The Food Choice Questionnaire: Factorial invariant over western urban populations?

Food Quality and Preference 17 (2006) 344–352 www.elsevier.com/locate/foodqual

The Food Choice Questionnaire: Factorial invariant over western urban populations? Audrey Eertmans a, An Victoir a, Guy Notelaers a, Greet Vansant b, Omer Van den Bergh a,* a

Department of Psychology, University of Leuven, Tiensestraat 102, B-3000 Leuven, Belgium b Department of Nutrition, University of Leuven, Herestraat 49, B-3000 Leuven, Belgium

Received 13 August 2004; received in revised form 22 February 2005; accepted 29 March 2005 Available online 4 June 2005

Abstract To assess the degree of measurement invariance of the Food Choice Questionnaire (FCQ) across western urban populations, it was filled out by demographically comparable samples in Canada (163 English speaking students, original version), Belgium (Flanders, N = 176, Dutch translation), and Italy (N = 163, Italian translation). Reliability of the FCQ-scales was moderate to good, but sometimes differed from the normative values. Item analysis pinpointed items with skewed distributions and low item-total correlations. Subsequent confirmatory and exploratory factor analyses revealed a suboptimal fit for the FCQ-model in all samples, with small to considerable divergences from the original configuration. The findings do not support the generalizability of the FCQÕs factor structure, but suggest that its items and underlying constructs may have different connotations across western urban populations. Explanations for the lack of convergence in factor structure and implications for research are discussed. Ó 2005 Elsevier Ltd. All rights reserved. Keywords: Food Choice Questionnaire; Measurement invariance; Factor structure; Cross-cultural; Western populations

1. Introduction Several models have been proposed to organize the wide variety of food choice determinants comprehensively (e.g., Eertmans, Baeyens, & Van den Bergh, 2001; Furst, Connors, Bisogni, Sobal, & Winter Falk, 1996), but actual empirical evidence on the relative importance of different food choice motives in various populations and situations remains rather scarce. An instrument useful to this aim is the Food Choice Questionnaire (FCQ), developed by Steptoe, Pollard, and Wardle (1995) in a demographically heterogeneous

*

Corresponding author. Tel.: +32 16 32 60 58; fax: +32 16 32 60 55. E-mail address: [email protected] (O. Van den Bergh). 0950-3293/$ - see front matter Ó 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2005.03.016

UK sample (N = 358). The FCQ contains 36 items, representing health and non-health related food characteristics. Respondents are instructed to rate the importance of each of these FCQ-items for their food choice ‘‘on a typical day’’ on a 4-point scale (1 = not at all important, 2 = little important, 3 = moderately important, and 4 = very important). The FCQ involves nine motivational dimensions or scales, each containing three to six items: Health, Mood, Convenience, Sensory Appeal, Natural Content, Price, Weight Control, Familiarity, and Ethical Concern. Steptoe et al. (1995) confirmed this 9-factor model in a second study (N = 358). They also found the FCQ-scales to have satisfactory test–retest reliability over a 2- to 3-week period (r = .71–.83), and to converge with measures of dietary restraint, eating style, the value of health, health locus of control, and personality factors. The authors

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concluded that ‘‘. . . within western urban populations, the FCQ provides the opportunity to assess a broad range of factors perceived as relevant to food selection.’’ In their UK samples, Steptoe et al. (1995) observed that Sensory Appeal, Health, Convenience and Price were rated as the most important among the food choice motives, while the other five were typically endorsed less strongly. They also report differences in food choice motives associated with gender, age and income. Further on, Steptoe and colleagues demonstrated that these demographic effects extended to self-reported food intake, with the motives acting as mediators (Pollard, Steptoe, & Wardle, 1998; Steptoe & Wardle, 1999). More recently, the FCQ has been translated to other languages. Lindeman and Va¨a¨na¨nen (2000), for example, assessed food choice motives in Finnish respondents and report a relative importance and gender effects similar to Steptoe et al.Õs (1995) findings. Cross-national comparisons in food choice motives have been made by Prescott, Young, OÕNeill, Yau, and Stevens (2002), between consumers from Japan, Taiwan, Malaysia and New Zealand. Thus far, however, research has not yet tested the cross-cultural validity of the FCQ. The cross-cultural validity of an instrument can statistically be defined as the degree of its measurement invariance across different populations. Measurement invariance refers to ‘‘whether or not, under different conditions of observing and studying phenomena, measurement operations yield measures of the same attribute’’ (Horn & McArdle, 1992, p. 117). Steenkamp and Baumgartner (1998) distinguish between six levels of measurement invariance within a framework based on the confirmatory factor analysis (CFA) model: (1) configural invariance (also factorial invariance; Meredith, 1993) requires identical patterns of zero and non-zero factor loadings in each population, indicating that the instrument measures the same constructs over populations (i.e., construct equivalence; Van de Vijver & Leung, 1997), (2) metric invariance assumes the matrix of factor loadings to be invariant across populations, indicating that the way in which the items of the questionnaire relate to the underlying constructs is the same across populations, (3) scalar invariance is characterized by equality of factor loadings and of item intercepts, implying that variables are measured on common interval scales and that cross-population differences in their means are due to differences in the means of the underlying constructs, (4) factor covariance invariance indicates that the constructs measured by the questionnaire are interrelated in an identical manner across populations, (5) factor variance invariance indicates that these constructs exhibit the same variation in different populations, and (6) error variance invariance requires the amount of measurement error in the observed variables to be invariant across populations, indicating that the items of the ques-

