Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Source
2.2. Data Preparation
2.3. Measurement of Brown and White Rice Consumption
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- FAO; WHO. Sustainable Healthy Diets—Guiding Principles; FAO and WHO: Rome, Italy, 2019. [Google Scholar]
- Willett, W.; Rockstrom, J.; Loken, B.; Springmann, M.; Lang, T.; Vermeulen, S.; Garnett, T.; Tilman, D.; DeClerck, F.; Wood, A.; et al. Food in the Anthropocene: The EAT-Lancet Commission on healthy diets from sustainable food systems. Lancet 2019, 393, 447–492. [Google Scholar] [CrossRef] [PubMed]
- Aune, D.; Keum, N.; Giovannucci, E.; Fadnes, L.T.; Boffetta, P.; Greenwood, D.C.; Tonstad, S.; Vatten, L.J.; Riboli, E.; Norat, T. Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality: Systematic review and dose-response meta-analysis of prospective studies. BMJ 2016, 353, i2716. [Google Scholar] [CrossRef] [PubMed]
- Aune, D.; Chan, D.S.; Lau, R.; Vieira, R.; Greenwood, D.C.; Kampman, E.; Norat, T. Dietary fibre, whole grains, and risk of colorectal cancer: Systematic review and dose-response meta-analysis of prospective studies. BMJ 2011, 343, d6617. [Google Scholar] [CrossRef] [PubMed]
- Hu, Y.; Ding, M.; Sampson, L.; Willett, W.C.; Manson, J.E.; Wang, M.; Rosner, B.; Hu, F.B.; Sun, Q. Intake of whole grain foods and risk of type 2 diabetes: Results from three prospective cohort studies. BMJ 2020, 370, m2206. [Google Scholar] [CrossRef] [PubMed]
- Juan, J.; Liu, G.; Willett, W.C.; Hu, F.B.; Rexrode, K.M.; Sun, Q. Whole Grain Consumption and Risk of Ischemic Stroke: Results From 2 Prospective Cohort Studies. Stroke 2017, 48, 3203–3209. [Google Scholar] [CrossRef] [PubMed]
- GBD Risk Factors Collaborators Global burden of 87 risk factors in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020, 396, 1223–1249. [CrossRef] [PubMed]
- Micha, R.; Khatibzadeh, S.; Shi, P.; Andrews, K.G.; Engell, R.E.; Mozaffarian, D.; Global Burden of Diseases, N.; Chronic Diseases Expert, G. 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. [Google Scholar] [CrossRef] [PubMed]
- Yoshiike, N.; Hayashi, F.; Takemi, Y.; Mizoguchi, K.; Seino, F. A New Food Guide in Japan: The Japanese Food Guide Spinning Top. Nutr. Rev. 2007, 65, 149–154. [Google Scholar] [CrossRef] [PubMed]
- Ministry of Education, Culture, Sports, Science, and Technology; Ministry of Health, Labour and Welfare; Ministry of Agriculture, Forestry and Fisheries. Main points of the revision of “Dietary guidelines for Japanese”. 2016. Available online: https://www.maff.go.jp/j/syokuiku/attach/pdf/shishinn-10.pdf (accessed on 15 April 2024).
- Yu, J.; Balaji, B.; Tinajero, M.; Jarvis, S.; Khan, T.; Vasudevan, S.; Ranawana, V.; Poobalan, A.; Bhupathiraju, S.; Sun, Q.; et al. White rice, brown rice and the risk of type 2 diabetes: A systematic review and meta-analysis. BMJ Open 2022, 12, e065426. [Google Scholar] [CrossRef] [PubMed]
- Sun, Q.; Spiegelman, D.; van Dam, R.M.; Holmes, M.D.; Malik, V.S.; Willett, W.C.; Hu, F.B. White rice, brown rice, and risk of type 2 diabetes in US men and women. Arch. Intern. Med. 2010, 170, 961–969. [Google Scholar] [CrossRef] [PubMed]
- Kennedy, E.; Luo, H. Association between Rice Consumption and Selected Indicators of Dietary and Nutritional Status using National Health and Nutrition Examination Survey 2007–2008. Ecol. Food Nutr. 2015, 54, 224–239. [Google Scholar] [CrossRef] [PubMed]
- Batres-Marquez, S.P.; Jensen, H.H.; Upton, J. Rice consumption in the United States: Recent evidence from food consumption surveys. J. Am. Diet. Assoc. 2009, 109, 1719–1727. [Google Scholar] [CrossRef] [PubMed]
- Nanri, A.; Mizoue, T.; Noda, M.; Takahashi, Y.; Kato, M.; Inoue, M.; Tsugane, S. Rice intake and type 2 diabetes in Japanese men and women: The Japan Public Health Center–based Prospective Study123. Am. J. Clin. Nutr. 2010, 92, 1468–1477. [Google Scholar] [CrossRef] [PubMed]
- Sawada, K.; Takemi, Y.; Murayama, N.; Ishida, H. Relationship between rice consumption and body weight gain in Japanese workers: White versus brown rice/multigrain rice. Appl. Physiol. Nutr. Metab. 2019, 44, 528–532. [Google Scholar] [CrossRef] [PubMed]
- Ministry of Health, Labour and Welfare. National Health and Nutrition Survey. Available online: http://www.mhlw.go.jp/bunya/kenkou/kenkou_eiyou_chousa.html (accessed on 12 March 2024).
