Psychometric Examination of the Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) among Spanish Adolescents and Young Adults

Citation: Paterna, A.; Alcaraz-Ibáñez, M.; Sicilia, A. Psychometric Examination of the Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) among Spanish Adolescents and Young Adults. Nutrients 2023,15, 626. https:// doi.org/10.3390/nu15030626 Academic Editor: Iole Tomassini Barbarossa Received: 22 December 2022 Revised: 19 January 2023 Accepted: 22 January 2023 Published: 26 January 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). nutrients Article Psychometric Examination of the Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) among Spanish Adolescents and Young Adults Adrian Paterna †, Manuel Alcaraz-Ibáñez *,† and Alvaro Sicilia Health Research Centre and Department of Education, University of Almería, 04120 Almería, Spain *Correspondence: [email protected] † These authors contributed equally to this work. Abstract: The Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) has been frequently used within the context of research on eating disorders (ED). Although both long (BEECOM-L) and short (BEECOM-S) versions of the instrument exist, their psychometric properties have not yet been concurrently investigated across different populations in terms of age and gender. The present study aimed to compare the psychometric properties of both the BEECOM-L and the BEECOM-S among Spanish male and female non-clinical adolescents and young adults. Data from 4 samples including 1213 middle school and college students enrolled in 10 education centers from southern Spain (age ranging from 12 to 35 years, M age = 17.796, SD age = 4.796, 53% females) were analyzed using factorial, correlation, and regression analysis techniques. Results provided evidence that support the reliability, measurement invariance according to age and gender, and convergent/incremental validity for the scores from both the BEECOM-L and BEECOM-S. Concerning factorial validity, marginally acceptable and adequate goodness-of-fit indices were obtained for the BEECOM-L and BEECOM-S, respectively. The BEECOM-S proves to be a psychometrically sound instrument with potential value for assessing social comparisons focused on body, eating, and exercise in non-clinical adolescents and young adults from Spain. Keywords: eating disorders; eating pathologies; disordered eating; social comparison; body image; psychometrics; factorial validity 1. Introduction Eating disorders (ED) are a group of increasingly prevalent psychiatric pathologies that, having a relative bad prognosis, account for significant morbidity and mortality in Western countries [ 1 – 3 ]. In this vein, the fact that around a third of women and half of men who meet the clinical criteria for ED do not seek professional help [ 4 ] means that the social and economic burden of ED extends beyond healthcare costs [ 5 ]. As a result, identifying modifiable risk factors for ED on which to focus treatment and prevention efforts has been a major research priority [6–8]. A cognitive process that has been consistently identified as a modifiable risk factor for ED is the tendency towards body/appearance-related social comparison [ 9 – 12 ]. However, an emerging line of research has begun to demonstrate that further consideration of comparisons focused on actions aimed at improving body appearance, such as eating or exercise behavior, may provide deeper insight into the cognitive processes underlying ED [ 13 – 16 ]. This body of research has been built around the only self-reported quantitative measure proposed to date for the purpose of assessing the three facets of ED-related social comparisons outlined above (i.e., the Body, Eating, and Exercise Comparison Orientation Measure, BEECOM) [17]. Findings from several research studies have been consistent in supporting the psychometric properties of the BEECOM scores in terms of both reliability and converNutrients 2023,15, 626. https://doi.org/10.3390/nu15030626 https://www.mdpi.com/journal/nutrients Nutrients 2023,15, 626 2 of 18 gent/incremental validity [ 14 , 16 – 18 ]. In contrast, the available evidence on the factorial validity of the instrument is far less conclusive. For example, evidence has been provided that supports the original long 18-item structure consisting of 6 items each for the three lower-order factors (body-, eating-, and exercise-related comparison orientation) and a higher-order factor (ED-related comparison orientation) on a sample of non-clinical U.S. college females [ 17 ]. However, this factor structure is not supported by the results of two subsequent studies. Firstly, the one conducted in a non-clinical sample of Iranian university male and female students with the aim of providing a Farsi translation of the original long version of the BEECOM (hereinafter BEECOM-L) revealed gender differences in the distribution of several items across the lower-order factors [ 18 ]. Secondly, the one conducted on a sample of U.S. females in their young adulthood revealed that several items did not load clearly on their theoretically relevant lower-order factors in the clinical subsample in terms of ED [ 16 ]. This finding led the authors to propose a short version of the instrument (BEECOM-S) consisting of 9 items (3 for each lower-order factor) instead of 18 items, whose adequate fit was subsequently corroborated in a second non-clinical subsample of otherwise similar socio-demographic characteristics to the first one [16]. Taken together, the available evidence suggests that (i) the content of BEECOM might be subject to gender-specific interpretations, which would make this instrument unsuitable for making comparisons across groups based on this