Improved eating behaviours mediate weight gain prevention of young adults: moderation and mediation results of a randomised controlled trial of TXT2BFiT, mHealth program

Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity

BACKGROUND

Obesity is considered to be a risk factor for various diseases, and its incidence has tripled worldwide since 1975. In addition to potentially being at risk for adverse health outcomes, people with overweight or obesity are often stigmatised. Behaviour change interventions are increasingly delivered as mobile health (m-health) interventions, using smartphone apps and wearables. They are believed to support healthy behaviours at the individual level in a low-threshold manner.

OBJECTIVES

To assess the effects of integrated smartphone applications for adolescents and adults with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, and LILACS, as well as the trials registers ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform on 2 October 2023 (date of last search for all databases). We placed no restrictions on the language of publication.

SELECTION CRITERIA

Participants were adolescents and adults with overweight or obesity. Eligible interventions were integrated smartphone apps using at least two behaviour change techniques. The intervention could target physical activity, cardiorespiratory fitness, weight loss, healthy diet, or self-efficacy. Comparators included no or minimal intervention (NMI), a different smartphone app, personal coaching, or usual care. Eligible studies were randomised controlled trials of any duration with a follow-up of at least three months.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodology and the RoB 2 tool. Important outcomes were physical activity, body mass index (BMI) and weight, health-related quality of life, self-efficacy, well-being, change in dietary behaviour, and adverse events. We focused on presenting studies with medium- (6 to < 12 months) and long-term (≥ 12 months) outcomes in our summary of findings table, following recommendations in the core outcome set for behavioural weight management interventions.

MAIN RESULTS

We included 18 studies with 2703 participants. Interventions lasted from 2 to 24 months. The mean BMI in adults ranged from 27 to 50, and the median BMI z-score in adolescents ranged from 2.2 to 2.5. Smartphone app versus no or minimal intervention Thirteen studies compared a smartphone app versus NMI in adults; no studies were available for adolescents. The comparator comprised minimal health advice, handouts, food diaries, smartphone apps unrelated to weight loss, and waiting list. Measures of physical activity: at 12 months' follow-up, a smartphone app compared to NMI probably reduces moderate to vigorous physical activity (MVPA) slightly (mean difference (MD) -28.9 min/week (95% confidence interval (CI) -85.9 to 28; 1 study, 650 participants; moderate-certainty evidence)). We are very uncertain about the results of estimated energy expenditure and cardiorespiratory fitness at eight months' follow-up. A smartphone app compared with NMI probably results in little to no difference in changes in total activity time at 12 months' follow-up and leisure time physical activity at 24 months' follow-up. Anthropometric measures: a smartphone app compared with NMI may reduce BMI (MD of BMI change -2.6 kg/m2, 95% CI -6 to 0.8; 2 studies, 146 participants; very low-certainty evidence) at six to eight months' follow-up, but the evidence is very uncertain. At 12 months' follow-up, a smartphone app probably resulted in little to no difference in BMI change (MD -0.1 kg/m2, 95% CI -0.4 to 0.3; 1 study; 650 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in body weight change (MD -2.5 kg, 95% CI -6.8 to 1.7; 3 studies, 1044 participants; low-certainty evidence) at 12 months' follow-up. At 24 months' follow-up, a smartphone app probably resulted in little to no difference in body weight change (MD 0.7 kg, 95% CI -1.2 to 2.6; 1 study, 245 participants; moderate-certainty evidence). A smartphone app compared with NMI may result in little to no difference in self-efficacy for a physical activity score at eight months' follow-up, but the results are very uncertain. A smartphone app probably results in little to no difference in quality of life and well-being at 12 months (moderate-certainty evidence) and in little to no difference in various measures used to inform dietary behaviour at 12 and 24 months' follow-up. We are very uncertain about adverse events, which were only reported narratively in two studies (very low-certainty evidence). Smartphone app versus another smartphone app Two studies compared different versions of the same app in adults, showing no or minimal differences in outcomes. One study in adults compared two different apps (calorie counting versus ketogenic diet) and suggested a slight reduction in body weight at six months in favour of the ketogenic diet app. No studies were available for adolescents. Smartphone app versus personal coaching Only one study compared a smartphone app with personal coaching in adults, presenting data at three months. Two studies compared these interventions in adolescents. A smartphone app resulted in little to no difference in BMI z-score compared to personal coaching at six months' follow-up (MD 0, 95% CI -0.2 to 0.2; 1 study; 107 participants). Smartphone app versus usual care Only one study compared an app with usual care in adults but only reported data at three months on participant satisfaction. No studies were available for adolescents. We identified 34 ongoing studies.

