Takahiro Wakihira

Seiko Miyashita

Minoru Kobayashi

Kazuhiko Uemura

Pascal Schlich
email: pascal.schlich@inrae.fr

Temporal Dominance of Sensations paired with dynamic wanting in an ad libitum setting: A new method of sensory evaluation with consumers for a better understanding of beer drinkability

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

p. 2 continuously. This methodology should be used with different types of beers and consumers to obtain a broader understanding of the sensory drivers of beer drinkability and consumer satisfaction.

[Keywords]

Temporal Dominance of Sensations (TDS), wanting, ad libitum, drinkability, Multiple-sip Drinkability Test, beer

[1] Introduction

Motivation for the research

It is an indubitable fact that a manufacturer's mission is to keep delivering benefits to consumers, which can be accomplished by examining the usage experience of their products. Sensory and consumer science is likely one of the best means of bridging the gap between a manufacturer and consumers caused by misunderstanding the consumers' expectations. The authors have struggled for a long time with an issue in consumer research in the beer industry; namely, why products that are liked/disliked in consumer research are not necessarily the ones that sell well/poorly in the market, and vice versa. The authors believe that the answer to this question does not simply lie in marketing investments in products, and thus began this research to search for methodologies to better understand consumer responses in a way that is relevant to consumption in real life as well as efficiently applicable to product development in the beer industry.

Liking has been used in the beer industry as a key measurement for a very long time.

Liking is an easy construct to work with because the construct itself is perfectly clear and the relationship between the word label (like/liking) and the construct is unambiguous to both consumers and researchers [START_REF] Thomson | Psychology of drinkability. European Brewery Convention[END_REF]. However, two beers which are liked equally at first are not always equally liked at the end of drinking. This aspect has long been discussed in the beer industry as a construct of "drinkability." In past years, the industry used consumer tests called the "Session Test" or the "Sessionability Test" in which participants were asked to drink large quantities of beer in one session and then researchers measured the total volume of consumption for each beer [START_REF] Greenhoff | Consumer measurement of drinkability[END_REF][START_REF] Dickie | Fancy another beer -same again? European Brewery Convention[END_REF]). These methods, however, include challenging issues related to ethics, health, feasibility, test controls, and so forth. Thus, the beer industry has long desired the development of a new scientific method to measure beer drinkability in consumer research.

Previous studies on beer drinkability

Several physiological studies on beer drinkability have been conducted in the last two p. 3 decades:

- [START_REF] Nagao | Correlation between the drinkability of beer and gastric emptying[END_REF] showed a correlation between beer drinkability and gastric emptying, and suggested that measurement of the relaxed cross-sectional area of the pylorus antrum was useful to evaluate stomach fullness during beer drinking.

-They also studied the sensory perceptions of stale beer and beer with an added unpleasant taste and flavor in correlation with the urination rate, and found that the unpleasant taste and off-flavor of beer resulted in a lower urination rate while drinking beer [START_REF] Nagao | Reduced urination rate while drinking beer with an unpleasant taste and off-flavor[END_REF]).

- [START_REF] Kojima | Relationships among throat sensation, beer flavor, and swallowing motion while drinking beer[END_REF] used a noninvasive biometric system to examine the relationship among throat sensation, beer flavor, and swallowing motion while drinking beer. They concluded that the sensation in the throat was an important factor in beer drinkability. These types of physiological studies have disentangled some of the aspects of beer drinkability with their objective measurements. Presently, though, there is a lack of consumer-relevant subjective approaches that would add more value in understanding the construct of drinkability by linking the results with those from physiological studies. While bearing in mind that the ultimate goal of studying beer drinkability is to maximize consumers' enjoyment of drinking beer, it is of paramount importance that we understand beer drinkability from the consumers' perspective. Thus, there is a strong need to develop a consumer-relevant approach for assessing beer drinkability.

According to [START_REF] Mattos | Recent review on beer drinkability[END_REF]Moretti (2005, 2006), drinkability can be defined as "the will of drinking or the weakness of the sensation of satiation" and "to be appreciated until the last drop." Several researchers have studied the impact of ingredients (malts, hops) and brewing technology (yeast, fermentation) on sensory perceptions linked with beer drinkability [START_REF] Davies | Malt -a vital part of the brewer's palette[END_REF][START_REF] Kaltner | Possible impact of hops on taste and drinkability of beer[END_REF]V. Opstaele et al. 2006;[START_REF] Taldi | Yeast and fermentation, tools for increasing drinkability[END_REF]. Despite their efforts to clarify factors affecting beer drinkability, it should be noted that each of these researchers needed to create their own measurement as a response variable of drinkability.

Unfortunately, the absence of commonly accepted methods for measuring drinkability has hampered efforts to clarify the factors affecting it. This is the impetus behind the present study aimed at developing a new method to measure "the will of drinking" with a focus on the sensory effect for beer drinkability, which could be widely used in consumer tests.

Consumer research in food and drink categories

The most popular type of consumer test with foods involves product trials at a central location. These kinds of tests offer reasonably good control conditions, and the staff can be well trained in product preparation and handling [START_REF] Lawless | Sensory Evaluation of Food: Principles and Practices[END_REF]. Although the product is not tested under its normal conditions of use, such as at home or at parties, p. 4 restaurants, etc., central location tests (CLTs) have the advantage that respondents evaluate the product under controlled conditions, which enables any misunderstandings to be cleared up [START_REF] Meilgaard | Sensory Evaluation Techniques: 5th Edition[END_REF]. With these points in mind, a consumer-relevant method for assessing beer drinkability that can be widely applicable in CLTs would be a valuable solution toward not only obtaining a greater scientific understanding of beer drinkability, but also for product development, particularly during the early stage when many prototypes need to be tested.

Being aware of the issue regarding CLTs, several researchers have studied the influence on product acceptance of how food and drink are consumed by respondents in CLTs. [START_REF] Matuszewska | Comparison of three procedures for consumer assessment of fat spreads: Short report[END_REF] compared three procedures for consumer assessment of fat spreads, and concluded that having consumers spread a margarine sample ad libitum by themselves on a standardized piece of bread was the most preferable procedure due to its superior discrimination power and labor-saving sample preparation. [START_REF] Zandstra | Laboratory hedonic ratings as predictors of consumption[END_REF] showed in their study on yogurts that the optimal sucrose concentration as determined by the taste-and-spit test was higher than that determined from the ad libitum consumption test. [START_REF] Posri | The influence of testing context on tea bag product acceptance in central location tests[END_REF] compared overall liking scores of tea bag products obtained from three CLTs in which the degree of freedom when making tea was different, and concluded that the provision of greater "freedom" in CLTs could result in greater discrimination between tested products. Although the influence of testing conditions on product acceptance could differ depending on the type of product, these previous studies indicated that improving the design of CLTs based on consumer insight could potentially result in a better understanding of estimating consumer response in real life.

Beer studies from the perspective of sensory and hedonic perceptions

Since the ultimate goal of studying beer drinkability is to maximize consumers' enjoyment of drinking beer, it is crucial that we investigate the factors affecting beer drinkability in terms of consumers' sensory perceptions as well as affection. Beer drinking behavior involves dynamic rather than static sensations, which implies the necessity of incorporating temporal aspects into evaluations to grasp changes in sensory perceptions over time while drinking. [START_REF] Pineau | Temporal dominance of sensations: A new technique to record several sensory attributes simultaneously over time[END_REF] proposed a new method of sensory evaluation, called Temporal Dominance of Sensations (TDS), in order to record several sensory attributes simultaneously over time. According to them, TDS makes it possible to collect temporal data during one single evaluation for up to 10 attributes of complex food products, and to draw curves of the dominance of each attribute over time for each product [START_REF] Pineau | Temporal Dominance of Sensations: Construction of the TDS curves and comparison with time-intensity[END_REF].

The same group of researchers also proposed an extended method of TDS, called multiple-intake (sip or bite) TDS, in order to avoid potentially misleading results from a single p. 5 intake because, as Koster (2003) pointed out, the evaluation on a single intake only would not capture the changes in sensory perceptions that occur during actual consumption. This method made it possible to obtain a series of consecutive TDS evaluations at every intake, which was more relevant to consumption of a product in real life [START_REF] Vandeputte | Innovative methods to assess the evolution of the sensory characteristics during the tasting of a full product portion (several bites)[END_REF][START_REF] Pineau | Extension of TDS to multi-bite evaluation[END_REF][START_REF] Schlich | Multi-bites or multi-sips TDS with untrained subjects: A live demonstration on chocolates[END_REF]. As an example, [START_REF] Zorn | Application of multiple-sip temporal dominance of sensations to the evaluation of sweeteners[END_REF] applied multiple-sip TDS methodology to evaluate different sweeteners in orange juice, and showed its effectiveness in identifying differences in the dynamics of their sensory characteristics, which had not been identified using static measurements. Furthermore, [START_REF] Thomas | Temporal drivers of liking[END_REF] suggested a new methodology for characterizing temporal drivers of liking (TDL) based on the ability of consumers to record their changes in liking and to perform a TDS task.

Several researchers have recently reported on their studies of beer using temporal aspects. Vazquez-Araujo et al. ( 2013) compared three different techniques of temporal sensory methods for evaluating beer flavors: time intensity, TDS, and drinking profile. They demonstrated that all three techniques are useful for evaluating beer flavor, and indicated the pros and cons for each method. [START_REF] Simioni | Multiple-sip temporal dominance of sensations associated with acceptance test: a study on special beers[END_REF] reported a study on special beers (Bohemian Pilsner, Witbier, Belgian Strong Ale Dubbel, and Russian Imperial Stout) in which consumers took six sips (20 mL each) in total to evaluate a sample of the four different beers on four consecutive days. The tasters performed TDS, followed by a liking evaluation, for every sip of each beer sample until they finished taking the 6 th sip. The authors concluded that multiple-sip TDS associated with an acceptance test promoted an enhanced understanding of consumer behavior regarding temporal description and sensory acceptability over repeated consumption. [START_REF] Ramsey | Using a combined temporal approach to evaluate the influence of ethanol concentration on liking and sensory attributes of lager beer[END_REF] applied a combination of temporal liking (TL) and temporal Check-All-That-Apply (TCATA), with the aim of determining the influence of ethanol concentration on consumer evaluation for lager beer.