- Government of Japan. Statistics Act. 2007. Available online: https://www.japaneselawtranslation.go.jp/ja/laws/view/148 (accessed on 12 March 2024).
- Ministry of Education, Culture, Sports, Science, and Technology; Ministry of Health, Labour and Welfare; Ministry of Economy, Trade and Industry. Ethical Guidelines for Medical and Biological Research Involving Human Subjects. 2021. Available online: https://www.lifescience.mext.go.jp/files/pdf/n2373_01.pdf (accessed on 12 March 2024).
- Ikeda, N.; Takimoto, H.; Imai, S.; Miyachi, M.; Nishi, N. Data Resource Profile: The Japan National Health and Nutrition Survey (NHNS). Int. J. Epidemiol. 2015, 44, 1842–1849. [Google Scholar] [CrossRef] [PubMed]
- Ministry of Education, Culture, Sports, Science, and Technology. Standard Tables of Food Composition in Japan—2010. 2010. Available online: https://www.mext.go.jp/b_menu/shingi/gijyutu/gijyutu3/houkoku/1298713.htm (accessed on 12 March 2024).
- Ministry of Education, Culture, Sports, Science, and Technology. Standard Tables of food Composition in Japan—2015—(Seventh Revised Edition). 2015. Available online: https://www.mext.go.jp/en/policy/science_technology/policy/title01/detail01/1374030.htm (accessed on 12 March 2024).
- Ikeda, N.; Nishi, N. Key variable combinations for identifying non-participants in the Japan National Health and Nutrition Survey through record linkage with the Comprehensive Survey of Living Conditions. Nihon Koshu Eisei Zasshi 2019, 66, 210–218. [Google Scholar] [PubMed]
- National Institutes of Biomedical Innovation, Health and Nutrition. Definitions and Assessment Criteria for the Physical Status Questionnaire Component of of the National Health and Nutrition Survey. Healteh Japan 21 (the Second Term) Analysis and Assessment Project. Available online: https://www.nibiohn.go.jp/eiken/kenkounippon21/eiyouchousa/annotation_shintai.html (accessed on 27 March 2024).
- National Institutes of Biomedical Innovation, Health and Nutrition. Definitions and Assessment Criteria for the Lifestyle Habits Questionnaire Component of the National Health and Nutrition Survey. Health Japan 21 (the Second Term) Analysis and Assessment Project. Available online: https://www.nibiohn.go.jp/eiken/kenkounippon21/eiyouchousa/annotation_seikatsu.html#01 (accessed on 27 March 2024).
- Korczak, R.; Slavin, J.L. Definitions, regulations, and new frontiers for dietary fiber and whole grains. Nutr. Rev. 2020, 78, 6–12. [Google Scholar] [CrossRef] [PubMed]
- Miller, K.B. Review of whole grain and dietary fiber recommendations and intake levels in different countries. Nutr. Rev. 2020, 78, 29–36. [Google Scholar] [CrossRef] [PubMed]
- Lichtenstein, A.H.; Appel, L.J.; Vadiveloo, M.; Hu, F.B.; Kris-Etherton, P.M.; Rebholz, C.M.; Sacks, F.M.; Thorndike, A.N.; Van Horn, L.; Wylie-Rosett, J. 2021 Dietary Guidance to Improve Cardiovascular Health: A Scientific Statement From the American Heart Association. Circulation 2021, 144, e472–e487. [Google Scholar] [CrossRef]
- Murakami, K.; Livingstone, M.B.E.; Sasaki, S. Meal-specific dietary patterns and their contribution to overall dietary patterns in the Japanese context: Findings from the 2012 National Health and Nutrition Survey, Japan. Nutrition 2019, 59, 108–115. [Google Scholar] [CrossRef] [PubMed]
- Fisheries Agency. Fisheries of Japan—FY 2022 (2021/2023) 2023. Available online: https://www.jfa.maff.go.jp/e/annualreport/attach/pdf/index-1.pdf (accessed on 28 March 2024).