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tionnaire measure the underlying constructs with the same reliabilities across populations.1 Of these increasing levels of measurement invariance, scalar invariance has been considered a prerequisite for making meaningful comparisons of mean scores between cultures, nations or language groups (Meredith, 1993). As long as it is not established, there is no way to decide whether differences in observed means are caused by true differences in the underlying construct or merely by group-specific bias (e.g., differences in the way people from different countries respond to certain items). As a consequence, conclusions based on those scale scores are at best ambiguous and at worst erroneous. The aim of the present study was to examine the degree to which the factor structure of the FCQ is invariant across western urban populations. Account was taken of the guidelines for translating and adapting psychological instruments in multilingual studies (Van de Vijver and Hambleton, in Van de Vijver & Leung, 1997).

2. Materials and methods 2.1. Subjects and procedure Lecturers or research associates at the University of Pavia (Italy), the University of Leuven (Belgium, Flemish part) and McGill University (Canada, English speaking) administered paper-and-pencil questionnaires collectively to first year university students in Psychology during a course. Data were obtained from 170 Italian, 438 Belgian and 215 Canadian students. As these initial groups differed significantly as regards age and gender ratios, a subsample was drawn from each group in order to obtain more or less comparable samples as regards the gender ratio (approximately 33.3% male to 66.7% female) and the age range (below 30).2 As such, data from 163 Italian, 176 Belgian and 163 Canadian students (total N = 502) were withheld for further analyses. Table 1 describes these samples. 2.2. Material The Food Choice Questionnaire (FCQ; Steptoe et al., 1995) was used in its original version in the Canadian sample. Italian and Dutch versions were created through 1

For a mathematical presentation of the various levels of measurement equivalence, we refer to the article by Steenkamp and Baumgartner (1998). 2 In the initial pool of respondents, few Belgian (n = 2) and Italian students (n = 7) were aged above 30, while about one-fourth of Canadian students (n = 52) were older than 30. Also, the Belgian sample contained relatively more women (80.1% to 19.2% men) than both the Italian and the Canadian sample (approximately 33.3 % male to 66.7% female).

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Table 1 Description of participants in Italy, Belgium and Canada

Total number of respondents Men Women Age: Mean SD Range BMI: Mean SD Rangea

Italy

Belgium

Canada

163

176

163

52 (31.9%) 111 (68.1%) 21.25 1.70 19–28 21.37 2.96 13.67–34.25

56 (31.8%) 120 (68.2%) 18.30 .78 17–23 20.76 2.41 15.43–32.32

56 (34.4%) 107 (65.6%) 22.13 2.67 16–29 22.21 2.92 16.47–35.13

a The majority of participants (74.9% in Canada to 92.0% in Belgium) were normal weight (BMI 15.0–24.9).

