Designing iCanFit: A Mobile-Enabled Web Application to Promote Physical Activity for Older Cancer Survivors

Yan Hong
Department of Health Promotion and Community Health Science
School of Rural Public Health
Texas A&M Health Science Center
College StationTXUnited States

PhD;Deborah Vollmer Dahlke
Texas Life Science Foundation
AustinTXUnited States

MPAff;Marcia Ory
Department of Health Promotion and Community Health Science
School of Rural Public Health
Texas A&M Health Science Center
College StationTXUnited States

PhD, MPH;Angela Hochhalter
Scott & White Healthcare
TempleTXUnited States

PhD;Jana Reynolds
Scott & White Healthcare
TempleTXUnited States

Ninfa Pena Purcell
Department of Health Promotion and Community Health Science School of Rural Public Health Texas A&M Health Science Center
Texas AgriLife Extension Agency
Texas A&M University System, College Station
1266TXUnited States

TAMU College Station
77843United States

PhD; Divya Talwar
Department of Health Promotion and Community Health Science
School of Rural Public Health
Texas A&M Health Science Center
College StationTXUnited States

MPH;Nola Eugene
Department of Health Promotion and Community Health Science
School of Rural Public Health
Texas A&M Health Science Center
College StationTXUnited States

PhDYan Hong
Designing iCanFit: A Mobile-Enabled Web Application to Promote Physical Activity for Older Cancer Survivors
10.2196/resprot.2440Original Paper Corresponding Author:
Background: Most older cancer survivors (OCS) do not engage in regular physical activity (PA) despite well-known health benefits. With the increased use of mobile technologies among older adults, mobile tools may be an effective method to deliver PA promotion programs for OCS.Objective: To document the process of designing an OCS-friendly mobile-enabled Web application of PA promotion program. Methods: Mixed methods encompassing group discussions, individual interviews, and brief surveys with community leaders, OCS, cancer care providers, and software professionals were used in this formative research.Results:The varied stakeholders welcomed the idea of developing an online tool to promote PA in OCS. Our formative research revealed several major barriers to regular PA including limited access to senior-friendly PA resources, lack of motivation and social support, and insufficient knowledge and skills on building safe and appropriate workout plans. This feedback was incorporated into the development of iCanFit, a mobile-enabled Web application, designed specifically for OCS. The iCanFit online tools allow users to locate PA resources, set and track goals for PA, network with peer OCS in a secure online space, and receive practical and evidence-informed healthy tips.Conclusions:Our mixed-method formative research led to the design of iCanFit protocol to promote PA and well-being of OCS. The involvement of stakeholders is critical in the planning and design of the mobile application in order to enhance program relevance, appeal, and match with the needs of target users.Protoc 2013;2(1):e12)(JMIR Res

Introduction

Early detection and improved treatment for cancer has resulted in approximately 13 million survivors in the Unites States today.

It has been estimated that these numbers will increase by nearly a third to 18 million by 2022 [1]. Most cancer survivors are 60 years of age or older, and the population of older cancer survivors (OCS) is increasing, resulting in many challenges associated with the continuity of care and resultant quality of life [2,3]. Countering these challenges, numerous studies point to the physiological and psychosocial benefits of physical activity (PA) for cancer survivors [4,5]. These benefits include improved physical endurance, capacity and strength, higher immune function and hemoglobin concentration, decreased risk of cancer recurrence, and improved quality of life as indicated by decreased fatigue and depression [6][7][8][9][10]. Several guidelines on PA for cancer survivors have been recently issued, recommending cancer survivors to engage in low to moderate impact PA regularly, specifically, at least 30 minutes of exercise a day for 5 days a week [11,12].

Despite the recognized importance of PA for cancer survivors, evidence suggests that the level of adherence to PA guidelines among cancer survivors is very low. Smith and Chagpar reported that only 4.6% of breast cancer survivors followed PA guidelines, compared to 12% of women without breast cancer [13]. The majority of cancer survivors are not participating in the recommended levels of PA, resulting in a greater disease risk and health care costs [14]. In a review of existing programs to promote PA among cancer survivors, Schmitz and colleagues observed that most existing programs are limited to walking only, and that there is a lack of diversity in types of PA for cancer survivors [15]. In addition, most existing studies of interventions to increase PA have relied on individual or small group counseling approaches, typically offered by nurses or health educators. Such face-to-face approaches, although promising, have encountered problems of high personnel cost and limited reach. Thus, a critical need exists for more cost-effective strategies to reach a large number of OCS with effective strategies for promoting PA [12,16].

In the exploration of interventions to promote PA among OCS, mobile technologies are gaining increased attention across all age groups. As of 2012, about 88% of US adults and nearly 70% of people older than 50 accessed the Internet. 85% of US adults owned cell phones, of those, 53% owned smartphones [17]. Approximately 70% of adults over 50 owned a cell phone, and more than 42% owned a laptop or tablet computer [18].

The percentage of older smartphones or mobile computer owners is expected to accelerate in the coming years. Further, recent surveys by National Cancer Institute indicated that more than 60% of cancer survivors access the Internet; and once online, they are more likely to use it for health-related purposes than general users [19,20]. Among cancer survivors, the Internet has become the second most used resource for finding health-related information (the primary resource was physicians) [21,22]. The ubiquity of Internet access in the US and the rapid penetration of smartphones and tablets suggests the feasibility of using mobile technologies to promote PA among OCS. In a recent review of existing Web and mobile applications for PA promotion, we found that most websites or applications were designed for general and younger populations. Few online PA programs were designed for cancer survivors, not to mention OCS. The purpose of this article was to describe a formative study we conducted to inform the design of a mobile or Web application for the purpose of promoting PA among OCS.

