Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Association between diet-related greenhouse gas emissions and nutrient intake adequacy among Japanese adults

  • Minami Sugimoto,

    Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

    Affiliation Department of Social and Preventive Epidemiology, Division of Health Sciences and Nursing, Graduate School of Medicine, University of Tokyo, Tokyo, Japan

  • Kentaro Murakami,

    Roles Writing – review & editing

    Affiliation Department of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan

  • Aya Fujiwara,

    Roles Formal analysis

    Affiliations Department of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan, Department of Nutritional Epidemiology and Shokuiku, National Institute of Biomedical Innovation, Health and Nutrition, Tokyo, Japan

  • Keiko Asakura,

    Roles Data curation

    Affiliation Department of Environmental and Occupational Health, School of Medicine, Toho University, Tokyo, Japan

  • Shizuko Masayasu,

    Roles Resources

    Affiliation Ikurien-Naka, Ibaraki, Japan

  • Satoshi Sasaki

    Roles Data curation, Funding acquisition, Supervision, Writing – review & editing

    stssasak@m.u-tokyo.ac.jp, sasakicrs@m.u-tokyo.ac.jp

    Affiliations Department of Social and Preventive Epidemiology, Division of Health Sciences and Nursing, Graduate School of Medicine, University of Tokyo, Tokyo, Japan, Department of Social and Preventive Epidemiology, School of Public Health, University of Tokyo, Tokyo, Japan

Abstract

Objectives

A growing number of Western studies have been exploring sustainable and healthy dietary patterns that target to reduce diet-related greenhouse gas emissions (GHGE) and to achieve nutritional needs. However, research is limited among Asian populations, where food sources for diet-related GHGE differ from those in Western populations. This study aimed to investigate associations between diet-related GHGE and the prevalence of inadequate nutritional intake.

Methods

A cross-sectional study was carried out among 392 healthy Japanese volunteers aged 20–69 years. Dietary intake was assessed by four-non-consecutive day diet record. Diet-related GHGE was estimated using the Global Link Input-Output model and adjusted for energy intake by residual method. Prevalence of inadequacy was defined as a percentage of participants with nutrient intake outside the Tentative Dietary Goal for Preventing Lifestyle-Related Disease or below the Estimated Average Requirement defined by the Dietary Reference Intakes (DRIs) for Japanese. The association between diet-related GHGE and the prevalence of inadequacy of the usual intake of each nutrient was examined using logistic regression models.

Results

Participants with higher diet-related GHGE had overall better adherence to the DRIs. Intakes of all selected nutrients were positively associated with diet-related GHGE, except for carbohydrate, total fat, and saturated fat. With increasing quartile of diet-related GHGE, the prevalence of inadequacy decreased for protein, dietary fiber, potassium, vitamins A, B-6, and C, thiamin, riboflavin, calcium, magnesium, iron, and zinc, while that for sodium increased.

Conclusions

Diets with lower diet-related GHGE did not have better adherence to the DRIs compared to diets with higher diet-related GHGE among Japanese adults. Drastic dietary change or other strategies such as improving the food system would be needed to achieve a sustainable and healthy diet among Japanese.

Introduction

In the context of growing interest for sustainable healthy diets [1] and climate change, many epidemiological studies have been focused on individual dietary choice and greenhouse gas emissions (GHGE) related to the diet [221]. Individual dietary choices would consequently affect emissions from the food sectors because it drives food systems, which contribute 21–37% global GHGE when pre- and post-production stages are included [22]. Thus, it is expected that achieving sustainable healthy dietary choices at individual level would reduce GHGE from food sector.

Most of previous observational studies have shown inverse associations between diet-related GHGE and adequacy of nutrient intake [3] and overall diet quality [49], while a few showed positive or null associations [2, 7]. On the other hand, a series of scenario studies have shown that modeled healthy diets meeting dietary guidelines did not always improve diet-related GHGE [1012]. However, these previous studies mainly come from Western countries [218], while research is limited among Asian countries including Japan, where meat intake is lower than Western countries [1921].

Japan was the sixth-largest greenhouse gas emitter in 2016 [23]. The Japanese government advocated the strategies “to reduce greenhouse gas emissions 80% by 2050 as its long-term goal [24].” The environmental dimension of diet has not been included in this statement nor mentioned in the dietary guidelines. It might be the result of a lack of evidence about the environmental impact of Japanese diet, including diet-related GHGE. Japanese dietary habits have long been of interest to researchers from other countries from a nutrition and health standpoint [25, 26], while its environmental aspects have been rarely investigated.

