A Mobile Phone-Based Program to Promote Healthy Behaviors Among Adults With Prediabetes Who Declined Participation in Free Diabetes Prevention Programs: Mixed-Methods Pilot Randomized Controlled Trial

Implementation and Evaluation of an Automated Text Message-Based Diabetes Prevention Program for Adults With Pre-diabetes

BACKGROUND

Despite the efficacy of diabetes prevention programs, only an estimated 5% of people with pre-diabetes actually participate. Mobile health (mHealth) holds promise to engage patients with pre-diabetes into lifestyle modification programs by decreasing the referral burden, centralizing remote enrollment, removing the physical requirement of a brick-and-mortar location, lowering operating costs through automation, and reducing time and transportation barriers.

METHODS

Non-randomized implementation study enrolling patients with pre-diabetes from a large health care organization. Patients were exposed to a text message-based program combining live human coaching guidance and support with automated scheduled, interactive, data-driven, and on-demand messages. The primary analysis examined predicted weight outcomes at 6 and 12 months. Secondary outcomes included predicted changes in HbA1c and minutes of exercise at 6 and 12 months.

RESULTS

Of the 163 participants included in the primary analysis, participants had a mean predicted weight loss of 5.5% at six months (P < .001) and of 4.3% at 12 months (P < .001). We observed a decrease in predicted HbA1c from 6.1 at baseline to 5.8 at 6 and 12 months (P < .001). Activity minutes were statistically similar from a baseline of 155.5 minutes to 146.0 minutes (P = .567) and 142.1 minutes (P = .522) at 6 and 12 months, respectively, for the overall cohort.

CONCLUSIONS

In this real-world implementation of the myAgileLife Diabetes Prevention Program among patients with pre-diabetes, we observed significant decreases in weight and HbA1c at 6 and 12 months. mHealth may represent an effective and easily scalable potential solution to deliver impactful diabetes prevention curricula to large numbers of patients.

A systematic review of the mechanisms influencing engagement in diabetes prevention programmes for people with pre-diabetes

AIMS

To identify barriers and enablers that influence engagement in and acceptability of diabetes prevention programmes for people with pre-diabetes. The results will provide insights for developing strategies and recommendations to improve design and delivery of diabetes prevention programmes with enhanced engagement and acceptability for people with pre-diabetes.

METHODS

This review used a critical realist approach to examine context and mechanisms of diabetes prevention programmes. Medline, Embase, PsycInfo, Cinahl, Web of Science, Scopus and Pre-Medline were searched for English language studies published between 2000 and 2023. A quality assessment was conducted using Joanna Briggs Institute critical appraisal tools.

RESULTS

A total of 90 papers met inclusion criteria. The included studies used a variety of quantitative and qualitative methodologies. Data extracted focused on barriers and enablers to engagement in and acceptability of diabetes prevention programmes, with seven key mechanisms identified. These included financial, environmental, personal, healthcare, social and cultural, demographic and programme mechanisms. Findings highlighted diverse factors that influenced engagement in preventive programmes and the importance of considering these factors when planning, developing and implementing future diabetes prevention programmes.

CONCLUSIONS

Mechanisms identified in this review can inform design and development of diabetes prevention programmes for people with pre-diabetes and provide guidance for healthcare professionals and policymakers. This will facilitate increased participation and engagement in preventive programmes, potentially reducing progression and/or incidence of pre-diabetes to type 2 diabetes and improving health outcomes.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Digital interventions for self-management of prediabetes: A scoping review

BACKGROUND

Rates of prediabetes, which can lead to type 2 diabetes, are increasing worldwide. Interventions for prediabetes mainly focus on lifestyle changes to diet and exercise. While these interventions are effective, they are often delivered face-to-face, which may pose a barrier to those with limited access to healthcare. Given the evidence for digital interventions addressing other noncommunicable diseases, these may also be effective for prediabetes self-management. The aim of this scoping review was to assess the breadth of evidence around digital interventions for prediabetes self-management.

METHODS

We developed a targeted search strategy and relevant studies were identified through searches conducted in four bibliographic databases (Medline, Embase, PsycInfo, and Scopus). Published studies were eligible if they included a digital intervention to support adults aged 18+ with prediabetes self-management. Titles and abstracts were first screened for relevance by one researcher. Full texts of selected records were assessed against the review criteria independently by two researchers for inclusion in the final analysis.

RESULTS

Twenty-nine studies were included, of which nine were randomised controlled trials. Most efficacy studies reported significant changes in at least one primary and/or secondary outcome, including participants' glycaemic control, weight loss and/or physical activity levels. About one-third of studies reported mixed outcomes or early significant outcomes that were not sustained at long-term follow-up. Interventions varied in length, digital modalities, and complexity. Delivery formats included text messages, mobile apps, virtually accessible dietitians/health coaches, online peer groups, and web-based platforms. Approximately half of studies assessed participant engagement/acceptability outcomes.

CONCLUSION

Whilst the evidence here suggests that digital interventions to support prediabetes self-management are acceptable and have the potential to reduce one's risk of progression to type 2 diabetes, more research is needed to understand which interventions, and which components specifically, have the greatest reach to diverse populations, are most effective at promoting user engagement, and are most effective in the longer term.

Mobile App Intervention of a Randomized Controlled Trial for Patients With Obesity and Those Who Are Overweight in General Practice: User Engagement Analysis Quantitative Study

BACKGROUND

The Health eLiteracy for Prevention in General Practice trial is a primary health care-based behavior change intervention for weight loss in Australians who are overweight and those with obesity from lower socioeconomic areas. Individuals from these areas are known to have low levels of health literacy and are particularly at risk for chronic conditions, including diabetes and cardiovascular disease. The intervention comprised health check visits with a practice nurse, a purpose-built patient-facing mobile app (mysnapp), and a referral to telephone coaching.

