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. 2016 Jun 30;19(18):3306–3318. doi: 10.1017/S1368980016001695

Monetary value of self-reported diets and associations with sociodemographic characteristics and dietary intake among Japanese adults: analysis of nationally representative surveys

Hitomi Okubo 1,*, Kentaro Murakami 2, Satoshi Sasaki 3
PMCID: PMC10270988  PMID: 27357725

Abstract

Objective

To examine the relationships of monetary value of diets with sociodemographic and lifestyle characteristics and dietary intake among Japanese adults.

Design

Cross-sectional study based on two nationally representative surveys: the Comprehensive Survey of Living Conditions and the National Health and Nutrition Survey, 2013. Dietary intake was assessed by a 1 d semi-weighed household dietary record with information on individual proportion of intakes. Diet cost was estimated by linking dietary data with retail food prices. A wide variety of sociodemographic and lifestyle variables were obtained from the two surveys.

Setting

A random sample of nationally representative households in Japan.

Subjects

Japanese adults aged 20 years or older (n 4658).

Results

Lower energy-adjusted diet cost (Japanese yen/4184 kJ) was significantly associated with being younger, having a lower education, less equivalent monthly household expenditure, large household size, less physical activity and living in rented houses. Lower diet cost was associated with a lower intake of pulses, vegetables, fruits, fish, meat and dairy products, and a higher intake of grain, eggs, and fats and oils. At the nutrient level, lower diet cost was associated with a lower intake of protein, alcohol, dietary fibre, cholesterol and all vitamins and minerals examined, and a higher intake of carbohydrate. Diet cost was inversely associated with dietary energy density.

Conclusion

These data suggest that certain low socio-economic subgroups in Japan consume diets of lower monetary value, resulting in a lower quality of food and nutrient intake pattern except for lower sodium, cholesterol and alcohol consumption.

Keywords: Monetary cost, Socio-economic status, Food intake, Nutrient intake, Japanese adults

Food price is now considered to be a major determinant influencing food choice( 1 – 3 ). It is well established in the literature that the more nutrient-rich foods, such as fruits, vegetables and fish, are more expensive per unit of energy than are foods of lower nutritional values such as grain, fats and oils, added sugars and sweets( 4 – 6 ). The higher cost of some recommended healthy foods may thus restrict their use by people with limited resources( 7 , 8 ). In fact, lower-quality foods with low cost tend to be selected by groups of lower socio-economic status, who are also more likely to be obese( 9 – 11 ). Understanding the effect of food prices and diet cost on overall diet quality and identifying vulnerable groups who are more sensitive to food price could bring about new insights related to strategies to prevent socio-economic disparities in health( 11 – 13 ).

The influence of variation in diet cost on overall diet quality is beginning to receive considerable attention( 14 – 23 ). There is growing awareness that higher monetary value of diets is linked to better diet in Western countries( 14 – 21 ), but little is known about this relationship in Asian countries, including Japan( 22 , 23 ). In a study of young Japanese women, higher monetary diet cost was not necessarily associated with a healthier food and nutrient intake pattern( 22 , 23 ), which is somewhat in conflict with findings from Western studies( 4 , 14 – 17 , 19 – 21 ). These inconsistent findings might be partly explained by the differences in food culture between Asian and Western countries. It is necessary to accumulate studies of this kind from various regions with different social and cultural backgrounds in order to obtain reliable scientific evidence on the relationship between diet cost and diet quality. It should also be noted that the previous studies conducted in Japan were limited to homogeneous populations of young women, such as female dietetics students( 22 ) and pregnant women( 23 ). Given that food and nutrient intake patterns may vary according to subject characteristics such as sex, age and socio-economic status( 24 – 26 ), further studies are needed to examine the relationships of monetary diet cost with dietary intake in other Japanese populations.

The objective of the present cross-sectional study was to examine the associations of the monetary value of self-reported diets with sociodemographic and lifestyle characteristics and dietary intake using representative data of Japanese adults.

Subjects and methods

Study population and procedure

The present cross-sectional study was based on data from two nationally representative surveys conducted by the Ministry of Health, Labour and Welfare: the 2013 Comprehensive Survey of Living Conditions (CSLC)( 27 ) and the 2013 National Health and Nutrition Survey (NHNS)( 28 ). Data from the two surveys were used with permission from the Japanese Ministry of Health, Labour and Welfare. Detailed descriptions of the CSLC and the NHNS have been published elsewhere( 27 – 29 ). Briefly, the CSLC has been collecting comprehensive information on the living conditions of people living in Japan such as sociodemographics, health, medical care, welfare and income since 1986 and a large-scale survey has been conducted every three years with a small-scale survey in each interim year( 27 ). The 2013 survey covered 295 367 households nationwide that were randomly selected from 5530 census tracts from the National Census 2010( 30 ). Five kinds of self-administered questionnaires were distributed to respondents in advance of each survey date (on 6 June for household/health/long-term care questionnaires and on 11 July for income/savings questionnaires) and later collected by trained investigators during home visits. For the present study, we used the data from the household questionnaire to obtain household demographics, education, occupation, marital status, household expenditure in May and housing. Information on income and savings was not available to link to the NHNS because the subjects of the income and the savings questionnaires were different from those of the NHNS. Of the 235 012 households that answered the household questionnaire (response rate = 79·6 %)( 27 ), data from 234 383 households and 603 211 household members were provided by the Ministry of Health, Labour and Welfare after excluding unclear answers.

The NHNS, which has been running since 1945, is an annual nationwide survey on the basis of the Health Promotion Law (Law No. 103, enacted in 2002) to assess the health status, food and nutrient intakes and lifestyles of people living in Japan( 28 , 29 ). The 2013 NHNS comprises: (i) a physical examination (for those aged 1 year or older); (ii) a blood test (aged 20 years or older); (iii) a dietary survey (aged 1 year or older); (iv) pedometer measurement (aged 20 years or older); and (v) a lifestyle questionnaire (aged 20 years or older). Participants are household members aged 1 year or older (as of 1 November 2013) of households living in the 300 unit blocks (approximately 5700 households and 15 000 household members) that were randomly selected from the 11 000 unit blocks (5530 census tracts) of the CSLC in 2013. Of the 5204 eligible households in the 300 unit blocks, dietary data were obtained from a total of 3493 households (response rate = 67·1 %)( 28 , 29 ). The exact number of participants approached was not officially published. For the present analysis, we restricted to the 5607 adults aged 20 years or older who completed all three surveys of physical examination, dietary survey and lifestyle questionnaire (Fig. 1). As the NHNS and the CSLC share sampling unit blocks, we linked the survey databases using prefecture, area, unit block, household number, sex and age. Among 5607 subjects of the 2013 NHNS, 5337 were linked to the 2013 CSLC. The final sample used in the current analysis comprised 4658 men and women aged 20 years or older with complete information on the variables of interest.