translation and backtranslation performed by a translation agency to ensure accurate translation and maximize linguistic equivalence. Table 2 displays the original wording of items per scale. Participants rated the importance of each of these 36 FCQ-items on a 4-point scale (1 = not at all important, 2 = little important, 3 = moderately important, and 4 = very important). Scores on each of the FCQ-scales were computed by averaging (unweighted) item ratings per scale. 2.3. Data analysis Preliminary analyses included pairwise comparisons of each of the present samples with (1) Steptoe et al.Õs (1995) sample, and (2) every other present sample, as regards the reliabilities of the FCQ-scales. Item descriptive statistical parameters (mean and standard deviation) and item-total correlations per FCQ-scale were also computed to further establish the psychometric properties of the FCQ for the present data. According to Van de Vijver and Leung (1997), these analyses may detect aberrant items, i.e. items showing floor or ceiling effects in some of the samples, or not measuring the same construct in all groups. Next, measurement invariance of the FCQ across the present samples was assessed. A variety of techniques are available to this end: exploratory factor analysis, structural equation modelling, multidimensional scaling, and cluster analysis (see Van de Vijver & Leung, 1997). They all focus on the structure of the data, and typically consist of a pairwise comparison of factors or dimensions between groups. However, there is a general agreement that the multi-group confirmatory factor analysis model (CFA; Jo¨reskog, 1971) represents the most powerful and versatile approach. Steenkamp and Baumgartner (1998) discuss a hierarchical model comparison procedure, in which six models with increasing levels of constraint are tested (see also Section 1). We started by testing the most lenient model, representing the lowest level of invariance between groups: configural invariance. Zero and non-zero factor loadings

were specified in accordance with the path diagram provided by Steptoe et al. (1995, p. 276). As this basic model did not appear to converge, we did not proceed with testing more restricted models. Instead, we estimated the fit of Steptoe et al.Õs (1995) 9-factor FCQ-model in each of the present samples separately. When the output of these CFAÕs showed suboptimal fit and numerous modification indices, we performed an exploratory factor analysis to detect the structure underlying the FCQ-data in each of the samples.3 More precisely, we used principal axis factoring with the eigenvalue higher than 1 criterion for the choice of a factor number and the varimax normalized rotational strategy. All analyses were run in Lisrel 8.54 (Jo¨reskog & So¨rbom, 1996) and SPSS 12.0.

3. Results 3.1. Scale reliabilities and item statistics The internal consistencies of the FCQ-scales for the present data ranged from .56 to .87 (for Sensory Appeal, respectively Health in the Belgian sample), indicating moderate to good reliability (see Table 3).4 As compared to the values reported by Steptoe et al. (1995) for their normative sample, five motivational scales in the Italian sample (Health, Mood, Natural Content, Price, and Familiarity), three in the Belgian sample (Sensory Appeal, Natural Content, and Ethical Concern), and only one in the Canadian sample (Price) showed different reliability indices.5 Overall, Steptoe et al.Õs (1995) values tended to be higher. Item statistics (mean, standard deviation and item-total correlation) are added for each FCQ-scales (Steptoe et al., 1995) and country in Table 2. A few items

3 An alternative method consists of altering the model in accordance with the modification indices provided by the CFA output for one of the countries (e.g., the one with the worst fit or with the best fit), and assessing the measurement invariance of this respecified model over countries. We have explored this method, testing models with increasing levels of modifications, but failed to reach acceptable fit. 4 The following values were used to evaluate internal consistency: <.50 = unsatisfactory, .50–.70 = moderate, .70–.90 = good, >.90 = excellent. 5 Equality of reliabilities of FCQ-scales was tested in each pair of samples by computing (1 a1)/(1 a2), with a1 the reliability obtained for the first sample and a2 the reliability for the second sample. When the resulting value exceeded the critical value of the F-distribution with numerator df1 = N1 1 and denominator df2 = N2 1 (N1 being the size of the first sample and N2 the size of the second sample), the hypothesis of equal reliabilities was rejected (Van de Vijver & Leung, 1997). Equality was tested at the p < .01 significance level. For example, comparing the Belgian sample with Steptoe et al. (1995) sample as regards the internal consistency of Sensory Appeal, yielded a value of (1 .56)/(1 .30) or 1.47, which exceeded the critical F-value at the p < .01 level with (df1 = 175, df2 = 357) of 1.28.

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Table 2 FCQ-items (scale labels in italics): Means and standard deviations (SD) and item-total correlations (r) per country No.

