Submitted:
02 May 2024
Posted:
02 May 2024
You are already at the latest version
Abstract
Keywords:
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
Supplementary Materials
Funding
Declaration of interests
Authorship
Acknowledgments
References
- FAO and WHO. Sustainable healthy diets – Guiding principles; FAO and WHO: Rome, 2019.
- 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.
- 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. [CrossRef]
- 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. [CrossRef]
- 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. [CrossRef]
- 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. [CrossRef]
- 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.
- 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. [CrossRef]
- Yoshiike, N.; Hayashi, F.; Takemi, Y.; Mizoguchi, K.; Seino, F. A New Food Guide in Japan: The Japanese Food Guide Spinning Top. Nutrition Reviews. 2007, 65, 149-154.
- 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 April 15, 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. [CrossRef]
- 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. [CrossRef]
- 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. Ecology of Food and Nutrition. 2015, 54, 224-239. [CrossRef]
- 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. [CrossRef]
- 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. The American Journal of Clinical Nutrition. 2010, 92, 1468-1477. [CrossRef]
- 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. Applied Physiology, Nutrition, and Metabolism. 2019, 44, 528-532. [CrossRef]
- 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 March 12, 2024).
- Government of Japan. Statistics Act. 2007. Available online: https://www.japaneselawtranslation.go.jp/ja/laws/view/148 (accessed on March 12, 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 March 12, 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. [CrossRef]
- Ministry of Education, Culture, Sports, Science, and Technology, Standard tables of food composition in Japan - 2010 -. 2010.
- 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 March 12, 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.
- Korczak, R.; Slavin, J.L. Definitions, regulations, and new frontiers for dietary fiber and whole grains. Nutrition Reviews. 2020, 78, 6-12. [CrossRef]
- Miller, K.B. Review of whole grain and dietary fiber recommendations and intake levels in different countries. Nutrition Reviews. 2020, 78, 29-36. [CrossRef]
- 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. [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. [CrossRef]
- 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 March 28, 2024).
- Adebamowo, S.N.; Eseyin, O.; Yilme, S.; Adeyemi, D.; Willett, W.C.; Hu, F.B.; Spiegelman, D.; Adebamowo, C.A.; , T.G.N.E.T.I. A Mixed-Methods Study on Acceptability, Tolerability, and Substitution of Brown Rice for White Rice to Lower Blood Glucose Levels among Nigerian Adults. Frontiers in Nutrition. 2017, 4.
- 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. [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. [CrossRef]
- Gyawali, P.; Tamrakar, D.; Shrestha, A.; Shrestha, H.; Karmacharya, S.; Bhattarai, S.; Bhandari, N.; Malik, V.; Mattei, J.; Spiegelman, D.; Shrestha, A. Consumer acceptance and preference for brown rice-A mixed-method qualitative study from Nepal. Food Sci Nutr. 2022, 10, 1864-1874. [CrossRef]
- 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. [CrossRef]
- Muhihi, A.; Gimbi, D.; Njelekela, M.; Shemaghembe, E.; Mwambene, K.; Chiwanga, F.; Malik, V.S.; Wedick, N.M.; Spiegelman, D.; Hu, F.B.; Willett, W.C. Consumption and acceptability of whole grain staples for lowering markers of diabetes risk among overweight and obese Tanzanian adults. Globalization and Health. 2013, 9, 26. [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. Journal of the American College of Nutrition. 2013, 32, 50-57. [CrossRef]
- 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. Journal of the American Dietetic Association. 2010, 110, 1216-1221. [CrossRef]
- 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. [CrossRef]
- 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 March 27, 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 March 27, 2024).