Fig. 1.

Fig. 1

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Procedure for selecting subjects for the current analysis

Dietary assessment

Dietary intake data were collected using a 1 d semi-weighed household dietary record on one optional day in November, excluding Sundays and national holidays. A detailed description of the procedure has been published elsewhere( 28 , 29 , 31 ). Briefly, during the orientation session before the survey, trained investigators (mainly dietitians and registered dietitians) gave household members who are usually responsible for food preparation (i.e. the main record-keeper) both written and verbal instructions on the study purpose and how to complete the dietary record. The subjects were instructed in the use of a scale to weigh each and every item of food and beverage consumed in the household prior to consumption and they were asked to record this information including food waste and leftovers in the recording form (although the equipment for weighing foods and beverages was not provided for the survey because of limited financial resources). When household members shared food from the same dish, the record-keeper was also asked to record approximate proportions of the food taken by each household member so that the dietary intake of each individual could be calculated. When weighing was not possible (e.g. eating out), the record-keeper was asked to record the size and quantity of foods they ate using household measures in as much detail as possible. When the trained investigators visited each home to collect the diet records, they checked the completeness of recording forms and, if necessary, corrected any missing and/or illogical information. In accordance with a study manual of the NHNS, the trained investigators converted these estimates of portion sizes being recorded using household measures into weights that can then be used to calculate food and nutrient intakes. After all of the collected dietary records were checked at the local centre, trained investigators input dietary intake data using software specifically developed for this survey. Estimates of food and beverage items, energy and nutrients for each individual were calculated from the record of household food consumption and, for shared dishes or foods, the approximate proportion consumed by each household member, based on the Standard Tables of Food Composition in Japan ( 32 ). Dietary energy density (kJ/g) was calculated by dividing total energy intake provided by the reported edible weight of food items only. Caloric and non-caloric beverages were excluded because beverages tend to water down the true energy density of the diet, which may lead to misinterpretation of the true exposure to a high-energy-dense diet( 33 , 34 ).

The validity of this household-based dietary record to estimate food and nutrient intakes at the individual level has been examined in Japan( 31 ). In a previous study of sixty-four female volunteers (female dietetic students and their mothers) in thirty-two households, dietary intakes among young women estimated by 1 d weighed household-based dietary record by their mothers were compared with those estimated by 1 d weighed individual-based dietary record, which was independently conducted by young women themselves. Mean differences between intakes estimated by the two methods were 6·2 % for energy, 5·7 % for protein, 6·7 % for fat and 6·3 % for carbohydrate, whereas Pearson correlation coefficients were 0·90 for energy, 0·89 for protein, 0·91 for total fat and 0·90 for carbohydrate.

Monetary diet cost

Monetary diet cost was estimated by linking the dietary data of the NHNS with retail food prices. The food prices were taken mainly from the National Retail Price Survey 2013( 35 ), which provides the average prices per 100 g portion of major food items. This survey is conducted annually in approximately 167 cities, towns and villages, and annual average prices were calculated as mean values of all survey areas, weighted for population size. To calculate monetary diet cost, food price values were assigned to each individual food and beverage item that appeared in the dietary record. Mixed dishes that were prepared from recipes were decomposed into ingredients. As information on foods that the subjects obtained from a restaurant or other food-service establishments was not collected in the NHNS, we could not consider the added costs associated with the preparation and service of foods and beverages consumed outside the home. The procedure for estimating costs was therefore based on the assumption that all foods and beverages were purchased at retail and prepared and eaten at home, in accordance with previous studies( 15 , 21 – 23 ). Calculations included correction for preparation and waste (e.g. trimming and peeling of vegetables and fruits, removal of bones and skin from fish).

Of the 1426 food and beverage items appearing in the dietary record, the National Retail Price Survey provided direct matches for 725 foods (50·8 %). For the 663 foods that could not be matched directly, price values for similar food items (e.g. same botanical group) were used as proxies (46·5 %). For the remaining thirty-eight items that had no price value and no comparable food in the National Retail Price Survey, prices (per 100 g) from the websites of a nationally distributed supermarket (Seiyu, Japan) were used. When more than one price was available from the websites, a mean value was calculated. Promotional or sale prices were not used to determine costs. Monetary value of diets (Japanese yen/d) was calculated by multiplying the food price per edible 100 g by the amount of each food consumed by the respondent (g/d) (divided by 100), and then summing these values for each participant.

Assessment of sociodemographic and lifestyle characteristics

Because the NHNS has little information on socio-economic status, information on sociodemographic and socio-economic variables was explored from the 2013 CSLC( 27 ). We obtained information on educational attainment (<13 years (high school or less); 13–14 years (technical or professional school); ≥15 years (university or more)), occupation (professional/manager; sales/service/clerical; security/transportation/labour; non-worker), marital status (married; unmarried; widowed; divorced), household size (1, 2, 3 or 4 and ≥5 persons), housing tenure (owned/occupied; council/housing association; rented) and household expenditure in May as socio-economic indicators. Equivalent household expenditure was calculated by dividing household expenditure in May by the square root of household size( 36 ) and then categorizing into thirds (low; middle; high). Six age categories were defined (20–29, 30–39, 40–49, 50–59, 60–69 and ≥70 years). Residential blocks were grouped into six regions (Hokkaido and Tohoku; Kanto; Hokuriku and Tokai; Kinki; Chugoku and Shikoku; Kyushu). The residential areas were also grouped into three categories according to population size (metropolitan area; city with population ≥150 000; city with population <150 000; hereafter referred to as ‘size of residential area’). At the physical examination of the NHNS, height and weight were measured to the nearest 0·1 cm and 0·1 kg, respectively, in light clothing without shoes. BMI (kg/m2) was calculated as weight (in kilograms) divided by height (in metres) squared. Weight status was defined based on BMI as follows: underweight (<18·5 kg/m2), normal (≥18·5 to <25·0 kg/m2) and overweight (≥25·0 kg/m2)( 37 ). Information on smoking status (never; past; current) and physical activity (none; habitual) was collected from the lifestyle questionnaire of the NHNS( 28 ). Habitual physical activity was defined as doing at least 30 min of exercise twice weekly over the previous year, in accordance with the NHNS( 28 ).

