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Nutr J ; 23(1): 42, 2024 Apr 17.
Artigo em Inglês | MEDLINE | ID: mdl-38627669

RESUMO

BACKGROUND: The Global Diet Quality Score (GDQS) was developed to be a simple, timely and cost-effective tool to track, simultaneously, nutritional deficiency and non-communicable disease risks from diet in diverse settings. The objective was to investigate the performance of GDQS as an indicator of adequate nutrient intake and dietary quality in a national-representative sample of the Brazilian population. METHODS: Nationally-representative data from 44,744 men and non-pregnant and non-lactating women aging ≥ 10 years, from the Brazilian National Dietary Survey were used. Dietary data were collected through two 24-h recalls (24HR). The GDQS was calculated and compared to a proxy indicator of nutrient adequate intake (the Minimum Dietary Diversity for Women-MDD-W) and to an indicator of high-risk diet for non-communicable diseases (caloric contribution from ultra-processed foods-UPF). To estimate the odds for overall nutrient inadequacy across MDD-W and GDQS quintiles, a multiple logistic regression was applied, and the two metrics' performances were compared using Wald's post-test. RESULTS: The mean GDQS for Brazilians was 14.5 (0-49 possible range), and only 1% of the population had a low-risk diet (GDQS ≥ 23). The GDQS mean was higher in women, elderly individuals and in higher-income households. An inverse correlation was found between the GDQS and UPF (rho (95% CI) = -0.20(-0.21;-0.19)). The odds for nutrient inadequacy were lower as quintiles of GDQS and MDD-W were higher (p-trend < 0.001), and MDD-W had a slightly better performance than GDQS (p-diff < 0.001). Having a low-risk GDQS (≥ 23) lowered the odds for nutrient inadequacy by 74% (95% CI:63%-81%). CONCLUSION: The GDQS is a good indicator of overall nutrient adequacy, and correlates well with UPF in a nationally representative sample of Brazil. Future studies must investigate the relationship between the GDQS and clinical endpoints, strengthening the recommendation to use this metric to surveillance dietary risks.


Assuntos
Dieta , Desnutrição , População da América do Sul , Masculino , Humanos , Feminino , Idoso , Ingestão de Energia , Ingestão de Alimentos
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