Physical activity (PA) and sedentary lifestyle are determinants in the development of chronic diseases and associated quality of life alterations. PA levels are correlated with quality of life and morbidity in chronic lung disease (COPD), cardiovascular disease, diabetes, cancer, chronic inflammatory rheumatism, fibromyalgia and anxiety disorders. In these diseases, low-intensity PA often represents the main PA and the quantity of PA is correlated with health parameters. This study aims to identify a typical profile (signature) in relation to the appearance of other chronic diseases, complications of your disease, from recording your physical activity and sedentary lifestyle by sensors evaluating very precisely the movements and taking into account the characteristics and disability related to your disease. The results of this study would therefore make it possible to identify this signature even before the appearance of complications or other diseases.
Study design : eMOB study is a monocentric prospective cohort study. We aim to explore in a longitudinal study the association of a digital signature of PA and sedentary lifestyle with the development of at least one additionnal comorbidity overs 4 years of follow-up in chronic diseases. Population : Patients with inflammatory rheumatic disease(rheumatoid arthritis and spondyloarthritis), pre-surgical knee and hip osteoarthritis, major depressive disorder and bipolar disorder, type 2 diabetes, obesity, COPD and chronic pain followed up in the observational cohorts specific to each pathology at the CHU of Clermont Ferrand, will be proposed to participate in the study during their follow-up visit. Method : The occurrence of comorbidity is monitored every year during follow-up visits of the patients. Physical activity and sedentary lifestyle is assessed using accelerometer and wearable sensors. The combination of quantitative analysis of movement with a more detailed analysis of movement and sequences of movements, and a personalization of the algorithm according to the disease and the context, could make it possible to establish predictive signatures either of the disease itself or of associated complications. 700 patients will be included in the study.They will be followed for 4 years with : * An annual visit during which : * clinical data in the routine follow-up will be collected (BMI, waist circumference, blood pressure, heart rate, comorbidities, activity and severity scores specific to each disease and used for the routine follow-up, treatments, lifestyle, family and socio-professional situation, education level) * comorbidities will be noted by the list used for the study * physical capacity will be assessed with the 6-minute walk test and the hand grip * questionnaires about Pain (QCD), Fatigue (FACIT-F), Anxiety and Depression (HADs), Quality of life (WhoQol-BREF), Poverty (EPICES), Physical activity questionnaire (RPAQ), Barriers and Facilitators to physical activity questionnaire (B\&F-AP), Sleep and daytime sleepiness (PSQI and Epworth), treatment compliance (MARS) will be completed * specific data for each pathology in each cohort will be collected * Accelerometer data 3 times a year for 5 days (3 weekdays and 2 weekend days) will be collected * Electronic patient report outcomes (e-PRO) every 4 months concerning the socio-professional situation of the patients, alcohol and tobacco consumption, skipping meals and snacking between meals, health problems they may encounter during the study. Numerical scales between 0 and 10 will be completed to assess disease status, health status, pain, sleep, fatigue, psychological well-being, and anxiety. Among the included patients, 10 patients per cohort will participate in the preliminary feasibility phase of the study before starting the follow-up in the study. It is a validation of the acquisition modalities of the pre-selected sensors and a calibration on representative samples of patients with the different chronic pathologies studied (locomotor, respiratory, metabolic, psychiatric, pain).
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
700
Patients will wear an accelerometer 3 times a year for 5 days (3 weekdays and 2 weekend days), the data will be collected
CHU de Clermont-Ferrand
Clermont-Ferrand, France
RECRUITINGOccurrence of one additional comorbidity in patients with chronic diseases.
Association of a digital signature of PA and sedentary lifestyle with the development of at least one additional comorbidity over 4 years of follow-up.
Time frame: year 4
Digital signature of sedentary lifestyle and PA in patients with chronic diseases.
A sensor of movement will be worn by the patients for 5 days every 4 months during the study, to detect and quantify the physical activity and the sedentarity according to their intensity. This sensor will be accelerometer, allowing the acquisition of movements second by second. The analysis of the data from the sensors, the occurrence of a new comorbidity, the clinical data will allow to establish an algorithm to define a profile (digital signature) of occurrence of a new chronic disease.
Time frame: Year 4
Occurence of multimorbidity in patients with chronic diseases.
Association of a sedentary and PA signature with the development over 4 years of one, two, three, or more comorbidities (multimorbidity).
Time frame: Year 1
Occurence of multimorbidity in patients with chronic diseases.
Association of a sedentary and PA signature with the development over 4 years of one, two, three, or more comorbidities (multimorbidity).
Time frame: year 2
Occurence of multimorbidity in patients with chronic diseases.
Association of a sedentary and PA signature with the development over 4 years of one, two, three, or more comorbidities (multimorbidity).
Time frame: Year 3
Occurence of multimorbidity in patients with chronic diseases.
Association of a sedentary and PA signature with the development over 4 years of one, two, three, or more comorbidities (multimorbidity).
Time frame: Yaer 4
Correlation of PA/sedentary signature with destabilization or improvement/stability of the chronic condition.
