Advertisement

European Journal of Nutrition

, Volume 58, Issue 8, pp 3349–3360 | Cite as

Rice intake and risk of type 2 diabetes: the Singapore Chinese Health Study

  • Jowy Y. H. Seah
  • Woon-Puay KohEmail author
  • Jian-Min Yuan
  • Rob M. van DamEmail author
Original Contribution

Abstract

Purpose

The prevalence of type 2 diabetes (T2D) is increasing in Asian populations. White rice is a common staple food in these populations and results from several studies suggest that high white rice consumption increases T2D risk. We assessed whether rice, noodles and bread intake was associated with T2D risk in an ethnic Chinese population.

Methods

We included data from 45,411 male and female Chinese participants of the Singapore Chinese Health Study cohort aged 45–74 years at baseline. Usual diet at baseline was evaluated by a validated 165-item semi-quantitative food frequency questionnaire. Physician-diagnosed T2D was self-reported during two follow-up interviews. Multivariable Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

During a mean follow-up of 11 years, 5207 incident cases of T2D were documented. Rice intake was not associated with higher T2D risk [HR for extreme quintiles, 0.98 (95% CI 0.90, 1.08)] despite the large variation in intake levels (median intake for extreme quintiles: 236.5 g/day vs. 649.3 g/day), although the precise risk estimate depended greatly on the substitute food. Replacing one daily serving of rice with noodles [HR 1.14 (95% CI 1.07, 1.22)], red meat [HR 1.40 (95% CI 1.23, 1.60)] and poultry [HR 1.37 (95% CI 1.18, 1.59)] was associated with higher T2D risk, whereas the replacement of rice with white bread [HR 0.90 (95% CI 0.85, 0.94)] or wholemeal bread [HR 0.82 (95% CI 0.75, 0.90)] was associated with lower T2D risk.

Conclusions

Higher rice consumption was not substantially associated with a higher risk of T2D in this Chinese population. Recommendations to reduce high white rice consumption in Asian populations for the prevention of T2D may only be effective if substitute foods are considered carefully.

Clinical Trial Registry number and website

NCT03356340, http://www.clinicaltrials.gov.

Keywords

Rice Noodles Bread Type 2 diabetes Grains Refined grains 

Abbreviations

T2D

Type 2 diabetes mellitus

HR

Hazard ratio

CI

Confidence interval

GI

Glycemic index

GL

Glycemic load

Notes

Acknowledgements

We are grateful to Siew-Hong Low of the National University of Singapore for supervising the fieldwork in the Singapore Chinese Health Study and Renwei Wang for the maintenance of the cohort study database. We also thank the founding principal investigator of the Singapore Chinese Health Study, Mimi C. Yu.

Author contributions

The authors’ responsibilities were as follows—JYHS: performed statistical analysis, wrote paper and had primary responsibility for final content; W-PK and RMvD: developed the analytical plan, co-wrote and reviewed the manuscript, and directed the work; all authors: reviewed and edited the manuscript and approved the final version of the manuscript.

Funding

This study was supported by the National Institutes of Health, USA (R01 CA144034 and UM1 CA182876). JYHS is supported by the NGS Scholarship. W-PK is supported by the National Medical Research Council, Singapore (NMRC/CSA/0055/2013).

Compliance with ethical standards

Conflict of interest

All authors have no conflicts of interest.

Supplementary material

394_2018_1879_MOESM1_ESM.docx (40 kb)
Supplementary material 1 (DOCX 39 KB)