Methods

Overview

A multidisciplinary research team from Communities of Texas: Cancer • Activity • Research • Education • Support (CTxCARES) program representing public health, medicine, health education, and technology development worked collaboratively to design the formative research protocol. A mixed-method approach was used to collect data to inform the structure and content of the mobile or Web application. Our team met regularly to discuss the data collected from field, enabling prompt feedback for project development and refinement. Data collection in formative research spanned from November 2011 to September 2012. We held group discussions with community leaders, individual interviews with cancer care providers, and conducted a brief survey and interviews with OCS. Table 1 lists all the data collection methods utilized. The study protocol was approved by the Institutional Review Boards at the Texas A&M University and Scott & White Healthcare.

Group Discussions with Community Leaders

The CTxCARES program has collaborated with local cancer communities and senior communities for several years, leading to established relationships. At the planning stage of the project, we communicated about our intention to develop a mobile or Web application for OCS to local senior and cancer community leaders and obtained their support. In our formative research, we had 2 group discussions with local community leaders to get their input on the feasibility of a website to engage OCS and promote their PA. The discussions took place in informal expanded meetings of community organizations in which community leaders and members were present. These discussions were not taped, but detailed notes were taken during and after the meeting.

Interviews with Cancer Care Providers

We also interviewed practicing cancer care providers who have patients either in active cancer treatment or are cancer survivors. The provider's interview guide was developed based on the literature review and informal discussions with community leaders. The guide focused on: (1) perceptions on OCS' barriers to regular PA, (2) current counseling of PA with OCS, (3) suggested contents of a mobile or online program, and (4) strategies to disseminate the program after piloting. The interview guide was piloted with 2 physicians before field use. A total of 14 cancer care providers were recruited during a large state cancer conference, representing surgeons, oncologists, family physicians, internists, health educators, and counselors. One-on-one interviews ranging from 20-45 minutes were conducted in a private space. All conversations were audio-taped and transcribed verbatim.

Survey with OCS

We conducted a brief survey with OCS who were at least 60 years old, had a cancer diagnoses, and had completed initial treatment. Surveys were distributed at local health fairs and cancer survivors' events. Participants reported on their Internet and cell phone use, current PA behaviors, access to health information, and attitudes toward mobile-based PA promotion program. It took the OCS approximately 10 minutes to complete the brief paper-pencil survey. A total of 92 OCS (mean age 62) provided oral consent and completed the survey. All survey data were entered into SPSS 16.0 (SPSS Inc, Chicago, IL, USA).

Interviews with OCS

Our third strategy was to conduct in-depth individual interviews with OCS. We developed an interview guide for OCS based on the brief survey with OCS and the in-depth interviews with cancer care providers. The interview guide consisted of the following domains: (1) current PA including type, intensity, duration, and frequency, (2) barriers to regular PA, (3) preferred PA and facilitators to regular PA, (4) attitudes toward an online or mobile PA promotion program, (5) suggestions on content and features of the mobile program, and (6) suggestions on program implementation and evaluation. A total of 11 OCS in Central Texas were recruited through community outreach strategies. The interviews were conducted face-to-face or over the phone, lasted 25-45 minutes, and were audio-taped. Each participant provided consent and received a $15 gift card.

Data Analysis and Interpretation

The data collected in the formative research included: (1) notes from the research team's regular meeting discussions, (2) detailed notes from discussions with community leaders, (3) transcripts from interviews with cancer care providers, (4) survey data from OCS, and (5) transcripts from interviews with OCS. Quantitative data were saved in SPSS and descriptive statistical methods were used to analyze frequency of key variables. Qualitative data were saved in Microsoft Word; thematic content analysis was used to identify the major themes and key exemplary quotes [23]. Findings from each data set were used to inform analysis and interpretation of other data sets. The data analysis was iterative and continued throughout the formative research; the findings were used to inform the design, content, and structure of the iCanFit mobile-enabled Web application.

Results

Feasibility of Mobile PA Promotion Program for OCS

The survey and interviews with OCS and discussions with community leaders revealed the current online behaviors of OCS. Most of OCS accessed the Internet, and the Internet was a major source of health information for the participants. For example, more than 80% of OCS in our interviews indicated that they would participate in an online PA promotion program or OCS support program. OCS also suggested that compared to younger people, they had shorter online duration and that they were more likely to visit the same authoritative sites. Less than 10% of OCS accessed the Internet through their cell phones frequently, but many had tablets such as iPads and many accessed the Internet through their mobile devices. Some OCS, especially those over 75 years old, reported less use of Internet themselves, but they relied on their families to access the Internet and obtain health information. More than 80% of the OCS we talked to have easy access to health information and could easily obtain this information from the Internet.

Barriers to PA Among OCS

The interviews with cancer care providers indicated that most of them were aware of regular PA as part of healthy living for cancer survivors, but very few discussed PA with their survivor patients. Care providers identified the lack of motivation to carry out PA from survivors as the major barrier to regular PA. For example, a physician related, "If they want to do it, they'll do it. If they don't, they won't." Most cancer care providers listed time constraint as a major barrier to discussing PA with their cancer survivor patients. As one physician indicated, "The conversation doesn't get that in-depth because we have so many other issues to discuss."

The interviews with OCS confirmed that most did not participate in regular PA. Four personal and structural level barriers to PA were identified. First, some survivors were not aware of the benefits of PA. Another OCS who had tried some programs said, "It did help a little but I quit going because they did not treat me as an individual but they just do everybody in mass." In addition, since PA was rarely discussed in their visit with health care providers, OCS did not know how to set up individualized plans that fit their health and needs. Fourth, some OCS did not have enough social support, especially peer support, to engage in regular PA. For instance, some OCS commented, "I am basically lazy…and I need somebody to crack the whip…If I had an exercise partner, I may go more often." Our brief survey with OCS suggested that only a small number of OCS were part of the online cancer support groups but most were willing to join one.