variable and (ii) that the revised short version of the instrument is likely to outperform the original long version in psychometric terms. However, the limited number of studies from which such evidence is drawn, coupled with the particular socio-demographic profiles of the participants included in these studies, precludes generalizing the above conclusions to other populations of interest in the context of ED. A clear example of such a population would be adolescent girls and boys under 17 (the minimum age of individuals on which the psychometric properties of the BEECOM have been tested so far [ 17 ]), who represent an important target group for ED prevention efforts [ 19 ]. The latter is clear in the light of the evidence suggesting that (i) 25–50% of ED onset occurs before the age of 17 years and (ii) that the differences in prevalence levels traditionally observed in favor of females are decreasing [4]. Simultaneous examination of the psychometric properties of both versions of the BEECOM in a wider range of populations in terms of age and gender than hitherto considered may provide valuable information on the applicability of the instrument and, in particular, with regard to the comparative psychometric performance of the two versions. Thus, should evidence confirming the superior performance of the short version be obtained, then its use could be recommended. This would mean halving the application time of the BEECOM, which may decrease the response burden and increase the response rate of surveys including this instrument [ 20 ]. In addition, evidence derived from examining whether the BEECOM scores are invariant across populations consisting of individuals of different gender and age would allow recommendations to be made concerning the appropriateness of using these scores in two main situations: firstly to make reasonably unbiased comparisons between these population groups [ 21 ] and secondly in the context of conducting regression analysis involving moderation testing, which—as a result of considering group membership as the moderating variable instead of conducting subgroup analyses—would benefit from an increased level of statistical power [22]. In view of the above, the main objective of the present study was to compare the psychometric properties of the scores derived from the BEECOM-L and the BEECOM-S in terms of factorial validity, reliability, measurement invariance according to age and gender, and convergent/incremental validity. Given the paucity of research on the topic and the inconclusive nature of the available evidence, no hypothesis was advanced concerning which version of the instrument would show better overall psychometric performance. According to findings from previous research, it was hypothesized that the BEECOM scores would show high levels of reliability in terms of internal consistency ( α ) or construct reliability ( ρ ) (i.e., >0.80) [ 14 , 17 , 18 ]. It was also expected that, providing evidence of convergent validity, the BEECOM scores would be positively correlated with two main groups of variables: Nutrients 2023,15, 626 3 of 18 firstly with comparisons strictly focused on physical appearance, with effect sizes expected to fall within a range of r= 0.53 to r= 0.76) [ 17 ] and secondly with several ED outcomes, these including (i) overall ED symptoms, with effect sizes expected to fall within a range of r= 0.37 to r= 0.71) [ 16 , 18 ]; (ii) weight and shape concerns, with effect sizes expected to fall within a range of r= 0.38 to r= 0.77) [ 13 , 17 , 23 ]; and (iii) dietary restraint, with effect sizes expected to fall within a range of r= 0.20 to r= 0.46) [ 13 , 18 ]. Finally, it was hypothesized that, consistent with the results of previous research providing evidence of incremental validity for the BEECOM scores [ 16 , 17 ], these would account for additional variance in all three ED outcomes under consideration over and above that accounted for by both body mass index (BMI) and the scores derived from a measure strictly focused on appearance-related comparisons. In the event that evidence was obtained to support measurement invariance of the BEECOM scores across age and gender groups, a secondary goal of the present study was to examine gender and age differences in ED-related comparison orientation. It was hypothesized that, in line with previous research examining appearance-focused comparisons [ 10 , 12 , 24 ], small-to-intermediate-sized differences would be found in favor of groups consisting of females and younger adults. 2. Materials and Methods 2.1. Sample Size Calculation The sample size of the study was drawn using two different procedures. Firstly, a Monte Carlo simulation was conducted in Mplus version 7 (http://www.statmodel.com/ index.shtml, accessed on 21 December 2022) [ 25 ] to determine the sample size needed to obtain reliable estimations for the parameters involved in the confirmatory factor analyses (CFA) [ 26 ]. This simulation was conducted taking into account the main features of the most complex model (i.e., the one corresponding to the BECCOM-L) in terms of the number of factors/indicators, the mean values expected for factor loadings, and the possible absence of normality of the data. The results of this simulation suggested that, assuming a missing data value of 1%, a sample size of 250 participants per group was sufficient to provide 80% statistical power in the estimation of the model parameters. Secondly, a power analysis using G*Power version 3.1 (Heinrich Heine University Düsseldorf, Düsseldorf, Germany) [ 27 ] was conducted to determine the sample size needed to conduct the regression analyses. The results suggested that that 1021 participants were needed to detect small effect sizes (i.e., f 2 = 0.025; α = 0.05 two tailed; 95% power) in regression models involving 11 predictors. 