An Investigation Into Diurnal Variability in Glucose Levels in Paediatric Patients With Type 1 Diabetes (T1D) and Their Responses to Different Food Compositions
Conditions: Type 1 Diabetes
Sponsor: University of Stirling

 
 
Page 1 Title: Study Protocol Summary  Date:  15/05/2021 Version 4 IRAS ID:273640 
 
 
 Project summary  
Type 1 diabetes (T1D) is a chronic disease which requires daily calculations of food intake 
and insulin dose adjustment to achieve good glycaemic control and minimise the risk of 
developing diabetic complications. However, even when glycaemic control appears to be 
good, as demonstrated by average glycated haemoglobin (HbA1c), children and young people 
with T1D frequently experience glucose variability, with levels above and below the target 
range. The main cause of diurnal glucose variability is food intake, which can cause 
postprandial hyperglycaemia. Postprandial hyperglycemia can occur after any meal, although 
there is some evidence that it may be worse after breakfast. There is limited data on the 
occurrence and cause of this and its association with different variables, including food 
composition.  
Methods:  
This project will be a quantitative, descriptive study. It will aim to describe distribution and 
dispersion of both glucose variability and postprandial hyperglycaemia following breakfast. 
The study proposes to recruit approximately 435 children and young people who have T1D 
and who regularly use Dexcom continuous glucose monitoring (CGM). Recruitment will be via 
their managing dietitian. The dietitian will be asked to provide baseline information about the 
participants which will include demographic data and information on clinical data, treatment 
and anthropometrics. Participants will be asked to provide access to Dexcom CGM data 
throughout the  period of recording. Participants will then be issued with, for seven consecutive 
days, two survey questionnaires, one in the morning at breakfast time and the other in the 
evening. The morning survey will include questions on the breakfast meal (including a 
photograph of the meal) and insulin dosage, similarly the evening survey will also include 
questions on diabetes management and food and fluid intake in addition to questions on 
activities all of which took place during the four-hour postprandial period. These data will be 
statistically described using univariate, bivariate and multivariate analysis.   
 
   
 
 

 
 
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Study protocol  
Full Study Title:  
An investigation into diurnal variability in glucose levels in paediatric patients with Type 1 
Diabetes (T1D) and their responses to different  food compositions.   
Short title 
Glucose variability in Type 1 Diabetes (T1D) and glycaemic responses to food composition.  
 
Summary Protocol version number 4, date:  15/05/2021. IRAS ID: 273640. REC reference: 
20/WS/0123 
 
 
Chief Investigator: 
Dr Stuart Galloway, University of Stirling, Stirling FK9 4LA 
 s.d.r.galloway@stir.ac.uk. 01786 466494 
Investigators:  
Dr Ashley Shepherd, University of Stirling, Stirling FK9 4LA 
ashley.shepherd@stir.ac.uk  01786 466334 
Julie Johnson, University of Stirling and NHS Highland, 
julie.johnson1@stir.ac.uk, 07815893076 
 
Statistician  
 
 
Dr Federico Andreis, Health Sciences, University of Stirling, Stirling 
FK9 4LA. Federico.andreis@stir.ac.uk 01786 466252 
 
Lead Sponsor:  
Rachel Beaton, Research Integrity and Governance Manager, 
University of Stirling, Stirling FK9 4LA. Rachel.beaton@stir.ac.uk 
01786 466196   
Lead R&D  
Frances Hines, Research, Development and Innovation Manager, 
NHS Highland, Centre for Health Sciences, Raigmore Hospital, Old 
Perth Road, Inverness, IV2 3UJ. frances.hines@nhs.scot. 01463 
255822  
Funder: 
Ethics approval:  
NHS Highland  
This study has been reviewed and provided a favorable opinion by 
the  NHS, Invasive or Clinical Research (NICR) Panel, University of 
Stirling and the West of Scotland Research Ethics Service 
(WoSRES) REC 5.  
 
