According to estimates in the Global Burden of Disease Study, suboptimal dietary intakes account for 22 % of total deaths and 15 % of disability-adjusted life years annually(1) and exceed those of any other risk factor including tobacco smoking(Reference Willett, Rockstrom and Loken2). Because of the complex and varied nature of individual characteristics that are related to dietary behaviours(Reference Ordovas, Ferguson and Tai3), an understanding of the factors that shape food choices and eating behaviours and thus determine the quality of diet is imperative(Reference Lyerly and Reeve4). According to the food choice process model(Reference Furst, Connors and Bisogni5), food choice values are supposed to represent the proximal influences on food choice and eating behaviours, conveying the effects of more distal determinants, including life course factors (such as socio-economic factors), socio-cultural resources and cognitive resources(Reference Lyerly and Reeve4).
Another relevant concept that has emerged recently is that of food literacy. Although there are several definitions of food literacy(Reference Truman, Lane and Elliott6–Reference Amouzandeh, Fingland and Vidgen8), the most widely cited definition is that developed by Vidgen and Gallegos(Reference Vidgen and Gallegos9), in which food literacy is described as ‘a collection of inter-related knowledge, skills and behaviours required to plan, manage, select, prepare and eat food to meet needs and determine intake’(Reference Vidgen and Gallegos9). Thus, food literacy is not just concerned with nutrition knowledge but also includes skills and behaviours, from knowing where food comes from to the ability to select and prepare these foods and behave in ways that meet dietary guidelines(Reference Vaitkeviciute, Ball and Harris10).
To date, only a limited number of studies have examined aspects of food choice values and food literacy in relation to some aspects of dietary behaviours(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11–Reference da Costa, Severo and Oliveira20). For example, a survey of Finnish adults suggests that the less healthy dietary habits (such as low consumption of vegetables/fruit and high consumption of energy-dense foods) are partly attributable to the higher priority of motives related to price and familiarity and the lower priority of health motives(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11). Several studies have also shown that a composite measure of food literacy is associated with a higher consumption of vegetables, fruit and fish and a lower consumption of sugar-sweetened beverages in Dutch adults(Reference Poelman, Dijkstra and Sponselee12) and a higher score of simple diet quality score in Korean adults(Reference Park, Park and Park13). Further, a relatively consistent positive association between nutrition knowledge and diet quality was observed(Reference Lavelle, Bucher and Dean14,Reference McGowan, Pot and Stephen15,Reference Bonaccio, Di Castelnuovo and Costanzo18,Reference Kullen, Farrugia and Prvan19) , with some exceptions(Reference Sexton-Dhamu, Livingstone and Pendergast16). Conversely, findings on cooking skills and food skills seem inconsistent. In an Australian sample consisting of predominantly females (80 %) with relatively high education and socio-economic status, a simple measure of diet quality was positively associated with food skills, but not with cooking skills(Reference Lavelle, Bucher and Dean14), whereas in a nationally representative sample of Irish adults, cooking skills, but not food skills, appeared to be associated with some aspects of healthy dietary behaviours such as lower saturated fat intake(Reference McGowan, Pot and Stephen15). For eating behaviours, a prospective cohort study among children showed that a higher score on food fussiness (i.e. tendency to refuse new foods at first) and a lower score on the enjoyment of food were associated with a lower quality of the diet(Reference da Costa, Severo and Oliveira20). To our knowledge, however, no research has comprehensively examined food choice values and food literacy in relation to overall diet quality in free-living settings.
Additionally, some of the previous studies mentioned have not considered even fundamental factors such as sex and age(Reference Kullen, Farrugia and Prvan19) or have relied on relatively crude or unvalidated measures of diet quality(Reference Poelman, Dijkstra and Sponselee12,Reference Park, Park and Park13,Reference McGowan, Pot and Stephen15) . Furthermore, almost all previous studies have been conducted in Western countries(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11,Reference Poelman, Dijkstra and Sponselee12,Reference Lavelle, Bucher and Dean14–Reference da Costa, Severo and Oliveira20) . Conversely, research in Asian countries, including Japan, where dietary habits are considerably different from those in Western countries(Reference Murakami, Shinozaki and Livingstone21–Reference Murakami, Livingstone and Sasaki27), is limited(Reference Park, Park and Park13). Therefore, the aim of the present cross-sectional study was to comprehensively examine food choice values and food literacy (characterised by nutrition knowledge, cooking and food skills, and eating behaviours) in relation to the nutritional quality of the overall diet in a nationwide sample of free-living Japanese adults. On the basis of previous studies(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11–Reference da Costa, Severo and Oliveira20), we hypothesised that several aspects of food choice values (such as health and accessibility) and food literacy (such as nutrition knowledge, cooking skills, food skills, food fussiness and enjoyment of food) are associated with diet quality. We also hypothesised that the association would be clearer for females than males, since it is usually females who are in charge of food preparation in Japanese households(Reference Tani, Fujiwara and Kondo28).
Methods
Study procedure and participants
Detailed descriptions of the study procedure and participants are available elsewhere(Reference Murakami, Shinozaki and Yuan29). Briefly, between October and December 2018, a questionnaire survey was conducted in thirty-two prefectures, where the residents account for > 85 % of the total population of Japan. The target population consisted of adult participants in the MINNADE (MINistry of health, labour and welfare-sponsored Nationwide study on Dietary intake Evaluation) study, a dietary record survey(Reference Murakami, Livingstone and Masayasu30). This was because the present study was originally designed as an add-on to the MINNADE study; however, the use of data obtained within the MINNADE study has not yet been permitted by the Ministry of Health, Labour and Welfare, Japan(Reference Murakami, Livingstone and Masayasu30). Potential participants were apparently healthy Japanese adults living in private households in Japan. Exclusion criteria were dietitians, individuals living with a dietitian, those working with a research dietitian, those who had received dietary counselling from a doctor or dietitian, those taking insulin treatment for diabetes, those receiving dialysis treatment and pregnant or lactating women. Participation of only one person per household was permitted. These criteria were made in accordance with those in the MINNADE study, the ultimate purpose of which was to describe nationwide data on dietary characteristics and eating behaviours in Japan(Reference Murakami, Livingstone and Masayasu30).