Collect during the study clinical data, disease activity parameters in each cohort, physical capacity, and self questionnaires to explore PA/sedentary signature and its trajectory associated with destabilization or improvement/stability of the chronic condition.
Time frame: Year 1
Correlation of PA/sedentary signature with destabilization or improvement/stability of the chronic condition.
Collect during the study clinical data, disease activity parameters in each cohort, physical capacity, and self questionnaires to explore PA/sedentary signature and its trajectory associated with destabilization or improvement/stability of the chronic condition.
Time frame: Year 2
Correlation of PA/sedentary signature with destabilization or improvement/stability of the chronic condition.
Collect during the study clinical data, disease activity parameters in each cohort, physical capacity, and self questionnaires to explore PA/sedentary signature and its trajectory associated with destabilization or improvement/stability of the chronic condition.
Time frame: Year 3
Correlation of PA/sedentary signature with destabilization or improvement/stability of the chronic condition.
Collect during the study clinical data, disease activity parameters in each cohort, physical capacity, and self questionnaires to explore PA/sedentary signature and its trajectory associated with destabilization or improvement/stability of the chronic condition.
Time frame: Year 4
Correlation of PA/sendetary and treatments for chronic diseases.
Collect treatments of patients in each cohort at inclusion and each year over the study to explore PA/sedentary signature and its trajectory associated with achieving a decline in background treatments for chronic disease.
Time frame: Year 1
Correlation of PA/sendetary and treatments for chronic diseases.
Collect treatments of patients in each cohort at inclusion and each year over the study to explore PA/sedentary signature and its trajectory associated with achieving a decline in background treatments for chronic disease.
Time frame: year 2
Correlation of PA/sendetary and treatments for chronic diseases.
Collect treatments of patients in each cohort at inclusion and each year over the study to explore PA/sedentary signature and its trajectory associated with achieving a decline in background treatments for chronic disease.
Time frame: Year 3
Correlation of PA/sendetary and treatments for chronic diseases.
Collect treatments of patients in each cohort at inclusion and each year over the study to explore PA/sedentary signature and its trajectory associated with achieving a decline in background treatments for chronic disease.
Time frame: Year 4
Correlation of PA and sedentary measures and quality of life (QOL) of patients
Quality of life will be assessed with the World Health Organization Quality of Life Instruments (WhoQol-BREF) questionnaire, which has 26 items, divided into 4 domains: physical health, psychological, social relationship and environment. The score for each item ranges from 1 to 5. The score for each domain is calculated using a template designed by the WhoQol-BREF development team. The higher the score, the better the health status. The association between the score of each domain of WhoQol-BREF and PA/sedentary profile will be explored.
Time frame: Year 1
Correlation of PA and sedentary measures and quality of life (QOL) of patients
Quality of life will be assessed with the World Health Organization Quality of Life Instruments (WhoQol-BREF) questionnaire, which has 26 items, divided into 4 domains: physical health, psychological, social relationship and environment. The score for each item ranges from 1 to 5. The score for each domain is calculated using a template designed by the WhoQol-BREF development team. The higher the score, the better the health status. The association between the score of each domain of WhoQol-BREF and PA/sedentary profile will be explored.
Time frame: Year 2
Correlation of PA and sedentary measures and quality of life (QOL) of patients
Quality of life will be assessed with the World Health Organization Quality of Life Instruments (WhoQol-BREF) questionnaire, which has 26 items, divided into 4 domains: physical health, psychological, social relationship and environment. The score for each item ranges from 1 to 5. The score for each domain is calculated using a template designed by the WhoQol-BREF development team. The higher the score, the better the health status. The association between the score of each domain of WhoQol-BREF and PA/sedentary profile will be explored.
Time frame: year 3
Correlation of PA and sedentary measures and quality of life (QOL) of patients
Quality of life will be assessed with the World Health Organization Quality of Life Instruments (WhoQol-BREF) questionnaire, which has 26 items, divided into 4 domains: physical health, psychological, social relationship and environment. The score for each item ranges from 1 to 5. The score for each domain is calculated using a template designed by the WhoQol-BREF development team. The higher the score, the better the health status. The association between the score of each domain of WhoQol-BREF and PA/sedentary profile will be explored.
Time frame: Year 4
Occurrence of hospitalization and/or surgery of patients in each cohort
Patient hospitalization and/or surgery data are collected during follow-up (period of hospitalization, condition of hospitalization).
Time frame: Year 1
Occurrence of hospitalization and/or surgery of patients in each cohort
Patient hospitalization and/or surgery data are collected during follow-up (period of hospitalization, condition of hospitalization).
Time frame: Year 2
Occurrence of hospitalization and/or surgery of patients in each cohort
Patient hospitalization and/or surgery data are collected during follow-up (period of hospitalization, condition of hospitalization).
Time frame: Year 3
Occurrence of hospitalization and/or surgery of patients in each cohort
Patient hospitalization and/or surgery data are collected during follow-up (period of hospitalization, condition of hospitalization).
Time frame: Year 4
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