Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

Abstract

Overeating for non-homeostatic needs contributes to childhood obesity. However, validated measures or eating motives and cross-cultural comparisons are limited. This study aimed to validate the Kids-Palatable Eating Motives Scale (K-PEMS) and its association with body mass index z score (BMIz) in China, and further assess its generalization across Chinese and American youth. Data were from participants aged 8–18 years from Hangzhou, China (n = 426) and Birmingham, AL, U.S (n = 73). The K-PEMS had sound reliability and validation (Cronbach’s α = 0.920 and all factor loadings >0.50) in the Chinese sample. Multi-group nested models CFAs showed that the ∆CFI of model comparisons of measurement weights and structural covariance, variance, and means were ⩽0.01, and ∆TLI of measurement intercepts ⩽0.05. Linear regressions revealed that frequency of consuming palatable foods and drinks for Coping, Reward Enhancement, and Conformity, but not Social motives, were positively associated with BMIz. The K-PEMS had good cross-cultural generalization and could be useful in treating obesity by identifying specific motives for consuming excessive calories.

Keywords

childhood obesity cross-cultural invariance eating behavior palatable food psychological measurement

Introduction

Overweight and obesity is a health problem that currently impacts more than 330 million children and adolescents in the world (Di Cesare et al., 2019). Rates are also increasing in both developed and developing countries (Di Cesare et al., 2019). Notably, the increasing rates are estimated to be higher in developing countries. In China, the obesity prevalence of school-aged children and adolescents (7–18 years) increased from 1.2% to 19.4% in 1986–2014, and the absolute number was as an astonishing 34.96 million (Pan et al., 2021; Zhang and Ma, 2018). This puts children and adolescents at a greater risk of developing chronic medical (Choukem et al., 2020) and psychological problems (Aldossari et al., 2021) but also at greater risk for unhealthy changes to their physical development (Maciałczyk-Paprocka et al., 2017). An important contributor to childhood obesity is the consumption of highly palatable food and drinks (HPFs). These tend to be highly processed and are high in sugar and/or fat content and thus also in caloric content. Energy intake from ultra-processed foods now makes up 66% of energy intake in children and adolescents, a 5.6% increase in the last two decades (Crimarco et al., 2021).

Consumption of HPFs can lead to rapid weight gain since they are commonly consumed in the absence of metabolic hunger (Fogel et al., 2018). Their tastiness, increased abundance, and ready accessibility has endowed these foods with functions beyond that of satisfying basic physiological needs. The Kids-Palatable Eating Motives Scale (K-PEMS) was developed by Boggiano et al. (2015) to identify these functions. They include to cope (e.g. with aversive feelings or situations), to increase reward (e.g. from the properties of the food itself), be more social (e.g. improving events or gatherings) and to conform (e.g. to fit and feel accepted). In adolescents, greater frequency of eating HPFs for the Social and Conformity motives of the K-PEMS was associated with higher BMIz (Boggiano et al., 2015), a standard indicator of overweight/obesity in children and adolescents (Verbiest et al., 2021). Furthermore, the K-PEMS revealed that the link between poor emotion regulation and obesity in adolescents was mediated by the intake of HPFs for Coping, Social, and Conformity motives (Orihuela et al., 2017).

In clinical practice, a diet based on energy restriction is common in weight loss programs (Bleich et al., 2018), but this strategy may not be safe for developing children and adolescents (Ojeda-Rodríguez et al., 2018). Therefore, exploring the association between eating motives in absence of hunger and weight status may be helpful in designing more effective and safe weight-loss interventions (Shriver et al., 2020). Given the increasing global rates of overweight and obesity in children and adolescents, and the global ubiquitous nature of HPFs in this age group, a cross-cultural measure of eating motives in children and adolescents is needed.

The K-PEMS, is valuable in its measure of eating motives in the absence of hunger in language that is comprehensible to children and adolescents. To our knowledge, the K-PEMS has not been translated and validated for use in a non-Western culture.

Thus, this study aimed to translate and examine the psychometric properties and cross-cultural generalization of the Chinese version of the K-PEMS (K-PEMS-C). In addition, the study explored associations between the frequency to eat for the various motives and weight status in a young Chinese population. This study could help to develop better tailored, and thus superior interventions to treat and prevent obesity in children and adolescents.

