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Citation |
Imperiale MN, Lieb R, Calkins ME, Meinlschmidt G. J. Psychiatr. Res. 2021; 141: 267-275. |
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Copyright |
(Copyright © 2021, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Our aim was to scrutinize multimorbidity in a community sample of youths (Philadelphia Neurodevelopmental Cohort) in form of co-occurrences of DSM-IV disorder symptom domains, elucidating if and when specific symptom domain interrelations emerge as mental disorder severity levels increase. We estimated four multimorbidity networks based on four severity cut-offs ('at least symptomatic', 'at least subthreshold', 'at least threshold', and 'impaired') and compared them pairwise on two measures: global network strength and network structure. We further computed community clusters for each network to detect symptom domain interrelations. Pairwise comparisons of the multimorbidity networks based on data from 9410 probands showed significant differences in global strength of the networks with the two highest severity cut-offs ('impaired' and 'at least threshold') with the at least symptomatic networks (p < .05). The networks with the three highest severity cut-offs ('impaired', 'at least threshold', and 'at least subthreshold') differed significantly (p < .001) from the at least symptomatic network regarding global network structure but did not significantly differ from each other (p > .05). We identified four common clusters in the impaired, at least threshold, and at least subthreshold networks consisting of i) domains associated with behavioral disorders; ii) domains associated with anxiety disorders (agoraphobia, social anxiety and specific phobia); iii) domains associated with anxiety/mood/eating and; iv) domains associated with mood/eating disorders. We found that major mental disorder symptom domain interrelations become consistent from a subthreshold level onwards. Language: en |
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Keywords |
Psychopathology; Community detection; Multimorbidity; Network analysis; Severity levels |