Key Functions and Structure of the Online PA Promotion Program

In addition to identifying barriers to regular PA, our participants of community leaders, cancer care providers, and OCS also provided suggestions on how to design the online program to address these barriers. Their input was incorporated into the design of a mobile-enabled Web application called iCanFit. The reason for a Web application instead of a mobile application is to fulfill the goal of making iCanFit accessible through all mobile devices with Internet connections. Most mobile applications are limited to certain devices or platforms. For example, iPhone apps will not work on Android phones. Our mobile-enabled interactive website allows seniors to access the program through their various mobile devices with minimal restrictions. Table 2 lists input from stakeholders on the barriers and corresponding functions on the Web application to address stakeholder feedback. The interactive iCanFit has the following 6 major functions addressing the needs and barriers to regular PA in OCS:

1. "Locator", a function that allows easy search for local resources of PA, including parks, facilities, and programs. Users can set their preferences for searching, for example, indoors, free, group activity, etc.

2. "Goals", a function that allows users to set long-and short-term goals of PA. They can track their PA by entering their weekly PA. The iCanFit system will provide tailored feedback on their progress and suggestions on changing on short-term goals. iCanFit sends weekly reports to the users tracking their goals and providing tailored tips and kudos. Those who met their goals were congratulated by a virtual coach and those who did not meet their goals received motivational messages from the virtual coach.

3. "Community", a function that offers social support through virtual networking. Users are able to create a profile, post images, and start and follow discussions and to connect with peers users. Users are also able to create a profile, post images, and start and follow discussions and to connect with peers users. Those who exceed the short-term PA goals will also be recognized and congratulated in the online community. 4. "Healthy Tips", a function that sends regular health tips to users. These consist of tips for seniors to make small changes in daily life and make incremental progress toward an active and healthy living. 5. "Library", is a function that provides convenient access to authoritative health information. In addition to links to major senior health and cancer survivor organizations, this function also allows keyword search for specific health information.

6. "Support", is a function where users can seek help and technical support when using iCanFit programs.

We included some screen shots to help visualize how iCan Fit works. Figure 1 depicts iCanFit homepage on a desktop, Figure  2 displays the key functions of iCanFit on a laptop, and Figure  3 shows iCanFit functions on an iPhone interface. In line with stakeholders' suggestions and the National Library of Medicine guidelines of "making your website senior friendly" [24], the iCanFit interface is simple with bigger icons, bigger fonts, more space between lines, and clear background in contrast with the main texts. The iCanFit protocol is currently being developed into active Web application. CL: Simple tips can make small changes, and small changes can add up.

•

Sends regular practical, senior-friendly, evidencebased healthy tips specific to OCS Library OCS: Many OCS are unaware of necessity and benefits of regular PA.

CCP: Do not have enough time to carry out patient education.

•

Provides convenient access to authoritative health information • Provides links to major senior health and cancer survivor organizations

Discussion

With the population of OCS expanding and few OCS having regular PA, a strong need exists for a cost-effective health promotion program targeting this population. Online access is increasingly common among older adults, and mobile use is also accelerating, thus offering a potential mode of widespread intervention delivery. A combination of Web and mobile technology that incorporates the best principles of chronic care management-including identifying patient preferences, addressing barriers to lifestyle changes, enhancing self-management skills, providing coaching and feedback, and facilitating peer support-offers an excellent opportunity to meet this need [25,26].

Although the number of online health promotion programs is skyrocketing with demonstrated efficacy [27,28], very few programs are available for OCS. This study documents the process necessary to develop a PA promotion program for OCS. It has long been recognized that employing user-centered design and development process is essential for ensuring a quality user experience [29][30][31]. Our formative research has involved the key stakeholders from very beginning and throughout the phase of protocol development. The resulting iCanFit protocol addresses OCS' barriers to regular PA. It provides an engaging venue for achieving behavioral change through easy access to community resources, goal setting and reinforcement, and peer support. It is important that these functions are relevant to OCS and presented in a format that appeal to the intended audience.

Several limitations should be noted for this study. First, we had a relatively small sample size in both quantitative and qualitative data collection, which might introduce potential reporting bias. However, our participants were drawn from a diverse background and the data suggested saturation. Second, as our participants were recruited from communities in Texas, the findings may not be generalizable to OCS from other locations. We employed community outreach versus online recruitment because we needed to conduct an in-depth and sometimes repeated interviews with OCS to obtain their feedback. Third, our program only addressed 3 key barriers to regular PA identified by OCS and their care providers. Whether the program met their expectations and could promote regular PA and health outcomes requires a long-term study. We are now developing the iCanFit protocol to the active Web application. Once beta-testing is completed, we will conduct an efficacy trial to assess whether it can promote PA and other health outcomes of OCS.

The design of online health promotion programs, especially behavioral change programs, should reflect collaborative efforts between researchers, computer software designers, and key stakeholders. Through this formative research, we learned the importance of setting a realistic timeline and recruiting participants from diverse backgrounds. We also appreciate the value of a mixed-method study that involves key stakeholders to understand target users' needs and preferences in order to identify best strategies for program development and evaluation of this new mobile-enabled Web application.

Figure 1 .
1iCanFit webpage interface on a desktop computer.

Figure 2 .
2Major functions of iCanFit on desktop interface.

Figure 3 .
3Major functions of iCanFIt on an iPhone interface.