 

 
 
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List of Contents 
Content  
Page Number 
 
 
Rationale 
4-5 
Aims & Objectives  
6 
Study Design 
6-7 
Methodology 
8-9 
Data Analysis  
Safety Considerations 
10 
10 
Data Management  
11-13 
Expected Outcome  
13 
Dissemination of Results 
13 
Ethical Considerations 
13 
Budget 
Insurance 
References  
14 
14 
15 
 
 
 
 
 
 
 
 
 

 
 
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Rationale 
Introduction  
Type 1 diabetes (T1D) is caused by autoimmune destruction of the beta-cells that secrete 
insulin (Eisenbarth, 1986; Bluestone et al. 2010). It requires life-long treatment of insulin 
therapy, with the aim to achieve near-normoglycaemia, gauged by the amount of glycated 
haemoglobin, or HbA1c concentration, there is in the erythrocytes (Bunn et al. 1978). This 
measurement of HbA1c, against a clinically 'desired' target (DiMeglio et al. 2018), is a gold 
standard element of diabetes management (DCCT, 1993). Despite this, HbA1c, as a mean 
measurement, does not reflect the full pattern of glycaemia (Derr & Garrett, 2003) and cannot 
be used to foresee glucose variability (Boland et al. 2001). Even when HbA1c is in target, 
nocturnal and diurnal glucose variability, involving both hypo- and hyperglycaemia can be a 
daily occurrence for children and young people with T1D (Boland et al. 2001; Tansey et al. 
2016). Data from continuous glucose monitoring (CGM) has shown that children experience 
nocturnal 
hypoglycaemia 
and 
diurnal 
hyperglycaemia, 
particularly 
postprandial 
hyperglycaemia (Boland et al. 2001; Tansey et al. 2016) and there is some evidence that this 
is worse after breakfast (Boland et al. 2001; Heptulla et al. 2004; Gandrud et al. 2007).   
Complications 
One of the reasons glucose variability and postprandial hyperglycaemia are a concern is that 
they both contribute to overall diabetes control (Standl et al. 2011). Poor glycaemic control 
causes cumulative and deleterious effects on both the cardiovascular (Koivisto et al. 1996) 
and microvascular systems (Kaiser et al. 1993). A further concern for children and young 
people, living with diabetes, is that they are vulnerable to alterations in glucose concentrations 
in the central nervous system owing to their high requirement for glucose for brain growth and 
development (Chugani et al. 1987). Several studies have observed alterations to both white 
and grey matter in children and adults with T1D (Perantie et al. 2007; Perantie et al. 2011; 
Marzelli et al. 2014; Mauras et al. 2015; Marziaka et al. 2016) and studies using CGM have 
observed an association with this and both glucose variability and hyperglycaemia (Marzelli et 
al. 2014; Barnea-Goraly et al. 2014; Mauras et al. 2015; Marziaka et al. 2016). Children with 
T1D often perform worse on cognition tests than those without the disease and decreases in 
IQ have been noted during periods of hyperglycaemia (Gonder-Frederick et al. (2009). T1D 
also appears to increase the risk of mental health difficulties (Butwicka et al. 2015) and this is 
associated with hyperglycaemia (McDonnell et al. 2007).   
Possible solutions to postprandial hyperglycaemia  
One potential solution to postprandial hyperglycaemia arises from the development of faster 
acting insulin. These could improve the lag time between insulin action and food absorption 

 
 
