Metabolic Syndrome
Conditions
Keywords
metabolic syndrome, lifestyle intervention, prevention, digital tools, elderly, older adults
Brief summary
In GATEKEEPER intervention, Big Data Analytics techniques will be exploited to address risk stratification and early detection, based on lifestyles analysis including: pattern recognition for the improvement of public health surveillance and for the early detection of chronic conditions; data mining for inductive reasoning and exploratory data analysis; Cluster Analysis for identifying high-risk groups among elder citizens. In the above cases timely intervention is provided by through AI-based, digital coaches, structured conversations, consultation and education. The main target group (N=960) is older adults and elderly citizens with risk factors for MetS and their carers. Therefore, the GATEKEEPER intervention aims at primary (avoid occurrence of disease) and secondary (early detection and management) prevention of the ageing population at risk for MetS.
Detailed description
Over 1.5 billion people worldwide are affected by Metabolic Syndrome (MetS) - a cluster of conditions reflecting behavioural risk factors typical of modern lifestyle (excessive food intake, low physical activity, etc) - with a huge socioeconomic impact and a total estimated cost of trillions of euros. Early prevention measures especially for elderly at high risk of chronic conditions, such as prediabetics or obese, include structured lifestyle change programs that help people achieve and sustain changes in dietary and physical activity habits. It is well established that MetS prevalence, as well as its individual components (high blood pressure, high glucose, central adiposity) increase with age. Notably, MetS percentages in the age group 50-55 years old and older is almost 2-3 times higher than in the younger age groups, probably due to a life time accumulation of adversities including overnutrition, a sedentary lifestyle, obesity and dyslipidemia, changes in the hormones, untreated hypertension, changes of the functioning of beta cells and other environmental and physiological factors. Therefore, it is important to target not only elderly citizens, but rather older adults aged ≥55 years old as the optimum target group for a MetS prevention intervention. In GATEKEEPER intervention, Big Data Analytics techniques will be exploited to address risk stratification and early detection, based on lifestyles analysis including: pattern recognition for the improvement of public health surveillance and for the early detection of chronic conditions; data mining for inductive reasoning and exploratory data analysis; Cluster Analysis for identifying high-risk groups among elder citizens. In the above cases timely intervention is provided by through AI-based, digital coaches, structured conversations, consultation and education. The main target group (N=960) is older adults and elderly citizens with risk factors for MetS and their carers. Therefore, the GATEKEEPER intervention aims at primary (avoid occurrence of disease) and secondary (early detection and management) prevention of the ageing population at risk for MetS. 960 older adults and elderly citizens (aged \>=55 years old) with risk factors for MetS as well as their carers (n=40) will be recruited and will be randomized to either: i) the intervention group 1 (n=320), who will be provided with the standard care plus a lifestyle application to promote self-management, increase health literacy and awareness through a digital coach, ii) the intervention group 2 (n=320), who will be provided with the standard care, the lifestyle application and additionally digital tools and wearables, such as a smart tracker and weight scale, or iii) the control group (n=320), who will only receive standard care, as provided by the local and national healthcare system as well as one face-to-face counselling session for lifestyle modification to improve their risk factors. The participants will be followed up for a total duration of 3 months, when they will be re-evaluated to assess whether their risk factors were improved through the lifestyle intervention. The users will be recruited at local community centres, such as the Open Day Elderly Centres, health centres, private offices of health care professionals, hospitals etc. upon written informed consent form.
Interventions
BEHAVIORALStandard care
Participants will receive only the standard care as provided by the local and national healthcare system as well as one face-to-face counselling session for lifestyle modification to improve their risk factors.
BEHAVIORALHealth-promotion application for self-management
Participants will be provided with a health-promotion application for self-management for 3 months, additionally to the standard care.
DEVICEWearables and devices
Participants will be provided with wearables and devices, including a weighing scale (assessing also body composition) device and a smartwatch/wristband to assess physical activity but also sleep pattern, for 3 months, additionally to the standard care and the Health-promotion application.