The contemporary Japanese diet is typically high in refined grains, seaweeds, vegetables, fish, legumes and low in whole grains, nuts and seeds, dairy products, sugar-sweetened beverage, and processed and unprocessed red meats [2729]. At the nutrient level, it is characterized by a high intake of sodium and a low intake of dietary fiber, calcium, and saturated fat [29, 30]. Major dietary sources of GHGE among Japanese included meat (19.7%), fish and seafood (13.8%), and cereals (13.1%) [19]. They are quite different from those observed in Western countries, where a considerably large proportion of diet-related GHGE is explained by meat (31.3–56.6%) and dairy products (13.1–25.2%), with a small contribution of fish and seafood (2.1–9.2%) and cereals (2.1–10.5%) [6, 1318]. Adverse health effects of higher meat intake have been reported in a population with high meat intake [31], while negative or no associations between meat intake and mortality from cardiovascular disease or cancer were generally found in Asian population with low meat intake [31, 32]. Hence, the association between diet-related GHGE and dietary intake among Japanese could differ from that observed in Western studies. Therefore, this study aimed to investigate associations between diet-related GHGE and the prevalence of inadequate nutritional intake in Japanese adults.

Materials and methods

Study design and participants

This cross-sectional study was based on data from healthy Japanese adults aged 20–69 years. Data collection was conducted in 20 study areas covering 23 of 47 prefectures between February and March 2013. Details of the study have been reported elsewhere [33, 34]. The primary objective of this survey was to estimate sodium and potassium excretion using biomarker and to identify food sources of sodium and potassium. First, 199 dietitians working in separate welfare facilities were recruited as research dietitians supporting the survey. Next, the research dietitians recruited participants from their co-workers or family members of co-workers with stratifying by sex and by five 10-year age bands (20–29, 30–39, 40–49, 50–59, and 60–69 years). The number of participants was targeted to be 40 adults in each study area to allow for statistical analysis stratified by sex, age, body mass index (BMI; in kg/m2), and physical activity. The exclusion criteria were: (i) licensed dietary or medical provider, (ii) residence in the prefecture or adjacent prefecture in which the facility was located for less than 6 months, (iii) individuals who were under diet therapy prescribed by a doctor or dietitian at the time of the study or within 1 y before the study, (iv) pregnant or lactating women, and (v) individuals who had history of hospitalization for diabetes education. Of those 800 adults recruited, nine adults withdrew from the survey. In total, 791 adults participated. To reduce the burden to the participants and the research dietitians, half of the participants (n = 400) were also asked to complete diet records. A total of 392 adults (196 men and 196 women) completed diet records and were included in the present analysis. BMI was calculated based on measured weight and height. The participants’ occupation, educational background, and smoking habits were assessed using a questionnaire (S1 Appendix in S1 File).

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Ethics Committee of the University of Tokyo, Faculty of Medicine (approval number: 10005, approval date: January 7, 2013). Written informed consent was obtained from all participants.

Dietary assessment

Dietary intake was assessed by four-non-consecutive-day diet records. The assessment days consisted of three working days and one day off. All participants were provided with digital kitchen scale (KD-812WH; Tanita, Tokyo, Japan), measuring spoon, measuring cup, a manual for the diet record, and recording sheets and instructed how to weigh and record foods and beverages consumed. Each participant was asked to weigh and record all food and beverages consumed on the four assessment days using the provided equipments and recording sheet. When weighing was difficult (e.g. eating out), the restaurant’s name, name of dishes, and an estimated amount of leftovers were reported. Pictures of food and beverages were also provided by some participants but not mandatory. All recorded foods and beverages were assigned food item numbers according to the Standard Tables of Food Composition in Japan, Fifth Revised and Enlarged Edition [35]. All records were checked twice (by the research dietitians at each facility and trained dietitian staff at the survey center). The research dietitian contacted the participants to clarify any ambiguities or missing data in the recording sheets. Daily intakes of foods, energy, and nutrients were estimated based on the Standard Tables of Food Composition in Japan in which free sugar content of each food item was added based on published sources [36, 37] due to the insufficiency of data for free sugars in original food composition tables.

To evaluate the accuracy of the reported energy intake (EI), the ratio of EI to basal metabolic rate (BMR) (EI:BMR) was compared to the Goldberg cut-off [38]. For this, the average EI of the four-assessment-days was used. BMR was calculated using the sex-specific equation for Japanese population based on age, weight, and height. Assuming sedentary lifestyle for all subjects because of a lack of objective information on physical activity in this study (physical activity level: 1.55 for men and 1.56 for women), under-, plausible-, and over-reporters were defined as having EI:BMR <1.02, 1.02–2.35, and >2.35 for men, and <1.03, 1.03–2.36, and >2.36 for women, respectively. Under- and over- reporters were identified in this study but were not excluded from the analysis to avoid bias for that exclusion. Assuming sedentary lifestyle for all subjects because of a lack of objective information on physical activity in this study (physical activity level: 1.55 for men and 1.56 for women), under-, plausible-, and over-reporters were defined as having EI:BMR <1.02, 1.02–2.35, and >2.35 for men, and <1.03, 1.03–2.36, and >2.36 for women, respectively [39, 40].