Methods

Participants

The data for this study were extracted from a study aimed at translating a battery of standardized English-language eating behavior questionnaires, of which one was the K-PEMS. A total of n = 426, 8–18-year old (mean = 10.53, SD = 1.68) males (35%) and females (65%) coming in for a routine health check-up completed the K-PEMS in a tertiary Children’s Hospital in Eastern China (see Supplemental Material-A for participant inclusion and exclusion criteria and data collection process). Raw data from the American sample (n = 73) was obtained from Boggiano, of the participants aged 12–17 years (M = 14.7, SD = 0.9), 48% were males and 52% were females (detailed information is in Boggiano et al., 2015). All participants consented and were assented by their parents. The study was approved by the Ethics Committee of Children’s Hospital of Zhejiang University.

Measures

Original and Chinese version of the K-PEMS (K-PEMS-C)

The original K-PEMS was tested in 12–17 year old Americans. It included 19 items rated on a 1–5 frequency scale. Items factored into four motives, Social, Coping, Reward Enhancement, and Conformity, each with good internal reliability (0.64–0.90). All but Conformity were associated with BMIz and showed good predictive validity ( $β$ ranged from 0.25 to 0.36, p < 0.05; Boggiano et al., 2015). Supplemental Material-C includes the items comprising each motive. Briefly, the Social motive reflects eating HPF to increase enjoyment of celebrations, parties, and time with friends; the Coping motive to forget about worries and problems and alleviate negative mood; the Reward Enhancement motive to enjoy the exciting and pleasant feelings of the properties of the HPF itself, and the Conformity motive to avoid being teased and feel accepted and liked by others. A PEMS Total score reflects general eating for reasons other than hunger.

The original K-PEMS was translated and back-translated into Chinese using Beaton’s method (Beaton et al., 2000). Translation details are in Supplemental Material-B. Like the original English version, the K-PEMS-C included 19 items which factored into four motives: Coping, Reward Enhancement, Social, and Conformity. For examples of the items that made up each motive in both English and Chinese, see the full scale in Supplemental Material-C. Additionally, the K-PEMS-C used a 7-point (1 = Never–7 = Always) response scale versus a 5-point scale for greater response accuracy (Preston and Colman, 2000). Higher scores indicate a greater frequency of consuming tasty foods or drinks for that motive. Motive scores were derived by calculating the mean of the responses that made up the motive score. A PEMS Total score was calculated as the mean across the 19 items.

Body mass index

The body mass index z-score (BMIz) was calculated by measured height and weight. The BMIz differs from BMI used in adults to account for the developing characteristics of children and adolescents. Calculation of BMIz is dependent on the individual’s age and gender and the z score is a standardized value that takes personal development stage into consideration. The BMIz can be directly compared among children and adolescents. World Health Organization (2022) categories were used to denote normal/underweight (BMIz ⩽ 1), overweight (1 < BMIz ⩽ 2), and obesity (BMIz > 2). The mean BMIz of the Chinese sample was 0.37, SD = 1.18 (median = 0.26, IQR = 1.51).

Children Eating Behavior Questionnaire (CEBQ) and Dutch Eating Behavior Questionnaire-Child (DEBQ-C)

The total score of the Chinese versions of the CEBQ (Xue, 2012) and DEBQ-C (Zhao, 2018) was used to test the criterion validity of the K-PEMS-C. The CEBQ is a 35-item parent-rated survey that yields eight observable dimensions of eating behaviors including reaction and enjoyment of food, satiety sensitivity, rate of eating, pickiness, emotion-related overeating/undereating, and desire for drinks (Wardle et al., 2001). The Chinese version of the CEBQ was validated in children with a mean age of 8.75; reliability was 0.7 (Xue, 2012). The DEBQ-C is a 20-item self-rated survey that measures three factors, behaviors aimed at losing weight, desire to eat for emotional reasons, and eating triggered by orosensory factors (Van Strien and Oosterveld, 2008). The Chinese version of the DEBQ-C was validated in a primary school and reliability was 0.77. The three factors derived from the 20 items explained 46.01% of the variance (Zhao, 2018).