Recruitment of participants and data collection were conducted by our research dietitians (n 476). The non-random sampling procedure was performed to reflect the proportion of the overall Japanese population in each region but with the intention to recruit an equal number of males and females. Of 2983 adult participants in the MINNADE study, 2248 individuals participated in the present study (response rate: 75 %). For analysis, we excluded participants with missing information related to the variables of interest (n 5) and those aged outside the 19–80 years age range (n 12), leaving 2231 participants aged 19–80 years. All information was collected by questionnaires specially designed for this survey. Responses to all questions (except for those regarding nutrition knowledge) were checked by staff at the study centre. If any responses were missing, the participant was asked to complete the questions again in person or by telephone.
The study was conducted according to the guidelines laid out in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Ethics Committee of the University of Tokyo Faculty of Medicine (protocol code: 12 031; date of approval: 17 July 2018). Written informed consent was obtained from each participant and from a parent or guardian for participants aged < 20 years.
Assessment of food choice values
Food choice values were assessed using the Japanese version of the food choice values scale(Reference Lyerly and Reeve4). As detailed descriptions on the development process of the Japanese version (as well as for other instruments shown below) are available elsewhere(Reference Murakami, Shinozaki and Yuan29), only a brief description is provided here. In short, the food choice values scale is a twenty-five-item, self-administered questionnaire measuring eight factors of food choice values: accessibility, convenience, health/weight control, tradition, sensory appeal, organic, comfort and safety(Reference Lyerly and Reeve4). Participants were asked to answer how important each item is when deciding what foods to buy or eat on a daily basis. The possible responses, based on a Likert scale, ranged from 1 to 5 (1: not at all, 2: a little, 3: moderately, 4: quite a bit and 5: very). The score for each factor was calculated by the sum of the scores divided by the number of items (four items for organic and three items for others), with possible scores ranging from 1 to 5. In the present sample, Cronbach’s α for the assessment of internal consistency ranged from 0·61 (sensory appeal) to 0·87 (convenience)(Reference Murakami, Shinozaki and Yuan29), which was comparable to observations in previous studies (range: 0·54–0·89)(Reference Lyerly and Reeve4,Reference Lyerly31) .
Assessment of food literacy
In this study, food literacy was characterised by nutrition knowledge, cooking and food skills, and eating behaviours, in accordance with the most widely used description of food literacy: ‘a collection of inter-related knowledge, skills and behaviours required to plan, manage, select, prepare and eat food to meet needs and determine intake’(Reference Vidgen and Gallegos9).
Nutrition knowledge
Nutrition knowledge was assessed using the Japanese general nutrition knowledge questionnaire (JGNKQ); the structure, validity and reliability of the JGNKQ have been described elsewhere(Reference Matsumoto, Tanaka and Ikemoto32). Briefly, the original version of the JGNKQ is a 147-item, self-administered questionnaire consisting of five sections: dietary recommendations, sources of nutrients, choosing everyday foods, diet–disease relationships and reading a food label. The JGNKQ used in this study was a 143-item version in which four items with a very low prevalence of correct answers in the original version were removed. For each item, the correct response was assigned 1 point, whereas an incorrect or missing response was assigned 0 point. Thus, the possible total score ranged from 0 to 143, with a higher score reflecting a higher level of nutrition knowledge. In the present sample, Cronbach’s α for the 143 items was 0·96(Reference Murakami, Shinozaki and Yuan29), which was comparable to that observed in the development process of the JGNKQ (0·95)(Reference Matsumoto, Tanaka and Ikemoto32).
Cooking and food skills
Cooking skills and food skills were assessed using the Japanese version of the English scale for cooking and food skills, a self-administered questionnaire(Reference Lavelle, McGowan and Hollywood33). Briefly, questions on cooking skills (n 14) ask about cooking methods and food preparation techniques, whereas questions on food skills (n 19) ask about meal planning and preparation, shopping, budgeting, resourcefulness and label reading/consumer awareness. Participants were asked to rate how well they felt they performed each of the skills described according to a seven-point Likert scale (1: very poor, 7: very good). An option of ‘never/rarely do it’ was also available for participants who considered that a skill is not used; a score of 0 was assigned when this response was selected. The scores of cooking skills and food skills were calculated as the sum of all the items; thus, possible scores ranged from 0 to 98 for cooking skills and from 0 to 133 for food skills. In the present sample, Cronbach’s α was 0·95 for the fourteen cooking skill items and 0·96 for the nineteen food skill items(Reference Murakami, Shinozaki and Yuan29), which was higher than those observed in the original study (range: 0·78–0·94)(Reference Lavelle, McGowan and Hollywood33).
Eating behaviours
Eating behaviours were assessed using the Japanese version of the Adult Eating Behavior Questionnaire (AEBQ) prepared based on the original English version(Reference Hunot, Fildes and Croker34). Briefly, the AEBQ is a thirty-five-item, self-administered questionnaire, measuring four food approach scales, namely hunger (five items), food responsiveness (four items), emotional overeating (five items) and enjoyment of food (three items), as well as four food avoidance scales, namely satiety responsiveness (four items), emotional undereating (five items), food fussiness (five items) and slowness in eating (four items)(Reference Hunot, Fildes and Croker34). Item responses were rated based on a five-point Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’, and a mean score was calculated for each scale (possible score ranging from 1 to 5). In the present sample, Cronbach’s α ranged from 0·65 (slowness in eating) to 0·89 (emotional undereating)(Reference Murakami, Shinozaki and Yuan29), which was comparable to those observed in previous studies (range: 0·67–0·97)(Reference Hunot, Fildes and Croker34–Reference Hunot-Alexander, Arellano-Gomez and Smith38).
