Increasing prevalence rates of modifiable risk factors in relatively young patients hospitalized for AMI

Modifiable Risk Factors in Young Adults With First Myocardial Infarction

Literature - Yandrapalli S, Nabors C, Goyal A et al. - JACC 2019;73(5):573-84

Introduction and methods

Important modifiable risk factors (RFs) for the development of an acute myocardial infarction (AMI) are hypertension, dyslipidemia, smoking, obesity, and diabetes mellitus (DM) [1-5]. Data have shown high prevalence rates of at least one of these RFs during a first or any episode of AMI [1,4,6]. Prevalence rates of these RFs are actually increasing in those experiencing an AMI [7,8]. Baseline RF profiles are dependent on sex and race [9-13]. Epidemiological data are an important basis for the implementation of primary and secondary preventive strategies to reduce the burden of chronic heart disease in appropriate patient populations.

However, few studies have focused on recent temporal trends in the prevalence of these RFs during a first AMI in younger patients. Preventive measures may be particularly effective in this population.

This retrospective cohort study therefore determined the overall prevalence, race and sex differences, and respective temporal trends of modifiable atherosclerotic RFs in 1.462.168 U.S. adults aged 18-59 years with hospitalizations for AMI, using data from the U.S. Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) (2005-2015). Patients were divided into two age groups based on age at first AMI: 18-44 years (19.2%; younger patients) and 45-59 years (80.8%; older patients). Race was categorized as white, black, Hispanic, or Asian/Pacific Islander. RFs were current or prior smoker, dyslipidemia, DM, hypertension, and obesity.

Primary outcomes were the overall prevalence of the RFs in the age subgroups, sex and race differences in RF prevalence, and respective temporal trends during the study period.

Main results

Age and prevalence of modifiable RFs during a first AMI

  • In younger patients, smoking (56.8%), dyslipidemia (51.7%) and hypertension (49.8%) were the most prevalent RFs, and 90.3% of these patients had at least one RF. Obesity and DM were observed in 20.7% and 22.6% of patients, respectively.
  • In older patients, hypertension (59.8%), dyslipidemia (57.5%) and smoking (51.9%) were the most prevalent RFs and 92% of these patients had at least one RF. DM was present in 28.5% of patients, and obesity in 17.1% of cases.

Sex and race differences in the prevalence of modifiable RFs during a first AMI

  • In both age groups, differences were seen in prevalences of the modifiable RFs between men and women, and between different races. See article for details.

Temporal trends in the prevalence of modifiable RFs during a first AMI

  • In 2015, prevalences of all six modifiable RFs were increased in both younger and older patients (P-trend<0.001 for each RF), compared with in 2005. Higher prevalences were observed in the older patient group. In the younger age group, rates of hypertension, smoking, DM and obesity increased the most, and in older patients hypertension and obesity.
  • The greatest relative observed increase in prevalence rate between 2005 and 2015 was found for obesity in both the younger group and older patient group (98% and 73%, respectively).
  • Regardless of age, the prevalence rate of dyslipidemia increased through 2012 and 2013 (~50% to 58%), and then gradually decreased in 2015 (to ~55%) in both men and women.
  • In older patients, the rate difference between men and women became smaller for hypertension (from 6.1% to 1.9%, higher in women), and smoking (from 5.8% to 0.9%, higher in men) during the study period.
Increasing prevalence rates of modifiable risk factors in relatively young patients hospitalized for AMI

Conclusion

In this retrospective cohort study, major modifiable atherosclerotic RFs were highly prevalent among younger (aged 18-44 years) U.S. patients hospitalized for a first AMI. Over 90% of patients had at least one such RF. Significant sex and racial differences were seen for individual RFs. Prevalence rates of RFs progressively increased between 2005 and 2015, except for dyslipidemia, which increased through 2012 and 2013 and then gradually decreased until in 2015. These data can help to reduce the burden of chronic heart disease by planning appropriate preventive strategies in specific patient populations.

Editorial comment

In her editorial comment [14], Safdar stresses the need for discovering clues that could guide a clinician to quickly identify an AMI when evaluating younger patients. A lower suspicion for AMI, atypical presentation and the fact that noncardiac causes of chest pain are more common in younger adults, may cause a delay in diagnosis.

She discusses lessons learned from the current study that are comparable with those found in the INTERHEART study. Both studies showed sex-risk attribution of modifiable risk factors for AMI. Hypertension, diabetes and obesity contribute to a higher risk for AMI in women, whereas smoking and dyslipidemia increased risk for AMI in men. These findings indicate that ‘consideration of these nuances could help the clinician to better risk-stratify young patients presenting with angina-equivalent symptoms’. Also, she highlights the need for better screening for AMI risk in younger patients who are often undertreated due to underestimates in standard risk stratification scores, especially in women. Young patients without a prior history of AMI are more likely to present at the time of their first AMI to a generalist rather than a cardiologist and widespread dissemination of sex-specific clues for consideration in patients with angina-equivalent symptoms is therefore critically.

Safdar emphasizes that it remains unknown whether risk factors are differentially linked with different phenotypes of AMI, and if their mitigation has a variable effect on primary and secondary prevention of these AMI or related outcomes. The author concludes: ‘AMI in the young is no longer a needle in the haystack, although it may present in different forms and needs newer lenses. And thus, to serve these patients better, we need to think beyond the traditional models of AMI and our search must continue for all causes of coronary ischemia.’

References

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11. Hutchinson RG, Watson RL, Davis CE, et al. Racial differences in risk factors for atherosclerosis: the ARIC study. Angiology 1997;48: 279–90.

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13. Jones DW, Chambless LE, Folsom AR, et al. Risk factors for coronary heart disease in African Americans: the Atherosclerosis Risk in Communities study, 1987-1997. Arch Intern Med 2002; 162:2565–71.

14. Safdar B. Clues to diagnose myocardial infarction in the young. JACC 2019;73(5):585-8.

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