OBJECTIVE

This study aimed to assess mysnapp app use, its user profiles, the duration and frequency of use within the Health eLiteracy for Prevention in General Practice trial, its association with other intervention components, and its association with study outcomes (health literacy and diet) to determine whether they have significantly improved at 6 months.

METHODS

In 2018, a total of 22 general practices from 2 Australian states were recruited and randomized by cluster to the intervention or usual care. Patients who met the main eligibility criteria (ie, BMI>28 in the previous 12 months and aged 40-74 years) were identified through the clinical software. The practice staff then provided the patients with details about this study. The intervention consisted of a health check with a practice nurse and a lifestyle app, a telephone coaching program, or both depending on the participants' choice. Data were collected directly through the app and combined with data from the 6-week health check with the practice nurses, the telephone coaching, and the participants' questionnaires at baseline and 6-month follow-up. The analyses comprised descriptive and inferential statistics.

RESULTS

Of the 120 participants who received the intervention, 62 (52%) chose to use the app. The app and nonapp user groups did not differ significantly in demographics or prior recent hospital admissions. The median time between first and last app use was 52 (IQR 4-95) days, with a median of 5 (IQR 2-10) active days. App users were significantly more likely to attend the 6-week health check (2-sided Fisher exact test; P<.001) and participate in the telephone coaching (2-sided Fisher exact test; P=.007) than nonapp users. There was no association between app use and study outcomes shown to have significantly improved (health literacy and diet) at 6 months.

CONCLUSIONS

Recruitment and engagement were difficult for this study in disadvantaged populations with low health literacy. However, app users were more likely to attend the 6-week health check and participate in telephone coaching, suggesting that participants who opted for several intervention components felt more committed to this study.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12617001508369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373505.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2018-023239.

Adults' perceived health promotion needs in the prediabetes stage: a meta-synthesis study

Introduction

One of the methods to promote pre-diabetic patients' adherence to preventive behaviors and improving their lifestyle is to pay attention to their needs in the designed educational programs. Therefore, this study was conducted with the aim of identifying the needs of individuals with prediabetes.

Methodology

Three databases, including ISI/Web of Sciences, PubMed, Scopus were searched without time limitation until August 2022. The quality of the included studies was assessed using the Critical Appraisal Skills Programme tool. This study was reported according to the Enhancing Transparency in Reporting the Synthesis of Qualitative Research guidelines and to achieve the research goal, Sandelowski and Barroso's seven-step meta-synthesis method (2007) was used. Thematic synthesis was used to analyses the data.

Results

Out of the 1934 studies obtained, 34 studies were finally examined and 805 codes were recorded based on the extracted data. Through synthesizing and analyzing the primary studies, 8 main themes were extracted regarding individuals' needs in the prediabetes stage: Information needs, Cultural needs, psychological needs, Social support needs, Education needs, Financial needs, Service needs and Skill needs.

Discussion and Conclusions

The perceived needs and their types in each of the dimensions in detail can be a proper guide for designing educational programs and various interventions to control the prediabetes condition, leading to a reduction in the prevalence of type 2 diabetes in the society.

The characteristics and acceptance of Technology-Enabled diabetes prevention programs (t-DPP) amongst individuals with prediabetes: A scoping review

AIM AND OBJECTIVE

As rising global prevalence of diabetes burdens an overstrained healthcare system, it would be prudent to employ primary prevention strategies. This review aims to detail characteristics of technology-enabled diabetes prevention programs (t-DPP) and the technology acceptance amongst prediabetic individuals.

DESIGN

A scoping review.

REVIEW METHODS

Summative and direct content analysis.

DATA SOURCES

Seven electronic databases-PubMed, Cochrane, Embase, CINAHL, Scopus, PsycINFO and Web of Science-were searched from inception till 9 June 2022 for primary studies conducted on t-DPP. Initial search identified 2412 unique articles. Removal of duplicates and irrelevant articles resulted in 58 full text articles screened and 17 articles meeting the eligibility criteria. There was no limitation to study type or year of publication, but language was limited to English.

RESULTS

Common t-DPP characteristics include physical activity (n = 17), diet control (n = 16), coaching (n = 12), social support (n = 9) and skills acquisition (n = 12). Technological acceptance of t-DPPs were generally positive as participants found them useful (n = 5) and easy to use (n = 4), with majority of the participants interested (n = 5) and engaging well with it (n = 13). However, personal-, design- and technological-level factors were found to negatively influence t-DPPs acceptance.

CONCLUSION

This review reported a generally positive technological acceptance. The result encourages remote delivery of diabetes prevention programs, offering researchers a guide to t-DPP development. However, it also highlights the need for integration of behavioural change theories and socio-cultural considerations, with gaps in knowledge amongst men and young adults.

IMPLICATIONS FOR NURSING

The success of t-DPP can reinforce clinical advice and sustain health behaviours advocated by nurses. Involvement of diabetes-trained nurses would enable continual risk assessment, monitoring and timely intervention to prevent diabetes and potential complications.

REPORTING METHOD

PRISMA-ScR checklist.

Using Peer Support to Prevent Diabetes: Results of a Pragmatic RCT

INTRODUCTION

High-contact structured diabetes prevention programs are effective in lowering weight and HbA1cs, yet their intensity level can create barriers to participation. Peer support programs improve clinical outcomes among adults with Type 2 diabetes, but their effectiveness in diabetes prevention is unknown. This study examined whether a low-intensity peer support program improved outcomes more than enhanced usual care in a diverse population with prediabetes.