- Murakami, K.; Livingstone, M.B.E.; Sasaki, S. Thirteen-Year Trends in Dietary Patterns among Japanese Adults in the National Health and Nutrition Survey 2003–2015: Continuous Westernization of the Japanese Diet. Nutrients 2018, 10, 994. [Google Scholar] [CrossRef] [PubMed]
- Adebamowo, S.N.; Eseyin, O.; Yilme, S.; Adeyemi, D.; Willett, W.C.; Hu, F.B.; Spiegelman, D.; Adebamowo, C.A.; Global Nutrition Epidemiologic Transition Initiative. A Mixed-Methods Study on Acceptability, Tolerability, and Substitution of Brown Rice for White Rice to Lower Blood Glucose Levels among Nigerian Adults. Front. Nutr. 2017, 4, 33. [Google Scholar] [CrossRef] [PubMed]
- Cabral, D.; Moura, A.P.; Fonseca, S.C.; Oliveira, J.C.; Cunha, L.M. Exploring Rice Consumption Habits and Determinants of Choice, Aiming for the Development and Promotion of Rice Products with a Low Glycaemic Index. Foods 2024, 13, 301. [Google Scholar] [CrossRef]
- Gondal, T.A.; Keast, R.S.J.; Shellie, R.A.; Jadhav, S.R.; Gamlath, S.; Mohebbi, M.; Liem, D.G. Consumer Acceptance of Brown and White Rice Varieties. Foods 2021, 10, 1950. [Google Scholar] [CrossRef] [PubMed]
- Gyawali, P.; Tamrakar, D.; Shrestha, A.; Shrestha, H.; Karmacharya, S.; Bhattarai, S.; Bhandari, N.; Malik, V.; Mattei, J.; Spiegelman, D.; et al. Consumer acceptance and preference for brown rice-A mixed-method qualitative study from Nepal. Food Sci. Nutr. 2022, 10, 1864–1874. [Google Scholar] [CrossRef] [PubMed]
- Monge-Rojas, R.; Mattei, J.; Fuster, T.; Willett, W.; Campos, H. Influence of sensory and cultural perceptions of white rice, brown rice and beans by Costa Rican adults in their dietary choices. Appetite 2014, 81, 200–208. [Google Scholar] [CrossRef] [PubMed]
- Muhihi, A.; Gimbi, D.; Njelekela, M.; Shemaghembe, E.; Mwambene, K.; Chiwanga, F.; Malik, V.S.; Wedick, N.M.; Spiegelman, D.; Hu, F.B.; et al. Consumption and acceptability of whole grain staples for lowering markers of diabetes risk among overweight and obese Tanzanian adults. Glob. Health 2013, 9, 26. [Google Scholar] [CrossRef]
- Sudha, V.; Spiegelman, D.; Hong, B.; Malik, V.; Jones, C.; Wedick, N.M.; Hu, F.B.; Willett, W.; Bai, M.R.; Ponnalagu, M.M.; et al. Consumer Acceptance and Preference Study (CAPS) on Brown and Undermilled Indian Rice Varieties in Chennai, India. J. Am. Coll. Nutr. 2013, 32, 50–57. [Google Scholar] [CrossRef] [PubMed]
- Zhang, G.; Malik, V.S.; Pan, A.; Kumar, S.; Holmes, M.D.; Spiegelman, D.; Lin, X.; Hu, F.B. Substituting Brown Rice for White Rice to Lower Diabetes Risk: A Focus-Group Study in Chinese Adults. J. Am. Diet. Assoc. 2010, 110, 1216–1221. [Google Scholar] [CrossRef] [PubMed]
- Multi Functional Brown Rice Association. Brown Rice Consumption White Paper 2019. 2019. Available online: http://www.mfbr.org/PDF/genmaishokuhakusho2019.pdf (accessed on 8 May 2024).
