1000Quantifying multiple causes of death: A systematic review and audit of methods and practice. (2nd September 2021)

• Record Type: Journal Article
• Authors: Balogun, Saliu; Bishop, Karen; Eynstone-Hinkins, James; Martin, Melonie; Moreno-Betancur, Margarita; Rao, Chalapati; Joshy, Grace
• Is Part Of: International journal of epidemiology. Volume 50(2021)Supplement 1
• Publication Date: 2021-09-02
• Subjects: Epidemiology -- Periodicals; 614.4
• DOI: 10.1093/ije/dyab168.057
• Languages: English
• ISSNs: 0300-5771

Abstract

Abstract: Background: Mortality reporting and research are typically focused on a single underlying cause of death (UCoD) selected from multiple reported causes. The need to incorporate multiple causes of death (MCoD) in mortality statistics is now recognised internationally, but there is scant methodological work to guide analytical approaches. This review aims to identify and appraise current methods and practices used to analyse MCoD data. Methods: The Web of Science, Medline, Pubmed and Scopus (from inception to December 2019) were queried. Studies reporting MCoD alone or in comparison with single UCoD were included. The review is supplemented by qualitative interview with international experts. Results: 3491 studies were identified; 141 full texts were included in the review. The measures usually estimated when analysing MCoD can be broadly categorised into descriptive measures (n = 93 studies), measures of associations between diseases (n = 46 studies) and advanced statistical methods (n = 11 studies). Descriptive statistics commonly used include standardized ratio of multiple to underlying cause (SRMU) and mortality rates based on any mention of a disease. Approaches used to assess measures of associations between diseases include the Cause-of-Death Association Indicator (CDAI) and social network analysis. The advanced statistical methods include weighting MCoD and lethal defect-wear model of mortality. Audit results will be discussed. Conclusions: This review provides a comprehensive and updated summary of methodological approaches used to analyse MCoD data. The merit of each analytical framework is discussed. Key messages: More work is needed to develop methodological frameworks that could be used to support routine consideration of MCoD in practice.