Pain and Rehabilitation Centre, and Department of Medical and Health Sciences, Linköping University, 581 85 Linköping, Sweden.
J Rehabil Med. 2019 Mar 13;51(3):183-192. doi: 10.2340/16501977-2519.
To determine whether the intensity, spread and sensitivity of chronic pain can be predicted using demographic features, socioeconomic conditions and comorbidities.
A longitudinal study design was employed. Data was collected at baseline and at 2-year follow-up.
General population in south-eastern Sweden.
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.
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.
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-demogra-phic and comorbidity predictors; the effect estimates for those significant predictors had decreased.
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.
确定使用人口统计学特征、社会经济状况和合并症是否可以预测慢性疼痛的强度、范围和敏感性。
采用纵向研究设计。数据在基线和 2 年随访时收集。
瑞典东南部的一般人群。
从瑞典总人口登记册中基于 404661 人的抽样框架中选择的 34000 名年龄在 18 至 85 岁之间的代表性分层随机样本。
合格的个人于 2013 年和 2015 年收到了邮寄调查。这 2 项调查包含了关于基本人口统计学数据、合并症和慢性疼痛强度、范围和敏感性的相同问题。
基线时的几个社会人口统计学特征和合并症是疼痛特征(强度、范围和敏感性)在 2 年随访时的显著预测因素。当将基线时的疼痛特征纳入回归分析时,它们是 2 年后疼痛特征的相对较强的显著预测因素。在此调整后,社会人口统计学和合并症预测因素较少;这些显著预测因素的效应估计值有所降低。
临床评估应侧重于疼痛的几个特征,并进行广泛的医学筛查,从纵向角度捕捉成年人整体疼痛负担。