|Grant Number:||5R01CA119171-07 Interpret this number|
|Primary Investigator:||Prentice, Ross|
|Organization:||Fred Hutchinson Cancer Research Center|
|Project Title:||Nutrition and Physical Activity Assessment Study (NPAAS)|
DESCRIPTION (provided by applicant): This competing renewal of R01 CA119171, "Nutrition and Physical Activity Assessment Study" (NPAAS), continues to focus on the use of biomarkers to evaluate and compare measurement properties of prominent nutritional and physical activity assessment methods, and on the use of biomarker-calibrated nutrient consumption and activity-related energy expenditure (AREE) estimates in studies in Women's Health Initiative (WHI) cohorts of postmenopausal women. Our aims are: 1) To conduct a controlled feeding study to develop biomarkers for additional nutrients and foods, and 2) To use biomarkers from the ongoing and proposed NPAAS study phases to develop biomarker-calibrated nutrient consumption and AREE estimates, throughout the WHI cohorts for use in disease-association studies. We will recruit 150 women, in the age range 60-80 y, enrolled in the WHI Seattle Field Center, into a feeding study of a highly individualized controlled diet, with each woman's diet designed to approximate her usual food consumption patterns. Women will receive all foods and beverages during the 2-week feeding period. We will obtain 24-h urine-derived nutritional measures, including nitrogen (protein), fructose, sucrose (sugars), alkylresorcinols (whole grains) and 1- and 3- methylhistidine (meat); and blood-derived nutritional measures, including carotenoids (fruits & vegetables), 1- and 3 -tocopherols (fats & oils), phospholipid fatty acids (fats & oils), and folate (fruits & vegetables) at the beginning and end of the 2-week feeding period. Biomarker evaluation will include an assessment of the ability of urine and blood measures, and study subject characteristics to explain variation in nutrients and foods provided during the feeding study. Total energy expenditure (TEE) will be measured using a doubly-labeled water protocol, as will resting energy expenditure (REE) using indirect calorimetry with 0.9TEE-REE as objective measure of AREE. We will develop calibration equations for each nutrient/food or activity measure having a suitable biomarker, by regression analysis of the biomarker on corresponding self-report measures using specimens and data from the women in both NPAAS project phases. Suitable biomarkers will be available for total energy, protein, percent of energy from protein, and for total activity-related energy expenditure. We will apply these calibration equations in the WHI cohorts using a food-frequency questionnaire and multiple-day food record to produce calibrated consumption estimates and using a WHI activity questionnaire to produce calibrated AREE estimates. These calibrated estimates will be related to the subsequent incidence of a broad range of clinical outcomes (e.g., cancer, cardiovascular disease, diabetes, frailty, obesity, etc) among the 161,808 women in the WHI cohorts. This work addresses fundamental gaps in diet and physical activity epidemiology research, in the context of national and international obesity epidemics, and in much related chronic disease morbidity and mortality.
Postmenopausal hormone therapy and the risks of coronary heart disease, breast cancer, and stroke.
Authors: Prentice RL
Source: Semin Reprod Med, 2014 Nov;32(6), p. 419-25.
EPub date: 2014 Oct 16.
Use of a urinary sugars biomarker to assess measurement error in self-reported sugars intake in the nutrition and physical activity assessment study (NPAAS).
Authors: Tasevska N, Midthune D, Tinker LF, Potischman N, Lampe JW, Neuhouser ML, Beasley JM, Van Horn L, Prentice RL, Kipnis V
Source: Cancer Epidemiol Biomarkers Prev, 2014 Dec;23(12), p. 2874-83.
EPub date: 2014 Sep 18.
Simultaneous association of total energy consumption and activity-related energy expenditure with risks of cardiovascular disease, cancer, and diabetes among postmenopausal women.
Authors: Zheng C, Beresford SA, Van Horn L, Tinker LF, Thomson CA, Neuhouser ML, Di C, Manson JE, Mossavar-Rahmani Y, Seguin R, Manini T, LaCroix AZ, Prentice RL
Source: Am J Epidemiol, 2014 Sep 1;180(5), p. 526-35.