References

  1. 1.
    Shaw JE, Sicree RA, Zimmet PZ (2010) Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract 87(1):4–14.  https://doi.org/10.1016/j.diabres.2009.10.007 CrossRefPubMedGoogle Scholar
  2. 2.
    Chan JCN, Malik V, Jia WP, Kadowaki T, Yajnik CS, Yoon KH, Hu FB (2009) Diabetes in Asia epidemiology, risk factors, and pathophysiology. J Am Med Assoc 301(20):2129–2140CrossRefGoogle Scholar
  3. 3.
    Ogurtsova K, Fernandes J, Huang Y, Linnenkamp U, Guariguata L, Cho NH, Cavan D, Shaw JE, Makaroff LE (2017) IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract 128:40–50.  https://doi.org/10.1016/j.diabres.2017.03.024 CrossRefPubMedGoogle Scholar
  4. 4.
    Woodward M, Zhang X, Barzi F, Pan W, Ueshima H, Rodgers A, MacMahon S (2003) The effects of diabetes on the risks of major cardiovascular diseases and death in the Asia-Pacific region. Diabetes Care 26(2):360–366CrossRefGoogle Scholar
  5. 5.
    Parving HH, Lewis JB, Ravid M, Remuzzi G, Hunsicker LG, Investigators D (2006) Prevalence and risk factors for microalbuminuria in a referred cohort of type II diabetic patients: a global perspective. Kidney Int 69(11):2057–2063.  https://doi.org/10.1038/sj.ki.5000377 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Barone BB, Yeh HC, Snyder CF, Peairs KS, Stein KB, Derr RL, Wolff AC, Brancati FL (2008) Long-term all-cause mortality in cancer patients with preexisting diabetes mellitus a systematic review and meta-analysis. J Am Med Assoc 300(23):2754–2764CrossRefGoogle Scholar
  7. 7.
    Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P, Son HY (2006) Epidemic obesity and type 2 diabetes in Asia. Lancet 368(9548):1681–1688.  https://doi.org/10.1016/s0140-6736(06)69703-1 CrossRefPubMedGoogle Scholar
  8. 8.
    Willi C, Bodenmann P, Ghali WA, Faris PD, Cornuz J (2007) Active smoking and the risk of type 2 diabetes—a systematic review and meta-analysis. J Am Med Assoc 298(22):2654–2664.  https://doi.org/10.1001/jama.298.22.2654 CrossRefGoogle Scholar
  9. 9.
    Muthayya S, Sugimoto JD, Montgomery S, Maberly GF (2014) An overview of global rice production, supply, trade, and consumption. Tech Consider Rice Fortificat Public Health 1324:7–14.  https://doi.org/10.1111/nyas.12540 CrossRefGoogle Scholar
  10. 10.
    Slavin JL, Martini MC, Jacobs DR, Marquart L (1999) Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nutr 70(3):459S–463SCrossRefGoogle Scholar
  11. 11.
    Atkinson FS, Foster-Powell K, Brand-Miller JC (2008) International tables of Glycemic Index and glycemic load values: 2008. Diabetes Care 31(12):2281–2283.  https://doi.org/10.2337/dc08-1239 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Larsen HN, Rasmussen OW, Rasmussen PH, Alstrup KK, Biswas SK, Tetens I, Thilsted SH, Hermansen K (2000) Glycaemic index of parboiled rice depends on the severity of processing: study in type 2 diabetic subjects. Eur J Clin Nutr 54(5):380–385.  https://doi.org/10.1038/sj.ejcn.1600969 CrossRefPubMedGoogle Scholar
  13. 13.
    Miller JB, Pang E, Bramall L (1992) Rice—a high or low Glycemic Index food. Am J Clin Nutr 56(6):1034–1036CrossRefGoogle Scholar
  14. 14.
    Sluijs I, Beulens JWJ, van der Schouw YT, van der ADL, Buckland, Kuijsten G, Schulze A, Amiano MB, Ardanaz P, Balkau E, Boeing B, Gavrila H, Grote D, Key VA, Li TJ, Nilsson KR, Overvad P, Palli K, Panico D, Quiros S, Rolandsson JR, Roswall O, Sacerdote N, Sanchez C, Sieri MJ, Slimani S, Spijkerman N, Tjonneland AMW, Tumino A, Sharp R, Langenberg SJ, Feskens C, Forouhi EJM, Riboli NG, Wareham E, InterAct NJ (2013) Dietary Glycemic Index, glycemic load, and digestible carbohydrate intake are not associated with risk of type 2 diabetes in eight European Countries. J Nutr 143(1):93–99.  https://doi.org/10.3945/jn.112.165605 CrossRefPubMedGoogle Scholar
  15. 15.
    Barclay AW, Petocz P, McMillan-Price J, Flood VM, Prvan T, Mitchell P, Brand-Miller JC (2008) Glycemic index, glycemic load, and chronic disease risk—a metaanalysis of observational studies. Am J Clin Nutr 87(3):627–637CrossRefGoogle Scholar
