Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue
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BioMed Central
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Replication of an empirical approach to delineate the heterogeneity of chronic unexplained fatigue Eric Aslakson1, Uté Vollmer-Conna2, William C Reeves*1 and Peter D White3 Address: 1Centers for Disease Control and Prevention, Atlanta, Georgia, USA, 2School of Psychiatry, University of NSW, Sydney, Australia and 3Center for Psychiatry, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine, Queen Mary University of London, UK Email: Eric Aslakson - [email protected]; Uté Vollmer-Conna - [email protected]; William C Reeves* - [email protected]; Peter D White - [email protected] * Corresponding author
Published: 5 October 2009 Population Health Metrics 2009, 7:17
doi:10.1186/1478-7954-7-17
Received: 22 September 2008 Accepted: 5 October 2009
This article is available from: http://www.pophealthmetrics.com/content/7/1/17 © 2009 Aslakson et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: Chronic fatigue syndrome (CFS) is defined by self-reported symptoms. There are no diagnostic signs or laboratory markers, and the pathophysiology remains inchoate. In part, difficulties identifying and replicating biomarkers and elucidating the pathophysiology reflect the heterogeneous nature of the syndromic illness CFS. We conducted this analysis of people from defined metropolitan, urban, and rural populations to replicate our earlier empirical delineation of medically unexplained chronic fatigue and CFS into discrete endophenotypes. Both the earlier and current analyses utilized quantitative measures of functional impairment and symptoms as well as laboratory data. This study and the earlier one enrolled participants from defined populations and measured the internal milieu, which differentiates them from studies of clinic referrals that examine only clinical phenotypes. Methods: This analysis evaluated 386 women identified in a population-based survey of chronic fatigue and unwellness in metropolitan, urban, and rural populations of the state of Georgia, USA. We used variables previously demonstrated to effectively delineate endophenotypes in an attempt to replicate identification of these endophenotypes. Latent class analyses were used to derive the classes, and these were compared and contrasted to those described in the previous study based in Wichita, Kansas. Results: We identified five classes in the best fit analysis. Participants in Class 1 (25%) were polysymptomatic, with sleep problems and depressed mood. Class 2 (24%) was also polysymptomatic, with insomnia and depression, but participants were also obese with associated metabolic strain. Class 3 (20%) had more selective symptoms but was equally obese with metabolic strain. Class 4 (20%) and Class 5 (11%) consisted of nonfatig
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