EPub date: 2014 Jul 12.
Measurement error corrected sodium and potassium intake estimation using 24-hour urinary excretion.
Authors: Huang Y, Van Horn L, Tinker LF, Neuhouser ML, Carbone L, Mossavar-Rahmani Y, Thomas F, Prentice RL
Source: Hypertension, 2014 Feb;63(2), p. 238-44.
EPub date: 2013 Nov 25.
Biomarker-calibrated protein intake and physical function in the Women's Health Initiative.
Authors: Beasley JM, Wertheim BC, LaCroix AZ, Prentice RL, Neuhouser ML, Tinker LF, Kritchevsky S, Shikany JM, Eaton C, Chen Z, Thomson CA
Source: J Am Geriatr Soc, 2013 Nov;61(11), p. 1863-71.
EPub date: 2013 Oct 28.
An exploratory study of respiratory quotient calibration and association with postmenopausal breast cancer.
Authors: Prentice RL, Neuhouser ML, Tinker LF, Pettinger M, Thomson CA, Mossavar-Rahmani Y, Thomas F, Qi L, Huang Y
Source: Cancer Epidemiol Biomarkers Prev, 2013 Dec;22(12), p. 2374-83.
EPub date: 2013 Oct 9.
Associations of serum insulin-like growth factor-I and insulin-like growth factor-binding protein 3 levels with biomarker-calibrated protein, dairy product and milk intake in the Women's Health Initiative.
Authors: Beasley JM, Gunter MJ, LaCroix AZ, Prentice RL, Neuhouser ML, Tinker LF, Vitolins MZ, Strickler HD
Source: Br J Nutr, 2014 Mar 14;111(5), p. 847-53.
EPub date: 2013 Oct 7.
Regression calibration in nutritional epidemiology: example of fat density and total energy in relationship to postmenopausal breast cancer.
Authors: Prentice RL, Pettinger M, Tinker LF, Huang Y, Thomson CA, Johnson KC, Beasley J, Anderson G, Shikany JM, Chlebowski RT, Neuhouser ML
Source: Am J Epidemiol, 2013 Dec 1;178(11), p. 1663-72.
EPub date: 2013 Sep 24.
Calibration of self-reported dietary measures using biomarkers: an approach to enhancing nutritional epidemiology reliability.
Authors: Prentice RL, Tinker LF, Huang Y, Neuhouser ML
Source: Curr Atheroscler Rep, 2013 Sep;15(9), p. 353.
Factors relating to eating style, social desirability, body image and eating meals at home increase the precision of calibration equations correcting self-report measures of diet using recovery biomarkers: findings from the Women's Health Initiative.
Authors: Mossavar-Rahmani Y, Tinker LF, Huang Y, Neuhouser ML, McCann SE, Seguin RA, Vitolins MZ, Curb JD, Prentice RL
Source: Nutr J, 2013 May 16;12, p. 63.
EPub date: 2013 May 16.
Physical activity assessment: biomarkers and self-report of activity-related energy expenditure in the WHI.
Authors: Neuhouser ML, Di C, Tinker LF, Thomson C, Sternfeld B, Mossavar-Rahmani Y, Stefanick ML, Sims S, Curb JD, Lamonte M, Seguin R, Johnson KC, Prentice RL
Source: Am J Epidemiol, 2013 Mar 15;177(6), p. 576-85.
EPub date: 2013 Feb 22.
Health risks and benefits from calcium and vitamin D supplementation: Women's Health Initiative clinical trial and cohort study.
Authors: Prentice RL, Pettinger MB, Jackson RD, Wactawski-Wende J, Lacroix AZ, Anderson GL, Chlebowski RT, Manson JE, Van Horn L, Vitolins MZ, Datta M, LeBlanc ES, Cauley JA, Rossouw JE
Source: Osteoporos Int, 2013 Feb;24(2), p. 567-80.
EPub date: 2012 Dec 4.
