Symptom load and functional status: results from the Ullensaker population study
1 Department of Community Health Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
2 Department of General Practice Institute of Health and Society, Faculty of Medicine, University of Oslo, P.O.Box 1130, Blindern, N-0318, Oslo, Norway
3 Health UMB, IHA, University of Life Sciences (UMB), Aas, Norway
4 Sintef Health Research, Oslo, Norway
BMC Public Health 2012, 12:1085 doi:10.1186/1471-2458-12-1085Published: 18 December 2012
There is evidence to support that the number of self-reported symptoms is a strong predictor of health outcomes. In studies examining the link between symptoms and functional status, focus has traditionally been on individual symptoms or specific groups of symptoms. We aim to identify associations between the number of self-reported symptoms and functional status.
A questionnaire was sent to people in seven age groups (N = 3227) in Ullensaker municipality in Southern Norway. The Standardised Nordic Questionnaire and the Subjective Health Complaints Inventory were used to record 10 musculoskeletal symptoms and 13 non-musculoskeletal symptoms, respectively. Four COOP-WONCA charts were used to measure functional status.
We found a strong linear association between the number of self-reported symptoms and functional status. The number of symptoms explained 39.2% of the variance in functional status after adjusting for the effects of age and sex. Including individual symptoms instead of only the number of symptoms made little difference to the effect of musculoskeletal pain but affected the influence of non-muscular symptoms. Including even minor problems captured substantially more of the variance in functional status than including only serious problems.
The strong association between the number of symptoms and functional status, irrespective of type of symptom, might indicate that the symptoms share some common characteristics. The simple act of counting symptoms may provide an approach to study the relationships between health and function in population studies and might be valuable in research on medically unexplained conditions.