STUDY DESIGN

The intervention was tested in a pragmatic 2-arm RCT.

SETTING/PARTICIPANTS

Participants were adults with prediabetes at three healthcare centers.

INTERVENTION

Participants randomized to the enhanced usual care arm received educational materials. Participants in the Using Peer Support to Aid in Prevention and Treatment in Prediabetes arm were matched with a peer supporter: another patient who had made healthy lifestyle changes and was trained in autonomy-supportive action planning. Peer supporters were instructed to provide weekly telephone support to their peers on specific action steps toward behavioral goals for 6 months, then monthly support for 6 months.

MAIN OUTCOME MEASURES

Changes in primary outcomes of weight and HbA1c and secondary outcomes of enrollment in formal diabetes prevention programs, self-reported diet, physical activity, health-specific social support, self-efficacy, motivation, and activation at 6 and 12 months were examined.

RESULTS

Data collection occurred from October 2018 to March 2022, with analyses completed in September 2022. Among 355 randomized patients, in intention-to-treat analyses, there were no between-group differences in HbA1c or weight changes at 6 and 12 months. Using Peer Support to Aid in Prevention and Treatment in Prediabetes participants were more likely to enroll in structured programs at 6 (AOR=2.45, p=0.009) and 12 (AOR=2.21, p=0.016) months and to report eating whole grains at 6 (4.49, p=0.026) and 12 (4.22, p=0.034) months. They reported greater improvements in perceived social support for diabetes prevention behaviors at 6 (6.39, p<0.001) and 12 (5.48, p<0.001) months, with no differences in other measures.

CONCLUSIONS

A stand-alone, low-intensity peer support program improved social support and participation in formal diabetes prevention programs but not weight or HbA1c. It will be important to examine whether peer support could effectively complement higher-intensity, structured diabetes prevention programs.

TRIAL REGISTRATION

This trial is registered at ClinicalTrials.gov, NCT03689530. Full protocol available at https://clinicaltrials.gov/ct2/show/NCT03689530.

A very low-carbohydrate diabetes prevention program for veterans with prediabetes: a single-arm mixed methods pilot study

Introduction

All Veterans Affairs (VA) Medical Centers offer the MOVE! Weight Management Program to help patients achieve and maintain a healthy weight through a calorie-restricted, low-fat diet and increased physical activity. Yet, most MOVE! participants do not achieve clinically significant weight loss of ≥5%. A carbohydrate-restricted diet may help more Veterans to achieve ≥5% weight loss.

Methods

This was a single-arm explanatory sequential mixed methods pilot study conducted in one VA health care system. Veterans with prediabetes and body mass index ≥25 kg/m2 were invited to participate in a group-based, virtual, very low-carbohydrate Diabetes Prevention Program (VLC-DPP) consisting of 23 sessions over 12 months. Participants were taught to follow a very low-carbohydrate eating pattern, defined as 20-35 grams of net carbohydrates per day. The primary outcomes were measures of feasibility and acceptability, including program uptake and session attendance. Secondary outcomes included change in weight, hemoglobin A1c, lipids, and patient-reported measures of food cravings, stress eating, perceived health status, and motivation. Interviews were conducted at 6 months to identify factors that facilitated or hindered participants' achievement of ≥5% weight loss.

Results

Among 108 screened Veterans, 21 enrolled in the study (19%), and 18 were included in the analytic cohort. On average, participants attended 12.4/16 weekly sessions and 3.6/8 bimonthly or monthly sessions. At 12 months, mean percent weight loss was 9.4% (SD = 10.7) with 9 participants (50%) achieving ≥5% weight loss. Three factors facilitated achievement of ≥5% weight loss among 10/16 interviewees: (1) enjoyment of low-carbohydrate foods; (2) careful monitoring of carbohydrate intake; and (3) reduced hunger and food cravings. Three factors hindered achievement of ≥5% weight loss among 6/16 interviewees: (1) food cravings, particularly for sweets; (2) challenges with maintaining a food log; and (3) difficulty with meal planning.

Conclusion

A VLC-DPP is feasible and acceptable and shows preliminary efficacy among Veterans with prediabetes. The program's weight loss effectiveness compared to standard MOVE! should be evaluated in a larger-scale trial. Such a program may be offered in addition to the standard MOVE! program to expand the menu of evidence-based lifestyle counseling options for Veterans.

Clinical Trial Registration

https://clinicaltrials.gov/ct2/show/NCT04881890, identifier NCT04881890.

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

BACKGROUND

Cardiovascular disease, cancer, diabetes mellitus, and obesity are common chronic diseases, and their prevalence is reaching an epidemic level worldwide. As the impact of chronic diseases continues to increase, finding strategies to improve care, access to care, and patient empowerment becomes increasingly essential. Health care providers use mobile health (mHealth) to access clinical information, collaborate with care teams, communicate over long distances with patients, and facilitate real-time monitoring and interventions. However, these apps focus on improving general health care concerns, with limited apps focusing on specific chronic diseases and the nutrition involved in the disease state. Hence, available evidence on the effectiveness of mHealth apps toward behavior change to improve chronic disease outcomes is limited.

OBJECTIVE

The objective of this scoping review was to provide an overview of behavior change effectiveness using mHealth nutrition interventions in people with chronic diseases (ie, cardiovascular disease, diabetes mellitus, cancer, and obesity). We further evaluated the behavior change techniques and theories or models used for behavior change, if any.

METHODS

A scoping review was conducted through a systematic literature search in the MEDLINE, EBSCO, PubMed, ScienceDirect, and Scopus databases. Studies were excluded from the review if they did not involve an app or nutrition intervention, were written in a language other than English, were duplicates from other database searches, or were literature reviews. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, the systematic review process included 4 steps: identification of records through the database search, screening of duplicate and excluded records, eligibility assessment of full-text records, and final analysis of included records.