- Saika, K.; Yonei, Y. Reduction of medical expenses by ingesting processed brown rice (sub-aleurone layer residual rinse-free rice, dewaxed brown rice). Glycative Stress Res. 2021, 8, 115–122. [Google Scholar]
- Ryu, S.H.; Wang, Z.L.; Kim, S.J.; Cho, H.J. Effects of multigrain rice and white rice on periodontitis: An analysis using data from the Korea National Health and Nutrition Examination Survey 2012–2015. Epidemiol. Health 2023, 45, e2023063. [Google Scholar] [CrossRef] [PubMed]
Data Source, Characteristics, Values | Reference Categories |
---|---|
National Health and Nutrition Survey | |
Sex | |
Females, males | Males |
Age, years | |
20–29; 30–39; 40–49; 50–59; 60–69; 70–79; ≥80 | 20–29 years |
Municipality of residence | |
21 major cities; other cities; towns/villages | Other cities |
Body mass index, kg/m2 a | |
<18.5; 18.5 to <25.0; 25.0 to <30.0; ≥30.0; missing | ≥ 25.0 kg/m2 |
Regular exercise habit b | |
Absent; present; missing | Absent |
Smoking status c | |
Former/never smoker; daily/occasional smoker; missing | Daily/occasional smoker |
Alcohol consumption (2014, 2015, 2017–2019) d | |
Non-drinker; drinker; missing | Drinker |
Comprehensive Survey on Living Conditions | |
Educational background | |
Elementary/junior high school; senior high school; junior/career college; university/graduate school; unknown | Elementary/junior high school |
Households without children aged <6 years | |
Not applicable; applicable | Not applicable |
Alcohol consumption (2013) d | |
Non-drinker; drinker; missing | Drinker |
Survey year | |
2013, 2014, 2015, 2017, 2018, 2019 | 2013 |
Year | n | Brown Rice Intake, Grams/Day | White Rice Intake, Grams/Day | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Percentiles | Percentiles | ||||||||||||||||||
1st | 5th | 10th | 25th | 50th | 75th | 90th | 95th | 99th | 1st | 5th | 10th | 25th | 50th | 75th | 90th | 95th | 99th | ||
Both sexes | |||||||||||||||||||
2012 | 26,726 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 57.1 | 0.0 | 11.9 | 50.0 | 95.2 | 150.0 | 214.3 | 285.7 | 314.3 | 415.5 |
2013 | 6481 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 57.1 | 0.0 | 0.0 | 47.6 | 86.0 | 142.9 | 197.1 | 266.7 | 302.4 | 400.0 |
2014 | 6727 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 42.4 | 0.0 | 0.0 | 47.6 | 94.0 | 142.9 | 200.0 | 266.2 | 309.5 | 419.0 |
2015 | 6172 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 43.2 | 81.0 | 138.1 | 190.5 | 261.9 | 296.2 | 395.2 |
2016 | 21,851 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 47.6 | 85.7 | 142.9 | 192.4 | 261.9 | 295.2 | 393.3 |
2017 | 5750 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 41.0 | 76.2 | 132.9 | 190.5 | 257.1 | 291.4 | 392.9 |
2018 | 5743 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 41.9 | 80.1 | 132.4 | 190.5 | 259.5 | 295.2 | 395.2 |
2019 | 4927 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 38.1 | 71.4 | 123.8 | 190.5 | 246.7 | 285.7 | 372.9 |
