Data source and study population
The NHNS is a nationally representative cross-sectional annual survey conducted by local public health centers under the supervision of the Ministry of Health, Labour, and Welfare. The present study was based on data from the 2015 NHNS conducted between November 1 to 30, 2015. Details of the 2015 NHNS has been described elsewhere.[29, 30] Briefly, the participants, who included households and family members (aged >1 year as of November 1, 2015) in 300 areas, were stratified and randomly extracted from the general census areas in the Comprehensive Survey of Living Conditions in 2015. The 2015 NHNS consisted of physical examination, dietary survey, and lifestyle questionnaire. A total of 3,507 out of 5,327 eligible households (65.8%) and 8,583 people participated in the survey. This current study included 5,048 adults aged 18–64 years. We excluded participants with missing data required for analysis in the present study, such as dietary information (n=1,127), body weight (n=592), smoking status or/and habitual alcohol consumption (n=270). Moreover, we excluded those with missing data on the frequency of eating out and take-away meals (n=5). We also excluded those who skipped breakfast, lunch, or/and dinner (n=749), because meal skipping may affect nutrient and food intakes[31, 32], and lactating or pregnant women who may have changed their usual dietary habits (n=84) .[33] Thus, the final participants consisted of 2,221 Japanese adults aged 18-64 years (921 men and 1,300 women).
The permission to use the 2015 NHNS data was obtained from the Ministry of Health, Labour, and Welfare, and only anonymised information was availed for this study. As this survey was conducted according to the Health Promotion Act, all participants gave informed consent to the local government, and approval from Institutional Review Board was not required.
Dietary assessment
Dietary intake data was collected using a one-day semi-weighed household dietary record administered in November 2015, excluding Sundays and public holidays. Prior to completing the survey, trained fieldworkers (mainly registered dieticians) provided an outline of the survey and explained to the participants how to complete the dietary record. The main record-keepers in the household (members who are usually responsible for preparing meals) were instructed to weigh all foods and beverages consumed by the household members and the amount of food waste and leftovers and record their names and weights on recording forms. Additionally, the main record-keepers recorded the approximate proportions of the food consumed by each household member when members shared foods from the same dish to enable estimation of individual intake. If weighing was not possible because the meal was consumed away from the home, the portion size consumed, or quantity of foods and details of any leftovers was estimated. Also, participants reported the type of meals consumed at breakfast, lunch, dinner, and snacks on the recording day according to the following categories: prepared at home, take-away meals (dishes prepared outside home, but eaten at home), eating out at a restaurant and a fast-food store, or other meals prepared outside the home (food served at nursery school, kindergarten, elementary school, junior high school, high school, or workplace). This selection was identified by the main dishes (staple food in case there were no main side dishes).
Trained fieldworkers visited each household and checked for any missing information and errors. In accordance with the survey manual of the NHNS, the trained fieldworkers converted these estimates of portion sizes or quantity of foods into weights of foods and coded each food item, according to the NHNS food number lists based on the Standard Tables of Food Composition in Japan[34] to calculate the intake of energy and nutrients. The trained fieldworkers inputted collected dietary intake data using software specifically developed for the NHNS.
Energy and nutrients were calculated based on the 2010 Standard Tables of Food Composition in Japan, and food items were classified into 17 groups based on the definition of the Standard Tables.[34] In this study, we adjusted the observed dietary intake for energy requirement to minimize errors associated with self-reporting assessment, using the density method. To render the comparison between the reported nutrient intake and the Dietary Reference Intake for Japanese (DRIs)[35] values practically possible, the following calculation was used: energy-adjusted intake (units/day)= observed intake (unit/day) × EER (kcal/day)/observed energy intake (kcal/day). The estimated energy requirement (EER) for each participant was assumed as when their physical activity level was at the second level in the Japanese DRIs (PAL=1.75). For protein, total fat, saturated fat, and carbohydrate, percentage of daily energy intake using reported values (crude) for each macronutrient was also calculated. Additionally, food intake values were energy-adjusted using the density method (i.e. their amounts per EER for food groups: energy-adjusted intake (g/day) = observed intake (g/day) × EER (kcal/day)/observed energy intake (kcal/day)).