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(Bowering et al. 2017). Results of their ability to reduce postprandial hyperglycaemia are 
conflicting (Bode et al. 2017; Buse et al. 2018) and there are currently no published trials 
involving children and young people (Danne et al. 2018). One advantage of faster acting 
insulins is found in their potential use in closed-loop systems (CLS) (Gingras et al. 2018) which 
respond automatically to CGM readings (Gingras et al. 2018). Postprandial glucose control 
remains a challenge for the CLS and the time spent above target is mainly after food 
consumption (Gingras et al. 2018). The development of CLS has driven vast improvements in 
the accuracy of CGM systems in recent years and CGM is now better able to identify 
postprandial hyperglycaemia because of the density of data it affords (Tansey et al. 2016; 
Mangrola et al. 2017).  CGM will likely help identify diverse responses to the myriad of dietary 
components (Bell et al. 2015) and thus CGM will likely allow for better prandial decision-
making.   
It is agreed that further research into the dietetic management of T1D is required (Smart et al. 
2018). There is also a dearth of evidence on prevalence and management of postprandial 
hyperglycaemia after breakfast. Seven studies tested meals at breakfast time (Ryan et al. 
2008; Smart et al. 2012; Smart et al. 2013; Piechowiak et al. 2017; Faber et al. 2017; Lopez 
et al. 2018) however none of the aims of these studies were to establish prevalence nor 
resolution of postprandial hyperglycaemia at breakfast. Only two considered diet quality at 
breakfast (Ryan et al. 2008; Groele et al. 2014) and neither of these provided any evidence of 
how to manage postprandial hyperglycaemia after breakfast. 
 
Conclusion  
It is known that chronic hyperglycaemia causes increased risk of diabetic complications. It is 
possible that both glucose variability and postprandial hyperglycaemia are independent risk 
factors for this as well. There is some evidence that glucose variability and postprandial 
hyperglycaemic are common occurrence for children who have T1D. However, there is a 
paucity of published data on the prevalence of postprandial hyperglycaemia after breakfast in 
children and young people with T1D and no evidence-base for how to manage this 
phenomenon. The need for long-term studies to examine glucose variability from CGM data 
and, for closer examination of postprandial glucose variability to elucidate methods to reduce 
this, has been highlighted (Tansey et al. 2016). Although this applies to all meals, focusing on 
minimising postprandial hyperglycaemia after breakfast is paramount. This can help ensure 
good control through the morning and rest of the day when children are at school and actively 
learning (Tansey et al. 2016). 
 
 

 
 
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Aim: 
To describe the distribution and dispersion of glucose variability and postprandial 
hyperglycaemia following breakfast, in children and young people with type 1 diabetes (T1D), 
using measurements from Dexcom CGM.  
Objectives:  
• 
To determine the glucose variability diurnally and nocturnally and in the four-hour 
postprandial breakfast period using measurement of ‘time in range’, ‘time above range’ 
and ‘time below range’.  
• 
To determine the variability of glucose excursion, level and peak and the recovery time 
in the four-hour postprandial breakfast period.  
• 
To determine the number and percentage of participants who achieved internationally 
agreed pre and postprandial glucose targets at breakfast time.   
• 
To describe comparisons between all the above measurements and the variables of 
sex, age, disease duration, BMI, HbA1c, insulin dose/sensitivity and insulin regimen.  
• 
To describe comparisons between all the above measurements and food compositions 
taken in the breakfast meal. 
• 
To describe comparisons between the above measurements and carbohydrate and 
insulin adjustments, fluid intake and activities that took place during in the four-hour 
postprandial breakfast period. 
Study design  
This is a descriptive, quantitative study. Dexcom CGM data will be collected retrospectively 
(for the previous three months) and for the period of recording. Photographic food diaries and 
answers to morning and evening questionnaire surveys will be collected for seven consecutive 
days. The morning questionnaire will request information on food and fluids consumed at 
breakfast as well as insulin management. The evening questionnaire will request information 
on the four-hour postprandial morning activities in addition to insulin and carbohydrate 
adjustments and fluid intake. The study duration, commencing with the recruitment of the first 
participant and ending when data has been fully described, is anticipated to be eighteen 
months.        
Participants  
Eligibility criteria  
• 
Children and young people aged between 1-17 years   
• 
Diagnosis of type 1 diabetes for a minimum of one year  

 
 
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• 
Using multiple daily injections (MDI) together with carbohydrate counting or 
Continuous Subcutaneous Insulin Infusion (CSII)  
• 
Using Dexcom continuous glucose monitoring (CGM) on a regular basis.  
• 
Access to internet and email   
Exclusion criteria  
• 
Prescribed anti-hyperglycaemia agents i.e. Glucophage (Metformin) and or 
antidepressants. 
• 
Have other medical conditions, including complications of diabetes and coeliac 
disease will be excluded.  
• 
Currently enrolled in another research study 
Recruitment  
Paediatric diabetes dietitians, working across the UK, will be enrolled to help recruit 
participants and become principal investigators for their site. On enrolment, the researcher will 
provide the dietitians with all the relevant participant information sheets and consent forms as 
well as an Excel spreadsheet for entering the baseline information. The study documentation 
are presented in Appendices 1-13.  
 