Greenhouse gas emissions of food and drinks

GHGE of foods and drinks were estimated using the food GHGE database based on the Global Link Input-Output (GLIO) model [41]. The detailed description of the database development was written elsewhere [19]. Briefly, the GLIO model includes 804 economic sectors in Japan and 230 foreign countries and regions describing the relationship between their production and consumption systems. Production-based GHGE values for 354 food items were calculated from the GLIO model. Then, the values of 354 foods and drinks were systematically linked to food items from the Standard Tables of Food Composition in Japan [35]. Diet-related GHGE was calculated by multiplying the GHGE value for food items and the mean food intake of the four assessment days.

Estimation of usual nutrient and food intakes and greenhouse gas emissions

The usual dietary intake of nutrients, foods, and diet-related GHGE were estimated with the Multiple Source Method (MSM) [42, 43]. For each participant, four-day measurements of food intake, nutrient intake, or diet-related GHGE data were imported to the MSM program. In the MSM, usual intake for each participant was calculated as following three steps: calculating the probability of eating a certain food or nutrient on a random day was estimated for each individual, estimating the usual amount of food or nutrient intake on a consumption day, and multiplying resulting numbers from former two steps by each other. The usual percent of energy from protein, fat, carbohydrate, saturated fat, and free sugar was estimated by the MSM after calculation of percent energy from these nutrients for each assessment day.

Assessment of nutrient intake inadequacy

For the nutrient intake inadequacy assessment, the estimated usual nutrient intakes were compared with age- and sex-specific reference values in the Dietary Reference Intakes (DRIs) for Japanese [44], as described in previous studies [45, 46]. In brief, several types of reference values are set according to their purposes in the Japanese DRIs. The Estimated Average Requirement (EAR) is defined as “the estimated intake amount that meets the requirements of 50% of the individuals belonging to an age or sex group [47].” The Tentative Dietary Goal for Preventing Lifestyle-Related Disease (DG) is defined as “the nutrient intake amount Japanese people should aim for, to prevent lifestyle-related diseases, in the foreseeable future [47].” The DGs are provided for macronutrient balance (% of energy from protein, total fat, saturated fat, and carbohydrates), dietary fiber, sodium, and potassium. For seven nutrients with DGs, participants whose intake levels were outside the range of the corresponding DG values were considered inadequate. For nutrients with EAR except for iron, participants whose intake was lower than the EAR were considered inadequate. Because of the strongly skewed distribution of iron requirements among menstruating women [48, 49] and the lack of information about menopause among female participants, less than 9.3 mg/d of iron intake (probability of inadequacy >50% for menstruating women whose bioavailability of iron is 15%) [50] was considered as inadequate among women under 50 years old using a probability method. For free sugar, the participants whose intake was 5% energy or more were deemed to be inadequate based on the conditional recommendation advocated by the World Health Organization (WHO) [51] because there is no reference value for free sugar in Japanese DRIs. The reference values are shown in S1 Table in S1 File.

We excluded biotin, iodine, selenium, chromium, and molybdenum for which EAR is set from the present analysis because of insufficiency of food composition tables for these nutrients in Japan.

Statistical analysis

All statistical analyses were performed with the 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. The mean and standard deviation (SD) of the usual nutrient intake and prevalence of inadequacy among all participants were described. Because energy intake was highly correlated with both nutrient intakes and diet-related GHGE, usual diet-related GHGE was adjusted for energy by residual method. Energy-adjusted diet-related GHGE was computed as the residuals from the regression model, with total energy intake as the independent variable and absolute diet-related GHGE as the dependent variable [52]. The participants were divided into sex-specific quartiles (i.e. divided separately by sex) according to the usual diet-related GHGE (g CO2-eq/d), and then mixed for further analysis as our sample size was small, and the analysis by sex showed similar results (S2–S6 Tables in S1 File).

Linear regression models were constructed to examine the association between diet-related GHGE (g CO2-eq/d) and age and BMI using the median value for each quartile as a continuous variable. Mean differences of age and BMI among quartile groups were also tested by one-way analysis of variance (ANOVA) with the post hoc Bonferroni test. The chi-square test was used to test differences in living area, occupation, educational background, and smoking habits.

Linear regression models were constructed to examine the association between diet-related GHGE (g CO2-eq/d) and the usual nutrition intake using the median value for each quartile as a continuous variable. Differences between quartiles were also assessed using one-way ANOVA with post hoc Bonferroni’s test. Next, using the logistic regression, the odds ratio (OR) and 95% confidence interval (CI) for inadequacy were calculated for each quartile of diet-related GHGE, with the lowest quartile category used as the reference. Further, linear trends of OR were tested with increasing levels of diet-related GHGE by assigning each subject the median value for the category and modeling this value as a continuous variable. For the nutrients of which the prevalence of inadequacy among all participants was less than 10%, the odds ratio and linear trends of OR were not analyzed due to a small prevalence of each quartile group. In addition, the association between diet-related GHGE and the usual food intake was examined using linear regression models and one-way ANOVA with post hoc Bonferroni’s test.

