Energy intake misreport: how different methods affect its prevalence and nutrient intake estimates

Autores da FMUP

• Milton Severo Barros Da Silva

  Autor

• Elisabete Da Conceição Pereira Ramos

  Autor

• Carla Maria De Moura Lopes

  Autor

Participantes de fora da FMUP

• Magalhaes, V
• Torres, D
• Goios, A
• IAN-AF Consortium

Unidades de investigação

• Ciências da Saúde Pública e Forenses, e Educação Médica

Abstract

Background Although different methods for the evaluation of energy intake (EI) misreport have been described, it is unclear which one is the most appropriate. Aim To assess the performance of these methods in the prevalence of EI misreports and accuracy of nutrient intake estimates. Methods Reports of 3,639 adults from the Portuguese National Food, Nutrition and Physical Activity Survey 2015-2016 were classified using univariate (Willett; interquartile range) and multivariate (Goldberg; predicted total energy expenditure [pTEE], testing different standard deviations [SD]) methods. Self-reported intakes were compared to their respective estimates by urinary excretion in a sub-sample of 80. The effect of the exclusion of misreporters on nutrient estimates was assessed by the differences in linear regression coefficients between plausible and total sample. Results The highest prevalence of EI misreport was observed using pTEE 1SD (63.9%). Differences in the associations between nutrient self-reported intake and estimated intake using urinary biomarkers were verified with misreporters' exclusion by pTEE 1SD method (beta-protein = 0.209; 95% CI = 0.074-0.529; beta-potassium = 0.276; 95% CI = 0.060-0.560) and Goldberg 2SD (beta-protein = 0.080; 95% CI = 0.025-0.235; beta-potassium = 0.106; 95% CI = -0.048-0.246). Conclusions Multivariate methods lead to a higher prevalence of misreports and larger differences in nutrient estimates. The application of the pTEE 1SD and Goldberg 2SD methods resulted in more accurate nutrient estimates.

Keywords

• Misreport; national dietary survey; energy intake; urinary biomarkers; Portugal