Table 1 .
1Data sources of formative research in the iCanFit program.Data collection mode
Recruitment venues
Participants
Data collection method

Face-to-face
Community centers
Community leaders (n=20)
Group discussion

Face-to-face, phone
Conferences, clinics
Cancer care providers (n=14)
Individual interview

Face-to-face, phone
Communities, clinics, cancer-
related events

Older cancer survivors (n=20)
Individual interview

Paper-pencil
Communities, cancer-related
events

Older cancer survivors (n=92)
Questionnaire

I use Internet many times a day, and I search for health information for myself and my family. I search the Internet using both my desktop and my iPhone…People have misconceptions about seniors using mobile technologies, many of us are computer savvy. [61 year old OCS]

For myself, since I got colon cancer, I became more cautious with what I eat. I see nutrition is more important for me…Physical activity? I do some yard work, and when I shop in Wal-Mart, I walk fast with my shopping cart [60 year old OCS] Second, some understood the importance of regular PA, but lacked motivation to be more physically active. After all the treatments, I just want to go back to my normal life. I know exercise is good for health, but it is probably the last thing in the mind now. I just want to get back to normal, rather than an enhancement or set up new goals. [67 year old OCS] Third, many OCS had limited access to information on local, senior-friendly PA programs and resources. They expressed frustration in finding senior-friendly PA resources. There is a senior center here in [omitted], but I've been there and looked into their exercise room and it's about twice the size of my hall bathroom; and it is so confined that I am not inspired to get in there and do anything. [70 year old OCS]

Table 2 .
2Proposed key iCanFit functions based on inputs from stakeholders.OCS: Need assistance in setting individualized plans.CL: Online community can expand OCS social networks, especially for rural residents.OCS: Need constant reminders to continue the momentum.Purpose
Proposed iCanFit

function

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AcknowledgmentsThis study was supported from a pilot grant from Scott & White Healthcare Senior Health Program, and Mobile Application Program Award from National Library of Medicine South Central Region Network and CTxCARES, which is supported by Cooperative Agreement Number 1U48 DP001924 from the Center for Disease Control and Prevention. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official positions of the funding agencies. We appreciate support from Gabriel Laguillo, Richard Wood, Debra Kellstedt, and Lorie Thibodeaux in data collection and thank all participants in our study.Conflicts of InterestNone declared.
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), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information. Deborah Hong, Marcia Vollmer Dahlke, Angela Ory, Jana Hochhalter, Ninfa Pena Reynolds, Divya Purcell, Nola Eugene Talwar, 14.02This is an open-access article distributed under the terms of the Creative Commons Attribution License. JMIR Research Protocols. as well as this copyright and license information must be included©Yan Hong, Deborah Vollmer Dahlke, Marcia Ory, Angela Hochhalter, Jana Reynolds, Ninfa Pena Purcell, Divya Talwar, Nola Eugene. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 14.02.2013. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.


Chronologically scheduled snacking with high-protein products within the habitual diet in type-2 diabetes patients leads to a fat mass loss: a longitudinal study

Santiago Navas-Carretero
Itziar Abete
Angeles Zulet
Alfredo Martínez
Chronologically scheduled snacking with high-protein products within the habitual diet in type-2 diabetes patients leads to a fat mass loss: a longitudinal study
R E S E A R C H Open Access
Background: Obesity is the most relevant overnutrition disease worldwide and is associated to different metabolic disorders such as insulin resistance and type-2 diabetes. Low glycemic load foods and diets and moderately high protein intake have been shown to reduce body weight and fat mass, exerting also beneficial effects on LDLcholesterol, triglyceride concentrations, postprandial glucose curve and HDL-cholesterol levels. The present study aimed at studying the potential functionality of a series of low glycemic index products with moderately high protein content, as possible coadjuvants in the control of type-2 diabetes and weight management following a chronologically planned snacking offer (morning and afternoon).Methods: The current trial followed a single group, sequential, longitudinal design, with two consecutive periods of 4 weeks each. A total of 17 volunteers participated in the study. The first period was a free living period, with volunteers' habitual ad libitum dietary pattern, while the second period was a free-living period with structured meal replacements at breakfast, morning snack and afternoon snack, which were exchanged by specific products with moderately high protein content and controlled low glycemic index, following a scheduled temporal consumption. Blood extractions were performed at the beginning and at the end of each period (free-living and intervention). Parameters analysed were: fasting glucose, insulin, glycosylated hemoglobin, total-, HDL-and LDLcholesterol, triglyceride, C -reactive protein and Homocysteine concentrations. Postprandial glucose and insulin were also measured. Anthropometrical parameters were monitored each 2 weeks during the whole study.Results: A modest but significant (p = 0.002) reduction on body weight (1 kg) was observed during the intervention period, mainly due to the fat mass loss (0.8 kg, p = 0.02). This weight reduction was observed without apparently associated changes in total energy intake. None of the biochemical biomarkers measured was altered throughout the whole study.Conclusions: Small changes in the habitual dietary recommendations in type-2 diabetes patients by the inclusion of specific low-glycemic, moderately high-protein products in breakfast, morning and afternoon snacks may promote body weight and fat-mass loss, without apparently altering biochemical parameters and cardiovascular risk-related factors.Trial Registration: Trial registered at clinicaltrials.gov NCT01264523.

Introduction

Type-2 diabetes prevalence in adults has grown in the last years in many societies, accompanying the high incidence of obesity-related and other cardiovascular risk factors [1]. Indeed, obesity is the most relevant overnutrition disease worldwide, being more dramatic than a self-esteem problem or an aesthetic issue, since it is associated to different metabolic disorders such as coronary diseases, hypertension, certain tumors, dislipidemia, biliary disorders, immunodeficiencies and insulin resistance [2].