Scale/item

Italy

FCQ1 22 29 10 27 30 9

Health Contains a lot of vitamins and minerals Keeps me healthy Is nutritious Is high in protein Is good for my skin/teeth/hair/nails etc. Is high in fibre and roughage

3.07 3.52 3.29 2.77 3.25 2.57

FCQ2 16 34 26 24 13 31

Mood Helps me to cope with stress Helps me to cope with life Helps me to relax Keeps me awake/alert Cheers me up Makes me feel good

FCQ3 1 15 28 35 11

Mean

Belgium r

Mean

r

Mean

.82 .69 .80 .81 .84 .89

.56 .58 .56 .36a .48 .41

2.70 3.07 2.88 2.24 2.35 2.13

.91 .88 .93 .92 .97 .87

.75 .68 .68 .71 .55 .68

2.91 3.51 3.29 2.66 2.93 2.40

.81 .73 .81 .86 .95 .91

.66 .65 .67 .51 .64 .52

2.63 2.64 2.28 2.63 2.82 3.35

.95 .99 .86 .96 1.04 .83

.58 .57 .53 .43 .47 .36a

1.56 1.77 1.95 1.94 2.39 2.48

.73 .87 .84 .84 1.02 .98

.61 .54 .67 .66 .51 .65

2.06 2.01 2.17 2.45 2.65 2.82

1.01 .98 .91 1.02 .98 1.01

.67 .65 .70 .35a .57 .57

Convenience Is easy to prepare Can be cooked very simply Takes no time to prepare Can be bought in shops close to where I live or work Is easily available in shops and supermarkets

2.61 2.74 2.47 2.63 2.91

.88 .89 .92 .92 .91

.62 .72 .55 .45 .46

2.68 2.61 2.34 2.28 2.69

.93 .92 .92 1.01 .96

.73 .77 .69 .52 .60

3.06 2.93 2.63 2.82 3.08

.83 .85 .99 .92 .90

.65 .59 .55 .50 .49

FCQ4 14 25 18 4

Sensory Appeal Smells nice Looks nice Has a pleasant texture Tastes good

3.06 2.69 2.90 3.61

.94 .92 .86 .66

.57 .58 .50 .34a

3.05 2.71 1.89 3.88

.91 .94 .81 .40

.45 .46 .33a .18a

2.87 2.45 2.77 3.78

.91 .96 .89 .50

.50 .49 .41 .23a

FCQ5 2 5 23

Natural Content Contains no additives Contains natural ingredients Contains no artificial ingredients

3.14 3.25 3.15

.90 .82 .89

.46 .53 .56

1.99 2.60 2.11

.82 .90 .84

.48 .56 .66

2.09 2.64 2.27

.92 .98 .99

.62 .59 .68

FCQ6 6 36 12

Price Is not expensive Is cheap Is good value for money

2.71 2.56 2.96

.84 .95 .92

.44 .52 .24a

2.76 2.49 3.03

.81 .89 .86

.73 .75 .62

2.85 2.47 3.04

.81 .91 .90

.63 .56 .54

FCQ7 3 17 7

Weight control Is low in calories Helps me control my weight Is low in fat

2.48 2.80 2.86

.94 1.01 .79

.57 .59 .61

1.86 2.03 2.25

.88 .97 .90

.70 .70 .71

2.54 2.66 2.88

1.03 1.06 .97

.71 .64 .70

FCQ8 33 8 21

Familiarity Is what I usually eat Is familiar to me Is like the food I ate when I was a child

2.21 2.29 1.67

.87 1.02 .80

.42 .46 .32a

2.06 2.27 1.43

.93 .88 .67

.53 .45 .32a

2.15 2.35 1.96

.93 1.02 .91

.65 .51 .45

FCQ9 20 32 19

Ethical Concern Comes from countries I approve of politically Has the country of origin clearly marked Is packaged in an environmentally friendly way

1.66 2.46 2.72

.95 1.08 .92

.28a .48 .50

1.40 1.38 2.18

.74 .64 .87

.50 .46 .26a

1.59 1.71 2.26

.87 .92 .96

.52 .44 .34a

a

SD

Canada SD

SD

r

Item-total r < .40.

appeared to have low item-total correlations (<.40) with the respective FCQ-scale (see Table 2). This was especially the case for the ÔtasteÕ item (item no. 4): it was weakly correlated with the Sensory Appeal scale in each of the samples. Its high mean and low standard deviation suggested a ceiling effect and skewed distribution of ratings, which was confirmed by additional statistics

(Italy: Skewness = 1.83, Kurtosis = 3.42; Belgium: Skewness = 4.09, Kurtosis = 19.77; Canada: Skewness = 2.52, Kurtosis = 7.42). Other items (e.g., item no. 20—‘‘comes from countries I approve of politically’’) also showed a skewed distribution in one or more of the samples, though less severely as that observed for ÔtasteÕ (Skewness >1 but <2).