Statistical analysis

All statistical analyses were performed using the SAS statistical software package version 9.4. All reported P values are two-tailed and P<0·05 was considered to be statistically significant. Descriptive data were presented as mean and 95 % confidence interval or as median and interquartile range for continuous variables, and as percentages of subjects for categorical variables. To avoid biased grouping due to variation in body size and energy requirement, nutrient and food intake values were energy-adjusted using the density method (i.e. percentage of energy for energy-providing nutrients and amount per 4184 kJ (1000 kcal) of energy for other nutrients and foods). We used crude and energy-adjusted values by the density method (per 4184 kJ) for monetary diet cost. Use of energy-adjusted values (for diet cost and dietary intake) by the residual method( 38 ) did not change the results materially (data not shown). All mean values of monetary diet cost (Japanese yen/d) and energy-adjusted diet cost (Japanese yen/4184 kJ) were calculated for the whole sample and for each category of the following sociodemographic and lifestyle variables: sex, age, residential block, size of residential area, educational attainment, occupation, marital status, housing tenure, equivalent monthly household expenditure, weight status, smoking status and physical activity. Differences in diet cost and energy-adjusted diet cost among categories of each variable were tested using univariate and multivariate regression analyses. Multivariate-adjusted diet cost was calculated by entering all variables simultaneously into a regression model to assess the independent associations between diet cost and sociodemographic and lifestyle characteristics.

Univariate and multiple linear regression analyses were performed to explore the associations of energy-adjusted diet cost with food and nutrient intakes. As a crude model, we calculated means for food and nutrient intakes and dietary energy density across the quintiles of energy-adjusted diet cost. We controlled for the effects of the following potential confounders: sex, age, residential block, size of residential area, educational attainment, occupation, marital status, household size, housing tenure, equivalent monthly household expenditure, weight status, smoking status and physical activity (multivariate model). Tests for trend associations were performed by modelling the median value of each quintile category as a continuous variable. In addition, effect modification by sex and age was considered by adding interaction terms to the model. We also calculated the regression coefficient and 95 % confidence interval of the variation in dietary intake, which reflect the change in dietary intake per 100 Japanese yen increase in energy-adjusted diet cost. When energy-adjusted diet cost was consistently associated with food and nutrient intakes in both categorical and continuous form, we considered it to be statistically significant. As crude and multivariate models showed similar results, only the latter are shown in the present paper.

Results

Characteristics of the study population

Characteristics of the 4658 analytical subjects are shown in Table 1. Compared with other participants in the 2013 CSLC and NHNS (n 679), those included in the analyses were younger and of normal weight status, and less likely to live in Kanto or Kinki regions or in metropolitan areas, to have large household size, to have high monthly expenditure or to currently smoke (all P<0·05). There were no differences in sex, educational attainment, occupation, marital status, housing tenure or physical activity between the subjects studied and the remaining participants.

Table 1.

Daily diet cost (Japanese yen/d) and energy-adjusted diet cost (Japanese yen/4184 kJ) according to sociodemographic and lifestyle characteristics among a nationally representative sample of Japanese adults aged ≥20 years in the National Health and Nutrition Survey 2013, Japan†