AUTHORS' CONCLUSIONS

The available evidence is limited and does not demonstrate a clear benefit of smartphone applications as interventions for adolescents or adults with overweight or obesity. While the number of studies is growing, the evidence remains incomplete due to the high variability of the apps' features, content and components, which complicates direct comparisons and assessment of their effectiveness. Comparisons with either no or minimal intervention or personal coaching show minor effects, which are mostly not clinically significant. Minimal data for adolescents also warrants further research. Evidence is also scarce for low- and middle-income countries as well as for people with different socio-economic and cultural backgrounds. The 34 ongoing studies suggest sustained interest in the topic, with new evidence expected to emerge within the next two years. In practice, clinicians and healthcare practitioners should carefully consider the potential benefits, limitations, and evolving research when recommending smartphone apps to adolescents and adults with overweight or obesity.

Nutrition and Physical Activity Interventions Provided by Nutrition and Exercise Practitioners for the General Population: An Evidence-Based Practice Guideline From the Academy of Nutrition and Dietetics and American Council on Exercise

A nutritious diet and adequate physical activity vitally contribute to disease prevention, but most adults do not meet population-based dietary and physical activity recommendations. Qualified nutrition and exercise practitioners can address challenges to adopting healthy lifestyle behaviors by providing consistent, individualized, and evidence-based education and programming within their professional scopes of practice to improve client outcomes. The objective of this evidence-based practice guideline is to inform practice decisions for nutrition and exercise practitioners providing nutrition and physical activity interventions for adults who are healthy or have cardiometabolic risk factors, but no diagnosed disease. Evidence from a systematic review was translated to practice recommendations using an evidence-to-decision framework by an interdisciplinary team of nutrition and exercise practitioners and researchers. This evidence-based practice guideline does not provide specific dietary or physical activity recommendations but rather informs nutrition and exercise practitioners how they may utilize existing guidelines for the general population to individualize programming for a range of clients. This evidence-based practice guideline provides widely applicable recommendation statements and a detailed framework to help practitioners implement the recommendations into practice. Common barriers and facilitators encountered when delivering nutrition and physical activity interventions, such as adherence to professional scopes of practice; methods to support behavior change; and methods to support inclusion, diversity, equity, and access, are discussed. Nutrition and exercise practitioners can consistently provide individualized, practical, and evidence-based interventions by seeking to understand their clients' needs, circumstances, and values and by co-creating interventions with the client and their allied health team.

Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework

Mobile Health Interventions (MHIs) have addressed a range of healthcare challenges and have been evaluated using Randomized Controlled Trials (RCTs) to establish clinical effectiveness. Using PRISMA we conducted a systematic literature review of RCTs for MHIs and identified 70 studies which were analyzed and classified using Nickerson-Varshney-Muntermann (NVM) taxonomy. From the resultant iterations of the taxonomy, we extracted insights from the categorized studies. RCTs cover a wide range of health conditions including chronic diseases, general wellness, unhealthy practices, family planning, end-of-life, and post-transplant care. The MHIs that were utilized by the RCTs were varied as well, although most studies did not find significant differences between MHIs and usual care. The challenges for MHI-based RCTs include the use of technologies, delayed outcomes, patient recruitment, patient retention, and complex regulatory requirements. These variances can lead to a higher rate of Type I/Type II errors. Further considerations are the impact of infrastructure, contextual and cultural factors, and reductions in the technological relevancy of the intervention itself. Finally, due to the delayed effect of most outcomes, RCTs of insufficient duration are unable to measure significant, lasting improvements. Using the insights from seventy identified studies, we developed a classification of existing RCTs along with guidelines for MHI-based RCTs and a research framework for future RCTs. The framework offers opportunities for (a) personalization of MHIs, (b) use of richer technologies, and (c) emerging areas for RCTs.

Can Digital Health Solutions Fill in the Gap for Effective Guideline Implementation in Cardiovascular Disease Prevention: Hope or Hype?

PURPOSE OF REVIEW

To evaluate the use of digital health solutions in improving the implementation of cardiovascular disease (CVD) prevention guidelines and review current evidence supporting it.

RECENT FINDINGS

Healthy diet guideline recommendations can be improved by text-messaging programs and apps for reinforcing healthy food intake and reducing unhealthy nutrients purchase and consumption. Wearable activity trackers are also effective in increasing physical activity levels. Text-messaging programs for smoking cessation have demonstrated benefits in increasing quitting rates; however, evidence on smartphone apps for smoking cessation is still lacking. Smartphone apps have the potential to improve medication adherence; however, better quality evidence is needed. Digital pills are another promising digital solution to improve medication adherence. The use of digital health solutions in CVD prevention is an evolving field and, to date, there is an increasing body of evidence that supports that such technologies are effective in improving CVD prevention guideline implementation.