Participants in their study drank 30 mL of a beer sample and continued the evaluation up to 60 seconds for TL or for TCATA in a separate session, and they repeated the same evaluation method for four different beers during the same session. The researchers demonstrated the effectiveness of using these combined temporal methodologies for clarifying the influence of ethanol on the perception of liking and sensory attributes by beer consumers.

These previous studies expanded the range of approaches for sensory and consumer science in evaluating beer flavors. However, these studies were conducted using controlled settings, such as the amount of beer in each sip or the number of sips per panelist. With the caveat presented by Koster (2003) in mind, these approaches with limited and controlled consumption might not provide sufficient information to understand consumers' responses p. 6 when drinking an entire beer. To the best of our knowledge, except for one study reported by [START_REF] Thomas | Alternating temporal dominance of sensations and liking scales during the intake of a full portion of an oral nutritional supplement[END_REF], no other studies have investigated the dynamics of sensory and hedonic perceptions throughout the consumption of a whole package of a food or a full portion of a drink in an ad libitum consumption setting. [START_REF] Thomas | Alternating temporal dominance of sensations and liking scales during the intake of a full portion of an oral nutritional supplement[END_REF] showed the effectiveness of using a method consisting of collecting TDS and dynamic liking data in the same session and during the consumption of the full portion of an oral nutritional supplement. However, no study on beer has been conducted from this perspective. Furthermore, when discussing topics such as beer drinkability or sense of satiation regarding food, collecting data on dynamic wanting rather than liking, as a measurement of evoked affection, would make more sense in a correlation with the volume of beer or the amount of food actually consumed.

Scope of the present study

Finally, two other topics should be mentioned when talking about beer drinkability: "context of consumption" and "emotions." Recently, [START_REF] Jaeger | Consumption context in consumer research: methodological perspectives[END_REF] pointed out in their review paper that "contextual influences partially shape food-related consumer behavior," and [START_REF] Nijman | The effect of consumption context on consumer hedonics, emotional response and beer choice[END_REF] elucidated the effects of consumption context towards consumer responses to beer. These studies indicate the importance of considering consumption context when assessing beer drinkability. Moreover, several studies have recently reported the effectiveness of measuring emotions evoked when drinking beer with the aim at differentiating products beyond liking [START_REF] Cardello | Cognitive and emotional differentiators for beer: An exploratory study focusing on "uniqueness[END_REF][START_REF] Gomez-Corona | Measuring the drinking experience of beer in real context situations. The impact of affects, senses, and cognition[END_REF]Jaeger et al. 2017;[START_REF] Jaeger | Supplementing hedonic and sensory consumer research on beer with cognitive and emotional measures, and additional insights via consumer segmentation[END_REF][START_REF] Silva | Effect of adding hop aroma in beer analysed by temporal dominance of sensations and emotions coupled with temporal liking[END_REF]. These studies indicate the potential benefit of measuring emotions to better understand the construct of beer drinkability for consumers. These two topics, "context of consumption" and "emotions," were not directly covered in the scope of the present study since its focus was to establish a basic method to evaluate beer drinkability from a sensory perspective.

Aim of the research

The main objective of the present study was to develop a new method of sensory evaluation with consumers to obtain a better understanding of beer drinkability. The aim was to establish a new method to measure "the will of drinking", which can be practically and effectively used in a wide range of consumer tests in ad libitum consumption settings. The ultimate goal of this study was to clarify the factors that affect beer drinkability, which could be achieved by investigating the effects of manipulating explanatory variables such as ingredients, recipes and brewing technologies. In this way, this research could contribute to the development and marketing of products for maximizing consumers' enjoyment of p. 7 drinking beer.

[2] Methods

Overview of the approach in this study

The investigation was divided into two different parts. In Phase 1, a test was conducted with an expert beer panel to confirm the capability and feasibility of our methodology. In Phase 2, a test was conducted with a consumer panel to confirm the validity of our methodology with beer consumers. This type of approach was used to acquire more implications and more aspects for discussion rather than jumping immediately into consumer tests.

Test design of Phase 1

In Phase 1, a test was conducted with an expert beer panel consisting of 11 employees of the R&D center at Asahi Breweries, Ltd. (Moriya, Japan) who were trained in tasting and evaluating beer. These panelists were recruited from approximately 40 panelists of the Asahi expert beer sensory panel who have from 6 months to nearly 20 years of experience in beer evaluations. These panelists evaluate beer samples regularly once or twice a day to contribute to beer sensory evaluations conducted in the R&D center. An annual training session and the daily participation in beer sensory evaluations help them maintain their ability to evaluate beer characteristics, which, in Phase 1, were based on consensus using the definition of the following sensory attributes: malty, hoppy, estery, sweet, sour, bitter, astringent, and stimulating feeling.

In Phase 1, the expert beer panel evaluated 4 products, with 2 repetitions each, for a total of 8 evaluations per panelist. Panelists in Phase 1 drank a maximum of 500 mL of each of the beer samples in 45 minutes. (See 2.1.3. Rationale behind the test designs on maximum consumption volume.)

Test design of Phase 2

In Phase 2, a test was conducted with a naïve panel consisting of 44 participants (30 men and 14 women, age range: 20s to 50s) who were recruited from the Asahi Group R&D Center (Moriya, Japan). These panelists were not trained for beer evaluation, but were used to drinking beer at least once a week. A drinking frequency of at least once a week and a male-to-female ratio of 2:1 among the study group are standard recruitment criteria when conducting consumer research in the beer industry in Japan.

In Phase 2, the naïve panel evaluated 3 products, with no repetition, for a total of 3 evaluations per panelist. Panelists in Phase 2 drank a maximum of 350 mL of each sample p. 8 in 30 minutes. (See 2.1.3. Rationale behind the test designs on maximum consumption volume.)

Rationale behind the test designs on maximum consumption volume

In Japan, around 70% of beer sales are attributed to beers consumed at home (Fuji Keizai Co., Ltd. 2019). Most of these beers for consumption at home are sold in the regular 350 mL can or the larger 500 mL can. Since it was expected that monitoring evaluations for a longer time would result in more discrimination among products, the 500 mL can was chosen for the full portion drinkability test in Phase 1. The volume of total consumption was restricted to 500 mL to be in line with the guideline on responsible drinking (around 20 g pure alcohol per day) established by the Ministry of Health, Labour and Welfare in Japan (Kenkou Nippon

21).

According to a survey conducted by Asahi Breweries in 2018, among beer drinkers (2000 men and 1000 women, age range: 20s to 50s) with a drinking frequency of at least once a week, 71% of men do not consume more than 700 mL of beer (27% stop after drinking one can of 350 mL and 44% stop after drinking one can of 500 mL or two cans of 350 mL) and 92% of women do not consume more than 700 mL (56% stop after drinking one can of 350 mL and 36% stop after drinking one can of 500 mL or two cans of 350 mL) in one session at home. Thus, the investigation with beer consumers in Phase 2 focused on the size of a full portion of a regular 350 mL can, which is at least half of the total consumption volume for a majority (71% for men and 92% for women) of beer consumers in the Japanese market.

Another reason for choosing the 350 mL can was its potentially high acceptability and feasibility when considering extensive use of our proposed methodology in consumer tests.

If evaluations of a full portion of 350 mL lead to sufficient product discrimination, it would be considerably useful for the beer industry in product development, particularly at the early stage when many prototypes need to be tested.

Test flow

Figure 1 shows the flow of the "Multiple-sip Drinkability Test." First, the panelists take a sip and participate in TDS for 30 seconds, followed by a Liking evaluation. Second, they wait until they feel like drinking another sip. Just before they want to have the 2 nd sip, they evaluate their residual sensation, which is the degree of flavor perceptions left in the mouth and nose. Next, they take the 2 nd sip and evaluate its ease of drinking. Again, they wait until they feel like drinking another sip. Just before they want to have the 3 rd sip, they evaluate how much they "Want to drink continuously." For the 4 th , 5 th , and 6 th sips, they perform the same evaluation methods as those for the 1 st , 2 nd , and 3 rd sips, respectively. Likewise, they p. 9 repeat the same evaluations every 3 sips. (Note: Residual sensation was only asked in Phase 1. See section 2.7 for further details.) Most importantly, both of the tests in Phase 1 and Phase 2 were conducted in an ad libitum setting in terms of the drinking amount and pace. Neither the amount of beer that should be drunk in each sip nor the timing of the sips was set in the tests. Panelists could also stop drinking whenever they wanted.

Test products

Four commercial beer samples marketed in Japan were used selected for this study. Detailed product information is not mentioned in the present paper to avoid identifying specific brands. Instead, these samples were labeled as B1, B2, B3 and B4. The main analytical and sensory characteristics of the samples are shown in Table 1. Samples B1, B3 and B4 were selected as test samples in this study because they were major brands sold in the market and because each possessed different sensory characteristics according to previous sensory tests evaluated by the Asahi expert beer sensory panel. Sample B2, however, was known to have quite similar characteristics to those of sample B4. Only a slight difference was previously reported between samples B4 and B2; namely, sample B2 was perceived as more hoppy and less malty than B4 in a very subtle way. The reason why we included Sample B2 was to see if our new methodology was able to detect any difference between it and B4 in the ad libitum setting of drinking. However, no significant difference was observed between samples B4 and B2 regarding sensory and hedonic perceptions in Phase 1 with the expert panel. Therefore, we decided to eliminate sample B2 in Phase 2 with consumers in order to simplify the test design and to reduce the respondents' burden while participating in the test.