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Table 3 Reliability of the FCQ-scales (CronbachÕs a) for Steptoe et al.Õs (1995) sample, and the Italian, Belgian and Canadian sample FCQ-scale

Steptoe et al.a

Italy

Belgium

Canada

1—Health 2—Mood 3—Convenience 4—Sensory Appeal 5—Natural Content 6—Price 7—Weight Control 8—Familiarity 9—Ethical Concern

.87 .83 .81 .70 .84 .82 .79 .70 .70

.75 .75 .78 .71 .70 .59 .75 .59 .60

.87 .83 .85 .56 .74 .84 .84 .62 .58

.83 .82 .78 .62 .79 .75 .82 .71 .62

a

Reliability indices are reported from Steptoe et al. (1995, Study 1).

3.2. Fit of the 9-factor FCQ-model Table 4 displays the following goodness-of-fit indices per country: v2 (the normal theory maximum likelihood chi-square), CFI (Comparative Fit Index), NNFI (Nonnormed Fit Index), and RMSEA (Root Mean Square Error of Approximation). A significant chi-square suggests that a significant amount of observed covariance between items remains unexplained by the model, while non-significance implies a good fit to the data (Cole, 1987). The CFI (Bentler, 1990) and NNFI (Bentler & Bonnet, 1980) are incremental fit indexes, representing the proportionate improvement in the model fit by comparing the target model with a baseline model. CFI and NNFI values greater than 0.90 indicate an adequate fit. The RMSEA (Steiger, 1990) takes account of the error of approximation in the population, as it is based on the idea that it is unreasonable to assume that the model holds exactly in the population. A RMSEA value of 0.05 indicates a close fit and values up to 0.08 represent reasonable errors of approximation in the population (Browne & Cudeck, 1993). The goodness-of-fit summary indicates that the simple 9-factor model, in which each item of the FCQ loaded on a single factor, did not provide an adequate fit for any of the samples. 3.3. Country-specific factor structures The principal axis method extracted 10 factors for every group. Table 5 shows eigenvalues of factors, as well as factor loadings of FCQ-items. The factor soluTable 4 Goodness-of-fit indices of the FCQ-model for the Italian, Belgian and Canadian sample, and for the Pooled sample Sample

v2 (df)

CFI

NNFI

RMSEA (95%CFI)

Italy Belgium Canada

1911.04 (558)*** 1642.43 (558)*** 1440.22 (558)***

.70 .85 .82

.66 .83 .80

.10 (.09–.10) .09 (.08–.10) .09 (.08–.09)

***

p < .001.

tions described 63.9%, 69.1% and 67.3% of total variance in the Italian, Belgian and Canadian FCQ-data, respectively. When compared to the structure reported by Steptoe et al. (1995) (see first column of Table 5), it appears that several factors were replicated, with items showing high loadings (>.70) and negligible cross-loadings (<.40). This was the case for Ethical Concern in the Italian sample, Weight Control in both the Belgian and the Canadian sample, and Health and Price in the Canadian sample. Other components also contained the same items as in Steptoe et al.Õs (1995) solution, but one or several items loaded (>.40) on other factors as well. These were the factors Convenience in the Italian sample, Familiarity in both the Italian and Canadian sample, and Mood in the Belgian sample. Several factors lacked one item, as compared to those reported by Steptoe et al. (1995), such as Mood in the Italian and Canadian solutions (items 31 and 24 respectively), Sensory Appeal in the Belgian solution (item 4; see also further), and Ethical Concern in the Canadian solution. Other factors appeared to be supplemented with one item. This could be seen for Sensory Appeal in both the Italian and the Canadian sample, and concerned a Mood item in both cases (items 24 and 13 respectively). In the Italian sample, the Health item ‘‘is high in fibre and roughage’’ (item 9) loaded on Weight Control, and the Convenience item ‘‘can be bought in shops close to where I live or work’’ (item 35) loaded on the Price factor. This latter item loaded on the Familiarity factor in the Belgian solution. It should be noted that all these additional items still loaded on the original FCQ-factor too. Where a factor included more than one additional item, it could be interpreted as a new factor or even as a higher-order factor. In the Canadian factor solution, for example, the Natural Content items loaded on the same factor as the Ethical Concern items. In the Italian sample, in contrast, the FCQ-items assessing Natural Content and Health loaded on a single factor. This was also the case for the Belgian sample, though less clearly: two items of the former FCQ-scale still had a cross-loading on a factor that further contained the third Natural Content item. In the Belgian solution, the two Convenience items, referring to the availability of food (items 11 and 35), merged with the Price items. The resulting factor could be interpreted as Ôaccessibility of foodÕ, in both financial and spatial ways. The other items, assessing the Ôease of preparationÕ (items 1, 15 and 28), loaded high (>.70) on a separate factor. A similar factor could be observed in the Canadian solution. A few factors were more difficult to interpret as they related aberrant items (i.e., items no longer loading on the original factor) to items with non-negligible crossloadings (>.40). Such factors were observed for the Italian sample (factor 9) and the Canadian sample

