Understanding the Coronary Heart Disease Versus Total Cardiovascular Mortality Paradox: A Method to Enhance the Comparability of Cardiovascular Death Statistics in the United States
Abstract
Background— Coronary heart disease (CHD) represents the largest share of cardiovascular disease in the United States, but there are conspicuous discrepancies between CHD and total cardiovascular death rates across the states, possibly due in part to variations in physician assignment of causes of death. Our aim was to identify exogenous individual- and community-level predictors of cause-of-death assignment and variability and to use these predictors to improve the comparability of CHD mortality estimates across states. Methods and Results— We performed a multinomial logistic regression analysis to estimate the effect of individual- and community-level factors on the likelihood of a death being certified as 1 of 3 ill-defined clusters (general atherosclerosis and unspecified heart disease, heart failure, and cardiac arrest) relative to being certified as CHD. The individual-level variables were the decedent’s race, sex, age, education, and place of death; the community-level variable was the number of cardiologists per capita. We used the model to estimate state-level CHD rates that are standardized with regard to the levels of individual- and community-level determinants of cause-of-death assignment. Decedents who died in hospitals and in counties with more cardiologists per capita were more likely to be assigned to CHD than to the ill-defined categories, as were white males relative to other race-sex combinations. Adjustment for these factors resulted in substantially improved correlation between death rates for CHD and all cardiovascular causes. Increases in CHD death rates across states after adjustment for external predictors of cause-of-death assignment ranged from 2% (North Dakota) to 72% (Washington, DC); New York had a decrease (1%) in CHD death rates after adjustment. Nationally, CHD death rates increased 10% for males and 15% for females. The total number of deaths in 2001 attributed to CHD in patients over 30 years of age rose from 433 625 to 489 836 after adjustment. Conclusions— Greater presence of medical knowledge at the time of death, reflected by place of death and cardiologists per capita, reduces the use of the ill-defined cardiovascular clusters. Racial and gender effects on CHD assignment may reflect disparities in access to care and quality of care. By adjusting for differentials in these parameters, a comparable and consistent set of CHD mortality estimates can be created. The role of the exogenous predictors in validity and comparability of cause-of-death statistics should be confirmed in carefully designed validation autopsy studies.
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Even for medically certified deaths, comparability of findings on leading causes is affected by variation in certification skills, diagnostic and pathological data, medical culture in choosing the underlying cause, and legal and institutional frameworks for mortality reporting.
“Even for these deaths, the comparability of findings on the leading causes of death is affected by variation in certification skills among physicians, the diagnostic and pathological data available at the time of completing a death certificate, variations in medical culture in choosing the underlying cause, and legal and institutional frameworks for governing mortality reporting.1–5”
From Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. (2012) · cites this paper as [1]
The Clinical Perspective (p. 2081) identifies differences in clinical information, certificate-completer skills, and regional cause-of-death practices as factors that can undermine comparability. The paper addresses cardiovascular deaths specifically; the cited passages do not establish the broader claim about leading causes of death or identify legal and institutional reporting frameworks as a factor. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe analysis adjusted for incomparability in cause-of-death assignment using previously described methods.
“We adjusted for incomparability in cause of death assignment using previously described methods [22],[23].”
From The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors (2009) · cites this paper as [22]
The validity and comparability of US cause-of-death statistics may be affected at the time of medical certification, especially for cardiovascular causes and diabetes.
“Although the US has automated (computerized) assignment of an International Classification of Diseases (ICD) code for the underlying cause of death, the validity and comparability of cause of death statistics may be affected at the time of medical certification, especially for cardiovascular causes and diabetes [22]–[24].”
From The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors (2009) · cites this paper as [22]
After adjustment for comparability of cause-of-death assignment, the four most common causes of death were ischemic heart disease (434,000 deaths), lung cancer (163,000 deaths), stroke (150,000 deaths), and chronic obstructive pulmonary diseases (124,000 deaths).
“After adjustment for comparability of cause-of-death assignment [22],[23], the four most common causes of death were IHD (434,000 deaths), lung cancer (163,000 deaths), stroke (150,000 deaths), and chronic obstructive pulmonary diseases (124,000 deaths).”
From The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors (2009) · cites this paper as [22]
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References 26 · Cited by 62
Research works printed but not linked: 2
- [21]21. Murray CJL, Lopez AD. Estimating causes of death: new methods and global and regional applications. In: Murray CJL, Lopez AD, eds. The Global Burden of Disease. Cambridge, Mass: Harvard School of Public Health (on behalf of the World Health Organization and the World Bank); 1996.
- [24]24. Stata Corporation. Stata Base Reference Manual. College Station, Tex: Stata Press; 2005.
- Authors
- Murray, C. J. L., Kulkarni, S. C., & Ezzati, M.
- Affiliations
- Harvard University (US)
- Venue
- Circulation
- Published
- 2006-05-02
- Volume
- 113
- Issue
- 17
- Pages
- 2071-2081
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2084970194
- Semantic Scholar
- c7609bd07a499e355c7f959c82916b3ff44aac89
- Cited by
- 62
- References
- 26
- Citations by year
- 2025: 1 · 2022: 1 · 2021: 7 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 4 · 2016: 2 · 2015: 2 · 2014: 5 · 2013: 1 · 2012: 8
- FWCI
- 2.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Centers for Disease Control and Prevention
- U.S. Public Health Service (U36 CCU300430-23)
- National Institute on Aging (P01 AG17625, P01AG017625)
- Topics
- Health Sciences › Medicine › Epidemiology › Healthcare Systems and Public Health
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- coronary heart disease mortality, cause of death assignment, cardiovascular mortality, place of death, in-hospital mortality, racial disparities, sex differences, health care access, quality of care
- MeSH terms
- Cardiovascular Diseases, Cause of Death, Coronary Disease, Humans, Regression Analysis, Risk, United States, Logistic Models
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