Background: Rigorous evidence is needed regarding the best approach for increasing the uptake of Diabetes Canada’s evidence-based recommendations to include low-glycemic index (GI) foods in daily meal planning as an effective dietary self-care strategy for glycemic control among people with type 2 diabetes (T2D).
Objective: This study aims to present the study design and baseline data from the Healthy Eating and Active Living for Diabetes-Glycemic Index (HEALD-GI) trial, which was designed to evaluate the effectiveness of an enhanced GI-targeted nutrition education on GI-related knowledge and mean daily GI among adults with T2D in Edmonton, Alberta.
Methods: We used a pragmatic randomized controlled trial design and allocated 67 adults (aged ≥18 years) with T2D living in Edmonton, Alberta, Canada, to a control group that received standard printed copies of Canada’s Food Guide and Diabetes Canada’s GI resources or to an intervention group that received the same materials, plus a customized Web-based platform with 6 self-directed learning modules and print material. Each module included videos, links to reliable websites, chat rooms, and quizzes. Evidence-based GI concept information included GI values of foods and low-GI shopping, recipes, and cooking tips by a registered dietitian. In addition, support through email, text messaging (short message service), phone calls, or postal mail was provided to reinforce participants’ learning. The primary outcome, average dietary GI, was assessed using 3-day food records. Additional measures including GI knowledge and self-efficacy, glycated hemoglobin (HbA1c), lipids, systolic blood pressure, body mass index (BMI; weight, height), waist circumference, and computer proficiency were assessed at baseline and at 3-month postintervention.
Results: Between November 2017 and February 2018, we contacted adults (aged ≥18 years) with T2D living in Edmonton, Alberta, screened and recruited eligible participants into the study. All data collection ended in June 2018. Overall, 64% (43/67) participants were males; mean age was 69.5 (SD 9.3) years, with a mean diabetes duration of 19.0 (SD 13.7) years. Mean BMI was 30.1 (SD 5.7) kg/m2, and mean HbA1c value was 7.1% (SD 1.2%). Data analysis was completed in December 2018.
Conclusions: The GI concept is often difficult to teach. The HEALD-GI study aims to provide evidence in support of an alternative approach to translating the GI concept to adults with T2D. Findings from this study may help registered dietitians to better disseminate low-GI dietary recommendations using efficient and cost-effective, patient-centered approaches. Furthermore, evidence generated will contribute to addressing some of the controversies regarding the clinical usefulness of the GI concept.
International Registered Report Identifier (IRRID): DERR1-10.2196/11707
Increasing prevalence of type 2 diabetes (T2D) remains a major public health challenge with adverse effects for individuals and health care systems globally. Currently, diabetes affects approximately 7.3% of Canadians, and the prevalence has been projected to rise to about 10% by 2020 . Health outcomes for individuals with diabetes, however, largely depend on their ability to self-manage the disease. Lifestyle interventions including healthy eating, physical activity, and smoking cessation, which enhance the acquisition of knowledge, skills, resources, and support to boost self-efficacy for day-to-day living, are, therefore, important for T2D management and prevention of long-term complications [ , ].
Healthy eating remains a key strategy for diabetes self-management, and dietary carbohydrates constitute one aspect of the diet with significant influence on blood glucose control. Different types and quantities of carbohydrates have been shown to impact blood glucose concentration differently [, ]. This property of foods, referred to as glycemic index (GI), is used to rank how quickly a given dietary carbohydrate raises blood glucose concentration immediately following a meal [ ]. Using GI and the portion size of a given food, glycemic load (GL), a composite measure of carbohydrate quality and quantity, can be calculated to predict blood glucose response to a specific type and amount of a dietary carbohydrate [ ]. Consuming low-GI foods is beneficial for metabolic control in diabetes management [ ]. Adopting a low-GI dietary pattern as part of a healthy eating lifestyle has been shown to markedly reduce cardiovascular risk factors (eg, total cholesterol, high-density lipoprotein); improve glycemic control, postprandial glycemia, and beta cell function; and decrease the need for antihyperglycemic agents among patients with diabetes [ - ]. Outlining effective approaches to promoting the concept of low-GI intake among individuals with T2D has been problematic. Hence, examining effective modes of delivery is necessary to support one aspect of T2D.
Effective and widespread use of information technologies (ITs), including the internet and mobile-based tools, is revolutionizing the traditional approaches for engaging, educating, and empowering individuals with chronic diseases such as diabetes [, ]. Increasing use of IT by diverse audiences, occasioned by low-cost Web- and mobile-based tools may, therefore, offer viable prospects for promoting swift and cost-effective GI concept education and support among people with T2D. Features of modern IT tools such as websites, chat rooms, social networking sites (eg, Facebook), and short message service (SMS) text messaging apps allow creation and exchange of health-promoting information and enable individuals to interact with other users who share connections with them [ , ]. Properly designed and managed websites can serve as credible sources of evidence-based GI-targeted messages. Websites enable integration and presentation of text, graphics, or audiovisuals on one platform, while chat rooms and emails facilitate engagement between users and health professionals in addressing pertinent issues [ ]. Furthermore, chat rooms provide Web-based social forums for peer group discussions, exchange of ideas, encouragement, and support [ , ].