RESULTS

In total, 46 studies comprising 256,430 patients were included. There was diversity in the chronic disease state, study design, number of participants, in-app features, behavior change techniques, and behavior models used in the studies. In addition, our review found that less than half (19/46, 41%) of the studies based their nutrition apps on a behavioral theory or its constructs. Of the 46 studies, 11 (24%) measured maintenance of health behavior change, of which 7 (64%) sustained behavior change for approximately 6 to 12 months and 4 (36%) showed a decline in behavior change or discontinued app use.

CONCLUSIONS

The results suggest that mHealth apps involving nutrition can significantly improve health outcomes in people with chronic diseases. Tailoring nutrition apps to specific populations is recommended for effective behavior change and improvement of health outcomes. In addition, some studies (7/46, 15%) showed sustained health behavior change, and some (4/46, 9%) showed a decline in the use of nutrition apps. These results indicate a need for further investigation on the sustainability of the health behavior change effectiveness of disease-specific nutrition apps.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

BACKGROUND

There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes.

METHODS

We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner.

RESULTS

A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction.

CONCLUSIONS

The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.

Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence

Objective

The National Diabetes Prevention Program (DPP) reduces diabetes incidence and associated medical costs but is typically staffing-intensive, limiting scalability. We evaluated an alternative delivery method with 3933 members of a program powered by conversational Artificial Intelligence (AI) called Lark DPP that has full recognition from the Centers for Disease Control and Prevention (CDC).

Methods

We compared weight loss maintenance at 12 months between two groups: 1) CDC qualifiers who completed ≥4 educational lessons over 9 months (n  =  191) and 2) non-qualifiers who did not complete the required CDC lessons but provided weigh-ins at 12 months (n  =  223). For a secondary aim, we removed the requirement for a 12-month weight and used logistic regression to investigate predictors of weight nadir in 3148 members.

Results

CDC qualifiers maintained greater weight loss at 12 months than non-qualifiers (M  =  5.3%, SE  =  .8 vs. M  =  3.3%, SE  =  .8; p  =  .015), with 40% achieving ≥5%. The weight nadir of 3148 members was 4.2% (SE  =  .1), with 35% achieving ≥5%. Male sex (β = .11; P  =  .009), weeks with ≥2 weigh-ins (β = .68; P < .0001), and days with an AI-powered coaching exchange (β = .43; P < .0001) were associated with a greater likelihood of achieving ≥5% weight loss.

Conclusions

An AI-powered DPP facilitated weight loss and maintenance commensurate with outcomes of other digital and in-person programs not powered by AI. Beyond CDC lesson completion, engaging with AI coaching and frequent weighing increased the likelihood of achieving ≥5% weight loss. An AI-powered program is an effective method to deliver the DPP in a scalable, resource-efficient manner to keep pace with the prediabetes epidemic.

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework

BACKGROUND

Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

OBJECTIVE

Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

METHODS

MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

RESULTS

In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

CONCLUSIONS

This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

Treatment self-regulation questionnaire across three self-care behaviours: An instrument validation study in Iranian patients with type 2 diabetes mellitus

Aim

The study aimed at testing the validity and reliability of the Persian version of the treatment self‐regulation questionnaire (TSRQ‐15) across healthy diet, exercise and medication‐use/glucose‐monitoring among Iranian people with type‐2 diabetes.

Design

Cross‐sectional design.

Methods

Content validity was investigated by 16 experts. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were employed. Construct validity, convergent/discriminant validity and internal consistency were examined. Concurrent validity was assessed using Spearman's rho correlation across different behaviours.

Results

Content validity was confirmed for Persian TSRQ‐15. A three‐factor structure was revealed, in which external regulation and introjected regulations were validated, while amotivation and autonomous failed to show discriminant validity. Internal consistency was sound, and concurrent validity was approved. The Persian version of TSRQ‐15 was shown to be a valid and reliable tool for assessing motivation behind the practice of healthy diet, exercise and medication‐use/glucose‐monitoring in people with type 2 diabetes.

Facilitators and Barriers to Uptake of Community-Based Diabetes Prevention Program Among Multi-Ethnic Asian Patients With Prediabetes

OBJECTIVE

This study aimed to identify facilitators and barriers to the uptake of a community-based diabetes prevention program (DPP) from the perspectives of decliners with prediabetes in a multi-ethnic Asian community.

METHODS

Semi-structured interviews were conducted with 29 individuals with prediabetes who declined participation in a large community-based diabetes prevention program in Singapore. Thematic analysis was undertaken to identify themes, which were subsequently mapped onto the Capacity-Opportunity-Motivation and Behavior model (COM-B).

RESULTS

We identified 16 key themes under three COM-B domains. Health status at the time of invitation, perceived ability of self-management, understanding of prediabetes condition and/or the program intention (Capability) were important determinants. Family commitment had the strong potential to enable or hinder physical and social Opportunity related to participation. Many participants desired involvement of physician as part of program invitation and component. Fear of exacerbation coupled with an automatic aversion for suffering influenced Motivation for participation.

CONCLUSION

Identifying facilitators and barriers embedded in the COM-B will assist systematic program modifications to increase participation of individuals with prediabetes. How information about modifiable risk factors is communicated by physicians at the point of diagnosis and program introduction is key to participation. Co-locating programs with family activity, development of mHealth, readiness assessment, and tailored explanation of program purpose may increase participation. These findings will be used to guide future national interventions in the community to ensure successful implementation.

