ABSTRACT:

Objective:

To analyze the convergent validity and invariance of a scale to measure adherence to eating practices recommended by the Dietary Guidelines for the Brazilian Population.

Methods:

A subsample (n=1309) of the NutriNet-Brasil cohort (self-filled web-based study) answered the 24-items scale based on the Guide, as well as socioeconomic and dietary questionnaires. The score in the scale (eGuia) was compared by Spearman’s correlation with scores of fresh and minimally processed foods (eG1) and ultra-processed foods (eG4) consumption, both composed of the average number of food items consumed in three random days. Correlations’ direction and strength were observed to infer convergent validity. A multi-group confirmatory factor analysis was used to assess scale invariance at the configural, factorial and metric levels, between subgroups of sex (men/women), age (≤37/>37, being 37 the median) and years of schooling (≤11/>11). The model was invariant when the goodness-of-fit indices varied within acceptable ranges compared to the previous level.

Results:

Participants were on average 39 years old (sd=13.7), 53% were women and 69% had more than 11 years of education. Correlations between eGuia and eG1, and between eGuia and eG4 were 0.56 and -0.51 (p<0.001), respectively. In all sociodemographic groups, the goodness-of-fit indices varied within acceptable ranges.

Conclusion:

The correlations show that the eating practices measured by the scale are aligned with a healthy food consumption, showing its convergent validity. In this sample, the scale measured the same dimensions, showed equivalence of items’ factor loadings, and generated comparable scores between subgroups of sex, age, and education.

Keywords:
Food guide; Food behaviour; Psychometrics; Validation study

INTRODUCTION

The Dietary Guidelines for the Brazilian Population is based on an expanded concept of healthy eating that takes into account biological, sociocultural and environmental aspects linked to the health and well-being of individuals and communities. Its recommendations cover practices surrounding the whole eating process—from the food choice to the settings in which it is consumed—and takes into account possible obstacles posed by contemporary lifestyles. In a non-quantitative format, the recommendations are expressed with terms such as “avoid” or “limit” and presented as an easy-to-understand text with illustrations¹1. Brasil. Ministério da Saúde. Secretaria de Atenção Básica. Departamento de Atenção Básica. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde; 2014.^,22. Monteiro CA, Cannon G, Moubarac JC, Martins APB, Martins CA, Garzillo J, et al. Dietary guidelines to nourish humanity and the planet in the twenty-first century. A blueprint from Brazil. Public Health Nutr 2015; 18(13): 2311-22. https://doi.org/10.1017/S1368980015002165
https://doi.org/https://doi.org/10.1017/... ^,33. Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Política nacional de alimentação e nutrição. Brasília: Ministério da Saúde; 2013.^,44. Brasil. Presidência da República. Casa Civil. Subchefia para Assuntos Jurídicos. Emenda Constitucional no 64, de 4 de fevereiro de 2010. Altera o art. 6o da Constituição Federal, para introduzir a alimentação como direito social. Brasília, 04 de fevereiro de 2010. Disponível em: http://www.planalto.gov.br/ccivil_03/constituicao/emendas/emc/emc64.htm#:~:text=EMENDA%20CONSTITUCIONAL%20N%C2%BA%2064%2C%20DE,a%20alimenta%C3%A7%C3%A3o%20como%20direito%20social.&text=.%22%20(NR)-,Art.,na%20data%20de%20sua%20publica%C3%A7%C3%A3o.
http://www.planalto.gov.br/ccivil_03/con... .

If, on the one hand, qualitative recommendations facilitate the dissemination and implementation of food guidelines because they are simpler, realistic and flexible²2. Monteiro CA, Cannon G, Moubarac JC, Martins APB, Martins CA, Garzillo J, et al. Dietary guidelines to nourish humanity and the planet in the twenty-first century. A blueprint from Brazil. Public Health Nutr 2015; 18(13): 2311-22. https://doi.org/10.1017/S1368980015002165
https://doi.org/https://doi.org/10.1017/... ^,55. Oliveira MS, Santos-Amparo L. Food-based dietary guidelines: a comparative analysis between the Dietary Guidelines for the Brazilian Population 2006 and 2014. Public Health Nutr 2018; 21(1): 210-7. https://doi.org/10.1017/S1368980017000428
https://doi.org/https://doi.org/10.1017/... , on the other hand, they are a challenge when it comes to the measurement of population adherence. Therefore, a self-administered scale to assess adherence to recommendations was developed and underwent initial validation steps. The scale contained 24 items that portray dietary practices recommended or discouraged by the document, and respondents were supposed to indicate how often they adhere to such practices in their daily lives⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... .