All the test samples were served in plastic cups at a temperature of 8 (± 1) °C, which is a common temperature for evaluating beers in sensory studies in Japan. Each product was presented with its own unbranded code using a three-digit random number, according to Williams Latin Square experimental designs.

Test environments

Each panelist evaluated one beer sample per day in an individual sensory booth in the R&D center at Asahi Breweries, Ltd. During the evaluation session, the panelists were not allowed to drink water to avoid disrupting evaluations of the beer samples. They were only allowed to eat non-topping salt crackers plain crackers with no salt topping while they were drinking the beer samples. All the panelists, including the expert panelists in Phase 1, were instructed to drink the beer samples freely in the way they usually consumed beer. Use of p. 10 phones or personal computers (PCs) for work was prohibited during the sessions, but magazines were available in the sensory booths for the participants to read. Following the instructions displayed on the PC screens in the isolated sensory booth, each panelist performed sensory and hedonic evaluations throughout the session, and the data were captured using the TimeSens© software (INRA, Dijon, France). After the panelists left the sensory room, the volume of beer actually consumed was calculated by weighing the remaining beer in the cups.

TDS evaluation

Each panelist took the 1 st sip of a beer sample and participated in TDS for 30 seconds.

Likewise, they repeated TDS every 3 sips, for the 4 th , 7 th , 10 th sips, and so on. In line with [START_REF] Pineau | Temporal Dominance of Sensations: What is a good attribute list?[END_REF] recommending not to include more than 10 attributes in a TDS evaluation, the TDS list in Phase 1 included eight attributes: "malty" (roasted, caramel, grainy, worty), "hoppy" (floral, grassy, resinous, spicy, citrus), "estery" (fruity, banana, apple, soapy, solvent-like), "sweet taste" (primary taste), "sour taste" (primary taste), "bitter/astringent" (bitter as primary taste / astringent as the feeling of mouth puckering, tannin-like), "stimulating feeling" (the feeling of pricking and stinging in the mouth and throat), and "others." These attributes were selected to sufficiently describe the sensory characteristics of the four beer samples based on previously obtained information from the Asahi expert beer sensory panel (Table 1). The expert panelists were all familiar with the definition of these attributes, and they were used to performing TDS with this list. Others was included as a choice in the list in case the panelists perceived some flavors that were not applicable to the seven specific attributes. In Phase 2, the naïve panelists received 5 minutes of instruction on the procedure of the TDS evaluation. The TDS list in Phase 2 included eight attributes: "malt-like flavor," "sweet flavor," "refreshing feel," "sweet taste," "sour taste," "bitter/astringent," "stimulating feel," and "others." These attributes had been commonly used in consumer tests with beer drinkers in Japan. The definition of each attribute was not explained to the naïve panelists as with normal consumer tests in Japan.

The others category was also included in the attribute list in Phase 2.

During the test, the selected TDS attributes were presented on one screen, and only dominance was recorded (intensity was not recorded). The attribute order on the screen was different for each panelist, but each panelist kept his or her own order for all sips and products to avoid attribute order effects while facilitating the task of the tasters [START_REF] Pineau | Temporal Dominance of Sensations: What is a good attribute list?[END_REF][START_REF] Thomas | Alternating temporal dominance of sensations and liking scales during the intake of a full portion of an oral nutritional supplement[END_REF]. They had to choose at any tasting time the dominant attribute among the eight proposed. The concept of dominant attribute was defined as "the attribute associated with the sensation catching the taster's attention at a given time." Panelists were p. 11 free to choose the same attribute several times during a tasting, or never select a sensation among the eight proposed [START_REF] Pineau | Temporal Dominance of Sensations: Construction of the TDS curves and comparison with time-intensity[END_REF][START_REF] Thomas | Alternating temporal dominance of sensations and liking scales during the intake of a full portion of an oral nutritional supplement[END_REF]. They were also able to unclick the attribute buttons in case they did not feel any sensations during the 30-second period, and those moments were regarded as No dominance when analyzing the results.

Dynamic evaluation of wanting

Just before the panelists wanted to have the 3 rd sip, they evaluated how much they "want to drink it continuously" on a linear rating scale ranging from "I do not want to drink it continuously at all" to "I want to drink it continuously very much." The panelist's indication on the linear rating scale was converted in the TimeSens© software to a score ranging from 0 to 10 for data analysis purposes (the same procedure was used for the measurements described in section 2.7.). They repeated this wanting evaluation every 3 sips, just before the 6 th , 9 th , 12 th sips, and so on. Since the main focus of this study was to measure "the will of drinking" for beer drinkability, the greatest importance was placed on this dynamic evaluation of "wanting to drink continuously."

Dynamic evaluation of liking, ease of drinking and residual sensation

Immediately after the panelists completed the TDS (1 st , 4 th , 7 th sips, and so on, every 3 sips), they indicated their liking for the beer sample on a linear rating scale ranging from "I do not like it at all" to "I like it very much."

Immediately after the subjects took the 2 nd , 5 th , 8 th sips, and so on, every 3 sips, they evaluated its ease of drinking on a linear rating scale ranging from "not easy to drink at all" to "very easy to drink." Subjects evaluated their residual sensation (from "not strong at all" to "very strong") just before they took the 2 nd , 5 th , 8 th sips, and so on, every 3 sips only in Phase 1. This measurement was not included in Phase 2 with the naïve panel in order to simplify the test design and to reduce potential fatigue caused by evaluating many attributes. with the naïve panel.

Data analyses

Data was analyzed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). TDS curves and TDS band plots were generated using TimeSens 1.3 (INRA, Dijon, France).

TDS analysis

A TDS curve represents the evolution of the dominance rate (which is the proportion of panelists who selected a certain attribute as dominant) over time. For each product, TDS p. 12 curves of all the tested attributes are depicted on the same graph. The TDS curves of the differences in the dominance rate can be superimposed to compare two products. The differences are plotted only when significantly different from zero and when the higher dominant rate is significantly higher than the chance level, thereby highlighting the differences between the products over time [START_REF] Pineau | Temporal Dominance of Sensations: Construction of the TDS curves and comparison with time-intensity[END_REF].

A TDS band plot is generated from TDS data to simplify interpretation of the TDS curves, and facilitates comparison of the sequence of the dominant attributes in all the products of the study.

Analysis of dynamic wanting

The analysis of variance (ANOVA) model used for analyzing the wanting data is: Wanting = product + sip + panelist + product*sip + product*panelist + sip*panelist + error In this model, the product, sip and product*sip interaction were treated as fixed effects.

The panelist and its interactions with the other factors were random effects. As mentioned in section 2.2., all the panelists drank the beer samples freely. This resulted in a different number of sips for each panelist for each sample, which requires use of a restricted maximum likelihood (REML) algorithm instead of the usual least squares algorithm.

Furthermore, successive evaluations of wanting were not independent from sip to sip by product within each panelist. Therefore, a repeated mixed model ANOVA was used with a first-order heterogeneous auto-regressive covariance structure among sips within panelist by product. This structure assumes that the covariance between two wanting scores from two sips of the same evaluation decreases with the number of sips in between these two sips.

The least square mean (LS-mean) and standard error were subsequently computed for each product, for each sip, and for each sip by each product, which enabled interpretation of the statistical differences among products, among sips, and among sips by each product, respectively. This analysis was accomplished using PROC MIXED in SAS 9.4.

Analysis of dynamic liking, ease of drinking and residual sensation

The same repeated mixed model ANOVA was used for other dynamic measurements, which included liking, ease of drinking and residual sensation.

Evolution of attribute dominance durations

Duration of dominance is obtained at the individual level by adding all the time periods p. 13 during which the attribute was cited as dominant, regardless of the moment of perception [START_REF] Galmarini | Advances in representation and analysis of mono and multi-intake Temporal Dominance of Sensations data[END_REF]. Data for the dominance duration of each attribute were analyzed by the same repeated mixed model ANOVA as those used for wanting and the other measurements.

[3] Results

Phase 1 results with the expert panel

Dynamic evaluation of wanting, liking, ease of drinking and residual sensation

Table 2a and Table 2b show results of the ANOVA with the expert panel. Fixed effects of both Sip and Product were observed for wanting, liking and ease of drinking at a statistically significant level (p < 0.05) (Table 2a), but not for residual sensation. Sip effect here refers to changes in evaluations over sips while drinking. The result also showed a significant Product by Sip interaction for wanting (p < 0.05). The p-values of Sip effect by Product (Table 2b) indicate that wanting for samples B1 and B3 significantly changed (decreased) while drinking, whereas wanting for samples B2 and B4 did not. Interestingly, the product differences in wanting, which were almost nonexistent at the beginning of Sip 3 (Sip Cycle 1), gradually became larger while drinking (Figure 2). As a result, the LS-means of wanting show a significant decrease in samples B1 (p = 0.0000) and B3 (p = 0.0000), but not in samples B2 (p = 0.2367) and B4 (p = 0.1576) (Table 2b). In this way, we found that samples B2 and B4 had higher beer drinkability than samples B1 and B3.

Figure 3 shows the evolution of ease of drinking. In contrast to the evolution of wanting (Figure 2), the product differences were already existent at the beginning of Sip 2 (Sip Cycle 1). In particular, this tendency was clearer when looking at the results of sample B1 compared with those of sample B4. Wanting for sample B1 was comparable to that for sample B4 at Sip 3 (Sip Cycle 1); however, ease of drinking for sample B1 was clearly lower than that for sample B4 at Sip 2 (Sip Cycle 1). The products with lower wanting at the end (samples B1 and B3) were lower in ease of drinking from the beginning. These results indicate that ease of drinking at each sip could lead to "wanting to drink continuously," that is, beer drinkability.