Dietary assessment
Information on dietary habits during the preceding month was assessed using a brief-type diet history questionnaire (BDHQ), details of which have been described elsewhere(Reference Kobayashi, Murakami and Sasaki39,Reference Kobayashi, Honda and Murakami40) . In brief, the BDHQ is a four-page self-administered questionnaire which consists of structured questions asking about the consumption frequency of selected foods commonly consumed in Japan, as well as general dietary behaviour and usual cooking methods. Estimates of daily intake of foods (fifty-eight items in total), energy and selected nutrients were calculated using an ad hoc computer algorithm for the BDHQ. This algorithm incorporates the sex-specific portion size, determined mainly based on recipe books for Japanese dishes(Reference Kobayashi, Murakami and Sasaki39), and nutrient composition of each food item derived from the 2015 version of the Standard Tables of Food Composition in Japan(41).
Information on dietary habits during the preceding month was also assessed using a food combination questionnaire (FCQ), a four-page self-administered questionnaire. Details of the FCQ’s development process, structure, content and algorithms for dietary intake calculation have been published elsewhere(Reference Murakami, Livingstone and Shinozaki26). Briefly, in the FCQ, questions on consumption frequency of staple foods (as the number of days per week) are followed by questions on relative consumption frequency of accompanying foods (‘always’, ‘sometimes’ and ‘never’) for each meal type (i.e. breakfast, lunch, dinner and snacks). These were determined based on the most commonly consumed combinations of seventeen selected food groups identified in the 16-d weighed dietary record data collected from 242 Japanese adults aged 31–81 years(Reference Murakami, Livingstone and Sasaki27) using the frequent item sets data mining methods(Reference Borgelt42). On the basis of a series of ad hoc computer algorithms in the FCQ(Reference Murakami, Livingstone and Shinozaki26,Reference Murakami, Livingstone and Sasaki27) and the 2015 version of the Standard Tables of Food Composition in Japan(41), estimated intakes of food groups, energy and selected nutrients were calculated. The calculation was done for each meal type, and the overall intake was calculated as the sum of the intake of each meal type.
Calculation of diet quality score
In the present study, we used the Healthy Eating Index 2015 (HEI-2015)(Reference Krebs-Smith, Pannucci and Subar43–Reference Panizza, Shvetsov and Harmon45) as a measure of diet quality. The HEI-2015 is a 100-point scale to assess compliance with the 2015–2020 Dietary Guidelines for Americans(46), with a higher score indicating a better quality of overall diet. The HEI-2015 consists of nine adequacy components (total fruits, whole fruits, total vegetables, greens and beans, whole grains, dairy products, total protein foods, seafood and plant proteins, and fatty acids as the ratio of the sum of PUFA and MUFA to SFA) and four moderation components (refined grains, Na, added sugars and saturated fats). The efficacy of the HEI-2015 in assessing the overall diet quality of Japanese has been supported by our previous analyses: a higher total score in the HEI-2015 was associated with favourable patterns of the overall diet, including higher intakes of dietary fibre and key vitamins and minerals and lower intakes of saturated fats, added sugars and Na(Reference Murakami, Livingstone and Fujiwara47,Reference Murakami, Shinozaki and Livingstone48) .
For both dietary assessment tools (i.e. BDHQ and FCQ), component scores needed for the calculation of HEI-2015 were calculated using the Japanese version(Reference Murakami, Livingstone and Fujiwara49) of the US Food Patterns Equivalents Database(Reference Bowman, Clemens and Friday50), except for fatty acids and Na, for which the 2015 version of the Standard Tables of Food Composition in Japan(41) was used. As described in detail elsewhere(Reference Murakami, Livingstone and Fujiwara49), we calculated the HEI-2015 component scores based on energy-adjusted values of overall dietary intake, namely amount per 1000 kcal of energy or percentage of energy, except for fatty acids, and then we summed up these scores to obtain the HEI-2015 (total) score. We derived the HEI-2015 score for total diet from both the BDHQ and the FCQ.
The relative validity of the BDHQ and FCQ for estimating the HEI-2015 has been examined. Briefly, the Pearson correlation coefficient between the BDHQ and a 16-d weighed dietary record was 0·52 in women (n 121) and 0·43 in men (n 121)(Reference Murakami, Livingstone and Fujiwara49). The Pearson correlation coefficient between the FCQ and a 4-d weighed dietary record was 0·50 among both 111 women and 111 men(Reference Murakami, Shinozaki and Livingstone51).
Assessment of basic characteristics
In this study, sex was self-reported. Age at the time of the study was calculated based on birth date of the participant and the date the questionnaires were answered. Self-reported information on body height and weight was obtained, based on which BMI was calculated (in kg/m2). We also calculated the ratio of reported energy intake (derived from the BDHQ or FCQ) to estimated energy requirement (as a measure of overall accuracy of dietary reporting). For each participant, estimated energy requirement was calculated based on sex-specific equations published from the US Dietary Reference Intakes(52), using information on age, body height, body weight and physical activity. We assumed ‘low active’ level of physical activity (i.e. physical activity level ≥ 1·4 to < 1·6) for all participants during this calculation not only because of a lack of information on physical activity in the present study but also because another nationwide study in 7000 adults aged 20–69 years showed a large proportion of the participants (69 %) categorised into ‘low active’ level of physical activity(Reference Tajima, Harada and Oguma53).
