Noom Coach was limited to energy output, but it had a high correlation with Dietplan6 (r=.91). Correlation coefficients ranged from r=–.12 for iron (Samsung Health vs Dietplan6) to r=.91 for protein (FatSecret vs Dietplan6).
We observed no other significant differences between Dietplan6 and the apps. Samsung Health and MyFitnessPal significantly underestimated calcium, iron, and vitamin C compared with Dietplan6, although there was no significant difference for vitamin A. Lose It! also gave significantly lower estimates for other reported outputs (carbohydrate, fat, fiber, and sodium) than did Dietplan6. Estimates of protein and sodium intake were significantly lower using Lose It! and FatSecret than using Dietplan6. The difference in estimation of energy and saturated fat intake between Dietplan6 and the diet apps was not significant. Participants had recorded their food consumption over a 24-hour period using standard protocols. We obtained 24-hour weighed food records from 20 participants (15 female, 5 male participants mean age 36.3 years mean body mass index 22.9 kg/m²) from previous controlled studies conducted at the Hugh Sinclair Unit of Human Nutrition, University of Reading, Reading, UK. We compared estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat, and fiber), and micronutrients (sodium, calcium, iron, vitamin A, and vitamin C) using paired t tests and Wilcoxon signed-rank tests, correlation coefficients, and Bland-Altman plots. We compared dietary analysis of 24-hour weighed food records (n=20) between 5 nutrition-related apps (Samsung Health, MyFitnessPal, FatSecret, Noom Coach, and Lose It!) and Dietplan6 (reference method), using app versions available in the United Kingdom. The objective of our study was to evaluate the level of agreement of popular nutrition-related apps for the assessment of energy and available macronutrients and micronutrients against a UK reference method. Nutrition-related apps are commonly used to provide information about the user’s dietary intake, but limited research has been performed to assess how well their outputs agree with those from standard methods. This review chapter has assessed the use and features of various mobile phone health applications, which helps individuals to overcome and monitor the above-mentioned health-related issues. Many mobile applications were developed for monitoring and calculating an energy level as well as healthy nutrition. In addition, today's busy schedule and less time availability restricts individuals to visit the doctors or nutritionists.
Adopting healthy habits, physical activity, exercise, sports, and walking can lead to a healthy lifestyle of an individual. Also, the unhygienic intake of food, intake of food on no fixed time, intake of fast food intake of other unhealthy stuff can lead to irregularities in the human body. Over-nutrition will result in obesity, Type II diabetes mellitus, and ischemic heart diseases. Similarly, undernutrition will cause a low intelligence quotient (IQ), osteoporosis, anemia, scurvy, pellagra, etc. Lack of proper diet causes many diseases like night blindness, gum death, rickets, osteomalacia, etc.
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