The measurements of wanting and liking were similar in that both of them detected a significant Sip effect (p = 0.0000 for wanting, p = 0.0023 for liking) and Product effect (p = 0.0037 for wanting, p = 0.0155 for liking) (Table 2a). Indeed, the correlation coefficient between wanting and liking was high at any sip cycle until Sip Cycle 6, which was 0.79, 0.87, 0.82, 0.86, 0.82, 0.83, respectively computed over 2 replicates, 11 panelists and 4 products (n = 88). However, as shown in Figure 4, in which the LS-mean scores over products in p. 14 Table 2b were plotted in order of sip, decreases in evaluation scores became more prominent for wanting than for liking after the middle of the drinking session (Sip Cycle 4). Also, product by sip interaction was only significant for wanting (p = 0.0310), but not for liking (p = 0.2672) (Table 2a). These findings indicate that asking about wanting could be more powerful in understanding beer drinkability as well as discriminating beer products, rather than asking about liking.

Although we found that samples B2 and B4 were significantly higher than samples B1 and B3 for wanting and ease of drinking (p < 0.05 for both), we could not detect any differences between samples B2 and B4 or between samples B1 and B3 for these measurements (Table 2a).

Dynamic evaluation (TDS) of flavor characteristics

Figure 5 shows the evolution of sensory perceptions. The TDS band plot is a summary of the TDS results for the four beer samples over time while drinking. From the left side, the TDS results are shown every 30 seconds in order of time for the 1 st , 4 th , 7 th sip, and so on.

The colors indicate the sensory characteristics that were significantly dominant during each second. For sample B1, "Hoppy" (blue) was perceived to be consistently dominant at the beginning of each sip and "Bitter/Astringent" (red) became more dominant over time while drinking. For sample B3, "Bitter/Astringent" was consistently dominant for most of the time from beginning to the end. Samples B2 and B4 were perceived to be quite similar to each other, with "Malty" (purple) and "No Dominance" (black) more dominant than the other two products. As previously mentioned in section 2.5. TDS evaluation, the moment when a panelist did not feel any sensations was regarded as "No Dominance" when analyzing the results. In summary, when comparing the products' characteristics, sample B1 was characterized as the most Hoppy, sample B3 as the most Bitter/Astringent, and samples B2 and B4 had the longest period of "No Dominance", which can be seen until the end of drinking.

Link between dynamic wanting and sensory perceptions

The relationship between the results of dynamic wanting and TDS for the four tested products reveals some indications for beer drinkability and sensory perceptions. The products that scored higher in wanting, samples B2 and B4 (Table 2a andFigure 2), were perceived as having less standout flavors such as "Hoppy" and "Bitter/Astringent" (Figure 5), thereby producing less build-up effects on sensory perceptions. These results indicated that the greater the sensory load produced by a beer, the less one wants to drink it continuously. p. 15

Phase 2 results with the naïve panel

Dynamic evaluation of wanting, liking and ease of drinking

Table 3a and Table 3b show the results of the ANOVA with the naïve panel. Fixed effects of both Sip and Product were observed for wanting, liking and ease of drinking at a statistically significant level (p < 0.05). Again, Sip effect means that the evaluation scores change over sips while drinking. The p-value for product by sip interaction for wanting (p = 0.1767) was relatively lower, but not at a statistically significant level in the naïve panel.

Similar to the results from Phase 1 with the expert panel, the p-values of Sip effect by Product indicate that wanting for samples B1 (p = 0.0101) and B3 (p = 0.0001) significantly changed (decreased) while drinking, but not for sample B4 (p = 0.1893) (Table 3b). Notably, the product differences in wanting, which were almost nonexistent at the beginning, gradually became larger while drinking (Figure 6). This finding is consistent with the results of Phase 1 with the expert panelists. The LS-mean of wanting for sample B4 was significantly higher than that for sample B3 (p < 0.0001), and almost significantly tended to be higher than that for sample B1 (p = 0.1007) (Table 3a).

For the results with the naïve panel, wanting and liking were similar in that both of them detected a Sip effect (p < 0.0001 for wanting, p = 0.0040 for liking) and Product effect (p < 0.0001 for both wanting and liking) and differences in product LS-means (p < 0.05) at statistically significant levels (Table 3a). The correlation coefficients between wanting and liking were high throughout all of the sip cycles, which were 0.77, 0.85, 0.87, 0.89, 0.94, 0.89 and 0.89, computed over panelist by product (n = 126). As shown in Figure 7, in which the LS-mean scores over products in Table 3b are plotted in the order of sip, development of decreases in these scores seem to be in alignment with each other, and no strong evidence was observed in the naïve panel regarding whether asking about wanting was more powerful than asking about liking. Compared with the expert panelists, the naïve panelists tended to use a narrow range on the linear rating scale while giving higher wanting scores overall, and they were less inclined to give lower scores during the entire experiment.

Dynamic evaluation (TDS) of flavor characteristics

Figure 8a shows TDS difference curves between samples B4 and B3, which were respectively the highest and the lowest in wanting scores (Table 3a). The sensory attributes over the centerline indicate a significantly higher (p < 0.1) dominance rate for sample B4, and those below the centerline indicate a significantly higher (p < 0.1) dominance rate for sample B3 over the 30-second period, within each sip. (Note: In Figure 8a and Figure 8b, "within sip" analyses were used to focus on direct comparison of sensory perceptions p. 16 between two products.) Sample B4 scored significantly higher for "Refreshing Feel" in the beginning and for "No Dominance" at the end. In contrast, sample B3 scored significantly higher for "Bitter/Astringent" from the beginning to the end.

Figure 8b shows TDS difference curves between samples B4 and B1, which were respectively the highest and the second highest in wanting scores (Table 3a). More dominance could be seen for sample B4 in "Stimulating Feeling" and "Malt-like Flavor."

However, the difference between samples B4 and B1 was not as clear as that observed by the expert panel, who perceived sample B1 as being more "Hoppy."

To grasp a better understanding of the panelists' responses, we conducted a segmentation analysis for samples B4 and B1 (Figure 9). The left graph shows TDS difference curves among the panelists, who gave a higher wanting score for sample B4.

Conversely, the right graph shows curves among those that gave a higher wanting score for sample B1. Interestingly, perceptional differences were found between these two groups.

The panelists who scored sample B4 higher in wanting perceived it as less dominant for "Bitter/Astringent," whereas it was the opposite for those who scored sample B1 higher for wanting. Because of the small number of panelists (n = 42) in this study, these findings from the segmentation analysis should be examined with caution and need to be validated with a larger number of consumers.

Development of bitter/astringent dominance duration

Figure 10 shows the development of dominance duration for "Bitter/Astringent" for all three products. Dominance duration refers to the total number of seconds that "Bitter/Astringent" was selected as dominant in each sip. Sample B3 was significantly higher (p < 0.01) for the dominance duration of "Bitter/Astringent" compared to samples B1 and B4, and B3 showed a tendency to accumulate "Bitter/Astringent" over time during the drinking session. Considering the fact that sample B3 was lower in wanting compared to samples B1 and B4, it can be assumed that the build-up of "Bitter/Astringent" could lead to low drinkability.

Wanting and volume of beer actually consumed

Figure 11a shows the volume of beer actually consumed by the expert panelists in Phase 1. Samples B2 and B4 tended to be consumed more than samples B1 and B3, but not at a statistically significant level because of the large variance observed among the panelists. By contrast, a significant difference in wanting scores was observed between the products (p < 0.05) (Table 2a). Therefore, in this case, asking about wanting was more useful for discriminating products than collecting data on the total volume consumed. p. 17 Similar results were found in Phase 2 with the naïve panelists (Figure 11b). No significant differences in consumed volume of beer were observed, while the trend in consumed volume was in line with the wanting scores (Table 3a). However, significant differences (p < 0.05) were found in wanting scores between products (Table 3a), with an indication that asking about wanting outperformed measuring the total volume of consumption in terms of discriminating products.

[4] Discussion

The present work aimed at developing a new method of sensory evaluation for beer drinkability, which can be widely and easily applied in consumer tests. On the construct of beer drinkability defined as "the will of drinking," a new method called the "Multiple-sip Drinkability Test" was developed based on TDS paired with dynamic wanting to drink continuously. In the present study, with no lengthy training, both the expert panelists and the naïve panelists were able to conduct TDS repeatedly while drinking a full portion of beer up to 500 mL or 350 mL, respectively. The panelists were able to understand TDS and implement it properly after receiving only 5 minutes of instruction. This is in line with the suggestions of [START_REF] Monaco | Temporal dominance of sensations: A review[END_REF] and [START_REF] Schlich | Temporal dominance of sensations (TDS): A new deal for temporal sensory analysis[END_REF]. Furthermore, the participants in this study only needed to follow the instructions displayed on PC screens to perform their evaluations readily and intuitively on a web site specifically allocated for each respondent.

These aspects of the present study will contribute as part of a widely applicable approach to sensory and consumer research for beer drinkability in CLTs.

To develop new, successful products, companies should gain a deep understanding of "the voice of the consumer" in the early stage of product development; however, this step is often ignored or poorly executed [START_REF] Van Kleef | Consumer research in the early stages of new product development: a critical review of methods and techniques[END_REF]. Koster (2003) raised issues concerning researchers' bias of subject consistency and possibly misleading outputs from consumer studies that rely only on single hedonic evaluation. The results from the present study were in agreement with Koster's statement. By measuring dynamic wanting while drinking a full portion of beer, product differences in wanting, which were almost nonexistent at the beginning, were found to gradually become larger while drinking. Investigations were also conducted on the panelists' responses for both wanting and liking asked dynamically over sips to find a relationship between these two evaluation scales. Phase 1 results with the expert beer panel showed a superiority of measuring wanting over liking in terms of identifying product differences over time. In contrast, no large differences were observed between these two evaluations in Phase 2 with the naïve panel, who used a relatively narrow range on the linear rating scale. We restricted the maximum volume of consumption to 350 mL in Phase 2 with the naïve panel (see section 2.1.3. Rationale behind the test p. 18 designs on maximum consumption volume); however, increasing the volume of maximum consumption up to 500 mL might lead consumer panelists to use a broader range of the linear rating scale for wanting, which could result in better discrimination of beers at the end of drinking. Furthermore, when considering that some consumer groups, such as heavy drinkers are likely to express their "will" of drinking beer continuously in a clearer attitude than to show their appreciation toward a beer, wanting would probably be a more valuable evaluation scale if a researcher needs to choose one of these two scales for studying beer drinkability.