Mobile Health Technology in the Primary Prevention of Type 2 Diabetes: a Systematic Review

PURPOSE OF REVIEW

The objective of this review was to summarize the current scientific evidence of mobile health technology in the primary prevention of type 2 diabetes in patients with prediabetes derived from randomized clinical trials.

RECENT FINDINGS

Few randomized clinical trials are available using mobile health technologies in the prevention of type 2 diabetes. There is heterogeneity in regard to the main study outcomes, duration of interventions, and study findings. Inconsistent findings have been reported whether mobile health technologies are effective in reducing HbA1C levels or the incidence of type 2 diabetes in patients with prediabetes. However, results are promising that mobile health interventions may decrease body weight. Future study may consistently measure changes in glycemic indicators as well as develop elements that better address behavior changes.

Using Community Health Workers to Address Barriers to Participation and Retention in Diabetes Prevention Program: A Concept Paper

Objective:

The PreventionLink of Southern Maryland is a 5-year project to eliminate barriers to participation and retention in the National Diabetes Prevention Program (DPP) lifestyle change program to prevent or delay the onset of type 2 diabetes in adults with prediabetes. This is the study to identify the obstacles to participation and retention in the DPP lifestyle change program among high burden populations and learn how CHWs have reduced the identified barriers to participation and retention for high burden populations.

Methods:

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to conduct this literature review. We have used the Scopus and PubMed, including all types of studies and peer-reviewed documents published in English between 2010 and 2020.

Results:

From 131 identified articles, 18 articles were selected for qualitative synthesis. The reviewed literature documented following as main barriers to participate in a DPP lifestyle change program: time, cost, lack of transportation, cost of transportation, commute distance, technology access, access to facilities and community programs, caregiver responsibilities, lack of health literacy and awareness, and language. CHWs can address these barriers to participation and retention, they were involved in educating and supporting roles; they worked as bridges between healthcare providers and participants and as intervention team members.

Conclusions:

Diabetes prevention program participants with social determinant risk factors who most need CHW services are unlikely to have financial resources to pay for CHW services out-of-pocket. Hence, the public and private health plans that pay for their prediabetes care should consider paying for these CHW services and there is a need to trust more to CHW and have them as a “community health teams” member.

Challenges in Participant Engagement and Retention using Mobile Health Apps: A Literature Review (Preprint)

Background

Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.

Objective

This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.

Methods

We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.

Results

Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.

Conclusions

Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.

Change Management and Digital Innovations in Hospitals of Five European Countries

The objective of the paper is to evaluate the quality of systemic change management (CHM) and readiness for change in five Central European countries. The secondary goal is to identify trends and upcoming changes in the field of digital innovations in healthcare. The results show that all compared countries (regardless of their historical context) deal with similar CHM challenges with a rather similar degree of success. A questionnaire distributed to hospitals clearly showed that there is still considerable room for improvement in terms of the use of specific CHM tools. A review focused on digital innovations based on the PRISMA statement showed that there are five main directions, namely, data collection and integration, telemedicine, artificial intelligence, electronic medical records, and M-Health. In the hospital environment, there are considerable reservations in applying change management principles, as well as the absence of a systemic approach. The main factors that must be monitored for a successful and sustainable CHM include a clearly defined and widely communicated vision, early engagement of all stakeholders, precisely set rules, adaptation to the local context and culture, provision of a technical base, and a step-by-step implementation with strong feedback.

Effect of ICT-Based Self-Management System DialBeticsLite on Treating Abdominal Obesity in the Specific Health Guidance in Japan: Randomized Controlled Trial. (Preprint)

Background

Mobile health (mHealth) interventions, a more cost-effective approach compared with traditional methods of delivering lifestyle coaching in person, have been shown to improve physical parameters and lifestyle behavior among overweight populations. In Japan, the Specific Health Checkups and Specific Health Guidance (SHG) started in 2008 to treat obesity and abdominal obesity. However, the effectiveness of SHG is limited owing to its in-person counseling. The effect of mHealth on SHG has yet to be demonstrated.

Objective

This study aims to determine whether a mobile self-management app (DialBeticsLite) could make the SHG more beneficial among patients with abdominal obesity to achieve a reduction in visceral fat area (VFA).

Methods

This study was an open-label, 2-arm, parallel-design randomized controlled trial. We recruited 122 people in September 2017 and randomly assigned them into either the intervention or control group. All participants attended an educational group session that delivered information regarding diet and exercise. In addition, participants in the intervention group were asked to use DialBeticsLite for 3 months. DialBeticsLite facilitated the daily recording of several physical parameters and lifestyle behavior and provided feedback to encourage an improvement in behavior. The primary outcome was the change in VFA from baseline to the 3-month follow-up. Secondary outcomes included changes in both physical and metabolic parameters from baseline to the 3-month follow-up. The Welch 2-tailed t test was conducted to analyze the effects of DialBeticsLite on both the primary and secondary outcomes.

Results

Of the 122 participants recruited, 75 (61.5%) were analyzed because 47 (38.5%) were excluded: 37 (30.3%) because of ineligibility and 10 (8.2%) because of withdrawal of consent. The mean age was 49.3 (SD 6.1) years in the intervention group (41/75, 55%) and 48.5 (SD 5.3) years in the control group (34/75, 45%), and all participants were men, although unintentionally. The baseline characteristics did not differ significantly between the intervention and control groups, except for VFA. The average change of VFA was −23.5 (SD 20.6) cm² in the intervention group and +1.9 (SD 16.2) cm² in the control group (P<.001). Statistically significant differences were also found for the change of body weight, BMI, and waist circumference. These findings did not change after adjusting for VFA at the baseline. The intervention had no significant effect on any of the metabolic parameters. An exploratory analysis showed significant associations between the change in VFA and steps per day and between the change in VFA and calorie intake per day within the intervention group.

