Development and Pilot Testing of the Snackability Smartphone Application to Identify Healthy and Unhealthy Snacks

Disordered Eating Attitudes and Their Association with Age, BMI, Stress, and Diet in College Students

OBJECTIVE

College students are at risk of disordered eating, particularly students with overweight/obesity and with higher stress, but little is known about how disordered eating may be related to diet. This study evaluated the associations between the Disordered Eating Attitudes Scale (DEAS) and age, BMI, stress, and diet.

METHODS

This is a secondary analysis of the baseline data in participants from the Snackability Trial. Participants completed a questionnaire on socio-demographics, DEAS, and snacking, self-reported their weight and height (to calculate BMI), and completed two 24 h non-consecutive dietary recalls (to calculate diet quality using HEI-2015 and snack quality score using an algorithm developed by our group). Associations between variables were assessed with Spearman correlations.

RESULTS

A total of 140 participants completed all assessments. The median age was 21.0 and the median BMI was 28.5 kg/m2 (43.7% had overweight and 41.5% had obesity). A total of 86.4% were females, 41.4% were white, 51.4% were low-income, and 30.7% were Hispanic/Latino. The total DEAS and the subscale 'Relationship with food' were positively correlated with stress and BMI (p < 0.05) but inversely correlated with HEI-2015 (p < 0.05). The subscales 'Restrictive and compensatory behaviors' and 'Concern about food and weight gain' were also positively correlated with stress (p < 0.001).

CONCLUSION

College students with higher disordered eating attitudes also had higher stress and BMI but poorer diet quality. Interventions may be needed for this group to manage stress and improve weight and diet quality, as well as promote awareness about disordered eating attitudes.

Effect of using the snackability app on snack quality among US college students with overweight and obesity: A randomized controlled trial

OBJECTIVE

To determine if using the Snackability app improves snack intake among college students.

PARTICIPANTS

US college students with overweight/obesity were recruited in June 2020-April 2021.

METHODS

A randomized controlled trial was conducted to test the Snackability app use for 12 wk on snack scores (calculated from the app) compared to controls. We also explored the effect on diet quality (Healthy Eating Index-2015) and weight. Outcomes were compared between the intervention and the control groups at 4, 8, and 12 wk using repeated measures ANOVA.

RESULTS

Participants in the app group significantly increased snack score at week 4 (p < 0.001) and week 8 (p = 0.015) and increased HEI-2020 score (p < 0.001) at week 4 compared to controls. The first 4 wk had the highest app usage. No significant differences were seen in body weight.

CONCLUSIONS

The Snackability app can be used as a tool to help improve snack and diet quality in this group.

Smartphone applications for nutrition Support: A systematic review of the target outcomes and main functionalities

INTRODUCTION

A proper nutrition is essential for human life. Recently, special attention on this topic has been given in relation to three health statuses: obesity, malnutrition and specific diseases that can be related to food or treated with specific diets. Mobile technology is often used to assist users that wish to regulate their eating habits, and identifying which fields of application have been explored the most by the app developers and which main functionalities have been adopted can be useful in view of future app developments.

METHODS

We selected 322 articles mentioning nutrition support apps through a literature database search, all of which have undergone an initial screening. After the exclusion of papers that were already reviews, not presenting apps or not focused on nutrition, not relevant or not developed for human subjects, 100 papers were selected for subsequent analyses that aimed at identifying the main treated conditions, outcome measures and functionalities implemented in the Apps.

RESULTS

Of the selected studies, 33 focus on specific diseases, 24 on obesity, 2 on malnutrition and 41 on other targets (e.g., weight/diet control). Type 2 diabetes is the most targeted disease, followed by gestational diabetes, hypertension, colorectal cancer and CVDs which all were targeted by more than one app. Most Apps include self-monitoring and coaching functionalities, educational content and artificial intelligence (AI) tools are slightly less common, whereas counseling, gamification and questionnaires are the least implemented. Body weight and calories/nutrients were the most common general outcome measures, while glycated hemoglobin (HbA1c) was the most common clinical outcome. No statistically significant differences in the effectiveness of the different functionalities were found.