The Effectiveness of Nutritional Education Interventions on Dietary Intake in Young Black Males: A Near-Empty Systematic Review

The incidence of several diet and lifestyle-related diseases, previously seen only in adults, is increasing in prevalence in young people. The Black population, and particularly Black males, are at high risk of developing lifestyle-related diseases. Adolescence and young adulthood are considered a transitional period with increasing independence and responsibility, along with the development of lifelong lifestyle habits. This systematic review aimed to establish which methods and approaches to nutritional education interventions are the most effective in improving the nutritional/dietary intake in healthy young Black males. Eligibility criteria were designed using PICOS and included controlled trials of nutrition education interventions designed to improve dietary intake in healthy young Black or mixed-race males aged 14–21 years old. Medline, Cinahl and Scopus were searched in April 2021, resulting in 20,375 records being screened, and subsequently 72 full-text articles were reviewed. Risk of bias was assessed using the ROBINS-I tool. One study met the eligibility criteria. Results are presented in a narrative format as meta-analysis was not possible. This systematic review revealed a lack of evidence on the effectiveness of nutritional education interventions in this high-risk population. Limitations are noted and recommendations have been made.

Impact of Nutrition and Physical Activity Interventions Provided by Nutrition and Exercise Practitioners for the Adult General Population: A Systematic Review and Meta-Analysis

Healthy dietary intake and physical activity reduce the risk of non-communicable diseases. This systematic review and meta-analysis aimed to examine the effect of interventions including both nutrition and physical activity provided by nutrition and exercise practitioners for adults in the general population (those without diagnosed disease). The MEDLINE, CINAHL, Cochrane Central, Cochrane Database of Systematic Reviews and SportDiscus databases were searched for randomized controlled trials (RCTs) published from 2010 until April 2021. Outcomes included physical activity, fruit and vegetable intake, waist circumference, percent weight loss, quality of life (QoL) and adverse events. Grading of Recommendations Assessment, Development and Evaluation (GRADE) methods were used to synthesize and grade evidence. Meta-analyses were stratified according to participant health status. The database search identified 11,205 articles, and 31 RCTs were included. Interventions increased physical activity amount [standardized mean difference (SMD) (95% CI): 0.25 (0.08, 0.43)] (low certainty evidence); increased vegetable intake [SMD (95% CI): 0.14 (0.05, 0.23)] (moderate certainty evidence); reduced waist circumference [MD (95% CI): −2.16 cm (−2.96, −1.36)] (high certainty evidence); and increased likelihood of achieving 5% weight loss for adults with overweight and obesity [relative risk (95% CI): 2.37 (1.76, 3.19)] (high certainty evidence). Very low and low certainty evidence described little-to-no effect on QoL or adverse events. Nutrition and exercise practitioners play key roles in facilitating positive lifestyle behaviors to reduce cardiometabolic disease risk in adults.

Digital Interventions on Healthy Lifestyle Management: Systematic Review

BACKGROUND

Digital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle.

OBJECTIVE

This study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns).

METHODS

We conducted a systematic literature review to search the scientific databases (Nature, SpringerLink, Elsevier, IEEE Xplore, and PubMed) that included digital interventions on healthy lifestyle, focusing on preventing obesity and being overweight as a prime objective. Peer-reviewed articles published between 2015 and 2020 were included. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a framework for an evidence-based systematic review. Furthermore, we improved the review process by adopting the Rayyan tool and the Scale for the Assessment of Narrative Review Articles.

RESULTS

Our initial searches identified 780 potential studies through electronic and manual searches; however, 107 articles in the final stage were cited following the specified inclusion and exclusion criteria. The identified methods for a successful digital intervention to promote a healthy lifestyle are self-monitoring, self-motivation, goal setting, personalized feedback, participant engagement, psychological empowerment, persuasion, digital literacy, efficacy, and credibility. In this study, we identified existing conceptual frameworks for digital interventions, different approaches to provide digital interventions, associated methods, and execution challenges and their impact on the promotion of healthy lifestyle management.

CONCLUSIONS

This systematic literature review selected intervention principles (rules), theories, design features, ways to determine efficient interventions, and weaknesses in healthy lifestyle management from established digital intervention approaches. The results help us understand how digital interventions influence lifestyle management and overcome the existing shortcomings. It serves as a basis for further research with a focus on designing, developing, testing, and evaluating the generation of personalized lifestyle recommendations as a part of digital health interventions.

