiles were designed in a similar way to the one employed for the self-assessment question, i.e. utilizing [START_REF] Cooper | Optimal bid selection for dichotomous contingent valuation surveys[END_REF] Individuals i and j respond differently to the maximum WTP assessment for the individual with the most favourable preference for the policy proposal, i.e. as described in profile for Ann (WTP j MAX > WTP i MAX ). Accordingly, it seems that individual j values more the policy proposal than individual i, as can be appreciated by the fact that WTP j > WTP i . The normalization of the differences in the use of the scale can be done

Modelling approach

The model for accounting for the impact of anchoring vignettes in the correction of scale perception bias could be based on a simultaneous equation approach. The dichotomous choice elicitation process involves a "yes/no" response to a bid price, which is posed by the individual in each vignette assessment as well as in her own assessment. Following [START_REF] Cameron | A New Paradigm for Valuing Non-market Goods Using Referendum Data: Maximum Likelihood Estimation by Censored Logistic Regression[END_REF] parameterization5 , we assume that the latent variable willingness to pay (WTP) has two components: a deterministic component µ and a random component ε. Thus, for each j assessment (own and others), we can define willingness to pay as the following:

j i j j i ε σ µ + = j i

WTP

, where j i µ and j σ are, respectively, the mean and the standard deviation of WTP j ; j=0 for the self-assessment WTP and j i ε is a random error term, which is assumed to follow a standard normal distribution.

For each vignette, the respondent is asked to pay a given amount of money (B j : j=1,2,...J). The interdependencies across the responses to self and others assessments of WTP can be modelled using a simultaneous equations with limited dependent variables (SLDV) approach. This approach reduces to a general triangular system [START_REF] Zellner | Introduction to Bayesian Inference in Econometrics[END_REF] for complete data sets. The equations are the following:

F o r P e e r R e v i e w 12 1 1 1 i i i WTP ε µ + = 2 2 2 i i i WTP ε µ + = 3 3 3 i i i WTP ε µ + = 1 4 4 i i i WTP ε µ + = 5 4 4 3 3 2 2 1 1 5 5 ... i i i WTP WTP WTP WTP WTP ε η η η η µ + + + + + =
(1) and ( ) Given the calculation of multiple integrals in the likelihood function for the model, estimation using full information maximum likelihood methods is generally avoided in favour of less efficient (but computationally simpler) estimation procedures, such as two-step algorithms (see [START_REF] Blundell | Coherency and Estimation in Simultaneous Models with Censoring and Qualitative Dependent Variables[END_REF]. On the other hand, by definition, the asymptotic properties of classical estimators are not guaranteed in small and finite A Bayesian approach obtains exact results in these cases, while at the same time allows for simple estimation procedures. Our approach is an extension of Li's (1998) approach for SLDV models and [START_REF] Araña | Willingness to pay for Health Risk Reduction in the Context of altruism[END_REF] methodology for DC1, which are based upon the framework introduced by [START_REF] Chib | Bayes Inference in the Tobit Censored Regression Model[END_REF] and [START_REF] Albert | Bayesian Analysis of Binary and Polichotomous Response Data[END_REF].

5 2 1 ,... , i i i ε ε ε ~( ) Σ , 0 5 MVN and                 = Σ

Results

An important element in testing for the reliability of the monetary scale as an instrument for measuring environmental risks involves the consideration of the sensitivity of the responses to the amount of risks involved. Probability neglect follows from the fact that individual responses in the market construct are not sensitive to the amount of risks, while market evidence shows that this is not necessarily the case. This might happen to be the situation for the application involving the amount of environmental risk reduction attributed to unsound production practices utilized in agriculture. These practices can have relevant impacts on the environment, and there is both non-market and market evidence that shows that individuals choose consumption according to their perception of the associated environmental effects. For a nice review of probability neglect and key references see for instance [START_REF] Sunstein | Terrorism and Probability Neglect[END_REF].

In order to test in a non-market context for the hypothesis of probability neglect associated with environmental risks due to agricultural production, we can conduct a regression analysis. As explained in the previous section, for convenience and easiness of interpretation, we follow [START_REF] Cameron | A New Paradigm for Valuing Non-market Goods Using Referendum Data: Maximum Likelihood Estimation by Censored Logistic Regression[END_REF] [START_REF] Hanemann | Welfare Evaluations in contingent valuation experiments with discrete responses[END_REF]. Table 1 displays the definition of the variables which were significant covariates in explaining WTP. Some other attitudinal variables were considered for the incorporation in the regression results, but showed weak significance in the context of the full regression model.

Table 2 presents the estimation results for the standard WTP regression model, i.e. without the consideration of the impact of anchoring vignettes, and for the model incorporating the effects of anchoring vignettes. These models have been estimated by maximum likelihood. The model with anchoring vignettes is a single equation model, which consists of the incorporation of the yes/no responses to the hypothetical vignettes as explanatory variables of the individual WTP. The socioeconomic variables of income and education make a positive contribution to mean WTP and are highly significant in explaining the elicited values with both models, while the health status of the individual also shows a positive sign and is significant at the 95% level. WTP is also larger for those individuals who use to eat substantial amounts of fresh food in their daily diet.

The model with anchoring vignettes in Table 2 shows that some of the assessments of the potential responses of the hypothetical individuals are significant explanatory variables of WTP. This is the case for WTP2 and WTP4, i.e. for those individuals representing a moderate environmental preference [Michael] and a complete absence of environmental concern [John], respectively. The results are not significant for the alternative two vignettes.

The significant impact of others assessments on the self individual assessment can be taken as evidence of the presence of a relationship between the vignettes and WTP. That The hypothesis of probability neglect in the context of the valuation of environmental risks cannot be rejected for the standard model in Table 2, since the dummy variables RISK50 and RISK90 are not significant. That is, individual responses are not sensitive to the amount of environmental risks, in what can be interpreted as giving support to the embedding or scope effect. However, the results are more challenging when considering the incorporation of anchoring vignettes in model M2. It can be seen that both risk levels have a positive impact on WTP. This indicates that risk levels can have a positive effect when anchoring effects are consequently incorporated into the model, thereby correcting for unobserved anchors or scale bias. Thus, the result of probability neglect with the traditional model can be attributed to the presence of self perception bias in the use of the monetary scale across groups of individuals. The mean WTP estimated for each type of model and risk level are presented in Table 3. The results confirm the relevance of the anchoring vignettes as was showed with the estimated WTP functions in Table 2. That is, WTP is not significantly different for model M1 across the risk levels of environmental risk, thereby it shows embedding or probably neglect effects. However, when anchoring vignettes are considered for the correction of self perception bias, the results show that WTP increases when the level of environmental risk is increased. Individuals are willing to pay higher amounts of money for agricultural production policies that enforce less risk of damage to the natural environment. The fact that the impact of implicit anchors on the individual's measurement scale does not allow to obtain this result for the standard model raises concerns about the standard approach to test for embedding effects and other anomalies encountered in non-market valuation.

