Thanya I Pathirana1, Caroline A Jackson2,3. 1. Centre for Research in Evidence based Practice, Faculty of Health Sciences and Medicine, Bond University, Queensland. 2. 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. 3. Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, UK.
Abstract
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.
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.
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