Females | |||||||||||||||||||
2012 | 14,461 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 60.0 | 0.0 | 0.0 | 47.6 | 76.2 | 128.6 | 176.2 | 225.7 | 259.5 | 309.5 |
2013 | 3483 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 40.5 | 71.4 | 114.3 | 166.7 | 214.3 | 247.1 | 290.5 |
2014 | 3615 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 47.6 | 0.0 | 0.0 | 42.9 | 71.4 | 117.1 | 166.7 | 209.5 | 238.1 | 285.7 |
2015 | 3332 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 33.3 | 71.4 | 109.5 | 166.7 | 214.3 | 242.9 | 309.5 |
2016 | 11,864 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 65.7 | 0.0 | 0.0 | 38.1 | 71.4 | 114.3 | 165.2 | 213.3 | 238.1 | 285.7 |
2017 | 3054 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 28.6 | 63.8 | 103.8 | 157.6 | 204.8 | 233.7 | 285.7 |
2018 | 3080 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 33.3 | 71.4 | 104.8 | 155.2 | 206.4 | 238.1 | 285.7 |
2019 | 2630 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 23.8 | 60.0 | 96.6 | 152.4 | 200.0 | 228.6 | 285.7 |
Males | |||||||||||||||||||
2012 | 12,265 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 47.6 | 0.0 | 47.6 | 71.4 | 123.8 | 190.5 | 252.4 | 314.3 | 357.1 | 457.1 |
2013 | 2998 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 47.6 | 0.0 | 33.3 | 71.4 | 104.8 | 176.2 | 238.1 | 302.4 | 342.9 | 428.6 |
2014 | 3112 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 14.8 | 0.0 | 42.9 | 71.4 | 114.3 | 185.7 | 238.1 | 309.5 | 357.1 | 457.1 |
2015 | 2840 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 57.1 | 0.0 | 0.0 | 57.1 | 95.2 | 171.4 | 238.1 | 294.8 | 342.9 | 431.0 |
2016 | 9987 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 23.8 | 66.7 | 107.1 | 173.2 | 236.7 | 295.2 | 333.8 | 433.3 |
2017 | 2696 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 58.6 | 0.0 | 0.0 | 57.1 | 95.2 | 166.7 | 228.6 | 290.5 | 333.3 | 442.9 |
2018 | 2663 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 72.0 | 0.0 | 0.0 | 57.1 | 95.2 | 161.9 | 228.6 | 295.2 | 335.7 | 428.6 |
2019 | 2297 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 42.6 | 0.0 | 0.0 | 50.0 | 95.2 | 160.7 | 219.0 | 285.7 | 319.0 | 428.6 |
Year | Brown Rice | White Rice Only | Neither | ||
---|---|---|---|---|---|
Total | Brown Rice only | Combined with White Rice | |||
Both sexes | |||||
2012 | 1.8 (1.6, 2.0) | 0.7 (0.6, 0.9) | 1.1 (0.9, 1.3) | 94.0 (93.6, 94.4) | 4.2 (3.9, 4.5) |
2013 | 1.6 (1.3, 2.1) | 0.8 (0.6, 1.2) | 0.8 (0.6, 1.2) | 93.5 (92.7, 94.2) | 4.9 (4.3, 5.6) |
2014 | 1.6 (1.2, 2.0) | 0.6 (0.4, 0.8) | 1.0 (0.7, 1.4) | 93.7 (92.8, 94.4) | 4.8 (4.1, 5.5) |
2015 | 2.4 (1.9, 3.1) | 1.0 (0.7, 1.4) | 1.5 (1.1, 2.0) | 91.6 (90.5, 92.5) | 6.0 (5.2, 6.9) |
2016 | 2.3 (2.0, 2.6) | 0.8 (0.7, 1.0) | 1.4 (1.2, 1.7) | 92.6 (92.1, 93.0) | 5.2 (4.8, 5.6) |
2017 | 2.2 (1.7, 2.8) | 1.0 (0.7, 1.4) | 1.2 (0.9, 1.6) | 91.7 (90.8, 92.6) | 6.1 (5.4, 6.9) |
2018 | 2.6 (2.1, 3.2) | 1.0 (0.8, 1.4) | 1.5 (1.2, 2.1) | 91.4 (90.4, 92.4) | 6.0 (5.2, 6.9) |
