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. 2024 Mar-Apr;20(2):61–73. doi: 10.48305/arya.2024.42327.2930

The prevalence of myocardial infarction in the elderly: A systematic review and meta-analysis

Fatemeh Rajati 1, Mojgan Rajati 2, Maryam Chegeni 3, Mohsen Kazeminia 4
PMCID: PMC11335027  PMID: 39170816

Abstract

BACKGROUND:

Myocardial Infarction (MI) refers to the destruction and death of cells in the myocardium of the heart. Its prevalence increases with age due to changes in the cardiovascular system. The aim of the present study was to combine, summarize, standardize, resolve inconsistencies in the results of studies, and investigate the impact of potential factors on the prevalence rate of MI in the elderly through a systematic review and meta-analysis.

METHODS:

This systematic review and meta-analysis was conducted from 1987 to March 2022. All relevant published studies were searched in PubMed, Embase, Scopus, Web of Science (WoS) databases, and Google Scholar search engine using related MeSH/Emtree and Free Text words. The heterogeneity among studies was quantified using the I2 index.

RESULTS:

In the initial search, 35453 studies were identified. After eliminating irrelevant studies, finally, 29 articles with a sample size of 3279136 subjects were included in the meta-analysis. After combining the results of the studies included in the meta-analysis, the total prevalence of MI in the elderly was estimated to be 17.6% (95% CI: 12.8 - 23.7%), 16.1% (95% CI: 11.0 - 22.8%) in males, and 12.5% (95% CI: 9.2 - 16.8%) in females. The prevalence of MI increased with the year of publication and the mean age of the elderly (P < 0.001).

CONCLUSION:

The results showed that due to the high prevalence of myocardial infarction (MI) in the elderly, it should be addressed within healthcare systems and policy makers should pay more attention to prevention of MI. However, considering the inclusion of heterogeneous studies, the pooled estimation should be interpreted with caution.

Key Words: MetaAnalysis; MI, Myocardial Infarction, Prevalence, Systematic Review

Introduction

One of the significant demographic phenomena of the 21st century is population aging1, an inevitable event in human life. Addressing the issues, problems, and needs of this stage is a social necessity2. According to the World Health Organization (WHO), individuals over the age of 60 are considered elderly, and a large percentage of this population resides in developing countries3. The elderly population is on the rise due to improvements in health status, a phenomenon known as the demographic revolution4. The WHO estimates that the number of elderly individuals will exceed 1.5 billion by 20505.

Aging is a life stage associated with decreased physical function, mobility limitations, increased health problems, chronic diseases, and dependency on others5. It also involves physical changes, such as cardiovascular disease, and psychological changes, such as anxiety and depression6,7. These problems can negatively impact the lives of the elderly8.

Cardiovascular diseases (CVDs) are among the most common chronic diseases and leading causes of death worldwide9. Among ischemic heart diseases, MI is one of the most prevalent and dangerous diseases in industrialized countries10. MI refers to the permanent and irreversible cell death in a portion of the heart muscle (myocardium), which occurs due to the cessation of blood flow and severe ischemia in the myocardium.

The cessation of blood flow can occur suddenly and without any preceding symptoms, or following several angina attacks (chest pain). The absence of myocardial blood flow (MBF) for an extended period, due to the occlusion (blockage) of the coronary arteries, results in MI11. The disruption of blood flow leads to an inadequate oxygen supply to the heart muscle, causing death (necrosis) of the heart muscle12. MI is typically the result of gradual plaque buildup (atherosclerosis) and clot formation associated with atherosclerosis within a vein11.

Heart diseases in middle-aged individuals often begin with a symptom, grow slowly, and eventually become severe13. In fact, the cardiovascular system undergoes irreversible changes, such as increased thickness and stenosis of arteries, with age. As a result of these changes, the heart is forced to pump blood with greater intensity and pressure, leading to a gradual increase in the individual’s blood pressure. This ultimately results in impaired heart rate and the development of heart failure or MI14,15. Approximately, 83% of patients who die from MI are elderly16.

Several primary studies on the prevalence of MI in the elderly have been conducted in various parts of the world in recent years. However, these studies have examined the prevalence rate in a limited area with a small sample size. Moreover, none of the studies investigated the effect of potential factors, such as the year of publication, sample size, mean age, and gender of the elderly, and did not report the prevalence by different continents. Furthermore, large differences in the reported prevalence rate are observed in their results. Therefore, it appears necessary to conduct a systematic review and meta-analysis study to combine, summarize, standardize, and resolve inconsistencies in the results of the studies and investigate the effect of potential factors on the prevalence rate. Consequently, the present study aimed to estimate the prevalence of MI in the elderly by systematic review and meta-analysis.