This instrument has been widely used not only for data collection in scientific research but also as a means of health promotion in health services. Three studies were identified in the literature using the scale, two of which described lifestyles and health-related behaviors of population groups in Brazil⁷7. Quaresma MVS, Marques CG, Magalhães ACO, Santos RVT. Emotional eating, binge eating, physical inactivity, and vespertine chronotype are negative predictors of dietary practices during COVID-19 social isolation: a cross-sectional study. Nutrition 2021; 90: 111223. https://doi.org/10.1016/j.nut.2021.111223
https://doi.org/https://doi.org/10.1016/... ^,88. Guimarães NS, Paula W, Aguiar AS, Meireles AL. Absence of religious beliefs, unhealthy eating habits, illicit drug abuse, and self-rated health is associated with alcohol and tobacco use among college students — PADu study. Journal of Public Health 2021; 1-9. https://doi.org/10.1007/S10389-020-01440-7
https://doi.org/https://doi.org/10.1007/... ^, while the other described sociodemographic factors associated with the score on the scale⁹9. Gabe KT, Jaime PC. Práticas alimentares segundo o guia alimentar para a população brasileira: fatores associados entre brasileiros adultos, 2018. Epidemiol Serv Saúde 2020; 29(1): e2019045. https://doi.org/10.5123/S1679-49742020000100019
https://doi.org/https://doi.org/10.5123/... . In addition, the scale composes the test “How is your diet?”, from the Ministry of Health, printed as a flier¹⁰10. Brasil. Ministério da Saúde. Como está sua alimentação? [Internet]. 2018 [acessado em 28 jan 2022]. Disponível em: Disponível em: http://189.28.128.100/dab/docs/portaldab/publicacoes/guiadebolso_folder.pdf
http://189.28.128.100/dab/docs/portaldab... and published in the ConectSUS¹¹11. Brasil. Ministério da Saúde. ConectSUS [Internet]. 2022 [acessado em 28 jan 2022]. Disponível em: Disponível em: https://conectesus-paciente.saude.gov.br/menu/home-default
https://conectesus-paciente.saude.gov.br... application, being recommended in obesity management activities in the context of Primary Health Care¹²12. Brasil. Ministério da Saúde. Instrutivo de abordagem coletiva para o manejo da obesidade no SUS: caderno de atividades. Brasília: Ministério da Saúde, 2021..

Despite these applications, additional validation steps are essential so that the use of this scale is more widespread and encouraged. In a previous study, it underwent content validation (by a panel of experts), draft validation (pre-tests with target audience) and initial stages of construct validation (internal structure analysis via exploratory and confirmatory factor analyses)⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... . However, according to the concept of validation by Furr and Bacharach¹³13. Furr RM, Bacharach VR. Pscychometrics: an introduction. 2nd edition. Thousand Oaks: SAGE Publications; 2013., one must still verify whether the measure generated by the scale correlates with variables that are theoretically associated with each other and whether it allows comparisons between different subgroups of the population.

Of the two missing aspects, the first can be evaluated through convergent validation and is important to confirm the construct. The second can be tested by means of invariance analysis and is essential for analyzing the distribution of the phenomenon in the population, as it allows comparison between groups¹³13. Furr RM, Bacharach VR. Pscychometrics: an introduction. 2nd edition. Thousand Oaks: SAGE Publications; 2013.. This study aims to verify the convergent validity and invariance of a scale that measures adherence to the recommendations of the Dietary Guide for the Brazilian Population.

METHODS

PARTICIPANTS AND DATA COLLECTION

Study carried out with a subsample of participants from the NutriNet-Brasil cohort, a fully online survey coordinated by the Center for Epidemiological Research in Nutrition and Health at USP (NUPENS-USP), whose objective was to investigate the relation between diet and morbidity/mortality from chronic non-communicable diseases in Brazil. People aged 18 and over living in Brazil voluntarily participated. The selection of participants in this research took place in two stages:

In the first stage, the objective of the draw was to obtain complete answers from 1,225 individuals (sample calculation performed according to the needs of another study linked to the same research project) distributed in quotas according to sex, educational level and region of residence, following proportions observed in the demographic census of 2010 from the Brazilian Institute of Geography and Statistics (IBGE). Regarding education, it was taken into account that, in NutriNet-Brasil, a greater participation of individuals with a higher level of education is expected than that observed in the Brazilian population in general. Therefore, two education groups were established with a cut-off point at the highest level collected by the IBGE, “up to complete high school” and “complete higher education or more”. Participants from NutriNet-Brasil who had reached the tenth month of follow-up were eligible for this draw, as the present study required data collected in questionnaires applied in previous months of follow-up (n=48,091).