Knowledge gaps exist between GI concept clinical guidelines and their translation to adults with T2D in Canada due to debates over clinical utility of GI, inconsistencies in teaching the GI concept by registered dietitians [, ], and limited patient-dietitian interactions [ ]; these limit patients’ knowledge and skills for uptake of GI dietary behavior. Patients lose out on the additional benefits of improving carbohydrate quality by consuming healthy, low-GI foods as part of healthy eating strategy for diabetes self-management. Hence, this study aims to examine the effectiveness of Web-based, GI-targeted nutrition education on dietary behavior and intakes among adults with T2D. We hypothesize that after 3 months, adults with T2D who were randomized to receive Web-based, GI-targeted nutrition education will consume a lower-GI diet and show improved glycemic control compared with a control group. Findings from this study will help determine whether, and how, current approaches to disseminating dietary recommendations pertaining to GI concept could be improved for better uptake using alternative, efficient, and cost-effective patient-centered approaches to nutrition self-care. Furthermore, the outcomes of this study will add to the body of evidence regarding the GI concept.
Study Design: Setting, Recruitment, Ethical Considerations, and Intervention
Setting and Population
Adults (aged ≥18 years) living in Edmonton, Alberta, Canada, with T2D and currently enrolled in the Alberta’s Caring for Diabetes (ABCD) cohort study  constituted the target population for this study. The ABCD cohort study [ ] was designed to explore different aspects of diabetes care and the development of complications among individuals with T2D in Alberta. The ABCD cohort enrolled 2040 participants between 2012 and 2013 from all over the province of Alberta at inception and provided a suitable eligible population from which to draw participants for this intervention. The characteristics of the ABCD cohort have been reported elsewhere [ ].
Inclusion and Exclusion Criteria
The inclusion criteria were as follows: individuals aged ≥18 years identified as having T2D and currently enrolled in the ABCD cohort study; able to read, understand, and converse in English; and willing to provide informed consent. For practical considerations, we prescreened all cohort participants living in Edmonton for enrollment in the intervention. Based on postal codes, 745 cohort participants who participated in the year 1 ABCD survey lived in Edmonton. However, due to relocation and mortality-related attrition, we invited only 485 ABCD cohort participants living in Edmonton between July 2017 and October 2017 to participate. Those who responded were screened for eligibility and subsequent recruitment into the study between November 2017 and February 2018. Those taking exogenous insulin and having physiological or medical conditions that interfere with usual digestive functions were excluded.
Participants Screening Procedures
We sent letters explaining details of the study to all eligible participants, asking them to contact the study staff if they were interested in participating in this study. We performed detailed prescreening over the phone to determine full eligibility once we received responses from those invited to participate. A maximum of 2 telephone contacts were made to remind eligible individuals who did not contact the research staff after 2 weeks of expressing their interest in participating in the study. We invited eligible participants to complete baseline anthropometry, biochemical, clinical, and dietary data collection at the Human Nutrition Research Unit located within the Alberta Diabetes Institute at the University of Alberta. A trained dietitian and registered nurse with data collection experience collected anthropometric data and relevant clinical measures using point-of-care instruments (DCA Vantage, Cholestech LDX, and BPTru).
The University of Alberta and Athabasca University Health Research Ethics Boards reviewed and approved the study protocol. In line with research ethics requirements, all participants received adequate information about the study and had the opportunity to ask questions. We obtained written informed consent from participants prior to obtaining any study measurements after providing them an explanation of (1) the purpose of the study; (2) the allocation process; (3) the use of data and the means of assuring confidentiality; (4) voluntary participation and the participants’ right to withdraw from the study at any time; and (5) any potential harm that could occur as a result of the intervention.
Randomization and Treatment Allocation
Using a pragmatic randomized trial design, we randomly allocated 67 eligible participants drawn from the ABCD cohort  who provided informed consent and completed baseline anthropometry, clinical, and dietary measurements to either the usual care or to intervention in a 1:1 ratio using a computer-generated allocation sequence (Stata SE 12.1; StataCorp) [ ]. Allocation sequence and group assignments were generated centrally and enclosed in sequentially numbered and sealed envelopes. A statistician not involved with other aspects of the trial performed all randomization-related procedures.
Study participants allocated to the usual care (control arm) received standard printed copies of Canada’s Food Guide and Diabetes Canada (formerly Canadian Diabetes Association) GI resources in line with current Diabetes Canada Clinical Practice Guidelines [, ]. The control group did not receive extra support aimed at increasing knowledge or skills for daily consumption of low-GI foods.
Enhanced Glycemic Index-Targeted Nutrition Education
Participants (n=33) allocated to the enhanced low-GI education intervention group received the same information as the control group in addition to vetted, evidence-based, learner-centered, low-cost, and actionable low-GI messages delivered through a Web-based platform with chat rooms, customized videos featuring a registered dietitian, and print material. Based on individual preference and needs, we provided additional support through email, SMS text messages, phone calls, or mail to reinforce participants’ learning. The GI concept and content of this intervention were in line with current Diabetes Canada Clinical Practice Guidelines as well as T2D patients’ suggested content and preferred modes of learning GI information [, ]. The intervention website was managed by a trained research assistant who also moderated chat room discussions under the supervision of coinvestigators: KS, a registered dietitian and researcher, and STJ and JAJ, who also possess extensive research experience.
