Predictors of Persistent Medically Unexplained Physical Symptoms: Findings From a General Population Study
Jonna F. van Eck van der Sluijs, Jonna F. van Eck van der Sluijs, Margreet ten Have and 6 more
Frontiers in Psychiatry · 2018
doi:10.3389/fpsyt.2018.00613 (opens in a new tab)
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Abstract
Objective: To explore the persistency of Medically Unexplained Symptoms (MUS) and its prognostic factors in the general adult population. Knowledge of prognostic factors of MUS may indicate possible avenues for intervention development.Methods: Data were derived from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), a nationally representative face-to-face cohort study among the Dutch general population aged 18–64 years. We selected subjects with MUS at baseline and who participated at follow-up (N = 324) and reassessed those subjects for having MUS at 3 year follow-up. Logistic regression analyses were used to determine risk factors for persistency of MUS.Results: 36.4% of the subjects had persistent MUS at follow-up. In logistic regression analyses adjusted for sex and age, persistency of MUS was predicted by the number of comorbid chronic medical disorder(s), lower education, female sex, not having a paid job, parental psychopathology as well as lower functioning. In the logistic regression analysis in which all significant variables adjusted for sex and age were entered simultaneously, three variables predicted persistent MUS: parental psychopathology, the number of comorbid chronic medical disorder(s) and physical functioning, with odds ratios of 2.01 (1.20–3.38), 1.19 (1.01–1.40), and 0.99 (0.97–1.00), respectively.Conclusion: In the adult general population, MUS were persistent in over one third of the subjects with MUS at baseline. Persistency was significantly predicted by parental psychopathology, number of comorbid chronic medical disorders, and physical functioning. These findings warrant further research into early intervention and treatment options for persons with an increased risk of persistent MUS.
Abstract licence: CC BY
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