The test results also indicated that ease of drinking at each sip could lead to "wanting to drink continuously," in other words, beer drinkability. This finding is useful from the perspective of product development, particularly during the early stage when many prototypes need to be tested. By using this knowledge, asking about the ease of drinking for just a portion of a beer sample, rather than the full volume every time, could work as a good predictor of beer drinkability for the purpose of screening prototypes, allowing the researcher to move on to further steps with a decreased number of candidates.

Since the focus in the present work was mostly methodological and not to investigate details of beer flavors, we conducted the tests with a relatively small number of panelists.

However, in addition to the development of the methodology, which enabled the discrimination of beers in terms of drinkability, the conducted study also elicited the flavor characteristics of beer with high drinkability. The results indicated that a product with less standout flavor, thereby producing fewer build-up effects on sensory perceptions, could be a beer with higher drinkability. In other words, the greater the sensory load produced by a beer, the less one wants to drink it continuously. These findings are in agreement with the results of some previous beer studies [START_REF] Guinard | Sensory determinants of the thirst-quenching character of beer[END_REF][START_REF] Mattos | Beer drinkability -A review[END_REF], 2006;[START_REF] Davies | Malt -a vital part of the brewer's palette[END_REF][START_REF] Greenhoff | Consumer measurement of drinkability[END_REF][START_REF] Kojima | Relationships among throat sensation, beer flavor, and swallowing motion while drinking beer[END_REF].

The ultimate goal for the investigation of beer drinkability was to maximize consumers' enjoyment of drinking beer. Since the present evaluation included only four commercial products marketed in Japan and a limited number of panelists, more tests with designed prototypes sampled by general consumers on a larger scale are necessary in order to clarify further the factors affecting beer drinkability. Since the effectiveness of using the "Multiple-sip Drinkability Test" was validated with consumers, it will be possible to further investigate the impacts of various factors such as ingredients, recipes and brewing technologies by manipulating those variables when making prototypes for consumer tests.

This study, particularly in Phase 2 with consumers, also showed the possibilities of perceptional differences and directional differences for highly drinkable beers depending on consumer segments. Applying this method with a large number of target consumers would p. 19 be beneficial for marketing and product development in the beer industry.

Results from the tests with the expert and the naïve panels showed that asking about wanting was more useful for discriminating products than collecting data on the total volume consumed. One of the reasons that no significant difference in the total consumption volume was observed among the products was because of the large variance observed among the panelists. Another reason was because of the small variance in the total consumption among the products for each panelist. Possibly, with a limited amount of consumption up to 500 mL or 350 mL, "the will of drinking" can be more readily captured by simply asking about wanting at a conscious level rather than letting a panelist show it by drinking behavior at a subconscious level. Since the maximum amount of a beer sample was the normal volume consumed daily by a panelist, there might have been psychological barriers to stop drinking a test sample unless its flavors strongly discouraged a panelist's will of drinking continuously.

This may also suggest that there could be inertia in beer drinking behavior; that is, beer could be a type of drink that is consumed continuously without a specific strong feeling of wanting while drinking. However, the reason for this finding remains unclear and warrants further investigation.

In the present study, the panelists were instructed to only eat non-topping salt crackers plain crackers with no salt topping while they were drinking the beer samples. However, considering beer drinking contexts in real life, further investigations of beer drinkability "with food" would add more value for product development and marketing purposes in the future. [START_REF] King | The effect of meal situation, social interaction, physical environment and choice on food acceptability[END_REF] reported that overall liking of a flavored iced tea significantly increased when it was served together with a salad and a pizza compared with the overall liking of the tea alone. [START_REF] Galmarini | Use of multi-intake temporal dominance of sensations (TDS) to evaluate the influence of cheese on wine perception[END_REF] conducted a study involving multi-intake TDS to evaluate the influence of cheese on wine perception, and the results of their study showed that the dominance duration of astringency and sourness for a red wine was reduced by cheese consumption between sips of the wine. These previous investigations suggest an effectiveness of taking into consideration the possibility of "meal context" affecting beer drinkability. With the effectiveness of using the "Multiple-sip Drinkability Test" with consumers in an ad libitum consumption setting demonstrated in the present study, it would be worth expanding this protocol to search for the optimal pairing with foods in the construct of beer drinkability for consumers.

[5] Limitations and further research

According to [START_REF] Mattos | Recent review on beer drinkability[END_REF]Moretti (2005, 2006), there are four different effects of beer drinkability: sensory, cognitive, post-ingestive and post-absorptive. Among these, our focus was on the sensory aspect of drinkability. For measuring it at a conscious level, the p. 20 quantities of consumption in the present study were limited to 500 mL. Consequently, it would not be possible to discuss the results from the aspects of post-ingestive or post-absorptive, which would require participants to drink large quantities of beer in one session. The consumer panelists in Phase 2 drank a maximum of 350 mL of each sample, which is the volume of a full portion of a regular can available in Japan. Therefore, the present method with consumers has a limitation that it could at most estimate the power to evoke wanting for the second 350 mL can. As mentioned in section "2.1.1. Test design of Phase 2," 2.1.3. Rationale behind the test designs on maximum consumption volume, however, the majority of beer consumers in Japan do not consume more than two cans of beer in one session at home. This is why the authors believe that this method is a consumer-relevant approach. In terms of product discrimination, increasing the maximum consumption volume up to 500 mL in future studies could result in better discrimination of beers.

In the present study, each panelist conducted their evaluation of beer individually in an isolated sensory booth. They were allowed to read magazines as they wanted during a test so that they could feel at ease; however, the test environment was not ideally designed to be or to make them feel as if they were in a "real" consumption context. As recently reported [START_REF] Jaeger | Consumption context in consumer research: methodological perspectives[END_REF][START_REF] Nijman | The effect of consumption context on consumer hedonics, emotional response and beer choice[END_REF], consumption context could be one of the key factors affecting beer drinkability. The present method was useful in assessing beer drinkability with consumers, so it would be valuable to evaluate beers in some different consumption contexts or evoked contexts by manipulating test conditions in future studies. It should also be mentioned that the test samples were served in plastic cups, although consumers usually drink beer in beer glasses or directly from cans in real life. This might have an effect on perceived sensation, possibly caused by mouthfeel when taking a sip, amount of beer taken in each sip, changes in beer temperature while drinking, and so forth.

Depending on the study objectives, this aspect should be taken into consideration when designing tests for future research.

As mentioned previously, the focus in this study was on the sensory aspect of beer drinkability. Thus, no list was provided for the panelists to assess their emotions while drinking beer samples. Given that the emotional aspect was proven to be effective in differentiating beers beyond liking [START_REF] Cardello | Cognitive and emotional differentiators for beer: An exploratory study focusing on "uniqueness[END_REF][START_REF] Gomez-Corona | Measuring the drinking experience of beer in real context situations. The impact of affects, senses, and cognition[END_REF]Jaeger et al. 2017;[START_REF] Jaeger | Supplementing hedonic and sensory consumer research on beer with cognitive and emotional measures, and additional insights via consumer segmentation[END_REF][START_REF] Silva | Effect of adding hop aroma in beer analysed by temporal dominance of sensations and emotions coupled with temporal liking[END_REF], the authors are considering further studies that incorporate measurements of emotions into the current protocol, such as a combination of TDS and Temporal Dominance of Emotions [START_REF] Jager | Temporal dominance of emotions: Measuring dynamics of food-related emotions during consumption[END_REF]) paired with dynamic wanting to better understand the construct of beer drinkability for consumers.

p. 21 [6] Conclusion

A new method called the "Multiple-sip Drinkability Test" was developed to evaluate beer drinkability defined as "the will of drinking," based on Temporal Dominance of Sensations paired with dynamic wanting. To the best of our knowledge, this is the first published methodology with consumers in an ad libitum setting, which could be widely and easily applied in central location tests to obtain a better understanding of beer drinkability.

The present method enabled the discrimination of beers in terms of drinkability, and the results revealed the importance of monitoring dynamic wanting over sips. It was found that product differences in wanting, which were almost nonexistent at the beginning, gradually became larger while drinking. The results of this study also indicated that a product with less standout flavor, thereby producing fewer build-up effects on sensory perceptions, could be a beer with higher drinkability. In other words, the greater the sensory load produced by a beer, the less one wants to drink it continuously.

Since the present work was mostly methodological with a relatively small number of panelists, more work will be required to clarify further the factors that affect beer drinkability for target consumers on a larger scale. This could be achieved by testing designed prototypes with this evaluation method to investigate the impacts of changing variables, such as, ingredients, recipes and brewing technologies.

[Acknowledgements]

Figure 1 .Figure 2 .

 12 Figure 1. Test flow of "Multiple-sip Drinkability Test."

Figure 3 .

 3 Figure 3. Development of ease of drinking -Expert Panel Product by Sip (Means ± Standard Error x 2; replicates pooled).

Figure 4 .Figure 4 .

 44 Figure 4. Development of "wanting" compared with "liking": Sip Cycle LS-Means over products -Expert Panel

Figure 5 .

 5 Figure 5. Development of sensory perceptions: TDS Band Plot and Products' characteristics.

Figure 6 .