Different studies have shown the efficacy of low-fat diets on weight reduction, which has been associated to an improvement in overweight-related chronic pathological conditions [3,4]. However, the concomitant high carbohydrate content in some weight-loss diets may imply the intake of foods with an elevated glycemic index, which leads to alterations in appetite directly associated to weight regain [5]. Furthermore, these commonly sugar-rich diets may exert negative effects on lipid profile [6] and insulin resistance [7]. In addition, there is increasing evidence about the key role of the quantity and quality of carbohydrates in diets, on the risk of developing chronic diseases [7][8][9][10][11]. Moreover, diets with a high glycemic load have been related to a higher risk of developing diabetes [6], while studies carried out with foods and diets of low glycemic load and high protein content have been associated with a reduction on LDL-cholesterol and triglyceride concentrations, as well as a lower postprandial glucose curve and an increase in HDL-cholesterol levels [7][8][9][10][11][12][13][14].

A number of trials have also demonstrated that diets with a low glycemic load increase satiety, reduce energy intake and produce a raised thermogenic effect [15,16], favoring weight loss and subsequently reducing cardiovascular disease and diabetes manifestations, although this apparently higher efficacy of diets with this macronutrient approach remains as a debate issue [17].

Additional investigations have shown that meals and diets with high protein content may be effective to combat the most important metabolic alterations observed in diabetic patients [7,12,[18][19][20]. Additionally, some studies have demonstrated beneficial effects associated to dietary interventions based on specific breakfast patterns [12,19,20].

The present study aimed at researching the potential functionality of a series of low glycemic index products with a moderately high protein content, as possible coadjuvants in the control of type 2-diabetes and weight management within a nutritionally balanced dietary pattern, following a chronologically planned snacking offer (morning and afternoon), as well as the influence on biomarkers of the metabolic syndrome and cardiovascular risk manifestations.

Methods

The study protocol was approved by the Clinical Research Ethics Committee of the University of Navarra (reference: 078/2009), and was registered at clinicaltrials. gov (identifier: NCT01264523). The full trial protocol can be accessed in Clinical Trials website (clinicaltrials. gov) by introducing the identifier. Recruitment took part during February -March 2010 and the study finished in June 2010. Written informed consent was given by all the volunteers participating in the intervention.

Taking into account the design of the present study as a single group longitudinal intervention, the authors have tried to fulfill the CONSORT 2010 guidelines [21], except for those points where it was considered nonapplicable, such as blinding.

Study design

The present trial was developed at the facilities of the University of Navarra with 17 participants, and followed a longitudinal design, with two consecutive periods of 4 weeks each. The first period, control phase, was a free living diet and status, where the patients followed their habitual ad libitum dietary pattern (following the recommendations of their physician), while the second period consisted on an intervention phase with structured meal replacements, where the volunteers' habitual breakfast, morning snack and afternoon snack, were exchanged by specific products, provided by the researchers, with a moderately high protein content and a controlled low glycemic index, following a scheduled temporal consumption. Therefore, the measurements and evaluation in the first period are considered as control values in relation to the intervention phase.

Blood extractions were performed at recruitment, if the volunteers didn't have a recent blood analysis (during the last three months), and on week 0 (beginning of the free living period), week 4 (end of free-living period and beginning of the intervention period) and week 8 (end of the intervention period). Anthropometrical parameters were also measured on weeks 0, 2, 4, 6 and 8 of the trial.

The primary outcomes of the current intervention were body-weight and fat mass, while glucose and lipid metabolism, as well as selected cardiovascular risk biomarkers were established as secondary outcomes.

Volunteers were asked to maintain their physical activity throughout the whole intervention. An important increase/decrease of physical activity compared to the baseline estimation was considered an exclusion criteria. Physical activity was estimated with a 24 h recall at the beginning and the end of the nutritional intervention.

Products assayed

The products employed for the intervention trial (Enerzona © ) were supplied by Equipe Enervit. These products are manufactured following a characteristic 40-30-30 energy distribution, with 40% of energy provided by proteins, 30% energy provided by carbohydrates and 30% energy provided by lipids. Additionally, all products are of low glycemic index (under 55 units). The variety of products assayed (Table 1), which volunteers had to consume all of them, with alternate options for each day, consisted on bars (27 g) with different flavors (orange, coconut, vanilla, cocoa and yoghourt), milk shakes (50 g) to dissolve in 150 mL semi-skimmed milk (chocolate, strawberry-yoghourt and cappuccino flavors), salted snacks (25 g packs, black olives and mediterranean style), biscuits (50 g/8 units, coconut, cocoa and oat) and minirock snacks (25 g/pack, soy and chocolate chips).

Study volunteers

Subjects participating in the nutritional intervention had to fulfill the following inclusion criteria: to be type-2 diabetes diagnosed patients, aged between 45 and 75 years old, following the dietary recommendations prescribed by their primary care physician, and eventually treated only with metformin (stable dosage during at least three months).

Exclusion criteria, which were controlled by a specifically trained physician, were to have a BMI under 22 or over 35 kg/m 2 , to follow a pharmacological treatment with other drugs but metformin, or being already insulindependent, to have other concomitant pharmacological treatments for weight loss, hormonal substitutive therapy, altered thyroid function, etc. without an stable dosage (at least three months prior the beginning of the study).

Additional exclusion criteria were to suffer from complications due to type 2 diabetes (microangiopathy, polyneuropathy, cardiopathy, hepatic and renal impairments, etc) or having a recent (within the three months prior to the beginning of the study) uncontrolled diagnostic of hypercholesterolemia and/or hypertryglyceridemia.

Sample size calculation

Assuming a maximum loss of 0.6 kg/week, and expecting a total weight loss during the intervention period of 2.4 ± 2.5 kg compared to the free-living period, for an α value of 0.05 (5%) and an statistical power of 80%, the number of participants needed was estimated at 13 volunteers. Assuming an expected 20% drop-out during the trial, the minimum sample size required was established at 16 volunteers.

