Somatic symptom reports in the general population: Application of a bi-factor model to the analysis of change

J Psychosom Res. 2015 Nov;79(5):378-83. doi: 10.1016/j.jpsychores.2015.09.006. Epub 2015 Sep 21.

Abstract

Objective: To investigate the latent structure of somatic symptom reports in the general population with a bi-factor model and apply the structure to the analysis of change in reported symptoms after the emergence of an uncertain environmental health risk.

Methods: Somatic symptoms were assessed in two general population environmental health cohorts (AMIGO, n=14,829 & POWER, n=951) using the somatization scale of the four-dimensional symptom questionnaire (4DSQ-S). Exploratory bi-factor analysis was used to determine the factor structure in the AMIGO cohort. Multi-group and longitudinal models were applied to assess measurement invariance. For a subsample of residents living close to a newly introduced power line (n=224), we compared a uni- and multidimensional method for the analysis of change in reported symptoms after the power line was put into operation.

Results: We found a good fit (RMSEA=0.03, CFI=0.98) for a bi-factor model with one general and three symptom specific factors (musculoskeletal, gastrointestinal, cardiopulmonary). The latent structure was found to be invariant between cohorts and over time. A significant increase (p<.05) was found only for musculoskeletal and gastrointestinal symptoms after the power line was put into operation.

Conclusions: In our study we found that a bi-factor structure of somatic symptoms reports was equivalent between cohorts and over time. Our findings suggest that taking this structure into account can lead to a more informative interpretation of a change in symptom reports compared to a unidimensional approach.

Keywords: Bi-factor model; Latent structure; Measurement invariance; Self-report; Somatic symptoms; Symptom patterns.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Environmental Health
  • Factor Analysis, Statistical
  • Female
  • Gastrointestinal Diseases / epidemiology
  • Heart Diseases / epidemiology
  • Humans
  • Lung Diseases / epidemiology
  • Male
  • Middle Aged
  • Models, Statistical
  • Musculoskeletal Diseases / epidemiology
  • Risk Assessment
  • Somatoform Disorders / epidemiology*
  • Somatoform Disorders / physiopathology
  • Surveys and Questionnaires