Sample size 
There are approximately 29,000 children and young people living in the UK with T1D (Juvenile 
Diabetes Research Federation (JDRF), 2018). The numbers of patients using Dexcom CGM 
appears to be on average 11% of this population. The number of dietitians, working in 
paediatric diabetes, is typically 0.5 whole time equivalent per 100 patients (National Paediatric 
Diabetes Audit, 2019) resulting in approximately 180 paediatric diabetes dietitians working in 
the UK. Contact with dietitians, to date, suggests it may be possible to gain agreement from 
approximately 18% of dietitians who are contacted directly. These dietitians would be 
managing an estimated 5220 patients. Assuming 11% of these use Dexcom CGM then an 
approximate number of participants that could be recruited is 572 resulting in approximately 
18 participants per dietitian. An average of 13-14 participants per dietitian would keep the 
workload to an average of no more than two working days. The time required for the 
researcher to contact participants, download and analysis data and food diaries is estimated 
to be 90 – 120 minutes per participant. For 435 participants this is the equivalent of 75-100 
working days which is achievable.  
 
 
 

 
 
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Methodology 
Baseline data  
In order to make comparisons between relevant variables and glucose levels, the following 
baseline data will be collected from the dietitians and sent to the researcher, along with the 
artificial identifier on the Excel spreadsheet as discussed earlier at the stage of recruitment of 
participants:  
• 
Parent’s email address 
• 
Sex, date of birth and recent weight and height (for calculation of BMI and BMI centile) 
• 
Date of diagnosis of T1D 
• 
Last four HbA1c 
• 
Total daily insulin dose (TDD) 
• 
Percentage basal/bolus (if known)  
• 
Insulin: carbohydrate ratios (ICR) and Insulin Sensitivity Factor (ISF)  
• 
Current insulin regimen (including type of insulin prescribed and if applicable type of 
insulin pump i.e. open or closed loop)  
Glucose measurement   
Data on interstitial glucose will be collected via Dexcom CGM. The Dexcom CGM data will be 
accessed by registering a research ‘Clarity Clinic’ with Dexcom CLARITY® Clinic Portal 
(Dexcom In, San Diego, CA, USA) with the researcher becoming the administrator of this 
clinic. Once the managing dietitian has obtained each participant’s consent, the participant’s 
parent’s email address will be sent to the researcher along with the baseline information/data 
as described above. The researcher, as administrator of the Clarity Clinic account, will then 
invite the participant, via email, to be added to the clinic. Once the invite has been accepted, 
it will stand for the period of the recording i.e. until the participant’s questionnaires been 
received unless the participant decides to withdraw from the study. Once the participant has 
submitted their last questionnaire, they will be removed from the Dexcom CLARITY® Clinic 
Portal.     
Survey questionnaires and photographic food diaries  
Following the provision of CGM data, participants will be asked to complete the questionnaires 
using ‘online survey’.  Participants will be asked to photograph their breakfast meal and drinks 
and email along with provide information after breakfast and in the evening, as per the 
questionnaire presented in Appendix 14 and 15. The CGM data will be collected throughout 
this time as discussed above.  