Biomarker-calibrated dietary energy and protein intake associations with diabetes risk among postmenopausal women from the Women's Health Initiative.
Authors: Tinker LF, Sarto GE, Howard BV, Huang Y, Neuhouser ML, Mossavar-Rahmani Y, Beasley JM, Margolis KL, Eaton CB, Phillips LS, Prentice RL
Source: Am J Clin Nutr, 2011 Dec;94(6), p. 1600-6.
EPub date: 2011 Nov 9.
Hazard ratio estimation for biomarker-calibrated dietary exposures.
Authors: Shaw PA, Prentice RL
Source: Biometrics, 2012 Jun;68(2), p. 397-407.
EPub date: 2011 Oct 17.
Measurement error modeling and nutritional epidemiology association analyses.
Authors: Prentice RL, Huang Y
Source: Can J Stat, 2011 Sep 1;39(3), p. 498-509.
Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers.
Authors: Prentice RL, Mossavar-Rahmani Y, Huang Y, Van Horn L, Beresford SA, Caan B, Tinker L, Schoeller D, Bingham S, Eaton CB, Thomson C, Johnson KC, Ockene J, Sarto G, Heiss G, Neuhouser ML
Source: Am J Epidemiol, 2011 Sep 1;174(5), p. 591-603.
EPub date: 2011 Jul 15.
Higher biomarker-calibrated protein intake is not associated with impaired renal function in postmenopausal women.
Authors: Beasley JM, Aragaki AK, LaCroix AZ, Neuhouser ML, Tinker LF, Cauley JA, Ensrud KE, Jackson RD, Prentice RL
Source: J Nutr, 2011 Aug;141(8), p. 1502-7.
EPub date: 2011 Jun 8.
Biomarker-calibrated energy and protein consumption and cardiovascular disease risk among postmenopausal women.
Authors: Prentice RL, Huang Y, Kuller LH, Tinker LF, Horn LV, Stefanick ML, Sarto G, Ockene J, Johnson KC
Source: Epidemiology, 2011 Mar;22(2), p. 170-9.
Protein intake and incident frailty in the Women's Health Initiative observational study.
Authors: Beasley JM, LaCroix AZ, Neuhouser ML, Huang Y, Tinker L, Woods N, Michael Y, Curb JD, Prentice RL
Source: J Am Geriatr Soc, 2010 Jun;58(6), p. 1063-71.
EPub date: 2010 May 7.
Dietary assessment and the reliability of nutritional epidemiology research reports.
Authors: Prentice RL
Source: J Natl Cancer Inst, 2010 May 5;102(9), p. 583-5.
EPub date: 2010 Apr 20.
Statistical Aspects of the Use of Biomarkers in Nutritional Epidemiology Research.
Authors: Prentice RL, Huang Y, Tinker LF, Beresford SA, Lampe JW, Neuhouser ML
Source: Stat Biosci, 2009 May 1;1(1), p. 112-123.
Biomarker-calibrated energy and protein consumption and increased cancer risk among postmenopausal women.
Authors: Prentice RL, Shaw PA, Bingham SA, Beresford SA, Caan B, Neuhouser ML, Patterson RE, Stefanick ML, Satterfield S, Thomson CA, Snetselaar L, Thomas A, Tinker LF
Source: Am J Epidemiol, 2009 Apr 15;169(8), p. 977-89.
EPub date: 2009 Mar 3.
The women's health initiative: lessons learned.
Authors: Prentice RL, Anderson GL
Source: Annu Rev Public Health, 2008;29, p. 131-50.
Use of recovery biomarkers to calibrate nutrient consumption self-reports in the Women's Health Initiative.
Authors: Neuhouser ML, Tinker L, Shaw PA, Schoeller D, Bingham SA, Horn LV, Beresford SA, Caan B, Thomson C, Satterfield S, Kuller L, Heiss G, Smit E, Sarto G, Ockene J, Stefanick ML, Assaf A, Runswick S, Prentice RL
Source: Am J Epidemiol, 2008 May 15;167(10), p. 1247-59.
EPub date: 2008 Mar 15.