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Table 5 Results from the exploratory factor analyses on the Italian, Belgian and Canadian FCQ-data: Factor loadings of (numbered) items, and interpretations and eigenvalues of factors Factors and items of Steptoe et al. (1995)

Italy

1—Health

1—Health and Natural Content 29 10 5 2 22 23 30 9a 27

5.83

2—Mood 16. Helps me to cope with stress 34. Helps me to cope with life 26. Helps me to relax 24. Keeps me awake/alert 13. Cheers me up 31. Makes me feel good

2—Convenience 15 1 28 11a 35a

3—Convenience 1. Is easy to prepare 15. Can be cooked very simply 28. Takes no time to prepare 35. Can be bought in shops close to where I live or work 11. Is easily available in shops and supermarkets

3—Mood 34 16 26 13

22. 29. 10. 27. 30. 9.

Contains a lot of vitamins and minerals Keeps me healthy Is nutritious Is high in protein Is good for my skin/teeth/hair/nails etc. Is high in fibre and roughage

24a

4—Sensory Appeal

4—Weight Control

14. 25. 18. 4.

3 7 17 9a

Smells nice Looks nice Has a pleasant texture Tastes good

Belgium

Canada

1—Health (and Natural Content) 22 27 10 9 29 30 5a 23a

7.84

3.41 .86 .80 .77 .48 .41

2—Accessibility 36 6 12 11 35a

4.42 .81 .79 .78 .60 .48

2—Ease of Preparation 1 28 15

3.19 .84 .82 .74

2.95 .79 .73 .61 .60

3—Mood 16 34 24 31

2.78 .75 .75 .72 .71

3—Mood 34 26 16 31

3.09 .81 .75 .71 .64

.70 .69 .68 .64 .63 .59 .51 .47 .46

.46

2.20 .79 .78 .75 .48

.80 .80 .76 .73 .68 .61 .56 .56

1—Health

6.98

22 29 30 10 27 9 19a

.74 .74 .74 .72 .68 .58 .33

26

.69

13a

.52

13a

.47

19

.32

4—Weight Control 17 3 7

2.11 .85 .83 .78

4—Natural Content and Ethical Concern 2 23 32 5 20 19a

2.44 .80 .78 .67 .65 .57 .36

5—Natural Content 2. Contains no additives 5. Contains natural ingredients 23. Contains no artificial ingredients

5—Ethical Concern 32 19 20

1.94 .70 .69 .63

5—Ethical Concern 20 32

1.66 .82 .78

5—Weight Control 3 7 17

1.92 .85 .76 .76

6—Price 6. Is not expensive 36. Is cheap 12. Is good value for money

6—Familiarity 8 33 21a

1.79 .80 .77 .38

6—Familiarity 33 8 21 35a

1.44 .77 .74 .54 .43

6—Familiarity 8 33 21

1.73 .81 .79 .61

7—Weight Control 3. Is low in calories 17. Helps me control my weight 7. Is low in fat

7—Sensory Appeal 14 25 18 4 24a

1.37 .76 .74 .68 .46 .40

7—Ease of Preparation 15 1 28 13a

1.34 .86 .84 .81 .53

7—Price 6 12 36

1.50 .87 .78 .67

8—Familiarity 33. Is what I usually eat 8. Is familiar to me 21. Is like the food I ate when I was a child

8—Price 6 36 35a 12a

1.29 .82 .73 .41 .40

8—Sensory Appeal 14 25 18

1.23 .77 .69 .55

8—(Rest)b 24 21a

1.26 .58 .49

9—Ethical Concern 20. Comes from countries I approve of politically

9—(Rest)b 11a

1.16 .56

9—Natural Content 2

1.05 .71

9—Availability 11

1.09 .62

(continued on next page)

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Table 5 (continued) Factors and items of Steptoe et al. (1995)

Italy

32. Has the country of origin clearly marked 19. Is packaged in an environmentally friendly way

12a 21a 10—Good Feeling 31

Belgium .50 .64 1.07 .62

19 23a 5a 10—Taste 4

Canada .54 .56 .43 1.00 .82

35 20 10—Sensory Appeal 14 4 13 18 25

.62 .49 1.01 .66 .65 .60 .55 .54

a

Items with cross-loadings. Only cross-loadings >.40 are included, unless the item did not load >.40 on any of the factors (see item 19 in the Canadian solution). b (Rest) indicates factors difficult to interpret.