Frequency of consuming meals prepared away from home
The frequency of consuming meals prepared away from home was assessed by the combination of two questions in the lifestyle questionnaire asking about the frequency of eating out and take-away meals. Participants reported the frequency of eating out and take-away meals (twice a day or more, once a day, 4–6 times per week, 2–3 times per week, once a week, less than once a week, seldom). Figure 1 shows the classification of participants into three groups according to the frequency of consuming meals prepared away from home, based on the previous reports[3, 15, 18]. Participants who answered, “twice a day or more” to either question and those who answered, “once a day,” “4–6 times a week” or “2–3 times a week” to both questions were classified into the High group (high frequency of consuming meals prepared away from home). Participants who responded to both questions “once a week,” “less than once a week,” “seldom” were classified in the Low group (low frequency of consuming meals prepared away from home). If none of the above applies to those, participants were classified into the Moderate group.
Determination of inadequate nutrient intake
Inadequate intake of each nutrient was determined by comparing energy-adjusted nutrient levels with the relevant dietary reference value according to the Japanese DRIs, using a previously reported method.[36-38] In the Japanese DRIs, different types of dietary reference values were established according to their purpose. The estimated average requirement (EAR) is set to prevent insufficient intake of nutrients, whereas the tentative dietary goal (DG) to prevent lifestyle-related diseases is set to prevent non-communicable diseases.
Nutrient intake inadequacy was defined as follows: energy-adjusted intake level below EAR was considered as inadequate using the cut-point method for the following 14 nutrients with known EARs: protein, vitamin A (as retinol activity equivalents), vitamin B1, vitamin B2, niacin (as niacin equivalent), vitamin B6, vitamin B12, folate, vitamin C, calcium, magnesium, iron, zinc, and copper. Regarding iron intake in menstruating women, we applied the value <9.3 mg/day as recommended by the World Health Organization (WHO) (bioavailability of iron as 15%, probability of inadequacy as 50%)[39] for women aged 20–49 years because the cut-point method is less applicable to these populations.[40, 41] For the following seven nutrients, the intake level (energy-adjusted intake level for total dietary fiber, sodium (as salt-equivalent) and potassium) outside the range of DG values was considered as inadequate: protein (as % energy: 13–20%) , total fat (as % energy: 20–30%), saturated fat (as % energy: 7% or less), carbohydrate (as % energy: 50–65%), total dietary fiber (man; 20 g/day or more, woman; 18 g/day or more), sodium (as salt-equivalent: man; less than 8.0 g/day, woman; less than 7.0 g/day), and potassium (man; 3000 mg/day or more, women; 2600 mg/day or more).
Other variables
Body height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) were measured for approximately 90% of the participants by trained field workers according to standardised procedures. For the remaining participants, height and weight were measured either by other household members at home or were self-reported. BMI was calculated as weight (kg) divided by height (m) squared. Smoking status and alcohol drinking habits during the preceding month were assessed by a self-administered questionnaire.
Statistical analysis
All statistical analyses were stratified by sex. The differences in characteristics among three groups according to the frequency of consuming meals prepared away from home were compared using the chi-square test for categorical variables and analysis of variance (ANOVA) for continuous variables. Differences in daily energy-adjusted nutrients and food group intake among the three groups according to the frequency of consuming meals prepared away from home were assessed by ANOVA in the crude model and a covariate analysis (ANCOVA) in the adjusted model. Dunnett test, with the Low group as reference, was performed in the post-hoc test. The nutritional inadequacy of each nutrient intake was represented as the proportion of participants whose energy-adjusted intake was below the EAR or outside the range of the DG in each group. Logistic regression analysis was used to examine the difference in the prevalence of meeting DRIs based on the High and Moderate groups according to the frequency of consuming meals prepared away from home compared with the Low group in the crude and adjusted model. Confounding factors considered in the adjusted model were age category (18–34, 35–50, and 51–64 years), occupation (professional/manager, sales/service/clerical, security/transportation/labour, student, housekeeper, and not in paid employment), living alone or not (yes or no), region (Hokkaido/Tohoku, Kanto, Hokuriku/Tokai, Kinki, Shikoku/Chugoku, Kyusyu), current smoker (yes or no) and habitual alcohol drinker (yes or no), which was reported as a factor affecting the frequency of consuming meals prepared away from home[8, 42]. All statistical analyses were performed with SAS statistical software, version 9.4 (SAS Institute Inc., Cary, NC, USA). All reported P values were two-tailed, with a P-value <0.05 considered statistically significant.
