Higher-protein diets, meal replacements, and greater early weight loss have separately been associated with greater weight loss. We compared a high-protein, meal replacement program with daily energy restriction (DER) to one which provided greater energy restriction adding alternate day fasting (ADF + DER; alternating days of modified-fasting and DER plus 1 ad libitum day/week) on retention, weight loss, physiological, nutritional, and behavioral markers. Participants were randomized to ADF + DER or DER for 16 weeks (n = 162, age 40 ± 8 years BMI 36 ± 6 kg/m2 (Mean ± SD)) plus 8 weeks weight maintenance. At week 16 weight change was −10.7 ± 0.5 kg and −11.2 ± 0.6 kg in ADF + DER and DER groups (treatment NS). Fat mass, visceral adipose tissue, and lean mass (p < 0.05) were similarly reduced between treatments. Weight loss was sustained to 24 weeks (treatment NS). Fasting LDL-cholesterol, triglycerides, insulin, hsCRP, glucose, and blood pressure all improved (p < 0.05; treatment NS). Transferrin saturation, ferritin, serum zinc, folate, and B12 improved (p < 0.05; treatment NS). Plasma thiamine and vitamin D levels decreased, reflecting lower carbohydrate intakes and seasonal changes, respectively. Food cravings, quality of life, and mood improved (treatment NS). Energy, fatigue, and pain improved slightly more in DER (p < 0.05). This study supports the use of higher protein, meal replacement programs with or without ADF in weight management.

While advanced cancer is often associated with weight loss, curative cancer treatment is often associated with weight gain. Weight gain during treatment may be associated with greater risk of cancer recurrence and development of lifestyle diseases. Currently, limited resources are available to cancer patients focussed on weight control. This study assessed the information needs of patients undergoing curative chemotherapy regarding diet, exercise and weight management for the purpose of developing weight management resources. Focus groups were held with oncology practitioners, patients and survivors to determine current information provision and needs. Focus groups highlighted a perception that information provision regarding diet, exercise and weight management is insufficient and no routine assessment of weight occurs during chemotherapy. Barriers to information provision described included lack of resources and time, and practitioners' uncertainty regarding appropriate messages to provide. Patients wanted more information regarding diet, exercise and weight during treatment time. The findings of this study suggest an increase in provision of diet, exercise and weight management information is needed. This information should be evidence-based and delivered at an appropriate time by the preferred health care professional. It would also be beneficial to implement protocols regarding assessment of weight during treatment.

Background Poor-quality dietary patterns are often characterized by inadequate consumption of fruits and vegetables. Changing dietary behavior is difficult, and although it is often clear what needs to change, how to enact change is more difficult. Smartphones have characteristics that may support the complexity of changing dietary behavior. Objective This paper describes the iterative process of developing a theory-based smartphone app called VegEze that aimed to increase vegetable consumption. Methods To upscale, reach target users, and create a user-friendly end product, a collaborative research-industry partnership was formed to build the app over a 20-week period. The Integrate, Design, Assess, and Share framework was used as a scientific basis to guide the development. The behavior change wheel was also used as a theoretical grounding in combination with other theory-based strategies, such as self-monitoring, social comparison, and gamification—which have all been shown to be successful in dietary change or digital health interventions. We conducted 1 consumer survey (N=1068), 1 usability testing session (N=11), and a pilot effectiveness and usability trial (N=283) to inform the design of the app. Results The target behavior for the app was defined as having 3 different types of vegetables at dinner. The perceived achievability of this target behavior was high; 93% of respondents (993/1068 users) felt they were likely or very likely to be able to regularly achieve the behavior. App features that users wanted included the following: recipes and meal ideas (876/1068, 82% of users), functionality to track their intake (662/1068, 62%), and information on how to prepare vegetables (545/1068, 51%). On the basis of importance of self-monitoring as a behavior change technique (BCT) and its rating by users, the vegetable tracker was a core feature of the app and was designed to be quick and simple to use. Daily feedback messages for logging intake and communicating progress were designed to be engaging and fun, using friendly, positive language and emoji icons. Daily and weekly feedback on vegetable consumption was designed to be simple, informative, and reinforce monitoring. A creative team was engaged to assist in the branding of the app to ensure it had an identity that reflected the fun and simple nature of the underlying behavior. The app included 16 BCTs, most of which were from the goals and planning subsection of the BCT taxonomy. Conclusions Combining a theoretical framework with an industry perspective and input resulted in an app that was developed in a timely manner while retaining its evidence-base. VegEze is an iOS app currently available in the App Store, and the overall impact of the VegEze app will be evaluated in an uncontrolled, quantitative study. Trial Registration ...

Background Large-scale initiatives to improve diet quality through increased vegetable consumption have had small to moderate success. Digital technologies have features that are appealing for health-related behavior change interventions. Objective This study aimed to describe the implementation and evaluation of a mobile phone app called VegEze, which aims to increase vegetable intake among Australian adults. Methods To capture the impact of this app in a real-world setting, the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework was utilized. An uncontrolled, quantitative cohort study was conducted, with evaluations after 21 and 90 days. The app was available in the Apple App Store and was accompanied by television, radio, and social media promotion. Evaluation surveys were embedded into the app using ResearchKit. The primary outcomes were vegetable intake (servings per day) and vegetable variety (types per day). Psychological variables (attitudes, intentions, self-efficacy, and action planning) and app usage were also assessed. Descriptive statistics and multiple linear regression were used to describe the impact of the app on vegetable intake and to determine the characteristics associated with the increased intake. Results Data were available from 5062 participants who completed the baseline survey; 1224 participants completed the 21-day survey, and 273 completed the 90-day survey. The participants resided across Australia and were mostly women (4265/5062, 84.3%) with a mean age of 48.2 years (SD 14.1). The mean increase in intake was 0.48 servings, from 3.06 servings at baseline to 3.54 servings at the end of the 21-day challenge (t1223=8.71; P<.001). The variety of vegetables consumed also increased by 0.35 types per day (t1123=9.59; P<.001). No changes in intake and variety were found from day 21 to the 90-day follow-up. Participants with the highest app usage increased their vegetable intake by 0.63 (SD 2.02) servings per day compared with 0.32 (SD 1.69) servings per day for those with the lowest app usage. On the basis of multiple linear regression, gender; age; BMI; psychological variables of self-efficacy, attitudes, intentions, and action planning specific to vegetable intake; baseline vegetable intake; and active days of app usage accounted for 23.3% of the variance associated with the change in intake (F9,1208=42.09; P<.001). Baseline vegetable intake was the strongest predictor of change in intake (beta=−.495; P<.001), with lower baseline intake associated with a greater change in intake. Self-efficacy (beta=.116; P<.001), action planning (beta=.066; P=.02), BMI (beta=.070; P=.01), and app usage (beta=.081; P=.002) were all significant predictors of the change in intake. Conclusions The VegEze app was able to increase intake by half a serving in a large sample of Australian adults. Testing the app in a real-world setting and embedding the consent process allowed for greater reach and an efficient, robust evaluation. Further work to improve engagement is warranted.

No abstract