In order for all quotas to be filled, a total of individuals equivalent to three times the desired number were notified in each quota, with the exception of quotas whose goal was lower than 30, for which 90 individuals were notified. Thus, 4,206 individuals were contacted, of which 2,083 responded to the scale, fulfilling all quotas. In the second stage, participants eligible for this research were selected based on the inclusion criterion established—having answered three food questionnaires within a maximum range of 60 days—, totaling 1,309 subjects. Important to stress out that this number exceeds the recommended minimum of 200 individuals for convergent validation, which is required even for weak correlations to be statistically significant¹⁴14. Cade J, Thompson R, Burley V, Warm D. Development, validation and utilisation of food-frequency questionnaires - a review. Public Health Nutr 2002; 5(4): 567-87. https://doi.org/10.1079/PHN2001318
https://doi.org/https://doi.org/10.1079/... .

INSTRUMENTS

Scale of dietary practices according to recommendations of the Dietary Guide for the Brazilian Population

This is a self-administered scale aimed at the adult Brazilian population (18 to 60 years old), with 24 four-point Likert-type items (“never”, “rarely”, “often”, “always”), comprising four dimensions of adequate and healthy eating addressed in the guide: food choice, modes of eating, planning and household organization.

Its development was based on elaboration of a pool of 96 items, afterwards submitted to a panel of experts, to pre-tests with potential users of the scale and to dimensionality tests. The final version, tested for application both in printed version and electronically, also underwent a reproducibility study⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... . Prior to data collection for this research, a group of experts carried out a new round of review, which resulted in wording adjustments for six items. In addition, the response options of the original version (“strongly disagree”, “disagree”, “agree” and “strongly agree”) were replaced by the current frequency scale, as proposed by experts. The new proposal was previously tested with 300 subjects, and the instrument was found to retain its psychometric properties (unpublished data).

Table 1 of the Supplementary Material shows the items according to dimension, from most to least representative of each one, that is, items that had higher factorial loads in the confirmatory factor analysis performed in the previous study⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... . Items that were somewhat changed are accompanied by their original version.

Food consumption questionnaire according to NOVA

In order to obtain the variables for comparison, a questionnaire was used to estimate the consumption of fresh and minimally processed foods (G1) and ultra-processed foods (G4), extreme groups of the NOVA classification¹⁵15. Sattamini IF. Instrumentos de avaliação da qualidade de dietas: desenvolvimento, adaptação e validação no Brasil [tese de doutorado]. São Paulo: Faculdade de Saúde Pública da Universidade de São Paulo (USP); 2019.^,1616. Costa CS, Faria RF, Gabe KT, Sattamini IF, Khandpur N, Leite FHM, et al. Escore Nova de consumo de alimentos ultraprocessados: descrição e avaliação de desempenho no Brasil. Rev Saúde Pública 2021; 55: 13. https://doi.org/10.11606/s1518-8787.2021055003588
https://doi.org/https://doi.org/10.11606... . In this questionnaire, the individual is asked to select all items consumed on the previous day from a list of 33 G1 foods and 24 G4 foods. G1 items are distributed as fruits (10), greenery (9), vegetables (9) and whole grains (5); G4 items comprise sweetened beverages (6), products that replace or accompany meals (10), and products commonly consumed in the form of snacks (7) (full version available in Table 2 of the Supplementary Material). An original version of this questionnaire was validated with users at a Primary Health Care service¹⁵15. Sattamini IF. Instrumentos de avaliação da qualidade de dietas: desenvolvimento, adaptação e validação no Brasil [tese de doutorado]. São Paulo: Faculdade de Saúde Pública da Universidade de São Paulo (USP); 2019.. The part related to G4 in the version adapted for NutriNet-Brasil, used in this investigation, has already been validated¹⁶16. Costa CS, Faria RF, Gabe KT, Sattamini IF, Khandpur N, Leite FHM, et al. Escore Nova de consumo de alimentos ultraprocessados: descrição e avaliação de desempenho no Brasil. Rev Saúde Pública 2021; 55: 13. https://doi.org/10.11606/s1518-8787.2021055003588
https://doi.org/https://doi.org/10.11606... ; the validation of G1 components will be published soon. Each individual answered the questionnaire on three non-consecutive random days, with intervals of 15 to 30 days, to minimize intra-individual variability of food consumption¹⁷17. Willett W. Nutritional epidemiology. 3rd edition. Oxford: Oxford University Press; 2012..