2.2. Participants A total of 1297 high school, middle school, and college students enrolled in 10 different education centers from southern Spain were invited to participate in the study using a non-probabilistic sampling technique. The following inclusion criteria were applied: (i) for the older age group, having a similar age to that of the participants included in the studies in which the BEECOM-L and the BEECOM-S were proposed (i.e., between 17 and 35 years old) [ 16 , 17 ]; (ii) for the younger age group, being aged between 12 and 16 years old; and (iii) for both age groups, to provide informed consent to participate in the research, which was additionally requested from parents or legal guardians for individuals aged under 18 years old. Failure to provide informed consent either by themselves (n= 18) or by parents or legal guardians (n= 29) led to the exclusion of 47 potential participants. Data were excluded from the analyses when the participants (i) reported having a clinical diagnosis in terms of ED (n= 10); (ii) identified themselves as non-binary in terms of gender (n= 14); or (iii) failed the embedded validity check question (n= 13). Thus, data from 1213 participants who mostly identified themselves in terms of ethnicity as White/Caucasian (96%) were analyzed considering the following four subgroups: (i) younger females (n= 287; M age = 14.066, SD age = 1.262); (ii) older females (n= 360; M age = 21.369, SD age = 3.490); (iii) younger males (n= 295; M age = 14.190, SD age = 1.127); and (iv) older males (n= 271; Mage = 20.926, SDage = 3.845). Nutrients 2023,15, 626 4 of 18 2.3. Instruments 2.3.1. Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) We used our Spanish translation (see File S1) of the BEECOM [ 17 ]. The 18 items comprising the instrument are rated on a 7-point scale from 1 (never) to 7 (always). The items are grouped into 3 factors consisting of 6 items (long version) or 3 items (short version) that assess body comparisons (e.g., “I compare my body shape to that of my peers”), eating comparisons (e.g., “During meals, I compare what I am eating to what others are eating”), and exercise comparisons (e.g., “I pay close attention when I hear peers talking about exercise in order to determine if I am exercising as much as they are”). Higher scores imply higher frequency of body, eating, and exercise comparisons. Values of internal consistency ( α ) and composite reliability ( ρ ) ≥ 0.875 and 0.876 (BEECOM-L), and ≥ 0.807 and 0.813 (BEECOM-S) were respectively found in the present study (see Table 1for details). Table 1. Composite reliability ( ρ ) and internal consistency ( α ) of study measures across population subgroups. Younger Females (n= 287) Older Females (n= 360) Younger Males (n= 295) Older Males (n= 271) Instrument Dimensionality Factor ρ α ρ α ρ α ρ α BEECOM-L Higher-Order ED-related social comparison 0.926 0.963 0.901 0.963 0.925 0.956 0.882 0.940 BEECOM-L First-Order (Factor 1) Body comparison orientation 0.928 0.928 0.954 0.954 0.902 0.905 0.914 0.915 BEECOM-L First-Order (Factor 2) Eating comparison orientation 0.923 0.921 0.920 0.917 0.890 0.887 0.881 0.876 BEECOM-L First-Order (Factor 3) Exercise comparison orientation 0.923 0.922 0.925 0.926 0.904 0.900 0.876 0.875 BEECOM-S Higher-Order ED-related social comparison 0.913 0.917 0.898 0.921 0.919 0.906 0.865 0.882 BEECOM-S First-Order (Factor 1) Body comparison orientation 0.881 0.876 0.915 0.910 0.837 0.825 0.846 0.845 BEECOM-S First-Order (Factor 2) Eating comparison orientation 0.894 0.892 0.898 0.895 0.882 0.879 0.841 0.832 BEECOM-S First-Order (Factor 3) Exercise comparison orientation 0.872 0.869 0.854 0.854 0.847 0.847 0.813 0.807 PACS-R Unidimensional Physical appearance comparisons 0.965 0.953 0.980 0.969 0.962 0.943 0.972 0.958 EDE-QS Unidimensional Overall ED symptoms 0.941 0.890 0.941 0.889 0.936 0.865 0.932 0.864 EDE-QS Sub-scale (items 4, 5 & 6) Weight and shape concerns 0.803 0.790 0.793 0.807 0.743 0.707 0.703 0.693 EDE-QS Sub-scale (items 1 & 2) Dietary restraint 0.777 0.622 0.642 0.508 0.657 0.478 0.632 0.469 Note. PACS-R = Physical Appearance Comparison Scale-Revised; BEECOM = Body, Eating, and Exercise Comparison Orientation Measure (-L = Long version, -S = Short version); EDE-QS = Eating Disorder Examination Questionnaire Short; ED = eating disorders. 2.3.2. Physical Appearance Comparison Scale-Revised (PACS-R) We used a Spanish translation [ 10 ] of the PACS-R [ 28 ]. The 11 items comprising the instrument (e.g., “When I’m out in public, I compare my body size to the body size of others”) are rated on a 5-point scale from 0 (Never) to 4 (Always). Higher scores imply higher frequency of physical appearance comparisons. Evidence has been found that supports the validity and reliability of the scores of this instrument in both male and female individuals from Spain [ 10 , 12 ]. Values ≥ 0.943 ( α ) and 0.962 ( ρ ) were found for the total score of the PACS-R in the present study (see Table 1for details). 