Participants received brief tutorials on website log-in, navigation, and usage during baseline data collection, which was reinforced at first log-in with a short video introduction to the program. The video emphasized the importance of low-GI eating and summarized the various aspects of the intervention. Those allocated to the intervention group covered a total of 6 modules over 12 weeks. These modules were aimed at enhancing knowledge and skills for improved GI dietary behavior change. Each module included customized videos featuring a registered dietitian, links to reliable websites, chat rooms for social support, and quizzes. Evidence-based GI content included GI values of foods; low-GI shopping, recipes, and cooking tips; and advice for eating out. Participants received a new module every 2 weeks. Specific topics covered in these modules included (1) general healthy eating for diabetes patients; (2) summary of the GI concept; (3) identifying, choosing, and shopping low-GI foods; (4) low-GI recipes, menus, and meal planning; (5) guidelines for eating out and snacking; and (6) GI concept and general diabetes self-management and healthy lifestyles. Participants were encouraged to outline and track personal, easily achievable goals that could enhance their GI knowledge and skills under each module. For example, in module 3, a participant could set a simple goal to learn how to identify low-GI versions of foods that he or she usually consumed. We delivered each module through the intervention website using user-friendly text, graphical displays, and module summary videos. All videos were developed in line with Canada’s Food Guide and Diabetes Canada Nutrition Therapy Clinical Practice Guidelines-based GI recommendations [, ] to teach participants “hands-on” application of GI to daily meal planning.
To sustain enthusiasm, participants were granted access to subsequent modules at the end of the preceding module on the first day of each 2-week cycle; this was accompanied with electronic reminders delivered through email or SMS text message based on participants’ choosing. Participants responded to short quizzes meant to bolster key GI principles and lessons learned. Chat rooms were activated for each module to enable participants to share experiences in the form of success stories, challenges, and tips that enhance a sense of community for social support among participants. The chat room forum was monitored, and timely responses were provided to questions and concerns of participants. In addition, we provided weblinks to the international tables of GI and GL values of foods  and additional evidence-based information on GI concept as well as general diabetes self-management and healthy lifestyles. A review of similar Web-based studies has shown that interventions that provide interactive elements such as the following have been effective at generating and sustaining participants’ interest and exposure to Web-based interventions: (1) quizzes, searchable database, audio or video; (2) counselor support through counselor-led chat sessions, email, or phone contacts; (3) peer support through Web-based discussion forums or chats; and (4) regular updates of information on intervention websites [ ].
Participants in the enhanced GI education arm also received copies of “The Shopper’s Guide to GI Values: the Authoritative Source of Glycemic Index Values for More Than 1,200 Foods”  in line with T2D patients’ preference for print-based material as a source GI information [ ]. Briefly, the Shopper’s Guide, which was recommended to participants seeking to know more about GI in a previous study [ ], is a lightweight, handy book coauthored by expert GI research scientists. It contains GI values of over 1200 foods arranged by categories to help identify healthier low-GI carbohydrate alternatives using handy household measures. The Shopper’s Guide is updated regularly and has comprehensive data on carbohydrates per serving and GL, a shopping list of low-GI essentials, ideas for gluten-free meals, facts about sugar and sweeteners, and tips for everyday meals and dining out. Furthermore, the Shopper’s Guide provides links to supplementary resources with reliable, evidence-based GI information [ ].
In addition to the website and the Shoppers Guide , participants in the intervention arm were offered periodic emails, SMS text messages or telephone calls, or postal mail prompts to visit the website and/or use the print materials to acquire more GI knowledge as per individual preference. Participants were encouraged to use these mediums to seek assistance regarding specific personal dietary issues, which they may not want to post in the chat room discussion section of the website.
Assessment of Study Outcomes
Our primary outcome measure was GI-related dietary behavior change and intake, measured using a 3-day food record.
Dietary Assessment, Glycemic Index, and Glycemic Load Estimation
Daily dietary intake was assessed for all participants at baseline and at 3 months using a 3-day food record. The 3-day food records are valid and reliable for capturing dietary behavior change by asking participants to record their food consumption as they eat . All participants were asked to record, in as much detail as possible, descriptions of foods and beverages consumed over a 3-day period (ie, 2 weekdays and 1 weekend day). Participants were given further instructions on how to fill out the 3-day food record. Color photographs were provided to assist participants with estimating and recording appropriate portion sizes of foods and beverages they consumed in the 3-day food record logbooks. Pictures showing sample portions sizes of foods measured against items including a finger, palm of a hand, and a hockey puck were included and participants were encouraged to choose photographs that best represented their portion sizes or specify whether they consumed more or less. Mean daily food consumption and nutrient intake were estimated using the Food Processor Diet Analysis and Fitness Software (ESHA Research) at baseline and 3 months using the Canadian nutrient file.
All carbohydrate-containing foods identified from the 3-day food records were assigned GI values corresponding to the best geographic and botanical matches in the published International Table of Glycemic Index and Glycemic Load Values [, ] or the updated University of Sydney Web-based database [ , ]. GI values were averaged for foods having more than one GI value from very similar matches. As the International Table and the University of Sydney Web-based databases do not provide an exhaustive entry of glycemic data for every food, the instances where foods could not be matched directly to those in the International Tables or Web-based database, GI values were calculated from the estimated GL [ ] or matched to listed foods with similar characteristics (ingredients, composition, and physical properties) based on all information available to HMA, a trained dietitian, and from his subjective experience and knowledge of foods [ - ]. As recommended [ , , ], daily average GI and GL was calculated for all carbohydrate-containing foods identified from the 3-day food records using published international GI tables [ , ] ( ).
