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. 2010 Aug;197(2):106-13.
doi: 10.1192/bjp.bp.109.069674.

Aetiology of fatigue in Sri Lanka and its overlap with depression

Harriet A Ball  1 , Athula Sumathipala, Sisira H Siribaddana, Yulia Kovas, Nick Glozier, Peter McGuffin, Matthew Hotopf
Affiliations

Aetiology of fatigue in Sri Lanka and its overlap with depression

Harriet A Ball et al. Br J Psychiatry. 2010 Aug.

Abstract

Background: Fatigue is a common symptom in Western high-income countries but is often medically unexplained and little is known about its presentation in other populations.

Aims: To explore the epidemiology and aetiology of fatigue in Sri Lanka, and of its overlap with depression.

Method: A total of 4024 randomly selected twins from a population-based register in Sri Lanka (Colombo district) completed home interviews including the Chalder Fatigue Questionnaire.

Results: The prevalence of fatigue was similar to that in other countries, although prolonged fatigue may be less common. There was substantial comorbidity with a screen for lifetime depression. Non-shared environmental factors made the largest contributions, although genetic/family factors also contributed. The aetiology appeared consistent across the spectrum of severity.

Conclusions: The aetiology of fatigue is broadly similar in Sri Lanka and Western high-income countries. Abnormal experiences of fatigue appear to be the extreme form of more common fatigue, rather than representing independent entities with different genetic or environmental risk factors.

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Figures

Fig. 1
Fig. 1
Diagram representing the bivariate twin model. Only one twin from each pair is shown. The double-headed arrows represent the correlations between latent factors (e.g. r, the correlation between the genetic influence (A) on fatigue and the genetic influence on depression). The genetic contribution to the overall phenotypic overlap is found by examining the size of three paths: the genetic contribution to fatigue, r, and the genetic contribution to depression. This is also calculated for C (shared environment) and E (non-shared environment). Since the total phenotypic correlation consists of contributions from A, C and E, percentage contributions can then be calculated.
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