Statistical analysis
All analyses were conducted for males and females separately; this a priori decision was based on large sex differences in mean values of food choice values and food literacy in this population(Reference Murakami, Shinozaki and Yuan29). Descriptive data are presented as means and standard deviations. As the main analysis, we examined the associations of food choice values and food literacy (characterised by nutrition knowledge, cooking and food skills, and eating behaviours) with diet quality (as assessed using the HEI-2015 derived from the BDHQ or FCQ) using sex-specific multiple linear regression models. All the variables of interest were included in a model simultaneously. We also included age, BMI and the ratio of energy intake (derived from the BDHQ or FCQ) to estimated energy requirement as covariates on the basis of the following reasons. First, these variables were associated with the explanatory variables in this population; see Murakami et al. (2022)(Reference Murakami, Shinozaki and Yuan29) for age and BMI and Pearson’s correlation coefficients for the ratio of energy intake to estimated energy requirement ranging from −0·24 (FCQ’s ratio and enjoyment of food for females) to 0·28 (FCQ’s ratio and slowness in eating for males). Second, our previous Japanese studies have shown that these variables were also associated with diet quality(Reference Murakami, Livingstone and Fujiwara47,Reference Murakami, Shinozaki and Livingstone48,Reference Murakami, Livingstone and Sasaki54) . The variance inflation factor scores for any variable in any model (range: 1·11–3·91) were within acceptable limits (< 10)(Reference O’Brien55), suggesting that multicollinearity was not an issue. Regression coefficients (β) were calculated as the change of the HEI-2015 with 1-sd increase of each variable. In this study, the estimates of HEI-2015 from the BDHQ and FCQ did not correlate well (Pearson’s correlation coefficient: 0·50 for males and 0·48 for females). Furthermore, as noted above, the correlation between the HEI-2015 by the BDHQ and that by the 16-d weighed dietary record was mediocre at best(Reference Murakami, Livingstone and Fujiwara49), as was the correlation between the HEI-2015 by the FCQ and that by the 4-d weighed dietary record(Reference Murakami, Shinozaki and Livingstone51); thus, external validation did not provide any reassurance. Since choosing which is the better indicator of diet quality in this study is difficult, we focused only on the consistently observed associations regardless of the diet assessment questionnaire. All statistical analyses were performed using SAS statistical software (version 9.4, SAS Institute Inc.). We considered two-tailed P values < 0·05 statistically significant.
Results
The present analysis included 1068 males and 1163 females aged 19–80 years, with a mean age of 50 years (Table 1). The mean BMI (kg/m2) was 23·7 (sd 3·3) for males and 22·3 (sd 3·5) for females. The mean values of HEI-2015 among males were 55·5 (sd 6·5) based on the BDHQ and 53·0 (sd 2·8) based on the FCQ. The corresponding values were 57·2 (sd 6·6) and 53·6 (sd 2·6) among females.
Basic characteristics of the study population (n 2231)
BDHQ, brief-type diet history questionnaire; EI, energy intake; EER, estimated energy requirement; FCQ, food combination questionnaire.
* Based on self-report.
† Calculated using self-reported body height and weight.
‡ A maximum score is 100. A higher score indicates a higher diet quality.
Table 2 shows associations of the HEI-2015 (derived from the BDHQ and FCQ) with food choice values and food literacy characterised by nutrition knowledge, cooking and food skills, and eating behaviours in males. After adjustment for potential confounding factors (including age, BMI and the ratio of reported energy intake to estimated energy requirement), the HEI-2015 derived from the BDHQ was significantly positively associated with the food choice values of health/weight control and organic, nutrition knowledge, and slowness in eating and inversely with food fussiness. The change of the HEI-2015 per 1 sd increase of each variable was +0·82 (se 0·23) for the food choice values of health/weight control, +0·82 (se 0·34) for the food choice values of organic, +0·49 (se 0·19) for nutrition knowledge, +0·52 (se 0·19) for slowness in eating and –1·17 (se 0·20) for food fussiness. When the HEI-2015 derived from the FCQ was examined, there were positive associations with the food choice values of organic and food skills and inverse associations with the food choice values of accessibility, cooking skills and food fussiness. The change of the HEI-2015 per 1 sd increase of each variable was +0·51 (se 0·15) for the food choice values of organic, +0·35 (se 0·15) for food skills, –0·26 (se 0·11) for the food choice values of accessibility, –0·38 (se 0·14) for cooking skills and –0·42 (se 0·09) for food fussiness.
Associations of the HEI-2015 assessed by the BDHQ and FCQ with food choice values and food literacy characterised by nutrition knowledge, cooking and food skills, and eating behaviours in 1068 males
β, regression coefficient; BDHQ, brief-type diet history questionnaire; FCQ, food combination questionnaire; HEI-2015, Healthy Eating Index-2015.
* A maximum score is 100. A higher score indicates a higher diet quality.
† Models with listed variables, age (years, continuous), BMI (kg/m2, continuous) and the ratio of energy intake (derived from the BDHQ or FCQ) to estimated energy requirement (continuous) as the explanatory variables and the HEI-2015 as the response variable; regression coefficients mean the change of HEI-2015 with 1-sd increase of each variable.
‡ Possible score ranging from 1 to 5 for each variable.
§ Possible score ranging from 0 to 143.
|| Possible score ranging from 0 to 98.
¶ Possible score ranging from 0 to 133.