2.3.3. Eating Disorder Examination—Questionnaire Short (EDE-QS) We used a Spanish translation [ 29 , 30 ] of the EDE-Q [ 31 ], which incorporated the two main modifications proposed in the short version of the instrument (i.e., a recall period on 7 instead of 28 days and 4 instead of 7 response categories) [ 32 ]. The 12 items comprising the instrument (e.g., “Have you been deliberately trying to limit the amount of food you eat to influence your weight or shape [whether or not you have succeeded]”), are rated on a 4-point scale from 0 (0 days or Not at all) to 3 (6–7 days or Markedly) and cover essential symptoms of anorexia nervosa, bulimia nervosa, and binge eating disorder [ 32 ]. According to the purposes of the present study, and consistent with previous research, three different scores derived from the instrument were used: (i) a score reflecting overall ED symptomatology [ 14 , 16 – 18 ]; (ii) an aggregate score of items covering dietary restraint symptoms (i.e., Items 1 and 2) [ 13 , 16 , 18 ]; and (iii) an aggregate score of items covering weight and shape concerns (i.e., Items 4, 5, and 6) [ 13 , 17 , 23 , 33 ]. Values ≥ 0.864 ( α ) and 0.932 ( ρ ) were found for the total scores of the EDE-QS in the present study (see Table 1 for details). Nutrients 2023,15, 626 5 of 18 2.3.4. Demographics Demographic data concerning date of birth, gender, ethnicity, current diagnosis of ED, and self-reported height and weight were collected via a set of questions created for the present study. Height and weight were employed to calculate BMI (kg/m 2 ). Given that the study sample consisted of both adolescents and adults, BMI values were subsequently adjusted according to percentile distribution taking into account age and gender norms [ 34 ]. 2.4. Translation and Procedure Firstly, a Spanish version of the BEECOM was obtained by following the procedures recommended for conducting linguistic adaptation of instruments addressing constructs in the body image domain [ 35 ]. In brief, the procedure involved the following steps: (i) two translators independently forward-translated the BEECOM items from English to Spanish; (ii) the two translations were checked by a third independent translator who, after resolving the observed discrepancies, proposed a synthesized translation; (iii) the resulting Spanish version was back-translated into English by a fourth independent translator; (iv) the forwardand back-translations were examined by a committee comprising all the aforementioned translators and the first author of the present study, who agreed on the prefinal version; (v) this version was pilot-tested in a sample of 12 participants (M age = 17.692, SD age = 3.750; 50% females); none of them referred to the presence of items that, in their opinion, were ambiguous or difficult to understand. Following approval by the ethics committee of the first author’s institution, potential participants were invited to participate in the study in classroom settings by one of the authors of the present study. The research project was described as a study on body, eating, and exercise attitudes. In the case of minors, prior consent was required from parents or legal guardians to participate in the research. After being informed of the voluntary, anonymous, and non-rewarded nature of their participation, those who provided their informed consent (96.43%) completed a paper-and-pencil questionnaire in the classroom setting, which took approximately 5–10 min to complete. The assessment instruments included in the survey were counterbalanced using two different arrangements. Upon completion of the questionnaire, the participants were thanked for their cooperation and then debriefed about the precise aim of the study. Data were collected within the first academic quarter of the 2019–2020 school year. 2.5. Analytic Plan Firstly, the factor structure of the long and the short versions of the BEECOM was examined across the population subgroups of interest using CFA techniques in Mplus version 7. These analyses were conducted using a full information maximum likelihood estimation method with robust standard errors (MLR). Two main considerations were taken into account while deciding to use this estimator: (i) that the response format of the instrument (i.e., a 7-point Likert-type) allowed their scores to be safely treated as continuous [ 36 ] and (ii) that MLR was the estimation method used in the previous studies investigating the factor structure of the BEECOM [ 16 , 17 ]. As model fit indices, values ≥ 0.95 or ≥ 0.90 for the comparative fit index (CFI), and ≤ 0.06 or ≤ 0.08 for both the root-mean-square error of approximation (RMSEA) and the standardized root-mean-square residual (SRMR), respectively, are considered as excellent or marginally acceptable [ 37 ]. Potential sources of model misspecification were identified by examining modification indices (MI) [37]. Results derived from the CFA were employed for computing composite reliability [ 38 ], which—along with the internal consistency values—served to provide evidence on reliability of both versions of the BEECOM. Secondly, examination of the measurement invariance of the BEECOM scores across the population subgroups was conducted using multigroup CFA following the procedure described elsewhere [ 21 ]. This involved testing the following six progressively constrained models: Model 0 (or baseline model), which examined the equivalence of the factor structure based on the simultaneous free estimation of the parameters in all the subgroups Nutrients 2023,15, 626 6 of 18 of interest; Model 1, which additionally examined the equivalence of the factor loadings of the three first-order factors; Model 2, which additionally tested the equivalence of the three factor loadings of the higher-order factor; Model 3, which additionally tested the equivalence of the items’ intercepts; Model 4, which additionally tested the equivalence of the intercepts of the three factor loadings of the higher-order factor; Model 5, which additionally examined the equivalence of the first-order factor disturbances; and Model 6, which additionally tested the equivalence of the item residual variances (i.e., the error variance of each item) [ 21 ]. Given that the Satorra–Bentler scaled chi-square test of model fit difference with MLR estimators is particularly sensitive to sample size and the