The results in Table 2 for the anchoring vignette model follow from a simple modelling approach which incorporates the vignette responses as explanatory variables. However, these results could be biased because of the endogenous bias following from the fact that the responses to the anchoring vignette situations are also endogenous variables, and therefore should be modelled accordingly. This is done following the model procedures outlined above, by the consideration of a simultaneous equation approach in which each of the anchoring vignette responses is modelled with an independent equation together with the equation explaining the individual's self assessment response.

The results for the simultaneous equation modelling approach are presented in Table 4.

The correlation coefficients across the responses of anchoring vignettes show a large value and are all significantly different from zero. The correction for endogenous bias certainly increases the significance of the anchoring vignette responses on WTP. Thus, the hypothesis of the utilization of a homogeneous scale monetary metric across the sample is rejected. Each individual clearly perceives a particularly personalized scale on which to base herself and others assessments of the WTP for the reduction of environmental risks caused by agricultural production. It can be seen that the hypothesis of probability neglect is also rejected, since monetary valuation, when corrected for scale perception bias, is sensitive to the variation in the risk reduction levels.

Conclusions

Contingent valuation and stated preference methods rely on the utilization of the money metric for the identification of individual preferences for environmental goods. There is a vast amount of research which indicates that this metric can be subject to important anomalies with respect to the theoretical precepts of consumer theory. This might call for alternative ways of eliciting individual preferences which bypass the encountered anomalies.

In this paper we have considered the issue of the impact of unobserved anchors in the monetary scale of WTP, and have developed a method for correcting for these anchors utilizing the individual assessment of others responses as described by characters described in hypothetical vignettes. It is a maintained hypothesis sustained by a large body of research that individuals might care about the behaviour of other individuals with similar or different degrees of preferences for a public or a private good. In Nevertheless, the differences in using the monetary scale metric across individuals can be also attributed to the impact of some elements of the market construct, such as the payment vehicle of the information content, which can be subjectively interpreted by the respondents. More generally, cognitive and emotional processes can also play a relevant role in the differences of the response scales across individuals in survey research.

The utilization of anchoring vignettes in surveys can allow for the normalization of subjective responses across the sample of respondents. In these vignettes the individuals are asked to assess the potential response of individuals with different degrees of preference for the environmental policy proposal, given the same income level and socioeconomic characteristics. We have developed an econometric approach for the correction of the self perception bias based on the utilization of a simultaneous equation model which takes into account of the impact of anchoring vignette responses on individual willingness to pay.

The performance of the technique of anchoring vignettes for correcting self perception bias with respect to the scale measure can be assessed with the investigation of the potential anomalies commonly encountered in contingent valuation and stated preference methods. We have considered the impact of probability neglect, which is one of the most important anomalies for which direct non-market valuation methods are criticised. Probability neglect follows from the fact that individuals are not sensitive to the levels of risk defined in a risk policy for ameliorating environmental risks. In this Our results have shown that the phenomenon of probability neglect with respect to a policy proposal for the reduction of the environmental risks caused by agricultural production is present with standard valuation methods. However, when the responses are corrected for self perception bias in the utilization of the measurement scale the results show that individuals are concerned with the level of risks, and that WTP rises significantly with the amount of environmental risk reduction.

There is a large research schedule emerging from the results and the approach put forward in this paper. First, further research should investigate more closely the impact and implications of self perception bias and the utilization of different monetary scales across individuals, both theoretically and empirically. Second, the potential anomalies of stated preference methods can be also revised for the correction of self perception bias utilizing the scale correction methods of anchoring vignettes. Third, although WTP for health risk reduction is expected to change proportionally with changes in risk according to the expected utility model, this may not be the case in other models of behaviour under risk in which cumulative probabilities are transformed in decision weights, such as prospect or rank-dependent utility theories [START_REF] Hammitt | Willingness to Pay for Health Protection: Inadequate Sensitivity to Probability?[END_REF]Graham, 1999, Botzen andvan der Bergh, 2009). These alternative interpretations of behaviour under different risk conditions may be wroth to explore be in future contingent

  a bias that can be defined as a scale-perception bias. This bias is due to the fact that individuals might hold a subjective perception of what should be the WTP responses (or non-monetary scale level) of identical individuals but with varying strengths of preference for an environmental good or policy proposal. In the context of contingent valuation, scale-perception bias is a measurement bias, which is induced by the different anchoring points that individuals have about the potential range of WTP.

  on the valuation of the reduction of environmental risks caused by the adoption of sound management practices in agricultural production. A CV survey was conducted in the Canary Islands (Spain) in the summer of 2005. A pre-test survey involving 70 subjects and two focus groups allowed us to define the critical elements of the scenario, such as the amount and type of information, the payment vehicle and the plausibility of the policy proposal.

  methods based on information from the open-test sample and focus groups.4 Also, and in order to avoid order effects, vignettes were presented randomly to each respondent. Our results show that this procedure ameliorates the potential influence of first vignette responses on the followup questions and potential center-seeking biases.The response to these anchoring vignettes can be utilized for the correction of potential scale perception bias which could follow by the fact that otherwise identical individual with similar preferences could value differently the same environmental good because of a different use of the money metric implicit in the valuation.A simple way of correcting for scale bias involves a re-escalation of the individual responses by reparametrization. Figure1illustrates the idea of the correction of self perception bias for the case of WTP responses to a hypothetical open ended question.

  by harmonizing WTP MAX across individuals. The ending result would be that individual B would value the policy proposal in a larger monetary amount than individual A.Thus, the utilization of anchoring vignettes can become a powerful tool for correcting the influence of unobserved anchors heterogeneity distributed across the target population. Individual survey responses can vary because of the utilization of different cues or anchors, which can be attributed to cognitive, emotional or cultural differences, personalized influence of the elements considered in the survey instrument. For the dichotomous choice format, the incorporation of the anchoring vignette responses into the individual monetary valuation involves a simultaneous equation model which is presented in the next section.