(factor 8). Item 31 of the Mood-scale (i.e., ‘‘the food makes me feel good’’) loaded on a separate factor in the Italian solution, and the item tapping the importance of a good taste (item 4) appeared as a separate factor in the Belgian solution. Finally, it can be noted that the Ethical Concern item referring to the environmentally package of food did not load clearly (>.40) on any factor in the Canadian solution. Instead, it showed negligible cross-loadings on three factors: Natural Content and Ethical Concern, Health, and Mood. In sum, the factor solutions of the present samples appeared to differ from the configuration obtained by Steptoe et al. (1995). Some divergences were rather small, whereas other incongruities were large enough to reinterpret factors. Of all factor solutions, the Canadian appeared to be the most similar to Steptoe et al.Õs (1995) FCQ-model.

4. Discussion The goal of the present study was to assess the degree to which the Food Choice Questionnaire (FCQ; Steptoe et al., 1995) shows measurement invariance across western urban populations. To this end, the FCQ was translated via translation–backtranslation, and administered to comparable samples as to relevant background variables (education, gender and age), within the same procedure. In doing so, we aimed at limiting item bias (e.g., caused by translation errors), sample bias (i.e., incomparability of samples) and administration bias (e.g., due to the differential expertise of administrators) within our study (Van de Vijver & Leung, 1997). The FCQ-scales appeared to be moderately to highly reliable for the present data, though sometimes less than for Steptoe et al.Õs (1995) normative sample. Item analysis revealed moderated item-total correlations and skewed item distributions, especially for the ÔtasteÕ item of the Sensory Appeal scale. It can be noted that severely skewed scores on items assessing the importance of taste have been observed for other food-related

questionnaires as well, such as for the food-related lifestyle instrument (Brunsø & Grunert, 1995; OÕSullivan, Scholderer, & Cowan, 2005; Scholderer, Brunsø, Brendahl, & Grunert, 2004). The preliminary analyses already suggested that Steptoe et al.Ôs (1995) FCQ-items, selected for UK samples, may not have been understood in the same way when translated to Italian and Dutch, or by a same-language group living in Canada. This was corroborated by the results of the subsequent factor analyses. No good fit was found for Steptoe et al.Õs (1995) 9-factor model in any of the samples. The exploratory factor analyses shed further light on the divergences of the present data structures from the configuration obtained by Steptoe et al. (1995). Some were rather small, whereas other incongruities were large enough to reinterpret factors. Among the latter, the merging of Natural Content with either Health (in Italy and Belgium) or Ethical Concern (in Canada) could be noticed. If the solutions of the principal axis method had suggested a subset of factors to be cross-nationally invariant (as compared to the FCQmodel), partial configural invariance could have been tested, as well as higher levels of measurement equivalence (see Steenkamp & Baumgartner, 1998). However, this was not the case: several FCQ-factors were reproduced, but they varied between countries. Overall, the Canadian FCQ-data were most similar to Steptoe et al.Õs (1995) as regards their psychometric properties and underlying structures, whereas the Italian were least similar. Several explanations can be hypothesized for the lack of convergence in the interpretation of FCQ-items and constructs (i.e., item respectively construct bias). First, the item content may have incidentally acquired differential connotative meaning across cultures. At construct level, this may have resulted in a partial overlap in the definitions of constructs (Van de Vijver, 2003). For example, the merging of Natural Content with Health in the Italian and Belgian sample suggests foodÕs natural content (or the absence of artificial ingredients or additives) is viewed as conditional for its healthfulness. In Canada, it appears to be more a matter of ‘‘Ethical