Univariate model Multivariate model
Diet cost (Japanese yen/d) Energy-adjusted diet cost (Japanese yen/4184 kJ) Diet cost (Japanese yen/d) Energy-adjusted diet cost (Japanese yen/4184 kJ)
n % Mean 95 % CI P value‡ Mean 95 % CI P value‡ Mean 95 % CI P value§ Mean 95 % CI P value§
Total 4658 100·0 1022 1011, 1033 – 525 521, 530 – – – – – – –
Sex
Male 2115 45·4 1132 1114, 1150 <0·001 513 507, 519 <0·001 1117 1099, 1134 <0·001 509 502, 515 <0·001
Female 2543 54·6 930 917, 944 535 530, 541 943 927, 959 539 534, 545
Age
20–29 years 377 8·1 923 887, 959 <0·001 468 456, 481 <0·001 935 889, 980 <0·001 471 454, 488 <0·001
30–39 years 590 12·7 924 894, 954 482 471, 493 951 918, 984 486 474, 498
40–49 years 720 15·5 936 910, 962 484 475, 493 956 927, 986 488 477, 498
50–59 years 707 15·2 1029 1001, 1058 521 512, 531 1016 987, 1044 518 508, 529
60–69 years 1011 21·7 1134 1108, 1160 563 554, 572 1114 1090, 1138 558 549, 567
≥70 years 1253 26·9 1052 1030, 1074 559 550, 567 1048 1022, 1075 560 550, 569
Residential block
Hokkaido and Tohoku 608 13·1 1006 974, 1038 0·01 527 516, 539 0·08 1008 979, 1038 0·01 526 515, 537 0·03
Kanto 1403 30·1 1037 1016, 1057 525 517, 532 1030 1010, 1050 525 518, 533
Hokuriku and Tokai 855 18·4 1005 979, 1032 532 522, 543 1019 995, 1044 535 526, 544
Kinki 741 15·9 1060 1031, 1090 532 522, 543 1058 1031, 1085 531 521, 541
Chugoku and Shikoku 476 10·2 994 959, 1029 517 505, 530 977 943, 1010 512 499, 524
Kyushu 575 12·3 1002 970, 1034 513 502, 524 1011 981, 1042 516 505, 528
Size of residential area
Metropolitan area 951 20·4 1027 1002, 1052 0·29 536 527, 546 0·002 1021 997, 1045 0·06 533 524, 542 0·004
City with population ≥150 000 1687 36·2 1010 992, 1028 517 510, 523 1005 988, 1023 517 510, 523
City with population <150 000 2020 43·4 1030 1012, 1047 528 521, 534 1036 1019, 1053 529 523, 536
Educational attainment
<13 years 2857 61·3 1008 993, 1022 <0·001 526 521, 531 0·77 1000 986, 1014 <0·001 517 512, 522 <0·001
13–14 years 815 17·5 993 967, 1019 522 513, 531 1057 1031, 1084 534 524, 543
≥15 years 986 21·2 1087 1061, 1112 526 517, 535 1056 1032, 1081 543 534, 552
Occupation
Professional/manager 708 15·2 1066 1036, 1096 <0·001 521 510, 531 <0·001 1035 1006, 1064 0·41 532 521, 543 0·003
Sales/service/clerical 1139 24·5 971 949, 993 516 507, 524 1025 1003, 1048 535 526, 543
Security/transportation/labour 697 15·0 1055 1026, 1084 487 478, 496 1037 1008, 1067 510 499, 521
Non-worker 2114 45·4 1024 1007, 1041 545 539, 551 1011 993, 1028 523 517, 530
Marital status
Married 3324 71·4 1039 1026, 1053 <0·001 530 525, 535 <0·001 1025 1011, 1038 0·16 526 521, 531 0·46
Unmarried 724 15·5 986 958, 1014 493 483, 504 1035 1002, 1068 530 518, 542
Widowed 400 8·6 964 927, 1001 552 538, 566 976 934, 1018 515 500, 531
Divorced 210 4·5 982 926, 1037 515 496, 534 1021 969, 1074 519 499, 538
Household size
1 person 481 10·3 1040 1004, 1076 <0·001 536 522, 551 <0·001 1085 1045, 1125 <0·001 540 525, 555 <0·001
2 people 1501 32·2 1108 1087, 1129 558 551, 566 1078 1058, 1098 541 534, 549
3 or 4 people 2089 44·9 985 969, 1001 510 504, 516 990 974, 1007 517 511, 523
≥5 people 587 12·6 919 892, 946 488 479, 497 939 908, 971 503 491, 514
Housing tenure
Owned/occupied 3729 80·1 1042 1029, 1055 <0·001 532 527, 537 <0·001 1041 1029, 1053 <0·001 530 525, 534 <0·001
Council/housing association 436 9·4 960 922, 999 505 491, 518 964 929, 1000 513 499, 526
Rented 493 10·6 924 891, 956 494 481, 507 928 893, 962 504 491, 517
Equivalent household expenditure
Low (<106 000 Japanese yen) 1566 33·6 966 947, 985 <0·001 503 496, 510 <0·001 981 963, 1000 <0·001 508 501, 515 <0·001
Middle (107 000–155 000 Japanese yen) 1540 33·1 1014 995, 1033 526 519, 533 1021 1003, 1040 528 521, 535
High (≥156 000 Japanese yen) 1552 33·3 1086 1066, 1107 547 540, 555 1064 1045, 1082 541 534, 548
Weight status
Underweight 406 8·7 940 904, 976 <0·001 525 511, 539 0·66 993 957, 1029 0·11 525 512, 539 0·83
Normal 3138 67·4 1020 1006, 1033 524 519, 529 1020 1007, 1033 525 520, 529
Overweight 1114 23·9 1058 1033, 1083 529 520, 537 1038 1016, 1059 528 520, 536
Smoking status
Non-smoker 3483 74·8 1009 996, 1022 <0·001 531 526, 536 <0·001 1023 1011, 1036 0·06 525 520, 530 0·40
Past smoker 344 7·4 1128 1083, 1173 530 515, 545 1057 1018, 1097 535 520, 550
Current smoker 831 17·8 1033 1005, 1062 500 490, 510 1001 974, 1028 523 514, 533
Physical activity
None 3739 80·3 1000 987, 1012 <0·001 519 514, 523 <0·001 1011 1000, 1023 <0·001 523 519, 528 0·04
Habitual 919 19·7 1112 1084, 1139 553 543, 563 1065 1040, 1089 534 525, 543
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†

100 Japanese yen = 0·64 Pound Sterling, 0·75 Euros and 1·02 US dollars in November 2013.

‡

P values for difference were calculated for sex, residential area and marital status and P values for trend were calculated by the linear trend test for the other variables.

§

For analysis of diet cost and energy-adjusted diet cost of each sociodemographic variable, adjustment was made for all other sociodemographic variables shown in the table.

Associations of monetary value of diets with sociodemographic and lifestyle characteristics

The mean monetary value of diets among Japanese adults was 1022 Japanese yen/d and the mean energy-adjusted monetary value was 525 Japanese yen/4184 kJ (1000 kcal). Both crude and energy-adjusted diet cost increased linearly with age (P<0·001).

In the univariate model, differences in crude and energy-adjusted diet cost were consistently observed across the categories of several sociodemographic and lifestyle variables, including sex, age, occupation, marital status, household size, housing tenure, equivalent monthly household expenditure, smoking status and physical activity. With some exceptions, similar results were also observed in the multivariate model. Older age, higher educational attainment, smaller household size, house owner/occupiers, higher equivalent monthly household expenditure and a habit of physical activity were clearly associated with higher diet cost and higher energy-adjusted diet cost (all P<0·05). In contrast, no independent associations were observed by marital status, weight status or smoking status in relation to diet cost or energy-adjusted diet cost.

Food contributors to monetary diet cost

The relative contributions of different food groups to monetary diet cost are shown in Table 2. The principal food groups were vegetables, mushrooms and seaweed (18·4 %), meat (16·4 %), fish and shellfish (16·2 %), beverages (12·7 %), grain (11·1 %; mainly rice (7·1 %)) and fruit (6·2 %), contributing ≥80 % to monetary diet cost per day. Differences in mean diet cost were observed in many food groups between different sex and age groups. The highest contributor to diet cost was meat for men (17·6 %) and the younger age group (20·3 %) and vegetables, mushrooms and seaweed for women (19·5 %) and the older age group (19·7 %).

Table 2.