Analyses

Internal reliability was assessed with Cronbach’s α, McDonald’s $ω, and$ test-retest reliability with the intraclass correlation coefficient (ICC). Content validity of items and structure of the K-PEMS-C were evaluated with the content validity index (CVI) and confirmatory factor analysis (CFA). Item-CVI ⩾ 0.83 (Polit et al., 2007) and factor loadings ⩾0.5 (Wu, 2010) were deemed as acceptable. Composite reliability (CR) and average variance extracted (AVE) were calculated by CR = $\frac{{(\sum λ_{i})}^{2}}{[{(Σ λ_{i})}^{2} + Σ Θ_{i i}]}$ and AVE = $\frac{\sum λ_{i}^{2}}{n}$ respectively (Qiu, 2009). Discriminant validity was assessed with comparisons between correlations and $\sqrt{A V E}$ of the K-PEMS-C motives (Qiu, 2009). Correlations between scores on the K-PEMS-C and the CEBQ and DEBQ-C tested criterion-related validity.

Measurement invariance across cultures for K-PEMS-C usage was evaluated by multi-group CFAs with nested models. Because the original data provided by Boggiano used the 5-point response scale, for invariance analysis, the 7-point response scale of the K-PEMS-C was converted to the 5-point original K-PEMS response scale (i.e. responses of “Almost Always” and “Almost Never” were coded the same as responses of “Always” and “Never”). Measurement weights, structural covariances, variance, measurement residual, intercepts, and structural means invariance comparison were conducted after a configural invariance assessment. Changes in CFI (∆ $C F I$ ) and TFI (∆ $T F I$ ) between two nested models were indicators of model equivalence, while ∆ $C F I$ ⩾0.01 (Cheung and Rensvold, 2002) or ∆ $T F I \geq 0.05$ (Little, 1997) denoted rejection of the constrained model. Reference criteria for model fit indices were as follows: χ²/df < 5, GFI > 0.9, AGFI > 0.9, TLI > 0.9, RMR < 0.05, RMSEA < 0.08 (Hou, 2004; Wu, 2010). Finally, associations between the K-PEMS-C motives and BMIz were analyzed with linear regression and, for descriptive purposes only, body weight categories were compared with analysis of variance (ANOVA) and Bonferroni correction for multiple comparisons. Analyses were conducted with SPSS v21 and AMOS 26. Alpha was set at p < 0.05 for significance.

Results

Of n = 903 participants that consented and enrolled, 426 completed the survey. Others did not participate due to lack of interest or a limited time schedule. There were no significant differences in demographics and weight status between those that completed the survey and those that did not (p > 0.05). Of the n = 426, 65% (277) were female and 35% (149) were male.

Reliability and validity of the K-PEMS-C

Cronbach’s $α$ and McDonald’s $ω$ for internal reliability were 0.920 and 0.927, respectively. As for test-retest reliability, n = 30 participants completed the retest survey 2–4 weeks after the first test. The ICC was 0.549 with a 95% confidence interval between 0.242 and 0.756, p < 0.01. Regarding content validity, the mean item-CVI across experts and across items were 0.85 and 0.86, respectively. Results from the discriminate validity test are shown in Table 1. The $\sqrt{A V E}$ values represented on the diagonal were larger than the correlations between motives, indicating good discriminate validity. Concerning criterion validity, the internal reliability of DEBQ-C and CEBQ was 0.795 and 0.734, respectively. The K-PEMS-C Total score was correlated with the total scores of the DEBQ-C (r = 0.484, p < 0.01) and CEBQ (r = 0.263, p < 0.05).

Table 1.

Correlations between the K-PEMS-C motives.

	AVE*	Coping	Reward	Social	Confirmation
Coping	0.595	0.771
Reward	0.557	0.655**	0.746
Social	0.500	0.514**	0.639**	0.707
Confirmation	0.526	0.524**	0.490**	0.605**	0.725

K-PEMS-C: Chinese version of the Kids-Palatable Eating Motives Scale; AVE: average variance extracted.

$\sqrt{A V E} values$ are represented on the diagonal; **p < .01.

