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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Aims/hypothesis</jats:title>
<jats:p>Diabetes distress is one of the most frequent mental health issues identified in people with type 1 and type 2 diabetes. Little is known about the role of glucose control as a potential contributor to diabetes distress and whether the subjective perception of glucose control or the objective glycaemic parameters are more important for the experience. With the emergence of continuous glucose monitoring (CGM), this is a relevant question as glucose values are now visible in real-time. We employed a precision monitoring approach to analyse the independent associations of perceived and measured glucose control with diabetes distress on a daily basis. By using <jats:italic>n</jats:italic>-of-1 analyses, we aimed to identify individual contributors to diabetes distress per person and analyse the associations of these individual contributors with mental health at a 3 month follow-up.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>In this prospective, observational study, perceived (hypoglycaemia/hyperglycaemia/glucose variability burden) and measured glucose control (time in hypoglycaemia and hyperglycaemia, CV) were assessed daily for 17 days using an ecological momentary assessment (EMA) approach with a special EMA app and CGM, respectively. Mixed-effect regression analysis was performed, with daily diabetes distress as the dependent variable and daily perceived and CGM-measured metrics of glucose control as random factors. Individual regression coefficients of daily distress with perceived and CGM-measured metrics were correlated with levels of psychosocial well-being at a 3 month follow-up.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Data from 379 participants were analysed (50.9% type 1 diabetes; 49.6% female). Perceived glucose variability (<jats:italic>t</jats:italic>=14.360; <jats:italic>p</jats:italic><0.0001) and perceived hyperglycaemia (<jats:italic>t</jats:italic>=13.637; <jats:italic>p</jats:italic><0.0001) were the strongest predictors of daily diabetes distress, while CGM-based glucose variability was not significantly associated (<jats:italic>t</jats:italic>=1.070; <jats:italic>p</jats:italic>=0.285). There was great heterogeneity between individuals in the associations of perceived and measured glucose parameters with diabetes distress. Individuals with a stronger association between perceived glucose control and daily distress had more depressive symptoms (β=0.32), diabetes distress (β=0.39) and hypoglycaemia fear (β=0.34) at follow-up (all <jats:italic>p</jats:italic><0.001). Individuals with a stronger association between CGM-measured glucose control and daily distress had higher levels of psychosocial well-being at follow-up (depressive symptoms: β=−0.31; diabetes distress: β=−0.33; hypoglycaemia fear: β=−0.27; all <jats:italic>p</jats:italic><0.001) but also higher HbA<jats:sub>1c</jats:sub> (β=0.12; <jats:italic>p</jats:italic><0.05).</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusions/interpretation</jats:title>
<jats:p>Overall, subjective perceptions of glucose seem to be more influential on diabetes distress than objective CGM parameters of glycaemic control. <jats:italic>N</jats:italic>-of-1 analyses showed that CGM-measured and perceived glucose control had differential associations with diabetes distress and psychosocial well-being 3 months later. The results highlight the need to understand the individual drivers of diabetes distress to develop personalised interventions within a precision mental health approach.</jats:p>
</jats:sec><jats:sec>
<jats:title>Graphical Abstract</jats:title>
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Hinweis
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DeepGreen-ID: 1208ab42d251420e820172dd2b93b2a1 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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