absence of normality, evaluation of changes ( ∆ ) in CFI (< − 0.010 signals lack of invariance) was alternatively considered [ 39 ]. In the presence of evidence supporting the invariant nature of the BEECOM scores across the population subgroups under consideration, differences in such scores [ 40 ] were computed. When calculating these differences, the pooled standard deviation was obtained by weighting the specific sample size of the different groups involved in the comparisons [ 41 ]. The magnitudes of the resulting effect sizes were interpreted as trivial (d= 0.00 to 0.20), small (d= 0.20 to 0.50), intermediate (d= 0.50 to 0.80), or large (d> 0.80) [40]. Thirdly, evidence of convergent validity was obtained by computing zero-order correlations (r) between the BEECOM scores and scores on (i) physical appearance comparisons and (ii) three different ED outcomes (i.e., overall ED symptoms, weight and shape concerns, and dietary restraint). The magnitudes of the resulting effect sizes were interpreted as trivial (0.00 to 0.10), small (0.10 to 0.30), moderate (0.30 to 0.50), or large (>0.50) [ 40 ]. Fourthly, evidence of incremental validity was obtained by conducting a set of linear regression analysis in which (i) the scores derived from both versions of the BEECOM and (ii) BMI and PACS-R scores (as covariates) were introduced as independent variables, whereas three different ED outcomes (i.e., overall ED symptoms, weight and shape concerns, and dietary restraint) were introduced as dependent variables. Finally, possible differences in the strength of the multivariate relationships between the BEECOM scores and the ED outcomes across populations subgroups were examining using Model 1 of PROCESS macro for SPPS following the procedure described elsewhere [ 42 ]. This meant introducing two new groups of independent variables into the regression models described in this paragraph. The first such group consisted of a multi-categorical moderating variable involving the four study population subgroups. This variable was indicator-coded in PROCESS with the younger female group as the reference group, yielding three dummy variables (younger males vs. younger females [D 1 ], older females vs. younger females [D 2 ], and older males vs. younger females [D 3 ]). The second of these groups consisted of the product terms between the predictor variable and the moderator (i.e., BEECOM scores x D 1–3 ). This procedure tested the interactions involving each of the candidate predictors (i.e., each of the specific BEECOM scores) in separate models. As a result of this procedure, conditional standardized effects of BEECOM scores on the three ED outcomes under consideration (i.e., simple slopes) for each of the four population subgroups were obtained. In order to deal with eventual violations of some of the assumptions inherent in the application of regression techniques (e.g., homoscedasticity of variance or residual normality), the last two sets of analyses described in this paragraph were conducted by applying a bias-corrected and accelerated bootstrapping technique of 5000 resamples [ 22 ]. Missing data (0.72%) were handled using full information imputation methods implemented in Mplus version 7 (http://www.statmodel.com/index.shtml, accessed on 21 December 2022). A significance level of 0.05 was used in all the statistical analyses. Nutrients 2023,15, 626 7 of 18 3. Results 3.1. Factorial Structure Marginally acceptable and adequate goodness-of-fit indices were obtained for the BEECOM-L and the BEECOM-S, respectively, in all the population subgroups under consideration (see Table 2). Further inspection of MI derived from the CFA involving the BEECOM-L revealed the following items as the main sources of poor model fit: (i) Item 17 (body comparison orientation factor), which was found to cross-load on the exercise comparison orientation factor both in the older male (MI = 12.207) and in the younger (MI = 20.903) and older (MI = 24.780) female subsamples; (ii) Items 8 and 16 (eating comparison orientation factor), which were found to cross-load on the exercise comparison orientation factor in the younger male subsample (MI = 25.405) and in the older female subsample (MI = 15.192), respectively; and (iii) Item 10 (exercise comparison orientation factor), which was found to cross-load on the eating comparison orientation factor both in the younger male (MI = 15.885) and in the older female (MI = 13.135) subsamples. Standardized factor loadings for both versions of the BEECOM are shown in Figure 1. These ranged from 0.540 to 0.953 (first-order factors) and from 0.717 to 0.951 (higher-order factor) for the BEECOM-L, and from 0.652 to 958 (first-order factors) and from 0.705 to 0.928 (higher-order factor) for the BEECOM-S. Table 2. Goodness-of-fit indexes across population subgroups and invariance testing of the long and short versions of the BEECOM. Version Population/Model χ2df χ2/df Comparison Models CFI ∆CFI RMSEA SRMR Est. 90% CI p Lower Upper Long Younger females (n= 287) 381.252 132 2.888 - 0.934 - 0.072 0.064 0.081 0.000 0.051 Older females (n= 360) 293.203 132 2.221 - 0.934 - 0.065 0.055 0.075 0.007 0.049 Younger males (n= 295) 305.732 132 2.316 - 0.910 - 0.070 0.059 0.080 0.001 0.052 Older males (n= 271) 238.592 132 1.808 - 0.941 - 0.052 0.042 0.063 0.348 0.056 M0: Baseline model (without invariance) 1205.833 528 2.284 - 0.931 - 0.065 0.060 0.070 0.000 0.052 M1: Invariant first-order factor loadings 1273.711 573 2.223 M1 vs. M0 0.929 −0.002 0.064 0.059 0.068 0.000 0.057 M2: M1 + Invariant higher-order factor loadings 1290.103 579 2.228 M2 vs. M1 0.928 −0.001 0.064 0.059 0.068 0.000 0.061 M3: M2 + Invariant items’ intercepts 1516.660 630 2.407 M3 vs. M2 0.910 −0.028 * 0.068 