Using network analysis, which takes a holistic approach to health systems, we aimed to identify which psychosocial burden dimensions are the most central and, thus, critical to prioritising to improve the overall health of people with type 1 diabetes (PwT1D).

A cross-sectional network analysis.

We used data from participants attending 44 diabetes centres in France, who were enrolled in the SFDT1 cohort study between June 2020 and February 2024.

We included 1430 PwT1D (52% women, median age (IQR) 41 (31–52.8) years) who had completed questionnaires on diabetes burden.

The items from questionnaires on diabetes distress, fear of hypoglycaemia, quality of life, treatment burden and the impact of diabetes on education and work.

The network was highly stable (correlation stability coefficient=0.75). We observed nine domains within the network; ‘Loneliness, Worrying & Burnout’ was the most influential. We further grouped the domains into three distinct syndromes labelled ‘Diabetes Distress’, ‘Treatment Burden’ and ‘Impact of Diabetes on Life’. These syndromes reflect the most relevant pillars of the psychosocial burden in PwT1D.

We observed that ‘Loneliness, Worrying & Burnout’ is the most influential psychosocial burden network domain to prioritise for type 1 diabetes care. This new network-based approach opens the path to defining personalised interventions targeting the most critical burden parameters to expect the most significant overall beneficial impact on PwT1D’s health.

NCT04657783.

Stress is nearly ubiquitous in everyday life; however, it imposes a tremendous burden worldwide by acting as a risk factor for most physical and mental diseases. The effects of geographic environments on stress are supported by multiple theories acknowledging that natural environments act as a stress buffer and provide deeper and quicker restorative effects than most urban settings. However, little is known about how the temporalities of exposure to complex urban environments (duration, frequency and sequences of exposures) experienced in various locations – as shaped by people’s daily activities – affect daily and chronic stress levels. The potential modifying effect of activity patterns (ie, time, place, activity type and social company) on the environment–stress relationship also remains poorly understood. Moreover, most observational studies relied quasi-exclusively on self-reported stress measurements, which may not accurately reflect the individual physiological embodiment of stress. The FragMent study aims to assess the extent to which the spatial and temporal characteristics of exposures to environments in daily life, along with individuals’ activity patterns, influence physiological and psychological stress.

A sample of 2000 adults aged 18–65 and residing in the country of Luxembourg completed a traditional and a map-based questionnaire to collect data on their perceived built, natural and social environments, regular mobility, activity patterns and chronic stress at baseline. A subsample of 200 participants engaged in a 15-day geographically explicit ecological momentary assessment (GEMA) survey, combining a smartphone-enabled global positioning system (GPS) tracking and the repeated daily assessment of the participants’ momentary stress, activities and environmental perceptions. Participants further complete multiple daily vocal tasks to collect data on vocal biomarkers of stress. Analytical methods will include machine learning models for stress prediction from vocal features, the use of geographic information systems (GIS) to quantify dynamic environmental exposures in space and time, and statistical models to disentangle the environment–stress relationships.

Ethical approval (LISER REC/2021/024.FRAGMENT/4-5-9-10) was granted by the Research Ethics Committee of the Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg. Results will be disseminated via conferences, peer-review journal papers and comic strips. All project outcomes will be made available at https://www.fragmentproject.eu/.