Use of Multiple-Cause Mortality Data in Epidemiologic Analyses: US Rate and Proportion Files Developed by the National Institute for Occupational Safety and Health and the National Cancer Institute

The authors have created US mortality rates (age, sex, race, and calendar-time specific) and proportions, using multiple cause-of-death data, for the years 1960–1989. Multiple cause-of-death data include the usual underlying cause of death from the death certificate as well as contributory causes an...

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Bibliographic Details
Published in:American journal of epidemiology 1992-10, Vol.136 (7), p.855-862
Main Authors: Steenland, Kule, Nowlin, Sue, Adams, Steven
Format: Article
Language:English
Subjects:
arthritis
Biological and medical sciences
casuality
Cause of Death
Death Certificates
diabetes mellitus
dioxins
Epidemiologic Methods
Epidemiology
Female
General aspects
Humans
kidney diseases
Male
Medical sciences
Methodology
Mortality - trends
National Institute for Occupational Safety and Health (U.S.)
National Institutes of Health (U.S.)
Public health. Hygiene
Public health. Hygiene-occupational medicine
sillica
United States
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Summary:The authors have created US mortality rates (age, sex, race, and calendar-time specific) and proportions, using multiple cause-of-death data, for the years 1960–1989. Multiple cause-of-death data include the usual underlying cause of death from the death certificate as well as contributory causes and other significant conditions. US multiple-cause rates and proportions enable the user to calculate the expected occurrences of disease on the death certificates of a cohort under study. There is an average of 2.66 causes and/or contributory conditions listed on US death certificates, increasing over time from 2.54 in the 1960s to 2.76 in the 1980s. The ratio of multiple-cause listings to underlying cause listings varies by disease, from low ratios for cancers to high ratios for diseases such as diabetes, arthritis, prostate disease, hypertension, pneumoconiosis, and renal disease. Use of these data is illustrated with two cohorts. Multiple-cause analysis (but not underlying cause analysis) revealed twofold significant excesses of renal disease and arthritis among granite cutters. For workers exposed to dioxin, neither multiple-cause nor underlying cause analysis indicated any excess of diabetes, an outcome of a priori interest. Good candidates for multiple-cause analysis are diseases that are of long duration, not necessarily fatal, yet serious enough to be listed on the death certificate.
ISSN:0002-9262
1476-6256
DOI:10.1093/aje/136.7.855