Results

The basic characteristics of the participants are described in Table 1. The mean age was 44.5 years and mean BMI was and 23.3 kg/m2. Around 80% of the participants worked on clerical or nursing care. The prevalence of under-reporters (defined as having EI:BMR <1.02 and for men and <1.03 for women) was 3.6% (nine men and five women) and that of over-reporters (defined as having EI:BMR >2.35 for men and >2.36 for women) was 2.3% (three men and six women). Participants with higher diet-related GHGE were significantly older than those with lower diet-related GHGE.

thumbnail
Table 1. Basic characteristics of participants according to quartile (Q) of diet-related GHGE (g CO2-eq/day) among 392 Japanese adultsa.

https://doi.org/10.1371/journal.pone.0240803.t001

The overall prevalence of inadequacy is shown in Table 2. Of seven nutrients with DG, over 60% of the participants did not meet the DRIs for saturated fat, dietary fiber, sodium, and potassium. In particular, 90% of the participants did not meet the DRIs for dietary fiber and sodium. Similarly, 72% of participants did not meet the WHO’s conditional recommendation on free sugar. Of 14 nutrients with EAR, the inadequacy prevalence for protein, niacin, vitamin B-12, folate, and copper was less than 10%, while the prevalence for vitamins A, thiamine, and calcium was nearly 60%.

thumbnail
Table 2. Usual nutrient intake according to quartile (Q) of diet-related GHGE (g CO2-eq/day) among 392 Japanese adults (aged 20–69 y)a.

https://doi.org/10.1371/journal.pone.0240803.t002

There was no association between diet-related GHGE and EI (Table 2). For nutrients, the diet-related GHGE was inversely associated with carbohydrate intake and positively with intakes of all the remaining nutrients, except for total fat and saturated fat. Analysis by one-way ANOVA with post hoc Bonferroni test showed similar results. There was no significant difference between quartile groups for total fat, saturated fat, and free sugars. On the other hand, higher quartile groups generally had lower intake for carbohydrate but higher intakes for other nutrients than lower quartile groups.

The overall adherence to the DG and EAR was better among participants in the higher diet-related GHGE quartile compared to participants in the lower quartile (Table 3). The prevalence of inadequacy for protein, dietary fiber, potassium, vitamins A, B-6, and C, thiamine, riboflavin, calcium, magnesium, iron, and zinc decreased with increasing quartile of the diet-related GHGE. Conversely, the prevalence of inadequate sodium intake was increased with increasing quartile, but the prevalence in the lowest quartile was not low: 89% and 98% of the participants had intake above the recommendations in lowest and highest quartile group.

thumbnail
Table 3. Odds ratios for inadequate nutrient intake compared to DRIs reference value according to the quartile (Q) of usual diet-related GHGE (g CO2-eq/day) among 392 Japanese adults (aged 20–69 y)a.

https://doi.org/10.1371/journal.pone.0240803.t003

The diet-related GHGE was positively associated with the intakes of potato, vegetables, mushrooms, seaweeds, fish and seafood, meat, tea and coffee, and seasonings, while negatively associated with cereals, fat and oils, and sweetened beverages (Table 4). Analysis by one-way ANOVA with post hoc Bonferroni test also found similar results.

thumbnail
Table 4. Usual food intake (g/d) according to quartile (Q) of usual diet-related GHGE (g CO2-eq/day) among 392 Japanese adults (aged 20–69 y)a.

https://doi.org/10.1371/journal.pone.0240803.t004

Discussion

To our knowledge, this is the first study to evaluate the association between diet-related GHGE and nutritional adequacy among Japanese adults. Our result would be useful to develop future public policies or dietary guidelines to encourage sustainable healthy dietary choices. We observed overall lower prevalence of inadequacy among higher diet-related GHGE quartiles compared to lower quartiles. The participants in higher quartiles had a higher intake of almost all nutrients examined. Thus, according to the current Japanese diet, diet-related GHGE was positively associated with nutrition adequacy. Our result is inconsistent with observational studies from Western countries, where relatively consistent inverse associations between diet-related GHGE and nutritional adequacy or diet-quality scores were found [39] with a few exceptions [2, 7]. These inconsistent findings between this study and Western studies could be at least partly explained by difference in food intake and major food sources of diet-related GHGE. In Western countries, a few food groups such as meat and dairy products predominantly contributed to diet-related GHGE. For example, contributions of meat and dairy products were estimated at 31.3%-38.4% and 11%-25%, respectively, in European countries [14, 16, 17] and 56.6% and 18.3%, respectively, in the US [18]. Studies from the Netherlands [17], the US [6], and Ireland [14] have shown consistent positive associations between diet-related GHGE and intakes of energy-dense foods such as alcoholic beverages [14, 17], and fats [6, 14, 17] as well as meat [6, 14, 17] and dairy products [6, 14, 17]. In Japan, meat was also the top contributor to diet-related GHGE (19.6%), followed by fish/seafood (13.8%) and cereals (13.1%) [19]. Nevertheless, it should be noted that the percentage contribution of meat was lower than that in the Western countries. In addition, the contribution of dairy products (4.6%) was low [19]. In relation to diet-related GHGE, intakes of vegetables, fish/seafood, and meat showed positive associations, while those of cereals and fat and oils showed inverse associations. In this regard, intakes of nutrient-dense foods and moderate meat intake would be associated with higher intakes of protein and micronutrients as well as diet-related GHGE among Japanese, while dietary patterns in Western countries characterized by higher intake of meat and dairy products would be associated with both higher diet-related GHGE and lower nutrient intake or diet quality [39].