Conclusions

Our findings indicate that an mHealth intervention facilitating the daily monitoring of several physical parameters and lifestyle behavior can be highly effective in inducing visceral fat loss and weight loss among adults eligible for SHG.

Trial Registration

UMIN Clinical Trials Registry UMIN000042045; https://tinyurl.com/4vat3v53

Evaluation of the Low Carb Program Digital Intervention for the Self-Management of Type 2 Diabetes and Prediabetes in an NHS England General Practice: Single-Arm Prospective Study

Background

Type 2 diabetes mellitus has serious health consequences, including blindness, amputation, and stroke. Researchers and clinicians are increasingly in agreement that type 2 diabetes may be effectively treated with a carbohydrate-reduced diet. Digital apps are increasingly used as an adjunct to traditional health care provisions to support remote self-management of long-term health conditions.

Objective

Our objective was to evaluate the real-world 12-month outcomes of patients prescribed the Low Carb Program digital health intervention at a primary care National Health Service (NHS) site. The Low Carb Program is a nutritionally focused, 12-session, digitally delivered, educational behavior change intervention for glycemic control and weight loss for adults with prediabetes and type 2 diabetes. The program educates and supports sustainable dietary changes focused on carbohydrate restriction by utilizing behavior change techniques, including goal setting, peer support, and behavioral self-monitoring, as well as personalized downloadable resources, including recipes and meal plans tailored to ethnicity, weekly shopping budget, and dietary preferences.

Methods

This study evaluated the real-world outcomes of patients recruited to the Low Carb Program at an NHS general practice in Southport, United Kingdom. All of the NHS patients recruited to the program were diagnosed with type 2 diabetes or prediabetes and were given access to the program at no cost. A total of 45 participants, with a mean age of 54.8 years (SD 13.2), were included in the study. Women made up 42% (19/45) of the sample. The mean hemoglobin A_1c (HbA_1c) of the sample was 56.7 mmol/mol (SD 16.95) and the mean body weight was 89.4 kg (SD 13.8).

Results

Of the 45 study participants recruited to the program, all of them (100%) activated their accounts and 37 (82%) individuals reported outcomes at 12 months. All 45 (100%) patients completed at least 40% of the lessons and 32 (71%) individuals completed more than nine out of 12 core lessons of the program. Glycemic control and weight loss improved, particularly for participants who completed more than nine core lessons in the program over 12 months. The mean HbA_1c went from 58.8 mmol/mol at baseline to 54.0 mmol/mol, representing a mean reduction of 4.78 mmol/mol (SD 4.60; t₃₁=5.87; P<.001). Results showed an average total body weight reduction of 4.17%, with an average weight reduction of 3.85 kg (SD 2.49; t₃₁=9.27; P<.001) at the 12-month follow-up point.

Conclusions

A digital app prescribed to adults with type 2 diabetes and prediabetes in a primary care setting supporting a transition to a low-carbohydrate diet has been shown to be effective in improving glycemic control and enabling weight loss. Further research to understand more about factors affecting engagement with the app and further positive health implications would be valuable.

A Mobile-Based Intervention for Dietary Behavior and Physical Activity Change in Individuals at High Risk for Type 2 Diabetes Mellitus: Randomized Controlled Trial

BACKGROUND

Intensive lifestyle modifications have proved effective in preventing type 2 diabetes mellitus (T2DM), yet the efficiency and effectiveness of these modifications need to be improved. Emerging social media interventions are considered useful in promoting these lifestyles; nevertheless, few studies have investigated the effectiveness of combining them with behavior theory.

OBJECTIVE

This study aims to examine the effectiveness of a 6-month mobile-based intervention (DHealthBar, a WeChat applet) combined with behavioral theory compared with a printed intervention in improving dietary behaviors, physical activity, and intention to change these behaviors among populations at high risk for T2DM.

METHODS

Participants aged 23 to 67 years were recruited offline in Beijing, China, and were randomized into the intervention group or the control group, which received educational content via DHealthBar or a printed handbook, respectively. Educational materials were culturally tailored recommendations on improving dietary behaviors, physical activity, and intention to change based on the transtheoretical model. Participants in the intervention arm received push notifications twice per week on WeChat and had access to the educational content for the 6-month study period. Participants in the control arm received the same intervention content through printed materials. The outcomes of participants' behavior change, intention to change behavior, and anthropometric characteristics were collected via online measuring tools at baseline, 3 months, and 6 months.

RESULTS

In this study, 79 enrolled individuals completed baseline information collection (control: n=38 vs intervention: n=41), and 96% (76/79) completed the 6-month follow-up visit. Attrition rates did not differ significantly between the 2 groups (χ21=0.0, P=.61). Baseline equivalence was found. Participants in both groups reported a statistically significant decrease in energy intake at the 2 follow-up assessments compared with baseline (3 months, control: exp[β]=0.83, 95% CI 0.74-0.92 vs intervention: exp[β]=0.76, 95% CI 0.68-0.85; 6 months, control: exp[β]=0.87, 95% CI 0.78-0.96 vs intervention: exp[β]=0.57, 95% CI 0.51-0.64). At 6 months, a significantly larger decrease was observed in the intervention group in energy, fat, and carbohydrate intake, accompanied with a significantly larger increase in moderate-intensity physical activity compared with the control group (energy: exp[β]=0.66, 95% CI 0.56-0.77; fat: exp[β]=0.71, 95% CI 0.54-0.95; carbohydrates: exp[β]=0.83, 95% CI 0.66-1.03; moderate-intensity physical activity: exp[β]=2.05, 95% CI 1.23-3.44). After 6 months of the intervention, participants in the intervention group were more likely to be at higher stages of dietary behaviors (exp[β]=26.80, 95% CI 3.51-204.91) and physical activity (exp[β]=15.60, 95% CI 2.67-91.04) than the control group.