Data source and study population
The NHNS is a nationally representative cross-sectional annual survey conducted by local public health centers under the supervision of the Ministry of Health, Labour, and Welfare. The present study was based on data from the 2015 NHNS conducted between November 1 to 30, 2015. Details of the 2015 NHNS has been described elsewhere.[29, 30] Briefly, the participants, who included households and family members (aged >1 year as of November 1, 2015) in 300 areas, were stratified and randomly extracted from the general census areas in the Comprehensive Survey of Living Conditions in 2015. The 2015 NHNS consisted of physical examination, dietary survey, and lifestyle questionnaire. A total of 3,507 out of 5,327 eligible households (65.8%) and 8,583 people participated in the survey. This current study included 5,048 adults aged 18–64 years. We excluded participants with missing data required for analysis in the present study, such as dietary information (n=1,127), body weight (n=592), smoking status or/and habitual alcohol consumption (n=270). Moreover, we excluded those with missing data on the frequency of eating out and take-away meals (n=5). We also excluded those who skipped breakfast, lunch, or/and dinner (n=749), because meal skipping may affect nutrient and food intakes[31, 32], and lactating or pregnant women who may have changed their usual dietary habits (n=84) .[33] Thus, the final participants consisted of 2,221 Japanese adults aged 18-64 years (921 men and 1,300 women).
The permission to use the 2015 NHNS data was obtained from the Ministry of Health, Labour, and Welfare, and only anonymised information was availed for this study. As this survey was conducted according to the Health Promotion Act, all participants gave informed consent to the local government, and approval from Institutional Review Board was not required.
Dietary assessment
Dietary intake data was collected using a one-day semi-weighed household dietary record administered in November 2015, excluding Sundays and public holidays. Prior to completing the survey, trained fieldworkers (mainly registered dieticians) provided an outline of the survey and explained to the participants how to complete the dietary record. The main record-keepers in the household (members who are usually responsible for preparing meals) were instructed to weigh all foods and beverages consumed by the household members and the amount of food waste and leftovers and record their names and weights on recording forms. Additionally, the main record-keepers recorded the approximate proportions of the food consumed by each household member when members shared foods from the same dish to enable estimation of individual intake. If weighing was not possible because the meal was consumed away from the home, the portion size consumed, or quantity of foods and details of any leftovers was estimated. Also, participants reported the type of meals consumed at breakfast, lunch, dinner, and snacks on the recording day according to the following categories: prepared at home, take-away meals (dishes prepared outside home, but eaten at home), eating out at a restaurant and a fast-food store, or other meals prepared outside the home (food served at nursery school, kindergarten, elementary school, junior high school, high school, or workplace). This selection was identified by the main dishes (staple food in case there were no main side dishes).
Trained fieldworkers visited each household and checked for any missing information and errors. In accordance with the survey manual of the NHNS, the trained fieldworkers converted these estimates of portion sizes or quantity of foods into weights of foods and coded each food item, according to the NHNS food number lists based on the Standard Tables of Food Composition in Japan[34] to calculate the intake of energy and nutrients. The trained fieldworkers inputted collected dietary intake data using software specifically developed for the NHNS.
Energy and nutrients were calculated based on the 2010 Standard Tables of Food Composition in Japan, and food items were classified into 17 groups based on the definition of the Standard Tables.[34] In this study, we adjusted the observed dietary intake for energy requirement to minimize errors associated with self-reporting assessment, using the density method. To render the comparison between the reported nutrient intake and the Dietary Reference Intake for Japanese (DRIs)[35] values practically possible, the following calculation was used: energy-adjusted intake (units/day)= observed intake (unit/day) × EER (kcal/day)/observed energy intake (kcal/day). The estimated energy requirement (EER) for each participant was assumed as when their physical activity level was at the second level in the Japanese DRIs (PAL=1.75). For protein, total fat, saturated fat, and carbohydrate, percentage of daily energy intake using reported values (crude) for each macronutrient was also calculated. Additionally, food intake values were energy-adjusted using the density method (i.e. their amounts per EER for food groups: energy-adjusted intake (g/day) = observed intake (g/day) × EER (kcal/day)/observed energy intake (kcal/day)).