| 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 | 16.0 | 51.4 | 95.2 | 151.0 | 214.3 | 285.7 | 314.3 | 417.1 |
| 2013 | 6,481 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 57.1 | 0.0 | 0.0 | 47.6 | 89.0 | 142.9 | 198.1 | 266.7 | 304.2 | 402.9 |
| 2014 | 6,727 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 42.4 | 0.0 | 0.0 | 47.6 | 95.2 | 142.9 | 200.0 | 266.7 | 309.5 | 419.0 |
| 2015 | 6,172 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 45.6 | 81.0 | 138.8 | 190.5 | 261.9 | 297.6 | 400.0 |
| 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 | 193.8 | 261.9 | 295.2 | 393.3 |
| 2017 | 5,750 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 41.7 | 76.2 | 133.3 | 190.5 | 257.1 | 291.4 | 392.9 |
| 2018 | 5,743 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 42.9 | 81.0 | 133.3 | 190.5 | 261.0 | 295.2 | 397.6 |
| 2019 | 4,927 | 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 | 247.6 | 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 | 77.1 | 128.6 | 176.2 | 226.7 | 259.8 | 309.5 |
| 2013 | 3,483 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 66.7 | 0.0 | 0.0 | 42.9 | 71.4 | 116.7 | 166.7 | 214.3 | 247.6 | 290.5 |
| 2014 | 3,615 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 47.6 | 0.0 | 0.0 | 45.0 | 71.4 | 118.6 | 166.7 | 209.5 | 238.1 | 285.7 |
| 2015 | 3,332 | 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 | 111.1 | 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 | 166.5 | 214.3 | 238.1 | 285.7 |
| 2017 | 3,054 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 0.0 | 28.6 | 64.3 | 104.0 | 158.6 | 204.8 | 234.3 | 285.7 |
| 2018 | 3,080 | 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 | 156.0 | 207.1 | 238.1 | 285.7 |
| 2019 | 2,630 | 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 | 97.6 | 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 | 358.6 | 457.1 |
| 2013 | 2,998 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 47.6 | 0.0 | 38.1 | 71.4 | 104.8 | 176.2 | 238.1 | 303.8 | 342.9 | 428.6 |
| 2014 | 3,112 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 14.8 | 0.0 | 47.6 | 71.4 | 114.3 | 185.7 | 238.1 | 309.5 | 357.1 | 457.1 |
| 2015 | 2,840 | 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 | 295.2 | 342.9 | 433.3 |
| 2016 | 9,987 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 71.4 | 0.0 | 25.0 | 67.5 | 108.6 | 173.8 | 238.1 | 295.2 | 335.7 | 433.3 |
| 2017 | 2,696 | 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 | 2,663 | 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 | 164.3 | 228.6 | 295.2 | 336.7 | 428.6 |
| 2019 | 2,297 | 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 | 161.9 | 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, 2.1) | 0.7 (0.6, 0.9) | 1.1 (0.9, 1.3) | 94.1 (93.6, 94.5) | 4.1 (3.8, 4.5) |
| 2013 | 1.7 (1.3, 2.2) | 0.8 (0.5, 1.2) | 0.8 (0.6, 1.2) | 93.7 (92.9, 94.4) | 4.7 (4.1, 5.4) |
| 2014 | 1.6 (1.2, 2.1) | 0.6 (0.4, 0.8) | 1.0 (0.7, 1.4) | 93.8 (93.0, 94.6) | 4.6 (4.0, 5.3) |
| 2015 | 2.4 (1.9, 3.1) | 1.0 (0.7, 1.4) | 1.5 (1.1, 2.0) | 91.7 (90.6, 92.7) | 5.9 (5.1, 6.8) |
| 2016 | 2.3 (2.1, 2.6) | 0.8 (0.7, 1.0) | 1.4 (1.2, 1.7) | 92.7 (92.2, 93.2) | 5.0 (4.7, 5.5) |
| 2017 | 2.2 (1.8, 2.8) | 1.0 (0.7, 1.3) | 1.2 (0.9, 1.6) | 91.7 (90.8, 92.6) | 6.1 (5.4, 6.9) |
| 2018 | 2.4 (1.9, 2.9) | 1.0 (0.8, 1.4) | 1.5 (1.2, 2.1) | 91.6 (90.6, 92.5) | 5.8 (5.0, 6.7) |
| 2019 | 2.3 (1.8, 3.0) | 1.3 (0.9, 1.7) | 1.4 (1.0, 1.9) | 91.2 (89.9, 92.2) | 6.2 (5.4, 7.1) |
| Females | |||||
| 2012 | 2.1 (1.8, 2.4) | 0.9 (0.7, 1.0) | 1.2 (1.0, 1.4) | 93.1 (92.5, 93.6) | 4.9 (4.5, 5.3) |
| 2013 | 1.9 (1.4, 2.5) | 0.9 (0.6, 1.4) | 0.9 (0.6, 1.2) | 92.5 (91.5, 93.4) | 5.7 (4.9, 6.6) |
| 2014 | 1.9 (1.5, 2.5) | 0.8 (0.5, 1.2) | 1.1 (0.7, 1.7) | 92.7 (91.5, 93.7) | 5.4 (4.6, 6.4) |
| 2015 | 2.6 (2.0, 3.2) | 1.1 (0.7, 1.5) | 1.5 (1.1, 2.0) | 90.7 (89.4, 91.8) | 6.8 (5.8, 7.9) |