Results from the confirmatory factor analysis

Results from the CFA are shown in Figure 1. The K-PEMS-C had the same motives and the items making up each motive were the same as in the original K-PEMS. Highest inter-motive correlations were between Coping and Reward Enhancement and between Reward Enhancement and Social. The model fit indices of the K-PEMS-C were: χ²/df = 4.052, GFI = 0.870, AGFI = 0.831, TLI = 0.880, RMR = 0.088, and RMSEA = 0.085. The factor loading of each item was >0.5. CR and AVE values were >0.8 and >0.5, respectively, for all four motives (see Table 2 for motive properties).

Figure 1.

Four-factor model of the Chinese version of K-PEMS using confirmatory factor analysis.

Table 2.

Properties of the four motives of the K-PEMS-C motives.

	Factor	USTD	S.E.	t	p	STD	SMC	CR	AVE
Item1	Coping	1.000				0.605	0.366	0.852	0.595
Item4		1.427	0.115	12.401	***	0.802	0.643
Item6		1.674	0.134	12.455	***	0.808	0.653
Item16		1.688	0.133	12.732	***	0.846	0.716
Item7	Reward	1.000				0.644	0.415	0.861	0.557
Item9		0.822	0.063	13.085	***	0.774	0.599
Item10		1.028	0.074	13.850	***	0.845	0.714
Item13		1.168	0.087	13.437	***	0.804	0.646
Item17		0.657	0.058	11.286	***	0.641	0.411
Item3	Social	1.000				0.599	0.359	0.831	0.500
Item5		1.432	0.148	9.688	***	0.584	0.341
Item11		1.375	0.119	11.518	***	0.750	0.563
Item14		1.646	0.137	12.058	***	0.819	0.671
Item15		1.557	0.135	11.546	***	0.753	0.567
Item2	Conformity	1.000				0.544	0.296	0.844	0.526
Item8		1.255	0.124	10.120	***	0.677	0.458
Item12		1.544	0.155	9.969	***	0.660	0.436
Item18		1.255	0.110	11.364	***	0.853	0.728
Item19		1.463	0.129	11.318	***	0.843	0.711

K-PEMS-C: Chinese version of the Kids-Palatable Eating Motives Scale; USTD: unstandardized estimate; STD: standardized factor loadings; SMC: squared multiple correlations; CR: composite reliability; AVE: average variance extracted.

***

p < 0.001.

Measurement invariance across cultures

The baseline models of the Chinese and American samples are presented in Figure 1 and Supplemental eFigure 1, respectively. The configural model fit indices were χ²/df = 3.229, GFI = 0.839, AGFI = 0.791, CFI = 0.874, RMSEA = 0.067, SRMR = 0.0675. Although all p values <0.05, including measurement weights, structural covariances, variance, measurement residual, intercepts, and structural means, the ∆ $C F I$ of the factor loading, covariances, and variance were <0.01, indicating measurement invariance across cultures (see Table 3).

Table 3.

K-PEMS measurement invariance across Chinese and American samples.

Model	df	$χ 2$	p	NFI	IFI	RFI	CFI	TLI
Model	df	$χ 2$	p	Delta-1	Delta-2	rho-1	Delta	rho2
Measurement weights	15	57.52	<0.001	0.010	0.011	0.002	0.008	0.002
Structural covariances	6	45.914	<0.001	0.008	0.009	0.005	0.008	0.006
Variance	4	64.562	<0.001	0.012	0.012	0.01	0.004	0.011
Measurement residual	25	450.601	<0.001	0.082	0.087	0.067	0.082	0.072
Measurement intercepts	19	87.599	<0.001	0.016	0.017	0.005	0.014	0.005
Structural means	4	18.686	0.001	0.003	0.004	0.001	0.003	0.001

K-PEMS: Kids-Palatable Eating Motives; NFI: Normed Fit Index; IFI: incremental fit index; RFI: relative fit index; CFI: Comparative Fit Index; TLI = Tucker-Lewis index.

Association between K-PEMS-C motives and BMIz

Linear regressions revealed a significant association between BMIz and frequency of consuming HPFs for Coping (β_standard = 0.113, t = 2.350, p = 0.019), Reward Enhancement (β_standard = 0.105, t = 2.183, p = 0.030), and Conformity (β_standard = 0.131, t = 2.722, p = 0.007) motives. BMIz was not associated with frequency to eat for Social motives (β_standard = 0.031, t = 0.648, p = 0.517).

