Performance of the Global Diet Quality Score (GDQS) App in Predicting Nutrient Adequacy and Metabolic Risk Factors among Thai Adults.

GDQS adults diet quality metrics dietary assessment dietary diversity metabolic syndrome noncommunicable disease nutrient adequacy nutrition surveillance nutritional epidemiology

Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 03 08 2023
revised: 03 10 2023
accepted: 06 10 2023
pubmed: 17 10 2023
medline: 17 10 2023
entrez: 16 10 2023
Statut: ppublish

Résumé

The Global Diet Quality Score (GDQS) was developed for monitoring nutrient adequacy and diet-related noncommunicable disease risk in diverse populations. A software application (GDQS app) was recently developed for the standardized collection of GDQS data. The application involves a simplified 24-h dietary recall (24HR) where foods are matched to GDQS-food groups using an onboard database, portion sizes are estimated at the food group level using cubic models, and the GDQS is computed. The study aimed to estimate associations between GDQS scores collected using the GDQS app and nutrient adequacy and metabolic risks. In this cross-sectional study of 600 Thai males and nonpregnant/nonlactating females (40-60 y), we collected 2 d of GDQS app and paper-based 24HR, food-frequency questionnaires (FFQs), anthropometry, body composition, blood pressure, and biomarkers. Associations between application scores and outcomes were estimated using multiple regression, and application performance was compared with that of metrics scored using 24HR and FFQ data: GDQS, Minimum Dietary Diversity-Women, Alternative Healthy Eating Index-2010, and Global Dietary Recommendations score. In covariate-adjusted models, application scores were significantly (P < 0.05) associated with higher energy-adjusted mean micronutrient adequacy computed using 24HR (range in estimated mean adequacy between score quintiles 1 and 5: 36.3%-44.5%) and FFQ (Q1-Q5: 40.6%-44.2%), and probability of protein adequacy from 24HR (Q1-Q5: 63%-72.5%). Application scores were inversely associated with BMI kg/m The GDQS app effectively assesses nutrient adequacy and metabolic risk in population surveys.

Sections du résumé

BACKGROUND BACKGROUND
The Global Diet Quality Score (GDQS) was developed for monitoring nutrient adequacy and diet-related noncommunicable disease risk in diverse populations. A software application (GDQS app) was recently developed for the standardized collection of GDQS data. The application involves a simplified 24-h dietary recall (24HR) where foods are matched to GDQS-food groups using an onboard database, portion sizes are estimated at the food group level using cubic models, and the GDQS is computed.
OBJECTIVES OBJECTIVE
The study aimed to estimate associations between GDQS scores collected using the GDQS app and nutrient adequacy and metabolic risks.
METHODS METHODS
In this cross-sectional study of 600 Thai males and nonpregnant/nonlactating females (40-60 y), we collected 2 d of GDQS app and paper-based 24HR, food-frequency questionnaires (FFQs), anthropometry, body composition, blood pressure, and biomarkers. Associations between application scores and outcomes were estimated using multiple regression, and application performance was compared with that of metrics scored using 24HR and FFQ data: GDQS, Minimum Dietary Diversity-Women, Alternative Healthy Eating Index-2010, and Global Dietary Recommendations score.
RESULTS RESULTS
In covariate-adjusted models, application scores were significantly (P < 0.05) associated with higher energy-adjusted mean micronutrient adequacy computed using 24HR (range in estimated mean adequacy between score quintiles 1 and 5: 36.3%-44.5%) and FFQ (Q1-Q5: 40.6%-44.2%), and probability of protein adequacy from 24HR (Q1-Q5: 63%-72.5%). Application scores were inversely associated with BMI kg/m
CONCLUSIONS CONCLUSIONS
The GDQS app effectively assesses nutrient adequacy and metabolic risk in population surveys.

Identifiants

DOI: 10.1016/j.tjnut.2023.10.007 PMID: 37844842
pubmed: 37844842
pii: S0022-3166(23)72661-8
doi: 10.1016/j.tjnut.2023.10.007
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3576-3594

Subventions

Organisme : FIC NIH HHS
ID : D43 TW010543
Pays : United States

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Sabri Bromage (S)

Community Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand; Department of Global Health and Populations, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Tippawan Pongcharoen (T)

Community Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand. Electronic address: tippawan.pon@mahidol.ac.th.

Aree Prachansuwan (A)

Human Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand.

Pornpan Sukboon (P)

Community Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand.

Weerachat Srichan (W)

Community Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand.

Sasiumphai Purttiponthanee (S)

Research and Innovation Service Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand.

Megan Deitchler (M)

Intake Center for Dietary Assessment, Washington, DC, USA.

Mourad Moursi (M)

Intake Center for Dietary Assessment, Washington, DC, USA.

Joanne Arsenault (J)

Intake Center for Dietary Assessment, Washington, DC, USA.

Nazia Binte Ali (NB)

Department of Global Health and Populations, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Carolina Batis (C)

Health and Nutrition Research Center, National Institute of Public Health, Cuernavaca, Morelos, México.

Wafaie W Fawzi (WW)

Department of Global Health and Populations, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Pattanee Winichagoon (P)

Community Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand.

Walter C Willett (WC)

Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Wantanee Kriengsinyos (W)

Human Nutrition Unit, Institute of Nutrition, Mahidol University, Salaya, Phutthamonthon, Nakhon Pathom, Thailand. Electronic address: wantanee.krieng@mahidol.edu.

Classifications MeSH