| 2016 | 2.5 (2.2, 2.8) | 0.9 (0.8, 1.1) | 1.5 (1.3, 1.8) | 91.6 (90.9, 92.1) | 6.0 (5.5, 6.6) |
| 2017 | 2.6 (2.1, 3.3) | 1.2 (0.9, 1.7) | 1.3 (0.9, 1.8) | 90.4 (89.2, 91.5) | 7.1 (6.1, 8.1) |
| 2018 | 2.6 (2.1, 3.3) | 1.3 (0.9, 1.8) | 1.6 (1.2, 2.2) | 90.6 (89.4, 91.7) | 6.5 (5.6, 7.6) |
| 2019 | 2.8 (2.1, 3.6) | 1.6 (1.1, 2.3) | 1.6 (1.1, 2.2) | 89.4 (87.9, 90.8) | 7.4 (6.3, 8.6) |
| Males | |||||
| 2012 | 1.5 (1.3, 1.8) | 0.5 (0.4, 0.7) | 1.0 (0.8, 1.2) | 95.2 (94.8, 95.6) | 3.3 (2.9, 3.6) |
| 2013 | 1.5 (1.1, 2.0) | 0.6 (0.4, 1.0) | 0.8 (0.5, 1.2) | 95.0 (94.1, 95.8) | 3.5 (2.9, 4.3) |
| 2014 | 1.2 (0.9, 1.7) | 0.3 (0.2, 0.6) | 0.9 (0.6, 1.3) | 95.2 (94.3, 95.9) | 3.6 (3.0, 4.4) |
| 2015 | 2.3 (1.7, 3.1) | 0.9 (0.6, 1.4) | 1.4 (1.0, 2.0) | 92.9 (91.7, 93.9) | 4.8 (4.0, 5.8) |
| 2016 | 2.1 (1.8, 2.5) | 0.7 (0.6, 0.9) | 1.4 (1.1, 1.6) | 94.0 (93.4, 94.5) | 3.9 (3.5, 4.4) |
| 2017 | 1.8 (1.3, 2.5) | 0.6 (0.4, 1.0) | 1.1 (0.8, 1.7) | 93.2 (92.2, 94.2) | 5.0 (4.2, 5.9) |
| 2018 | 2.1 (1.6, 2.8) | 0.8 (0.5, 1.2) | 1.5 (1.0, 2.2) | 92.8 (91.6, 93.8) | 5.0 (4.1, 5.9) |
| 2019 | 1.8 (1.3, 2.5) | 0.9 (0.6, 1.4) | 1.1 (0.7, 1.7) | 93.1 (91.9, 94.2) | 4.9 (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 | 1,745.7 | (26.9) | 1,692.5 | (5.1) | 0.049 | 2,161.1 | (40.8) | 2,117.4 | (6.9) | 0.288 |
| Water, g | 1,604.6 | (33.6) | 1,479.7 | (7.5) | < 0.001 | 1,796.3 | (47.9) | 1,723.6 | (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 | 3,652.3 | (88.5) | 3,630.0 | (17.0) | 0.805 | 4,279.0 | (121.9) | 4,273.9 | (21.3) | 0.967 |
| Potassium, mg | 2,704.3 | (55.4) | 2,206.1 | (11.0) | < 0.001 | 2,960.0 | (81.8) | 2,366.5 | (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 | 1,147.3 | (20.4) | 918.7 | (3.8) | < 0.001 | 1,352.2 | (29.9) | 1,054.3 | (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 | 2,267 | 37 (1.6) | Reference |
| 30–39 years | 3,497 | 64 (1.8) | 1.45 (0.92, 2.28) |
| 40–49 years | 4,969 | 95 (1.9) | 1.32 (0.85, 2.04) |
| 50–59 years | 4,881 | 127 (2.6) | 1.76 (1.22, 2.56) |
| 60–69 years | 6,949 | 185 (2.7) | 1.87 (1.23, 2.85) |
| 70–79 years | 6,103 | 164 (2.7) | 1.85 (1.19, 2.87) |
| ≥ 80 years | 3,009 | 49 (1.6) | 1.19 (0.71, 1.98) |
| Municipality of residence | |||
| 12 major cities | 6,196 | 185 (3.0) | 1.36 (1.07, 1.72) |
| Other cities | 21,843 | 463 (2.1) | Reference |
| Towns/villages | 3,636 | 73 (2.0) | 1.03 (0.74, 1.44) |
| Households without children aged < 6 years | |||
| Not applicable | 3,035 | 38 (1.3) | Reference |
| Applicable | 28,640 | 683 (2.4) | 1.91 (1.22, 2.99) |
| Educational background | |||
| Elementary/junior high school | 4,629 | 74 (1.6) | Reference |
| Senior high school | 12,853 | 249 (1.9) | 1.19 (0.87, 1.63) |
| Junior/career college | 5,406 | 164 (3.0) | 1.90 (1.34, 2.70) |
| University/graduate school | 6,488 | 199 (3.1) | 2.13 (1.49, 3.04) |
| Unknown | 2,299 | 35 (1.5) | 0.90 (0.55, 1.47) |
| Health behaviors | |||
| Body mass index | |||
| < 18.5 kg/m2 | 2,045 | 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 | 5,556 | 92 (1.7) | Reference |
| ≥ 30.0 kg/m2 | 1,053 | 16 (1.5) | 0.96 (0.55, 1.68) |
| Missing | 5,534 | 104 (1.9) | 1.48 (1.02, 2.15) |
| Regular exercise habit | |||
| Absent | 13,241 | 289 (2.2) | Reference |
| Present | 5,434 | 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 | 5,472 | 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 | 6,199 | 114 (1.8) | Reference |
| Missing | 492 | 9 (1.8) | 0.72 (0.31, 1.66) |
| Survey year | |||
| 2013 | 5,818 | 103 (1.8) | Reference |
| 2014 | 6,098 | 102 (1.7) | 0.92 (0.64, 1.33) |
| 2015 | 5,502 | 144 (2.6) | 1.39 (0.98, 1.98) |
| 2017 | 4,966 | 113 (2.3) | 1.23 (0.86, 1.77) |
| 2018 | 4,956 | 137 (2.8) | 1.51 (1.07, 2.14) |
| 2019 | 4,335 | 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 (http://creativecommons.org/licenses/by/4.0/).
