Chronic pain in families: A cross-sectional study of shared social, behavioural, and environmental influences

Generation Scotland, Paul Campbell (Lead / Corresponding author), Kelvin P. Jordan, Blair Smith, Kate M. Dunn

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    17 Citations (Scopus)
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    Abstract

    Chronic pain is common and creates significant burden to the individual and society. Emerging research has shown the influence of the family environment on pain outcomes. However it is not clear what shared factors between family members associate with chronic pain. This study aimed to investigate the family level contribution to an individual’s chronic pain status. This was a cross sectional study using the Generation Scotland: Scottish Family Health Study dataset. This study focused on a nested cohort of dyads (only 2 relatives per family, n = 2714). Multilevel modelling was first carried out to estimate the extent of variance in chronic pain at the family level. Then each member of the dyad was randomly assigned as either the exposure or outcome family member and logistic regression was used to identify shared factors associated with the outcome of chronic pain status. Multilevel modelling showed just under 10% of variation in chronic pain status was at a family level. There was an increase in odds of chronic pain if exposure family member had chronic pain (OR 1.30, 95% CI 1.02, 1.65), if both were female (OR 1.39, 95% CI 0.99, 1.94), both older age (OR 1.80, 95% CI 1.31, 2.48), and if both had low household income (OR 3.27, 95% CI 1.72, 6.21). These findings show that the majority of explanation for chronic pain is still at the individual level. However some significant shared effects between family members associate with chronic pain, and this highlights the influence of the family context.
    Original languageEnglish
    Pages (from-to)41-47
    Number of pages7
    JournalPain
    Volume159
    Issue number1
    Early online date11 Sept 2017
    DOIs
    Publication statusPublished - 1 Jan 2018

    Keywords

    • Chronic pain
    • Family
    • Multilevel Modelling
    • Social
    • Generation Scotland
    • Concordance

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