2019 | 2.6 (2.0, 3.4) | 1.3 (0.9, 1.7) | 1.4 (1.0, 1.9) | 91.1 (89.9, 92.2) | 6.3 (5.5, 7.2) |
Females | |||||
2012 | 2.0 (1.8, 2.3) | 0.9 (0.7, 1.1) | 1.2 (1.0, 1.4) | 93.0 (92.5, 93.5) | 4.9 (4.5, 5.4) |
2013 | 1.8 (1.4, 2.4) | 1.0 (0.7, 1.4) | 0.8 (0.6, 1.2) | 92.3 (91.3, 93.2) | 5.9 (5.1, 6.8) |
2014 | 1.9 (1.5, 2.5) | 0.8 (0.5, 1.2) | 1.1 (0.7, 1.7) | 92.4 (91.2, 93.4) | 5.7 (4.8, 6.7) |
2015 | 2.6 (2.0, 3.2) | 1.1 (0.7, 1.5) | 1.5 (1.1, 2.0) | 90.5 (89.3, 91.7) | 6.9 (5.9, 8.0) |
2016 | 2.4 (2.1, 2.8) | 0.9 (0.8, 1.1) | 1.5 (1.3, 1.8) | 91.4 (90.8, 92.0) | 6.1 (5.6, 6.7) |
2017 | 2.5 (2.0, 3.2) | 1.3 (0.9, 1.8) | 1.2 (0.9, 1.8) | 90.4 (89.2, 91.5) | 7.1 (6.1, 8.1) |
2018 | 2.9 (2.3, 3.6) | 1.3 (0.9, 1.8) | 1.6 (1.2, 2.2) | 90.4 (89.1, 91.5) | 6.8 (5.8, 7.9) |
2019 | 3.2 (2.5, 4.1) | 1.6 (1.1, 2.3) | 1.6 (1.1, 2.2) | 89.4 (87.9, 90.7) | 7.4 (6.4, 8.6) |
Males | |||||
2012 | 1.5 (1.3, 1.8) | 0.5 (0.4, 0.7) | 1.0 (0.8, 1.2) | 95.1 (94.7, 95.6) | 3.3 (3.0, 3.7) |
2013 | 1.4 (1.1, 1.9) | 0.6 (0.4, 1.0) | 0.8 (0.5, 1.2) | 94.8 (93.9, 95.6) | 3.7 (3.1, 4.5) |
2014 | 1.2 (0.9, 1.7) | 0.3 (0.2, 0.6) | 0.9 (0.6, 1.3) | 95.1 (94.2, 95.9) | 3.7 (3.0, 4.5) |
2015 | 2.3 (1.7, 3.1) | 0.9 (0.6, 1.4) | 1.4 (1.0, 2.0) | 92.8 (91.6, 93.8) | 4.9 (4.1, 5.9) |
2016 | 2.1 (1.8, 2.4) | 0.7 (0.6, 0.9) | 1.4 (1.1, 1.6) | 93.9 (93.3, 94.5) | 4.0 (3.6, 4.5) |
2017 | 1.8 (1.3, 2.4) | 0.6 (0.4, 1.0) | 1.1 (0.8, 1.7) | 93.2 (92.1, 94.2) | 5.0 (4.2, 5.9) |
2018 | 2.3 (1.7, 3.0) | 0.8 (0.5, 1.2) | 1.5 (1.0, 2.2) | 92.7 (91.5, 93.7) | 5.1 (4.2, 6.1) |
2019 | 2.0 (1.4, 2.7) | 0.9 (0.6, 1.4) | 1.1 (0.7, 1.7) | 93.1 (91.8, 94.1) | 5.0 (4.1, 5.9) |
Females | Males | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Brown Rice | White Rice Only | p-Value a | Brown Rice | White Rice Only | p-Value a | |||||
Total energy, kcal | 1745.7 | (26.9) | 1692.5 | (5.1) | 0.049 | 2161.1 | (40.8) | 2117.4 | (6.9) | 0.288 |
Water, g | 1604.6 | (33.6) | 1479.7 | (7.5) | <0.001 | 1796.3 | (47.9) | 1723.6 | (8.9) | 0.139 |
Total protein, g | 69.0 | (1.2) | 63.9 | (0.3) | <0.001 | 82.8 | (1.9) | 76.2 | (0.3) | <0.001 |
Animal-based protein, g | 35.4 | (1.0) | 34.1 | (0.2) | 0.201 | 43.8 | (1.5) | 41.5 | (0.3) | 0.135 |
Plant-based protein, g | 33.6 | (0.6) | 29.7 | (0.1) | <0.001 | 39.1 | (0.9) | 34.8 | (0.1) | <0.001 |
Total fat, g | 54.8 | (1.4) | 51.7 | (0.3) | 0.029 | 66.4 | (1.9) | 60.6 | (0.3) | 0.002 |
Animal-based fat, g | 24.9 | (0.9) | 25.7 | (0.2) | 0.344 | 33.1 | (1.5) | 31.1 | (0.2) | 0.181 |
Plant-based fat, g | 30.0 | (1.0) | 26.0 | (0.2) | <0.001 | 33.2 | (1.2) | 29.4 | (0.2) | 0.001 |
Saturated fatty acids, g | 14.2 | (0.4) | 14.0 | (0.1) | 0.552 | 17.2 | (0.6) | 15.9 | (0.1) | 0.024 |
Monounsaturated fatty acids, g | 18.5 | (0.6) | 17.5 | (0.1) | 0.101 | 23.1 | (0.7) | 21.1 | (0.1) | 0.007 |
Polyunsaturated fatty acids, g | 12.5 | (0.3) | 11.1 | (0.1) | <0.001 | 14.8 | (0.5) | 13.2 | (0.1) | 0.001 |
