Frontiers in Nutrition (Nov 2023)

High resting energy expenditure in women with episodic migraine: exploring the use of predictive formulas

  • Laís Bhering Martins,
  • Laís Bhering Martins,
  • Jéssica Sales Ribeiro,
  • Ana Maria dos Santos Rodrigues,
  • Luana Caroline dos Santos,
  • Antonio Lúcio Teixeira,
  • Adaliene Versiani Matos Ferreira

DOI
https://doi.org/10.3389/fnut.2023.1296937
Journal volume & issue
Vol. 10

Abstract

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IntroductionMigraine is a common and disabling primary headache, and its pathophysiology is not fully understood. Previous studies have suggested that pain can increase humans’ Resting Energy Expenditure (REE). However, no previous study has investigated whether the REE of individuals with migraine differs from the general population. Therefore, this study aims to assess whether the REE of women with migraine differs from that of women without headaches. We also tested the accuracy of REE predictive formulas in the migraine patients.MethodsThis cross-sectional study involves 131 adult women aged between 18 and 65 years, 83 with migraine and 48 without (controls). We collected clinical, demographic, and anthropometric data. Migraine severity was measured using the Migraine Disability Test and Headache Impact Test, version 6. The REE was measured by indirect calorimetry, and it was compared with the predicted REE calculated by formulas.ResultsPatients with migraine had higher REE when compared to controls (p < 0.01). There was a positive correlation between REE and the patient-reported number of migraine attacks per month (Rho = 0.226; p = 0.044). Mifflin-St Jeor and Henry and Rees were the predictive formulas that have more accuracy in predicting REE in women with migraine.DiscussionConsidering the benefits of nutritional interventions on treating migraines, accurately measuring REE can positively impact migraine patient care. This study enhances our understanding of the relationship between pain and energy expenditure. Our results also provide valuable insights for healthcare professionals in selecting the most effective predictive formula to calculate energy expenditure in patients with migraine.

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