Secondary outcome measures, including GI knowledge and skills, self-efficacy, body mass index (BMI; weight and height), waist circumference, clinical measures (glycated hemoglobin [HbA1c], systolic blood pressure, total cholesterol, and high-density lipoprotein), and computer proficiency were assessed at the baseline and at 3 months after completing the intervention. In addition, demographic data were collected.
Glycemic Index Knowledge and Self-Efficacy Assessment
Pre- and postintervention GI concept knowledge and self-efficacy were assessed and quantified using the Glycemic Index Foods Quiz from a previous study . Dietary data from a previous intervention within the same population showed that, out of 196 participants, 16% were not familiar with low-GI eating and 28% did not include low-GI foods in their diets [ ]. About 35% (70/199) indicated that they did not know about GI, and of those who claimed the knowledge of GI, only 34% reported choosing low-GI foods for >6 months in another study [ ]. These corroborate previous findings in which only 38% of people with diabetes received nutrition therapy across Canada [ ] with <40% of dietitians including the GI concept in T2D dietary self-care counseling [ , ]. Overall dietary self-care behavior was assessed using dietary items in the validated and widely used Summary of Diabetes Self-care Activities measure [ ]. The Glycemic Index Foods Quiz, therefore, enabled assessment of the net change in GI knowledge and self-efficacy due to the intervention.
Clinical and Anthropometric Measures
Clinical outcome measures included HbA1c, systolic blood pressure, and lipid profile. Capillary blood samples (35 μL) were collected from participants to assess HbA1c value using previously validated point-of-care testing device for HbA1c (DCA Vantage)  and lipid profile (Cholestech LDX). Systolic blood pressure was measured according to the standard protocols using (BPTru) [ ].
In addition, weight, height, and waist circumference were assessed according to the Canadian Physical Activity, Fitness and Lifestyle Appraisal procedures . Body weight in kilograms (kg) and height in meters (m) were measured for each subject in light clothing and with no shoes on. Body weight was measured to the nearest 0.1 kg with a portable digital scale (Tanita BWB-800S, Arlington Heights, IL, USA), and height was measured using a portable stadiometer (Tanita HR-100). Waist circumference was measured to 1 mm at the top of the iliac crest using a spring-loaded Gulick anthropometric tape (FitSystems Inc, Calgary, AB, Canada). Regular, monthly quality assurance checks were conducted on the point-of-care devices and scale.
Self-reported physical activity was assessed using the Godin Leisure Time Exercise Questionnaire ; the validity of this questionnaire is well established [ ], and data suggest that self-reported physical activity estimates function as a suitable predictor of future behavior [ ]. Participants were asked to report the frequency and duration of light-, moderate-, and vigorous-intensity leisure-time physical activity that lasted at least 10 minutes over a typical week during the past month. The number of weekly minutes for each intensity level was calculated by multiplying the frequency of activity by the duration in minutes. The sum of weekly minutes of moderate-to-vigorous physical activity (MVPA) gave the total MVPA minutes per week.
Participants’ computer proficiency was measured using the Computer Proficiency Questionnaire (CPQ) at baseline and 3-month postintervention. The CPQ was developed for evaluating the competencies of seniors with regards to use of computers and associated applications such as the internet . The CPQ assesses competence across 6 different subscales: computer basics, printing, communication, internet, scheduling software (calendar), and multimedia use (entertainment) for gauging an individual’s specific and overall computer proficiency.
Demographic information including age, sex, marital status, education, employment status, income, and personal history of cardiovascular disease risk factors (eg, smoking) and time since T2D diagnosis were collected at baseline using a questionnaire.
Intervention Preference and Website Usage Data
Preference and usefulness of the Web-based, print , email, SMS text messages or telephone call, and postal mail were assessed by asking participants how many times they visited the webpage, read and made references to Shopper’s Guide [ ], and how much time they spent on the website or reading the book. In addition, participants were asked which medium they found most helpful and whether the information about the GI concept was informative and helped increase their knowledge and self-efficacy for consuming low-GI foods. Website data measurement programs were built into the website design to compile data points as connections occur with the target audience [ ]. Regularly collecting, tracking, and using measurement data makes it possible to understand participants’ characteristics and helps keep the intervention appealing and relevant for achieving the greatest effect [ ].
Statistical Analysis, Power, and Sample Size Rationale
Change in the mean daily GI of dietary carbohydrates from baseline to 3 months will be used as our primary effectiveness measure for improved low-GI knowledge and application. Descriptive statistics will be computed for all variables to determine the nature of the data and to test for normality assumptions. Changes in outcomes will be assessed using repeated-measures 2-way analysis of covariance. Potential sociodemographic and clinical factors associated with enhanced GI learning will be evaluated using generalized linear mixed-model analysis. Treatment condition, baseline scores, participant characteristics (eg, sex, education, and income), and computer proficiency that may be significantly related to outcomes will be controlled for. All data will be analyzed using Stata SE 12.1 (StataCorp).
