Login / Signup

Validity and Reproducibility of a Culture-Specific Electronic Food Frequency Questionnaire: A Trinidad and Tobago Diet Assessment Study.

Lesley Ann Foster-NicholasDavid ShavlikCeline E HeskeyPatricia DyettGina Siapco
Published in: Inquiry : a journal of medical care organization, provision and financing (2024)
Nutritional epidemiologists use culture-specific food frequency questionnaires (FFQs) to assess the dietary intake of groups based on country, region or ethnic groups. This study aimed to validate a culture-specific semi-quantitative electronic Food Frequency Questionnaire (e-FFQ) to estimate food group intake in the adult population of Trinidad and Tobago. A 139-item semi-quantitative e-FFQ containing local dishes and street food was administered twice to adults 18 years and older and compared against four 1-day food records (FRs) using digital photographs, which served as the reference method. The validity and reproducibility of the e-FFQ food group intake estimates were determined using paired t -tests, bivariate correlations, and cross-classifications. Reproducibility correlations between the reported food group intakes in the first and repeat administration of the e-FFQ ranged from moderate ( r  = .44, P  ≤ .0001) for sweetened beverages to high ( r  = .91 P  ≤ .0001) for alcohol. The cross-classification agreements ranged from 70% (street food) to 92% (alcohol). Energy-adjusted deattenuated validity correlations between the e-FFQ and FR ranged from ( r  = .08) for water to ( r  = .81) for food from animal sources, with a mean validity correlation of .36. An average of 68% of the e-FFQ estimates was correctly classified within the ±1 quintile of the exact agreement with the FRs. Agreements between the e-FFQ and FRs ranged from 55% for street foods to 95% for water, all significant at P  ≤ .0001. This study shows that the culture-specific e-FFQ is a valid tool for assessing and ranking food category intake estimates of the adult population living in Trinidad and Tobago.
Keyphrases
  • human health
  • machine learning
  • risk assessment
  • mass spectrometry
  • high resolution
  • weight loss
  • body mass index
  • high intensity
  • density functional theory