CONCLUSIONS

DHealthBar was initially effective in improving dietary behavior, physical activity, and intention to change these behaviors among populations who were at high risk of developing T2DM, with significant differences in the changes of outcomes over the 6-month intervention period.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2000032323; https://tinyurl.com/y4h8q4uf.

Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis

BACKGROUND

Unhealthy behaviors, such as physical inactivity, sedentary lifestyle, and unhealthful eating, remain highly prevalent, posing formidable challenges in efforts to improve cardiovascular health. While traditional interventions to promote healthy lifestyles are both costly and effective, wearable trackers, especially Fitbit devices, can provide a low-cost alternative that may effectively help large numbers of individuals become more physically fit and thereby maintain a good health status.

OBJECTIVE

The objectives of this meta-analysis are (1) to assess the effectiveness of interventions that incorporate a Fitbit device for healthy lifestyle outcomes (eg, steps, moderate-to-vigorous physical activity, and weight) and (2) to identify which additional intervention components or study characteristics are the most effective at improving healthy lifestyle outcomes.

METHODS

A systematic review was conducted, searching the following databases from 2007 to 2019: MEDLINE, EMBASE, CINAHL, and CENTRAL (Cochrane). Studies were included if (1) they were randomized controlled trials, (2) the intervention involved the use of a Fitbit device, and (3) the reported outcomes were related to healthy lifestyles. The main outcome measures were related to physical activity, sedentary behavior, and weight. All the studies were assessed for risk of bias using Cochrane criteria. A random-effects meta-analysis was conducted to estimate the treatment effect of interventions that included a Fitbit device compared with a control group. We also conducted subgroup analysis and fuzzy-set qualitative comparative analysis (fsQCA) to further disentangle the effects of intervention components.

RESULTS

Our final sample comprised 41 articles reporting the results of 37 studies. For Fitbit-based interventions, we found a statistically significant increase in daily step count (mean difference [MD] 950.54, 95% CI 475.89-1425.18; P<.001) and moderate-to-vigorous physical activity (MD 6.16, 95% CI 2.80-9.51; P<.001), a significant decrease in weight (MD -1.48, 95% CI -2.81 to -0.14; P=.03), and a nonsignificant decrease in objectively assessed and self-reported sedentary behavior (MD -10.62, 95% CI -35.50 to 14.27; P=.40 and standardized MD -0.11, 95% CI -0.48 to 0.26; P=.56, respectively). In general, the included studies were at low risk for bias, except for performance bias. Subgroup analysis and fsQCA demonstrated that, in addition to the effects of the Fitbit devices, setting activity goals was the most important intervention component.

CONCLUSIONS

The use of Fitbit devices in interventions has the potential to promote healthy lifestyles in terms of physical activity and weight. Fitbit devices may be useful to health professionals for patient monitoring and support.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42019145450; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019145450.

Mobile Delivery of the Diabetes Prevention Program in People With Prediabetes: Randomized Controlled Trial

BACKGROUND

The Centers for Disease Control and Prevention (CDC) diabetes prevention program (DPP) has formed the foundation for Type 2 Diabetes Mellitus (T2DM) prevention efforts and lifestyle change modifications in multiple care settings. To our knowledge, no randomized controlled trial has verified the efficacy of a fully mobile version of CDC's diabetes prevention program (DPP).

OBJECTIVE

This study aimed to investigate the long-term weight loss and glycemic efficacy of a mobile-delivered DPP compared with a control group receiving usual medical care.

METHODS

Adults with prediabetes (N=202) were recruited from a clinic and randomized to either a mobile-delivered, coach-guided DPP (Noom) or a control group that received regular medical care including a paper-based DPP curriculum and no formal intervention. The intervention group learned how to use the Noom program, how to interact with their coach, and the importance of maintaining motivation. They had access to an interactive coach-to-participant interface and group messaging, daily challenges for behavior change, DPP-based education articles, food logging, and automated feedback. Primary outcomes included changes in weight and hemoglobin A_1c (HbA_1c) levels at 6 and 12 months, respectively. Exploratory secondary outcomes included program engagement as a predictor of changes in weight and HbA_1c levels.

RESULTS

A total of 202 participants were recruited and randomized into the intervention (n=101) or control group (n=99). In the intention-to-treat (ITT) analyses, changes in the participants' weight and BMI were significantly different at 6 months between the intervention and control groups, but there was no difference in HbA_1c levels (mean difference 0.004%, SE 0.05; P=.94). Weight and BMI were lower in the intervention group by -2.64 kg (SE 0.71; P<.001) and -0.99 kg/m2 (SE 0.29; P=.001), respectively. These differences persisted at 12 months. However, in the analyses that did not involve ITT, program completers achieved a significant weight loss of 5.6% (SE 0.81; P<.001) at 6 months, maintaining 4.7% (SE 0.88; P<.001) of their weight loss at 12 months. The control group lost -0.15% at 6 months (SE 0.64; P=.85) and gained 0.33% (SE 0.70; P=.63) at 12 months. Those randomized to the intervention group who did not start the program had no meaningful weight or HbA_1c level change, similar to the control group. At 1 year, the intervention group showed a 0.23% reduction in HbA_1c levels; those who completed the intervention showed a 0.28% reduction. Those assigned to the control group had a 0.16% reduction in HbA_1c levels.

