Evaluation of a Novel Tool for Screening Inadequate Food Intake in Age-Related Macular Degeneration Patients.
Diana TangPaul MitchellGerald LiewGeorge BurlutskyVictoria M FloodBamini GopinathPublished in: Nutrients (2019)
Diet assessment tools provide valuable nutrition information in research and clinical settings. With growing evidence supporting dietary modification to delay development and progression of age-related macular degeneration (AMD), an AMD-specific diet assessment tool could encourage eye-care practitioners to refer patients in need of further dietary behavioural support to a dietitian and/or support network. Therefore, the aim of this study was to evaluate clinical use of a novel, short dietary questionnaire (SDQ-AMD) to screen for inadequate food intake in AMD patients by comparing it against a validated food frequency questionnaire (FFQ). Recruitment sources included Sydney-based private eye clinics and research databases (N = 155; 57% female; 78 ± 8 years). Scoring criteria based on the Australian Dietary Guidelines and dietary recommendations for AMD in literature were developed and applied to dietary data from the FFQ and SDQ-AMD. Bland-Altman plot of difference suggests agreement between the FFQ and SDQ-AMD as most mean difference scores were within the 95% CI (6.91, -9.94), and no significant bias between the scores as the mean score increased ((regression equation: y = 0.11x - 2.60) (95% CI: -0.058, 0.275, p-value = 0.20)). Scores were also significantly correlated (0.57, p ≤ 0.0001). The SDQ-AMD shows potential as a diet screening tool for clinical use, however, additional studies are warranted to validate the SDQ-AMD.
Keyphrases
- age related macular degeneration
- end stage renal disease
- ejection fraction
- chronic kidney disease
- physical activity
- healthcare
- primary care
- systematic review
- palliative care
- cross sectional
- peritoneal dialysis
- electronic health record
- single cell
- health insurance
- deep learning
- patient reported
- drinking water
- health information
- network analysis