  individuals own WTP and WTP1, …, WTP4 represents others WTTP. On the other hand, vector k i µ (k=1,2,...5) represent the mean of WTP k and are linked to the probability of a positive response by a multivariate normal cumulative distribution (MVN), also known as the "link" function. These link functions can be made dependent on a set of explanatory variables or covariates. Simultaneity in the response effects across anchoring vignettes is captured by the lower triangular components of the symmetric matrix Σ ( 1

  parameterization of a binary response can be seen as equivalent to the discrete choice alternative based on

  monetary scales utilized by individuals when grading different degrees of preference for an environmental good are not equal across the sample. The overall implication is that there could be individuals with identical socioeconomic variables who rate differently the expected monetary value of various degrees of preference for the reduction of the environmental risks caused by agricultural production.Therefore, the results support the evidence of the hypothesis of scale perception effect or bias, which follows from the fact that individuals employ different comparative scales consistent with a common monetary metric. The use of different monetary scales across individuals can be due to the implicit anchors to be present in the subjective mind when answering monetary valuation questions. It can also reflect the impacts across groups of individual responses of other elements of the market construct, such as the hypothetical context effect, yea saying, implicit cues, cognitive processes and affective reactions.

  tend to use the monetary measures according to their specific perception of the impact of the proposed policy on their subjective well-being.

  neglect for risk assessment is similar to the embedding or scope effect encountered in the valuation of other types of non-market goods.

  valuation studies. A final line of further research could follow from the investigation of the cognitive and affective processes leading to anchoring behaviour in individuals' decisions. From a more technical point of view, new research might contribute to define and to what extent this approach can be helpful in measuring social preferences in more "complicated" contexts (e.g. high emotional, unfamiliarity).

  Figure1

Table 1 . Description of variables

 1

	Variables	Description

Table 2 .

 2 WTP functions with and without anchoring vignettes information. (t-student in parentheses)

		M1 model		M2 model
	Variables	Standard		Anchoring vignettes I
		Parameters Elasticities* Parameters	Elasticities*
	Intercept	-1.31	-	-11.98**	-
		(-0.22)		(-2.45)
	HS2	8.87** (3.15)	1.67	6.05** (2.94)	1.49
	HS3	7.93** (3.81)	1.49	7.12** (3.56)	1.33
	HS4	9.45** (3.02)	2.83	7.83** (2.41)	1.76
	HS5	9.13** (4.18)	2.47	6.98** (2.95)	1.66
	HS6	7.12** (3.11)	1.52	6.27** (3.73)	1.39
	FRESHF	(2.5) 2.44**	0.63	(-0.93) -8.45**	-1.12
	HRISKAT	4.59**	1.27	4.62**	1.36
		(1.3)		(1.51)
	INC	4.22**	4.52	2.81**	2.15
		(4.18)		(3.67)
	EDUC	(5.07) 0.83**	1.70	(1.85) 0.32	0.67
	RISK50	(1.12) 2.31**	0.43	(2.21) 5.19*	0.79
	RISK90	(0.93) 3.91**	0.36	(3.37) 10.85**	1.85
	WTP1	-	-	(0.95) 17.32	3.83
	WTP2	-	-	(2.47) 3.85**	2.12
	WTP3	-	-	(-0.35) -11.31	-3.15
	WTP4	-	-	(2.46) 6.29**	2.85
	σ	(21.42) 13.44**	-	(24.85) 16.31**	-
	N	525	-	525	-
	Log L	-471.11	-	-408.61	-
	The reference class is RISK10. Elasticities are calculated for averagee values of
	variables.

Table 3 .

 3 Mean WTP and mean attitude scale for alternative risk reduction programs. (95% confidence intervals in brackets)

			Probability Reduction
		10 %	50 %	90 %
	M1 Mean WTP	17.36 (4.04)	18.85 (3.94)	21.15 (4.23)
	M2 Mean WTP	11.75 (3.12)	15.37 (3.09)	23.54 (4.85)

Table 4 .

 4 Results of the anchoring vignettes system of equations model.

	Estimated equations

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

We also conducted individualized think-allowed experiments, which showed support for the hypothesis that individuals use to reflect about what would be the right amount to pay for the policy proposal and what would other individuals respond to the same question.

The particular bid offered in eacg sploit sample were 12, 24, 36 annd

euros. Page 11 of 27 Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript

[START_REF] Cameron | A New Paradigm for Valuing Non-market Goods Using Referendum Data: Maximum Likelihood Estimation by Censored Logistic Regression[END_REF] approach has the advantage of its easiness of interpretation. Alternatively, it can be used the random utility approach by[START_REF] Hanemann | Welfare Evaluations in contingent valuation experiments with discrete responses[END_REF].

Attitudinal questions asked the following: In a scale (1-5) where 1 is no concern at all and 5 is very concerned, how much are you concern with the following issues that may affect your health status?. The variables were i) living close to industrial companies; ii) smoking; iii) contaminated air; iv) genetic modified food; v) food with pesticides.

Editorial Office, Dept of Economics, Warwick University, Coventry CV4 7AL, UK Submitted Manuscript


domain: math info

text:
Germán Cano-Sancho

Jean-Pierre Gauchi

Vicent Sanchis

Sonia Marín

Antonio J Ramos

G Cano-Sancho

J.-P Gauchi

German Cano-Sancho

Quantitative Dietary Exposure Assessment of the Catalonian Population (Spain) to the Mycotoxin Deoxynivalenol

Keywords: prob modelling, Risk assessment, Total diet studies Mycotoxins -trichothecenes Food Types: Cereals, Bread, Baby food, Beer Risk assessment, exposure, deoxynivalenol, cereal food

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

The mycotoxin deoxynivalenol (DON) is one of the most common contaminants of cereals worldwide, and its occurrence has been widely reported in raw foods and foodstuffs, around the European region, including Catalonia. In the present work, a stochastic methodology has been applied to accurately assess the exposure of the Catalonian population (Spain) to DON through food consumption. Raw contamination data was provided by a large survey conducted in this region, in addition to the raw consumption data from a nutritional study specifically designed to assess the dietary intake of the main foodstuffs related to DON contamination for all population age groups. Contamination and consumption data were combined by simulation using an essentially parametric (P-P) method. The P-P method draws sampling values from distribution functions fitted to consumption and contamination datasets. Moreover, to quantify the accuracy and reliability of the statistics estimates, we built the related confidence intervals using a Pseudo-Parametric bootstrap method. Considering the results drawn from methodology has been applied to accurately assess the exposure of the Catalonian population (Spain) to DON through food consumption. Raw contamination data was provided by a large survey conducted in this region, in addition to the raw consumption data from a nutritional study specifically designed to assess the dietary intake of the main foodstuffs related to DON contamination for all population age groups. Contamination and consumption data were combined by simulation using an essentially parametric (P-P) method. The P-P method draws sampling values from distribution functions fitted to consumption and contamination datasets.