On the contrary to observational studies, previous scenario studies in European populations showed that healthy dietary pattern complying dietary guidelines would not always reduce diet-related GHGE [1012]. These results suggest that there would be trade-offs between nutrient intake and diet-related GHGE when achieving further improvement of nutrition intake, although healthier diet would associate with lower diet-related GHGE within the current observed diet in Western populations. On the other hand, our study suggests that just shifting to the diets with lower diet-related GHGE that were currently observed could not achieve sufficient nutritional adequacy among Japanese. A drastic dietary change would be needed to achieve both a reduction in the diet-related GHGE and an improvement in the nutritional adequacy. Even though meat and fish were major contributors to diet-related GHGE among Japanese [19], a previous modeling study for Japanese aiming at achieving nutritional goals reported a need for increasing intake of meat and fish in young adults [53]. Thus, there would be a trade-off between impact to diet-related GHGE and contribution to micronutrient intake by animal-based foods among Japanese. It is not known what amount of intake of animal-based food should be recommended for Japanese when both nutritional benefits and impact for diet-related GHGE are taken into account. Further research is needed to design optimized dietary patterns to achieve nutrition goals as well as reduction of diet-related GHGE.

Apart from intakes of animal-based foods, dietary modification would be needed for reducing sodium intake among Japanese. In the present study, prevalence of inadequate sodium intake was generally high and increased with increasing quartiles of diet-related GHGE. Similarly, previous Japanese studies reported that one of three or four dietary patterns identified had the lowest prevalence of inadequacy for fifteen nutrients and the highest prevalence for sodium [45, 46]. These results suggest that participants who seem to have favorable dietary patterns do not always comply with a lower sodium diet. Thus, because seasonings is the top food source of sodium (61.7% for men and 62.9% for women) [33] and the fifth largest contributor of diet-related GHGE (9.4%) among Japanese [19], reducing seasonings intake is demanded in population level for both aspects of healthy diets and diet-related GHGE.

Several limitations of the present study warrant mention. First, the participants in this study were not randomly sampled from the general Japanese population. The participants would be more health-conscious than the general Japanese population. In addition, most of the participants were working at welfare facilities. Moreover, proportion of urban and rural area was not considered at recruitment although regional differences in dietary habits were considered at sampling. Thus, further research in a national representative sample would be needed. Second, our relatively small sample size (n = 396) would limit the power to detect moderate associations with statistical significance. In addition, the estimated usual intake distributions of nutrients and foods would be uncertain due to the small sample size [54]. Nevertheless, significant associations were generally observed between diet-related GHGE and intakes of nutrient and food. Although our sample size might be sufficient to detect the difference between quartiles of diet-related GHGE, further studies with larger sample sizes would be needed. Third, the system boundaries considered in the GHGE database were limited to the production stage due to the lack of quality data to develop the GHGE database for Japanese diet including the whole life cycle. Fourth, both nutritional adequacy and diet-related GHGE were estimated based on the self-reported dietary assessment method, which is prone to measurement errors due to, for example, changes in dietary habits during the assessment period, under-recording, under-eating, and intentional, or unintentional misreporting [39]. Given that a positive association between EI and diet-related GHGE is widely reported [8, 13], misreporting of EI may have a substantial influence on the estimation of diet-related GHGE. However, diet-related GHGE was adjusted for EI by the residual method to avoid a confounding effect of energy intake on associations between diet-related GHGE and nutritional adequacy. In addition, the effect of energy-misreporting would be small in this study because similar results have shown when under- and over-reporters were excluded from the analysis (S7–S10 Tables in S1 File). Thus, any potential effect of energy misreporting was minimized in our study. Fifth, due to a lack of objective information on physical activity, bias can be present in the identification of under- and over-reporters. Nevertheless, the potential effect of energy-misreporting in this study would be small. Finally, this study was conducted from February to March. Several previous studies have reported seasonal differences in intakes among Japanese adults [5558]. Thus, this limited period for the survey might have produced some bias in assessing the usual intake.

