Socioeconomic deprivation and prognostic outcomes in acute coronary syndrome: A meta-analysis using multidimensional socioeconomic status indices

https://doi.org/10.1016/j.ijcard.2023.04.042Get rights and content

Highlights

  • Socioeconomic deprivation affects Acute Coronary Syndrome (ACS) outcomes and quality of care received.

  • The low SES group had significantly higher risk of all-cause mortality and lower rates of coronary revascularisation.

  • There was a disproportionately higher number of females and individuals with diabetes in the low SES group.

  • There are statistically significant differences in the results drawn based on the socioeconomic index used.

Abstract

Background

Low socioeconomic status (SES) is an important prognosticator amongst patients with acute coronary syndrome (ACS). This paper analysed the effects of SES on ACS outcomes.

Methods

Medline and Embase were searched for articles reporting outcomes of ACS patients stratified by SES using a multidimensional index, comprising at least 2 of the following components: Income, Education and Employment. A comparative meta-analysis was conducted using random-effects models to estimate the risk ratio of all-cause mortality in low SES vs high SES populations, stratified according to geographical region, study year, follow-up duration and SES index.

Results

A total of 29 studies comprising of 301,340 individuals were included, of whom 43.7% were classified as low SES. While patients of both SES groups had similar cardiovascular risk profiles, ACS patients of low SES had significantly higher risk of all-cause mortality (adjusted HR:1.19, 95%CI: 1.10–1.1.29, p < 0.001) compared to patients of high SES, with higher 1-year mortality (RR:1.08, 95%CI:1.03–1.13, p = 0.0057) but not 30-day mortality (RR:1.07, 95%CI:0.98–1.16, p = 0.1003). Despite having similar rates of ST-elevation myocardial infarction and non-ST-elevation ACS, individuals with low SES had lower rates of coronary revascularisation (RR:0.95, 95%CI:0.91–0.99, p = 0.0115) and had higher cerebrovascular accident risk (RR:1.25, 95%CI:1.01–1.55, p = 0.0469). Excess mortality risk was independent of region (p = 0.2636), study year (p = 0.7271) and duration of follow-up (p = 0.0604) but was dependent on the SES index used (p < 0.0001).

Conclusion

Low SES is associated with increased mortality post-ACS, with suboptimal coronary revascularisation rates compared to those of high SES. Concerted efforts are needed to address the global ACS-related socioeconomic inequity.

Registration and protocol

The current study was registered with PROSPERO, ID: CRD42022347987.

Introduction

Acute coronary syndrome (ACS) is one of the leading causes of death worldwide, accounting for approximately one in six deaths [1,2]. This public health concern has prompted urgent global efforts in tackling traditional cardiovascular risk factors for both the primary and secondary prevention of ACS [3,4]. Beyond addressing conventional biological risk factors, increasing evidence have demonstrated that social determinants of health such as socioeconomic deprivation, play an important role as a non-traditional risk factor affecting post-ACS outcomes, quality of care received and treatment adherence [5]. The World Health Organization (WHO) states that socioeconomic deprivation, often measured by socioeconomic status (SES) [6], contributes heavily to inequitable but avoidable differences in health outcomes worldwide [7]. Patients with low SES have been reported to bear higher burden of cardiovascular risk factors, with more severe presentation of cardiovascular diseases [8,9]. Previous meta-analyses [10,11] have also elucidated higher risks of post-ACS mortality and suboptimal medical care in patients with low SES.

Considering the vast attention on the primary and secondary prevention of ACS in present clinical practice guidelines, our study addresses the current gap in the literature beyond the biological underpinnings of ACS by providing comprehensive analysis on the association between SES and post-ACS survival, its complications and the provision of guideline-directed interventions [8,9,12]. Despite previous meta-analyses [10,11], there remains a paucity of data on the effects of SES on ACS survival based on geographical regions, socioeconomic deprivation indices used, as well as trends of mortality differences across time. Moreover, the included studies of previous meta-analyses used unidimensional indices of socioeconomic parameters which may not holistically encompass the major indicator components of socioeconomic deprivation [10,11] as recommended by the American Psychological Association [13]. As such, with a stricter inclusion criterion of articles adopting multidimensional socioeconomic indices, our study aims to add to the existing evidence with comprehensive evaluations of the impact of socioeconomic deprivation, as well as additional analysis highlighting the differences in the effects of the SES gap across various regions, timelines, and socioeconomic indices. These unique perspectives on the differential effect of SES can help inform stakeholders in designing effective strategies when addressing socioeconomic inequity as a non-traditional risk factor in ACS.

