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BACKGROUND: Cross-sectional studies have reported an inverse relationship between socio-economic status and the prevalence of chronic widespread pain (CWP). However, the extent to which this relationship is explained by psychological factors is unknown. The aim of this study was to examine the hypothesis that socio-economic status predicts the onset of CWP but that this relationship would be explained by psychological factors. METHODS: Subjects from three diverse socio-economic areas were recruited into a population-based prospective survey of pain. Subjects completed a questionnaire at baseline that assessed pain status and psychological factors and occupation. Fifteen months later subjects completed a follow-up questionnaire which assessed pain status. RESULTS: A total of 3489 subjects were free of CWP at baseline and eligible for follow-up, of whom 2782 (79.7%) participated. Of those, 281 (10%) subjects were classified as having new CWP. Logistic regression analysis revealed that compared to subjects from the most affluent socio-economic area, those from the moderate and least affluent areas were respectively, 1.47 (95% CI: 1.08-2.01) and 1.35 (95% CI: 1.00-1.82) times more likely to have new CWP. However, in a stepwise multivariate logistic regression analysis, controlling for psychological factors, the relationship between new onset CWP and socio-economic status was no longer evident. CONCLUSIONS: This study has demonstrated that socio-economic status is related to new onset CWP, but the association is explained by psychological factors. Understanding the factors underlying the association between socio-economic status and pain should help to design intervention strategies which may reduce the burden of chronic pain in identified high risk population groups.

Original publication

DOI

10.1016/j.ejpain.2008.07.003

Type

Journal article

Journal

Eur J Pain

Publication Date

07/2009

Volume

13

Pages

635 - 640

Keywords

Adolescent, Adult, Aged, Anxiety, Chronic Disease, Female, Humans, Illness Behavior, Logistic Models, Male, Middle Aged, Occupations, Pain, Pain Measurement, Patient Selection, Population, Residence Characteristics, Social Class, Surveys and Questionnaires, Young Adult