Omega-3 fatty acids, g | 2.2 | (0.1) | 2.1 | (0.0) | 0.302 | 2.6 | (0.1) | 2.5 | (0.0) | 0.525 |
Omega-6 fatty acids, g | 10.1 | (0.3) | 8.8 | (0.0) | <0.001 | 12.0 | (0.4) | 10.5 | (0.1) | <0.001 |
Cholesterol, mg | 305.5 | (10.0) | 290.1 | (1.8) | 0.127 | 376.0 | (16.7) | 344.2 | (2.2) | 0.061 |
Carbohydrates, g | 238.9 | (4.1) | 234.3 | (0.7) | 0.269 | 285.4 | (6.3) | 286.7 | (1.0) | 0.848 |
Total dietary fiber, g | 19.5 | (0.5) | 14.3 | (0.1) | <0.001 | 21.3 | (0.6) | 15.0 | (0.1) | <0.001 |
Soluble dietary fiber, g | 4.5 | (0.1) | 3.3 | (0.0) | <0.001 | 4.8 | (0.2) | 3.4 | (0.0) | <0.001 |
Insoluble dietary fiber, g | 14.3 | (0.3) | 10.5 | (0.1) | <0.001 | 15.7 | (0.5) | 11.0 | (0.1) | <0.001 |
Vitamins | ||||||||||
Vitamin A, mcg RAE | 642.9 | (33.0) | 502.1 | (8.3) | <0.001 | 710.7 | (57.8) | 538.8 | (9.8) | 0.004 |
Vitamin D, mcg | 9.3 | (0.6) | 7.6 | (0.1) | 0.004 | 9.1 | (0.7) | 8.4 | (0.1) | 0.254 |
Vitamin E, mg | 8.0 | (0.2) | 6.3 | (0.0) | <0.001 | 8.7 | (0.3) | 6.8 | (0.0) | <0.001 |
Vitamin K, mcg | 303.1 | (13.6) | 228.6 | (2.1) | <0.001 | 347.4 | (19.0) | 247.3 | (2.5) | <0.001 |
Vitamin B1, mg | 1.0 | (0.0) | 0.8 | (0.0) | <0.001 | 1.3 | (0.0) | 0.9 | (0.0) | <0.001 |
Vitamin B2, mg | 1.2 | (0.0) | 1.1 | (0.0) | <0.001 | 1.4 | (0.0) | 1.2 | (0.0) | <0.001 |
Niacin equivalents, mg | 18.6 | (0.4) | 13.5 | (0.1) | <0.001 | 22.6 | (0.7) | 16.5 | (0.1) | <0.001 |
Vitamin B6, mg | 1.5 | (0.0) | 1.1 | (0.0) | <0.001 | 1.8 | (0.1) | 1.2 | (0.0) | <0.001 |
Vitamin B12, mcg | 6.7 | (0.4) | 5.8 | (0.1) | 0.030 | 8.2 | (0.6) | 7.0 | (0.1) | 0.043 |
Folate, mcg | 337.1 | (8.2) | 282.8 | (1.9) | <0.001 | 365.9 | (11.9) | 300.3 | (2.1) | <0.001 |
Pantothenic acid, mg | 6.3 | (0.1) | 5.1 | (0.0) | <0.001 | 7.4 | (0.2) | 5.8 | (0.0) | <0.001 |
Vitamin C, mg | 120.5 | (4.8) | 97.6 | (1.0) | <0.001 | 116.5 | (5.8) | 93.4 | (1.0) | <0.001 |
Minerals | ||||||||||
Sodium, mg | 3652.3 | (88.5) | 3630.0 | (17.0) | 0.805 | 4279.0 | (121.9) | 4273.9 | (21.3) | 0.967 |
Potassium, mg | 2704.3 | (55.4) | 2206.1 | (11.0) | <0.001 | 2960.0 | (81.8) | 2366.5 | (12.0) | <0.001 |
Calcium, mg | 580.6 | (15.2) | 491.2 | (2.9) | <0.001 | 621.5 | (20.9) | 502.5 | (3.2) | <0.001 |
Magnesium, mg | 332.6 | (6.6) | 231.3 | (1.0) | <0.001 | 386.2 | (10.2) | 260.2 | (1.2) | <0.001 |
Phosphorus, mg | 1147.3 | (20.4) | 918.7 | (3.8) | <0.001 | 1352.2 | (29.9) | 1054.3 | (4.4) | <0.001 |
Iron, mg | 9.2 | (0.2) | 7.3 | (0.0) | <0.001 | 10.4 | (0.3) | 8.1 | (0.0) | <0.001 |
Zinc, mg | 8.1 | (0.1) | 7.3 | (0.0) | <0.001 | 9.9 | (0.2) | 8.9 | (0.0) | <0.001 |
Copper, mg | 1.3 | (0.0) | 1.1 | (0.0) | <0.001 | 1.4 | (0.0) | 1.3 | (0.0) | <0.001 |
Characteristics | n | Bown Rice Consumers, n (%) | Odds Ratio (95% Confidence Interval) |
---|---|---|---|
Total | 31,675 | 721 (2.3) | |
Sociodemographic characteristics | |||
Sex | |||
Females | 16,754 | 437 (2.6) | 1.17 (1.00, 1.35) |
Males | 14,921 | 284 (1.9) | Reference |
Age | |||