Statistical analysis

Convergent Validation

The score on the total scale (eGuide) and by dimension was calculated by the simple sum of answers provided to each item, with “never” = 0, “rarely” = 1, “often” = 2 and “always” = 3 for the direct items (planning and household organization dimensions), or the opposite for inverted items, in which the answer “never” represents the most appropriate practice and, therefore, receives the score of 3 (modes of eating and food choice dimensions). Thus, the score can range from 0 to 72. Consumption scores of fresh and minimally processed foods (eG1) and ultra-processed foods (eG4) were composed of the average number of items consumed on each of the three days, and could range from 0 to 33 and from 0 to 23, respectively. The scores were compared using Spearman’s correlation, where we expected to see a positive correlation between eGuia and eG1 and a negative correlation between eGuia and eG4. Correlations up to |0.5| were considered weak; >|0.5| a |0.7|, moderate; and >|0.7|, strong¹⁷17. Willett W. Nutritional epidemiology. 3rd edition. Oxford: Oxford University Press; 2012.^,1818. Akoglu H. User’s guide to correlation coefficients. Turk J Emerg Med 2018; 18(3): 91-3. https://doi.org/10.1016/j.tjem.2018.08.001
https://doi.org/https://doi.org/10.1016/... . Also part of the convergent validity model, the percentage of individuals placed in the upper quartile of each score according to age group was analyzed. The χ² test was used to assess statistically significant differences between prevalence values according to age group for each of the scores.

Invariance analysis

The sample was divided into two subgroups for each variable of interest: sex (female and male); age (≤37 and >37, 37 being the sample median); and educational level (≤complete high school and >incomplete higher education). Confirmatory factor analysis was used with multiple groups, which makes it possible to verify whether the model maintains its original properties when tested in a stratified manner in subgroups. Three levels of invariance were tested, where the subsequent level depends on the satisfaction of the previous, less constrained:

Conclusions can be drawn by observing the variation of goodness of fit indices as the restrictions are inserted in the model¹⁹19. Brown TA. Confirmatory factor analysis for applied research methodology in the social sciences. New York: Guilford Press; 2015.. The most recommended indices for invariance analysis studies were adopted: Root Mean Square Error of Approximation (RMSEA), which estimates the fit for the sample, compensating for the model complexity when considering the number of estimated parameters; the Comparative Fit Index, which compares the proposed model to a standardized one; and the Standardized Root Mean Square Residual (SRMR), which is an indicator of the average discrepancy between correlations observed in the sample correlation matrix and correlations predicted by the model. For the configural level, the model was considered adequate when at least two of these criteria were met: RMSEA ≤0.08, SRMR ≤0.10 and CFI ≥0.90, which would indicate the maintenance of the model’s original characteristics. For the factorial and metric levels, the difference (∆) of indicators in relation to the previous, less restricted step was analyzed. The model was considered invariant when at least two of the following criteria were met: ∆CFI ≤0.015; ∆RMSEA ≤0.015; and ∆SRMR ≤0.030 for the factorial level and ≤0.015 for the metric level²⁰20. Putnick DL, Bornstein MH. Measurement invariance conventions and reporting: the state of the art and future directions for psychological research. Dev Rev 2016; 41: 71-90. https://doi.org/10.1016/j.dr.2016.06.004
https://doi.org/https://doi.org/10.1016/... . All analyses were performed in the RStudio software version 6.4.

Ethical aspects

The study was approved by the Research Ethics Committee of the Public Health School of Universidade de São Paulo (CAAE: 29139220.9.0000.5421).

