Fliesser Michael, De Witt Huberts Jessie, Wippert Pia-Maria
Sociology of Health and Physical Activity, University of Potsdam, Am Neuen Palais 10, 14469, Potsdam, Germany.
BMC Health Serv Res. 2017 Dec 2;17(1):800. doi: 10.1186/s12913-017-2735-9.
In health research, indicators of socioeconomic status (SES) are often used interchangeably and often lack theoretical foundation. This makes it difficult to compare results from different studies and to explore the relationship between SES and health outcomes. To aid researchers in choosing appropriate indicators of SES, this article proposes and tests a theory-based selection of SES indicators using chronic back pain as a health outcome.
Strength of relationship predictions were made using Brunner & Marmot's model of 'social determinants of health'. Subsequently, a longitudinal study was conducted with 66 patients receiving in-patient treatment for chronic back pain. Sociodemographic variables, four SES indicators (education, job position, income, multidimensional index) and back pain intensity and disability were obtained at baseline. Both pain dimensions were assessed again 6 months later. Using linear regression, the predictive strength of each SES indicator on pain intensity and disability was estimated and compared to the theory based prediction.
Chronic back pain intensity was best predicted by the multidimensional index (beta = 0.31, p < 0.05), followed by job position (beta = 0.29, p < 0.05) and education (beta = -0.29, p < 0.05); whereas, income exerted no significant influence. Back pain disability was predicted strongest by education (beta = -0.30, p < 0.05) and job position (beta = 0.29, p < 0.05). Here, multidimensional index and income had no significant influence.
The choice of SES indicators influences predictive power on both back pain dimensions, suggesting SES predictors cannot be used interchangeably. Therefore, researchers should carefully consider prior to each study which SES indicator to use. The introduced framework can be valuable in supporting this decision because it allows for a stable prediction of SES indicator influence and their hierarchy on a specific health outcomes.
在健康研究中，社会经济地位（SES）指标常常被互换使用，且往往缺乏理论基础。这使得不同研究结果之间难以比较，也难以探究社会经济地位与健康结果之间的关系。为帮助研究人员选择合适的社会经济地位指标，本文以慢性背痛作为健康结果，提出并检验了一种基于理论的社会经济地位指标选择方法。
使用布鲁纳和马尔莫的“健康的社会决定因素”模型进行关系强度预测。随后，对66名因慢性背痛接受住院治疗的患者进行了一项纵向研究。在基线时获取了社会人口统计学变量、四个社会经济地位指标（教育程度、工作职位、收入、多维指数）以及背痛强度和残疾情况。6个月后再次评估了这两个疼痛维度。使用线性回归估计每个社会经济地位指标对疼痛强度和残疾的预测强度，并与基于理论的预测进行比较。
多维指数对慢性背痛强度的预测效果最佳（β = 0.31，p < 0.05），其次是工作职位（β = 0.29，p < 0.05）和教育程度（β = -0.29，p < 0.05）；而收入没有显著影响。教育程度（β = -0.30，p < 0.05）和工作职位（β = 0.29，p < 0.05）对背痛残疾的预测作用最强。在此，多维指数和收入没有显著影响。
社会经济地位指标的选择会影响对两个背痛维度的预测能力，这表明社会经济地位预测指标不能互换使用。因此，研究人员在每项研究之前应仔细考虑使用哪个社会经济地位指标。所引入的框架在支持这一决策方面可能很有价值，因为它能够对社会经济地位指标对特定健康结果的影响及其层级进行稳定的预测。