Power and Sample Size Rationale
Based on previous studies regarding the efficacy of GI-based nutritional education and glycemic control [, ] and meta-analysis of studies on low-GI diets and diabetes management [ ], an estimated effect size of d=1 was set for this intervention. Previous data [ ] suggest an SD of GI intake of 4-5 units; thus, an effect size d=1 could be achieved with an absolute mean difference of 5 units of GI intake. Given the estimated effect size, 42 participants (21 per arm) would be sufficient for detecting an absolute mean difference of 5 units on the GI intake scale between means with an error of alpha=.05 (2-sided) and beta=.1 (power 1−β=.90; ); this difference is considered to have significant health benefits from a previous study in which a change of 15 GI units yielded a corresponding HbA1c change of −1.5% [ ] and another study in which a change of 4.6 GI units yielded an HbA1c change of −0.25 (95% CI −0.50 to −0.004) [ ]. With an estimated attrition rate of 30% (based on the ABCD cohort year 2 participation rate), eligible participants were oversampled (N=67) during recruitment to account for possible loss to follow-up during randomization and intervention periods. This sample size was feasible in view of the dietary assessment (3-day food record) method used to assess food intakes and change in dietary GI, the cost of biochemical and clinical measurements, and the duration of the study.
Summary of Progress to Date
Intervention milestones including ethics application, hiring and training of research assistants, and development and pilot-testing of intervention materials ran from July 2016 to October 2017. Data Analysis was completed December 2018.
Recruitment or Enrollment Status and Timelines
Recruitment and enrollment in the Healthy Eating and Active Living for Diabetes-Glycemic Index (HEALD-GI) trial ran from November 2017 to February 2018.shows the flow diagram detailing the recruitment, screening, random allocation, and baseline and follow-up data collection. Baseline and 3-month follow-up data collection were completed in June 2018. Currently, the study database is being compiled in preparation for performing appropriate analyses and dissemination of findings.
Overall, 64% (43/67) participants were males; mean age was 69.5 (SD 9.3) years, with a mean diabetes duration of 19.0 (SD 13.7) years, BMI of 30.1 (SD 5.7) kg/m2, and HbA1c value of 7.1% (SD 1.2%) ().
|Characteristics||All (n=67)||Intervention (n=33)||Control (n=34)|
|Males, n (%)||43 (64)||20 (61)||23 (68)|
|Age (years), mean (SD)||69.5 (9.3)||70.7 (9.0)||68.4 (9.6)|
|Marital status, n (%)|
|Married or common law||47 (70)||20 (61)||27 (79)|
|Not married (never married, widowed, divorced, or refused to answer)||20 (30)||13 (39)||7 (21)|
|Ethnicity, n (%)|
|Caucasian||62 (93)||30 (91)||32 (94)|
|Non-Caucasian||5 (7)||3 (9)||2 (6)|
|High school and less||21 (31)||12 (9)||12 (35)|
|College and higher||46 (69)||24 (73)||22 (65)|
|Employed||10 (15)||2 (6)||8 (23)|
|Unemployed||5 (7)||1 (3)||4 (12)|
|Retired||52 (78)||30 (91)||22 (65)|
|Annual household income (Can $), n (%)|
|<40,000||8 (12)||3 (9)||5 (15)|
|40,000-79,999||30 (45)||16 (49)||14 (41)|
|≥80,000||20 (30)||7 (21)||13 (38)|
|Do not know or refused to answer||9 (13)||7 (21)||2 (6)|
|Diabetes duration (years), mean (SD)||19.0 (13.7)||20.0 (11.7)||18.0 (15.5)|
|Glycated hemoglobin value (%), mean (SD)||7.1 (1.2)||7.0 (1.4)||7.1 (0.9)|
|Lipid profile, mean (SD)|
|Total cholesterol (TC; mmol/L)||4.4 (1.0)||4.3 (1.0)||4.5 (0.9)|
|HDL (High-density lipoprotein; mmol/L)||1.3 (0.4)||1.4 (0.4)||1.3 (0.4)|
|TC/HDL ratio||3.6 (1.5)||3.3 (0.9)||3.9 (1.9)|
|Blood pressure (BP; mm Hg), mean (SD)|
|Systolic BP||127.9 (12.4)||127.7 (9.9)||128.2 (14.6)|
|Diastolic BP||70.1 (10.6)||69.8 (8.1)||70.5 (12.8)|
|Resting heart rate (bpm), mean (SD)||77.8 (14.5)||78.8 (15.3)||76.8 (13.9)|
|Body mass index (kg/m2), mean (SD)||30.1 (5.7)||28.0 (5.1)||32.0 (5.6)|
|Waist circumference (cm), mean (SD)||107.4 (16.1)||102.5 (15.5)||112.2 (15.4)|
This protocol outlines the study rationale, design, and evaluation of the HEALD-GI pragmatic randomized controlled trial and reports the baseline characteristics of 67 individuals living with T2D in Edmonton, Alberta, Canada. The HEALD-GI trial was designed to evaluate the effectiveness of Web-based, GI-targeted nutrition education on GI-related knowledge and intakes among adults with T2D.
Major strengths of this trial include the evidence-informed components of the Web-based enhanced, GI-targeted nutrition education including internet chat rooms for peer support and use of email, SMS text messages, and telephone support, which have been shown to enhance the intervention uptake and effectiveness [, ]. Emails, SMS text messages, and telephone support enable educational content-related exchanges, while chat room platforms in Web-based learning environments enhance social support through creation of relationships that support collaborative learning and sharing of relevant experiences [ - ]. In addition, the involvement of a health professional as a moderator of the Web environment has been shown to enhance Web-based intervention outcomes [ , ]. The provision of “The Shopper’s Guide to GI Values: the Authoritative Source of Glycemic Index Values for More Than 1,200 Foods” [ ] also supports preferences for print-based material as a source GI information [ ]. This may enhance participant knowledge and self-efficacy for low-GI concept uptake. Use of a 3-day food record method for dietary intake data will help curb recall bias, which is often associated with memory-dependent dietary assessment methods such as 24-hour recall [ ].