CONCLUSION

The use of mobile technology to improve nutrition has been widely explored in the last years, especially for weight control and specific diseases like diabetes; however, other food-related conditions such as Irritable Bowel Diseases appear to be less targeted by newly developed smartphone apps and their related studies. All different kinds of functionalities appear to be equally effective, but further specific studies are needed to confirm the results.

Snacking behavior is associated with snack quality, overall diet quality, and body weight among US college students

Snacking behavior may affect snack quality, overall diet quality, and body weight; however, the associations between these variables have not been studied among college students. The objective of this study was to associate snacking behaviors with snack quality, diet quality, and weight status among college students with overweight and obesity. We hypothesized that a higher snacking frequency, accessibility and availability of unhealthy snacks, and lack of knowledge would be associated with lower snack and diet quality, and higher weight. Participants (n = 140) completed a snack behavior questionnaire, three 24-hour dietary recalls to assess diet quality using Healthy Eating Index 2015 (HEI-2015), and snack score using an algorithm based on the US DA Smart Snack guidelines and reported weight and height to calculate body mass index (BMI). Analysis of variance and Pearson correlation was used in the analyses. After adjusting for confounders, snack frequency was not associated with snack score, HEI-2015 score, or BMI, but evening snacks had a significantly lower snack score compared with late afternoon snacks (P = .017). Also, those with more accessibility and availability of unhealthy snacks had a lower snack score (P = .001), lower HEI-2015 score (P = .006), and higher BMI (P = .019). Snacking for pleasure was significantly associated with a lower snack score (P = .037). Snack score was positively correlated with HEI-2015 score but not with BMI. In conclusion, late snacking, unhealthy snack environment, and snacking for pleasure were associated with lower snack and diet quality. These findings could be used in future intervention strategies to improve snacking behaviors and the food environment.

Expanding the Capabilities of Nutrition Research and Health Promotion Through Mobile-Based Applications

Mobile-based applications are popular and prevalently used in the US population. Applications focusing on nutrition offer platforms for quantifying and changing behaviors to improve dietary intake. Such behavior changes can intervene in the relation of diet to promote health and prevent disease. Mobile applications offer a safe and convenient way to collect user data and share it back to users, researchers, and to health care providers. Other lifestyle factors like activity, sleep, and sedentary behavior, can also be quantified and included in investigations of how lifestyle is related to health. Yet, challenges in the assessment offered through mobile applications and effectiveness to change behavior still remain, including rigorous evaluation, demonstration of successful health improvement, and participant engagement. The data mobile applications generate, however, expands opportunities for discovery of the integrated and time-based nature of various daily activities in relation to health. This article is a summary of a symposium at Nutrition 2020 Live Online on the role of mobile applications as a tool for nutrition research and health promotion. The types and capabilities of mobile applications, challenges in their evaluation and use in research, and opportunities for the data they generate along with a specific example, are reviewed.

Analysis of Platforms and Functions of Mobile-Based Personal Health Record Systems

OBJECTIVES

Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems.

METHODS

The unit of analysis was general hospitals with more than 100 beds. This study was based on a PHR survey conducted from May 1 to June 30, 2020 and the National Health Insurance administrative data as of March 31, 2020. The study considered the platform, Android and iPhone operation system (iOS), and types of functionalities of PHR systems. Among the 316 target hospitals, 103 hospitals had adopted PHR systems. A logistic regression analysis was used.

RESULTS

This study found that 103 hospitals had adopted mobile-based PHR systems for their patients. Sixty-four hospitals (62.1%) were adopting both Android and iOS, but 36 (35.0%) and 3 (2.9%) hospitals were adopting Android only or iOS only, respectively. The PHR systems of hospitals adopting both platforms were more likely to have functions for viewing prescriptions, clinical diagnostic test results, and upcoming appointment status compared to those adopting a single platform (p < 0.001). The number of beds (odds ratio [OR] = 1.004; confidence interval [CI], 1.001-1.007; p = 0.0029) and the number of computed tomography systems (CTs) per 100 beds (OR = 6.350; CI, 1.006-40.084; p = 0.0493) were significantly associated with the adoption of both platforms.

CONCLUSIONS

More than 60% of hospitals had adopted both Android and iOS platforms for their patients in Korea. Hospitals adopting both platforms had additional functionalities and significant association with the number of beds and CTs.