Centre for Research in Evidence based Practice, Faculty of Health Sciences and Medicine, Bond University, Queensland.
Centre for Research Excellence in Women's Health in the 21st Century, Centre for Longitudinal and Life Course Epidemiology, School of Public Health, University of Queensland.
Aust N Z J Public Health. 2018 Apr;42(2):186-194. doi: 10.1111/1753-6405.12762. Epub 2018 Feb 14.
We performed a systematic review to identify, critically appraise and synthesise the existing literature on the association between SEP and multimorbidity occurrence.
We searched Medline and Embase from inception to December 2014. Where possible we performed meta-analysis to obtain summary odds ratios (ORs), exploring heterogeneity between studies through sub-group analysis.
We identified 24 cross-sectional studies that largely reported on education, deprivation or income in relation to multimorbidity occurrence. Differences in analysis methods allowed pooling of results for education only. Low versus high education level was associated with a 64% increased odds of multimorbidity (summary OR: 1.64, 95% CI 1.41 to 1.91), with substantial heterogeneity between studies partly explained by method of multimorbidity ascertainment. Increasing deprivation was consistently associated with increasing risk of multimorbidity, whereas the evidence on income was mixed. Few studies reported on interaction with age or sex.
More methodologically robust studies that address these gaps and investigate alternate measures of social circumstances and environment may advance our understanding of how SEP affects multimorbidity risk. Implications for public health: A deeper understanding of the socioeconomic and demographic patterning of multimorbidity will help identify sub-populations at greatest risk of becoming multimorbid.
我们进行了一项系统评价，以确定、批判性地评价并综合现有文献中关于社会经济地位（SEP）与多种疾病发生之间关系的研究。
我们检索了 Medline 和 Embase 从建库到 2014 年 12 月的数据。如有可能，我们进行了荟萃分析以获得汇总优势比（OR），通过亚组分析探索研究之间的异质性。
我们共纳入了 24 项横断面研究，这些研究主要报道了教育、贫困或收入与多种疾病发生的关系。由于分析方法的差异，仅对教育的结果进行了汇总。与高教育水平相比，低教育水平与多种疾病发生的几率增加 64%相关（汇总 OR：1.64，95%CI 1.41 至 1.91），但研究间存在很大的异质性，部分原因是多种疾病确定方法不同。与高教育水平相比，贫困程度越高，多种疾病发生的风险越高，而关于收入的证据则存在差异。很少有研究报告了与年龄或性别之间的相互作用。
更多方法学上更可靠的研究可以解决这些差距，并调查社会环境和环境的替代衡量指标，这可能有助于我们更好地理解社会经济地位如何影响多种疾病的发生风险。对公共卫生的意义：更深入地了解多种疾病的社会经济和人口统计学模式将有助于确定最有可能成为多种疾病患者的亚人群。