RESULTS

Most of the 1,309 participants were females (53.0%), had completed high school (65.8%) and reported being white (70.4%). The most prevalent age group was 40-59 years (32.5%) and the region was Southeast (39%). Participants obtained on average 44.1 points on the scale of adherence to guidelines, with eGuia ranging from 14 to 70. The mean score of three days of food consumption was 2.3 for the eG4 (ranging from 1 to 10 .7) and 7.2 for eG1 (ranging from 0 to 20.3) (Table 1).

Table 2 shows that all correlations of eGuia with eG1 were positive and, with eG4, negative (p<0.0001), which is in accordance with expectations. The total eGuia showed a moderate correlation with both consumption scores. By dimension, moderate correlations were seen between planning and eG1, and between food choice and eG4. The other correlations by dimension were weak.

Figure 1 shows the percentage of individuals placed in the last quartile of eGuia, and of eG1 and eG4 according to age group. The probability of being placed in the quartile of greater adherence to the dietary practices recommended by the guide (Q4 of eGuide) tended to increase with age, following the trend of food consumption. According to the χ² test, the distribution of quartile classifications differed from the expected if there was no association between the score and age variables (p<0.001 for the three scores).

In the invariance analysis for all subgroups, the model’s goodness of fit indices varied within the limits allowed to conclude that the measure is equivalent in different strata of the tested characteristics (Table 3).

DISCUSSION

In this study, the scale of adherence to eating practices according to the Dietary Guide for the Brazilian Population was evaluated in a convergent validation and invariance analyses for subgroups of sex, age and education. As expected, the score on the scale was associated with higher consumption of fresh and minimally processed foods and inversely associated with consumption of ultra-processed foods. Furthermore, the results of the invariance analysis show that the scale is equivalent for different subgroups of the tested characteristics.

There is growing evidence of the negative impact of ultra-processed foods on health and the substitution effect that these foods have on dietary patterns based on fresh and minimally processed foods²¹21. Askari M, Heshmati J, Shahinfar H, Tripathi N, Daneshzad E. Ultra-processed food and the risk of overweight and obesity: a systematic review and meta-analysis of observational studies. Int J Obes (Lond.) 2020; 44(10): 2080-91. https://doi.org/10.1038/s41366-020-00650-z
https://doi.org/https://doi.org/10.1038/... ^,2222. Pagliai G, Dinu M, Madarena MP, Bonaccio M, Iacoviello L, Sofi F. Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. Br J Nutr 2021; 125(3): 308-18. https://doi.org/10.1017/S0007114520002688
https://doi.org/https://doi.org/10.1017/... . The adoption of indicators based on these two food groups is justified by the golden rule of the guide, which recommends that in-natura and minimally processed foods (predominantly plant-based) and their culinary preparations constitute the basis of the diet, and that ultra-processed foods be avoided¹1. Brasil. Ministério da Saúde. Secretaria de Atenção Básica. Departamento de Atenção Básica. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde; 2014.. Thus, the direction of the observed correlations is in line with the expected: people with a higher degree of adherence to guidelines consumed more in-natura and minimally processed foods and a less ultra-processed foods.

Although the magnitudes of correlations varied from weak to moderate, according to the paradigm adopted in the guide, healthy eating is not limited to food consumption, but also encompasses the context of meals and the pleasure provided by food¹1. Brasil. Ministério da Saúde. Secretaria de Atenção Básica. Departamento de Atenção Básica. Guia alimentar para a população brasileira. Brasília: Ministério da Saúde; 2014.. This aspect may explain the fact that the dimensions with the weakest correlations with consumption scores were modes of eating and household organization, precisely the ones whose items are more directly related to the recommendations of chapter 4 in the guide (“The act of eating and commensality”). On the other hand, the dimension with the highest correlation with the G1 score was planning and, with the G4 score, food choice, which contain items directly related to the habitual consumption of foods in these groups and are thus closer to a direct measure of food consumption.

Castelo et al.²³23. Castelo AFM, Schäfer M, Silva ME. Food practices as part of daily routines: a conceptual framework for analysing networks of practices. Appetite 2021; 157: 104978. https://doi.org/10.1016/j.appet.2020.104978
https://doi.org/https://doi.org/10.1016/... define “eating practices” as a set of daily routines related to the act of eating, which ranges from meal planning to consumption itself. The structuring of these practices in people’s lives is determined by materials and skills such as access to food and cooking skills, and by the meanings attributed to food such as concern with health and pleasure in eating. The practices resulting from the combination of these three elements—materials, skills and meanings—are still influenced by time, space and social context.