Section snippets

Search strategy

This paper was conducted in accordance with the Preferred Reporting Items for Systemic Reviews and Meta-Analyses guidelines [14] (Fig. 1). Medline and Embase were searched for articles reporting outcomes of ACS patients stratified by socioeconomic status until 1 July 2022. Key search terms such as “acute coronary syndrome”, “socioeconomic deprivation”, “socioeconomic status”, “index”, and a quantitative filter were used. Articles were retrieved and duplicates were removed using EndNote 20. The

Summary of included studies

Our initial search strategy yielded a total of 5092 articles, of which 1121 duplicates were removed. A total of 3500 studies were excluded after title and abstract sieve, with 471 studies selected for full text review. A total of 29 ACS studies were then included in this meta-analysis (Fig. 1). By region, the articles were from Europe (n = 14) [16,18,20,23,25,[37], [38], [39], [40], [41], [42], [43], [44], [45]], Oceania (n = 5) [5,15,19,21,46], Asia (n = 5) [17,[47], [48], [49], [50]] and

Discussion

Established risk classifications tools for ACS such as GRACE [53] and TIMI [54], utilise conventional cardiac risk factors to guide the management of ACS [[55], [56], [57]]; however they fail to account for important socioeconomic factors that have been closely linked with poorer survival in patients with ACS [12]. The present meta-analysis extensively examines comparative data of ACS outcomes across SES groups over the past two decades. Our findings highlight that ACS patients with low SES

Conclusion

Despite similar cardiovascular risk profiles, individuals of low SES received lower rates of coronary revascularisation and had higher mortality rates following ACS compared to those of high SES. The socioeconomic gap in ACS care is a global health concern, that has become more evident in the past decade, with worrisome trends of unfavourable survival in the low SES population likely to persist in the coming years. The unified goal in addressing ACS-related socioeconomic inequity deserves its

Funding sources

None.

CRediT authorship contribution statement

Vickram Vijay Anand: Conceptualization, Formal analysis, Data curation, Writing – original draft, Writing – review & editing, Visualization. Ethan Lee Cheng Zhe: Conceptualization, Formal analysis, Data curation, Writing – original draft, Writing – review & editing, Visualization. Yip Han Chin: Conceptualization, Formal analysis, Validation, Data curation, Writing – original draft, Writing – review & editing, Visualization. Rachel Sze Jen Goh: Conceptualization, Writing – original draft,

Declaration of Competing Interest

The authors report no relationships that could be construed as a conflict of interest.

Acknowledgements

All authors have made substantial contributions to all the following: (1) the conception and design of the study, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. No writing assistance was obtained in the preparation of the manuscript. The manuscript, including related data, figures and tables has not been previously published and the

References (82)

  • A. Koren et al.

    Israel study group on first acute myocardial I. socioeconomic environment and recurrent coronary events after initial myocardial infarction

    Ann. Epidemiol.

    (2012)
  • C. Blais et al.

    Impact of socioeconomic deprivation and area of residence on access to coronary revascularization and mortality after a first acute myocardial infarction in Quebec

    Canad. J. Cardiol.

    (2012)
  • G. Kong et al.

    Higher mortality in acute coronary syndrome patients without standard modifiable risk factors: results from a global meta-analysis of 1,285,722 patients

    Int. J. Cardiol.

    (2023)
  • N.W.S. Chew et al.

    Meta-analysis of percutaneous coronary intervention versus coronary artery bypass grafting for left Main narrowing

    Am. J. Cardiol.

    (2022)
  • N.W.S. Chew et al.

    Long-term prognosis of acute myocardial infarction associated with&#xa0;metabolic health and obesity status

    Endocr. Pract.

    (2022)
  • S. Poon et al.

    Bridging the gender gap: insights from a contemporary analysis of sex-related differences in the treatment and outcomes of patients with acute coronary syndromes

    Am. Heart J.

    (2012)
  • P. Matthew et al.

    Income inequality and health outcomes in the United States: an empirical analysis

    Soc. Sci. J.

