In a recent study published in Journal of the American Heart Association, a group of researchers evaluated trends in substance use(SU) and cardiovascular disease(CVD)-related mortality in the United States (U.S.) using Centers for Disease Control and Prevention (CDC) data.

Background 

In the U.S. from 1999 to 2019, SU and CVD related mortality have significantly increased. This rise shows notable variations among different groups. Particularly, women, younger people, non-Hispanic (NH) American Indian or Alaska Native individuals, residents of nonmetropolitan areas, and users of cannabis and psychostimulants experienced sharper increases in SU and CVD mortality.

Clinically, this highlights the importance of identifying and targeting high-risk groups with preventive strategies to mitigate SU and CVD 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, the researchers utilized the CDC Wide-Ranging Online Data for Epidemiologic Research (WONDER) database to extract relevant data. The database provided access to Multiple Cause-of-Death Public Use record death certificates, which were the primary source for identifying deaths where both SU and CVD were mentioned as contributing or underlying causes.

For the identification of patients, the researchers employed the International Classification of Diseases Tenth Revision Clinical Modification (ICD-10-CM) codes. These codes were utilized to categorize patients into those with SU and those with CVD. Patients with SU were identified using specific ICD-10-CM codes listed in supplementary files, while those with CVD were identified using ICD-10-CM codes I00-I99, which represent diseases of the circulatory system. 

The study focused on patients aged 25 years and older. One notable aspect of the methodology was the exclusion of smoking or tobacco use from the primary analyses as a form of SU. Additionally, if a patient had multiple SUs listed on their death certificate, they were only counted once for SU-related death. However, for 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 pertaining to accidental or assault-related substance use. As the CDC WONDER database consists of publicly available and anonymized data, the researchers did not seek Institutional Review Board approval. Furthermore, the nature of the publicly available data negated the requirement for informed consent. 

Study results 

The present analysis involved examining the population size and location of these deaths, which were categorized into various settings like medical facilities, homes, hospices, and nursing homes.

Demographic data such as sex, ethnicity, race, age, and regional information, including urban-rural and state classifications, were also extracted. Races and ethnicities were categorized into NH White, NH Black, Native American or Alaska Native, Hispanic, and NH Asian or Pacific Islander.

Age groups were defined in five categories ranging from 25 to 85 and above years. However, due to the CDC WONDER database’s limitations, adults aged 18 to 24 were not included in the analysis. For urban-rural classifications, the 2013 National Center for Health Statistics 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 U.S. population for that year.

The researchers used the Joinpoint Regression Program from the National Cancer Institute to identify trends in AAMR over time. This program analyzes annual percent change (APC) by fitting a series of straight lines on a log scale to the data, identifying significant shifts in trends. For this study, which spanned 21 years, 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 reported as a summary of the mortality trend for the entire study period. These APCs were considered to be increasing or decreasing based on the slope of the mortality change, with statistical significance inferred from non-overlapping CIs.

This comprehensive approach enabled a detailed examination of the temporal trends in SU+CVD-related mortality in the U.S., shedding light on the changing patterns and demographics of these deaths over two decades. The use of both crude and age-adjusted rates, alongside sophisticated statistical methods, provided a better understanding of these trends and their implications.

Conclusions

The analysis of SU and CVD trends in the United States from 1999 to 2019 reveals significant findings. Despite overall CVD mortality reduction, SU+CVD-related mortality saw an average annual increase of 4%. The highest AAMRs were in men, American Indian or Alaska Native individuals, those aged 55-69, and nonmetropolitan areas. In 2019, the leading substances contributing to these deaths were alcohol, opioids, stimulants, and cocaine.

The increase in SU+CVD mortality was notably higher in women, younger individuals, nonmetropolitan areas, and stimulant users, with a marked acceleration since 2012. Alcohol was the most common substance associated with these deaths, followed by opioids. While cannabis showed the lowest absolute AAMR, its annual percent change increased significantly, possibly due to changing legalization and higher potency.

Stimulant use, especially methamphetamines, linked with significant cardiotoxicity, emerged as a rapidly growing contributor to CVD mortality. The study highlights gender differences in SU+CVD mortality and underlines substantial racial disparities, with American Indian or Alaska Native individuals experiencing the highest absolute AAMRs. These disparities emphasize the need for targeted efforts to understand and mitigate the causes of these trends in high-risk groups.