Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Epidemiology

Low-carbohydrate, high-protein score and mortality in a northern Swedish population-based cohort

Abstract

Background/Objective:

Long-term effects of carbohydrate-restricted diets are unclear. We examined a low-carbohydrate, high-protein (LCHP) score in relation to mortality.

Subjects/Methods:

This is a population-based cohort study on adults in the northern Swedish county of Västerbotten. In 37 639 men (1460 deaths) and 39 680 women (923 deaths) from the population-based Västerbotten Intervention Program, deciles of energy-adjusted carbohydrate (descending) and protein (ascending) intake were added to create an LCHP score (2–20 points). Sex-specific hazard ratios (HR) were calculated by Cox regression.

Results:

Median intakes of carbohydrates, protein and fat in subjects with LCHP scores 2–20 ranged from 61.0% to 38.6%, 11.3% to 19.2% and 26.6% to 41.5% of total energy intake, respectively. High LCHP score (14–20 points) did not predict all-cause mortality compared with low LCHP score (2–8 points), after accounting for saturated fat intake and established risk factors (men: HR for high vs low 1.03 (95% confidence interval (CI) 0.88–1.20), P for continuous=0.721; women: HR for high vs low 1.10 (95% CI 0.91–1.32), P for continuous=0.229). For cancer and cardiovascular disease, no clear associations were found. Carbohydrate intake was inversely associated with all-cause mortality, though only statistically significant in women (multivariate HR per decile increase 0.95 (95% CI 0.91–0.99), P=0.010).

Conclusion:

Our results do not support a clear, general association between LCHP score and mortality. Studies encompassing a wider range of macronutrient consumption may be necessary to detect such an association.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1

Similar content being viewed by others

References

  1. The 2010 Dietary Guidelines for Americans; US Department of Agriculture, Centre for Nutrition Policy and Promotion. Available from Internet: http://www.cnpp.usda.gov/dietaryguidelines.htm (accessed 23 March 2011) (cited 10 March 2011).

  2. Hession M, Rolland C, Kulkarni U, Wise A, Broom J . Systematic review of randomized controlled trials of low-carbohydrate vs low-fat/low-calorie diets in the management of obesity and its comorbidities. Obes Rev 2009; 10, 36–50.

    Article  CAS  Google Scholar 

  3. Sacks FM, Katan M . Randomized clinical trials on the effects of dietary fat and carbohydrate on plasma lipoproteins and cardiovascular disease. Am J Med 2002; 113 (Suppl 9B), 13S–24S.

    Article  CAS  Google Scholar 

  4. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Sato M et al. Influence of fat and carbohydrate proportions on the metabolic profile in patients with type 2 diabetes: a meta-analysis. Diabetes Care 2009; 32, 959–965.

    Article  CAS  Google Scholar 

  5. Kirk JK, Graves DE, Craven TE, Lipkin EW, Austin M, Margolis KL . Restricted-carbohydrate diets in patients with type 2 diabetes: a meta-analysis. J Am Diet Assoc 2008; 108, 91–100.

    Article  CAS  Google Scholar 

  6. Wylie-Rosett J, Davis NJ . Low-carbohydrate diets: an update on current research. Curr Diab Rep 2009; 9, 396–404.

    Article  CAS  Google Scholar 

  7. Bantle JP, Wylie-Rosett J, Albright AL, Apovian CM, Clark NG, Franz MJ et al. Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care 2008; 31 (Suppl 1), S61–S78.

    CAS  Google Scholar 

  8. Hernandez TL, Sutherland JP, Wolfe P, Allian-Sauer M, Capell WH, Talley ND et al. Lack of suppression of circulating free fatty acids and hypercholesterolaemia during weight loss on a high-fat, low-carbohydrate diet. Am J Clin Nutr 2010; 91, 578–585.

    Article  CAS  Google Scholar 

  9. Sjogren P, Becker W, Warensjo E, Olsson E, Byberg L, Gustafsson IB et al. Mediterranean and carbohydrate-restricted diets and mortality among elderly men: a cohort study in Sweden. Am J Clin Nutr 2010; 92, 967–974.

    Article  Google Scholar 

  10. Trichopoulou A, Psaltopoulou T, Orfanos P, Hsieh CC, Trichopoulos D . Low-carbohydrate-high-protein diet and long-term survival in a general population cohort. Eur J Clin Nutr 2007; 61, 575–581.

    Article  CAS  Google Scholar 

  11. Lagiou P, Sandin S, Weiderpass E, Lagiou A, Mucci L, Trichopoulos D et al. Low carbohydrate-high protein diet and mortality in a cohort of Swedish women. J Intern Med 2007; 261, 366–374.

    Article  CAS  Google Scholar 

  12. Fung TT, van Dam RM, Hankinson SE, Stampfer M, Willett WC, Hu FB . Low-carbohydrate diets and all-cause and cause-specific mortality: two cohort studies. Ann Intern Med 2010; 153, 289–298.