  16. 16.
    Mohan V, Radhika G, Sathya RM, Tamil SR, Ganesan A, Sudha V (2009) Dietary carbohydrates glycaemic load, food groups and newly detected type 2 diabetes among urban Asian Indian population in Chennai, India (Chennai Urban Rural Epidemiology Study 59). Br J Nutr 102(10):1498–1506.  https://doi.org/10.1017/s0007114509990468 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Sun Q, Spiegelman D, van Dam RM, Holmes MD, Malik VS, Willett WC, Hu FB (2010) White rice, brown rice, and risk of type 2 diabetes in US men and women. Arch Intern Med 170(11):961–969CrossRefGoogle Scholar
  18. 18.
    Villegas R, Liu SM, Gao YT, Yang G, Li HL, Zheng W, Shu XO (2007) Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2, diabetes mellitus in middle-aged Chinese women. Arch Intern Med 167(21):2310–2316.  https://doi.org/10.1001/archinte.167.21.2310 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Aune D, Norat T, Romundstad P, Vatten LJ (2013) Whole grain and refined grain consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. Eur J Epidemiol 28(11):845–858.  https://doi.org/10.1007/s10654-013-9852-5 CrossRefPubMedGoogle Scholar
  20. 20.
    Nanri A, Mizoue T, Noda M, Takahashi Y, Kato M, Inoue M, Tsugane S (2010) Rice intake and type 2 diabetes in Japanese men and women the Japan Public Health Center-based Prospective Study. Am J Clin Nutr 92(6):1468–1477.  https://doi.org/10.3945/ajcn.2010.29512 CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Hodge AM, English DR, O’Dea K, Giles GG (2004) Glycemic index and dietary fiber and the risk of type 2 diabetes. Diabetes Care 27(11):2701–2706.  https://doi.org/10.2337/diacare.27.11.2701 CrossRefPubMedGoogle Scholar
  22. 22.
    Hu EA, Pan A, Malik V, Sun Q (2012) White rice consumption and risk of type 2 diabetes: meta-analysis and systematic review. BMJ 344.  https://doi.org/10.1136/bmj.e1454 CrossRefGoogle Scholar
  23. 23.
    Yuan JM, Stram DO, Arakawa K, Lee HP, Yu MC (2003) Dietary cryptoxanthin and reduced risk of lung cancer: The Singapore Chinese health study. Cancer Epidemiol Biomark Prevent 12(9):890–898Google Scholar
  24. 24.
    Hankin JH, Stram DO, Arakawa K, Park S, Low SH, Lee HP, Yu MC (2001) Singapore Chinese Health Study: development, validation, and calibration of the quantitative food frequency questionnaire. Nutr Cancer Int J 39(2):187–195.  https://doi.org/10.1207/S15327914nc392_5 CrossRefGoogle Scholar
  25. 25.
    Eshak ES, Iso H, Date C, Yamagishi K, Kikuchi S, Watanabe Y, Wada Y, Tamakoshi A, Grp JS (2011) Rice intake is associated with reduced risk of mortality from cardiovascular disease in Japanese men but not women. J Nutr 141(4):595–602.  https://doi.org/10.3945/jn.110.132167 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Koh WP, Yuan JM, Wang R, Lee HP, Yu MC (2010) Body mass index and smoking-related lung cancer risk in the Singapore Chinese Health Study. Br J Cancer 102(3):610–614.  https://doi.org/10.1038/sj.bjc.6605496 CrossRefPubMedGoogle Scholar
  27. 27.
    Odegaard AO, Koh WP, Arakawa K, Yu MC, Pereira MA (2010) Soft drink and juice consumption and risk of physician-diagnosed incident type 2 diabetes. Am J Epidemiol 171(6):701–708.  https://doi.org/10.1093/aje/kwp452 CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Nathan DM, Balkau B, Bonora E, Borch-Johnsen K, Buse JB, Colagiuri S, Davidson MB, DeFronzo R, Genuth S, Holman RR, Ji L, Kirkman S, Knowler WC, Schatz D, Shaw J, Sobngwi E, Steffes M, Vaccaro O, Wareham N, Zinman B, Kahn R, Int Expert C (2009) International expert committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 32(7):1327–1334.  https://doi.org/10.2337/dc09-9033 CrossRefGoogle Scholar
  29. 29.
    Willett WC, Howe GR, Kushi LH (1997) Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65(4):1220–1228CrossRefGoogle Scholar
  30. 30.
    Hu FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13(1):3–9.  https://doi.org/10.1097/00041433-200202000-00002 CrossRefPubMedGoogle Scholar
  31. 31.