Anthropometrical measures

Body weight, and body composition status were measured by a bioimpedance equipment (Tanita SC-330, Tanita corp, Japan), waist and hip circumferences were measured with a commercial measure tap following validated protocols [22]. Measures were taken with the participants in a fasting state of at least 8 hours.

Glucose metabolism determinations

Fasting glycosylated hemoglobin levels were assessed at the Clinica Universidad de Navarra (Pamplona, Spain), by a high pressure liquid chromatography (HPLC) methodology [23]. Serum glucose was measured in an autoanalyser Pentra C-200 (HORIBA ABX, Madrid, Spain) and insulin concentrations were determined by an enzyme-linked immunosorbent assay (ELISA) kit (Mercodia, Uppsala, Sweden) in a Triturus autoanalyser (Grifols SA, Barcelona, Spain). Insulin resistance was estimated by the Homeostasis Model Assessment Index (HOMA-IR), which was calculated as stated in the following formula [24]: HOMA-IR = [glucose (mmol/L) × insulin (µU/ml)]/22, 5 Postprandial serum glucose and insulin levels were also measured at 30, 60 and 120 minutes after the consumption of both the habitual breakfast and the test breakfast with 40-30-30 products at weeks 4 and 8, respectively.

Lipid metabolism variables

Total cholesterol, HDL-cholesterol and triglyceride serum concentrations were measured in an autoanalyser Pentra C-200 (HORIBA ABX, Madrid, Spain). LDL-cholesterol levels were calculated following the Friedewald formula [25].

Inflammatory markers

C -reactive protein concentrations were analysed by an ELISA assay (Inmunodiagnostics, MA, USA) in a Triturus autoanalyser (Grifols SA, Barcelona, Spain). Homocysteine was determined in an autoanalyser Pentra C-200 (HORIBA ABX, Madrid, Spain).

Dietary intake and satiety assessment

During the free-living period and during the nutritional intervention period, participants filled two 72 h dietary records, in which they must declare all the foods and quantities they had eaten in each period [26]. These questionnaires were further analysed with the DIAL software (Alce Ingenieria, Madrid, Spain).

Satiety was measured through self-reported questionnaires previously validated [27], based on a Visual Analogue Scale (VAS). Volunteers filled a total of four questionnaires during the postprandial glucose curves (before, having breakfast, 30, 60 and 120 minutes after having breakfast) at weeks 4 and 8.

Statistics

The differences on variables between the beginning and the end of each period were analysed by a paired t-test, while the analysis of differences between both periods (free-living vs. intervention) was performed through an independent measures t-test. Postprandial glucose and insulin concentrations were analysed through a repeated measures ANOVA. Values of p < 0.05 were considered as statistically significant. All the statistical analysis were performed with the SPSS 15.1 software for Windows (SPSS Inc, Chicago, USA).

Results

Adherence to the nutritional intervention

Fifty-two subjects suffering from type-2 diabetes demonstrated an interest in participating on the study. Once at the Metabolic Unit, staff explained to them the complete protocol of the present nutritional intervention, 12 subjects declined the invitation to participate, and another 23 patients were excluded for not fulfilling the inclusion criteria: 11 were on another pharmacological treatment but not metformin, 6 subjects had a recent diabetes diagnostic and treatment was not yet established and 5 subjects were not within the requested age range, while another subject exceeded BMI criteria.

Finally, 17 selected volunteers started the study, from which 2 subjects withdrew before the final visit, whose baseline anthropometrical characteristics of the participants are reported (Table 2).

Changes in anthropometrical parameters

Initial BMI on volunteers was of 28.6 kg/m 2 . Body weight remained unchanged during the free-living period (from week 0 to week 4), while a statistically significant decrease of about 1 kg was detected (Figure 1a) during the intervention period (week 4-week 8). Interestingly this change was observed without apparently associated changes in total energy intake (Table 3). In fact, energy intake was slightly higher in the intervention period (ns). This weight reduction was associated to a marked (p < 0.02) fat mass loss (0.8 kg), without statistically significant changes in fat-free mass (Figure 1b).

Food intake and satiety assessment

Total energy intake did not greatly differ between the free-living and the nutritional intervention period (table  3), while protein intake significantly increased during the dietary snacking substitution with 40-30-30 products. Caloric profile in breakfast, morning and afternoon snack switched from a typical distribution around    (45) Values are Mean ± SD. Values within parentheses concern % of energy supplied by the respective macronutrients * Significant differences (p < 0.05) between the free-living period and the intervention period breakfast (Figure 2), while the values obtained during the 120 minutes postprandial state were as expected.

Changes in biochemical biomarkers

Blood analysis did not evidence statistically significant changes in any biochemical measurement during the whole study (table 4). Equally, postprandial glucose and insulin responses were similar in both periods (Figure 3).

Discussion

The present trial reports the benefits of including within the habitual diet, different moderately high protein products (40% Carbohydrates-30% protein-30% lipids) for weight management, following a chronologically scheduled pattern. Thus it has been demonstrated that, within a free-living diet without dietary or energy restrictions, the substitution of a single meal by products with higher protein content resulted in a weight loss, due mainly to a fat mass reduction. In this sense, the results obtained with this work are in accordance with data previously reported [26,[28][29][30][31].

Ad libitum diets with high protein intake have been considered as useful approaches for effective weight loss and later maintenance [11,28,29]. Indeed, some longterm studies with no calorie restriction and programmed macronutrient distribution have resulted in a more effective weight loss and maintenance than conventional macronutrient distribution energy-restricted diets [11,30,31]. In a recent study, an isocaloric diet with a moderately high content in protein led to a body weight and fat mass reduction after 10 weeks [26], without affecting fat-free mass and maintaining glucose and lipid profile, which matches with the outcomes of the current intervention.

