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1.
Dig Dis Sci ; 69(8): 2996-3007, 2024 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-38850506

RESUMO

BACKGROUND: Insights into (poly)phenol exposure represent a modifiable factor that may modulate inflammation in chronic pancreatitis (CP), yet intake is poorly characterized and methods for assessment are underdeveloped. AIMS: The aims are to develop and test a method for estimating (poly)phenol intake from a 90-day food frequency questionnaire (FFQ) using the Phenol-Explorer database and determine associations with dietary patterns in CP patients versus controls via analysis of previously collected cross-sectional data. METHODS: Fifty-two CP patients and 48 controls were recruited from an ambulatory clinic at a large, academic institution. To assess the feasibility of the proposed methodology for estimating dietary (poly)phenol exposure, a retrospective analysis of FFQ data was completed. Mann-Whitney U tests were used to compare (poly)phenol intake by group; Spearman correlations and multivariable-adjusted log-linear associations were used to compare (poly)phenol intakes with dietary scores within the sample. RESULTS: Estimation of (poly)phenol intake from FFQs was feasible and produced estimates within a range of intake previously reported. Total (poly)phenol intake was significantly lower in CP vs controls (463 vs. 567mg/1000kcal; p = 0.041). In adjusted analyses, higher total (poly)phenol intake was associated with higher HEI-2015 (r = 0.34, p < 0.001), aMED (r = 0.22, p = 0.007), EDIH (r = 0.29, p < 0.001), and EDIP scores (r = 0.35, p < 0.001), representing higher overall diet quality and lower insulinemic and anti-inflammatory dietary potentials, respectively. CONCLUSIONS: Using enhanced methods to derive total (poly)phenol intake from an FFQ is feasible. Those with CP have lower total (poly)phenol intake and less favorable dietary pattern indices, thus supporting future tailored dietary intervention studies in this population.


Assuntos
Pancreatite Crônica , Humanos , Pancreatite Crônica/diagnóstico , Masculino , Feminino , Pessoa de Meia-Idade , Adulto , Estudos Retrospectivos , Polifenóis/administração & dosagem , Estudos Transversais , Dieta/estatística & dados numéricos , Dieta/efeitos adversos , Estudos de Viabilidade , Inquéritos sobre Dietas , Estudos de Casos e Controles
2.
Nutrients ; 16(15)2024 Jul 30.
Artigo em Inglês | MEDLINE | ID: mdl-39125354

RESUMO

The 2020-2025 Dietary Guidelines for Americans recommend limiting intakes of saturated fat and added sugars (SF/AS) to <10% total energy. Data-driven approaches to identify sources of SF/AS are needed to meet these goals. We propose using a population-based approach to identify the leading food and beverage sources of SF/AS consumed by US adults. Foods and beverages reported as consumed were assessed from two, 24 h dietary recalls (24HRDR) from 36,378 adults aged 19 years and older from the 2005-2018 National Health and Nutrition Examination Survey. Intakes of SF/AS were aggregated across both 24HRDR to identify What We Eat in America food categories accounting for ≥90% of SF/AS, respectively, by the total population and within population subgroups. Data were weighted to estimate a nationally representative sample. Ninety-five discrete food categories accounted for ≥90% of the total SF/AS intakes for >88% of the representative sample of U.S. adults. The top sources of SF were cheese, pizza, ice cream, and eggs. The leading sources of AS were soft drinks, tea, fruit drinks, and cakes and pies. This analysis reflects a parsimonious approach to reliably identify foods and beverages that contribute to SF/AS intakes in U.S. adults.


Assuntos
Gorduras na Dieta , Açúcares da Dieta , Inquéritos Nutricionais , Humanos , Adulto , Estados Unidos , Feminino , Masculino , Pessoa de Meia-Idade , Adulto Jovem , Gorduras na Dieta/análise , Gorduras na Dieta/administração & dosagem , Açúcares da Dieta/análise , Açúcares da Dieta/administração & dosagem , Bebidas/análise , Idoso , Ácidos Graxos/administração & dosagem , Ácidos Graxos/análise , Dieta/estatística & dados numéricos , Política Nutricional
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