Given the multiplicity of factors linked to dietary practices, the correlations found in this work are plausible and corroborated by the literature. Another convergent validation study also found correlations ranging from 0.16 to 0.46 between a score of eating habits and indicators of food consumption among adolescents²⁴24. Johnson F, Wardle J, Griffith J. The adolescent food habits checklist: reliability and validity of a measure of healthy eating behaviour in adolescents. Eur J Clin Nutr 2002; 56(7): 644-9. https://doi.org/10.1038/sj.ejcn.1601371
https://doi.org/https://doi.org/10.1038/... . Stjernqvist et al.²⁵25. Stjernqvist NW, Elsborg P, Ljungmann CK, Benn J, Bonde AH. Development and validation of a food literacy instrument for school children in a Danish context. Appetite 2021; 156: 104848. https://doi.org/10.1016/j.appet.2020.104848
https://doi.org/https://doi.org/10.1016/... found that a food literacy score explained 41.0% of the variance of another score with a similar construct, health literacy, but only 5.7% of the variance in food consumption score. According to a systematic review by Spronk et al.²⁶26. Spronk I, Kullen C, Burdon C, O’Connor H. Relationship between nutrition knowledge and dietary intake. Br J Nutr 2014; 111(10): 1713-26. https://doi.org/10.1017/S0007114514000087
https://doi.org/https://doi.org/10.1017/... , most studies that investigated the association between knowledge on food and nutrition and quality of food consumption found positive but weak correlations. Although these constructs are not the same as in this study, they are also not directly observable, but conceptually associated with dietary practices, allowing for comparison.

The performance of eGuia in discriminating age groups similarly to food consumption variables also reinforces its convergent validity. Several studies with populations of different age groups consistently reported a direct relationship between age and food quality. The relative share of ultra-processed foods in total calories tends to be lower—and, consequently, the share of fresh and minimally processed foods tends to be higher—as age increases²⁷27. Costa CS, Sattamini IF, Steele EM, Louzada MLC, Claro RM, Monteiro CA. Consumption of ultra-processed foods and its association with sociodemographic factors in the adult population of the 27 Brazilian state capitals (2019). Rev Saude Publica 2021; 55: 47. https://doi.org/10.11606/s1518-8787.2021055002833
https://doi.org/https://doi.org/10.11606... ^,2828. Baraldi LG, Steele EM, Canella DS, Monteiro CA. Consumption of ultra-processed foods and associated sociodemographic factors in the USA between 2007 and 2012: evidence from a nationally representative cross-sectional study. BMJ Open 2018; 8(3): e020574. https://doi.org/10.1136/bmjopen-2017-020574
https://doi.org/https://doi.org/10.1136/... ^,2929. Khandpur N, Cediel G, Obando DA, Jaime PC, Parra DC. Sociodemographic factors associated with the consumption of ultra-processed foods in Colombia. Rev Saude Publica 2020; 54: 19. https://doi.org/10.11606/s1518-8787.2020054001176
https://doi.org/https://doi.org/10.11606... . This is consistent with the results of a previous study carried out with the scale, in which a linear association was found between the score of adherence to guidelines and participants’ age⁹9. Gabe KT, Jaime PC. Práticas alimentares segundo o guia alimentar para a população brasileira: fatores associados entre brasileiros adultos, 2018. Epidemiol Serv Saúde 2020; 29(1): e2019045. https://doi.org/10.5123/S1679-49742020000100019
https://doi.org/https://doi.org/10.5123/... .

Finally, it was also analyzed whether the measures generated by the scale are equivalent in different sociodemographic groups. Few studies have analyzed the invariance of psychometric measures in the area of food, which makes this analysis one of the strengths of this study. Among the features explored here, sex seems to be the most frequently analyzed in studies of this type: three with this objective were found, and all of them also reported equivalence in the evaluated instruments—scales for addiction to food³⁰30. Carr MM, Schulte EM, Saules KK, Gearhardt AN. Measurement invariance of the modified yale food addiction scale 2.0 across gender and racial groups. Assessment 2020; 27(2): 356-64. http://doi.org/10.1177/1073191118786576
https://doi.org/http://doi.org/10.1177/1... , compulsive eating³¹31. Escrivá-Martínez T, Galiana L, Rodríguez-Arias M, Baños RM. The binge eating scale: structural equation competitive models, invariance measurement between sexes, and relationships with food addiction, impulsivity, binge drinking, and body mass index. Front Psychol 2019; 10: 530. http://doi.org/10.3389/fpsyg.2019.00530
https://doi.org/http://doi.org/10.3389/f... and eating motivations³²32. Serier KN, Belon KE, Smith JM, Smith JE. Psychometric evaluation of the power of food scale in a diverse college sample: measurement invariance across gender, ethnicity, and weight status. Eat Behav 2019; 35: 101336. http://doi.org/10.1016/j.eatbeh.2019.101336
https://doi.org/http://doi.org/10.1016/j... . No studies evaluating the invariance according to age and educational level of scales related to food were found.