 
 
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The food consumed at breakfast will be analysed using Diet Plan 7, a nutrient analysis 
programme based on the UK food composition tables (Public Health England, 2014). This will 
provide a calculation of energy and macro and micronutrient intake and allow the accuracy of 
carbohydrate calculations to be assessed. Where possible, the glycaemic index of the 
breakfast will be calculated. The analysis from this will be transferred into a CSV file and saved 
as an Excel spreadsheet as presented in Appendix 16.  
Recruitment for Dexcom CGM DATA only 
As per Amendment 273640.10, dated 15/05/2021, participants can be recruited to provide 
CGM data only. This amendment as submitted in order to attempt to obtain large quantities of 
CGM data as recruitment to the study has been slow. Some families have reported to the 
recruiting dietitians (Principal Investigators) that they have been reluctant to join because of 
the time commitment required for completing the survey questionnaires.  
Outcome measures 
Primary and secondary outcome measures will be based on international guidelines and 
consensus DiMegloi et al. 2018; Battelino et al. 2019) of the metrics and target glucose levels 
to be used in CGM analysis in clinical practice. These are agreed to be: 
Metrics: 
• 
Mean glucose  
• 
Glucose variability (GV) % coefficient of variation (COV) target ≤36% 
• 
Time in range (TIR) % and time spent between 3.9-10mmol/l 
• 
Time above target (TAR)  % and time spent >10.1-<13.9mmol/l) and >13.9mmol/l 
• 
Time below range (TBR) % and time spent 3.0-3.8mmol/l and <3mmol/l  
Target glucose levels:  
• 
TIR - % of readings >70% or 16hr 48min 
• 
TAR - % of readings <25% or <6hr high and <5% 1hr 12min very high  
• 
TBR- % of readings <4% or <1hr low and <1% or <15min very low     
Primary outcome measure:  
• 
Mean glucose (mmol/l) in the four-hour postprandial breakfast period calculated from 
the CGM measurements at 5 minutes intervals.   
Secondary outcome measures – post prandial period:   
• 
Number and percentage who had pre-prandial glucose in target Mean peak glucose 
level (mmol/l), mean time to peak (mins), mean time to recover (to pre-prandial levels) 
(mins) in the four-hour postprandial breakfast period 

 
 
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• 
TIR, TBR and TAR (% and time) in the four-hour postprandial breakfast period  
• 
Comparisons of the above measurements between cohorts and breakfast meal 
compositions and drinks, snacks taken in the morning and activities and insulin 
adjustments taken in the 4-hour postprandial period.  
Secondary outcome measures – glucose variability:  
• 
TIR, TBR and TAR (% and time) between the hours of 06.00-22.00, 22.00-06.00 and 
24-hour period. 
Data analysis  
This will be a mix of univariate, bivariate and multivariate analysis as this is best suited to 
describing, summarising and visualising these data. Outputs will include the distribution of 
glucose levels and diurnal, nocturnal and post-breakfast variability to determine the spread 
and dispersion of the data. As well as providing new evidence on this phenomenon, it will also 
assist in determining required sample size for any subsequent investigation including an 
intervention testing of effects on interstitial glucose levels arising from different food intakes. 
Safety considerations  
Recruitment/consent 
 
Consideration will be given to those potential participants/families who are experiencing 
difficulties managing their condition, for example ‘diabetes burnout’; poor glycaemic control or 
other stressors, for example, family difficulties, stress at school, for example, dealing with 
bullying or exam pressures. This will be minimised by recruiting via the managing dietitian who 
will have significant knowledge of the potential participant and who will be expected to 
discourage recruitment, if it is felt the family have enough to cope with. Those who are newly 
diagnosed will not meet the eligibility criteria as it is felt this would be unethical given the 
pressure they will be experiencing dealing with a new diagnosis of a chronic disease. 
Participants will not be asked to change their usual diabetes management or dietary intake.   
 
Personal data collection  
 
Personal data as described above will be collected and will be securely managed. How this 
will be managed is described in the ‘Data Management’ section. 
 
Burden on dietitians  
 
Dietitians, as Principal Investigators, will need to be allowed additional time to recruit 
participants. Dietitians will be asked to discuss this with their managers and gain their approval 
for this and also with their diabetes teams.   
 

 
 
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Burden on families 
This is minimised by utilisation of digital technology to ensure that completion of food diaries 
and questionnaire surveys are not time consuming. Payment for expenses and time may be 
considered. Funding to support this (from the British Dietetic Association) will be applied for 
but can only be submitted once ethical approval has been sought and granted.   
 