Preventing weight gain in adults: A systematic review and meta-analysis of randomized controlled trials

Weight gain prevention is a global public health priority to address escalating adiposity in adults. This review evaluates the efficacy of weight gain prevention trials targeting adults aged 18-50 years and adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Trials of any duration from inception to May 2020 that evaluated a weight gain prevention intervention (using either prescriptive diet, prescriptive physical activity, prescriptive diet, and/or physical activity or non-prescriptive lifestyle) and included weight or body mass index (weight [kg]/height [m² ]) were eligible. Twenty-nine trials across 34 publications (participants n = 37,407) were included. Intervention resulted in less weight gain compared with controls (-1.15 kg [95% CI -1.50, -0.80 kg] p < 0.001). Subgroup analysis demonstrated greater effectiveness with prescriptive (-1.60 kg [95% CI -2.00, -1.19] p < 0.001) compared with non-prescriptive (-0.81 kg [95% CI 1.10, -0.53] p < 0.001) intervention types. Interventions had greatest impact in healthy weight (18.5-24.9 kg/m² ) (-0.82 kg [95% CI -1.5, -0.50] p < 0.001) or overweight (25.0-29.9 kg/m² ) (-1.48 kg [95% CI -1.85, -1.12] p < 0.001) compared with obese populations (≥30.0 kg/m² ) (-0.56 kg [95% CI -1.40, 0.27] p = 0.19). These findings demonstrate that lifestyle intervention prevents cumulative weight gain in non-obese adults, with future research required to inform cost-effectiveness and implementation feasibility.

Nutrition and physical activity interventions for the general population with and without cardiometabolic risk: a scoping review

OBJECTIVE

The objective of this scoping review was to examine the research question: In the adults with or without cardiometabolic risk, what is the availability of literature examining interventions to improve or maintain nutrition and physical activity-related outcomes? Sub-topics included: (1) behaviour counseling or coaching from a dietitian/nutritionist or exercise practitioner, (2) mobile applications to improve nutrition and physical activity and (3) nutritional ergogenic aids.

DESIGN

The current study is a scoping review. A literature search of the Medline Complete, CINAHL Complete, Cochrane Database of Systematic Reviews and other databases was conducted to identify articles published in the English language from January 2005 until May 2020. Data were synthesised using bubble charts and heat maps.

SETTING

Out-patient, community and workplace.

PARTICIPANTS

Adults with or without cardiometabolic risk factors living in economically developed countries.

RESULTS

Searches resulted in 19 474 unique articles and 170 articles were included in this scoping review, including one guideline, thirty systematic reviews (SR), 134 randomised controlled trials and five non-randomised trials. Mobile applications (n 37) as well as ergogenic aids (n 87) have been addressed in several recent studies, including SR. While primary research has examined the effect of individual-level nutrition and physical activity counseling or coaching from a dietitian/nutritionist and/or exercise practitioner (n 48), interventions provided by these practitioners have not been recently synthesised in SR.

CONCLUSION

SR of behaviour counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner are needed and can inform practice for practitioners working with individuals who are healthy or have cardiometabolic risk.

Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions With Information and Communication Technology: Systematic Review

BACKGROUND

We systematically reviewed the literature on human coaching to identify different coaching processes as behavioral interventions and methods within those processes. We then reviewed how those identified coaching processes and the used methods can be utilized to improve an electronic coaching (eCoaching) process for the promotion of a healthy lifestyle with the support of information and communication technology (ICT).

OBJECTIVE

This study aimed to identify coaching and eCoaching processes as behavioral interventions and the methods behind these processes. Here, we mainly looked at processes (and corresponding models that describe coaching as certain processes) and the methods that were used within the different processes. Several methods will be part of multiple processes. Certain processes (or the corresponding models) will be applicable for both human coaching and eCoaching.

METHODS

We performed a systematic literature review to search the scientific databases EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MDPI, Google Scholar, and PubMed for publications that included personal coaching (from 2000 to 2019) and persuasive eCoaching as behavioral interventions for a healthy lifestyle (from 2014 to 2019). The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework was used for the evidence-based systematic review and meta-analysis.

RESULTS

The systematic search resulted in 79 publications, including 72 papers and seven books. Of these, 53 were related to behavioral interventions by eCoaching and the remaining 26 were related to human coaching. The most utilized persuasive eCoaching methods were personalization (n=19), interaction and cocreation (n=17), technology adoption for behavior change (n= 17), goal setting and evaluation (n=16), persuasion (n=15), automation (n=14), and lifestyle change (n=14). The most relevant methods for human coaching were behavior (n=23), methodology (n=10), psychology (n=9), and mentoring (n=6). Here, "n" signifies the total number of articles where the respective method was identified. In this study, we focused on different coaching methods to understand the psychology, behavioral science, coaching philosophy, and essential coaching processes for effective coaching. We have discussed how we can integrate the obtained knowledge into the eCoaching process for healthy lifestyle management using ICT. We identified that knowledge, coaching skills, observation, interaction, ethics, trust, efficacy study, coaching experience, pragmatism, intervention, goal setting, and evaluation of coaching processes are relevant for eCoaching.