Contribution of food groups to monetary diet cost (Japanese yen/d) among Japanese adults aged ≥20 years in the National Health and Nutrition Survey 2013, Japan†

Sex Age
All (n 4658) Men (n 2115) Women (n 2543) 20–59 years (n 2394) ≥60 years (n 2264)
Cost of food group‡(Japanese yen/100 g) Diet cost (Japanese yen/d) Diet cost (Japanese yen/d) Diet cost (Japanese yen/d) Diet cost (Japanese yen/d) Diet cost (Japanese yen/d)
n Median IQR Mean 95 % CI % Mean 95 % CI % Mean§ 95 % CI % Mean 95 % CI % Mean§ 95 % CI %
Total monetary diet cost – – – 1022 1011, 1033 – 1132 1114, 1150 – 930 917, 944 – 959 944, 974 – 1089 1072, 1106 –
Cost of each food group
Vegetables, mushrooms and seaweed 323 93 71–159 188 184, 192 18·4 196 190, 201 17·3 182*** 177, 186 19·5 162 158, 167 16·9 215*** 209, 221 19·7
Meat 112 199 127–234 167 163, 172 16·4 199 192, 207 17·6 141*** 135, 146 15·1 194 188, 201 20·3 139*** 133, 145 12·7
Fish and shellfish 277 189 149–356 165 160, 171 16·2 186 177, 194 16·4 148*** 142, 155 15·9 131 125, 137 13·7 202*** 193, 210 18·5
Beverages 75 20 12–89 130 126, 134 12·7 172 165, 180 15·2 95*** 92, 99 10·2 131 125, 137 13·6 129 124, 135 11·9
Alcoholic beverages 24 71 49–135 54 50, 58 5·3 94 87, 101 8·3 21*** 18, 24 2·3 55 49, 60 5·7 53 48, 58 4·9
Soft drinks 34 16 12–20 13 12, 15 1·3 18 15, 20 1·6 10*** 9, 11 1·1 16 14, 18 1·7 11*** 9, 12 1·0
Non-energy-containing beverages 17 15 12–510 63 61, 64 6·1 61 58, 63 5·4 64* 62, 66 6·9 60 58, 62 6·2 66*** 64, 68 6·0
Grain 103 22 20–45 114 112, 115 11·1 134 131, 136 11·8 97*** 96, 99 10·5 120 118, 123 12·5 107*** 105, 109 9·8
White rice 13 21 20–73 72 71, 73 7·1 88 86, 90 7·7 59*** 58, 61 6·3 75 73, 77 7·8 69*** 68, 71 6·4
Noodles 30 22 16–52 19 18, 21 1·9 24 22, 26 2·1 16*** 15, 17 1·7 23 21, 25 2·4 16*** 14, 17 1·4
Bread 10 40 40–40 14 14, 15 1·4 14 13, 14 1·2 15** 14, 16 1·6 14 14, 15 1·5 15 14, 15 1·3
Others 17 31 21–73 4 3, 4 0·4 4 3, 4 0·3 3 3, 4 0·4 4 4, 5 0·5 3*** 2, 3 0·3
Whole grain 33 21 19–22 4 4, 5 0·4 5 4, 6 0·4 4* 3, 4 0·4 4 3, 5 0·4 5* 4, 6 0·5
Fruits 78 60 26–94 63 61, 66 6·2 57 54, 60 5·0 69*** 66, 72 7·4 37 35, 40 3·9 91*** 87, 94 8·3
Sugars and confectioneries 158 121 100–141 51 49, 54 5·0 46 42, 49 4·0 56*** 52, 59 6·0 51 47, 55 5·3 52 48, 55 4·8
Dairy products 35 161 59–316 42 40, 44 4·1 37 35, 39 3·3 46*** 44, 48 4·9 38 36, 40 3·9 47*** 44, 49 4·3
Pulses and nuts 85 79 52–113 31 30, 32 3·0 32 31, 34 2·9 30** 29, 31 3·2 27 25, 28 2·8 36*** 34, 37 3·3
Seasoning 118 54 28–218 31 30, 31 3·0 33 32, 34 2·9 29*** 28, 30 3·1 31 30, 32 3·2 31 30, 31 2·8
Potatoes 32 37 21–72 22 21, 22 2·1 22 21, 23 1·9 21 20, 22 2·3 18 17, 19 1·9 25*** 24, 26 2·3
Eggs 10 35 31–61 11 11, 11 1·1 12 11, 12 1·0 10*** 10, 10 1·1 11 11, 11 1·1 11 10, 11 1·0
Fats and oils 19 75 32–100 7 6, 7 0·6 7 7, 7 0·6 6** 6, 6 0·7 7 7, 8 0·7 6*** 6, 6 0·5
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IQR, interquartile range.

†

100 Japanese yen = 0·64 Pound Sterling, 0·75 Euros and 1·02 US dollars in November 2013.

‡

Median (IQR) of food cost for each food group that appeared in the 1 d semi-weighed dietary record among 4658 Japanese adults aged 20 years or older.

§

P values for difference in mean value of food cost between subgroups (sex and age groups) were calculated by Student’s t test (*P < 0·05, **P < 0·01, ***P < 0·001).

Associations between energy-adjusted diet cost and dietary intake

Table 3 shows the cross-sectional associations of energy-adjusted diet cost with dietary intake. Generally, similar results were consistently observed when energy-adjusted diet cost was treated as a categorical variable (quintile) and as a continuous variable, with the exception of energy and SFA intake. At the food level, energy-adjusted diet cost was positively associated with the consumption of pulses and nuts, vegetables, mushrooms and seaweed, fruit, fish and shellfish, meat, dairy products and beverages, and negatively associated with the consumption of grain (white rice, bread, noodles), eggs, and fats and oils (all P for trend < 0·001). At the nutrient level, energy-adjusted diet cost was positively associated with the intake of protein, alcohol, dietary fibre, cholesterol and all vitamins and minerals examined, and was negatively associated with the intake of carbohydrate (all P for trend < 0·001). Further, energy-adjusted diet cost was inversely associated with energy density (P for trend < 0·01). These associations were still evident after taking into account potential confounders, including sociodemographic and lifestyle factors. In contrast, no association was observed between energy-adjusted diet cost and whole grain, potatoes, sugars and confectioneries, or total fat.

Table 3.