Moreover, to quantify the accuracy and reliability of the statistics estimates, we built the related confidence intervals using a Pseudo-Parametric bootstrap method. Considering the

Introduction

Trichothecenes are a family of related cyclic sesquiterpenoids, which are divided into four groups (types A-D) according to their characteristic functional groups, the type A and B being the most common. Type A is represented by HT-2 toxin (HT2) and T-2 toxin (T2) and type B is most frequently represented by deoxynivalenol (DON). Trichothecenes are produced in several cereals by species of Fusarium, thus a wide range of cereal-based foods have been reported to be contaminated by these toxins (JECFA 2001), DON being one of the most common contaminants of cereals worldwide [START_REF] Jelinek | Worldwide occurrence of mycotoxins in foods and feeds-an update[END_REF][START_REF] Scott | Trichothecene Mycotoxicosis: Pathophysiologic Effects[END_REF].

Acute effects of food poisoning by DON in humans are abdominal pains, dizziness, headache, throat irritation, nausea, vomiting, diarrhoea, and blood in stool [START_REF] Rotter | Toxicology of deoxynivalenol (vomitoxin)[END_REF]. A tolerable daily intake (TDI) of 1 µg/kg body weight based on a reduction of body weight gain was established by the EC SCF (SCF 2002).

Occurrence of DON has been widely reported in raw foods and foodstuffs in European countries (JECFA 2001), confirming that food processing methods do not completely remove mycotoxins [START_REF] Hazel | Influence of processing on trichothecene levels[END_REF]. The presence of trichothecenes in Catalonia (Spain) has been recently studied by means of a thorough methodology involving a large sampling and accurate chemical analysis. That study concluded that the occurrence of DON was high in [START_REF] Cano-Sancho | Presence of trichothecenes and co-occurrence in cereal-based food from Catalonia (Spain)[END_REF]. Cereal-based foods are the base of the energy intake in Catalonia, as well as in the other Mediterranean countries [START_REF] Serra-Majem | Avaluació de l'estat nutricional de la població catalana 2002-2003[END_REF]. Therefore, in the food safety framework, to assess the exposure of Catalonian population to DON is a priority.

To our knowledge, few studies have been published to assess the exposure to DON, and the ones that have been published have generally used deterministic approaches (SCOOP 2003).

Experts have recommended the use of a stochastic approach to provide a more realistic exposure assessment, taking model uncertainties and variability into consideration.

Nevertheless, there is no consensus on which specific methodology should be applied in each case [START_REF] Kroes | Visconti A. Assessment of intake from the diet[END_REF]WHO 2005;EFSA 2006;Verger and Fabiansson 2008). A stochastic methodology was developed by [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF] to assess the exposure of human populations to food contaminants, as in the case of the exposure of the French population to ochratoxin A (OTA). The authors proposed two simulation approaches to estimate the exposure, based on Monte Carlo simulations (using NonParametric-NonParametric and Mixed Parametric-Parametric methods), leading to the assessment of four types of bootstrap confidence intervals. The aim of this paper is to quantitatively assess the exposure of the Catalonian population (Spain) to DON. were obtained in six hypermarkets and supermarkets from twelve main cities (Tortosa, Tarragona, Reus, Vilanova i la Geltrú, l'Hospitalet de Llobregat, Barcelona, Terrassa, Sabadell, Mataró, Girona, Manresa and Lleida) of Catalonia, Spain, representative of 72 % of the population. From each supermarket or hypermarket, 3 items (if present) of each product were randomly taken. The level of trichothecenes was determined in a total of 72 composite samples obtained by pooling the 3 items taken from each store if available (12 cities x 6 stores / city = 72 samples / category). However, in some cases, no items were available in the store, thus, less than 72 composites could be obtained. Finally, a wide range of brands was obtained, which can be considered the majority of market share in Catalonia of these products, as well as in the rest of the Spanish market. Moreover, some commodities were selected because they are highly consumed by some population groups with different dietary patterns: baby foods, ethnic foods and gluten-free foods. DON was determined in breakfast cereals, snacks and pasta samples following extraction, clean-up, derivatization and final analysis by GC-ECD.

Materials and Methods

Raw contamination data

Moreover, this mycotoxin was determined in sliced bread, sweet corn, beer, baby food, ethnic food and gluten-free food by LC-DAD. In this study, non-detected samples were assumed to be equal to the limit of detection (LOD) divided by 2, an assumption widely recognised to reduce the uncertainty of values between 0 and the LOD (GEMs/Food-WHO, 1995). Some statistics from contamination data and the related histograms are shown in Table I andFig Message to the editor: Place Table I andFig Food dietary intake was assessed through a specific Food Frequency Questionnaire (FFQ), developed for the Catalonian population including those foods typically consumed in the region that may be potentially contaminated with these mycotoxins. According to World Health Organization (WHO) recommendations, studies to assess the dietary intake of chemical contaminants should show the significant intake within the standard population, as well as within all population groups that could have different dietary patterns. Therefore, five different age population groups were considered: infants (0-3 years), children (4-9 years), adolescents (10-19 years), adults (20-65 years) and seniors (> 65 years). Moreover, adult celiac sufferers and adults with ethnic dietary pattern were included in the nutritional study, and studied separately. The FFQ included 38 specific food items known to be the major foods contaminated by mycotoxins worldwide, excluding those foods not consumed in the region.

Concerning consumption frequency, five response options, ranging from 'never' to 'annually', according to their sex, with a major population group of 336 adult males and another of 384 adult females. Individuals were from 89 cities and towns from Catalonia. An example of some statistics from the consumption data of adult females and the related histograms is shown in Table II andFig. 2, respectively. They are in the line of those obtained for males. II andFig.2 approximately here. [Table II. Normalised consumption of the main foodstuff related to DON contamination by the

Message to the editor: Place Table

adult females (g kg -1 body weight day -1 ).] [Fig 2. Consumption histograms (relative frequencies) for adult female consumers, in µg kg -1 bw day -1 ]

Dependencies on consumption patterns can be quantified by Spearman correlation coefficients and can be taken into account by the Iman and Conover method [START_REF] Iman | A distribution-free approach to inducing rank correlation among input variables[END_REF]. However, [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF] did not report significant differences in the results, regardless of whether or not dependencies were taken into account. We therefore did not consider dependencies in the present work.

