Socioeconomic status and multimorbidity: A systematic review and meta-analysis

Thanya I. Pathirana*, Caroline A. Jackson

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

221 Citations (Scopus)
235 Downloads (Pure)


Objectives: We performed a systematic review to identify, critically appraise and synthesise the existing literature on the association between SEP and multimorbidity occurrence. Methods: 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. Results: 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. Conclusions: 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.

Original languageEnglish
Pages (from-to)186-194
Number of pages9
JournalAustralian and New Zealand Journal of Public Health
Issue number2
Early online date14 Feb 2018
Publication statusPublished - Apr 2018


Dive into the research topics of 'Socioeconomic status and multimorbidity: A systematic review and meta-analysis'. Together they form a unique fingerprint.

Cite this