Data management  
Assessment of existing data  
There appears to be a dearth of available data on the distribution and dispersal of glucose 
levels in children and young people who have T1D. Nor does there appear to be any published 
data comparing glucose measurements from Dexcom CGM with different breakfast 
compositions in children and young people with T1D. The project is therefore not creating new 
data when existing data could be re-used.    
Creation of new data   
This will include the following: 
• 
Retrospective and on-going Dexcom CGM measurements of interstitial glucose  
• 
Baseline information as discussed earlier   
• 
Information and analysis of food and drink intake at breakfast and activities and 
adjustments in the four-hour postprandial period as discussed earlier. 
Methods of anonymisation, pseudonymisation and encryption 
None of participants names and addresses will be collected. Surnames are likely to be known, 
owing to the need to obtain email address for the CGM data collection. The participants date 
of birth is required for the Dexcom Clarity clinic. Pseudonymisation will take place as 
recommended by GDPR regulation (General Data Protection Regulation (GDPR) 2018). 
Artificial identifiers, to be used for all communication and data storage, will be provided for 
each participant at the stage of recruitment. All data, including parent’s email addresses, will 
be stored on an NHS Highland secure remote server which is password protected with files 
encrypted. Breeches of data will be reported through both the Data Management Committee 
(see below) and the NHS Highland incident reporting system (DATIX).  
Collection, storage and transfer of data - baseline information  
Baseline information will be collected by the participant’s managing dietitians, taken from 
diabetes clinical records. These data will be pseudonymised with the artificial identifier and 
entered into an Excel spreadsheet, by the enrolled dietitian and communicated via ‘NHS mail’ 
(see Appendix 1). ‘NHS mail’ is accredited to government official status for sharing patient 

 
 
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identifiable and sensitive information and meets the secure email standard (DCB1596). All 
data will be stored on the NHS Highland laptop.  
 
Collection, storage and transfer of data - Dexcom CGM data  
The researcher will set up a research clinic on Dexcom CGM Clarity which is accessed via the 
internet and is password and username protected. The researcher, as administrator of this 
clinic, will then invite the participants, via their parent’s email address, to join the clinic. This a 
standard way of accessing Dexcom CGM data. The invite will include the artificial identifier, 
and this is the identifier that will be visible when the data is accessed and not the name of the 
participant. For the invite to work it must include the participant’s date of birth for verification 
purposes. Email addresses and date of birth will be recorded in the baseline information 
spreadsheet and this will be stored on the NHS Highland laptop. Dexcom have their own 
security management and personal information is transmitted in encrypted form. CGM data 
will transferred to a CSV file, saved as an Excel file and stored on an NHS Highland laptop. 
An example of this in presented in Appendix 17. As consumers of Dexcom CGM the 
participants will have access to the Dexcom, Inc Privacy Policy which complies with the 
GDPR) 2016. 
(https://www.dexcom.com/en-GB/linked/documentservice/PrivacyPolicy).    
 
Collection, storage and transfer of data - survey questionnaires  
The researcher plans to use Jisc ‘Online Surveys’ (formerly BOS). The University of Stirling 
subscribes to this service and the researcher has a unique username and password for 
accessing this, known only to the researcher. Jisc is registered with the Information 
Commissioners Office (ICO) (registration number Z9546606) and meets the requirements of 
GDPR (https://www.onlinesurveys.ac.uk/gdpr-and-online-surveys/) and is certified to ISO 
27001 (https://www.jisc.ac.uk/about/certification ). All survey responses are collected over 
encrypted SSL (TLS) connections and deleted after three months. The university GDPR 
statement is added to all the survey questionnaires. Responses to the survey will be 
transferred to a CSV file then saved as an Excel file on the NHS Highland laptop. An example 
of this is presented in Appendix 18 and 19.  
 