0.064 0.073 0.000 0.066 M3P: M2 + Partially invariant items’ intercepts a1427.879 622 2.296 M3P vs. M2 0.918 −0.010 0.065 0.061 0.070 0.000 0.064 M4: M3P + Invariant first-order factor intercepts 1454.815 625 2.328 M4 vs. M3P 0.916 −0.002 0.066 0.062 0.071 0.000 0.078 M5: M4 + Invariant first-order factor disturbances 1475.005 634 2.327 M5 vs. M4 0.914 −0.002 0.066 0.062 0.071 0.000 0.078 M6: M5 + Invariant item residual variances 1544.027 688 2.244 M6 vs. M5 0.913 −0.001 0.064 0.060 0.068 0.000 0.082 Younger females (n= 287) 47.988 24 2.000 - 0.983 - 0.053 0.030 0.074 0.390 0.032 Older females (n= 360) 40.702 24 1.696 - 0.983 - 0.049 0.020 0.075 0.487 0.035 Younger males (n= 295) 30.235 24 1.260 - 0.991 - 0.031 0.000 0.061 0.827 0.029 Older males (n= 271) 28.854 24 1.202 - 0.993 - 0.026 0.000 0.056 0.890 0.033 Short M0: Baseline model (without invariance) 145.661 96 1.517 - 0.987 - 0.041 0.027 0.054 0.855 0.032 M1: Invariant first-order factor loadings 161.685 114 1.418 M1 vs. M0 0.987 −0.000 0.037 0.023 0.050 0.954 0.036 M2: M1 + Invariant higher-order factor loadings 173.387 120 1.445 M2 vs. M1 0.986 0.001 0.038 0.025 0.050 0.944 0.044 M3: M2 + Invariant items’ intercepts 274.654 144 1.907 M3 vs. M2 0.965 −0.021 * 0.055 0.045 0.064 0.209 0.056 M3P: M2 + Partially invariant items’ intercepts b230.563 140 1.647 M3P vs. M2 0.976 −0.010 0.046 0.035 0.057 0.714 0.047 M4: M3P + Invariant first-order factor intercepts 247.490 143 1.731 M4 vs. M3P 0.972 −0.004 0.049 0.039 0.059 0.546 0.068 M5: M4 + Invariant first-order factor disturbances 261.440 152 1.720 M5 vs. M4 0.971 −0.001 0.049 0.039 0.059 0.571 0.068 M6: M5 + Invariant item residual variances 277.779 179 1.552 M6 vs. M5 0.974 0.003 0.043 0.032 0.052 0.894 0.071 Note. CFI = comparative fit index; RMSEA = root mean square error of approximation; CI = confidence interval; df = degrees of freedom; Est. = estimate; Lo = lower; up = Upper; SRMR = standardized root mean square residual; M = model. * ∆ CFI < − 0.01 (signals lack of invariance). a Intercepts of items 5, 11, 15, and 18 (younger males), Item 13 (older females) and Items 6, 15, and 18 (older males) are freed. b Intercepts of Items 9 and 12 (younger males) and Items 6 and 15 (older males) are freed. Nutrients 2023,15, 626 8 of 18 Nutrients 2023, 15, 626 9 of 20 Figure 1. Factor structure for the long (BEECOM-L) and the short (BEECOM-S) versions of the Body, Eating, and Exercise Comparison Orientation Measure [16,17]. ED = eating disorders. The four rows of values correspond to the groups consisting of younger females, younger males, older females, and older males, respectively. Values outside square brackets represent standardized factor loadings (λ). Values inside square brackets represent standardized errors (SE). Figure 1. Factor structure for the long (BEECOM-L) and the short (BEECOM-S) versions of the Body, Eating, and Exercise Comparison Orientation Measure [ 16 , 17 ]. ED = eating disorders. The four rows of values correspond to the groups consisting of younger females, younger males, older females, and older males, respectively. Values outside square brackets represent standardized factor loadings (λ). Values inside square brackets represent standardized errors (SE). 3.2. Invariance Analyses and Differences in BEECOM Scores across Population Subgroups The results of invariance analysis (see Table 2) revealed substantial differences between the models under comparison only in those aimed at testing the invariant nature of items’ intercepts. These differences were no longer remarkable after removing the equality restriction for 8 of the 72 (BEECOM-L) and 4 of the 36 (BEECOM-S) intercepts under examination. The effect sizes of differences in study variables across population subgroups are shown in Table 3. In terms of ED-related social comparisons, mainly small-sized differences were found, which tended to favor the groups consisting of female and older participants. Of all scores derived from the BEECOM, differences of at least intermediate magnitude were observed only between older female and younger male groups in terms of body comparison orientation, which favored the former. Small differences were also found for several ED outcomes, which tended to favor the female groups. Nutrients 2023,15, 626 9 of 18 Table 3. Scores of Study Variables and Effect Sizes of Differences Across Population Subgroups. Younger Females (n= 287) Older Females (n= 360) Younger Males (n= 295) Older Males (n= 271) Younger vs. Older Females Younger Females vs. Younger Males Younger Females vs. Older Males Older Females vs. Younger Males Older Females vs. Older Males Younger vs. Older Males Range aMSD MSD MSD MSD d d d d d d PercentileBMI 0–99.40 50.353 27.862 50.464 27.564 58.405 27.530 54.597 26.811 0.004 0.290 0.155 0.288 0.152 −0.140 BEECOM-L (Total score) 1–7 2.463 1.426 2.888 1.482 2.240 1.263 2.544 1.131 0.292 −0.166 0.063 −0.467 −0.256 0.253 BEECOM-L (Body) 1–7 2.859 1.702 3.345 1.809 2.306 1.392 2.574 1.340 0.276 −0.356 −0.186 −0.636 −0.475 0.196 BEECOM-L (Eating) 1–7 2.230 1.490 2.738 1.590 2.054 1.300 2.437 1.282 0.328 −0.126 0.149 −0.466 −0.205 0.297 BEECOM-L (Exercise) 1–7 2.300 1.476 2.580 1.524 2.366 1.460 2.621 1.278 0.186 0.045 0.233 −0.143 0.029 0.185 BEECOM-S (Total score) 1–7 2.509 1.478 2.924 1.529 2.302 1.362 2.623 1.194 0.275 −0.146 0.084 −0.427 −0.215 0.250 BEECOM-S (Body) 1–7 2.947 1.777 3.403 1.850 2.410 1.530 2.654 1.433 0.251 −0.324 −0.181 −0.579 −0.445 0.164 BEECOM-S (Eating) 1–7 2.152 1.566 2.620 1.696 2.036 1.454 2.356 1.377 0.285 −0.077 0.138 −0.367 −0.168 0.225 BEECOM-S (Exercise) 1–7 2.427 1.622 2.748 1.629 2.449 1.598 2.857 1.437 0.197 0.014 0.280 −0.185 0.070 0.268 PACS-R 0–4 1.162 0.991 1.356 1.104 0.967 0.888 1.062 0.916 