The GI concept is often difficult to teach. The HEALD-GI study aims to provide evidence in support of an alternative approach to translating the GI concept to adults with T2D. Findings from this study may help registered dietitians to better disseminate low-GI dietary recommendations using the efficient and cost-effective patient-centered approaches. Furthermore, evidence generated will contribute to addressing some of the controversies regarding debates surrounding the clinical usefulness of the GI concept.
Funding for this study was provided by the Canadian Foundation for Dietetic Research and a Knowledge Translation Accelerator Award from the Danone Institute of Canada. The opinions expressed in the written work here are those of the authors only and are not officially endorsed by the funders.
Conflicts of Interest
Multimedia Appendix 1
Sample size and power calculations.PDF File (Adobe PDF File), 40KB
Multimedia Appendix 2
CFDR peer-review feedback.PDF File (Adobe PDF File), 37KB
- Doucet G, Beatty M. The Cost of Diabetes in Canada: The Economic Tsunami. Canadian Journal of Diabetes 2010 Jan;34(1):27-29. [CrossRef]
- Evans RG, Stoddart GL. Producing health, consuming health care. Soc Sci Med 1990;31(12):1347-1363. [Medline]
- Huber M, Knottnerus JA, Green L, van der Horst H, Jadad AR, Kromhout D, et al. How should we define health? BMJ 2011 Jul 26;343:d4163. [CrossRef] [Medline]
- Jenkins DJ, Wolever TM, Taylor RH, Barker H, Fielden H, Baldwin JM, et al. Glycemic index of foods: a physiological basis for carbohydrate exchange. Am J Clin Nutr 1981 Mar;34(3):362-366. [CrossRef] [Medline]
- Thomas D, Elliott EJ. Low glycaemic index, or low glycaemic load, diets for diabetes mellitus. Cochrane Database Syst Rev 2009 Jan 21(1):CD006296. [CrossRef] [Medline]
- Liu S, Willett WC, Stampfer MJ, Hu FB, Franz M, Sampson L, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am J Clin Nutr 2000 Jun;71(6):1455-1461. [CrossRef] [Medline]
- American Diabetes Association, Bantle JP, Wylie-Rosett J, Albright AL, Apovian CM, Clark NG, et al. Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care 2008 Jan;31 Suppl 1:S61-S78. [CrossRef] [Medline]
- Brand-Miller J, Hayne S, Petocz P, Colagiuri S. Low-glycemic index diets in the management of diabetes: a meta-analysis of randomized controlled trials. Diabetes Care 2003 Aug;26(8):2261-2267. [Medline]
- Opperman A, Venter C, Oosthuizen W, Thompson R, Vorster HH. Meta-analysis of the health effects of using the glycaemic index in meal-planning. Br J Nutr 2004 Sep;92(3):367-381. [Medline]
- Thomas D, Elliott EJ. The use of low-glycaemic index diets in diabetes control. Br J Nutr 2010 Sep;104(6):797-802. [CrossRef] [Medline]
- Wolever T, Gibbs A, Mehling C, Chiasson J, Connelly P, Josse R, et al. The Canadian Trial of Carbohydrates in Diabetes (CCD), a 1-y controlled trial of low-glycemic-index dietary carbohydrate in type 2 diabetes: no effect on glycated hemoglobin but reduction in C-reactive protein. Am J Clin Nutr 2008 Jan;87(1):114-125. [CrossRef] [Medline]
- Jenkins D, Kendall C, McKeown-Eyssen G, Josse R, Silverberg J, Booth G, et al. Effect of a low-glycemic index or a high-cereal fiber diet on type 2 diabetes: a randomized trial. JAMA 2008 Dec 17;300(23):2742-2753. [CrossRef] [Medline]
- Wolever T, Mehling C, Chiasson J, Josse R, Leiter L, Maheux P, et al. Low glycaemic index diet and disposition index in type 2 diabetes (the Canadian trial of carbohydrates in diabetes): a randomised controlled trial. Diabetologia 2008 Sep;51(9):1607-1615. [CrossRef] [Medline]
- Amano Y, Sugiyama M, Lee J, Kawakubo K, Mori K, Tang A, et al. Glycemic index-based nutritional education improves blood glucose control in Japanese adults: a randomized controlled trial. Diabetes Care 2007 Jul;30(7):1874-1876. [CrossRef] [Medline]
- Ma Y, Olendzki B, Merriam P, Chiriboga D, Culver A, Li W, et al. A randomized clinical trial comparing low-glycemic index versus ADA dietary education among individuals with type 2 diabetes. Nutrition 2008 Jan;24(1):45-56 [FREE Full text] [CrossRef] [Medline]
- Canadian Diabetes Association Clinical Practice Guidelines Expert Committee, Dworatzek PD, Arcudi K, Gougeon R, Husein N, Sievenpiper JL, et al. Nutrition therapy. Can J Diabetes 2013 Apr;37 Suppl 1:S45-S55. [CrossRef] [Medline]
- Ley SH, Hamdy O, Mohan V, Hu FB. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. The Lancet 2014 Jun;383(9933):1999-2007. [CrossRef]
- Bhupathiraju S, Tobias D, Malik V, Pan A, Hruby A, Manson J, et al. Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis. Am J Clin Nutr 2014 Jul;100(1):218-232 [FREE Full text] [CrossRef] [Medline]
- Kaufman N. Internet and information technology use in treatment of diabetes. Int J Clin Pract Suppl 2010 Feb(166):41-46. [CrossRef] [Medline]
- Stellefson M, Chaney B, Barry AE, Chavarria E, Tennant B, Walsh-Childers K, et al. Web 2.0 chronic disease self-management for older adults: a systematic review. J Med Internet Res 2013 Feb 14;15(2):e35 [FREE Full text] [CrossRef] [Medline]
- Leist AK. Social media use of older adults: a mini-review. Gerontology 2013;59(4):378-384 [FREE Full text] [CrossRef] [Medline]
- Kaplan A, Haenlein M. Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons 2010 Jan;53(1):59-68. [CrossRef]
- Cavill J, Jancey J, Howat P. Review and recommendations for online physical activity and nutrition programmes targeted at over 40s. Glob Health Promot 2012 Jun;19(2):44-53. [CrossRef] [Medline]
- Powers M, March S, Evert A. Use of Internet Technology to Support Nutrition and Diabetes Self-Management Care. Diabetes Spectrum 2008 Apr 01;21(2):91-99. [CrossRef]
- Davis MS, Miller CK. Educational Needs Regarding the Glycemic Index in Diabetes Management. Topics in Clinical Nutrition 2006;21(1):17-25.