It is worth noting that the choice of variables for invariance studies depends not only on the heterogeneity of the instrument’s target audience, but also on the characteristics considered critical to the measured construct¹⁹19. Brown TA. Confirmatory factor analysis for applied research methodology in the social sciences. New York: Guilford Press; 2015.^,3333. Damásio BF. Contribuições da Análise Fatorial Confirmatória Multigrupo (AFCMG) na avaliação de invariância de instrumentos psicométricos. Psico-USF 2013; 18(2): 211-20. https://doi.org/10.1590/S1413-82712013000200005
https://doi.org/https://doi.org/10.1590/... . The choice of variables sex, age and education in this study lives up to the differences observed in the diet of Brazilians according to subgroups of these characteristics, as shown in a survey that evaluated the prevalence and distribution of healthy and unhealthy eating markers based on the National Health Survey³⁴34. Santin FG, Gabe KT, Levy RB, Jaime PC. Marcadores de consumo alimentar e fatores associados no Brasil: distribuição e evolução, Pesquisa Nacional de Saúde, 2013 e 2019. Cadernos de Saúde Pública 2022; (No prelo).. The study also shows that the variables income and skin color accompany schooling, evidencing their role as an indicator of socioeconomic status. The heterogeneity of the scale’s target audience (adult Brazilian population) and the relevance to the context of variables adopted accentuate the importance of the analysis.

This study has some limitations. It is possible that the convenience sample of the NutriNet-Brasil study is composed of people more interested in food and, therefore, does not represent the Brazilian population. However, people with greater interest in the topic are not expected to have different performance in analyses, especially because the factorial structure of the instrument found in this study corroborates a previous work with the same scale, whose sample did not have this same profile⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... . Furthermore, the draw based on quotas by region, sex and educational level aimed to bring the profile of the subsample closer to that of the Brazilian population. Despite this, the inclusion of individuals with a lower level of education was compromised. It is noteworthy that the previous study included people with lower levels of education in the stages of apparent validation and evaluation of the internal structure⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... .

Conversely, this investigation makes an important contribution to both national and international literatures. At the national level, the validation of this instrument can boost its use by researchers and public managers across the country for describing the level of adherence of population groups to the guide, for health promotion activities or for evaluating the impact of interventions, as their temporal stability was tested through test-retest⁶6. Gabe KT, Jaime PC. Development and testing of a scale to evaluate diet according to the recommendations of the Dietary Guidelines for the Brazilian Population. Public Health Nutr 2019; 22(5): 785-96. https://doi.org/10.1017/S1368980018004123
https://doi.org/https://doi.org/10.1017/... . Although applicable only in Brazil, this study adds knowledge to the growing body of literature about food quality assessment metrics, which has increasingly identified the need for tools that encompass multiple dimensions of food in addition to the already consolidated consumption metrics. This study can also inspire researchers from other countries such as Ecuador, Israel, Peru and Uruguay, which also present non-quantitative recommendations based on NOVA³⁵35. Koios D, Machado P, Lacy-Nichols J. Representations of ultra-processed foods: a global analysis of how dietary guidelines refer to levels of food processing. Int J Health Policy Manag 2022. http://doi.org/10.34172/ijhpm.2022.6443
https://doi.org/http://doi.org/10.34172/... , to develop instruments applicable in their contexts.

In conclusion, the scale for the assessment of eating practices according to recommendations of the Dietary Guide for the Brazilian Population has convergent validity, and the score generated by it is comparable between subgroups of sex, age and education. This instrument is, therefore, valid and useful to assess adherence to recommendations and the impacts of local interventions based on it.

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