Methods

Search strategy

The current systematic review and meta-analysis were conducted based on the guidelines of PRISMA 2020 (http://www.prisma-statement.org/), which includes identification, screening, eligibility, and inclusion17 from 1987 to March 2022. All steps of identification, selection, and quality assessment of studies, as well as data extraction, were performed independently by two researchers (S.M and M.K) in accordance with the PRISMA guidelines. Any disagreement between the two researchers was resolved through consensus and consultation with a third researcher (F.R).

Identification of studies

A systematic literature review was conducted in the international databases of PubMed, Embase, Scopus, and Web of Science (WoS) to identify studies related to the prevalence of MI in the elderly. The searches included the combinations of the following MeSH/ Emtree and Free Text words: “Epidemiology”, “Prevalence*”, “Prevalent *”, “Myocardial Infarction”, “Myocardial Infarctions”, “Infarction, Myocardial”, “Infarctions, Myocardial”, “Cardiovascular Stroke”, “Cardiovascular Strokes”, “Stroke, Cardiovascular”, “Strokes, Cardiovascular”, “Myocardial Infarct”, “Infarct, Myocardial”, “Infarcts, Myocardial”, “Myocardial Infarcts”, “Heart Attack”, “Heart Attacks”, “Elderly”, “Old*”, “Geriat*”, “Elderlys”, “Elderlies”, and “Aged”. No time limitation were considered for the search to retrieve as comprehensive as possible relevant studies. The Google Scholar motor engine and references of all relevant articles were manually reviewed to maximize the comprehensiveness of the search.

Inclusion Criteria 

The inclusion criteria were original scientific-research studies, observational studies (cross-sectional study, cohort study, etc.), access to the full text of the article, and studies that reported the rate or frequency of MI in the elderly. If cohort studies were retrieved, the prevalence of MI was extracted from baseline data.

Exclusion Criteria 

The exclusion criteria included irrelevant studies, interventional studies (clinical trial study and field trial study), qualitative studies, case series, case reports, letters to the editor, articles presented at conferences, systematic review and meta-analysis studies, dissertations, lack of access to the full text of the article after sending an email to the corresponding author three times, and studies with duplicate and overlapping data.

Selection Process of Studies 

After identifying the search strategy for each database, all articles obtained from different databases were imported into EndNote X8 software. The studies with duplicate and overlapping data were initially eliminated. Then, the names of authors, institutes, and journals of all articles were deleted. The title and abstract of the studies were thoroughly screened to exclude irrelevant studies. The full text of the remaining articles was carefully assessed to remove the studies that did not meet the inclusion criteria. Ultimately, the quality assessment of all studies included in the systematic review and meta-analysis was conducted.

Quality assessment of the studies

The quality assessment of the studies was conducted using the Joanna Briggs Institute (JBI) checklist, a standard and well-known tool for assessing the quality of studies reporting prevalence data18. This checklist comprises nine items, including sample frame, participants, sample size, detailed description of study subjects and setting, data analysis, valid methods for identifying conditions, condition measurement, statistical analysis, and adequate response rate. The responses “Yes” for pointed, “No” for not pointed, and “Not applicable” for not reported are used for scoring. The total score range, based on the number of “Yes” responses, is between 0 and 9. Table 1 presents the results of the quality assessment of the studies included in the meta-analysis.

Table 1.

The characteristics of studies included in the systematic review and meta-analysis