 6 Figure 6. Development of wanting -Naïve Panel Product by Sip (Means ± Standard Error x 2).

Figure 7 .

 7 Figure 7. Development of wanting compared with liking: Sip Cycle LS-Means over products -Naïve Panel.

Figure 8a .

 8a Figure 8a. TDS difference curves of the samples B4 and B3 -Naïve panel.

Figure 8b .

 8b Figure 8b. TDS difference curves of the samples B4 and B1 -Naïve panel.

Figure 9 .

 9 Figure 9. TDS difference curves of the samples B4 and B1 by wanting segmentation -Naïve panel.

Figure 10 .

 10 Figure 10. Development of Duration: Bitter/Astringent -Naïve Panel Dominance duration means with their 95% confidence level.

Figure 11a .

 11a Figure 11a. Volume of beer actually consumed by the expert panel (Mean ± Standard Error x 2).

Figure 11b .

 11b Figure 11b. Volume of beer actually consumed by the naïve panel (Mean ± Standard Error x 2).

Figure # Title 1 Figure 1 . 2 Figure 2 .

 1122 Figure # Title 1 Figure 1. Test flow of "Multiple-sip Drinkability Test." 2 Figure 2. Development of "wanting" -Expert Panel Product by Sip (Means ± Standard Error x 2; replicates pooled). 3 Figure 3. Development of "ease of drinking" -Expert Panel Product by Sip (Means ± Standard Error x 2; replicates pooled). 4 Figure 4. Development of "wanting" compared with "liking": Sip Cycle LS-Means over products -Expert Panel. 5 Figure 5. Development of sensory perceptions: TDS Band Plot and Products' characteristics. 6 Figure 6. Development of "wanting" -Naïve Panel Product by Sip (Means ± Standard Error x 2). 7 Figure 7. Development of "wanting" compared with "liking": Sip Cycle LS-Means over products -Naïve Panel. 8a Figure 8a. TDS difference curves of the samples B4 and B3 -Naïve panel. 8b Figure 8b. TDS difference curves of the samples B4 and B1 -Naïve panel. 9 Figure 9. TDS difference curves of the samples B4 and B1 by wanting segmentation -Naïve panel. 10 Figure 10. Development of Duration: "Bitter/Astringent" -Naïve Panel Dominance duration means with their 95% confidence level. 11a Figure 11a. Volume of beer actually consumed by the expert panel (Mean ± Standard Error x 2). 11b Figure 11b. Volume of beer actually consumed by the naïve panel (Mean ± Standard Error x 2).

Table 1

 1 ABV, IBU, Linalool and sensory descriptions of beer samples used in this study. Less standout flavors, Light finish (Note: ABV = alcohol by volume. IBU = international bitterness unit. ppb = parts per billion.) (Note: Information about alcohol content was obtained from the product package. Bitterness and linalool were analyzed in the R&D center at Asahi Breweries, Ltd. Sensory descriptors were obtained from the results of quantitative descriptions and sensory comments, both of which were acquired from the Asahi expert beer sensory panel.)Table 2aANOVA of dynamic wanting, liking, ease of drinking and residual sensation: Repeated Mix Model (1/2) -Expert Panel -Using Restricted Maximum Likelihood (REML) algorithm with first-order heterogeneous auto-regressive covariance structure among sips Means with two different letters are significantly different (p < 0.05). ANOVA of dynamic wanting, liking, ease of drinking and residual sensation: Repeated Mix Model (2/2) -Expert Panel -Using Restricted Maximum Likelihood (REML) algorithm with first-order heterogeneous auto-regressive covariance structure among sips

		Alcohol
		content	Bitterness	Linalool
	Sample	(% ABV)	(IBU)	(ppb)	Sensory descriptions
	B1	5	22.5	21.3	Hoppy, Malty, Bitter
	B2	5	19.5	1.5	Less standout flavors, Light finish
	B3	5	29	2.4	Malty, Bitter, Full body
	B4	5	19.5	1.2

Table 3a

 3a ANOVA of dynamic wanting, liking and ease of drinking: Repeated Mix Model (1/2) -Naïve Panel -Using Restricted Maximum Likelihood (REML) algorithm with first-order heterogeneous auto-regressive covariance structure among sips Means with two different letters are significantly different (p < 0.05). ANOVA of dynamic wanting, liking and ease of drinking: Repeated Mix Model (2/2) -Naïve Panel -Using Restricted Maximum Likelihood (REML) algorithm with first-order heterogeneous auto-regressive covariance structure among sips

	Table 3b
		p-values of tests of fixed effects Sip Cycle LS-Means			Product LS-Means p-values of	p-values for comparing products p-values of Sip Effect by Product
	Descriptor Descriptor	Sip 1	2	3	Product 4	5	Product*Sip 6	7	B1 Sip Effect B3	B4 B1	B3	B1-B3	B1-B4 B4	B3-B4
	Wanting Wanting	<0.0001 7.09 6.79 6.46 6.23 6.15 6.14 5.85 <0.0001 0.1767	6.52b <0.0001	5.69a	6.95b 0.0101	<0.0001 0.1007 0.0001 0.1893	<0.0001
	Liking Liking	0.0040 7.03 6.81 6.58 6.40 6.28 6.28 6.24 <0.0001 0.5063	6.74b 0.0040	5.70a	7.11b 0.1616	<0.0001 0.1346 0.0084 0.4305	<0.0001
	Ease of Drinking Ease of Drinking	0.0041 7.03 6.82 6.67 6.51 6.40 6.42 6.11 <0.0001 0.6762	6.80b 0.0041	5.66a	7.23b 0.4283	<0.0001 0.1037 0.0172 0.1261	<0.0001

We thank all the volunteer panelists who participated in our tests. This research was funded by Asahi Breweries, Ltd.

We would also like to thank the reviewers who contributed to improve significantly the quality of the manuscript. p. 22


Elodie Marguillier

Rémi Beranger

Ronan Garlantézec

Jean Leveque

Linda Lassel

Chloé Rousseau

Vincent Lavoue

M.D. Maela Le Lous

Jean Levêque

Chloe Rousseau

Endocrine disruptors and pregnancy: Knowledge, attitudes and practice of perinatal health professionals. A French multicentre survey

Keywords: Endocrine disruptors and pregnancy: knowledge, attitudes and practice of perinatal health professionals. A French multicentre survey Endocrine disruptors, Environmental toxicants, Reproductive health, Environmental health, Perinatal health professionals, Attitudes, Risk perception Endocrine disruptors, Environmental toxicants, Reproductive health, Environmental health, Perinatal health professionals, Attitudes, Risk perception

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

1

Abstract

Introduction

Endocrine disruptors (ED) such as phthalates or bisphenol A are ubiquitous and pregnant women and children are particularly vulnerable. Perinatal health professionals are well-placed to inform pregnant women about the risks. We set out to evaluate perinatal health professionals' knowledge of ED and the information they give during pregnancy.

Material and Methods

We invited midwives, obstetrician-gynecologists (OB/GYN), general practitioners (GP), and general medicine and OB/GYN residents to respond to a short Google survey between August and November 2018 by email using perinatal network.

Results

Out of 4100 questionnaires sent, 1650 completed questionnaires were returned and analyzed. The participation rate was 41% with the following distribution: midwives (n=1215, 74%), OB/GYN residents (n=102, 6%), OB/GYNs (n=129, 8%), GPs and residents in general medicine (n=204, 12%), in private and public hospitals in France. Only 181 of the respondents thought they were well-informed about ED including 160 midwives (11%). Most of the responding professionals reported not to give any information during pregnancy (n=946, 57.3%). Midwives (n=452, 37.2 %), people >50 years (n=104, 41.6%) and people working in private structures (n=451, 34.9%) were the most likely to give information, mainly orally. Overall, 346 (74.2%) of the respondents considered that information about health risks of endocrine disruptors was important and most of them wished they were better informed (n=1532, 92.9%).

Conclusion

Our study suggests that perinatal health professionals do not have enough medical information, training or tools to communicate about the risks associated with ED to pregnant women and consequently cannot educate them. Research is needed to further explore the risks and support prevention of environmental exposure for pregnant women.

Introduction

Since the discovery of the estrogen-like effect of chlordecone in rats [START_REF] Hammond | Estrogenic activity of the insecticide chlordecone (Kepone) and interaction with uterine estrogen receptors[END_REF] in the 80's, endocrine disruptors have been at the center of a lively and permanent debate attracting considerable scrutiny by the media. There is no question that they pose a major threat to public health. At an international level, different definitions of an endocrine disruptor co-exist and are constantly being re-evaluated. The most common definition used is that by the WHO in 2002: "an endocrine disruptor is an exogenous substance or mixture that alters functions of the endocrine system and consequently causes adverse health effects in an intact organism, or its progeny" [START_REF]WHO | Global assessment of the state-of-the-science of endocrine disruptors[END_REF]. The effects observed involve signaling pathways, regulation or physiological mechanisms as opposed to classic direct toxicity mechanisms.

Phtalates, bisphenol A and parabens are the most famous of them. They are associated with a potential deterioration of the male reproductive health [START_REF] Chin | Association of urinary concentrations of early pregnancy phthalate metabolites and bisphenol A with length of gestation[END_REF] [START_REF] Bonde | The epidemiologic evidence linking prenatal and postnatal exposure to endocrine disrupting chemicals with male reproductive disorders: a systematic review and metaanalysis[END_REF]. Others substances like pesticides may also affect thyroid function [START_REF] Calsolaro | Thyroid Disrupting Chemicals[END_REF][10] or like PBDEs that affects neurological functions [11][12] [13] [START_REF] Meeker | Exposure to environmental endocrine disrupting compounds and men's health[END_REF].