The short duration of the present trial together with a total modest increase of the total protein intake (from  18 to 22% of caloric intake) may have played a role on the slight, although statistically significant, weight and fat mass reduction (approximately 1 kg). However, a period of 4 weeks is a good predictor of body fat changes with a dietary approach [32,33]. Indeed, when analyzing meals separately, the total protein content in breakfast, morning and afternoon snack has been increased in a range from 50 to 95% during the intervention compared to the free-living period, which seemed to be enough to produce a body weight reduction without caloric restriction, and gives support about the importance on timing of energy consumption, meal  frequency and nutrient quality intake for weight maintenance [3,4,8,11,12,34].

The combination of protein content and glycemic index in a diet could be determinant on body composition changes [11,35]. In a recent study in Europe [11], it has been demonstrated the efficacy of high-protein, lowglycemic index diets on adults for weight maintenance [11]. In this same study, it was suggested that the isolated effect of protein content or glycemic index in ad libitum diets did not influence body weight in children, while the conjunction of these two dietary factors has been shown as protective against obesity [35]. Likewise, the current dietary intervention achieved an increase in protein intake together with a low glycemic index in the substituted meals, which may explain the observed improvement in body composition as assessed by bioimpedance measurements, a method which has been recently validated in our research group using Dual X-Ray Absorptiometry (DXA) as gold standard reference [22].

For the first time to our knowledge, it has been demonstrated that the inclusion of some specific meals in the habitual diet with high-protein low-glycemic index products may be sufficient for weight management, preserving lean mass and helping to decrease fat mass in type-2 diabetes patients, compared to a control period of free-living diet. These effects should be ascribed to the protein induced rise in thermogenesis [7,11,26,36,37], or even to the increased satiety consequence of high protein ingestion [38,39], although the assessed satiety scores have not reflected this effect in the current study.

In relation to the lack of changes concerning glucose and insulin levels as well as the insulin resistance index, it may be due to the short intervention period, although previous studies with similar or even shorter periods have shown clinically relevant effects with respect to an improvement on insulin sensitivity [9].

Furthermore, contrasting with other nutritional intervention studies, our results did not show differences between the free-living and the intervention periods on lipid metabolism. Several studies have evidenced that exchanging protein for fat improves lipid-related cardiovascular risk profile [36,40]. However, most of these studies used energy-restricted, lowfat, high-protein diets [37,[40][41][42][43]. Indeed, all the foods included in these hypocaloric diets were low fat products, decreasing also saturated fat intake, which could be one of the main factors involved in the reduction of total and LDL cholesterol. On the other hand and in agreement with our findings, several studies comparing high protein diets have not observed changes in lipid profile, concretely on total and LDL cholesterol [7,37,42]. However, a recent study by Morenga and co-workers [36] found that an ad libitum diet relatively high in protein improved total cholesterol and lowdensity lipoprotein cholesterol in comparison with standard dietary advice. In this case, the fiber content of the diet was also relatively high (>35 g per day), which could counteract the high fat consumption in this group [36]. It is important to point out that, in the present study, the driven substitution of specific single meals by 40-30-30 products, led to a modest increase in the total dietary daily protein content (22%), which is lower than the quantities routinely used in high protein intervention programmes [36].

High protein diets have been also related with reductions in triglyceride levels [36,37,44,45]. Comparing the duration of the present nutritional intervention period to other nutritional programmes, this one may have been relatively short to achieve significant changes in triglyceride levels. Indeed, triglyceride levels tended to be lower at the end of the nutritional intervention period in spite of not reaching statistical significance. Moreover, the effect on triglyceride levels has not always been observed in longer dietary interventions with a moderately high-protein content [7,46] A limitation encountered for the implementation of the current nutritional intervention has been the low sample size and the limited duration of the intervention, which can not permit us to generalize the outcomes obtained without further research. However, it is generally assumed that finding statistical significance with a small population is more difficult than when having a higher sample size. This outcome usually indicates that there is a real difference between the experimental periods. In any case, a type II error can not be discarded [47]. Furthermore, as the study was designed as a longitudinal intervention with two consecutive periods, the first period is really a control, where the researchers only performed observational follow-up work. This approach has been already successfully employed and published elsewhere [48][49][50][51].

The overall results of this study may have been partly affected by the fact that the participants in the nutritional intervention were type-2 diabetes patients with initially controlled dietary treatment. In fact, the glycemic indexes in the breakfast, morning and afternoon snack during the free-living period were relatively low at baseline (< 55 units), and similar to the glycemic load reached with the products assayed. Thus, in another trial [38], the consumption of a low glycemic index breakfast during 21 days, compared to a high glycemic breakfast, led to a significant reduction on fasting glucose levels without affecting other biochemical biomarkers in obese subjects. In addition, a benefit on satiety was also reported, as it increased with the low glycemic index meal [38], which was not seen in the current trial.

These observations suggest that in this population, the moment/time of consumption may be relevant in interpreting the results.

Moreover, when comparing two hypocaloric diets differing in the glycemic index, beneficial additional effects were found after weight loss (-5.3% vs. -7.5% change with the high-or low-glycemic diet, respectively) as well as in total-and LDL-cholesterol concentrations, where the decrease was 4-fold higher in the low glycemic index diet [52].

The reduction of glycemic index in a specific meal [38] or a diet [39] has also been associated to an increase in the satiety and a reduction on the voluntary food intake during the postprandial state. Indeed, the voluntary food intake may be an 80% higher after the consumption of a high glycemic vs. a low glycemic index meal [39]. In this context, it is also in agreement with previous studies the similarity of the satiety scores observed between the free-living period and the intervention period in the present trial, as glycemic index remained unchanged between both periods.

The present results together with those from others [19,34,38] indicate the evident benefits of nutritional interventions on selected meals, giving an increasing importance to chrononutrition and meal frequency intake. Therefore, this is a good example of translational research carried out in a limited number of volunteers.