CONCLUSIONS

This systematic literature review selected processes, associated methods, strengths, and limitations for behavioral interventions from established coaching models. The identified methods of coaching point toward integrating human psychology in eCoaching to develop effective intervention plans for healthy lifestyle management and overcome the existing limitations of human coaching.

Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks

The importance of eating behavior risk factors in the primary prevention of obesity has been established. Researchers mostly use the linear model to determine associations among these risk factors. However, in reality, the presence of nonlinearity among these factors causes a bias in the prediction models. The aim of this study was to explore the potential of a hybrid model to predict the eating behaviors. The hybrid model of structural equation modelling (SEM) and artificial neural networks (ANN) was applied to evaluate the prediction model. The SEM analysis was used to check the relationship of the emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) and their effect on different categories of eating behavior patterns (EBP). In the second step, the input and output required for ANN analysis were obtained from SEM analysis and were applied in the neural network model. 340 university students participated in this study. The hybrid model (SEM-ANN) was conducted using multilayer perceptron (MLP) with feed-forward network topology. Moreover, Levenberg–Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The tangent/sigmoid function was used for the input layer, while the linear function was applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) were calculated. Using the hybrid model, the optimal network happened at MLP 3-17-8. It was proved that the hybrid model was superior to SEM methods because the R² of the model was increased by 27%, while the MSE was decreased by 9.6%. Moreover, it was found that BSC, BAS, and EES significantly affected healthy and unhealthy eating behavior patterns. Thus, a hybrid approach could be suggested as a significant methodological contribution from a machine learning standpoint, and it can be implemented as software to predict models with the highest accuracy.

Baseline Psychosocial and Demographic Factors Associated with Study Attrition and 12-Month Weight Gain in the DIETFITS Trial

OBJECTIVE

The purpose of this study was to examine correlates of failure-trial attrition and weight gain-in a randomized clinical weight-loss trial.

METHODS

The Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial included 609 adults (18-50 years; BMI 28-40). Participants were randomized to a 12-month healthy low-fat or healthy low-carbohydrate diet for weight loss. At baseline, participants completed psychosocial, demographic, and anthropometric measures. Stepwise logistic regressions identified baseline factors associated with (1) study attrition and (2) among trial completers, weight gain at 12 months.

RESULTS

Having higher baseline food addiction and self-efficacy was linked to treatment failure. Being younger, not having a college education, having higher outcome expectations and quality of life, and having lower social functioning and self-control increased the odds of trial attrition. Identifying as other than non-Hispanic white; not being married or cohabitating; having higher cognitive restraint and self-control; and having lower amotivation, family encouragement, and physical limitations increased the odds of gaining weight by treatment's end.

CONCLUSIONS

Participants' baseline psychosocial and demographic factors may support or impede successful weight loss. Trialists should attend to these factors when designing treatments in order to promote participants' likelihood of completing the trial and achieving their weight-loss goals.

Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults

Assessing the implementation of nutrition interventions is important to identify characteristics and dietary patterns of individuals who benefit most. The aim was to report on young adults' experiences of receiving dietary feedback text messaging intervention. Diet was captured using an image-based 4-day mobile food recordTM application (mFRTM) and assessed to formulate two tailored feedback text messages on fruit and vegetables and energy-dense nutrient-poor (EDNP) foods and beverages. At 6-months 143 participants completed a second mFRTM and a questionnaire evaluating the dietary feedback. Participants who agreed the text messages made them think about how much vegetables they ate were more likely to increase their intake by at least half a serve than those who disagreed [odds ratio (OR) = 4.28, 95% Confidence Interval (CI): 1.76 to 10.39]. Those who agreed the text messages made them think about how much EDNP foods they ate, were twice as likely to decrease their intake by over half a serve (OR = 2.39, 95%CI: 1.12 to 5.25) than those who disagreed. Undertaking detailed dietary assessment ensured the tailored feedback was constructive and relevant. Personal contemplation about vegetable and EDNP food intake appears to be a mediator of dietary change in young adults.