Examining these associations as a function of BMIz categories revealed that frequency of eating HPFs for Coping (F = 5.064, p = 0.007, $η_{p}^{2} =$ 0.023), Reward Enhancement (F = 7.110, p = 0.001, $η_{p}^{2} =$ 0.033), and Conformity (F = 7.109, p = 0.001, $η_{p}^{2} =$ 0.033), but not Social motives (F = 1.422, p = 0.242, $η_{p}^{2} =$ 0.007) differed by weight categories (Figure 2). Scores on these three motives were significantly higher in the Obesity group (BMIz > 2) compared to the Normal/Underweight group (BMIz ⩽ 1). Scores on the Reward and Conformity motives were also significantly higher in the Overweight group (1 < BMIz ⩽ 2) compared to the Normal/Underweight group. There were no significant differences in any of the motive scores between the Overweight and Obesity group.

Figure 2.

Comparisons of the Chinese version of the K-PEMS motives among different weight groups.

Discussion

The K-PEMS was translated into Chinese and validated in children and adolescents with good psychometric properties. In addition, the multi-group CFA analysis indicated invariance of K-PEMS application in Chinese and American samples. This suggests a good cross-cultural generalization for the usage of the K-PEMS. Moreover, the K-PEMS-C Coping, Reward Enhancement, and Conformity motives were able to significantly distinguish children and adolescents with obesity from those with normal/underweight BMIz. The large sample size also allowed an observable difference between Reward Enhancement and Conformity scores between the normal and overweight BMIz groups. These results support that greater frequency of eating tasty foods for reasons other than hunger contributes to increasing BMIz and that targeting them with cognitive/behavioral methods should help treat and prevent obesity.

Studies with the K-PEMS are still scarce but in the original validation of the K-PEMS in American 12–17 year old adolescents, eating more frequently for Social motives was associated with higher BMIz (Boggiano et al., 2015). However, in the Chinese sample, eating more frequently for Social motives was the only motive not associated with BMIz. A possible explanation may be that the American sample was predominantly lower income, of Black ethnicity, and from Alabama, a Southern American state. Together, this is a population that commonly consumes fast food and fried foods as regular family meals and even as school meals (Lucan et al., 2010). In addition to eating unhealthy snacks and desserts for Social motives, BMIz would expectedly be increased in this population. In contrast, among Chinese youth, fast food is very strictly limited by their parents, especially in high educated families in Eastern China (Zhao et al., 2017), where the data were collected. High-energy density snacks, and fried foods are only eaten in meals on special occasions as a reward or celebration (Fu, 2016). Hence, eating HPFs for Social motives would not increase BMIz as it would for the American adolescents. Indeed, the mean BMIz was much higher in the American versus Chinese sample (0.84 vs 0.31; t = −8.124, p < 0.001).

Although it is interesting that absolute mean Social scores were equivalent across the two samples, the different cultures may contribute to the association differences between Social eating and BMIz. Studies with the adult PEMS consistently yield no relation between the Social motive and obesity or disordered eating (Boggiano, 2016; Boggiano et al., 2017; Burgess et al., 2014).

In that sense, it is the most normative reason for eating HPFs when not metabolically hungry. Since Social scores in the Chinese adolescents were unassociated with BMIz, it may also prove to be the most normative of the motives in this group. Closer inspection of the young American sample revealed that if overweight and obese BMIz adolescents were analyzed separately from lean counterparts, higher Conformity, but not higher Social motive scores, were associated with BMIz (Boggiano et al., 2015). Hence, pressure from others to eat as they do may further augment BMI in American kids that are already overweight. In their Chinese counterparts, eating for Conformity was also associated with higher BMIz

Regarding the common association between BMIz and eating more frequently for Conformity motives in both cultures, it is known that among children and adolescents with overweight or obesity, there is a higher prevalence of low self-esteem and feelings of being stigmatized (Hill, 2017). This may lead them to be more acquiescent to eating behaviors. For example, they may attempt to please others by consuming the foods and drinks they see their peers or family consuming, thereby increasing their risk for weight gain.