In conclusion, there was an overall better nutritional adequacy observed in the participants with higher diet-related GHGE when compared to individuals with lower GHGE among Japanese adults. This suggests that current dietary choices should be drastically changed to achieve sustainable diets. Further studies are needed to design sustainable diets.

Acknowledgments

We thank the dietitians who supported the survey in each welfare facility for their valuable contribution and Editage (www.editage.jp) for English language editing.

References

  1. 1. FAO. Biodiversity and sustainable diets-united against hunger. Food Agric Organ United Nations. Rome, Italy: Food and Agriculture Organization of the United Nations; 2010.
  2. 2. Vieux F, Soler L, Touazi D, Darmon N. High nutritional quality is not associated with low greenhouse gas emissions in self-selected diets of French adults. Am J Clin Nutr. 2013;97: 569–83. pmid:23364012
  3. 3. Sjörs C, Hedenus F, Sjölander A, Tillander A, Bälter K. Adherence to dietary recommendations for Swedish adults across categories of greenhouse gas emissions from food. Public Health Nutr. 2017;20: 3381–3393. pmid:28879831
  4. 4. Murakami K, Livingstone MBE. Greenhouse gas emissions of self-selected diets in the UK and their association with diet quality: is energy under-reporting a problem? Nutr J. 2018;17: 27. pmid:29466993
  5. 5. Biesbroek S, Verschuren WMM, Boer JMA, Van De Kamp ME, Van Der Schouw YT, Geelen A, et al. Does a better adherence to dietary guidelines reduce mortality risk and environmental impact in the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition? Br J Nutr. 2017;118: 69–80. pmid:28768562
  6. 6. Rose D, Heller MC, Willits-Smith AM, Meyer RJ. Carbon footprint of self-selected US diets: nutritional, demographic, and behavioral correlates. Am J Clin Nutr. 2019;109: 526–534. pmid:30698631
  7. 7. Mertens E, Kuijsten A, Geleijnse JM, Boshuizen HC, Feskens EJM, Van’T Veer P. FFQ versus repeated 24-h recalls for estimating diet-related environmental impact. Nutr J. 2019;18: 1–12.
  8. 8. Monsivais P, Scarborough P, Lloyd T, Mizdrak A, Luben R, Mulligan AA, et al. Greater accordance with the Dietary Approaches to Stop Hypertension dietary pattern is associated with lower diet-related greenhouse gas production but higher dietary costs in the United Kingdom. Am J Clin Nutr. 2015;102: 138–145. pmid:25926505
  9. 9. Seconda L, Baudry J, Allès B, Boizot-Szantai C, Soler LG, Galan P, et al. Comparing nutritional, economic, and environmental performances of diets according to their levels of greenhouse gas emissions. Clim Change. 2018;148: 155–172.
  10. 10. Vieux F, Perignon M, Gazan R, Darmon N. Dietary changes needed to improve diet sustainability: are they similar across Europe? Eur J Clin Nutr. 2018;72: 951–960. pmid:29402959
  11. 11. van Dooren C, Tyszler M, Kramer GF, Aiking H. Combining low price, low climate impact and high nutritional value in one shopping basket through diet optimization by linear programming. Sustain. 2015;7: 12837–12855.
  12. 12. van de Kamp ME, van Dooren C, Hollander A, Geurts M, Brink EJ, van Rossum C, et al. Healthy diets with reduced environmental impact?–The greenhouse gas emissions of various diets adhering to the Dutch food based dietary guidelines. Food Res Int. 2018;104: 14–24. pmid:29433779
  13. 13. Temme EHM, Toxopeus IB, Kramer GFH, Brosens MCC, Drijvers JMM, Tyszler M, et al. Greenhouse gas emission of diets in the Netherlands and associations with food, energy and macronutrient Intakes. Public Health Nutr. 2014;18: 2433–2445. pmid:25543460
  14. 14. Hyland JJ, Henchion M, McCarthy M, McCarthy SN. The climatic impact of food consumption in a representative sample of Irish adults and implications for food and nutrition policy. Public Health Nutr. 2017;20: 726–738. pmid:27667716
  15. 15. Vieux F, Darmon N, Touazi D, Soler LG. Greenhouse gas emissions of self-selected individual diets in France: Changing the diet structure or consuming less? Ecol Econ. 2012;75: 91–101.
  16. 16. Mertens E, Kuijsten A, van Zanten HH, Kaptijn G, Dofková M, Mistura L, et al. Dietary choices and environmental impact in four European countries. J Clean Prod. 2019;237: 117827.