First Author (Reference ) Year Country (Continent) Sample size (n) Age (year) Type of study Diagnostic tool Prevalence ) % ( Quality score
Total Male Female Total Male Female
Sheifer et al 19 2000 USA (America) 5888 2355 3533 72.1 Cross-Sectional ECG 15.3 - - 6
Rathore et al 20 2000 USA (America) 106780 53283 53497 76.8 Cross-Sectional ECG 22.1 - - 6
Aronow et al 21 1987 USA (America) 708 469 239 82±8 Cross-Sectional ECG 30.0 27.7 34.7 5
Mehta et al 22 2001 USA (America) 163140 101963 61177 ˃65 Cross-Sectional ECG 28.2 - - 5
Rathore et al 23 2001 USA (America) 3402 - - ˃65 Cross-Sectional ECG 8.3 - - 5
Lusiani et al 24 1994 Italy (Europe) 94 60 34 68.5±11.5 Retrospective ECG 32 27 36 6
O'Neal et al 25 2014 Senegal (Africa) 4608 1843 2765 ˃65 Cross-Sectional ECG 17.3 22.0 14.1 6
Brugts et al 26 2005 Netherlands (Europe) 4484 1628 2856 69.6±8.8 Cross-Sectional ECG 4.86 7.6 3.2 6
Nadelmann et al 27 1990 USA (America) 390 139 251 79±3, ˃75 Cross-Sectional ECG 8.8 - - 5
Duan et al 28 2007 USA (America) 1519086 607634 911452 76 Population-Based Cross-Sectional and Cohort Study ECG 8.8 7.3 9.9 7
Dangelser et al 29 2005 France (Europe) 1672 1256 416 79 Cross-Sectional ECG 20.45 - - 5
Barbier et al 30 2011 Sweden (Europe) 394 206 188 ˃75 Population-Based Cross-Sectional ECG 30 37 23 6
Khera et al 31 2013 USA (America) 1434579 - - ≥65 Cross-Sectional ECG 35.7 - - 5
Claussen et al 32 2014 Norway (Europe) 4092 3088 1004 ≥65 Prospective Cohort Study ECG 10.6 - - 7
Reiter et al 33 2011 Spain (Europe) 404 218 186 78 (74-82) Multi-Centre Study ECG 36 - - 6
Goch et al 34 2009 Poland (Europe) 40 25 15 81 (75-95) Cross-Sectional ECG 52.5 65 52 5
Pastori et al 35 2015 England (Europe) 3223 1812 1411 73.2±8.7 Prospectively ECG 25.1 - - 7
Sato et al 36 2020 Japan (Asia) 6596 4141 2455 ≥65 Prospective, Multicenter, and Observational Study - 8.1 - - 5
Schelbert et al 37 2012 Iceland (Europe) 936 452 484 76 (72-81) Cohort ECG 16.23 15.04 18.36 8
Maynard et al 38 2006 USA (America) 7054 6936 118 73.5±10.0 Retrospective Cohort Study ECG 11.2 - - 5
Amann et al 39 2016 Germany (Europe) 1191 678 513 79 (75-84) Observational Population-Based Study ECG 41 - - 8
DeLuca et al 40 2006 USA (America) 287 204 83 63±8 Cross-Sectional ECG 22.6 - - 5
Ahto et al 41 1998 Finland (Europe) 1196 488 708 74±7 Observational Population-Based Study ECG 9.5 14 7 7
Kim et al 42 2009 USA (America) 185 122 63 60.4±11.2 Prospective Study DE-CMR 27 - - 6
Figueroa-Triana et al 43 2021 Colombia (America) 1015 679 336 66.4±13.7 Retrospective Cohort Study ECG 38 - - 8
Kılıç et al 16 2020 Turkey (Europe) 1626 1149 477 61.5±12.5 National Multi-Center, Observational Study ECG 6.7 5.22 10.27 9
Gianfagna et al 44 2018 Italy (Europe) 3755 2391 1364 68.5±4.3 Population Based Cross-Sectional Study ECG 6.4 8.9 2.1 8
Kohn et al 45 2005 USA (America) 1633 784 621 ˃65 Retrospective Cohort Study ECG 10.7 - - 5
Sajadieh et al 46 2005 Denmark (Europe) 678 397 281 64.5±6.8 Cross-Sectional ECG 11.4 9.6 13.8 6
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Data Extraction 

Data were manually extracted from all studies included in the systematic review and meta-analysis using a pre-prepared checklist. This checklist included the name of the first author, year of publication, country and continent, sample size, age, diagnostic tools, prevalence rate, and quality assessment score.

Statistical analysis

In this study, the prevalence rate of MI in the elderly was reviewed. The rate or relative frequency of MI in each study was used to combine the results of different studies. Heterogeneity among studies was checked using the I2 index. Given the high heterogeneity between the results of the studies included in the meta-analysis (I2 > 75%), the random effects model was used. Therefore, the results of the random effects model in heterogeneous conditions are more generalizable than those of the fixed effect model.