In this study, children, and adolescents with greater frequency of eating for Coping motives had a greater risk of higher BMIz. Eating palatable food momentarily helps relieve negative emotions (Thomas et al., 2020). Despite few studies that have focused on eating for positive emotions, it is a dimension included in the assessment of emotional eating (Aparicio et al., 2016). Eating to cope with both negative and positive emotions is thought to reflect difficulties in emotional regulation (Barnhart et al., 2021), a trait that is common among children and adolescents with overweight/obesity (Aparicio et al., 2016). Using the K-PEMS, poorer emotion regulation in youth was found to predict eating for Coping while eating for Coping motives did not predict emotion regulation (Orihuela et al., 2017). Therefore, a deficit in emotional regulation appears to drive eating tasty but energy-dense food as a coping strategy, a behavior that contributes to obesity. A future study using the K-PEMS-C should examine if the same pattern emerges among Chinese youth. Eating for Coping motives in the young American sample was also strongly associated with symptoms of binge-eating disorder (Boggiano et al., 2015). Future studies with the K-PEMS-C and eating disorder criteria in Chinese youth should be valuable in preventing the full development of eating disorders as well as obesity.

This study had several limitations. Firstly, the American sample was tested about 6 years before the Chinese sample. Hence, extraneous environmental variables had a greater chance of influencing results than if the samples had been tested concomitantly. Secondly, although the Chinese participants were healthy children, their data were collected in a hospital and may not ideally represent responses collected from a community center or school. Future testing of the K-PEMS in Chinese children should be conducted in more normative settings. Thirdly, the two samples compared in this study were not perfectly matched for age range, income status, or male/female distribution. Lastly, validation of K-PEMS in this study was based on classical test theory but not item-response theory. The latter could be used to obtain more precise measurement of information captured by the K-PEMS.

Despite these limitations, the study attempted to narrow an important gap in eating behavior research. This is the lack of invariance measurement between different cultures. Although validated assessments have been developed and translated in recent decades, invariance comparisons across different cultures are still limited. Hopefully, the invariance measures of the K-PEMS between China and the USA will spur future cross-cultural comparisons. In this study, intercepts variance indicated differences between item scores. However, the invariance in structural means supports the conclusion that Chinese and American children and adolescents share the same motives for eating HPF when not in caloric need, and these same motives are measured by the same items. More studies are needed to characterize eating motives and their associations to obesity in children and adolescents worldwide.

Conclusion

In sum, the K-PEMS-C proved to be a reliable instrument with which to assess motives unrelated to metabolic hunger, that is, for consuming tasty and typically energy-dense foods and drinks in Chinese youth. There was good generalization in the instrument across young Chinese and American populations. Among the Chinese youth tested, many more motives were associated with obesity. Further research will verify the inference that in Asian cultures, eating for reasons other than energy needs is, in general, more detrimental to the health of young people than it is in the West. Future research with the K-PEMS-C should test if the motives predict binge-eating and other disordered eating behaviors that are also dangerous to health. The use of the K-PEMS-C promises to elucidate the psychological mechanisms behind obesity in Asian cultures, thereby helping to de-stigmatize the disease. In turn, the insight can be used to develop novel, more tailored interventions to treat and prevent overweight and obesity in youth.

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Footnotes

Acknowledgements

We would like to thank Xiaofei Chen, Kexian Liu, and Huiwen Li for their generous help in the enrollment of participants. We also give a special thanks to all the participants and their families involved in this study.

Author contributions

Junfen Fu and Yuzheng Hu conceived the idea and supervised the study, Dan Wang and Ke Huang designed the data collection tools and collected the data. Dan Wang completed the data analyses and drafted the manuscript. Mary M Boggiano revised the manuscript for language and required contents. All authors approved of the final version.

Data sharing statement

The current article is accompanied by the relevant raw data generated during and/or analysed during the study, including files detailing the analyses and either the complete database or other relevant raw data. These files are available in the Figshare repository and accessible as Supplemental Material via the Sage Journals platform. Ethics approval, participant permissions, and all other relevant approvals were granted for this data sharing.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The study was approved by the Ethics Committee of Children’s Hospital (#2020-IRB-179). Clinical Trial Registration# ChiCTR2100052239.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Junfen Fu

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