A simple dietary assessment tool to monitor food intake of hospitalized adult patients

BACKGROUND/OBJECTIVES: Monitoring food intake of patients during hospitalization using simple methods and minimal training is an ongoing problem in hospitals. Therefore, there is a need to develop and validate a simple, easy to use, and quick tool that enables staff to estimate dietary intake. Thus, this study aimed to develop and validate the Pictorial Dietary Assessment Tool (PDAT). SUBJECTS AND METHODS: A total of 37 health care staff members consisting of dietitians, nurses, and serving assistants estimated 130 breakfast and lunch meals consumed by 67 patients using PDAT. PDAT was developed based on the hospital menu that consists of staple food (rice or porridge), animal source protein (chicken, meat, eggs, and fish), and non-animal source protein (tau fu and tempeh), with a total of six pictorials of food at each meal time. Weighed food intake was used as a gold standard to validate PDAT. Agreement between methods was analyzed using correlations, paired t-test, Bland–Altman plots, kappa statistics, and McNemar’s test. Sensitivity, specificity, and area under the curve of receiver operating characteristic were calculated to identify whether patients who had an inadequate food intake were categorized as at risk by the PDAT, based on the food weighing method. Agreement between different backgrounds of health care staff was calculated by intraclass correlation coefficient and analysis of variance test. RESULTS: There was a significant correlation between the weighing food method and PDAT for energy (r=0.919, P<0.05), protein (r=0.843, P<0.05), carbohydrate (r=0.912, P<0.05), and fat (r=0.952; P<0.05). Nutrient intakes as assessed using PDAT and food weighing were rather similar (295±163 vs 292±158 kcal for energy; 13.9±7.8 vs 14.1±8.0 g for protein; 46.1±21.4 vs 46.7±22.3 g for carbohydrate; 7.4±3.1 vs 7.4±3.1 g for fat; P>0.05). The PDAT and food weighing method showed a satisfactory agreement beyond chance (k) (0.81 for staple food and animal source protein; 0.735 for non-animal source protein). Intraclass correlation coefficient ranged between 0.91 and 0.96 among respondents. There were no differences in energy, protein, carbohydrate, and fat intake estimated among health care staff (P=0.967; P=0.951; P=0.888; P=0.847, respectively). CONCLUSION: In conclusion, PDAT provides a valid estimation of macronutrient consumption among hospitalized adult patients.