    Neelakantan N, Naidoo N, Koh WP, Yuan JM, van Dam RM (2016) The Alternative Healthy Eating Index is associated with a lower risk of fatal and nonfatal acute myocardial infarction in a Chinese adult population. J Nutr 146(7):1379–1386.  https://doi.org/10.3945/jn.116.231605 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Chiuve SE, Fung TT, Rimm EB, Hu FB, McCullough ML, Wang ML, Stampfer MJ, Willett WC (2012) Alternative dietary indices both strongly predict risk of chronic disease. J Nutr 142(6):1009–1018.  https://doi.org/10.3945/jn.111.157222 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Kulldorff M, Sinha R, Chow WH, Rothman N (2000) Comparing odds ratios for nested subsets of dietary components. Int J Epidemiol 29(6):1060–1064.  https://doi.org/10.1093/ije/29.6.1060 CrossRefPubMedGoogle Scholar
  34. 34.
    Halton TL, Willett WC, Liu SM, Manson JE, Stampfer MJ, Hu FB (2006) Potato and french fry consumption and risk of type 2 diabetes in women. Am J Clin Nutr 83(2):284–290CrossRefGoogle Scholar
  35. 35.
    Orsini N, Li RF, Wolk A, Khudyakov P, Spiegelman D (2012) Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software. Am J Epidemiol 175(1):66–73.  https://doi.org/10.1093/aje/kwr265 CrossRefPubMedGoogle Scholar
  36. 36.
    Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, Hu FB (2011) Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. Am J Clin Nutr 94(4):1088–1096.  https://doi.org/10.3945/ajcn.111.018978 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Talaei M, Wang YL, Yuan JM, Pan A, Koh WP (2017) Meat, dietary heme iron, and risk of type 2 diabetes mellitus the Singapore Chinese Health Study. Am J Epidemiol 186(7):824–833.  https://doi.org/10.1093/aje/kwx156 CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Yu D, Zheng W, Cai H, Xiang YB, Li H, Gao YT, Shu XO (2017) Long-term diet quality and risk of type 2 diabetes among urban Chinese adults. Diabetes Care.  https://doi.org/10.2337/dc17-1626 CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Murakami K, Sasaki S, Takahashi Y, Okubo H, Hosoi Y, Horiguchi H, Oguma E, Kayama F (2006) Dietary glycemic index and load in relation to metabolic risk factors in Japanese female farmers with traditional dietary habits. Am J Clin Nutr 83(5):1161–1169CrossRefGoogle Scholar
  40. 40.
    Nanri A, Mizoue T, Yoshida D, Takahashi R, Takayanagi R (2008) Dietary patterns and A1C in Japanese men and women. Diabetes Care 31(8):1568–1573.  https://doi.org/10.2337/dc08-0297 CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Radhika G, Van Dam RM, Sudha V, Ganesan A, Mohan V (2009) Refined grain consumption and the metabolic syndrome in urban Asian Indians (Chennai Urban Rural Epidemiology Study 57). Metab Clin Exp 58(5):675–681.  https://doi.org/10.1016/j.metabol.2009.01.008 CrossRefPubMedGoogle Scholar
  42. 42.
    Zuniga YLM, Rebello SA, Oi PL, Zheng HL, Lee J, Tai ES, Van Dam RM (2014) Rice and noodle consumption is associated with insulin resistance and hyperglycaemia in an Asian population. Br J Nutr 111(6):1118–1128.  https://doi.org/10.1017/s0007114513003486 CrossRefPubMedGoogle Scholar
  43. 43.
    Soriguer F, Colomo N, Olveira G, Garcia-Fuentes E, Esteva I, de Adana MSR, Morcillo S, Porras N, Valdes S, Rojo-Martinez G (2013) White rice consumption and risk of type 2 diabetes. Clin Nutr 32(3):481–484.  https://doi.org/10.1016/j.clnu.2012.11.008 CrossRefPubMedGoogle Scholar
  44. 44.
    Golozar A, Khalili D, Etemadi A, Poustchi H, Fazeltabar A, Hosseini F, Kamangar F, Khoshnia M, Islami F, Hadaegh F, Brennan P, Boffetta P, Abnet CC, Dawsey SM, Azizi F, Malekzadeh R, Danaei G (2017) White rice intake and incidence of type-2 diabetes: analysis of two prospective cohort studies from Iran. BMC Public Health.  https://doi.org/10.1186/s12889-016-3999-4 CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Salmeron J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, Stampfer MJ, Wing AL, Willett WC (1997) Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 20(4):545–550.  https://doi.org/10.2337/diacare.20.4.545 CrossRefPubMedGoogle Scholar
  46. 46.