In females (Table 3), the HEI-2015 derived from the BDHQ was positively associated with food choice values of health/weight control and safety, nutrition knowledge, and cooking skills and inversely with the food choice values of accessibility, emotional overeating and food fussiness. The change of the HEI-2015 per 1 sd increase of each variable was +0·79 (se 0·21) for the food choice values of health/weight control, +0·54 (se 0·27) for the food choice values of safety, +0·44 (se 0·17) for nutrition knowledge, +0·67 (se 0·25) for cooking skills, –0·43 (se 0·20) for the food choice values of accessibility, –0·42 (se 0·20) for emotional overeating and –0·47 (se 0·19) for food fussiness. When the HEI-2015 derived from the FCQ was examined, there were positive associations with the food choice values of health/weight control and organic, nutrition knowledge, and cooking skills and inverse associations with the food choice values of convenience and food fussiness. The change of the HEI-2015 per 1 sd increase of each variable was +0·22 (se 0·09) for the food choice values of health/weight control, +0·39 (se 0·13) for the food choice values of organic, +0·17 (se 0·07) for nutrition knowledge, +0·27 (se 0·11) for cooking skills, –0·20 (se 0·09) for the food choice values of convenience and –0·21 (se 0·08) for food fussiness.
Associations of the HEI-2015 assessed by the BDHQ and FCQ with food choice values and food literacy characterised by nutrition knowledge, cooking and food skills, and eating behaviours in 1163 females
β, regression coefficient; BDHQ, brief-type diet history questionnaire; FCQ, food combination questionnaire; HEI-2015, Healthy Eating Index-2015
* A maximum score is 100. A higher score indicates a higher diet quality.
† Models with listed variables, age (years, continuous), BMI (kg/m2, continuous) and the ratio of energy intake (derived from the BDHQ or FCQ) to estimated energy requirement (continuous) as the explanatory variables and the HEI-2015 as the response variable; regression coefficients mean the change of HEI-2015 with 1-sd increase of each variable.
‡ Possible score ranging from 1 to 5 for each variable.
§ Possible score ranging from 0 to 143.
|| Possible score ranging from 0 to 98.
¶ Possible score ranging from 0 to 133.
Discussion
In this cross-sectional study, we found that in males, after adjustment for potential confounding factors, the HEI-2015 derived from BDHQ and that derived from FCQ were associated significantly and positively with the food choice values of organic and inversely with food fussiness. In females, the HEI-2015 showed positive associations with the food choice values of health/weight control, nutrition knowledge, and cooking skills and an inverse association with food fussiness, irrespective of the dietary assessment questionnaire. To our knowledge, this is the first study to comprehensively examine food choice values and food literacy (characterised by nutrition knowledge, cooking and food skills, and eating behaviours) in relation to overall diet quality.
Generally consistent with a previous study(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11), a positive association between the food choice values of health/weight control and diet quality was found for females in both BDHQ- and FCQ-based analyses but not for males (the positive association was only observed in the BDHQ-based analysis). Reasonable explanations for this finding may include the fact that females are primarily responsible for cooking and possibly grocery shopping in many Japanese households(Reference Tani, Fujiwara and Kondo28), that females tend to be exposed to stronger sociocultural norms regarding body shape(Reference Buote, Wilson and Strahan56), and that females are more involved and preoccupied with food than males(Reference Konttinen, Halmesvaara and Fogelholm57). Conversely, a positive association between the food choice values of organic and diet quality was found for males in both BDHQ- and FCQ-based analyses but not for females (the positive association was only observed in the FCQ-based analysis). A recent study showed that higher levels of organic food consumption were associated with healthier dietary patterns overall(Reference Baudry, Alles and Peneau58), consistent with the present findings. It is unclear why the association was more evident in males than in females in the present study, but it may be that for males, choosing foods labelled ‘organic’ is an easy, recognisable and healthy option. Regarding the food choice values of accessibility (i.e. physical and financial ease of purchasing the product), we did not find consistent associations (inverse relations observed only in the FCQ- and BDHQ-based analyses in males and females, respectively). This might reflect the cautious dietary habits of the Japanese, such as low intake of sugar-sweetened beverages and infrequent snacking behaviours(Reference Murakami, Shinozaki and Livingstone21,Reference Murakami, Shinozaki and Livingstone48,Reference Yamada, Murakami and Sasaki59,Reference Huseinovic, Winkvist and Slimani60) .
We found a positive association between nutrition knowledge and diet quality in females, regardless of the dietary assessment questionnaire. This is consistent with the results from several previous studies(Reference Lavelle, Bucher and Dean14,Reference McGowan, Pot and Stephen15,Reference Bonaccio, Di Castelnuovo and Costanzo18,Reference Kullen, Farrugia and Prvan19) but also is supported by a traditional hypothesis that an increase in nutrition knowledge improves attitudes towards healthy eating and subsequently improves eating behaviours (i.e. knowledge-attitude-behaviour model)(Reference Baranowski, Cullen and Nicklas61).
In relation to cooking skills, significant positive associations with diet quality were observed in females (for both BDHQ and FCQ). These findings are in line with a study which has shown that a high level of cooking skills is associated with a high consumption frequency of fruit and vegetables in Japanese females(Reference Tani, Fujiwara and Kondo28). In addition, cooking identity (i.e. the degree to which someone sees himself or herself as a good cook), but not cooking skills, was independently and positively associated with a simple diet quality score in a study in Ireland(Reference McGowan, Pot and Stephen15). An Australian study showed that cooking skills were positively correlated with a diet quality score and intakes of several healthy foods such as fruit and vegetables, although the association between cooking skills and the diet quality score did not reach statistical significance after adjustment for other factors such as sex, age and nutrition knowledge(Reference Lavelle, Bucher and Dean14). Conversely, we found no association between food skills and diet quality in any analyses in females, which may be because food skills are, on average, high in females in Japan(Reference Murakami, Shinozaki and Yuan29).
Among eating behaviours, we found that food fussiness was consistently and inversely associated with overall diet quality in both males and females. Often observed in children(Reference da Costa, Severo and Oliveira20), this appears plausible given that food fussiness may hinder access to healthy foods, lowering diet quality. On the other hand, no association between enjoyment of food and diet quality was found in any of the analyses, contrasting with previous findings in children(Reference da Costa, Severo and Oliveira20). The reason for this is unclear but may be due to the overall high enjoyment of food in this population(Reference Murakami, Shinozaki and Yuan29).