Diet Quality in a Weight Gain Prevention Trial of Reproductive Aged Women: A Secondary Analysis of a Cluster Randomized Controlled Trial

Reproductive-aged women are at high risk for obesity development. Limited research exploring weight gain prevention initiatives and associated modifiable risk factors, including diet quality exists. In a secondary analysis of a 12 month, cluster randomized controlled trial for weight gain prevention in reproductive-aged women, we evaluated change in diet quality, macronutrient and micronutrient intake, predictors of change and associations with weight change at follow-up. Forty-one rural towns in Victoria, Australia were randomized to a healthy lifestyle intervention (n = 21) or control (n = 20). Women aged 18⁻50, of any body mass index and without conditions known to affect weight, were recruited. Diet quality was assessed by the Dietary Guideline Index (DGI) and energy, macronutrient, and micronutrient intake as well as anthropometrics (weight; kg) were measured at baseline and 12 months. Results were adjusted for group (intervention/control), town cluster, and baseline values of interest. Of 409 women with matched data at baseline and follow-up, 220 women were included for final analysis after accounting for plausible energy intake. At 12 months, diet quality had improved by 6.2% following the intervention, compared to no change observed in the controls (p < 0.001). Significant association was found between a change in weight and a change in diet quality score over time β -0.66 (95%CI -1.2, -0.12) p = 0.02. The percentage of energy from protein (%) 0.009 (95%CI 0.002, 0.15) p = 0.01 and glycemic index -1.2 (95%CI -2.1, -0.24) p = 0.02 were also improved following the intervention, compared to the control group. Overall, a low-intensity lifestyle intervention effectively improves diet quality, with associated weight gain preventions, in women of reproductive age.

The Relationship between Vegetable Intake and Weight Outcomes: A Systematic Review of Cohort Studies

The relationship between vegetable consumption and measures of adiposity was assessed in cohort studies. Seven databases were searched from inception until February 2018. The quality of individual studies was assessed using the Joanna Briggs Institute Critical Appraisal of Cohort Studies tool. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was applied to determine the quality of the body of evidence. Ten studies were included. Six measured change in vegetable intake over time. Two showed that increasing vegetable consumption resulted in weight loss of 0.09⁻0.1 kg over four years (p < 0.001). Increased vegetable intake was also associated with a reduced risk of weight gain and overweight or obesity (Odds ratios (ORs) ranged from 0.18 to 0.88) in other studies. Four studies measured vegetable intake at the baseline only. One showed that intakes >4 servings/day reduced the risk of weight gain (OR 0.27 (95% confidence interval (CI) 0.08⁻0.99) and another found an inverse association with waist circumference in women (-0.36 cm per vegetable serving/day). This review provides moderate quality evidence for an inverse association between vegetable intake and weight-related outcomes in adults. When these findings are coupled with no apparent harm from vegetable consumption, the evidence-base can be used with acceptable confidence to guide practice and policy.

Good intentions are not enough: how informatics interventions can worsen inequality

Health informatics interventions are designed to help people avoid, recover from, or cope with disease and disability, or to improve the quality and safety of healthcare. Unfortunately, they pose a risk of producing intervention-generated inequalities (IGI) by disproportionately benefiting more advantaged people. In this perspective paper, we discuss characteristics of health-related interventions known to produce IGI, explain why health informatics interventions are particularly vulnerable to this phenomenon, and describe safeguards that can be implemented to improve health equity. We provide examples in which health informatics interventions produced inequality because they were more accessible to, heavily used by, adhered to, or effective for those from socioeconomically advantaged groups. We provide a brief outline of precautions that intervention developers and implementers can take to guard against creating or worsening inequality through health informatics. We conclude by discussing evaluation approaches that will ensure that IGIs are recognized and studied.

Mediators of two selective prevention interventions targeting both obesity and eating disorders

The present study tested hypothesized mechanisms underlying the effects of two selective prevention interventions targeting both obesity and eating disorders (Healthy Weight and the newly developed Project Health), relative to video control. Tests examined mediation for the significant weight gain prevention and eating disorder symptom prevention effects previously reported. College students (N = 364; 72% women) with weight concerns were randomized to condition and assessed for 2-years post-intervention. Project Health participants had significant improvements in 2 of the 7 proposed mediators relative to comparisons (i.e., cognitive dissonance, the unhealthy Western dietary pattern) but change in these variables did not mediate its effect on long-term BMI change. Two variables emerged as full mediators of the eating disorder prevention effects for both experimental interventions: body dissatisfaction and negative affect. Analyses failed to support the exploratory hypothesis that change in eating disorder symptoms mediated the effects of condition on BMI gain. This report is the among the first to examine mediation for programs aimed at preventing both weight gain and eating disorders, particularly in mixed-gender groups. Mediational analyses are essential in identifying the mechanism of intervention action, which can inform improvements to prevention programs.