    (2018)
  • S.L. Dickman et al.

    Inequality and the health-care system in the USA

    Lancet

    (2017)
  • N.W.S. Chew et al.

    FIB-4 predicts MACE and cardiovascular mortality in patients with nonalcoholic fatty liver disease

    Can. J. Cardiol.

    (2022)
  • E.J. Benjamin et al.

    Heart disease and stroke statistics&#x2014;2017 update: a report from the American Heart Association

    Circulation.

    (2017)
  • D. Mozaffarian et al.

    Executive summary: heart disease and stroke statistics—2016 update

    Circulation.

    (2016)
  • J.Z.K. Toh et al.

    A Meta-analysis on the global prevalence, risk factors and screening of coronary heart disease in nonalcoholic fatty liver disease

    Clin. Gastroenterol. Hepatol.

    (2021)
  • J. Dirksen et al.

    Exploring the potential for a new measure of socioeconomic deprivation status to monitor health inequality

    Int. J. Equity Health

    (2022)
  • Organization WH

    Social Determinants of Health

    (2022)
  • D. Alter et al.

    Influence of education and income on atherogenic risk factor profiles among patients hospitalized with acute myocardial infarction

    Canad. J. Cardiol.

    (2004)
  • K.K. Hyun et al.

    The effect of socioeconomic disadvantage on prescription of guideline-recommended medications for patients with acute coronary syndrome: systematic review and meta-analysis

    Int. J. Equity Health

    (2017)
  • Association AP

    Measuring Socioeconomic Status and Subjective Social Status

    (2015)
  • M.J. Page et al.

    The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

    BMJ

    (2021)
  • S. Biswas et al.

    Impact of socioeconomic status on clinical outcomes in patients with ST-segment-elevation myocardial infarction

    Circ. Cardiovasc. Qual. Outcomes.

    (2019)
  • J. Schmucker et al.

    Socially disadvantaged city districts show a higher incidence of acute ST-elevation myocardial infarctions with elevated cardiovascular risk factors and worse prognosis

    BMC Cardiovasc. Disord.

    (2017)
  • L.W. Evans et al.

    Impact of service redesign on the socioeconomic inequity in revascularisation rates for patients with acute myocardial infarction: a natural experiment and electronic record-linked cohort study

    BMJ Open

    (2016)
  • R.J. Korda et al.

    Universal health care no guarantee of equity: comparison of socioeconomic inequalities in the receipt of coronary procedures in patients with acute myocardial infarction and angina

    BMC Public Health

    (2009)
  • M.C. MacLeod et al.

    Geographic, demographic, and socioeconomic variations in the investigation and management of coronary heart disease in Scotland

    Heart

    (1999)
  • J.I. Morton et al.

    Treatment gaps, 1-year readmission and mortality following myocardial infarction by diabetes status, sex and socioeconomic disadvantage

    J. Epidemiol. Community Health

    (2022)
  • L. Nobel et al.

    Neighborhood socioeconomic status predicts health after hospitalization for acute coronary syndromes: findings from TRACE-CORE (transitions, risks, and actions in coronary events-Center for Outcomes Research and Education)

    Med. Care

    (2017)
  • S. Picciotto et al.

    Associations of area based deprivation status and individual educational attainment with incidence, treatment, and prognosis of first coronary event in Rome, Italy

    J. Epidemiol. Community Health

    (2006)
  • K.L. Tang et al.

    An exploration of the subjective social status construct in patients with acute coronary syndrome

    BMC Cardiovasc. Disord.

    (2018)
  • H. Tizon-Marcos et al.

    Socioeconomic status and prognosis of patients with ST-elevation myocardial infarction managed by the emergency-intervention “Codi IAM” network

    Front. Cardiovasc. Med.

    (2022)
  • J.A. Udell et al.

    Neighborhood socioeconomic disadvantage and care after myocardial infarction in the National Cardiovascular Data Registry

    Circ. Cardiovasc. Qual. Outcomes.

    (2018)
  • J.-P. Collet et al.

    2020 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: The task force for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC)

    Eur. Heart J.

    (2020)
  • X. Wan et al.

    Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

    BMC Med. Res. Methodol.

    (2014)
  • Cited by (4)

    1

    These authors contributed equally as co-first authors.

    2

    These 2 authors supervised the work equally as senior authors.

    View full text