Literature DB >> 35321795

Improving Diet Quality in U.S. Adults: A 30-Year Health and Economic Impact Microsimulation.

Patricia M Herman1, Annie Yu-An Chen2, Roland Sturm3.   

Abstract

INTRODUCTION: Epidemiologic studies relating health outcomes to dietary patterns captured by diet quality indices have shown better quality scores associated with lower mortality and chronic disease incidence. However, changing chronic disease risk factors only alters population health over time, and initial diet quality systematically varies across the population by sociodemographic status. This study uses microsimulation to examine 30-year impacts of improved diet quality by sociodemographic group.
METHODS: Diet quality across 12 sex-, race/ethnicity-, and education-defined subgroups was estimated from the 2011-2012 National Health and Nutrition Examination Survey. In 2021, the Future Adults (dynamic microsimulation) Model was used to simulate population health and economic outcomes over 30 years for these subgroups and all adults. The modeled pathway was through lowering risk for heart disease by following U.S. Dietary Guidelines.
RESULTS: Diet quality varied across the sociodemographic subgroups, and half of U.S. adults had diet quality that would be classified as poor. Improving U.S. diet quality to that reported for the top 20% in 2 large health professionals' samples could reduce incidence of heart disease by 9.9% (7.6%-13.8% across the 12 sociodemographic groups) after 30 years. Year 30 would also have 37,000 fewer deaths, 694,000 more quality-adjusted life years, and healthcare cost savings of $59.6 billion (2019 U.S. dollars).
CONCLUSIONS: Dynamic microsimulation enables predictions of socially important outcomes of prevention efforts, most of which are many years in the future and beyond the scope of trials. This paper estimates the 30-year population health and economic impact of poor diet quality by sociodemographic group.
Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2022        PMID: 35321795      PMCID: PMC9308633          DOI: 10.1016/j.amepre.2022.01.022

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   6.604


  27 in total

1.  The Healthy Eating Index-2010 is a valid and reliable measure of diet quality according to the 2010 Dietary Guidelines for Americans.

Authors:  Patricia M Guenther; Sharon I Kirkpatrick; Jill Reedy; Susan M Krebs-Smith; Dennis W Buckman; Kevin W Dodd; Kellie O Casavale; Raymond J Carroll
Journal:  J Nutr       Date:  2014-01-22       Impact factor: 4.798

2.  Estimating the global and regional burden of suboptimal nutrition on chronic disease: methods and inputs to the analysis.

Authors:  R Micha; S Kalantarian; P Wirojratana; T Byers; G Danaei; I Elmadfa; E Ding; E Giovannucci; J Powles; S Smith-Warner; M Ezzati; D Mozaffarian
Journal:  Eur J Clin Nutr       Date:  2011-09-14       Impact factor: 4.016

3.  Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: A Second Update of a Systematic Review and Meta-Analysis of Cohort Studies.

Authors:  Jakub Morze; Anna Danielewicz; Georg Hoffmann; Lukas Schwingshackl
Journal:  J Acad Nutr Diet       Date:  2020-10-14       Impact factor: 4.910

4.  Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level.

Authors:  Hazel A B Hiza; Kellie O Casavale; Patricia M Guenther; Carole A Davis
Journal:  J Acad Nutr Diet       Date:  2012-11-15       Impact factor: 4.910

5.  Diet quality, change in diet quality and risk of incident CVD and diabetes.

Authors:  Zhe Xu; Lyn M Steffen; Elizabeth Selvin; Casey M Rebholz
Journal:  Public Health Nutr       Date:  2019-09-12       Impact factor: 4.022

6.  Diet Quality as Assessed by the Healthy Eating Index, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension Score, and Health Outcomes: An Updated Systematic Review and Meta-Analysis of Cohort Studies.

Authors:  Lukas Schwingshackl; Berit Bogensberger; Georg Hoffmann
Journal:  J Acad Nutr Diet       Date:  2017-10-27       Impact factor: 4.910

7.  Index-based dietary patterns and the risk of prostate cancer in the NIH-AARP diet and health study.

Authors:  Claire Bosire; Meir J Stampfer; Amy F Subar; Yikyung Park; Sharon I Kirkpatrick; Stephanie E Chiuve; Albert R Hollenbeck; Jill Reedy
Journal:  Am J Epidemiol       Date:  2013-02-13       Impact factor: 4.897

8.  Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

Authors:  Amy F Subar; Nancy Potischman; Kevin W Dodd; Frances E Thompson; David J Baer; Dale A Schoeller; Douglas Midthune; Victor Kipnis; Sharon I Kirkpatrick; Beth Mittl; Thea P Zimmerman; Deirdre Douglass; Heather R Bowles; Yikyung Park
Journal:  J Acad Nutr Diet       Date:  2020-08-17       Impact factor: 4.910

9.  Cardiovascular mortality attributable to dietary risk factors in 51 countries in the WHO European Region from 1990 to 2016: a systematic analysis of the Global Burden of Disease Study.

Authors:  Toni Meier; Kira Gräfe; Franziska Senn; Patrick Sur; Gabriele I Stangl; Christine Dawczynski; Winfried März; Marcus E Kleber; Stefan Lorkowski
Journal:  Eur J Epidemiol       Date:  2018-12-14       Impact factor: 8.082

10.  Cost-effectiveness of financial incentives for improving diet and health through Medicare and Medicaid: A microsimulation study.

Authors:  Yujin Lee; Dariush Mozaffarian; Stephen Sy; Yue Huang; Junxiu Liu; Parke E Wilde; Shafika Abrahams-Gessel; Thiago de Souza Veiga Jardim; Thomas A Gaziano; Renata Micha
Journal:  PLoS Med       Date:  2019-03-19       Impact factor: 11.069

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