Association of food and nutrient intakes with energy-adjusted monetary diet cost among Japanese adults aged ≥20 years in the National Health and Nutrition Survey 2013, Japan†

Quintile of energy-adjusted diet cost (Japanese yen/4184 kJ)‡
Q1 (n 931) Q2 (n 932) Q3 (n 932) Q4 (n 932) Q5 (n 931) Effect per 100 Japanese yen/
368 (135·8–409·9)§ 443 (410·0–475·8)§ 508 (475·9–539·0)§ 576 (539·1–621·4)§ 701 (621·5–1799)§ P for 4184 kJ increase
Unit Mean 95 % CI Mean 95 % CI Mean 95 % CI Mean 95 % CI Mean 95 % CI trend|| β 95 % CI P value
Food intake
Grain g/4184 kJ 281 276, 285 245 240, 249 225 220, 229 211 207, 216 195 190, 199 <0·001 −20·3 −21·7, −18·8 <0·001
White rice g/4184 kJ 198 192, 203 173 168, 179 160 155, 165 149 144, 154 138 133, 143 <0·001 −13·9 −15·5, −12·2 <0·001
Bread g/4184 kJ 23 21, 24 21 19, 22 20 19, 22 19 17, 20 16 15, 18 <0·001 −1·6 −2·1, −1·1 <0·001
Noodles g/4184 kJ 48 44, 52 38 34, 42 32 29, 36 32 28, 36 28 24, 32 <0·001 −4·9 −6·2, −3·7 <0·001
Others g/4184 kJ 4·8 4·1, 5·5 4·4 3·7, 5·0 5·2 4·6, 5·9 4·2 3·5, 4·8 4·0 3·3, 4·7 0·27 −0·2 −0·4, 0·0 0·10
Whole grain g/4184 kJ 7·5 5·5, 9·5 8·1 6·1, 10·1 7·3 5·3, 9·2 7·5 5·5, 9·5 8·9 6·9, 10·9 0·74 0·3 −0·4, 0·9 0·38
Potatoes g/4184 kJ 26 24, 29 27 25, 29 28 26, 30 28 26, 30 28 26, 30 0·30 0·3 −0·3, 1·0 0·33
Pulses and nuts g/4184 kJ 29 26, 32 34 31, 36 36 33, 39 37 35, 40 39 36, 41 <0·001 2·7 1·8, 3·5 <0·001
Vegetables, mushrooms and seaweed g/4184 kJ 113 107, 118 149 143, 154 163 157, 168 183 178, 189 217 211, 222 <0·001 25·5 23·7, 22·5 <0·001
Fruits g/4184 kJ 38 34, 43 50 46, 54 59 55, 63 72 68, 76 78 74, 82 <0·001 9·2 7·9, 10·5 <0·001
Fish and shellfish g/4184 kJ 23 21, 25 34 32, 36 39 37, 42 46 44, 48 62 60, 64 <0·001 10·2 9·5, 10·8 <0·001
Meat g/4184 kJ 35 33, 37 41 39, 43 44 42, 46 48 46, 50 50 48, 52 <0·001 3·3 2·6, 4·0 <0·001
Eggs g/4184 kJ 19 18, 20 20 18, 21 18 17, 19 16 15, 17 17 16, 18 <0·001 −1·0 −1·4, −0·6 <0·001
Dairy products g/4184 kJ 41 37, 45 49 45, 53 52 48, 56 54 50, 58 55 51, 59 <0·001 3·3 2·0, 4·6 <0·001
Fats and oils g/4184 kJ 6·1 5·8, 6·4 5·7 5·4, 6·0 5·2 4·9, 5·5 4·8 4·6, 5·1 4·3 4·0, 4·6 <0·001 −0·4 −0·5, −0·3 <0·001
Sugars and confectioneries g/4184 kJ 21 19, 23 22 20, 24 22 20, 24 21 19, 23 22 20, 23 0·94 0·1 −0·6, 0·7 0·83
Beverages g/4184 kJ 260 245, 276 301 285, 316 354 339, 370 400 385, 416 492 477, 508 <0·001 57·5 52·5, 62·3 <0·001
Alcoholic beverages g/4184 kJ 11 3, 18 31 24, 39 59 51, 66 72 64, 79 99 91, 106 <0·001 21·1 18·6, 23·5 <0·001
Soft drinks g/4184 kJ 25 21, 30 22 18, 27 26 21, 31 27 22, 32 27 23, 32 0·46 1·4 −0·1, 2·9 0·07
Non-energy-containing beverages g/4184 kJ 224 210, 239 247 232, 261 270 255, 284 302 287, 316 366 352, 381 <0·001 35·0 30·3, 39·6 <0·001
Nutrient intake
Protein % of energy 12·9 12·7, 13 14·4 14·2, 14·5 15·0 14·8, 15·2 15·7 15·5, 15·9 17·1 16·9, 17·3 <0·001 1·03 0·97, 1·09 <0·001
Total fat % of energy 26·0 25·6, 26·5 26·7 26·2, 27·2 26·4 25·9, 26·9 26·4 25·9, 26·9 26·1 25·6, 26·5 0·63 0·01 −0·15, 0·16 0·94
SFA % of energy 7·1 7, 7·3 7·4 7·2, 7·5 7·3 7·1, 7·5 7·4 7·3, 7·6 7·4 7·2, 7·5 0·06 0·06 0·00, 0·12 0·04
Carbohydrate % of energy 58·9 58·3, 59·5 56·1 55·5, 56·6 54·7 54·2, 55·3 53·7 53·1, 54·2 52·0 51·4, 52·6 <0·001 −1·63 −1·81, −1·44 <0·001
Alcohol % of energy 0·6 0·2, 0·9 1·6 1·2, 1·9 2·8 2·5, 3·1 3·4 3·1, 3·7 4·2 3·9, 4·5 <0·001 0·84 0·73, 0·95 <0·001
Dietary fibre g/4184 kJ 6·5 6·3, 6·7 7·4 7·2, 7·6 7·7 7·5, 7·8 8·3 8·1, 8·4 8·8 8·7, 9 <0·001 0·56 0·51, 0·62 <0·001
Cholesterol mg/4184 kJ 140 134, 146 162 156, 167 164 159, 170 168 162, 174 186 180, 192 <0·001 9·7 7·8, 11·5 <0·001
Vitamin A μg/4184 kJ 237 204, 269 292 261, 324 315 283, 346 337 306, 369 362 330, 394 <0·001 30·4 20·1, 40·7 <0·001
Vitamin D μg/4184 kJ 3·2 2·9, 3·5 4·2 3·9, 4·5 4·3 4, 4·6 4·8 4·5, 5·1 5·4 5·1, 5·7 <0·001 0·48 0·38, 0·58 <0·001
Vitamin E mg/4184 kJ 3·0 2·9, 3·1 3·4 3·3, 3·5 3·5 3·4, 3·6 3·7 3·6, 3·7 4·0 3·9, 4·1 <0·001 0·26 0·23, 0·29 <0·001
Thiamin mg/4184 kJ 0·44 0·43, 0·45 0·49 0·48, 0·50 0·52 0·50, 0·53 0·55 0·54, 0·56 0·59 0·57, 0·60 <0·001 0·04 0·03, 0·04 <0·001
Riboflavin mg/4184 kJ 0·55 0·54, 0·57 0·62 0·61, 0·64 0·65 0·64, 0·66 0·68 0·67, 0·70 0·75 0·74, 0·76 <0·001 0·05 0·04, 0·05 <0·001
Vitamin C mg/4184 kJ 47 44, 49 59 57, 62 64 62, 67 76 73, 78 82 80, 85 <0·001 8·2 7·5, 9·0 <0·001
Folate μg/4184 kJ 141 136, 146 171 166, 176 182 177, 187 200 195, 205 228 223, 233 <0·001 21·3 19·7, 22·9 <0·001
Na mg/4184 kJ 2010 1962, 2059 2095 2048, 2143 2159 2112, 2207 2227 2180, 2275 2321 2273, 2369 <0·001 82·5 67·0, 98·0 <0·001
K mg/4184 kJ 1091 1069, 1113 1287 1266, 1309 1373 1352, 1395 1501 1479, 1522 1683 1661, 1705 <0·001 145 138, 152 <0·001
Ca mg/4184 kJ 220 213, 228 252 245, 260 272 265, 279 286 279, 293 312 305, 319 <0·001 23·0 20·6, 25·3 <0·001
Mg mg/4184 kJ 116 114, 118 131 129, 134 138 135, 140 147 145, 149 163 161, 165 <0·001 11·8 11·1, 12·5 <0·001
Fe mg/4184 kJ 3·6 3·5, 3·7 4·1 4, 4·2 4·2 4·1, 4·3 4·4 4·4, 4·5 4·8 4·8, 4·9 <0·001 0·29 0·27, 0·32 <0·001
Energy intake kJ/d 7967 7825, 8109 8258 8120, 8397 8349 8211, 8486 8290 8151, 8429 7974 7833, 8114 0·005 −45·2 −90·4, 0·10 0·05
Edible weight consumed g/d 1173 1148, 1198 1288 1264, 1313 1341 1317, 1365 1389 1365, 1414 1415 1390, 1440 <0·001 51·7 43·6, 59·7 <0·001
Energy density kJ/g 6·99 6·9, 7·08 6·58 6·49, 6·67 6·38 6·29, 6·46 6·14 6·05, 6·23 5·88 5·79, 5·97 <0·001 −0·26 −0·29, −0·24 <0·001
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†