- Grant S, Wolever TMS. Perceived barriers to application of glycaemic index: valid concerns or lost in translation? Nutrients 2011 Mar;3(3):330-340 [FREE Full text] [CrossRef] [Medline]
- Kalergis M, Pytka E, Yale J, Mayo N, Strychar I. Canadian dietitians' use and perceptions of glycemic index in diabetes management. Can J Diet Pract Res 2006;67(1):21-27. [CrossRef] [Medline]
- Leiter LA, Berard L, Bowering CK, Cheng AY, Dawson KG, Ekoé JM, et al. Type 2 diabetes mellitus management in Canada: is it improving? Can J Diabetes 2013 Apr;37(2):82-89. [CrossRef] [Medline]
- Al Sayah F, Majumdar S, Soprovich A, Wozniak L, Johnson S, Qiu W, et al. The Alberta's Caring for Diabetes (ABCD) Study: Rationale, Design and Baseline Characteristics of a Prospective Cohort of Adults with Type 2 Diabetes. Can J Diabetes 2015 Oct;39 Suppl 3:S113-S119. [CrossRef] [Medline]
- Suresh K. An overview of randomization techniques: An unbiased assessment of outcome in clinical research. J Hum Reprod Sci 2011 Jan;4(1):8-11 [FREE Full text] [CrossRef] [Medline]
- Eating Well with Canada's Food Guide. Ottawa, Ontario: Health Canada; 2007.
- Canadian Diabetes Association Clinical Practice Guidelines Expert Committee, Cheng AY. Canadian Diabetes Association 2013 clinical practice guidelines for the prevention and management of diabetes in Canada. Introduction. Can J Diabetes 2013 Apr;37 Suppl 1:S1-S3. [CrossRef] [Medline]
- Atkinson F, Foster-Powell K, Brand-Miller JC. International tables of glycemic index and glycemic load values: 2008. Diabetes Care 2008 Dec;31(12):2281-2283 [FREE Full text] [CrossRef] [Medline]
- Brouwer W, Kroeze W, Crutzen R, de Nooijer J, de Vries NK, Brug J, et al. Which intervention characteristics are related to more exposure to internet-delivered healthy lifestyle promotion interventions? A systematic review. J Med Internet Res 2011 Jan 06;13(1):e2 [FREE Full text] [CrossRef] [Medline]
- Brand-Miller J, Foster-Powell K. The Shopper's Guide to GI Values: The Authoritative Source of Glycemic Index Values for More Than 1,200 Foods. Boston, MA: Da Capo Lifelong Books; 2015.
- McGowan C, Walsh J, Byrne J, Curran S, McAuliffe FM. The influence of a low glycemic index dietary intervention on maternal dietary intake, glycemic index and gestational weight gain during pregnancy: a randomized controlled trial. Nutr J 2013 Oct 31;12(1):140. [CrossRef] [Medline]
- Thompson FE, Subar AF. Dietary assessment methodology. In: Coulston A, Boushey C, Ferruzzi MG, editors. Nutrition in the Prevention and Treatment of Disease. Amsterdam: Elsevier/AP; 2013:5-46.