Methodology used to calculate the exposure

In this section we recall some general aspects concerning the exposure calculations, already given in [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF].

The main limitation to estimate the normalised exposure distribution of consumer populations is derived from the equation:

∑ = = p j j j T C E 1 , π π (1)
where the random variable "normalised global exposure in a consumer population π" (E π ) is a function of the random variables: "normalised consumption of the foodstuff j in a consumer 7 population π " (C π, j ) and "DON concentration level of the foodstuff j" ( T j ). The difficulty is due to the probability density functions (pdf) since these variables are generally unknown and even if they are known, they are generally different and not independent. Moreover, the C π, j

x T j pdf products are unknown, too.

If we assume independency between consumption (C π, j ) and contamination (T j ), as well as between their products, we can estimate the mean exposure of the population π with the population sample π 0 as follows:

∑ = = p j j j T C E 1 , 0 0 ˆπ π (2) Where j C , 0 π
is the arithmetical mean of the normalised consumption of the foodstuff j in the population group π 0 , and j T is the arithmetical mean of the available contamination data of the related food.

Under these assumptions we can also calculate the variance estimate

) ( ˆ0 π E V
using Eq. ( 5) and Eq. ( 6) in [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF]. We could consider this approach to be a theoretical approach, but because of the postulated assumptions, it would have to be a (very) simplified theoretical approach. For example, this simplified approach does not enable us to calculate complicated statistics such as high quantiles. Simulation methods would therefore be required to obtain estimates of these statistics. Finally, we will consider this approach to be a direct approach.

Stochastic procedure to calculate the exposure: Parametric-Parametric (P-P) method

In this section we recall some elements of the methodology used to calculate the exposure by means of the stochastic procedure, already given in [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF].

The main advantage of the use of a parametric method is derived from the fact that NonParametric-NonParametric method could lead us to less reliable estimations, especially of [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF]. Taking the asymmetrical appearance of consumption and contamination histograms and our previous experience into account, we fitted the probability density functions, choosing the gamma distribution to be the best candidate. Therefore, for each consumption and contamination dataset, the gamma pdf was fitted with the method of maximum likelihood using the CAPABILITY procedure of SAS software (SAS 2010). The Chi-Square statistic was used in the goodness-of-fit test, considering a significance level greater than 95%, to accept the distribution as a suitable candidate. Moreover, several graphical methods such as quantile-quantile plot exist, making it possible to quickly check if the fitted distribution is adapted to the selected hypothesis [START_REF] Smout | Statistical variability of heat penetration parameters in relation to process design[END_REF]. Shape and scale parameters were estimated for each contamination set, in accordance with the methodology described above.

Concerning consumption datasets, the foodstuffs selected are commonly consumed within the Catalonian population, despite several exceptions related to age-group dietary patterns. The appearance of the histograms is therefore continuous and only one distribution was considered pooling all age groups data, fitting all data to gamma pdf. In case of gluten-free foods, the mean contamination was used in the simulations because few data were available.

The P-P method used to estimate the normalised exposure k of the S simulation set was built as follows:

∑ = - = p j j j i P P k t c E 1 ) ( ] [ ~ (4) where ) ( ~j i c
is a random normalised consumption i for the foodstuff j, drawn from j C ˆ, the corresponding adjusted gamma pdf, and j t ~ is a random contamination for the foodstuff j, drawn from j T ˆ, the corresponding adjusted gamma pdf. The density parameter estimates for j C ˆ and j T ˆ are shown in Table V. The mean of normalised exposures over the simulation set S was then estimated using the following equation, where n was the number of random deviates drawn (10,000 in the present study):

] [ 1 ] [ 1 ˆP P k n k P P S E n E - = - ∑ = (5)
Other statistics were directly computed on the histogram built with the simulations of the S set, and statistics were also estimated from the lognormal and gamma fitted pdfs.

Method to build the bootstrap confidence intervals

To know the validity and accuracy of the high quantiles estimated for the simulation method, the confidence intervals are required. Therefore, this section focuses on building bootstrap confidence intervals in order to determine the reliability of the simulation methods. Several methods to build bootstrap [START_REF] Efron | Guidance of the scientific committee on a request from EFSA related to uncertainties in dietary exposure assessment[END_REF]) confidence intervals (CI b ) were assessed by [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF], revealing the difficulties involved in applying the nonparametric CI b and highlighting the "pseudo-parametric CI b " as the best choice from among the other parametric procedures and analytical methods proposed. We therefore built CI b according to this method.

"Pseudo-parametric CI b ", referred to as Type 1, was built by randomly drawing B samples of size 0 π n in the exposure simulation set S. Typically, B is equal to 10,000

The boundaries of the 95% confidence interval are calculated taking the 0.025 th and 0.975 th empirical quantiles of the final bootstrap distribution. III. They should be compared with the results of the subsequent tables. We observed that they were quite different; the infants and ethnics being the most exposed groups.

Results

Results of the Direct Approach

Message to the editor: Place Table III approximately here (if possible).

[Table III. Results of exposure using the direct approach.]

Results of the P-P Method

The scale and shape parameters estimated from the gamma pdf fitted to consumption and contamination datasets are shown in Table IV.

Message to the editor: Place Table IV approximately here (if possible). [Table IV. Parameters of the gamma pdf fitted to the subclasses of normalized consumption.]

Table V provides statistics calculated from the simulation outputs. The estimated statistics presented are the mean, standard deviation, skewness and kurtosis, as well as the median and the main high quantiles (90 th , 95 th and 99 th ). The highest values of skewness and kurtosis were found in the celiac sufferers group, while it was assumed that the most exposed group would be the infants and ethnics, with the highest mean and quantiles, especially the related 99th

quantile. An example of exposure output histograms of relative frequencies, obtained for adult females is given in Fig. 3. When the estimated means from the simulation method are compared to those obtained through the direct approach, it is observed that they are quite higher. [Fig. 3. Exposure output histograms (relative frequencies) obtained with the P-P method, for adult females. Exposure in µg kg -1 bw day -1 ] [Table V. Results of exposure assessment of the population groups from P-P simulation method. These results were obtained directly from the N simulation outputs without pdf fittings; they must be compared to the results of Table VI (in µg kg -1 bw day -1 ).]