Sponsors
CitiesNet
University of Thessaly
University of Patras
BioAssist
University of Ioannina
Centre for Research & Technology Hellas (CERTH)
Harokopio University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
NONE
Intervention model description
The present study is a cluster-randomized lifestyle intervention aimed at primary and secondary prevention of MetS, including three study arms: standard care (control group), standard care plus lifestyle application (intervention group 1) and standard care plus lifestyle application and wearables and devices (intervention group 2). It is conducted with older adults and elderly (aged ≥55 years old) living at home and at risk for MetS, as well as their carers. The total duration of the intervention for each participant will be 3 months.
Eligibility
Sex/Gender
ALL
Age
55 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Males and females aged ≥55 years old * Having any of the following risk factors for MetS: * waist circumference \>94 cm for men and \>80 cm for women * Triglycerides (TG) ≥150 mg/dL * High-density lipoprotein cholesterol (HDL-C) \<40 mg/dL for men and \<50 mg/dL for women * Fasting glucose ≥100 mg/dL * Blood pressure ≥130 /≥85 mm Hg * Living at home (either alone or with relatives) * Informed consent form provided
Exclusion criteria
* Having severe hearing or vision problems or any other acute or chronic condition that would limit the ability of the user to participate in the study * Having dementia or cognitive impairment * Being institutionalised * Participation in another research project
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Waist circumference (cm) from baseline to 3 months | baseline and monthly until 3-month follow-up | Participants' waist circumference will be measured in triplicates (in cm) at baseline and at the 3rd month follow-up visit. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Changes in percentage of body fat from baseline to 3 months | baseline and monthly until 3-month follow-up | Participants' percentage of body fat will be measured at baseline and at the 3rd month follow-up visit. |
| Patient-reported outcome measures (PROMs) | baseline and 3 months | Patient-reported outcome measures (PROMs), including satisfaction of the intervention at baseline and at the 3rd month follow-up visit. Satisfaction of the intervention will be measured via the UTAUT questionnaire \[Liu D et al. 2019\] or other validated questionnaire. |
| Changes in Diet quality on FFQ and healthy diet score from baseline to 3 months | baseline and 3 months | Diet quality will be assessed via the food-frequency questionnaire (FFQ) and the healthy diet score developed and validated in the EU-funded Feel4Diabetes-study (www.feel4diabetes-study.eu) or other validated questionnaires at baseline and at the 3rd month follow-up visit. |
| Changes in body mass index (kg/m2) from baseline to 3 months | baseline and monthly until 3-month follow-up | Participants' BMI will be measured in triplicates (in kg/m2) at baseline and at the 3rd month follow-up visit. |
| Changes in Physical activity on validated questionnaires from baseline to 3 months | baseline and 3 months | Physical activity will be assessed via validated questionnaires at baseline and at the 3rd month follow-up visit. |
| Changes in sedentary time on validated questionnaires from baseline to 3 months | baseline and 3 months | Sedentary time will be assessed via validated questionnaires at baseline and at the 3rd month follow-up visit. |
| Changes in Sleep duration/quality on Athens Insomnia Scale questionnaire from baseline to 3 months | baseline and 3 months | Sleep duration and sleep quality will be assessed via the Athens Insomnia Scale questionnaire \[Soldatos CR et al. 2000\] or other validated questionnaires at baseline and at the 3rd month follow-up visit. |
| Changes in Quality of life on EQ5D (Generic HRQL) from baseline to 3 months | baseline and 3 months | Quality of life will be assessed via the EQ5D (Generic HRQL) \[Konerding U et al. 2014\] at baseline and at the 3rd month follow-up visit. |
Countries
Greece
Contacts
Primary ContactYannis Manios, PhD
Backup ContactEva Karaglani, PhD-c
Outcome results
None listed