  17. 17. Biesbroek S, Bueno-de-Mesquita HB, Peeters PHM, Verschuren WM, van der Schouw YT, Kramer GFH, et al. Reducing our environmental footprint and improving our health: greenhouse gas emission and land use of usual diet and mortality in EPIC-NL: a prospective cohort study. Environ Health. 2014;13: 27. pmid:24708803
  18. 18. Heller MC, Willits-Smith A, Meyer R, Keoleian GA, Rose D. Greenhouse gas emissions and energy use associated with production of individual self-selected US diets. Environ Res Lett. 2018;13: 044004. pmid:29853988
  19. 19. Sugimoto M, Murakami K, Asaskura K, Masayasu S, Sasaki S. Diet-related greenhouse gas emission and major food contributor among Japanese adults: comparison of different calculation methods. Public Health Nutr. 2020; 1–11. Online ahead of print. pmid:32389142
  20. 20. Green RF, Joy EJM, Harris F, Agrawal S, Aleksandrowicz L, Hillier J, et al. Greenhouse gas emissions and water footprints of typical dietary patterns in India. Sci Total Environ. 2018;643: 1411–1418. pmid:30189557
  21. 21. Song G, Li M, Fullana-i-palmer P, Williamson D, Wang Y. Dietary changes to mitigate climate change and benefit public health in China. Sci Total Environ. 2017;577: 289–298. pmid:27802883
  22. 22. Mbow C, Rosenzweig C, Barioni LG, Benton TG, Herrero M, Krishnapillai M, et al. Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Nature. 2019.
  23. 23. Olivier J, Schure K, Peters J. Trends in global CO2 and total greenhouse gas emissions. The Hague; 2017. http://www.pbl.nl/sites/default/files/cms/publicaties/pbl-2017-trends-in-global-co2-and-total-greenhouse-gas-emis-sons-2017-report_2674.pdf.
  24. 24. Government of Japan. The plan for global warming countermeasure (in Japanese). 2016 [cited 30 Jul 2019]. http://www.env.go.jp/press/files/jp/102816.pdf
  25. 25. Sasaki S. The value of the National Health and Nutrition Survey in Japan. Lancet. 2011;378: 1205–6. pmid:21885109
  26. 26. Ikeda N, Saito E, Kondo N, Inoue M, Ikeda S, Satoh T, et al. What has made the population of Japan healthy? Lancet. 2011;378: 1094–105. pmid:21885105
  27. 27. Imamura F, Micha R, Khatibzadeh S, Fahimi S, Shi P, Powles J, et al. Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment. Lancet Glob Heal. 2015;3: e132–e142. pmid:25701991
  28. 28. Micha R, Khatibzadeh S, Shi P, Andrews KG, Engell RE, Mozaffarian D. Global, regional and national consumption of major food groups in 1990 and 2010: A systematic analysis including 266 country-specific nutrition surveys worldwide. BMJ Open. 2015;5: e008705. pmid:26408285
  29. 29. Ministry of Health Labour and Welfare. The National Health and Nutrition Survey in Japan, 2013 (in Japanese). [cited 20 Aug 2019]. http://www.mhlw.go.jp/bunya/kenkou/kenkou_eiyou_chousa.html
  30. 30. Zhou BF, Stamler J, Dennis B, Moag-Stahlberg a, Okuda N, Robertson C, et al. Nutrient intakes of middle-aged men and women in China, Japan, United Kingdom, and United States in the late 1990s: the INTERMAP study. J Hum Hypertens. 2003;17: 623–30. pmid:13679952
  31. 31. Yip CSC, Lam W, Fielding R. A summary of meat intakes and health burdens. Eur J Clin Nutr. 2018;72: 18–29. pmid:28792013
  32. 32. Nagao M, Iso H, Yamagishi K, Date C, Tamakoshi A. Meat consumption in relation to mortality from cardiovascular disease among Japanese men and women. Eur J Clin Nutr. 2012;66: 687–693. pmid:22333876
  33. 33. Asakura K, Uechi K, Masayasu S, Sasaki S. Sodium sources in the Japanese diet: difference between generations and sexes. Public Health Nutr. 2015;19: 2011–23. pmid:26573337
  34. 34. Asakura K, Uechi K, Sasaki Y, Masayasu S, Sasaki S. Estimation of sodium and potassium intakes assessed by two 24 h urine collections in healthy Japanese adults: a nationwide study. Br J Nutr. 2014;112: 119–205. pmid:25111316
  35. 35. Science and Technology Agency. Standard Tables of Food Composition in Japan. (in Japanese). 7th editio. Printed Bureau of Ministry of Finance; 2015.
  36. 36. Fujiwara A, Murakami K, Asakura K, Uechi K, Sugimoto M, Wang H-C, et al. Association of free sugar intake estimated using a newly-developed food composition database with lifestyles and parental characteristics among Japanese children aged 3–6 years: DONGuRI Study. J Epidemiol. 2018;29: 414–423. pmid:30344196
