Selma Gicevic1,2, Emin Tahirovic3, Sabri Bromage2, Walter Willett2,4. 1. The London Centre for Integrative Research on Agriculture and Health, London, UK. 2. Department of Nutrition, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA02115, USA. 3. Department of Software Engineering, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina. 4. Department of Epidemiology, Harvard T.H. Chan School of Public Health: Boston, USA.
Abstract
OBJECTIVE: We assessed the ability of the Prime Diet Quality Score (PDQS) to predict mortality in the US population and compared its predictiveness with that of the Healthy Eating Index-2015 (HEI-2015). DESIGN: PDQS and HEI-2015 scores were derived using two 24-h recalls and converted to quintiles. Mortality data were obtained from the 2015 Public-Use Linked Mortality File. Associations between diet quality and all-cause mortality were evaluated using multivariable Cox proportional hazards models, and predictive performance of the two metrics was compared using a Wald test of equality of coefficients with both scores in a single model. Finally, we evaluated associations between individual metric components and mortality. SETTING: A prospective analysis of the US National Health and Nutrition Examination Survey (NHANES) data. PARTICIPANTS: Five-thousand five hundred and twenty-five participants from three survey cycles (2003-2008) in the NHANES aged 40 years and over. RESULTS: Over the 51 248 person-years of follow-up (mean: 9·2 years), 767 deaths were recorded. In multivariable models, hazard ratios between the highest and lowest quintiles of diet quality scores were 0·70 (95 % CI 0·51, 0·96, Ptrend = 0·03) for the PDQS and 0·77 (95 % CI 0·57, 1·03, Ptrend = 0·20) for the HEI-2015. The PDQS and HEI-2015 were similarly good predictors of total mortality (Pdifference = 0·88). CONCLUSION: Among US adults, better diet quality measured by the PDQS was associated with reduced risk of all-cause mortality. Given that the PDQS is simpler to calculate than the HEI-2015, it should be evaluated further for use as a diet quality metric globally.
OBJECTIVE: We assessed the ability of the Prime Diet Quality Score (PDQS) to predict mortality in the US population and compared its predictiveness with that of the Healthy Eating Index-2015 (HEI-2015). DESIGN: PDQS and HEI-2015 scores were derived using two 24-h recalls and converted to quintiles. Mortality data were obtained from the 2015 Public-Use Linked Mortality File. Associations between diet quality and all-cause mortality were evaluated using multivariable Cox proportional hazards models, and predictive performance of the two metrics was compared using a Wald test of equality of coefficients with both scores in a single model. Finally, we evaluated associations between individual metric components and mortality. SETTING: A prospective analysis of the US National Health and Nutrition Examination Survey (NHANES) data. PARTICIPANTS: Five-thousand five hundred and twenty-five participants from three survey cycles (2003-2008) in the NHANES aged 40 years and over. RESULTS: Over the 51 248 person-years of follow-up (mean: 9·2 years), 767 deaths were recorded. In multivariable models, hazard ratios between the highest and lowest quintiles of diet quality scores were 0·70 (95 % CI 0·51, 0·96, Ptrend = 0·03) for the PDQS and 0·77 (95 % CI 0·57, 1·03, Ptrend = 0·20) for the HEI-2015. The PDQS and HEI-2015 were similarly good predictors of total mortality (Pdifference = 0·88). CONCLUSION: Among US adults, better diet quality measured by the PDQS was associated with reduced risk of all-cause mortality. Given that the PDQS is simpler to calculate than the HEI-2015, it should be evaluated further for use as a diet quality metric globally.
Authors: Xiao Gu; Dong D Wang; Teresa T Fung; Dariush Mozaffarian; Luc Djoussé; Bernard Rosner; Frank M Sacks; Walter C Willett Journal: Am J Clin Nutr Date: 2022-08-04 Impact factor: 8.472
Authors: Shristi Rawal; Valerie B Duffy; Lauren Berube; John E Hayes; Ashima K Kant; Chuan-Ming Li; Barry I Graubard; Howard J Hoffman Journal: Nutrients Date: 2021-12-20 Impact factor: 5.717