[4][5][6][7]
Of course, the diethylstilbestrol tragedy (DES) serves as a stark reminder that chemical substances acting like a hormone do not only have the potential to seriously affect the health of people exposed but also to produce irreversible disorders in their offspring [START_REF] Cravedi | The concept of endocrine disruption and human health[END_REF]. Moreover, it is becoming more and more obvious that the pre-and post-natal periods are critical windows of exposure, especially the first 1000 days [START_REF] Black | Early childhood development coming of age: science through the life course[END_REF].

It would appear that both health professionals and patients lack adequate knowledge about endocrine disruptors [START_REF] Marie | Perception of Environmental 14 Risks and Health Promotion Attitudes of French Perinatal Health Professionals[END_REF]. Several health professionals are concerned: midwives, gynecologistobstetricians (OB/GYN) and residents in gynecology-obstetrics (OB/GYN residents), and general practitioners (GP) and residents in general medicine. These professionals are in the front line to inform patients and prevent the risks associated with environmental exposure to endocrine disruptors. Nevertheless, the topic is not specifically covered during medical school.

The objective of this study was to assess perinatal health professionals' knowledge about endocrine disruptors and the information given to pregnant women about the associated risks during pregnancy.

Material and Methods

Design

We created a 7-item questionnaire using Google form which was sent by e-mail to midwives, OB/GYNs, GPs, OB/GYN residents and general medicine residents throughout France (Metropolitan and Overseas Territories). The survey was sent between August and November 2018 and followed up once with a reminder. Our study was exempted from IRB approval, as it wasn't dealing with patients.

Health professionals contacted

Health professionals were identified using mailing lists from the prenatal diagnostic network (mainly in Brittany, about 200 people contacted), mailing lists from perinatal networks (in Brittany and in Auvergne-Rhône-Alpes, about 400 people contacted), OB/GYNs working in various University Hospitals (32 French University Hospitals, about 500 professionals contacted), the residents' office of the same University Hospitals (about 600 OB/GYN residents and residents in general medicine contacted), via the professional board of midwives (about 2300 midwives contacted) or via social networks (Facebook, mainly for residents, GPs and OB/GYNs, about 100 people contacted).

Data Collection

The first part of the questionnaire collected the demographic characteristics of the respondents (age, profession, area of activity, working structure). The second part focused on attitudes, beliefs and practices about the risks associated with endocrine disruptors: level of knowledge about the endocrine disruptors, how often they informed their patients, type of information given (orally or with written support), the importance they accorded the subject, and their interest in obtaining additional information.

Statistical analysis

Qualitative variables were described by size (N) and percentage (%) for each category, quantitative variables were presented using mean +/-standard deviation (SD). Quantitative data were compared using the chi2 test and Fisher's exact test when appropriate. If there were more than two groups with an overall difference, 2 by 2 comparisons were made with a Bonferroni correction.

A p-value <0.05 was selected to denote significance. The analyzes were performed with the SAS software, version 9.4.

Results

Of a total of 4100 questionnaires sent, 1650 completed questionnaires were returned and analyzed. The participation rate was 41% (Figure 1) with most of the respondents being hospital or freelance midwives (n=1215, 73.6%). There were also responses from GPs/residents in general medicine (n=204, 12.4%), OB/GYNs (n=129, 7.8%), and OB/GYN residents (n=102, 6.2%).

The sociodemographic and geographical characteristics of the respondents are detailed in Table 1. More than half of them were under 40 years (n=1113, 67.5%). All OB/GYN residents and general medicine residents were part of this category as were 763 (63%) of the midwives and 72 (56%) of the OB/GYNS.

Most of the respondents worked as freelancers or for the private sector 1348 (82%) vs 302 (18%) for a public hospital (university or non-university public hospitals). A total of 1131 midwives (93.1%) worked for the private sector as well as 166 GPs (81.4%). All the residents were working in a public hospital as were most of the OB/GYNs (n=80, 62%).

Most of the respondents felt that they were not sufficiently informed about the risks of endocrine disruptors during pregnancy (n=1407, 85%); 181 (11%) of them thought they were pretty well informed, mostly midwives (n=160, 13.2%); and 62 (4%) did not express an opinion. (Table 2). Midwives expressed more concern about endocrine disruptors than the other professionals: 356 (29.3%) thought the question was "very important" versus five (4.9%) OB/GYN residents, 18 (14%) OB/GYNs and 32 (15.7%) GPs. Nine-hundred and forty-six (57.3%) provided no information about the risk of endocrine disruptors to their patients (Table 2).

In a comparison based on age, those over 50 years declared they were more informed (n=43, 17.2%) than those under 30 years (yes: n=44, 8.4%) (p<0.001). Respondents over 50 years old are also more likely to give information to patients (answers yes: n=104, 41.6%), than those under 30 years-old (n=112, 21.3%; p<0.05), those between 30 and 40 years old (n=189, 32.2% p <0.05), and those between 40 and 50 years-old (n= 84, 29.3%, p <0.05) (Table 3).

Comparing the workplace, health professionals working as freelancers or in the private sector declared to be better informed (yes: n=168, 10.2%) than those working in a public structure (n=13, 0.8 %) (p <0.001). Office-based professionals (n=451, 34.9%) also declared they gave more information than those working in a university hospital (n=19, 10.2%, p <0.05), in a private hospital (n=8, 14.8%, p <0.05) or non-university public hospital (n=11, 9.6%, p <0.05) (Table 4).

The information (when provided) was mainly given orally (n=356/466, 76.4%) than in written supports (n=110/466, 23.6%). There was no significant difference between the different health professionals, nor between the different age groups or work structures in the type of information given (Tables 2 to 4). Twenty-three people did not answer this question (n=22 for midwives, and n=1 for OB/GYNs).

Finally, most of the responding health professionals said they would like to have more information about the subject (n=1532, 92.9%). Only 38 (2.3%) of them did not want more information and 80 (4.8%) of them were undecided.

Discussion

This study is one of the first in France to focus on the knowledge and practices of health professionals about the risks of endocrine disruptors for pregnant women. Our results suggest that, although little information is given to patients, in practice, most perinatal health professionals feel that it is "quite" to "very" important to provide information about the risk of endocrine disruptors to pregnant women. Thus, while most health professionals recognized the importance of the subject and the impact of endocrine disruptors on human health, there appears to be a lack of training and tools at their disposal which prevents them from being able to provide sufficient information and advice to the women during their pregnancy.

The most frequent endocrine disruptor are the phthalates that are contained is plastic packagings, cosmetics, paints, clothes, toys. They are toxic for the human reproduction, and can cause early puberty in both genders [START_REF] Golestanzadeh | Association of phthalate exposure with precocious and delayed pubertal timing in girls and boys: a systematic review and meta-analysis[END_REF]. We can also cite the bisphenol A, estrogeno-mimetic, contained in cans, bottles, or receipts, which is associated with all types of cryptorchidism [START_REF] Fisher | Maternal serum concentrations of bisphenol A and propyl paraben in early pregnancy are associated with male infant genital development[END_REF].

Midwives, people over 50 years, and those working in a private structure were more likely to inform women, although mainly orally. We had very few answers from the OB/GYNs (7.8%).

They may have less time to answer the survey and feel less concerned by the subject. They also may have less time per patient to discuss this problem as they deal with patients with highpregnancy-risks conditions. Another explanation may be the fact that the profile of patients attending public hospital is different, with high-risk pregnancies and time-consuming management.

The younger populations of health professionals, especially those under 30 years old, felt less concerned about the issue and seem to attach less importance to it. However, a majority of people were interested in obtaining additional information on the subject.

The strength of this study is in the power as we were able to collect a large number of completed questionnaires from perinatal health professionals throughout France (metropolitan and Overseas Territories). The large and unselected sample of professionals provided a complete vision of endocrine disruptor risk prevention during pregnancy follow-up.

The study suffers from a selection bias, which is typical to such transversal studies. It was easier to contact midwives than OB/GYNs or GPs, which is why midwives are over-represented.

Nevertheless, the high number of midwives who participated might be because they felt more concerned by the subject and that, consequently, they responded to the questionnaire more readily.

The geographical distribution of the responding health professionals was also heterogeneous. This was because some areas were more accessible than others (such as the west or south-east areas of France). In addition, some areas have a small number of health professionals compared to others, which may explain a low answer rate.

A similar French study (the PERI-HELPE study, Perception of Risk-HEaLth Professionals & Environment Study) the aim of which was to assess the perception of environmental risks for pregnant women among health professionals, was conducted in 2014 in the region of Auvergne by a team from Clermont-Ferrand [START_REF] Marie | Perception of Environmental 14 Risks and Health Promotion Attitudes of French Perinatal Health Professionals[END_REF]. The study included interviews of 188 people (OB/GYNs, midwives and GPs). Few health professionals in this study claimed to question pregnant women about their exposure to chemicals or to advise them to reduce exposure. The most common toxins named were carbon monoxide, pesticides and lead. Lack of information, training and scientific evidence were the most frequently cited reasons to justify the little information given to pregnant women. These results are concordant with our findings.

Another larger self-reported questionnaire study was conducted in 2017 in the south of France (PACA area) with 962 participants (41.1% of midwives, 25.6% of OB/GYNs, pediatricians and GPs) and 11% of nurses) [18]. The results obtained were similar to ours. Fear of the patient's reaction and lack of a reliable solution to manage environmental risks were mentioned as major barriers.

In 2014, a team in the United States conducted a study among OB/GYN members of the American Congress of Obstetricians and Gynecologists (ACOG) [START_REF] Stotland | Counseling patients on preventing prenatal environmental exposures--a mixed-methods study of obstetricians[END_REF]. Most (78%) of the 2514 health professionals who responded believed that they could reduce the risk of exposure to endocrine disruptors of pregnant women by advising patients However, 50% of them said that they rarely asked pregnant women about their environment and practices, and fewer than 20% did it frequently. Only around 7% believed they had been sufficiently trained about the subject. The barriers found were similar to those commonly named in French studies: lack of knowledge or clear evidence on the subject, doubt about the ability of patients to effectively reduce their exposure to risk, and fear of causing anxiety to the patient.