100 Japanese yen = 0·64 Pound Sterling, 0·75 Euros and 1·02 US dollars in November 2013.

‡

Values are means and 95 % CI adjusted for sex (male and female), age (continuous), residential block (Hokkaido and Tohoku; Kanto; Hokuriku and Tokai, Kinki; Chugoku and Shikoku; Kyushu), size of residential area (metropolitan area; city with population ≥150 000; city with population <150 000), educational attainment (<13 years (high school or less); 13–14 years (technical or professional school); ≥15 years (university or more)), occupation (professional/manager; sales/service/clerical; security/transportation/labour; non-worker), marital status (married; unmarried; widowed; divorced), household size (1, 2, 3 or 4 and ≥5 persons), housing tenure (owned/occupied; council/housing association; rented), equivalent monthly household expenditure (low; middle; high), BMI (underweight; normal; overweight), smoking status (never; past; current) and physical activity (none; habitual).

§

Energy-adjusted monetary diet cost (Japanese yen/4184 kJ): median (range).

||

A linear trend test was used with the median value in each quintile as a continuous variable in regression analysis. Adjusted for the variables described above.

Values are regression coefficients indicating the change in dietary intake per unit increase in 100 Japanese yen/4184 kJ.

We also conducted the same analyses for men and women and for younger and older age groups separately. Similar patterns of association were observed between energy-adjusted diet cost and dietary intake, and tests for interaction with sex or age were not significant (data not shown).

Discussion

The principal finding of the current cross-sectional study was that independent associations with monetary value of diets were evident for certain socio-economic indicators (i.e. educational attainment, equivalent monthly household expenditure and housing tenure). The second finding was that higher monetary value of diets was associated with favourable food and nutrient intake patterns, except for higher sodium, cholesterol and alcohol intake. These associations were still evident after adjustment for additional sociodemographic and lifestyle factors. To the best of our knowledge, the present study is the first to examine the relationships of diet cost to sociodemographic characteristics and food and nutrient intake pattern on the basis of data from a nationally representative survey in a non-Western population.

There is now a growing body of evidence from Western countries that higher monetary value of diets is consistently associated with healthier diets, including a higher intake of fruit, vegetables and key vitamins and minerals, a lower intake of fats and sweets, and lower dietary energy density( 14 – 21 ). In Japanese adults, we similarly found positive associations of monetary diet cost and intake of pulses, vegetables, fruits, fish, meat, dietary fibre and key vitamins and minerals examined, and lower intake of fats and oils and lower dietary energy density. In contrast, we also found an association with an unfavourable intake pattern, including higher intake of cholesterol and alcohol and lower intake of carbohydrate, which was not seen in previous Western studies. However, the favourable and unfavourable aspects of the relationships between monetary diet cost and diet quality were also observed in previous Japanese studies of young female dietetic students( 22 ) and pregnant women( 23 ). Our study extended these findings by examining other Japanese populations.