Table VI shows the estimated statistics of exposure to DON by lognormal and gamma pdf fitted to the outputs of the simulation method. An example of the exposure histograms is given in Fig. 4 where the fitted gamma and lognormal pdfs for adolescents are given. The Anderson-Darling and Chi-Square statistics showed that lognormal and gamma distributions can be acceptable, with the exception of fitted lognormal pdf for adult females and ethnics.

When comparing the means from lognormal and gamma pdf fittings to the simulation outputs, the values were close for all age groups with the exception of infants, the highest value of which was estimated for lognormal pdf fittings. On the other hand, large differences were found for the high quantiles (95th and 99th quantiles), with the biggest values observed again for infants.

Message to the editor: Table VI approximately here (if possible).

[Table VI. Estimated statistics of exposure to DON by lognormal and gamma pdf fitted to the outputs of the P-P method. See the rigorous definitions of the shape and scale parameters in the appendix. (in µg kg -1 bw day -1 ).] [Fig. 4. Fitted gamma (solid line) and lognormal (broken line) pdfs for adult females.

Relative parameters are given in

Results of the Bootstrap Confidence Intervals

Confidence intervals built using the bootstrap pseudo-parametric method for the outputs of P-P method are given in Table VII. The estimates given in Tables IV andVI were always are contained in the confidence intervals. It was therefore considered that the P-P method provided reliable estimates, and that this hypothesis was valid for both those statistics estimated from lognormal and gamma pdf fitted to the outputs of this simulation method.

Another point to highlight in this section is the progressive decrease in accuracy when we estimate the CI b of high quantiles, particularly excessive in the case of the 95 th and 99 th quantiles. It is an accepted fact that it is very difficult to obtain good accuracy for the 99 thquantile, in particular [START_REF] Breiman | Robust confidence bounds for extreme upper quantiles[END_REF][START_REF] Beirlant | Practical analysis of extreme values[END_REF][START_REF] Beirlant | On the impossibility of estimating densities in the extreme tail[END_REF].

Message to the editor: Table VII approximately here (if possible).

[Table VII. Bootstrap confidence intervals obtained from the results of the P-P method. (in µg kg -1 bw day -1 ).]

Discussion

In the present work the stochastic methodology developed by [START_REF] Gauchi | Quantitative assessment of exposure to the mycotoxin Ochratoxin A in food[END_REF] was applied to quantify the exposure of Catalonian population to deoxynivalenol. A raw contamination data set obtained by means of thorough chemical analysis of many foodstuff samples was used. Moreover, consumption data was taken from a specific nutritional study to assess the consumption of those commodities susceptible to mycotoxin contamination, by Catalonian population. The exposure was estimated, in one hand, through a direct method, the 13 most commonly method used in the previous studies, and in the other hand, by means of a simulation method (P-P). Finally, the pseudo-parametric bootstrap confidence intervals were calculated for the parameters obtained through the simulation method.

In both cases, direct method and simulation method, the most exposed groups to DON were infants and ethnics. The means estimated through the simulation method were 0.15 and 0.96 µg kg -1 bw day -1 , for celiac sufferers and ethnics, respectively. The median was quite low in all cases (0.04-0.36 µg kg -1 bw day -1 ), but the high percentiles increased these estimated intakes until worrying values, for example 3.82 µg kg -1 bw day -1 (percentile 95 for ethnic group). When the estimates were compared to the TDI of 1 µg kg -1 body weight (SCF 2002), it was observed that the mean values were between 15% and 96% of TDI, and the high percentiles commonly exceeded it.

Other studies have already estimated a high DON consumption worldwide, for example, JECFA estimated human dietary intake of DON in five regional diets, the highest one occurring in the Middle Eastern region (2.4 µg kg -1 bw day -1 ), followed by Far Eastern and European (1.6 and 1.4 µg kg -1 bw day -1 , respectively) [START_REF] Canady | Deoxynivalenol. Safety Evaluation of Certain Mycotoxins in Food[END_REF]). In the First French Total Diet Study, [START_REF] Leblanc | Estimated dietary exposure to principal food mycotoxins from The First French Total Diet Study[END_REF] estimated DON daily intakes of 0.28 and 0.57 µg kg -1 bw day -1 , for mean and percentile 95 for adults, respectively; while 0.45 and 0.93 µg kg -1 bw day -1 , were estimated for children. A probabilistic methodology to assess the exposure to DON was conducted in Netherlands, concluding that 1-year-old children was the most exposed group, with estimated intakes of 0.46 and 1.00 µg kg -1 bw day -1 , for the median and percentile 95, respectively [START_REF] Pieters | Reduced intake of deoxynivalenol in the Netherlands: A risk assessment update[END_REF]).

To our knowledge, this is the first study to assess the exposure of special population groups to deoxynivalenol. The special groups selected in the present study had dietary habits markedly different from the general population. In one hand, celiac sufferers substitute the wheat-based food for other gluten free cereals, and in the other hand, some ethnic groups partially maintain To sum up, considering our results from the P-P simulation method, the Catalonian population should be expected to be exposed at moderated levels of deoxynivalenol, being the infants and individuals with ethnic dietary patterns, the most exposed population groups.

Although the majority of the population do not exceed the TDI of 1 µg kg -1 bw day -1 , there is still a large population exceeding this safety value. A reduction of DON levels in foodstuffs would entail to reach safety levels on global DON intake. where m X and σ X are λ and r, the scale and the shape parameters, respectively. X then follows a normal distribution with mean m X and variance 2 X σ . The mean and the variance of Y are defined by

( ) 2 exp ) ( 2 X X m Y E σ + = and ( ) [ ] ( ) [ ] 1 exp 2 exp ) ( 2 2 - + = X X X m Y V σ σ
, respectively.

The gamma pdf for a continuous random variable X defined in [0, +∞[ is:

      - -       - Γ = - λ θ λ θ λ x x r x f r exp ) ( 1 ) ( 1
where r, λ and θ are the shape, scale, and the threshold parameters, respectively, and Γ(r) is the usual Euler's integral. The mean and variance of the gamma distribution are related to r and λ in the following way: E(X) = rλ and V(X) = rλ 2 . Table I. Occurrence of deoxynivalenol in food matrices from food available on the Catalonian market.