As hypothesised, the observed association was somewhat clearer for females than males. This may reflect that females are generally responsible for food preparation in Japanese households(Reference Tani, Fujiwara and Kondo28), as mentioned above, as well as insufficient interest in nutrition, nutritional knowledge, cooking skills and food skills among males as a whole(Reference Murakami, Shinozaki and Yuan29). Furthermore, this may suggest that the correlates of diet quality are more difficult to understand among males than among females, considering a recent finding that Japanese males with lower cooking skills tended to be married and have a family member as the main meal preparer (wife and mother), while most Japanese females cooked by themselves irrespective of marital status(Reference Tani, Fujiwara and Kondo28). In this regard, information about the living circumstance (e.g. responsibility for food selection and cooking) might be more fruitful.
The strengths of the present study include the simultaneous and comprehensive focus on food choice values and food literacy (nutrition knowledge, cooking and food skills, and eating behaviours) and the use of well-established scales for these variables (particularly nutrition knowledge) and diet quality (HEI-2015), as well as a large nationwide sample with almost the equal proportions for sex and age categories. However, there are also several limitations. First, the cross-sectional nature of this study does not permit the assessment of causality or its direction owing to the uncertain temporality of the association. Future research with prospective design is needed to confirm the present findings. Second, as described previously(Reference Murakami, Shinozaki and Yuan29), the present population, not a nationally representative sample of the Japanese, may have been biased towards greater health consciousness. Further research in a more representative sample is thus warranted. Third, the development process of the Japanese versions of assessment tools for food choice values, cooking and food skills, and eating behaviours did not consider cultural differences between Japan and Western countries. Consequently, these tools may not be optimal for use in the Japanese population, although the internal consistency of all the scores was comparable to that observed in previous studies. Fourth, although the assessment of diet quality was made using a well-established measure (HEI-2015) on the basis of validated tools (BDHQ and FCQ), measurement of dietary intake cannot be done without error. To minimise this issue, we focused only on the consistently observed associations regardless of the diet assessment questionnaire, as well as using a measure of the overall accuracy of dietary reporting (ratio of reported energy intake to estimated energy requirement) as a covariate. Finally, although we made adjustment for basic and important variables and all analyses were conducted for males and females separately, the possibility of residual confounding could not be ruled out. In particular, the present analysis could not consider any socio-economic variables because of a lack of information. However, while it is generally considered that education is a strong determinant of future employment and income and that knowledge and skills are attained through education(Reference Galobardes, Shaw and Lawlor62), nutrition knowledge was not significantly related to education or household income in a previous study of 1165 Japanese adults aged 18–64 years(Reference Matsumoto, Ishige and Sakamoto63). Further, previous Western studies have indicated that the associations of age and sex with food choice values(Reference Konttinen, Sarlio-Lahteenkorva and Silventoinen11,Reference Schliemann, Woodside and Geaney64) , except for values related to price cheapness of food(Reference Konttinen, Halmesvaara and Fogelholm57), as well as with cooking and food skills(Reference Lavelle, Bucher and Dean14,Reference McGowan, Pot and Stephen15) , were stronger than those with education, although nutrition knowledge was strongly associated with education(Reference Hendrie, Coveney and Cox65–Reference De Vriendt, Matthys and Verbeke67). Taken together, it is unlikely that socio-economic factors entirely explain the findings observed here. Nevertheless, future research should incorporate the assessment of socio-economic variables to obtain more comprehensive pictures.