  37. 37. Fujiwara A, Murakami K, Asakura K, Uechi K, Sugimoto M, Wang H-C, et al. Estimation of starch and sugar intake in a Japanese population based on a newly developed food composition database. Nutrients. 2018;10: 1474. pmid:30309012
  38. 38. Black AE. The sensitivity and specificity of the Goldberg cut-off for EI:BMR for identifying diet reports of poor validity. Eur J Clin Nutr. 2000;54: 395–404. pmid:10822286
  39. 39. Livingstone MBE, Black AE. Markers of the validity of reported energy intake. J Nutr. 2003;133: 895S–920S. pmid:12612176
  40. 40. Murakami K, Livingstone MBE. Prevalence and characteristics of misreporting of energy intake in US adults: NHANES 2003–2012. Br J Nutr. 2015;145: 2715–24. pmid:26299892
  41. 41. Nansai K, Kagawa S, Kondo Y, Suh S, Inaba R, Nakajima K. Improving the completeness of product carbon foodprints using a global link input-output model: The case of Japan. Econ Syst Res. 2009;9: 267–290.
  42. 42. Harttig U, Haubrock J, Knüppel S, Boeing H. The MSM program: Web-based statistics package for estimating usual dietary intake using the multiple source method. Eur J Clin Nutr. 2011;65: S87–S91. pmid:21731011
  43. 43. Haubrock J, Nöthlings U, Volatier J-L, Dekkers A, Ocké M, Harttig U, et al. Estimating usual food intake distributions by using the Multiple Source Method in the EPIC-Potsdam Calibration Study. J Nutr. 2011;141: 914–920. pmid:21430241
  44. 44. Ministry of Health Labour and Welfare. Dietary Reference Intakes for Japanese, 2020. (in Japanese). 2020.
  45. 45. Saito A, Matsumoto M, Hyakutake A, Saito M, Okamoto N, Tsuji M. The frequency of cooking dinner at home and its association with nutrient intake adequacy among married young-to-middle-aged Japanese women: the POTATO Study. J Nutr Sci. 2019. pmid:31037217
  46. 46. Murakami K, Okubo H, Livingstone MBE, Fujiwara A, Asakura K, Uechi K, et al. Adequacy of usual intake of Japanese children aged 3−5 years: A nationwide study. Nutrients. 2018;10: 1150. pmid:30142935
  47. 47. Ministry of Health Labour and Welfare. Dietary Reference Intakes for Japanese, 2015. 2015.
  48. 48. FAO/WHO. Requirements of Vitamin A, Iron, Folate and Vitamin B12. Report of a Joint FAO/WHO Expert Consultation. Rome, Italy; 1988.
  49. 49. Institute of Medicine Food and Nutrition Board. Dietary Reference Intakes: Applications in Dietary Assessment. Washington, DC: National Academies Press; 2000.
  50. 50. WHO/FAO. Guidelines on Food Fortification with Micronutrients. Geneva, Switzerland; 2006.
  51. 51. WHO. Guideline: Sugars intake for adults and children. World Heal Organ. Geneva, Switzerland; 2015. 978 92 4 154902 8
  52. 52. Willett W. Implications of Total Energy Intake for Epidemiologic Analyses. Third edit. Nutritional Epidemiology. Third edit. Oxford University Press; 2012. p. 274.
  53. 53. Okubo H, Sasaki S, Murakami K, Yokoyama T, Hirota N, Notsu A, et al. Designing optimal food intake patterns to achieve nutritional goals for Japanese adults through the use of linear programming optimization models. Nutr J. 2015;14: 57. pmid:26048405
  54. 54. Souverein OW, Dekkers AL, Geelen A, Haubrock J, de Vries JH, Ocké MC, et al. Comparing four methods to estimate usual intake distributions. Eur J Clin Nutr. 2011;65: S92–S101. pmid:21731012
  55. 55. Tokudome Y, Imaeda N, Nagaya T, Ikeda M, Fujiwara N, Sato J, et al. Daily, weekly, seasonal, within- and between-individual variation in nutrient intake according to four season consecutive 7 day weighed diet records in Japanese female dietitians. J Epidemiol. 2002;12: 85–92. pmid:12033533
  56. 56. Mori S, Saito K, Wakasa Y. Studies on annual fluctuation of food intake in female college students. Japanese J Nutr Diet. 1981;39: 243–368. https://doi.org/10.1093/mnras/183.3.341
  57. 57. Owaki A, Takatsuka N, Kawakami N, Shimizu H. Seasonal variations of butrient intake assessed by 24 hour recall method. Japanese J Nutr Diet. 1996;54: 11–18.
  58. 58. Taguchi C, Kishimoto Y, Takeuchi I, Tanaka M, Iwashima T, Fukushima Y, et al. Estimated dietary polyphenol intake and its seasonal variations among Japanese University students. J Nutr Sci Vitaminol (Tokyo). 2019;65: 192–195. pmid:31061289