Table II. Normalised consumption of the main foodstuff related to DON contamination by the 384 adult females (g kg -1 body weight day -1 ).

Table III. Results of exposure using the direct approach.

Table IV. Parameters of the gamma pdf fitted to the subclasses of normalized consumption.

Table V. Results of exposure assessment of the population groups from P-P simulation method. These results were obtained directly from the N simulation outputs without pdf fittings; they must be compared to the results of Table VI (in µg kg -1 bw day -1 ).

Table VI. Estimated statistics of exposure to DON by lognormal and gamma pdf fitted to the outputs of the P-P method. See the rigorous definitions of the shape and scale parameters in the appendix. (in µg kg -1 bw day -1 ).

Table VII. Bootstrap confidence intervals obtained from the results of the P-P method. (in µg kg -1 bw day -1 ). VI. Exposure in µg kg -1 bw day -1 .

Figures Captions

  foodstuffs from Catalonian market, especially in wheat flakes, corn flakes, corn snacks, pasta and bread

  Raw contamination data was mainly taken from the study of[START_REF] Cano-Sancho | Presence of trichothecenes and co-occurrence in cereal-based food from Catalonia (Spain)[END_REF], and completed with some data from the Project to Assess the Exposure of the Catalonian Population to Mycotoxins (UdL-ACSA 2010).

  work, during the months of June and July 2008, corn flakes (n=168), wheat flakes (n=27), sweet corn (n=185), corn snacks (n=213), pasta (n=201), beer (n=213), sliced bread (n=147), bread (n=31), gluten-free foods (n=12), ethnic foods (n=35) and baby foods (n=90)

  .1 approximately here.

  . Occurrence of deoxynivalenol in food matrices from food available on the Catalonian market] [Fig 1. Contamination histograms (relative frequencies), in µg g -1 for each food] Raw consumption data Consumption data were taken from the Project to Assess the Exposure of the Catalonian Population to Mycotoxins (UdL-ACSA 2010). This study involved a wide nutritional survey designed to specifically identify the dietary patterns of the Catalonian population in relation to the main foodstuffs susceptible to mycotoxins contamination.

  photograph models. Finally, 76 seniors, 720 adults, 235 adolescents, 69 children, 164 parents

  editor: Place Figure3and Table V approximately here (if possible).

  from their country of origin. In Catalonia during 2009, the immigrant population represented 15.9 % of the total population[START_REF] Migracat | Observatori de la Imigracio a Catalunya[END_REF], therefore, their specificities should be taken into account to assess the exposure of this collective in other close regions.

  Fabiansson S. 2008. Recent progress in exposure assessment and its interaction with the risk analysis process. Trends Food Sci Technol. 19:92-8.World Health Organization (WHO). 2005. Dietary exposure assessment of chemicals in food.Report of a joint FAO/WHO consultation, Annapolis, Maryland, USA.

Fig 1 .Fig 2 .Fig. 3 .Fig. 4 .

 1234 Fig 1. Contamination histograms (relative frequencies), in µg g-1 for each food 190x275mm (96 x 96 DPI)

Fig 1 .Fig. 3 .

 13 Fig 1. Contamination histograms (relative frequencies), in µg g -1 for each food

Table VI .

 VI Exposure in µg kg -1 bw day-1 ]

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y

Table I .

 I Occurrence of deoxynivalenol in food products available in the Catalonian market. Contamination data provided by Cano-Sancho et al. (2010). 2 Contamination data provided by UdL-ACSA et al. (2010).

	Page 21 of 32	Food Additives and Contaminants
		N individual	N composite	Samples >LOQ	Mean± ± ± ±sd	Max
					µ µ µ µg/g	µ µ µ µg/g
	Wheat flakes 1	27	27	20/27	0.190±0.117	0.437
	Corn flakes 1 Beer 1 Sweet corn 1 F o r 168 213 185	65 71 72	49/65 1/70 2/72	0.109±0.078 0.012 0.114±0.036	0.580 0.012 0.139
	Corn snacks 1 Pasta 1 Sliced bread 1 Bread 1	213 201 P 147 31 e e 71 70 72 31 r	56/71 52/70 12/72 31/31	0.153±0.058 0.226±0.177 0.068±0.018 0.246±0.158	0.304 0.946 0.098 0.739
	Ethnic foods 2 Gluten-free Bread 2 Gluten-free pasta 2 Baby food x	35 5 7 30	35 5 7 30 R e v 20/35 1/5 1/7 12/30 i e w	0.406±0.272 0.270 0.163 0.131±0.054	1.080 0.270 0.163 0.286
				O n
					l y

1 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

Table II .

 II Normalised consumption of the main foodstuffs related to DON contamination by the 384 adult females (g/kg body weight/day).

		Food Additives and Contaminants		Page 22 of 32
			%
	Consumers	Consumers	Mean	SD	Max
	Breakfast cereals	153	39.8	0.48	0.46	2.35
	Sliced Bread	161	41.9	0.22	0.32	1.74
	Bread	365	95.1	0.91	0.72	4.78
	Pasta	378	98.4	0.34	0.29	3.51
	Corn Snacks Beer Sweet Corn F o	114 204 143	29.7 53.1 37.2	0.07 1.43 0.50	0.11 1.97 1.08	0.91 10.14 8.33
	r
	P
	e e r
			R e v i e w
				O n
					l y

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Table III .

 III Results of exposure using the direct approach.

	Page 23 of 32	Food Additives and Contaminants
			ˆπ E	0	( ˆ0 π E V	)
	Seniors		0.04	(0.04) 2
	Celiac sufferers	0.13	(0.09) 2
	Ethnics		0.57	(0.47) 2
	Adults females	0.09	(0.07) 2
	Adults males	0.10	(0.08) 2
	Adolescents	0.15	(0.13) 2
	Children Infants (µg kg -1 bw day -1 ) o F r	0.36 0.74	(0.27) 2 (0.71) 2
	P
	e
	e r
		R
		e
		v i e
				w
					O n l
					y

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Table IV .

 IV Parameters of the gamma pdf fitted to the subclasses of normalized consumption.

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y

Table V .

 V Results of exposure assessment of the population groups from P-P simulation method. These results were obtained directly from the N simulation outputs without pdf fittings; they must be compared to the results of Table VI (in µg kg -1 bw day -1 ).