- Foster-Powell K, Holt S, Brand-Miller JC. International table of glycemic index and glycemic load values: 2002. Am J Clin Nutr 2002 Jul;76(1):5-56. [CrossRef] [Medline]
- Self Nutrition Data. 2016. Estimated Glycemic Load™ URL: https://nutritiondata.self.com/stylesheets/global_print.css [accessed 2018-12-09] [WebCite Cache]
- The University of Sydney. 2018. The Glycemic Index URL: http://www.glycemicindex.com/ [accessed 2019-01-17] [WebCite Cache]
- Olendzki B, Ma Y, Culver A, Ockene I, Griffith J, Hafner A, et al. Methodology for adding glycemic index and glycemic load values to 24-hour dietary recall database. Nutrition 2006;22(11-12):1087-1095 [FREE Full text] [CrossRef] [Medline]
- Wolever T, Jenkins D, Jenkins A, Josse RG. The glycemic index: methodology and clinical implications. Am J Clin Nutr 1991 Nov;54(5):846-854. [CrossRef] [Medline]
- Lin C, Kimokoti R, Brown L, Kaye E, Nunn M, Millen BE. Methodology for adding glycemic index to the National Health and Nutrition Examination Survey nutrient database. J Acad Nutr Diet 2012 Nov;112(11):1843-1851. [CrossRef] [Medline]
- Avedzi H, Mathe N, Storey K, Johnson J, Johnson ST. Examining sex differences in glycemic index knowledge and intake among individuals with type 2 diabetes. Prim Care Diabetes 2018 Dec;12(1):71-79. [CrossRef] [Medline]
- Burani J, Longo PJ. Low-glycemic index carbohydrates: an effective behavioral change for glycemic control and weight management in patients with type 1 and 2 diabetes. Diabetes Educ 2006;32(1):78-88. [CrossRef] [Medline]
- Avedzi H, Mathe N, Bearman S, Storey K, Johnson J, Johnson ST. Examining Diet-Related Care Practices Among Adults with Type 2 Diabetes: A Focus on Glycemic Index Choices. Can J Diet Pract Res 2017 Dec;78(1):26-31. [CrossRef] [Medline]
- Alberta's CFD. Accelerometer and Dietary Sub-study. Unpublished Research 2014.
- Toobert DJ, Hampson SE, Glasgow RE. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care 2000 Jul;23(7):943-950 [FREE Full text] [Medline]
- Leca V, Ibrahim Z, Lombard-Pontou E, Maraninchi M, Guieu R, Portugal H, et al. Point-of-care measurements of HbA(1c): simplicity does not mean laxity with controls. Diabetes Care 2012 Dec;35(12):e85 [FREE Full text] [CrossRef] [Medline]
- Allison C. BpTRU(tm) blood pressure monitor for use in a physician's office. Issues Emerg Health Technol 2006 Aug(86):1-4. [Medline]
- Janssen I, Heymsfield S, Ross R. Application of simple anthropometry in the assessment of health risk: implications for the Canadian Physical Activity, Fitness and Lifestyle Appraisal. Can J Appl Physiol 2002 Aug;27(4):396-414. [Medline]
- Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985 Sep;10(3):141-146. [Medline]
- Jacobs DR, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc 1993 Jan;25(1):81-91. [Medline]
- Rhodes R, Plotnikoff RC. Can current physical activity act as a reasonable proxy measure of future physical activity? Evaluating cross-sectional and passive prospective designs with the use of social cognition models. Prev Med 2005 May;40(5):547-555. [CrossRef] [Medline]
- Boot W, Charness N, Czaja S, Sharit J, Rogers W, Fisk A, et al. Computer proficiency questionnaire: assessing low and high computer proficient seniors. Gerontologist 2015 Jun;55(3):404-411 [FREE Full text] [CrossRef] [Medline]
- Tobey LN, Manore MM. Social media and nutrition education: the food hero experience. J Nutr Educ Behav 2014;46(2):128-133. [CrossRef] [Medline]
- Hallberg SJ, McKenzie AL, Williams PT, Bhanpuri NH, Peters AL, Campbell WW, et al. Effectiveness and Safety of a Novel Care Model for the Management of Type 2 Diabetes at 1 Year: An Open-Label, Non-Randomized, Controlled Study. Diabetes Ther 2018 Apr;9(2):583-612 [FREE Full text] [CrossRef] [Medline]
- Pereira K, Phillips B, Johnson C, Vorderstrasse A. Internet delivered diabetes self-management education: a review. Diabetes Technol Ther 2015 Jan;17(1):55-63. [CrossRef] [Medline]
- Haythornthwaite C. Building Social Networks Via Computer Networks: Creating and Sustaining Distributed Learning Communities. In: Renninger K, Shumar W, editors. Building Virtual Communities: Learning and Change in Cyberspace. Cambridge, MA: Cambridge University Press; 2002:159-190.
- Arambepola C, Ricci-Cabello I, Manikavasagam P, Roberts N, French DP, Farmer A. The Impact of Automated Brief Messages Promoting Lifestyle Changes Delivered Via Mobile Devices to People with Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Controlled Trials. J Med Internet Res 2016 Apr 19;18(4):e86 [FREE Full text] [CrossRef] [Medline]
- Lindsay S, Smith S, Bellaby P, Baker R. The health impact of an online heart disease support group: a comparison of moderated versus unmoderated support. Health Educ Res 2009 Aug;24(4):646-654. [CrossRef] [Medline]
|ABCD: Alberta’s Caring for Diabetes Cohort Study|
|BMI: body mass index|
|CPQ: Computer Proficiency Questionnaire|
|GI: glycemic index|
|GL: glycemic load|
|HEALD-GI: Healthy Eating and Active Living for Diabetes-Glycemic Index|
|IT: information technology|
|MVPA: Moderate-To-Vigorous Physical Activity|
|SMS: short message service|
|T2D: type 2 diabetes|
Edited by N Kuter, G Eysenbach; submitted 30.07.18; peer-reviewed by M Nomali, M Khosravi; comments to author 01.10.18; revised version received 16.11.18; accepted 22.11.18; published 06.03.19Copyright
©Hayford M Avedzi, Kate Storey, Jeffrey A Johnson, Steven T Johnson. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 06.03.2019.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), 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.