    Article  Google Scholar 

  13. Adam-Perrot A, Clifton P, Brouns F . Low-carbohydrate diets: nutritional and physiological aspects. Obes Rev 2006; 7, 49–58.

    Article  CAS  Google Scholar 

  14. Alexander DD, Weed DL, Cushing CA, Lowe KA . Meta-analysis of prospective studies of red meat consumption and colorectal cancer. Eur J Cancer Prev 2011; 20, 293–307.

    Article  CAS  Google Scholar 

  15. de Koning L, Fung TT, Liao X, Chiuve S, Rimm EB, Willett WC et al. Low-carbohydrate diet scores and risk of type 2 diabetes in men. Am J Clin Nutr 2011; 94, 611.

    Google Scholar 

  16. Halton TL, Liu S, Manson JE, Hu FB . Low-carbohydrate-diet score and risk of type 2 diabetes in women. Am J Clin Nutr 2008; 87, 339–346.

    Article  CAS  Google Scholar 

  17. Weinehall L, Hallgren CG, Westman G, Janlert U, Wall S . Reduction of selection bias in primary prevention of cardiovascular disease through involvement of primary health care. Scand J Prim Health Care 1998; 16, 171–176.

    Article  CAS  Google Scholar 

  18. Pukkala E, Andersen A, Berglund G, Gislefoss R, Gudnason V, Hallmans G et al. Nordic biological specimen banks as basis for studies of cancer causes and control—more than 2 million sample donors, 25 million person years and 100 000 prospective cancers. Acta Oncol 2007; 46, 286–307.

    Article  Google Scholar 

  19. Schofield WN . Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 1985; 39 (Suppl 1), 5–41.

    Google Scholar 

  20. Johansson I, Hallmans G, Wikman A, Biessy C, Riboli E, Kaaks R . Validation and calibration of food-frequency questionnaire measurements in the Northern Sweden Health and Disease cohort. Public Health Nutr 2002; 5, 487–496.

    Article  Google Scholar 

  21. Wennberg M, Vessby B, Johansson I . Evaluation of relative intake of fatty acids according to the Northern Sweden FFQ with fatty acid levels in erythrocyte membranes as biomarkers. Public Health Nutr 2009; 12, 1477–1484.

    Article  Google Scholar 

  22. Johansson I, Van Guelpen B, Hultdin J, Johansson M, Hallmans G, Stattin P . Validity of food frequency questionnaire estimated intakes of folate and other B vitamins in a region without folic acid fortification. Eur J Clin Nutr 2010; 64, 905–913.

    Article  CAS  Google Scholar 

  23. Winkvist A, Hornell A, Hallmans G, Lindahl B, Weinehall L, Johansson I . More distinct food intake patterns among women than men in northern Sweden: a population-based survey. Nutr J 2009; 8, 12.

    Article  Google Scholar 

  24. Willett W, Stampfer MJ . Total energy intake: implications for epidemiologic analyses. Am j epidemiol 1986; 124, 17–27.

    Article  CAS  Google Scholar 

  25. Black AE . Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord 2000; 24, 1119–1130.

    Article  CAS  Google Scholar 

  26. Johansson G, Westerterp KR . Assessment of the physical activity level with two questions: validation with doubly labeled water. Int J Obes (Lond) 2008; 32, 1031–1033.

    Article  CAS  Google Scholar 

  27. Brand-Miller J, McMillan-Price J, Steinbeck K, Caterson I . Dietary Glycemic Index: Health Implications. J Am College Nutr 2009; 28 (4 Supplement 1), 446S–449S.

    Article  CAS  Google Scholar 

  28. Taylor VH, Misra M, Mukherjee SD . Is red meat intake a risk factor for breast cancer among premenopausal women? Breast Cancer Res Treat 2009; 117, 1–8.

    Article  Google Scholar 

  29. Nafziger AN, Lindvall K, Norberg M, Stenlund H, Wall S, Jenkins PL et al. Who is maintaining weight in a middle-aged population in Sweden? A longitudinal analysis over 10 years. BMC public health 2007; 7, 108.

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by Nordic Health Whole Grain Food (HELGA)/NordForsk and Visare Norr, Northern County Councils. We thank the participants in the Västerbotten Intervention Program for their valuable contribution to medical research. We also acknowledge Professor Göran Broström of the Department of Statistics, Umeå University, for excellent statistical advice.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L M Nilsson.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nilsson, L., Winkvist, A., Eliasson, M. et al. Low-carbohydrate, high-protein score and mortality in a northern Swedish population-based cohort. Eur J Clin Nutr 66, 694–700 (2012). https://doi.org/10.1038/ejcn.2012.9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2012.9

Keywords

This article is cited by

Search

Quick links