	P-P Method
			Seniors		Adult females	Adult males
	N		10000		10000	10000
	Mean		0.28		0.56	0.37
	SD		0.48		0.77	0.48
	Skewness		5.58		4.97	4.79
	Kurtosis Median 0.90 th quantile 0.95 th quantile 0.99 th quantile	F o r	59.47 0.12 0.71 1.08 2.27		41.65 0.32 1.26 1.84 3.70	41.08 0.22 0.82 1.18 2.33
		Adolescents P	Children	Infants
	N Mean SD Skewness	10000 0.43 e 0.55 3.26 e r	10000 0.68 1.83 10.16	10000 0.90 1.51 4.80
	Kurtosis Median 0.90 th quantile 0.95 th quantile 0.99 th quantile		14.39 0.25 0.99 1.46 2.86 Ethnics	156.74 0.24 1.38 2.49 8.17 Celiac sufferers v R e i e	42.15 0.36 2.33 3.57 7.15
	N Mean		10000 0.96		10000 0.15 w
	SD		1.98		0.55
	Skewness Kurtosis Median 0.90 th quantile		6.95 79.96 0.36 2.24		19.20 724.87 0.04 0.29 O n l
	0.95 th quantile 0.99 th quantile		3.82 9.38		0.64 2.18	y

Table VI .

 VI Estimated statistics of exposure to DON by lognormal and gamma pdf fitted to the outputs of the P-P method. See the rigorous definitions of the shape and scale parameters in the appendix. (in µg kg -1 bw day -1 ).

		Ethnics	Celiacs
	Lognormal	rˆ=1.434; λ ˆ=-1.088	rˆ=1.374; λ ˆ=-3.089
	P-P Method Mean	1.00	0.12
	SD	Seniors 2.61	Adult Females 0.28	Adult Males
	Lognormal Median 0.90 th quantile	rˆ=1.614; λ ˆ=-2.302 0.36 2.25	rˆ=1.061; λ ˆ=-1.146 0.05 0.27	rˆ=1.036; λ ˆ=-1.526
	Mean 0.95 th quantile	0.37 3.78	0.56 0.44	0.37
	SD 0.99 th quantile	1.30 10.06	0.80 1.11	0.52
	Median AD (p-value)	0.10 0.46 (0.267)	0.32 66.40 (<0.005)	0.22
	0.90 th quantile 0.95 th quantile 0.99 th quantile AD (p-value) Gamma Gamma Mean SD Median Mean SD Median 0.90 th quantile 0.95 th quantile 0.99 th quantile 0.90 th quantile 0.95 th quantile 0.99 th quantile Chi-Sq (p-value) AD: Anderson Darling statistic; Chi-Sq : Chi Square statistic 0.79 1.42 4.27 31.88 (<0.005) rˆ=0.607; λ ˆ=0.456 F o r rˆ=0.622; λ ˆ=1.546 0.96 1.22 0.52 F o r 0.28 0.36 0.15 0.72 0.99 1.65 P e e r 2.48 3.51 5.67 P 52310.98 (<0.001) e e r	1.24 1.82 3.75 0.25 (>0.5) rˆ=1.027; λ ˆ=0.542 rˆ=0.517; λ ˆ=0.299 0.16 0.22 0.07 0.56 0.55 0.39 1.27 1.65 2.53 0.42 0.59 1.01 154786.81 (<0.001)	0.82 1.19 2.42 0.79 (<0.042) rˆ=1.083; λ ˆ=0.340 0.37 0.35 0.26 0.83 1.07 1.63
	Chi-Sq (p-value) Lognormal Mean SD Median	15402.96 (<0.001) Adolescents R R rˆ=1.066; λ ˆ=-1.389 e rˆ=1.397; λ ˆ=-1.439 133.80 (<0.001) Children e 0.44 0.63 0.64 1.55 0.25 0.24 v i e v i e	108.08 (<0.001) Infants rˆ=1.841; λ ˆ=-1.240 1.58 8.44 0.29
	0.90 th quantile 0.95 th quantile	0.98 1.44	1.42 2.36 w w	3.06 5.98
	0.99 th quantile AD (p-value) Gamma Mean SD Median	2.98 4.37 (<0.005) rˆ=1.039; λ ˆ=0.417 0.43 0.43 0.31	6.12 3.79 (<0.005) rˆ=0.591; λ ˆ=-1.146 0.68 0.88 O n l rˆ=0.550; λ ˆ=1.644 20.98 80.97 (<0.005) 0.90 O n l 1.22 0.35 0.45 y y
	0.90 th quantile	0.99	1.77	2.40
	0.95 th quantile	1.28	2.45	3.36
	0.99 th quantile	0.96	4.10	5.69
	Chi-Sq (p-value)	1239.06 (<0.001)	190006.68 (<0.001)	14077.63 (<0.001)
	AD: Anderson Darling statistic; Chi-Sq: Chi Square statistic

Table VII .

 VII Bootstrap confidence intervals obtained from the results of the P-P method. (in µg kg -1 bw day -1 ).

	P-P Method 95% Bootstrap Confidence Interval
	Seniors	Adult Females	Adult Males
	Mean F o
	r
	P
	e e r
	R e v i e w
		O n
		l y

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Scientific Committee on Food (SCF). Opinion on Fusarium toxins-Part 6: Group evaluation of T-2 toxin, HT-2 toxin, nivalenol and deoxynivalenol [Internet]. 26 February 2002. [Cited 2010 Feb 15]. Available from: http://europa.eu.int/comm/food/fs/sc/scf/out123 en.pdf. SCOOP (Scientific Cooperation Task 3.2.10 of the European Commission). 2003. Collection of occurrence data of Fusarium toxins in food and assessment of dietary intake by the

Acknowledgements

The authors would like to acknowledge Exposure Assessment of Spanish Population to Fusarium Toxins Project, National Plan of Spanish Government (AGL2008-05030-C02-01), Catalonian Food Safety Agency of 'Generalitat de Catalunya' Health Department and University of Lleida for their financial support, and to Mathematics and Informatics Applied Group, INRA (Jouy-en-Josas center), for their technical support.

Appendix: Definitions of the lognormal and gamma probability density functions

The lognormal pdf for the continuous random variable Y defined in [0,+∞[ is:

Adult females ( rˆ, λ ˆ) Adult males ( rˆ, λ ˆ) Teenagers ( rˆ, λ a Values between parentheses are rˆ and λ ˆ of the Gamma pdf fitted to the contamination data.

-, no consumption data