|Grant Number:||1R01CA119171-01A1 Interpret this number|
|Primary Investigator:||Prentice, Ross|
|Organization:||Fred Hutchinson Can Res Ctr|
|Project Title:||Nutrition and Physical Activity Assessment Study (NPAAS)|
DESCRIPTION (provided by applicant): This proposal requests support for a Nutrition and Physical Activity Assessment Study within the Observational Study (OS) component of the Women's Health Initiative (WHI). The OS cohort is comprised of 93,676 postmenopausal women in the age range 50-79 when enrolled at the 40 WHI Clinical Centers in the U.S. between 1994 -1998. The study will be conducted among 450 postmenopausal weight-stable women with oversampling of racial/ethnic minority women and of women in the extremes of body mass index. Participating women will complete the same food frequency questionnaire (FFQ) and physical activity questionnaire used at screening for WHI enrollment, a four-day food record (4DFR) as was used at baseline in the WHI Dietary Modification Trial (48,835 women), and other selected dietary and physical activity assessments (three 24-hour dietary recalls, a physical activity frequency questionnaire, social desirability measures, and a 7-day physical activity recall). Participating women will follow a doubly-labeled water protocol to objectively assess total energy expenditure and an indirect calorimetry protocol to assess resting energy expenditure, thereby also yielding an objective assessment of activity-related energy expenditure. The expenditure of protein, sodium, and potassium will also be assessed from urine specimens, and the concentrations of selected nutrients will be measured in blood specimens. These data will be used to evaluate and contrast measurement properties of the dietary and physical activity assessment tools and their combination, with an emphasis on: systematic bias as a function of body mass, ethnicity, age, and other individual characteristics; the magnitude of person- specific and random measurement error variances; and the correlation patterns among errors from differing assessment procedures. Additionally, the data will be used to calibrate the FFQ, 4DFR, and physical activity questionnaire data collected at baseline, and subsequently, in the WHI, for use in a range of analyses to associate dietary and physical activity patterns with weight change and disease risk over an average 10-year follow-up period among 161,808 women in the WHI Clinical Trial and Observational Study. The study will provide much needed data regarding dietary and physical activity assessment in an understudied segment of the U.S. population, and will provide crucial information for interpreting existing studies and for future study planning.
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;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.
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.
The women's health initiative: lessons learned.
Authors: Prentice RL, Anderson GL
Source: Annu Rev Public Health, 2008;29, p. 131-50.