20–29 years | 2267 | 37 (1.6) | Reference |
30–39 years | 3497 | 64 (1.8) | 1.45 (0.92, 2.28) |
40–49 years | 4969 | 95 (1.9) | 1.32 (0.85, 2.04) |
50–59 years | 4881 | 127 (2.6) | 1.76 (1.22, 2.56) |
60–69 years | 6949 | 185 (2.7) | 1.87 (1.23, 2.85) |
70–79 years | 6103 | 164 (2.7) | 1.85 (1.19, 2.87) |
≥80 years | 3009 | 49 (1.6) | 1.19 (0.71, 1.98) |
Municipality of residence | |||
12 major cities | 6196 | 185 (3.0) | 1.36 (1.07, 1.72) |
Other cities | 21,843 | 463 (2.1) | Reference |
Towns/villages | 3636 | 73 (2.0) | 1.03 (0.74, 1.44) |
Households without children aged <6 years | |||
Not applicable | 3035 | 38 (1.3) | Reference |
Applicable | 28,640 | 683 (2.4) | 1.91 (1.22, 2.99) |
Educational background | |||
Elementary/junior high school | 4629 | 74 (1.6) | Reference |
Senior high school | 12,853 | 249 (1.9) | 1.19 (0.87, 1.63) |
Junior/career college | 5406 | 164 (3.0) | 1.90 (1.34, 2.70) |
University/graduate school | 6488 | 199 (3.1) | 2.13 (1.49, 3.04) |
Unknown | 2299 | 35 (1.5) | 0.90 (0.55, 1.47) |
Health behaviors | |||
Body mass index | |||
<18.5 kg/m2 | 2045 | 58 (2.8) | 1.71 (1.21, 2.41) |
18.5 to <25.0 kg/m2 | 17,487 | 451 (2.6) | 1.52 (1.20, 1.92) |
25.0 to <30.0 kg/m2 | 5556 | 92 (1.7) | Reference |
≥30.0 kg/m2 | 1053 | 16 (1.5) | 0.96 (0.55, 1.68) |
Missing | 5534 | 104 (1.9) | 1.48 (1.02, 2.15) |
Regular exercise habit | |||
Absent | 13,241 | 289 (2.2) | Reference |
Present | 5434 | 191 (3.5) | 1.46 (1.19, 1.79) |
Missing | 13,000 | 241 (1.9) | 0.83 (0.65, 1.07) |
Smoking status | |||
Former/never smoker | 25,100 | 668 (2.7) | 2.74 (1.96, 3.82) |
Daily/occasional smoker | 5472 | 44 (0.8) | Reference |
Missing | 382 | 9 (2.4) | 4.56 (1.90, 10.92) |
Alcohol consumption | |||
Non-drinker | 24,984 | 598 (2.4) | 1.14 (0.92, 1.42) |
Drinker | 6199 | 114 (1.8) | Reference |
Missing | 492 | 9 (1.8) | 0.72 (0.31, 1.66) |
Survey year | |||
2013 | 5818 | 103 (1.8) | Reference |
2014 | 6098 | 102 (1.7) | 0.92 (0.64, 1.33) |
2015 | 5502 | 144 (2.6) | 1.39 (0.98, 1.98) |
2017 | 4966 | 113 (2.3) | 1.23 (0.86, 1.77) |
2018 | 4956 | 137 (2.8) | 1.51 (1.07, 2.14) |
2019 | 4335 | 122 (2.8) | 1.57 (1.10, 2.23) |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ikeda, N.; Yamaguchi, M.; Nishi, N. Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019. Nutrients 2024, 16, 1473. https://doi.org/10.3390/nu16101473
Ikeda N, Yamaguchi M, Nishi N. Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019. Nutrients. 2024; 16(10):1473. https://doi.org/10.3390/nu16101473
Chicago/Turabian StyleIkeda, Nayu, Miwa Yamaguchi, and Nobuo Nishi. 2024. "Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019" Nutrients 16, no. 10: 1473. https://doi.org/10.3390/nu16101473
APA StyleIkeda, N., Yamaguchi, M., & Nishi, N. (2024). Trends and Characteristics of Brown Rice Consumption among Adults in Japan: An Analysis of the National Health and Nutrition Surveys, 2012–2019. Nutrients, 16(10), 1473. https://doi.org/10.3390/nu16101473