Frequency of consuming meals prepared away from home
The frequency of consuming meals prepared away from home was assessed by the combination of two questions in the lifestyle questionnaire asking about the frequency of eating out and take-away meals. Participants reported the frequency of eating out and take-away meals (twice a day or more, once a day, 4–6 times per week, 2–3 times per week, once a week, less than once a week, seldom). Figure 1 shows the classification of participants into three groups according to the frequency of consuming meals prepared away from home, based on the previous reports[3, 15, 18]. Participants who answered, “twice a day or more” to either question and those who answered, “once a day,” “4–6 times a week” or “2–3 times a week” to both questions were classified into the High group (high frequency of consuming meals prepared away from home). Participants who responded to both questions “once a week,” “less than once a week,” “seldom” were classified in the Low group (low frequency of consuming meals prepared away from home). If none of the above applies to those, participants were classified into the Moderate group.
Determination of inadequate nutrient intake
Inadequate intake of each nutrient was determined by comparing energy-adjusted nutrient levels with the relevant dietary reference value according to the Japanese DRIs, using a previously reported method.[36-38] In the Japanese DRIs, different types of dietary reference values were established according to their purpose. The estimated average requirement (EAR) is set to prevent insufficient intake of nutrients, whereas the tentative dietary goal (DG) to prevent lifestyle-related diseases is set to prevent non-communicable diseases.
Nutrient intake inadequacy was defined as follows: energy-adjusted intake level below EAR was considered as inadequate using the cut-point method for the following 14 nutrients with known EARs: protein, vitamin A (as retinol activity equivalents), vitamin B1, vitamin B2, niacin (as niacin equivalent), vitamin B6, vitamin B12, folate, vitamin C, calcium, magnesium, iron, zinc, and copper. Regarding iron intake in menstruating women, we applied the value <9.3 mg/day as recommended by the World Health Organization (WHO) (bioavailability of iron as 15%, probability of inadequacy as 50%)[39] for women aged 20–49 years because the cut-point method is less applicable to these populations.[40, 41] For the following seven nutrients, the intake level (energy-adjusted intake level for total dietary fiber, sodium (as salt-equivalent) and potassium) outside the range of DG values was considered as inadequate: protein (as % energy: 13–20%) , total fat (as % energy: 20–30%), saturated fat (as % energy: 7% or less), carbohydrate (as % energy: 50–65%), total dietary fiber (man; 20 g/day or more, woman; 18 g/day or more), sodium (as salt-equivalent: man; less than 8.0 g/day, woman; less than 7.0 g/day), and potassium (man; 3000 mg/day or more, women; 2600 mg/day or more).
Other variables
Body height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) were measured for approximately 90% of the participants by trained field workers according to standardised procedures. For the remaining participants, height and weight were measured either by other household members at home or were self-reported. BMI was calculated as weight (kg) divided by height (m) squared. Smoking status and alcohol drinking habits during the preceding month were assessed by a self-administered questionnaire.
Statistical analysis
All statistical analyses were stratified by sex. The differences in characteristics among three groups according to the frequency of consuming meals prepared away from home were compared using the chi-square test for categorical variables and analysis of variance (ANOVA) for continuous variables. Differences in daily energy-adjusted nutrients and food group intake among the three groups according to the frequency of consuming meals prepared away from home were assessed by ANOVA in the crude model and a covariate analysis (ANCOVA) in the adjusted model. Dunnett test, with the Low group as reference, was performed in the post-hoc test. The nutritional inadequacy of each nutrient intake was represented as the proportion of participants whose energy-adjusted intake was below the EAR or outside the range of the DG in each group. Logistic regression analysis was used to examine the difference in the prevalence of meeting DRIs based on the High and Moderate groups according to the frequency of consuming meals prepared away from home compared with the Low group in the crude and adjusted model. Confounding factors considered in the adjusted model were age category (18–34, 35–50, and 51–64 years), occupation (professional/manager, sales/service/clerical, security/transportation/labour, student, housekeeper, and not in paid employment), living alone or not (yes or no), region (Hokkaido/Tohoku, Kanto, Hokuriku/Tokai, Kinki, Shikoku/Chugoku, Kyusyu), current smoker (yes or no) and habitual alcohol drinker (yes or no), which was reported as a factor affecting the frequency of consuming meals prepared away from home[8, 42]. All statistical analyses were performed with SAS statistical software, version 9.4 (SAS Institute Inc., Cary, NC, USA). All reported P values were two-tailed, with a P-value <0.05 considered statistically significant.