Conclusions

Summing up, the present trial evidences that small changes in the habitual dietary recommendations in type-2 diabetes patients by the inclusion of specific lowglycemic, moderately high-protein products in breakfast, morning and afternoon snacks may promote body weight and fat-mass loss, without apparently altering biochemical parameters and cardiovascular risk-related factors. The importance of these findings are related to the novelty of demonstrating that increasing protein content of selected meals offered in specific moments (breakfast, morning and afternoon snack) leads to an improvement in body composition, and it is also important to highlight the effect of regulating meal frequency and timing as a basis for future research concerning chrononutrition.

Figure 1
130 products consumption. No changes were observed in relation to physical activity during the intervention period (data not shown).The analysis of the VAS questionnaire during the postprandial glucose curve, revealed no differences on hunger, satiety, satisfaction, intake and thirst (not shown), between the habitual breakfast or the 40-30-30 Anthropometrical changes during the study. The free living period corresponds to week 0 -week 4, while the nutritional intervention with 40-30-30 products corresponds to weeks 4-8. 1a: Body weight evolution. 1b: Fat mass Vs Fat-free mass.

Figure 2
2VAS postprandial questionnaire results. 2(a). Hunger score; 2(b). Satiety score; 2(c). Satisfaction score; 2(d) Intake score.

Figure 3
3Postprandial glucose and insulin curves either with the habitual breakfast and the 40-30-30 snacks, which were not significantly different. 3a: Postprandial glucose curve. 3b: Postprandial insulin curve.

Table 1
1Substitution guidelines during the intervention period of the volunteers' habitual breakfast, morning and afternoon snack.Breakfast (choose alternatively one option each day)

Females
Males

• 3 bars
• 4 bars

or

Table 2
2Anthropometrical baseline characteristics of the subjects who completed the study (n = 15).There were no differences in anthropometrical features at the beginning of the second phase of the study compared to the values shown.VARIABLE
MEAN
SD

Weight (kg)
82.5
12.7

BMI (kg/m 2 )
28.6
4.3

Waist circumference (cm)
102.0
10.7
Hip circumference (cm)
102.7
9.8

Fat mass (%)
29.5
8.1

Fat-free mass (kg)
58.4
6.9

Water (%)
50.7
2.9

Table 3
3Changes in macronutrient intake between the free-living and the intervention periodFREE-LIVING PERIOD (WEEK 0 TO 4)
INTERVENTION PERIOD (WEEK 4 TO 8)

Daily intake Breakfast
Morning
snack

Lunch
Afternoon
snack

Dinner
Daily intake Breakfast
Morning
snack

Lunch
Afternoon
snack

Dinner

Energy (kcal)
1710 ± 354
300 ± 168
93 ± 86
713 ± 115
110 ± 86
493 ± 223
1815 ± 335
346 ± 59
111 ± 54
722 ±
154

111 ± 66
524 ±
238

Carbohydrates
(g)

152 ± 52
(36)

39 ± 24
(52)

12 ± 11
(52)

51 ± 21
(29)

12 ± 11
(44)

38 ± 23
(31)

145 ± 48
(32)

34 ± 6
(39)

10 ± 4
(36)

53 ± 29
(30)

10 ± 6
(36)

38 ± 18
(29)

-Sugars (g)
73 ± 25
23 ± 17
8 ± 8
17 ± 7
7 ± 7
18 ± 8
72 ± 16
26 ± 6
7 ± 4
15 ± 7
7 ± 5
15 ± 9

Glycemic Index
51 ± 10
43 ± 22
37 ± 21
58 ± 9
40 ± 10
40 ± 10

Fiber (g)
20 ± 8
4 ± 3
1 ± 1
9 ± 6
1 ± 1
5 ± 2
22 ± 7
4 ± 1
1 ± 1
10 ± 5
1 ± 1
5 ± 2

Proteins (g)
78 ± 16* (18)
11 ± 6*
(15)

4 ± 5*
(17)

37 ± 7
(21)

4 ± 4
(15)

21 ± 13
(17)

100 ± 15*
(22)

25 ± 5*
(29)

7 ± 3*
(25)

36 ± 9
(20)

7 ± 5
(25)

24 ± 11
(18)

Lipids (g)
74 ± 13 (39)
10 ± 6
(30)

2 ± 2
(19)

33 ± 6
(42)

4 ± 3
(33)

24 ± 12
(44)

79 ± 15
(39)

12 ± 2
(31)

4 ± 1
(32)

35 ± 9
(44)

4 ± 2
(32)

26 ± 11

Table 4
4Changes in biochemical determinations between the beginning and the end of the study.Baseline
Final
p

Navas-Carretero et al. Nutrition Journal 2011, 10:74 http://www.nutritionj.com/content/10/1/74 Page 8 of 11
Acknowledgements and FundingThe authors are grateful to the volunteers of the study, as well as Mutilva medical center for the support on volunteers' recruitment, specifically Dr. Carmen Frauca. They also want to thank clinical and laboratory support to Blanca Martinez de Morentin, Salome Perez and Veronica Ciaurriz. The supply of the high-protein, low-glycemic index products from Equipe Enervit, and the partial funding from Rovi Laboratories SA is gratefully acknowledged. This study was also funded by the special research line "Nutrition, Health and Obesity" of the University of Navarra (LE/97).Authors' contributions SNC participated in the design of the study, development of the trial, outcomes measurements, data analysis and drafted the final manuscript. IA participated in the design of the study, outcomes measurements and drafted the final manuscript. MAZ participated in the design of the study, data analysis and helped to draft the final manuscript. JAM conceived the study, participated on its design and coordination and performed a critical review of the final manuscript. He also managed the funding to carry out the intervention. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.
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