CONCLUSIONS

This novel mobile-delivered DPP achieved significant weight loss reductions for up to 1 year compared with usual care. This type of intervention reduces the risk of overt diabetes without the added barriers of in-person interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03865342; https://clinicaltrials.gov/ct2/show/NCT03865342.

Android and iPhone Mobile Apps for Psychosocial Wellness and Stress Management: Systematic Search in App Stores and Literature Review

BACKGROUND

In an oversaturated market of publicly available mobile apps for psychosocial self-care and stress management, health care providers, patients, and consumers interested in mental health-related apps may wonder which, if any, are efficacious. Readily available metrics for consumers include user popularity and media buzz rather than scientific evidence.

OBJECTIVE

This systematic review aimed to (1) examine the breadth of therapeutic contents and features of psychosocial wellness and stress management apps available to self-help seekers for public download and (2) determine which of these apps have original research support.

METHODS

First, we conducted a systematic review of publicly available apps on the iPhone App Store (Apple Inc) and Android Google Play (Google LLC) platforms using conventional self-help-seeking search terms related to wellness and stress. The results were limited to English-language apps available for free download. In total, 2 reviewers independently evaluated all apps and discussed the findings to reach 100% consensus regarding inclusion. Second, a literature review was conducted on the included apps to identify supporting studies with original data collection.

RESULTS

We screened 3287 apps and found 1009 psychosocial wellness and stress management apps. Content varied widely. The most common evidence-based strategy was mindfulness-meditation, followed by positive psychology and goal setting. Most apps were intended to be used as self-help interventions, with only 1.09% (11/1009) involving an electronic therapist and 1.88% (19/1009) designed as a supplement to in-person psychotherapy. Only 4.66% (47/1009) of apps targeted individuals with psychological disorders, and less than 1% of apps (6/1009, 0.59%) targeted individuals with other chronic illnesses. Approximately 2% (21/1009, 2.08%) were supported by original research publications, with a total of 25 efficacy studies and 10 feasibility studies. The Headspace mindfulness app had the most evidence, including 8 efficacy studies. Most other scientifically backed apps were supported by a single feasibility or efficacy study.

CONCLUSIONS

Only 2.08% (21/1009) of publicly available psychosocial wellness and stress management mobile apps discoverable to self-help seekers have published, peer-reviewed evidence of feasibility and/or efficacy. Clinicians and investigators may use these findings to help patients and families navigate the volume of emerging digital health interventions for stress management and wellness.

Using a RE-AIM framework to identify promising practices in National Diabetes Prevention Program implementation

BACKGROUND

The National Diabetes Prevention Program (National DPP) is rapidly expanding in an effort to help those at high risk of type 2 diabetes prevent or delay the disease. In 2012, the Centers for Disease Control and Prevention funded six national organizations to scale and sustain multistate delivery of the National DPP lifestyle change intervention (LCI). This study aims to describe reach, adoption, and maintenance during the 4-year funding period and to assess associations between site-level factors and program effectiveness regarding participant attendance and participation duration.

METHODS

The Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework was used to guide the evaluation from October 2012 to September 2016. Multilevel linear regressions were used to examine associations between participant-level demographics and site-level strategies and number of sessions attended, attendance in months 7-12, and duration of participation.

RESULTS

The six funded national organizations increased the number of participating sites from 68 in 2012 to 164 by 2016 across 38 states and enrolled 14,876 eligible participants. By September 2016, coverage for the National DPP LCI was secured for 42 private insurers and 7 public payers. Nearly 200 employers were recruited to offer the LCI on site to their employees. Site-level strategies significantly associated with higher overall attendance, attendance in months 7-12, and longer participation duration included using self-referral or word of mouth as a recruitment strategy, providing non-monetary incentives for participation, and using cultural adaptations to address participants' needs. Sites receiving referrals from healthcare providers or health systems also had higher attendance in months 7-12 and longer participation duration. At the participant level, better outcomes were achieved among those aged 65+ (vs. 18-44 or 45-64), those who were overweight (vs. obesity), those who were non-Hispanic white (vs. non-Hispanic black or multiracial/other races), and those eligible based on a blood test or history of gestational diabetes mellitus (vs. screening positive on a risk test).

CONCLUSIONS

In a time of rapid dissemination of the National DPP LCI the findings of this evaluation can be used to enhance program implementation and translate lessons learned to similar organizations and settings.

Data Independent Acquisition Mass Spectrometry Can Identify Circulating Proteins That Predict Future Weight Loss with a Diet and Exercise Programme

We investigated biological determinants that would associate with the response to a diet and weight loss programme in impaired glucose regulation (IGR) people using sequential window acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry (MS), a data acquisition method which complement traditional mass spectrometry-based proteomics techniques. Ten women and 10 men with IGR underwent anthropometric measurements and fasting blood tests. SWATH MS was carried out with subsequent immunoassay of specific peptide levels. After a six-month intervention, 40% of participants lost 3% or more in weight, 45% of patients remained within 3% of their starting weight and 15% increased their weight by 3% or more. Hemoglobin A1c (HbA1C) level was reduced with weight loss with improvements in insulin sensitivity. SWATH MS on pre-intervention samples and subsequent principal component analysis identified a cluster of proteins associated with future weight loss, including insulin-like growth factor-II (IGF-II) and Vitamin D binding protein. Individuals who lost 3% in weight had significantly higher baseline IGF-II levels than those who did not lose weight. SWATH MS successfully discriminated between individuals who were more likely to lose weight and potentially improve their sensitivity to insulin. A higher IGF-II baseline was predictive of success with weight reduction, suggesting that biological determinants are important in response to weight loss and exercise regimes. This may permit better targeting of interventions to prevent diabetes in the future.