To complete our study, it would be interesting to interview midwives, pediatricians and GPs about whether they give information about the risks of endocrine disruptors during the postpartum period and early childhood. Young children are equally as vulnerable as pregnant women and the compulsory follow-up period of newborns and children could be an ideal opportunity to communicate about such risks.

Another question to consider is whether parents feel they are sufficiently informed and to what extent. Rouillon et al. studied this point using a qualitative psycho-social survey conducted in 300 women (pregnant or postpartum) in the Vienne Department (France) between August 2015 and March 2016 [START_REF] Rouillon | Determinants of Risk Perception Related to Exposure to Endocrine Disruptors during Pregnancy: A Qualitative and Quantitative Study on French Women[END_REF]. The objective was to assess the patients' knowledge, attitudes (risk perception), behaviors and anxiety towards endocrine disruptors. They reported an average endocrine disruptor knowledge score of 42.9 ± 9.8 out of 100 revealing a poor knowledge of the risks. However, most of the women (92%) felt ready to change their habits to avoid environmental risks. Anxiety increased significantly after answering the survey and to a greater extent when knowledge of endocrine disruptors was high (OR=2.30, 95% CI [1.12-4.71]).

Conclusion

Most of the health professionals who took part in our study recognized the importance of the risk of endocrine disruptors in pregnant women and the role they have to play in preventing these risks. However, they feel that they lack sufficient training about these risks and few of them inform patients properly. This is a real public health issue. Medical education with clear guidelines and adapted tools to communicate to patients are necessary to support the preventive role of all healthcare professionals managing vulnerable patients exposed to environmental risks. National recommendations are in progress.

To overcome the lack of action from the public authorities, many initiatives are taking place at a regional or departmental level: proposals for training for health professionals and patients "Environment and Health" congresses, and specialized consultations such as those organized by the ARTEMIS (Aquitaine ReproducTion Enfance Maternité et Impact en Santé environnement) center in Bordeaux. Santé Publique France also build a website on the subject : (https://agir-pourbebe.fr/). At an individual level, it is possible for any health professional to put informative posters in their waiting rooms, distribute information flyers, or smartphone applications (either already made and easy to print out from the internet or made by the professional him/herself) or at least give pregnant women some oral information about the risks of endocrine disruptors. NS : Not Significant. Yo : years old.

Figure 1 .

 1 Figure 1. Flow Chart

Table 1 .

 1 Sociodemographic and geographical characteristics of respondents

	GP : General practitionners
	OB/GYN : Obstetrics and Gynecology
		4000 Questionnaires sent
		1650 answers (41%)
	1215 Midwives	204 GP (residents	129 Obstetricians	102 OB/GYN
	(73.6%)	or seniors) (12.4%)	(7.8%)	Residents (6.2%)

Table 2 .

 2 Responses about endocrine disruptors according to type of perinatal health professional.

			Residents in
			Gynecology-	Gynecologists-
		Midwives (n=1215,	obstetrics (n=102,	obstetricians (n=129,	General practitioners or residents in
		73.6 %)	6.2%)	7.8 %)	General Medicine (n=204, 12.4%)	P
	Q1.Do you think you are sufficiently informed about the					< 0.001
	risks of endocrine disruptors in pregnant women?
	No n(%)	1003 (82.6%)	99 (97.1%)	116 (89.9%)	189 (92.6%)
	Yes	160 (13.2%)	2 (2.0%)	11 (8.5%)	8 (3.9%)
	Don't know	52 (4.3%)	1 (1.0%)	2 (1.6%)	7 (3.4%)
	Q2. Do you (or another person working in the same					< 0.001
	structure) give any information on the risk of endocrine
	disruptors during pregnancy? »
	No n(%)	604 (49.7%)	88 (86.3%)	89 (69.0%)	165 (80.9%)
	Yes	452 (37.2%)	2 (2.0%)	21 (16.3%)	14 (6.9%)
	Maybe	159 (13.1%)	12 (11.8%)	19 (14.7%)	25 (12.3%)
	Q3.If yes, what kind of information do you give?	430	2	20	14	NS
	Oral information n(%)	330 (76.7%)	2 (100.0%)	13 (65.0%)	11 (78.6%)
	Written information	100 (23.3%)	0 (0.0%)	7 (35.0%)	3 (21.4%)
	Q4. How

important is the information provided to the pregnant woman during her follow-up on the risk of endocrine disruptors? »

					< 0.001
	1 : not important n(%)	41 (3.4%)	18 (17.6%)	7 (5.4%)	18 (8.8%)
	2	113 (9.3%)	25 (24.5%)	26 (20.2%)	27 (13.2%)
	3	312 (25.7%)	37 (36.3%)	43 (33.3%)	76 (37.3%)
	4	393 (32.3%)	17 (16.7%)	35 (27.1%)	51 (25.0%)
	5 : very important	356 (29.3%)	5 (4.9%)	18 (14.0%)	32 (15.7%)

Q5. Would you like more information about the risk of endocrine disruptors in pregnant women?

					0,01
	No n(%)	29 (2.4%)	1 (1.0%)	4 (3.1%)	4 (2.0%)
	Yes	1139 (93.7%)	89 (87.3%)	114 (88.4%)	190 (93.1%)
	Maybe	47 (3.9%)	12 (11.8%)	11 (8.5%)	10 (4.9%)
	NS : Not Significant

Table 3 . Responses about endocrine disruptors according to the age of the health professionals.

 3

	Age

Do you give (or is it given by another person working in the same structure)any information on the risk of endocrine disruptors during pregnancy? »

						< 0.001
	No n(%)	353 (67.1%)	325 (55.4%)	166 (57.8%)	102 (40.8%)
	Yes	112 (21.3%)	189 (32.2%)	84 (29.3%)	104 (41.6%)
	Maybe	61 (11.6%)	73 (12.4%)	37 (12.9%)	(17.6%)
	Q3 : « If yes, what kind of information ? »	107 (5)	180 (9)	78 (6)	101 (3)	NS
	Oral information n(%)	86 (80.4%)	142 (78.9%)	56 (71.8%)	(71.3%)
	Written information	21 (19.6%)	38 (21.1%)	22 (28.2%)	(28.7%)
	Q4 : «

How important is the information provided to the pregnant woman during her follow-up on the risk of endocrine disruptors? »

					< 0.001
	1 : not important n(%)	48 (9.1%)	24 (4.1%)	9 (3.1%)	(1.2%)
	2	73 (13.9%)	62 (10.6%)	37 (12.9%)	19 (7.6%)
	3	171 (32.5%)	161 (27.4%)	79 (27.5%)	(22.8%)
	4	145 (27.6%)	202 (34.4%)	77 (26.8%)	(28.8%)
	5 : very important	89 (16.9%)	138 (23.5%)	85 (29.6%)	(39.6%)
	Q5 : «

Would you like more information on the risk of endocrine disruptors in pregnant women? »

					NS
	No n(%)	8 (1.5%)	14 (2.4%)	8 (2.8%)	(3.2%)
	Yes	489 (93.0%)	549 (93.5%)	261 (90.9%)	233 (93.2%)
	Maybe	29 (5.5%)	24 (4.1%)	18 (6.3%)	(3.6%)

Table 4 .

 4 Responses about endocrine disruptors according to the place of activity.

		Activity structures
		2-University
	1-Office-based	hospital (n=187,	3-Private hospital	4-Non-University public
	(n=1294, 78.4% )	11.3%)	(n=54, 3.3%)	hospital (n=115, 7%)	P
	Q1 : «

Do you think you are sufficiently informed about the risks of endocrine disruptors in pregnant women? ? »

					<0.001
	No n(%)	1075 (83.1%)	177 (94.7%)	48 (88.9%)	107 (93.0%)
	Yes	163 (12.6%)	9 ( 4.8%)	5 ( 9.3%)	4 ( 3.5%)
	Don't know	56 ( 4.3%)	1 ( 0.5%)	1 ( 1.9%)	4 ( 3.5%)
	Q2 : « Do you give (or is it given by another				< 0.001
	person working in the same structure)any
	information on the risk of endocrine
	disruptors during pregnancy? »
	No n(%)	688 (53.2%)	142 (75.9%)	31 (57.4%)	(73.9%)
	Yes	451 (34.9%)	19 (10.2%)	8 (14.8%)	11 (9.6%)
	Maybe	155 (12.0%)	26 (13.9%)	15 (27.8%)	(16.5%)
	Q3 : « If yes, what kind of information ? »				NS
	Oral information n(%)	328 (76.5%)	14 (77.8%)	6 (75.0%)	8 (72.7%)
	Written information	101 (23.5%)	4 (22.2%)	2 (25.0%)	3 (27.3%)
	Q4 : «

How important is the information provided to the pregnant woman during her follow-up on the risk of endocrine disruptors? »

					< 0.001
	1 : not important n(%)	48 (3.7%)	23 (12.3%)	3 (5.6%)	10 (8.7%)
	2	126 (9.7%)	40 (21.4%)	6 (11.1%)	(16.5%)
	3	355 (27.4%)	55 (29.4%)	21 (38.9%)	(32.2%)
	4	408 (31.5%)	42 (22.5%)	17 (31.5%)	(25.2%)
	5 : very important	357 (27.6%)	27 (14.4%)	7 (13.0%)	(17.4%)
	Q5 : « Would you like more information on				NS
	the risk of endocrine disruptors in pregnant
	women? »
	No n(%)	32 (2.5%)	4 (2.1%)	1 (1.9%)	1 (0.9%)
	Yes	1208 (93.4%)	168 (89.8%)	48 (88.9%)	108 (93.9%)
	Maybe	54 (4.2%)	15 (8.0%)	5 (9.3%)	6 (5.2%)