Effectiveness of lifestyle interventions for preventing harmful weight gain among young adults from lower socioeconomic status and ethnically diverse backgrounds: a systematic review

The incidence of overweight and obesity are increasing with each successive generation of young adults. Associated co-morbidities will emerge at an earlier age unless weight gain is prevented. Evidence has demonstrated young adults (aged 18-35 years) from low socioeconomic and ethnically diverse backgrounds are at greater risk of overweight or obesity, yet it is unclear how to effectively intervene in this population. This systematic review aimed to assess the effectiveness of lifestyle interventions conducted in this population. Thirty studies reporting on lifestyle interventions for prevention of weight gain were identified from eight electronic databases searched. Six interventions included subgroup analyses to determine if ethnicity moderated weight change, and two included subgroup analyses to determine if socioeconomic status had an effect on change in weight. Five of these six studies were effective in preventing weight gain, and subgroup analyses showed no differences in effect by ethnicity. Of these five studies, two included a subgroup analysis that showed socioeconomic status to have no effect on weight outcome. Despite the promising results from these five lifestyle interventions utilizing online and mobile components to effectively reach and prevent weight gain in this priority population, the evidence base of high quality trials is limited.

Causal Analysis of Self-tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials

Many of an individual's historically recorded personal measurements vary over time, thereby forming a time series (e.g., wearable-device data, self-tracked fitness or nutrition measurements, regularly monitored clinical events or chronic conditions). Statistical analyses of such n-of-1 (i.e., single-subject) observational studies (N1OSs) can be used to discover possible cause-effect relationships to then self-test in an n-of-1 randomized trial (N1RT). However, a principled way of determining how and when to interpret an N1OS association as a causal effect (e.g., as if randomization had occurred) is needed.Our goal in this paper is to help bridge the methodological gap between risk-factor discovery and N1RT testing by introducing a basic counterfactual framework for N1OS design and personalized causal analysis.We introduce and characterize what we call the average period treatment effect (APTE), i.e., the estimand of interest in an N1RT, and build an analytical framework around it that can accommodate autocorrelation and time trends in the outcome, effect carryover from previous treatment periods, and slow onset or decay of the effect. The APTE is loosely defined as a contrast (e.g., difference, ratio) of averages of potential outcomes the individual can theoretically experience under different treatment levels during a given treatment period. To illustrate the utility of our framework for APTE discovery and estimation, two common causal inference methods are specified within the N1OS context. We then apply the framework and methods to search for estimable and interpretable APTEs using six years of the author's self-tracked weight and exercise data, and report both the preliminary findings and the challenges we faced in conducting N1OS causal discovery.Causal analysis of an individual's time series data can be facilitated by an N1RT counterfactual framework. However, for inference to be valid, the veracity of certain key assumptions must be assessed critically, and the hypothesized causal models must be interpretable and meaningful.

Educational nutrition messaging at breakfast reduces snack intake and influences snack preferences in adult men and women

Breakfast skipping is associated with increased risk of weight gain and obesity in young adults, possibly due to increased snacking later in the day. Recent research suggests that providing and animal versus a plant source of protein at breakfast can reduce snack intake later in the day. In addition, providing nutrition information via a nutrition label, front-of-pack information, or via text messaging has been shown to help individuals make healthier food choices. The objective of this study was to determine if educational nutrition messaging and protein source influenced snack intake 2 h following the breakfast meal. Participants (n = 33) were randomly assigned to one of two groups: educational nutrition messaging (EM; n = 16) or no messaging (NM; n = 17) group. The study was conducted using a randomized, cross-over design in which each participant received each of two breakfast beverages, whey protein- (WP) and pea protein (PP)- based. Appetite was assessed at 0, 15, 30, 60, 90, and 120 min after each test breakfast using visual analog scales. Participants were then provided with a selection of healthy and unhealthy snacks for 60 min. There was no effect of protein source on appetite or snack intake. However, participants presented with EM had reduced snack intake over the snacking period compared to NM (P = 0.058) and, of the snacks consumed, the EM group consumed a higher percentage of healthy versus unhealthy snacks compared to NM (P < 0.0001), resulting in lower calorie intake. Taken together these data suggest that protein source, as part of a higher protein breakfast, does not affect appetite response or snack intake, but EM may help play a role in reducing snack intake between meals.

