Biomarker-calibrated dietary energy and protein intake associations with diabetes risk among postmenopausal women from the Women's Health Initiative.

BACKGROUND Self-report of dietary energy and protein intakes has been shown to be systematically and differentially underreported. OBJECTIVE We assessed and compared the association of diabetes among postmenopausal women with biomarker-calibrated and uncalibrated dietary energy and protein intakes from food-frequency questionnaires (FFQs). DESIGN The analyses were performed for 74,155 participants of various race-ethnicities from the Women's Health Initiative. Uncalibrated and calibrated energy and protein intakes from FFQs were assessed for associations with incident diabetes by using HR estimates based on Cox regression. RESULTS A 20% increment in uncalibrated energy consumption was associated with increased diabetes risk (HR) of 1.03 (95% CI: 1.01, 1.05), 2.41 (95% CI: 2.06, 2.82) with biomarker calibration, and 1.30 (95% CI: 0.96, 1.76) after adjustment for BMI. A 20% increment in uncalibrated protein (g/d) resulted in an HR of 1.05 (95% CI: 1.03, 1.07), 1.82 (95% CI: 1.56, 2.12) with calibration, and 1.16 (95% CI: 1.05, 1.28) with adjustment for BMI. A 20% increment in uncalibrated protein density (% of energy from protein) resulted in an HR of 1.13 (95% CI: 1.09, 1.17), 1.01 (95% CI: 0.75, 1.37) with calibration, and 1.19 (95% CI: 1.07, 1.32) with adjustment for BMI. CONCLUSIONS Higher protein and total energy intakes (calibrated) appear to be associated with a substantially increased diabetes risk that may be mediated by an increase in body mass over time. Diet-disease associations without correction of self-reported measurement error should be viewed with caution. This trial is registered at clinicaltrials.gov as NCT00000611.

[1]  R. Prentice,et al.  Measurement error modeling and nutritional epidemiology association analyses , 2011, The Canadian journal of statistics = Revue canadienne de statistique.

[2]  R. Sinha,et al.  Urinary Biomarkers of Meat Consumption , 2011, Cancer Epidemiology, Biomarkers & Prevention.

[3]  M. S. Kirkman,et al.  Response to Comment on: American Diabetes Association. Standards of Medical Care in Diabetes—2011. Diabetes Care 2011;34(Suppl. 1):S11–S61 , 2011, Diabetes Care.

[4]  D. van der A,et al.  Dietary Intake of Total, Animal, and Vegetable Protein and Risk of Type 2 Diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-NL Study , 2009, Diabetes Care.

[5]  R. Prentice,et al.  Statistical Aspects of the Use of Biomarkers in Nutritional Epidemiology Research , 2009, Statistics in biosciences.

[6]  R. Prentice,et al.  Biomarker-calibrated energy and protein consumption and increased cancer risk among postmenopausal women. , 2009, American journal of epidemiology.

[7]  Jennifer G. Robinson,et al.  Low-fat dietary pattern and risk of treated diabetes mellitus in postmenopausal women: the Women's Health Initiative randomized controlled dietary modification trial. , 2008, Archives of internal medicine.

[8]  M. Rosal,et al.  Underreporting of energy intake and associated factors in a Latino population at risk of developing type 2 diabetes. , 2008, Journal of the American Dietetic Association.

[9]  Jennifer G. Robinson,et al.  Validity of diabetes self-reports in the Women's Health Initiative: comparison with medication inventories and fasting glucose measurements , 2008, Clinical trials.

[10]  Pamela A Shaw,et al.  Use of recovery biomarkers to calibrate nutrient consumption self-reports in the Women's Health Initiative. , 2008, American journal of epidemiology.

[11]  Heather K. Neilson,et al.  Estimating activity energy expenditure: how valid are physical activity questionnaires? , 2008, The American journal of clinical nutrition.

[12]  R. Prentice,et al.  Low-fat dietary pattern and cancer incidence in the Women's Health Initiative Dietary Modification Randomized Controlled Trial. , 2007, Journal of the National Cancer Institute.

[13]  D. Marrero,et al.  Adapting the Diabetes Prevention Program Lifestyle Intervention for Delivery in the Community , 2007, The Diabetes educator.

[14]  Steven Kahn,et al.  Adherence to Preventive Medications , 2006, Diabetes Care.

[15]  J. Manson,et al.  Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. , 2006, JAMA.

[16]  J. Manson,et al.  Low-fat dietary pattern and risk of colorectal cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. , 2006, JAMA.

[17]  J. Manson,et al.  Use of a dummy (pacifier) during sleep and risk of sudden infant death syndrome (SIDS): population based case-control study , 2005, BMJ : British Medical Journal.

[18]  A. Cicero,et al.  Relative role of major risk factors for Type 2 diabetes development in the historical cohort of the Brisighella Heart Study: an 8‐year follow‐up , 2005, Diabetic medicine : a journal of the British Diabetic Association.

[19]  Annette M. Molinaro,et al.  Prediction error estimation: a comparison of resampling methods , 2005, Bioinform..

[20]  J. Manson,et al.  A prospective study of red meat consumption and type 2 diabetes in middle-aged and elderly women: the women's health study. , 2004, Diabetes care.

[21]  Aesha Drozdowski,et al.  Standards of medical care in diabetes. , 2004, Diabetes care.

[22]  N. Day,et al.  Dietary fat and the risk of clinical type 2 diabetes: the European prospective investigation of Cancer-Norfolk study. , 2004, American journal of epidemiology.

[23]  R. Chlebowski,et al.  The Women's Health Initiative Dietary Modification trial: overview and baseline characteristics of participants. , 2003, Annals of epidemiology.

[24]  R. Langer,et al.  The Women's Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures. , 2003, Annals of epidemiology.

[25]  D. Midthune,et al.  Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. , 2003, American journal of epidemiology.

[26]  A. Mokdad,et al.  Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. , 2003, JAMA.

[27]  C Y Wang,et al.  Research strategies and the use of nutrient biomarkers in studies of diet and chronic disease , 2002, Public Health Nutrition.

[28]  A. Kristal,et al.  Measurement characteristics of the Women's Health Initiative food frequency questionnaire. , 1999, Annals of epidemiology.

[29]  JoAnn E. Manson,et al.  Design of the Women's Health Initiative clinical trial and observational study. The Women's Health Initiative Study Group. , 1998, Controlled clinical trials.

[30]  J. Manson,et al.  Diet and risk of clinical diabetes in women. , 1992, The American journal of clinical nutrition.

[31]  G A Colditz,et al.  Weight as a risk factor for clinical diabetes in women. , 1990, American journal of epidemiology.

[32]  V. Basevi.  Standards of Medical Care in Diabetes—2011 , 2011, Diabetes Care.

[33]  J. Freudenheim,et al.  The problem of profound mismeasurement and the power of epidemiological studies of diet and cancer. , 1988, Nutrition and cancer.