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Concern’’. In contrast, the factor structure reported by Steptoe et al. (1995) suggests that the presence of artificial ingredients did not necessarily interfere with the healthfulness of foods as conceived by their UK samples. Second, construct bias may have stemmed from another source: incomplete coverage of all relevant aspects of the constructs or construct underrepresentation (Van de Vijver, 2003). In reference to Ethical Concern, for example, Lindeman and Va¨a¨na¨nen (2000) have already proposed to complement the FCQ with several scales measuring different ethical food choice motives (viz., Ecological Welfare, Political Values, and Religion). Third, the divergence from the FCQ-model may indicate an evolution that has occurred in the meaning attributed to food characteristics since the development of the FCQ. It can be noted that several major crises struck the European agricultural sector between 1995 and 2001 (when the data were collected), involving the contamination of feedstuff, food-producing animals and food products. Changes in food attitudes (e.g., animal welfare concerns) have been reported, both over the time periods that included major media coverage on these issues (e.g., the BSE crisis) and persisting afterwards (e.g., Bernues, Olaizola, & Corcoran, 2003; Harvey et al., 2001; Hunt & Frewer, 2001; Smith, Young, & Gibson, 1999). It would be interesting to reinvestigate the structure of the FCQ in the UK, one of the hardest hit countries. Whichever explanation holds, it must be noted that several FCQ-factors (e.g., Natural Content, Health, and Ethical Concern) were moderately but significantly correlated in Steptoe et al.Õs (1995) studies. Minor differences in correlations between their items may thus have easily resulted in the divergences observed in the present samples (e.g., the merging of Natural Content with Health or Ethical Concern). The finding that the Canadian factor solution, rather than the Belgian or Italian, was most similar to Steptoe et al.Õs (1995) model, may not be surprising, considering that the potentially confounding factor of language was held constant in its comparison to the UK solution. In summary, the results of our preliminary test do not support Steptoe et al.Õs (1995) assumption that the Food Choice Questionnaire has a factor structure that would generalize from their UK samples across western urban populations (i.e., that it would show configural invariance). Instead, they suggest that the FCQ-items and the underlying constructs may have different connotations in other western cultures, whether it concerns English speaking or non-English speaking countries. This implies that cross-cultural differences between food choice motives reported and interpreted by previous research (e.g., Prescott et al., 2002) should not be taken for granted. Although methodologists acknowledge the difficulty of establishing scalar, metric or even complete (as opposed to partial) factorial invariance (e.g.,

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Jo¨reskog, June 2002, personal communication; Van de Vijver & Leung, 1997), they emphasize that comparisons across populations can only be made after the level of invariance has been established for the scale on which scores are reported, and only at that level (Van de Vijver & Leung, 1997, p. 51). Future research may design generalizability studies that are fuller replications of Steptoe et al.Õs (1995) original study (e.g., with larger, more heterogeneous samples), providing more robust tests of the scalar invariance of the Food Choice Questionnaire (Van de Vijver & Leung, 1997). Should they offer support for scalar invariance, this would allow discussing differences between countries as to absolute levels of food choice motives (mean FCQ-scale scores). Should they only find metric invariance to hold, analyses involving means would have to be carried out separately within each of the countries under study. Comparisons between cultures as to the relative importance of various food choice motives within countries (i.e., differences in ranks of motives) would then still be allowed and provide valuable information to health promotion and marketing. Acknowledgements The present study was conducted as part of an international project funded by the Danone Institutes. The authors are grateful to Dr. Hellas Cena at the University of Pavia, Italy, and to Prof. Dr. Katherine Gray-Donald and Mrs. Leticia Troppmann at McGill University, Canada for their collaboration in the data collection. References Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 217, 238–246. Bentler, P. M., & Bonnet, D. G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–606. Bernues, A., Olaizola, A., & Corcoran, K. (2003). Labelling information demanded by European consumers and relationships with purchasing motives, quality and safety of meat. Meat Science, 65(3), 1095–1106. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage Publications. Brunsø, K., & Grunert, K. G. (1995). Development and testing of a cross-culturally valid instrument: Food-related lifestyle. Advances in Consumer Research, 22, 475–480. Cole, D. A. (1987). Utility of confirmatory factor analysis in test validation research. Journal of Consulting and Clinical Psychology, 55, 584–594. Eertmans, A., Baeyens, F., & Van den Bergh, O. (2001). Food likes and their relative importance in human eating behavior: Review and preliminary suggestions for health promotion. Health Education Research, 16(4), 443–456. Furst, T., Connors, M., Bisogni, C. A., Sobal, J., & Winter Falk, L. (1996). Food choice: A conceptual model of the process. Appetite, 26, 247–266.

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