Social Determinants and Poor Diet Quality of Energy-Dense Diets of Australian Young Adults

This research aimed to determine the diet quality and socio-demographic determinants by level of energy-density of diets of Australian young adults. Secondary analysis of the Australian National Nutrition and Physical Activity Survey-2011/2012 for adults aged 18–34 years (n = 2397) was conducted. Diet was assessed by 24-h recalls. Dietary energy-density was calculated as dietary energy/grams of food (kJ/g) and the Healthy-Eating-Index-for-Australians (HEIFA-2013) was used to assess diet quality (highest score = 100). Dietary energy-density was examined with respect to diet quality and sociodemographic determinants including gender, highest tertiary-education attainment, country-of-birth, age, income, and socio-economic-index-for-area (SEIFA). Higher dietary energy-density was associated with lower diet quality scores (β = −3.71, t (2394) = −29.29, p < 0.0001) and included fewer fruits and vegetables, and more discretionary foods. The mean dietary energy-density was 7.7 kJ/g and 7.2 kJ/g for men and women, respectively. Subpopulations most at risk of consuming high energy-dense diets included those with lower education, Australian and English-speaking countries of birth, and men with low income and women from areas of lower socio-economic status. Young adults reporting low energy-dense diets had higher quality diets. Intensive efforts are needed to reduce the high energy-density of young adults’ diets, and should ensure they include populations of lower socio-economic status.

Opportunities of mHealth in Preconception Care: Preferences and Experiences of Patients and Health Care Providers and Other Involved Professionals

Background

The importance of the preconception period and preconception care (PCC) are broadly acknowledged and the potential benefits regarding health promotion have been studied extensively. PCC provides the opportunity to identify, prevent, and treat modifiable and nonmodifiable risk factors to optimize the health of couples trying to become pregnant. The prevalence of modifiable and nonmodifiable risk factors in these couples is high, but the uptake of PCC remains low.

Objective

The aim of this study is to identify the preferences and experiences of women and men (patients) trying to become pregnant and of health care providers and other involved professionals regarding mobile health (mHealth), in particular the coaching platform Smarter Pregnancy, and its potential role in PCC.

Methods

Patients who participated in the Smarter Pregnancy randomized controlled trial (RCT) and health care providers and professionals also involved in PCC were invited to participate in a qualitative study. The barriers, benefits, and opportunities of big data collection by mHealth were discussed in focus group sessions, prompted with statements regarding PCC.

Results

We composed five focus groups, consisting of 27 patients in total (23 women and 4 men), who participated in the RCT, and nine health care providers and other professionals. Of the patients, 67% (18/27) were familiar with the concept of PCC, but only 15% (4/27) received any form of PCC. A majority of 56% (combined percentages of statements 1 [n=18], 2 [n=11], and 3 [n=16]) of the patients believed in the benefit of receiving PCC, and all agreed that men should be involved in PCC as well. Patients did not have a problem using anonymized data obtained from mHealth tools for scientific purposes. Patients and health care providers and other professionals both acknowledged the lack of awareness regarding the importance of PCC and stated that mHealth provides several opportunities to support clinical PCC.

Conclusions

Our findings substantiate previous studies addressing the low uptake of PCC due to unawareness or lack of perception of its relevance by couples who are trying to become pregnant. The positive judgment and experiences with mHealth, in particular Smarter Pregnancy, will stimulate future research and further development of effective and cost-effective personalized mHealth apps for patients, health care providers, and other professionals as an add-on to clinical PCC.

The fruit and vegetable intake of young Australian adults: a population perspective

OBJECTIVE

To examine intakes and variety of fruit and vegetables consumed by Australian young adults, also assessing differences by meal occasion and sociodemographic characteristics.

DESIGN

Secondary analysis of cross-sectional 24 h recall data collected through the 2011-12 National Nutrition and Physical Activity Survey. Crude means and proportions consuming fruits and vegetables were calculated. Pearson χ 2 tests, Kruskal-Wallis analyses and linear regression models were used to assess differences in mean intakes by age, BMI and sociodemographic variables. The variety eaten was determined based on the number of fruit and vegetable subgroups consumed.

SETTING

Representative sample of metropolitan and rural areas across Australia.

SUBJECTS

Respondents aged 18-34 years were included (n 2397).

RESULTS

Mean daily intake of fruit (128 g/0·9 servings) and vegetables (205 g/2·7 servings) was lower than the minimum recommended intake set at 2 and 5 servings, respectively. Age was positively associated with fruit and vegetable intake (P=0·002, P<0·001), with 18-24-year-olds reporting the poorest vegetable variety compared with 25-29- and 30-34-year-olds (P=0·002). When controlling for total energy, males consumed less vegetables than females (P=0·002). A large proportion of the 15 % of respondents who consumed adequate amounts of fruits and vegetables on the day prior to the survey reported intake across all meal occasions (P<0·001).

CONCLUSIONS

Fruit and vegetable intake is suboptimal among Australian young adults. An age-appropriate campaign is recommended to target increased consumption, particularly for those aged 18-24 years, with opportunity to promote increased variety and consumption across the day.