The differences in findings between Western and Japanese studies might be at least partly explained by the different food cultures and country-specific dietary intake patterns. For Japanese people, white rice is a main staple food that is consumed at almost every meal. The role of staple food in the Japanese diet is as a main food source of carbohydrate and energy (55–60 % energy), and it connects with main and several side dishes consisting of fish, meat, eggs, vegetables and pulses to provide the macro- and micronutrients required( 39 ). In general, grain such as white rice, noodles and bread are relatively inexpensive in comparison with the other foodstuffs included in main and side dishes in Japan (Table 2). According to the results of the 2011 NHNS( 40 ), more than 30 % of Japanese adults, especially almost half of the younger age group (20–49 years), cited higher food prices as the main barrier to choosing and buying fresh foods such as vegetables, fruits, meat and fish. Given that certain socio-economic indicators were significantly associated with monetary diet cost in the present study (Table 1), people of lower socio-economic status with limited food budgets would mainly consume grain such as white rice, noodles and bread, with a relatively low amount and/or less variety of foodstuffs for main and side dishes. This is supported by the results of the latest NHNS examining the relationship between household income and food intake( 41 ). In comparison with people whose household income was more than six million Japanese yen, people whose annual household income was less than two million Japanese yen consumed significantly more grain and less vegetables, fruits and meat.

The unfavourable aspects of diet at the nutrient level were a higher intake of cholesterol, alcohol and sodium and a lower intake of carbohydrate in accordance with increasing diet cost. With the exception of total fat and alcohol, similar results were observed in previous studies( 22 , 23 ). As mentioned in previous studies( 22 , 23 ), this might be mainly due to the lower consumption of grain and the food intake patterns associated with lower grain intake with increased diet cost. This is consistent with the negative correlation of grain seen with cholesterol (Pearson correlation coefficient, r=−0·19) and the positive correlation with carbohydrate (r=0·57) in the present study. In addition, the higher intake of sodium seen with higher dietary cost might be due to a higher intake of vegetables, fish and shellfish, and pulses which are generally accompanied by seasonings with a salty taste, such as salt, soya sauce, miso and salt-containing dressings.

There is now growing awareness that economic concerns strongly influence food choice, particularly in lower socio-economic groups( 3 , 7 , 42 ). In the present study, people who had lower energy-adjusted diet cost were likely to have a lower educational attainment, less equivalent household expenditure, large household size, to live in rented houses, and to be younger and physically inactive. Socio-economic status (e.g. income and education) is a well-known factor affecting food choice and eating patterns, because knowledge and awareness of how to eat in a healthy manner could be more common among people in more highly educated groups and with fewer economic constraints( 42 ). Although the association between higher monetary diet cost and a better profile of food and nutrient intake pattern was independent of socio-economic status and lifestyle in the present study (Table 3), it is important to promote healthy food choices and better diet quality among people at risk of lower diet cost by giving nutrition education and by introducing food price policies( 43 ).

Our study has a number of limitations. First, although the study samples were randomly selected from nationally representative households in Japan, only 67·1 % of households sampled took part in the survey( 28 ). Furthermore, the exact response rate at the individual level is not known. If participants with lower socio-economic status were less likely to respond, the relationship between socio-economic status and monetary value of diets might have been underestimated. Second, food prices were estimated from the National Retail Price Survey and websites of a nationally distributed supermarket because of a lack of information on actual food expenditure. In addition, we could not consider foods and beverages purchased and eaten away from home (e.g. at restaurants and other food-service establishments) and varieties of food items (e.g. organic, fresh or frozen, domestic or imported products) because such information was not available in the NHNS. However, we note that a similar methodology has been used in most previous observational studies( 14 – 23 ). Our estimate of the daily diet cost (1022 Japanese yen/d) was not far from the mean national expenditure for foods at home as calculated by the 2013 Family Income and Expenditure Survey (957 Japanese yen/person per d)( 44 ). Third, dietary intake was assessed by a 1 d semi-weighed household dietary record, with a combination of the approximate proportions by which each dish was divided among family members. Although the utility of this household dietary record for estimating dietary intake at the individual level has previously been confirmed among young women, the validity of this method has not been examined among men and the other age groups of women. In addition, the days of dietary assessment were intentionally selected from weekdays on only one month (November), which likely introduces some bias in the estimation of average intake. Furthermore, misreporting of self-reported food intake is a source of measurement error. However, the data used here are the only data for individual diet cost and dietary intake in a nationally representative sample, and the results of the present analyses, based on 1 d dietary record, are consistent with previous studies using diet history questionnaires( 22 , 23 ). Fourth, sociodemographic and lifestyle information in the CSLC and dietary data in the NHNS were evaluated at different time points, the former in June and the latter in November. This time gap in assessment might have influenced the results slightly, although some sociodemographic variables (e.g. educational attainment) would not have changed between survey times. Finally, monetary value of the diet may act as a marker for other healthy behaviours and/or highly health-conscious habits of the individual and household that could potentially confound associations with food and nutrient intakes. Although we controlled for a wide range of potential confounders and other influences on food and nutrient intakes, such as socio-economic status and lifestyle variables, we cannot rule out unmeasured or residual confounding in an observational study.

Conclusion

In conclusion, the present cross-sectional study of a representative sample of Japanese adults showed that higher monetary value of diets was associated with a higher intake of favourable food groups and nutrients, whereas lower monetary value of diets was associated with a higher intake of carbohydrate with less key vitamins and minerals. Given that certain socio-economic subgroups in Japan consume diets of lower monetary value that result in a lower quality of food and nutrient intake pattern, further cross-sectional and prospective studies using representative data to examine the effects of monetary value of diets on long-term health outcomes are required.

Acknowledgements

Financial support: This work was supported in part by a Grant-in-Aid for Young Scientists (B) from the Japan Society for the Promotion of Science. The funders had no role in the design, analysis or writing of this article. Conflict of interest: None of the authors have any personal or financial conflicts of interest to declare. Authorship: H.O. created the monetary diet cost database for estimation from the diet records, conducted the statistical analysis, interpreted the data and wrote the manuscript. K.M. assisted in diet cost database establishment, data interpretation and manuscript preparation. S.S. assisted in manuscript preparation. All authors contributed to and approved the final manuscript. Ethics of human subject participation: This survey was conducted according to the guidelines of the Declaration of Helsinki and verbal informed consent was obtained from all individual subjects. The Comprehensive Survey of Living Conditions and the National Health and Nutrition Survey, conducted by the Ministry of Health, Labour and Welfare, Japan, have stringent protocols and procedures that ensure confidentiality and protect individual participants from being identified. Additionally, the present secondary analysis was based on a public-use data set consisting solely of information that had already been anonymized. Thus, Institutional Review Board approval was not required.

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