Collection, storage and transfer of data - Photo food diaries 
The participants will be asked to only photograph the meal and not include anything else that 
may be identifiable in the photograph. Instruction on how to do this is provided in a separate 
sheet as presented in Appendix 20. The photographs will be emailed to the researchers NHS 
mail email account. These will be downloaded and saved to the NHS Highland remote secure 

 
 
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server as described above. Should any identifying information be included in the photograph 
this will be deleted from the photograph before it is saved. 
 
Collection, storage and transfer of data - Nutritional analysis 
The breakfast meals will be analysed using DietPlan 7 which will be accessed via an NHS 
Highland desktop. Data entered will be pseudonymised, using the artificial identifier as 
described below. The analysis will be transferred to a CSV file, saved as an Excel file and 
emailed via NHS mail to be saved on the NHS Highland laptop. 
 
Data ownership 
It is anticipated that new data, arising from the study, and the associated intellectual property 
will be owned jointly by the University of Stirling and NHS Highland with a sharing agreement. 
Dexcom were contacted about this, via email, in January 2020 and have failed to respond.   
 
Destruction of data  
The Dexcom Clarity clinic only stores CGM data for three months. Once these data have been 
collected for the period of the study, the Dexcom research clinic will be closed. Any transferred 
data will be stored on the NHS Highland secure remote server for 10 years before being 
deleted. Responses to surveys are backed up on the Online Survey system for three months 
then they are deleted and destroyed.    
Reviewing the data management plan 
At the suggestion of the NHS Highland Research and Development office, a Data 
Management Committee will be set up. Meetings will be arranged at regular intervals to ensure 
the data management plan is adhered to and to address any difficulties.      
Expected outcomes  
The aim of this study is to describe the distribution and dispersion of glucose variability and 
postprandial hyperglycaemia after breakfast and establish comparisons of these between 
variables obtained from baseline information and nutrient analysis. It is hoped this will 
formulate a quantitative research question and power calculation for a sample size for a 
intervention trial to test different meals at breakfast.     
Dissemination of results  
It is anticipated that one paper will be submitted for publication. The proposed journals for 
publication include:  
• 
Pediatric Diabetes 
• 
Diabetic Medicine 

 
 
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• 
Diabetologia 
• 
Diabetes Technology & Therapeutics 
• 
Acta Diabetologica.    
Ethical considerations 
This study has been reviewed and provided a favorable opinion by the  NHS, Invasive or 
Clinical Research (NICR) Panel, University of Stirling and the West of Scotland Research 
Ethics Service (WoSRES) REC 5. Consent will be obtained from parents and/or carers and, 
where appropriate, the children and young people themselves. As Principal Investigators, the 
recruiting dietitians will be asked to encourage, where possible, the children and young people 
to be involved in the decision to participant in the study. To assist with this, several age 
appropriate ‘Patient Information Sheets’ have been developed and will be provided to the 
enrolled dietitians. The dietitians will therefore be asked to ensure conversations regarding 
the study be discussed when the child/young person is present. It should be noted that in 
Scotland, children over the age of 12 years old are usually considered to be mature enough 
to give a view about taking part in research even if they are not fully able to give consent. The 
recruiting dietitians will be asked to discourage parents from consenting to participate if their 
child expresses either verbally or non-verbally that they do not wish to participate.  
Budget 
Only participants already self-funding or receiving NHS funding for Dexcom CGM will be 
recruited therefore there will no cost for using Dexcom CGM. The University of Stirling already 
subscribe to www.onlinesurveys.ac.uk.  Funding to purchase an NHS Highland laptop will be 
sought. Funding to pay expenses to participants and dietitians will be considered (applications 
to obtain financial support for this can only be submitted once ethical approval has been 
obtained).  
Insurance  
The University of Stirling provide indemnity insurance although the risk of adverse events is 
low given that this is a descriptive study.  

 
 
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References 
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Mauras, N., White, N.H. and Fox, L.A., (2014). Alterations in white matter structure in young children with type 1 
diabetes. Diabetes Care, 37(2), pp.332-340. 
 
Battelino, T., Danne, T., Bergenstal, R.M., Amiel, S.A., Beck, R., Biester, T., Bosi, E., Buckingham, B.A., Cefalu, 
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