Diabetes Mellitus, Type 2
Conditions
Keywords
physical activity, sedentary behavior, sleep
Brief summary
A healthy lifestyle has proved beneficial health effects in managing type 2 diabetes mellitus (T2DM). Important lifestyle behaviors, i.e. sleep, sedentary time (SB), and physical activity (PA) subdivided into light physical activity (LPA) and moderate to vigorous physical activity (MVPA), have shown an impact on T2DM disease-specific characteristics (e.g. glycemic control). However, these behaviors have often been investigated separately. Therefore, a recent shift in research emphasizes the importance of considering these behaviors as part of a 24-hour day. Since T2DM patients can benefit from an optimal 24-hour composition as part of a healthy lifestyle, it may be interesting to investigate the 24-hour movement composition among these T2DM patients over time. Moreover, exploring associations with different personal determinants, environmental determinants, and cardiometabolic markers will provide meaningful insights in developing recommendations and creating an intervention.
Detailed description
The present study aims (1) to conduct a longitudinal observational study over two years to explore 24-hour movement behavior composition patterns among T2DM patients in comparison with a healthy control group and (2) to examine associations between these movement behaviors and personal and environmental determinants, and cardiometabolic markers. This study's primary endpoint is to develop insights into the 24-hour movement composition combined with T2DM patients' characteristics, determinants, and health profile to set the groundwork with the aim to develop, implement and evaluate an intervention in a future randomized controlled trial
Interventions
OTHERNo intervention
This project contains a longitudinal observational study design. The investigator will collect data out of a group with type 2 diabetes mellitus patients and out of group with control adults on three time points (baseline, follow-up after one year, and follow-up after two years). Therefore, the investigator will only collect observational data and the participants will not be exposed to a certain intervention.
Sponsors
University Ghent
University Hospital, Ghent
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 100 Years
Healthy volunteers
Yes
Inclusion criteria
T2DM patients * Adults aged \>18 years old * Diagnosed with T2DM by a physician or an HbA1C above 6.5%
Exclusion criteria
T2DM patients * Diagnosed with type 1 diabetes mellitus (T1DM) * Diagnosed with pregnancy diabetes * Diagnosed with latent autoimmune diabetes in adults (LADA) * Physical disabilities that obstruct the normal PA pattern (e.g. amputations, paralysis) * Cognitive disabilities that obstruct daily functioning (e.g. dementia, psychological disorders) * Other conditions affecting the normal PA pattern (e.g. heart failure NYHA class 3 and 4, chronic respiratory diseases (COPD stage 4), end stage nonalcoholic fatty liver disease, end stage renal failure, cancer, hospitalized) * Pregnancy or pregnancy \<1 year ago * Participating in a physical activity intervention Inclusion criteria control participants \- Adults aged \> 18 years old
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in 24-hour movement composition from baseline over one year and two-year follow-up | Baseline | During their visit to Ghent University hospital, participants will receive a wGT3X-BT ActiGraph accelerometer that will objectively measure their 24-hour movement behaviors (PA, SB, and sleep). The participants will wear the accelerometer for seven consecutive days. Additionally, this accelerometer data will be supplemented with a diary to validate sleep time and (non)wear time. Furthermore, the individuals will subjectively report on their PA, SB, and sleep (duration and quality) through an online questionnaire based on international standardized PA (IPAQ), SB (SIT-Q-7d), and sleep questionnaires (Munich Chronotype questionnaire, Pittsburg sleep quality index, and Sleep Hygiene Index) (IPAQ, Sit-7Q, Munich Chronotype questionnaire, and Pittsburg sleep quality index, Sleep Hygiene Index). By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in triglycerides from baseline to two-year follow-up | Baseline | Triglycerides will only be collected within the type 2 diabetes group. This will be collected by an analysis of a fasting blood sample. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in glucose from baseline to two-year follow-up | Baseline | Glucose will only be collected within the type 2 diabetes group. This will be collected by an analysis of a fasting blood sample. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in Homeostatic Model Assessment (HOMA) from baseline to two-year follow-up | Baseline | The HOMA Is a method to quantify insulin resistance and beta-cell function. HOMA-IR and HOMA-B will only be collected within the type 2 diabetes group. The HOMA-IR and HOMA-B will be calculated based on the collected insulin and glucose level by the HOMA2 calculator. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in Body Mass Index (BMI) from baseline to one and two-year follow-up | baseline | BMI will be calculated by measuring weight (in kilograms) (Seca 861) and height (in meters) (Seca 213). The weight and height will be used in this formula: BMI (kg/m²)= (weight in kg)/(height in m)². By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in waist circumference from baseline to one and two-year follow-up | Baseline | The waist circumference and hip circumference will be measured with a measuring tape (Seca 201). Both measurements will be used to calculate the waist-to-hip ratio, i.e. WHR= (waist circumference in cm)/ (hip circumference in cm). By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in systolic and diastolic blood pressure from baseline to one and two-year follow-up | baseline | Diastolic and systolic (mm Hg) blood pressure will be measured twice (interval of one minute) with an automatic OMRON M6 Comfort device after 10 minutes of rest. By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in Advanced Glycation Endproducts from baseline to one and two-year follow-up | baseline | AGE's are interesting to explore as predictors in developing several comorbidities (e.g. cardiovascular diseases, microvascular complications). Predictors will be measured with an AGE-reader, which is a quick and non-invasive device. By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in HbA1c from baseline to two-year follow-up | baseline | HbA1C will only be collected within the type 2 diabetes group. This will be collected by an analysis of a fasting blood sample. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in cholesterol (total, HDL, LDL) from baseline to two-year follow-up | baseline | Cholesterol (total, HDL, LDL) will only be collected within the type 2 diabetes group. This will be collected by an analysis of a fasting blood sample. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Change in insulin from baseline to two-year follow-up | Baseline | Insulin will only be collected within the type 2 diabetes group. This will be collected by an analysis of a fasting blood sample. By collecting the same variable on two timepoints, it is possible to determine if this outcome will change or remain stable over time. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Explanatory variables: change in quality of Life (QoL) from baseline to one and two-year follow-up | baseline | The WHOQoL-BREF quality of life scale is classified into four domains: Physical health, psychological well-being, social relationships, and environmental health. A better score means a better QoL (min. 0 and max. 100). By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Explanatory variables: Behavioral factors | baseline | A new questionnaire has been developed and is currently at the final stage of testing the test-retest reliability. This questionnaire questions the behavioral factors included within the integrated behavior change model i.e. autonomous motivation, attitude, self-efficacy, subjective norm, internal control and external control. A higher score means a behavior factor that positively relates to the health behavior. Furthermore, the cut-off point for the behavioral factors will be determined by the cumulative percentage. In addition, by collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Explanatory variables: socio-environmental factors | baseline | A new questionnaire has been developed and is currently at the final stage of testing the test-retest reliability. Socio-environmental factors include questions regarding social support and modeling. A higher score means a socio-environmental factors that positively relates to the health behavior. Furthermore, the cut-off point for the socio-environmental factors will be determined by the cumulative percentage. In addition, by collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Explanatory variables: physical environmental factors | baseline | A new questionnaire has been developed and is currently at the final stage of testing the test-retest reliability. Physical environmental factors include questions regarding walkability, neighborhood, work environment, sleep environment, and electronic devices at home. A higher score means a physical environmental factors that positively relates to the health behavior. Furthermore, the cut-off point for the physical environmental factors will be determined by the cumulative percentage. In addition, by collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Explanatory variables: change in demographics from baseline to one and two-year follow-up | baseline | The following demographics will be questioned: age, sex, ethnicity, smoking, educational level, profession, family situation, medication intake, and timing of T2DM diagnosis (only for the T2DM patient group). By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
| Explanatory variables: change in dietary factors from baseline to one and two-year follow-up | baseline | A Food frequency questionnaire will collect dietary information. This questionnaire is based on the Flemish food-based dietary guidelines for adults. This questionnaire can make a distinction between an intake of a healthy plant based diet or unhealthy plant based diet. A higher score means a more healthy plant based diet (min. 16 and max 80). By collecting the same variable on three timepoints, it is possible to determine if this outcome will change or remain stable over time. |
Countries
Belgium
Contacts
Primary ContactIris Willems, PhD student
Backup ContactMarieke De Craemer, Professor
Outcome results
None listed