To conclude, in this nationwide cross-sectional study in Japan, several aspects of food choice values and food literacy were associated with diet quality, and the aspects related differed between males and females. Given that the selection, amount, combination of foods consumed and thus nutritional quality are markedly different between meal types (i.e. breakfast, lunch, dinner and snacks)(Reference Murakami, Shinozaki and Livingstone21–Reference Murakami, Livingstone and Sasaki27), a sensible next step would be to investigate if the associations of food choice values and food literacy with diet quality differ by meal types.
Acknowledgements
The authors would like to thank the research dietitians who conducted the data collection: Tamotsu Noshiro*, Ikuko Kato, Yoshie Awa, Erika Takayama, Mari Sakurai, Mihoko Yanase, Masae Kato, Mihoko Furukawa, Yuna Nodera, Kazue Fukushi, Miwako Onodera, Yoshie Sato, Megumi Yoshida, Masako Shimooka, Kaori Takahashi and Fuki Kudo (Hokkaido); Yumiko Sato, Yutaka Shojiguchi, Kazunori Kimoto, Saori Kikuchi, Megumi Maeta, Mayumi Sugawara, Shinogu Muraoka, Kanako Takahashi, Noriko Suzuki, Yoko Fujihira and Megumi Onodera (Iwate); Yukiko Takahashi, Kaoru Honda, Chie Yamada, Miki Sato, Katsue Watanabe, Akemi Konno and Reina Kato (Miyagi); Akiko Sato, Hiromi Kawaguchi, Miyuki Awano, Chigusa Miyake, Ayako Konno, Ayumi Goto, Shizuko Taira, Yuka Takeda, Akiko Matsunaga, Nao Konta, Yumi Miura, Satoshi Numazawa, Chiemi Ito, Sachie Yokosawa, Manami Endo and Hiromi Seki (Yamagata); Yoko Tsukada, Tomoko Oga, Satoko Fujita, Hitomi Sonobe, Hanayo Kadoi, Toshie Nakayama, Hiromi Takasawa, Yoko Ichikawa, Yuko Takano, Junko Hanzawa, Kiyomi Seki, Emi Kamoshita, Yuri Kawakami and Hisako Watahiki (Ibaraki); Reiko Ishii, Yoshiyuki Tatsuki, Daisuke Mogi, Akiko Nakamura, Suguru Yagi, Yumiko Furushima, Noriko Ogiwara, Kiyomi Kimura, Kinue Takahashi, Kikue Tomaru, Kana Tsukagoshi, Fumiko Fujiu, Kyoko Maehara and Yuki Kobayashi (Gunma); Kaoru Goto, Yuka Inaba, Michiko Koresawa, Tomoko Tsuchida, Naoko Sakakibara, Fumika Shimoyama, Akiko Kato, Miki Hori, Rika Kurosaki, Hiroko Yamada, Hitomi Sasaki, Keiko Arai, Yuka Arai, Manami Honda, Akiko Utsumi, Asako Hamada, Keiko Sekine, Akiko Yamada, Mami Ono, Satoko Maruyama, Emiko Kajiwara, Taeko Takahashi, Hitomi Kawata, Satoru Arai, Ryoko Hirose, Madoka Ono and Mihoko Ainai (Saitama); Masako Shinohara, Noriko Nakamura, Mitsuko Ito, Yuka Takahara, Minako Fukuda, Masae Ito, Yayoi Sueyoshi, Hiroko Shigeno, Tomohiro Murakami, Masako Kametani, Kyoko Wada, Mika Ueda, Jun Kouno, Hiroyo Yama-guchi, Mariko Oya, Junko Suegane, Yumiko Asai, Miyuki Ono, Mitsuko Uekusa, Chieko Sunada, Yumi Tanada, Mariko Shibata, Emi Tsukii, Kae Terayama, Hiroko Iwasaki, Keiko Yokoyama, Haruna Kayano, Kazuyo Shimota, Keiko Ifuku and Keiko Honma (Chiba); Yoshiko Saito, Me-gumi Suzuki, Eiko Kobayashi, Yoshiko Katayama, Sonoko Yamaguchi, Tomoko Kita, Naoko Yuasa, Hitomi Okahashi, Shinobu Matsui, Yurina Arai, Sanae Togo, Eiko Horiguchi, Juri Sato, Takehiro Komatsu, Yumi Matsuura, Junko Higashi, Ayaka Nakashita, Takako Sakanashi, Yoko Kono, Naomi Nakazawa and Yukiko Shibata (Tokyo); Machiko Tanaka, Ikue Sahara, Yasue Watanabe, Kanako Yoshijima, Yuko Harashima, Yoshiko Iba, Haruko Irisawa, Junko Inose, Reiko Okui, Taeko Endo, Mayuko Sakitsu, Ikuko Endo, Haruko Terada, Chiaki Nishikawa, Ai Yasudomi, Suzuyo Takeda, Kaori Shimizu, Mari Ikeda, Yuko Okamoto, Keiko Yamada, Fumiko Nemoto, Shinobu Katayama, Yuki Takakuwa, Michiru Goukon, Megumi Koike, Masae Kamiya, Takako Okada, Yayoi Hayashi, Etsuko Abe, Akiko Hamamoto, Kumiko Ono, Kazumi Takagi, Sachiko Ito, Yuki Kumagai, Noriko Ozaki, Haruka Sato, Hisae Takahashi, Masuko Komazaki, Akiko Nako, Tatehiro Inamoto and Kimiyo Matsumoto (Kanagawa); Masako Koike, Reiko Kunimatsu, Keiko Kuribayashi, Hiroko Adachi, Yuri Shikama, Yurika Seida, Ryouko Ito, Satoko Kimura, Yoko Sato, Michiyo Nakamura, Hisako Kaneko, Hatsuyo Ikarashi, Mamiko Karo, Keiko Hirayama, Ikumi Torigoe and Fumiko Gumizawa (Niigata); Natsuko Mizuguchi, Aki Sakai, Hisako Noguchi, Chie Tanabe, Yokako Osaki, Ikiko Kawasaki, Nobuko Yoshii, Yumiko Nishihara, Izumi Takahara, Mika Minato, Yuuki Okamoto, Yukiyo Sakai, Shitomi Nakamura, Kanako Kobayashi, Emi Hano and Megumi Emori (Toyama); Kazumi Horiguchi, Michiyo Kubota, Naoya Mochizuki, Miyuki Yokokoji, Kazuko Koizumi, Megumi Ariizumi, Hozumi Kakishima, Mayumi Kawakubo, Chisato Nakajima, Yasuko Ishii, Yukie Shiogami, Yukiko Uchida, Ikuko Kayanuma and Kikuyo Moriya (Yamanashi); Noriko Sumi, Noriko Takahashi, Kuniko Watanabe, Yoko Ido, Akiko Adachi and Manami Tauchi (Gifu); Naoya Terada, Chisato Suwa, Toshihiro Tamori, Natsuko Osakabe, Toshiyuki Serizawa, Akiko Seki, Izumi Mochizuki, Nagako Matsui, Eiko Watanabe, Kyoko Yui, Yuki Murakami, Tomomi Iwasaki and Tomoko Sugiyama (Shizuoka); Keiko Kawasumi, Masako Tanaka, Kayoko Ishida, Megumi Yamatani, Shihoko