Predictors of chronic pain intensity, spread, and sensitivity in the general population: A two-year follow-up study from the SWEPAIN cohort

Abstract

This study shows how characteristics of chronic pain (intensity, spread and sensitivity) can be predicted using demographic and socioeconomic factors and other medical conditions. Information was collected from 34,000 individuals between 18 and 85 years of age in southeastern Sweden. Several socio-demographic factors and other medical conditions were predictors of pain intensity, spread and sensitivity after 2 years. When pain characteristics were taken into consideration in the analysis they were relatively strong predictors of the pain characteristics after 2 years. After modification of the analysis, there were fewer socio-demographic and medical predictors and their importance had decreased. In planning treatment and rehabilitation for chronic pain, pain intensity, spread and sensitivity should specifically be taken into account. Objective: To determine whether the intensity, spread and sensitivity of chronic pain can be predicted using demographic features, socioeconomic conditions and comorbidities. Design: A longitudinal study design was employed. Data was collected at baseline and at 2-year followup. Setting: General population in southeastern Sweden. Subjects: A representative stratified random sample of 34,000 individuals, between 18 and 85 years of age, selected from a sampling frame of 404,661 individuals based on the Swedish Total Population Register. Methods: Eligible individuals were sent postal surveys in 2013 and 2015. The 2 surveys included the same questions about basic demographic data, comorbidities, and chronic pain intensity, spread and sensitivity. Results: Several socio-demographic features and comorbidities at baseline were significant predictors of characteristics of pain (intensity, spread and sensitivity) at the 2-year follow-up. When characteristics of pain at baseline were included in the regression analyses they were relatively strong significant predictors of characteristics of pain after 2 years. After this adjustment there were fewer socio-demographic and comorbidity predictors; the effect estimates for those significant predictors had decreased. Conclusion: Clinical assessment should focus on several characteristics of pain and include a broad medical screening to capture the overall burden of pain in adults from a longitudinal perspective.

Natural Variation in Volatile Emissions of the Invasive Weed Calluna vulgaris in New Zealand

“…A Generalised Linear Model (GLM) assuming Gamma distribution (log-link) was first performed to compare the proportions of VOC classes between the four sites using the GLM function in R. VOC classes were response variables while the four study sites were used as a categorical predictor. The relevel function was used to construct a set of level contrasts for the four sites [69,70] and the Wald test used to evaluate the significance of estimated effects [71].…”

Predictive association between immigration status and chronic pain in the general population: results from the SwePain cohort

“…The sample frame consisted of 404,661 individuals who were 16-85 years old and living in south-eastern Sweden. The TPR uses a representative stratified random sample of 34,000 individuals of the sample frame [26][27][28][29]. The random sampling was stratified by sex and municipality to reach individuals living in urban and rural areas [29].…”

“…The random sampling was stratified by sex and municipality to reach individuals living in urban and rural areas [29]. The analytical procedures of the sample design methods and survey questionnaire including items of the SwePain cohort have been described in detail elsewhere [26][27][28][29]. Data were collected by Statistics Sweden (SCB) [30].…”

“…The collection of questionnaires ended in May 2013. Follow-up data were collected 2 years later [26,27]. The surveys at baseline and follow -up included the same questions.…”

“…These individuals completed and returned the questionnaire at baseline for a response rate of 46% (Additional File 1: Supplementary Table 1). The response rate at baseline was lower among men, single people, and immigrants (Additional File 1: Supplementary Table 1) [26]. At the two-year follow-up, from 15, 563 individuals who participated at baseline, 11386 individuals (55% women) completed and returned the questionnaire, a response rate of 73%.…”