    Salmeron J, Manson JE, Stampfer MJ, Colditz GA, Wing AL, Willett WC (1997) Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. J Am Med Assoc 277(6):472–477.  https://doi.org/10.1001/jama.277.6.472 CrossRefGoogle Scholar
  47. 47.
    Meyer KA, Kushi LH, Jacobs DR, Slavin J, Sellers TA, Folsom AR (2000) Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr 71(4):921–930CrossRefGoogle Scholar
  48. 48.
    van Dam RM, Hu FB, Rosenberg L, Krishnan S, Palmer JR (2006) Dietary calcium and magnesium, major food sources, and risk of type 2 diabetes in US black women. Diabetes Care 29(10):2238–2243.  https://doi.org/10.2337/dc06-1014 CrossRefPubMedGoogle Scholar
  49. 49.
    Schulze MB, Schulz M, Heidemann C, Schienkiewitz A, Hoffmann K, Boeing H (2007) Fiber and magnesium intake and incidence of type 2 diabetes—a prospective study and meta-analysis. Arch Intern Med 167(9):956–965.  https://doi.org/10.1001/archinte.167.9.956 CrossRefPubMedGoogle Scholar
  50. 50.
    Willett W, Manson J, Liu SM (2002) Glycemic index, glycemic load, and risk of type 2 diabetes. Am J Clin Nutr 76(1):274S–280SCrossRefGoogle Scholar
  51. 51.
    Kahn SE, Hull RL, Utzschneider KM (2006) Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 444(7121):840–846.  https://doi.org/10.1038/nature05482 CrossRefPubMedGoogle Scholar
  52. 52.
    Chun YH, Han K, Kim DH, Park YG, Cho KH, Choi YS, Kim SM, Kim YH, Nam GE (2016) Association of urinary sodium excretion with insulin resistance in Korean adolescents results from the Korea National Health and Nutrition Examination Survey 2009–2010. Medicine.  https://doi.org/10.1097/md.0000000000003447 CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Hu G, Jousilahti P, Peltonen M, Lindstrom J, Tuomilehto J (2005) Urinary sodium and potassium excretion and the risk of type 2 diabetes: a prospective study in Finland. Diabetologia 48(8):1477–1483.  https://doi.org/10.1007/s00125-005-1824-1 CrossRefPubMedGoogle Scholar
  54. 54.
    Marshall JA, Bessesen DH, Hamman RF (1997) High saturated fat and low starch and fibre are associated with hyperinsulinaemia in a non-diabetic population: the San Luis Valley Diabetes Study. Diabetologia 40(4):430–438.  https://doi.org/10.1007/s001250050697 CrossRefPubMedGoogle Scholar
  55. 55.
    Rebello SA, Koh H, Chen C, Naidoo N, Odegaard AO, Koh WP, Butler LM, Yuan JM, van Dam RM (2014) Amount, type, and sources of carbohydrates in relation to ischemic heart disease mortality in a Chinese population: a prospective cohort study. Am J Clin Nutr 100(1):53–64.  https://doi.org/10.3945/ajcn.113.076273 CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Energy and Nutrient Composition of Food (2017). https://focos.hpb.gov.sg/eservices/ENCF/. Accessed 8 Apr 2018
  57. 57.
    Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witschi J, Hennekens CH, Speizer FE (1985) Reproducibility and validity of a Semiquantitative Food Frequency Questionnaire. Am J Epidemiol 122(1):51–65CrossRefGoogle Scholar
  58. 58.
    Seah JYH, Gay GMW, Su J, Tai ES, Yuan JM, Koh WP, Ong CN, van Dam RM (2017) Consumption of red meat, but not cooking oils high in polyunsaturated fat, is associated with higher arachidonic acid status in Singapore Chinese adults. Nutrients.  https://doi.org/10.3390/nu9020101 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Saw Swee Hock School of Public HealthNational University of Singapore (NUS)SingaporeSingapore
  2. 2.NUS Graduate School for Integrative Sciences and EngineeringNUSSingaporeSingapore
  3. 3.Health Services and Systems ResearchDuke-NUS Medical SchoolSingaporeSingapore
  4. 4.Division of Cancer Control and Population Sciences, UPMC Hillman Cancer CenterUniversity of PittsburghPittsburghUSA
  5. 5.Department of Epidemiology, Graduate School of Public HealthUniversity of PittsburghPittsburghUSA
  6. 6.Department of Medicine, Yong Loo Lin School of MedicineNUS and National University Health SystemSingaporeSingapore
  7. 7.Department of NutritionHarvard School of Public HealthBostonUSA

Personalised recommendations