In a recent study published in the Journal of the American Heart Association, a group of researchers examined trends in substance use (SU) and mortality related to cardiovascular disease (CVD) in the United States (USA) using data from the Centers for Disease Control and Prevention (CDC).
In the USA, SU- and CVD-related mortality increased significantly from 1999 to 2019. This increase showed distinct differences among various groups, particularly women, younger people, non-Hispanic American Indians or Alaska Natives, residents of non-urban areas, and consumers of cannabis and psychostimulants experienced a more significant increase in SU- and CVD-related mortality.
Clinically, this underscores the importance of identifying high-risk groups and addressing them with preventive strategies to reduce SU- and CVD-related mortality. Further research is essential to understand the underlying causes of the increasing trends in SU- and CVD-related mortality and to develop targeted interventions for the most affected groups.
About the Study
In this study, researchers used the CDC Wide-Ranging Online Data for Epidemiological Research (WONDER) database to extract relevant data. The database provided access to publicly available multiple-cause-of-death files, which were the primary source for identifying deaths where both SU and CVD were mentioned as contributing or underlying causes.
To identify patients, the researchers used the ICD-10-CM codes (International Classification of Diseases Tenth Revision Clinical Modification). These codes were used to categorize patients into those with SU and those with CVD. Patients with SU were identified based on specific ICD-10-CM codes listed in supplementary files, while patients with CVD were identified using the ICD-10-CM codes I00–I99, representing diseases of the circulatory system.
The study focused on patients aged 25 and older. A notable aspect of the methodology was the exclusion of smoking or tobacco use as a form of SU from the primary analyses. Additionally, if a patient’s death certificate listed multiple SUs, they were counted only once for SU-related deaths. However, for the subgroup analysis by drug category, each drug category listed on the death certificate was considered separately.
The study included ICD codes related to intentional substance overdoses but excluded those related to accidental or assaultive substance use. Since the CDC WONDER database consists of publicly available and anonymized data, the researchers did not obtain Institutional Review Board approval. Furthermore, the nature of the publicly accessible data negated the requirement for informed consent.
The current analysis included an examination of the population size and location of these deaths, categorized into various areas such as medical facilities, homes, hospices, and nursing homes.
Demographic data such as gender, ethnic background, race, age, and regional information, including urban-rural and state-level classifications, were also extracted. Races and ethnicities were categorized into non-Hispanic Whites, non-Hispanic Blacks, American Indians or Alaska Natives, Hispanics, and non-Hispanic Asians or Pacific Islanders.
Age groups were defined in five categories from 25 to 85 years and older. However, due to limitations of the CDC WONDER database, adults aged 18 to 24 years were not included in the analysis. For the urban-rural classification, the National Center for Health Statistics‘ 2013 urban-rural classification scheme was used.
The study calculated both crude and age-adjusted mortality rates (AAMRs) per 100,000 population. Crude mortality rates were determined by dividing the number of SU+CVD-related deaths by the US population for that year.
The researchers used the National Cancer Institute’s Joinpoint Regression Program to identify trends in AAMR over time. This program analyzes the annual percent change (APC) by fitting a series of straight lines on a logarithmic scale to the data, identifying significant trend shifts. For this 21-year study, a maximum of three inflection points were identified.
The calculation of APCs included their 95% confidence intervals (CIs) using the Monte Carlo permutation test. The average APCs (AAPCs) and corresponding 95% CIs were provided as a summary of mortality trends for the entire study period. Based on the slope of mortality change, these APCs were assumed to increase or decrease, with statistical significance derived from non-overlapping CIs.
This comprehensive approach allowed for a detailed examination of temporal trends in SU+CVD-related mortality in the USA and shed light on the changing patterns and demographic characteristics of these deaths over two decades. The use of both crude and age-adjusted rates, as well as sophisticated statistical methods, provided a better understanding of these trends and their impacts.
The analysis of SU- and CVD-related trends in the United States from 1999 to 2019 reveals significant findings. Despite the overall decline in CVD mortality, SU+CVD-related mortality saw an average annual increase of 4%. The highest AAMRs were observed in men, American Indian or Alaska Native individuals, individuals aged 55 to 69, and non-urban areas. In 2019, alcohol, opioids, stimulants, and cocaine were the primary causes of these deaths.
The increase in SU+CVD-related mortality was significantly higher in women, younger individuals, non-urban areas, and stimulant consumers, with a distinct acceleration since 2012. Alcohol was the most common substance associated with these deaths, followed by opioids. While cannabis had the lowest absolute AAMR, its annual percentage change increased significantly, possibly due to changing legalization and higher potency.
The consumption of stimulants, especially methamphetamines, associated with significant cardiotoxicity, emerged as a rapidly growing cause of mortality from cardiovascular diseases. The study highlights gender-specific differences in SU+CVD mortality and underscores significant racial differences, with American Indian or Alaska Native individuals showing the highest absolute AAMRs. These differences underscore the need for targeted efforts to understand and mitigate the causes of these trends in high-risk groups.