0.184 −0.207 −0.105 −0.384 −0.286 0.105 Overall ED Symptoms 0–3 0.685 0.624 0.651 0.590 0.550 0.567 0.536 0.505 −0.056 −0.226 −0.261 −0.174 −0.207 −0.026 Weight and shape concern 0–3 0.880 0.912 0.651 0.590 0.587 0.746 0.581 0.691 −0.012 −0.352 −0.368 −0.341 −0.110 −0.008 Dietary Restraint 0–3 0.643 0.810 0.658 0.743 0.539 0.729 0.548 0.673 0.019 −0.135 −0.127 −0.161 −0.154 0.013 Note. BMI = body mass index; BEECOM = Body, Eating, and Exercise Comparison Orientation Measure (-L = Long version, -S = Short version); PACS-R = Physical Appearance Comparison Scale-Revised; ED = eating disorders. aObserved range in the case of Percentile-BMI and possible range for the remaining variables. Nutrients 2023,15, 626 16 of 18 Funding: This research was funded by Ministerio de Ciencia e Innovación (MCIN, Spain), Agencia Estatal de Investigación (AEI; https://doi.org/10.13039/501100011033), Spain, grant number PID2019-107674RB-I00. MAI (UAL RRA202101) is funded by Ministerio de Universidades (Plan de Recuperación, Transformación y Resiliencia, Next Generation EU). Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of University of Almería (UALBIO2018/013, 1 March 2018). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data presented in this study are available on request from the corresponding author. Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. References 1. Qian, J.; Wu, Y.; Liu, F.; Zhu, Y.; Jin, H.; Zhang, H.; Wan, Y.; Li, C.; Yu, D. An update on the prevalence of eating disorders in the general population: A systematic review and meta-analysis. Eat. Weight Disord. 2022,27, 415–428. [CrossRef] [PubMed] 2. Demmler, J.C.; Brophy, S.T.; Marchant, A.; John, A.; Tan, J.O.A. Shining the light on eating disorders, incidence, prognosis and profiling of patients in primary and secondary care: National data linkage study. Br. J. Psychiatry 2020,216, 105–112. [CrossRef] 3. James, S.L.; Abate, D.; Abate, K.H.; Abay, S.M.; Abbafati, C.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdela, J.; Abdelalim, A.; et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018 ,392, 1789–1858. [CrossRef] 4. Mohler-Kuo, M.; Schnyder, U.; Dermota, P.; Wei, W.; Milos, G. The prevalence, correlates, and help-seeking of eating disorders in Switzerland. Psychol. Med. 2016,46, 2749–2758. [CrossRef] 5. Samnaliev, M.; Noh, H.L.; Sonneville, K.R.; Austin, S.B. The economic burden of eating disorders and related mental health comorbidities: An exploratory analysis using the U.S. Medical Expenditures Panel Survey. Prev. Med. Rep. 2015 ,2, 32–34. [CrossRef] [PubMed] 6. Walker, D.C.; White, E.K.; Srinivasan, V.J. A meta-analysis of the relationships between body checking, body image avoidance, body image dissatisfaction, mood, and disordered eating. Int. J. Eat. Disord. 2018,51, 745–770. [CrossRef] 7. Kerr-Gaffney, J.; Harrison, A.; Tchanturia, K. Social anxiety in the eating disorders: A systematic review and meta-analysis. Psychol. Med. 2018,48, 2477–2491. [CrossRef] [PubMed] 8. Schaefer, L.M.; Thompson, J.K. Self-objectification and disordered eating: A meta-analysis. Int. J. Eat. Disord. 2018 ,51, 483–502. [CrossRef] 9. Yao, L.; Niu, G.; Sun, X. Body image comparisons on social networking sites and Chinese female college students’ restrained eating: The roles of body shame, body appreciation, and body mass index. Sex Roles 2021,84, 465–476. [CrossRef] 10. Alcaraz-Ibáñez, M.; Sicilia, A.; Díez-Fernández, D.M.; Paterna, A. Physical appearance comparisons and symptoms of disordered eating: The mediating role of social physique anxiety in Spanish adolescents. Body Image 2020,32, 145–149. [CrossRef] 11. Barnhart, W.R.; Sun, H.; Lin, Z.; Lu, C.; Han, X.; He, J. Integrating the tripartite influence, minority stress, and social comparison theories to explain body image and disordered eating in Chinese sexual minority men and women. Body Image 2022 ,43, 95–106. [CrossRef] 12. Alcaraz-Ibáñez, M.; Paterna, A.; Griffiths, M.D.; Sicilia, A. Examining the role of social physique anxiety on the relationship between physical appearance comparisons and disordered eating symptoms among Spanish emerging adults. Scand. J. Psychol. 2020,61, 803–808. [CrossRef] [PubMed] 13. Fitzsimmons-Craft, E.E.; Bardone-Cone, A.M.; Bulik, C.M.; Wonderlich, S.A.; Crosby, R.D.; Engel, S.G. Examining an elaborated sociocultural model of disordered eating among college women: The roles of social comparison and body surveillance. Body Image 2014,11, 488–500. [CrossRef] [PubMed] 14. Fitzsimmons-Craft, E.E.; Bardone-Cone, A.M. One-year temporal stability and predictive and incremental validity of the body, eating, and exercise comparison orientation measure (BEECOM) among college women. Body Image 2014,11, 27–35. [CrossRef] 15. Thompson, K.A.; Bardone-Cone, A.M. Social comparison, disordered eating, and body dissatisfaction among postpartum women. Body Image 2022,42, 401–412. [CrossRef] 16. Saunders, J.F.; Eaton, A.A.; Fitzsimmons-Craft, E.E. Body-, eating-, and exercise-related comparisons during eating disorder recovery and validation of the BEECOM-R. Psychol. Women Q. 2019,43, 494–508. [CrossRef] 17. Fitzsimmons-Craft, E.E.; Bardone-Cone, A.M.; Harney, M.B. Development and validation of the Body, Eating, and Exercise Comparison Orientation Measure (BEECOM) among college women. Body Image 2012,9, 476–487. [CrossRef] [PubMed] Nutrients 2023,15, 626 17 of 18 18. Sahlan, R.N.; Saunders, J.F.; Fitzsimmons-Craft, E.E.; Taravatrooy, F. The validity and reliability of the Farsi version of the Body, Eating, and Exercise Comparison Orientation Measure (F-BEECOM) among Iranian male and female students. Body Image 2020 , 34, 72–84. [CrossRef] [PubMed] 19. Dakanalis, A.; Clerici, M.; Stice, E. Prevention of eating disorders: Current evidence-base for dissonance-based programmes and future directions. Eat. Weight Disord. 