Yama, Miyuki Otono, Mie Kojima, Tamaki Kobayashi, Hiroe Komaki, Miki Yanagida, Yumiko Fukaya, Syoko Sawaki, Tomomi Ota, Yasuko Kito, Mei Tobinaga, Takashi Yasue, Kuniko Hatamoto, Toru Ono, Takako Minami, Akemi Ku-mazawa, Masami Kato, Miyuki Kondo, Kyoko Shimizu, Sayoko Tanaka and Shizue Masuda (Aichi); Hiromi Ashida, Shintaro Hinaga, Yoshiko Shoji, Ryusuke Yamaguchi, Hiroka Morita and Atsuko Nakabayashi (Mie); Erika Shioi, Sawa Mizukawa, Miwako Ohashi, Eriko Taniguchi, Yuri Mitsushima, Mariko Teraya, Kazuko Ogawa, Yoko Minami, Megumi Ito, Yasuhiro Morimoto, Shizuka Kurokawa and Manami Hayashi (Kyoto); Yumiko Noutomi, Yoshiko Iwamoto, Junko Ikukawa, Shinobu Fujiwara, Tami Irei, Keiko Takata, Yasuka Tabuchi, Naoko Murayama, Kaori Maruyama, Hiromi Tashiro, Miki Tanaka, Miho Nomura, Shizuyo Umezawa, Minori Shintani, Ikuyo Maruishi, Atsuko Toyokawa, Rumi Kitada, Yuka Takashima, Eriko Nakatani, Wakana Tsujimoto, Yumi Koori, Emi Iwamoto and Masumi Yamada (Osaka); Atsuko Konishi, Yoshiko Nakamori, Yumi Ikawa, Junko Shimizu, Mie Atsumi, Atsuko Fukuzaki, Akemi Yamamoto, Ya-suko Inoue, Miyuki Nakahara, Reiko Fujii, Yumi Tanaka, Rika Miyachi, Mari Matsuyama, Ayana Honda, Tomoka Nakata, Miho Inagaki, Mikiyo Ueno, Mami Kamei, Kiyomi Kawachi, Yasuyo Hasegawa and Masayo Fukumoto (Hyogo); Sachiyo Otani, Tomomi Sugimoto, Kanako Mizo-guchi, Tomomi Shimada, Shima Takahashi, Yoshiko Okuno, Takahide Kijima, Masayo Ueda, Yuko Sakamoto, Hitoshi Matsuda, Yumie Shimizu, Rie Hataguchi, Junko Nohara, Yuko Sakakitani, Hatsuki Matsumoto, Sakiko Tanaka, Moe Yoshikawa and Rena Yuki (Nara); Yurika Adachi, Akiko Notsu, Keiko Uzuki, Atsuko Umeda, Hiroko Nishio, Chikako Takeshita and Sayuri Omoso (Tottori); Hiromi Watanabe, Nami Sakane, Nao Hino, Sakiko Sonoyama, Yukiko Katagiri, Kaori Nagami, Tsunemi Moriyama and Yoshiko Kirihara (Shimane); Sachiko Terao, Akemi Inoue, Mieko Imanaka, Noriyuki Kubota, Sachiko Sugii, Yuri Fujiwara and Tomoko Miyake (Okayama); Youko Fujii, Hiroko Tamura, Kimie Tanaka, Izumi Hase, Etsuko Kimura, Akiko Hamada, Tomoko Kawai, Masako Ogusu and Emi Isomichi (Hiroshima); Kyoko Ueda, Atsuko Nakanishi, Tomoko Ishida, Nobuko Morishita, Hitomi Nakata and Takako Yagi (Yamaguchi); Yuriko Doihara, Toyoko Kitadai, Hideyo Yamada, Mariko Nakamura, Nanako Honda, Eri Ikeuchi, Kayo Hash-imoto, Azusa Onishi and Manami Iwase (Tokushima); Machiko Ueda, Ayano Kamei, Reiko Motoie, Yoko Moriki, Nobumi Yoshida and Kiyoko Kubo (Ehime); Kyoko Kaku, Emi Ibushi, Miho Otsuka, Kiyoko Katayama, Hisami Kumagai, Chizuru Shibata, Miki Hamachi, Yuko Hayashida, Akiko Matsuzaki, Mika Yoshioka, Yoshie Yanase, Yoshiko Yahagi and Tomomi Ota (Fukuoka); Junko Kiyota, Hiromi Ide, Takako Fukushima, Shiho Tominaga, Satsuki Miyama, Yoko Okamura, Kayoko Kurahara, Tomomi Nagamori, Chika Shino, Akiko Taira, Yuki Kuwajima and Miyuki Matsushita (Kumamoto); Miki Hamada, Kiyomi Aso, Toshie Eto, Mitsue Kodama, Miyoko Sato, Mutsuko Shuto, Yuko Soga, Taeko Nagami, Machiko Hirayama, Mika Moribe, Junko Yamamoto, Hideko Yoshioka, Yuko Kawano, Rika Matsuoka and Satomi Sato (Oita); and Hisami Yamauchi, Satomi Moromi, Satoko Tomari, Kaoru Miyara, Chikako Murahama, Yukiko Furugen, Kana Awano, Hiromi Arakaki, Suzumi Uema, Yasuko Tomori, Nariko Mori, Ayako Iho, Michiru Hokama, Yasue Higa and Chigusa Chibana (Okinawa). The authors would also like to thank the research team staff at the survey centre (University of Tokyo): Tomoko Doi, Hitomi Fujihashi, Akiko Hara, Nana Kimoto, Nanako Koe, Eri Kudo, Fumie Maeda, Keika Mine, Akemi Nakahara, Hiroko Onodera, Hiroko Sato, Chifumi Shimomura and Fusako Tanaka. *Deceased.
This work was supported in part by a Challenging Research (Exploratory) from the Japan Society for the Promotion of Science (to K.M.; grant number: 18K19727). The Japan Society for the Promotion of Science had no role in the design, analysis or writing of this article.
K. M. contributed to the concept and design of the survey and data collection and management, formulated the research question, analysed and interpreted the data, prepared the first draft of the manuscript, and had primary responsibility for the final content; N. S. contributed to the concept and design of the survey and provided critical input into the final draft of the manuscript; M. B. E. L. provided critical input into the final draft of the manuscript; X. Y., R. T., M. M. and S. S. contributed to the concept and design of the survey; and S. M. managed the study field establishment and recruitment and contributed to data collection. All authors read and approved the final manuscript.
There are no conflicts of interest.
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