2019,24, 597–603. [CrossRef] [PubMed] 20. Rolstad, S.; Adler, J.; Rydén, A. Response burden and questionnaire length: Is shorter better? A review and meta-analysis. Value Health 2011,14, 1101–1108. [CrossRef] 21. Dimitrov, D.M. Testing for factorial invariance in the context of construct validation. Meas. Eval. Couns. Dev. 2010 ,43, 121–149. [CrossRef] 22. Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; Guilford Press: New York, NY, USA, 2013. 23. Hill, E.M.; Nolan, M.T. Examining eating disorder-related social comparison orientation and body dissatisfaction in the relationship between fit ideal internalization and drunkorexia engagement. Eat. Behav. 2021,41, 101480. [CrossRef] [PubMed] 24. Senín-Calderón, C.; Santos-Morocho, J.; Rodríguez-Testal, J.F. Validation of a Spanish version of the physical appearance comparison scales. Int. J. Environ. Res. Public Health 2020,17, 7399. [CrossRef] [PubMed] 25. Muthén, L.K.; Muthén, B.O. Mplus Version 7: User’s Guide, 7th ed.; Muthén & Muthén: Los Angeles, CA, USA, 2015. 26. Muthén, L.K.; Muthen, B. How to use a Monte Carlo study to decide on sample size and determine power. Struct. Equ. Model. 2002,9, 599–620. [CrossRef] 27. Faul, F.; Erdfelder, E.; Buchner, A.; Lang, A.G. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behav. Res. Methods 2009,41, 1149–1160. [CrossRef] 28. Schaefer, L.M.; Thompson, J.K. The development and validation of the Physical Appearance Comparison Scale-Revised (PACS-R). Eat. Behav. 2014,15, 209–217. [CrossRef] 29. Peláez-Fernández, M.A.; Labrador, F.J.; Raich, R.M. Validation of Eating Disorder Examination Questionnaire (EDE-Q) –Spanish Version– for Screening Eating Disorders. Span. J. Psychol. 2012,15, 817–824. [CrossRef] 30. Peláez-Fernández, M.A.; Labrador, F.J.; Raich, R.M. Norms for the Spanish version of the Eating Disorders Examination Questionnaire. Pisothema 2013,25, 107–114. [CrossRef] 31. Fairburn, C.G.; Beglin, S. Eating disorder examination questionnaire (EDE-Q 6.0). In Cognitive Behavior Therapy and Eating Disorders; Guilford Press: New York, NY, USA, 2008; pp. 309–313. 32. Gideon, N.; Hawkes, N.; Mond, J.; Saunders, R.; Tchanturia, K.; Serpell, L. Development and psychometric validation of the EDE-QS, a 12 item short form of the Eating Disorder Examination Questionnaire (EDE-Q). PLoS ONE 2016 ,11, e0152744. [CrossRef] 33. Thompson, K.A.; Bardone-Cone, A.M. Sources of body comparison and their relation to body image concerns among middle-aged women. Eat. Behav. 2021,40, 101468. [CrossRef] 34. Kuczmarski, R.J.; Ogden, C.L.; Guo, S.S.; Grummer-Strawn, L.M.; Flegal, K.M.; Mei, Z.; Wei, R.; Curtin, L.R.; Roche, A.F.; Johnson, C.L. 2000 CDC growth charts for the United States: Methods and development. Vital Health Stat. 2002,11, 1–190. 35. Swami, V.; Barron, D. Translation and validation of body image instruments: Challenges, good practice guidelines, and reporting recommendations for test adaptation. Body Image 2019,31, 204–220. [CrossRef] 36. Raykov, T. Scale construction and development using structural equation modeling. In Handbook of Structural Equation Modeling; Hoyle, R.H., Ed.; Guilford Press: New York, NY, USA, 2012; pp. 472–492. 37. Brown, T.A. Confirmatory Factor Analysis for Applied Research, 2nd ed.; The Guilford Press: New York, NY, USA, 2015. 38. Raykov, T. Behavioral scale reliability and measurement invariance evaluation using latent variable modeling. Behav. Ther. 2004 , 35, 299–331. [CrossRef] 39. Chen, F.F. Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct. Equ. Model. 2007 ,14, 464–504. [CrossRef] 40. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Lawrence Erlbaum: Hillsdale, NJ, USA, 1988. 41. Hedges, L.V.; Olkin, I. Statistical Methods for Meta-Analysis; Elsevier Science: New York, NY, USA, 1985. 42. Hayes, A.F.; Montoya, A.K. A tutorial on testing, visualizing, and probing an interaction involving a multicategorical variable in linear regression analysis. Commun. Methods Meas. 2017,11, 1–30. [CrossRef] 43. Kline, R.B. Principles and Practice of Structural Equation Modeling, 3rd ed. ; Guilford Press: New York, NY, USA, 2011. 44. Lewthwaite, M.; LaMarre, A. “That’s just healthy eating in my opinion”—Balancing understandings of health and ‘orthorexic’ dietary and exercise practices. Appetite 2022,171, 105938. [CrossRef] [PubMed] 45. Greville-Harris, M.; Talbot, C.V.; Moseley, R.L.; Vuillier, L. Conceptualisations of health in orthorexia nervosa: A mixed-methods study. Eat. Weight Disord. 2022,27, 3135–3143. [CrossRef] [PubMed] 46. Myers, T.A.; Crowther, J.H. Social comparison as a predictor of body dissatisfaction: A meta-analytic review. J. Abnorm. Psychol. 2009,118, 683–698. [CrossRef] 47. Sicilia, A.; Fuller-Tyszkiewicz, M.; Rodgers, R.F.; Granero-Gallegos, A.; Lo Coco, G.; Dion, J.; McCabe, M.; Strodl, E.; Markey, C.H.; Aimé, A.; et al. Cross-country measurement invariance and effects of sociodemographic factors on body weight and shape concern-related constructs in eight countries. Body Image 2020,35, 288–299. [CrossRef] Nutrients 2023,15, 626 18 of 18 48. Aimé, A.; Fuller-Tyszkiewicz, M.; Dion, J.; Markey, C.H.; Strodl, E.; McCabe, M.; Mellor, D.; Granero Gallegos, A.; Pietrabissa, G.; Alcaraz-Ibánez, M.; et al. Assessing positive body image, body satisfaction, weight bias, and appearance comparison in emerging adults: A cross-validation study across eight countries. Body Image 2020,35, 320–332. [CrossRef] [PubMed] 49. Samuels, K.L.; Maine, M.M.; Tantillo, M. Disordered eating, eating disorders, and body image in midlife and older women. Curr. Psychiatry Rep. 2019,21, 70. [CrossRef] [PubMed] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.