The funnel plot and Egger’s regression intercept were employed to assess the publication bias. Furthermore, meta-regression was used to examine the relationship between the prevalence rate of MI in the elderly and sample size, the year of publication, and mean age of the elderly.

Subgroup analysis was performed based on the different continents (Asia, Africa, Europe, and America) and gender (male and female). The comprehensive meta-analysis software (version 2) was used for meta-analysis and P < 0.05 was considered statistically significant.

Results

The summary of how studies included in the meta-analysis

The systematic literature search in various databases yielded 35435 articles, and 18 articles were identified through manual searches. After removing 26351 studies with duplicate and overlapping data via EndNote, 8974 irrelevant studies were excluded by screening the title and abstract. The full text of the remaining 128 studies was carefully inspected, and 99 articles (No primary outcome= 51, Irrelevant studies= 19, Study design= 6, and Overlapping data= 23) were eliminated due to not meeting the eligibility criteria. Finally, 29 articles were included in the meta-analysis after quality assessment. The PRISMA 2020 flow diagram (Figure 1) illustrates this process.

Fig. 1.

Fig. 1

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PRISMA 2020 search flow diagram

General characteristics of the studies

The meta-analysis included a total sample size of 3279136 from all the articles. The studies spanned from 1987 to 2021, with the USA contributing the most studies (12 articles). The study with the largest sample size was conducted by Duan et al. (2007) with 1519086 subjects, while the study with the smallest sample size was by Goch et al. (2009) with 40 subjects. Most studies employed Electrocardiogram (ECG) for diagnosing MI. The characteristics and data of the studies included in the systematic review and meta-analysis are detailed in Table 1.

Meta-analysis of the prevalence of MI in elderly

Given that the I2 test for the total prevalence of MI in the elderly revealed significant heterogeneity among studies (I2 = 99.99), the data were analyzed using a random effects model. The results of Egger’s regression indicated no publication bias in the studies at the level of 0.05 (P = 0.441) (Figure 2). After combining the results of studies included in the meta-analysis, the prevalence rate of MI in the elderly was estimated to be 17.6% (95% CI: 12.8%-23.7%) based on the random effects model. As shown in Figure 3, the black square represents the prevalence rate, the length of the line segment displays the 95% CI in each study, and the rhombus symbol illustrates the total prevalence rate of MI in the elderly. The results of the sensitivity analysis demonstrated that the pooled estimation did not change significantly by removing each of the studies (Figure 4).

Fig. 2.

Fig. 2

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The Funnel plot of the results of the overall estimation of the prevalence rate of MI in the elderly

Fig. 3.

Fig. 3

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The forest plot of the overall estimation of the prevalence rate of MI in the elderly based on the random effects model

Fig. 4.

Fig. 4

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The sensitivity analysis chart of the prevalence rate of MI in the elderly

The meta-regression of the prevalence rate of MI in the elderly

The relationship between the sample size (Figure 5), year of publication (Figure 6), and mean age (Figure 7) and the prevalence of MI in the elderly was assessed using meta-regression. The results indicated a significant difference between the prevalence rate of MI in the elderly and these potential factors (P < 0.001). The prevalence of MI in the elderly decreased with an increase in sample size and increased with the year of publication and mean age (Figures 5-7).

Fig. 5.

Fig. 5

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The meta-regression of the relationship between sample size and the prevalence of MI in the elderly

Fig. 6.

Fig. 6

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The meta-regression of the relationship between the year of the publication and the prevalence of MI in the elderly

Fig. 7.

Fig. 7

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The meta-regression of the relationship between the mean age and the global prevalence of MI in the elderly

Subgroup analysis

Considering the high heterogeneity among the studies (I2 = 99.99), subgroup analysis was reported based on the different continents (Asia, Africa, Europe, and America) and gender (male and female) (Table 2). The results of the subgroup analysis illustrated that the highest prevalence rate of MI in the elderly was related to the America continent with 18.4% (95% CI: 11.4 - 28.4%) and male with 16.1% (95% CI: 11.0 - 22.8%). However, there was still a high level of heterogeneity between studies (Table 2).

Table 2.

The subgroup analysis of estimating the prevalence rate of MI in the elderly by continents and gender

Subgroups Number Studies Point estimate Lower limit Upper limit Z -value P -value P -value between I 2 (%) Tau Egger’s regression intercept
Continents Africa 1 0.173 0.162 0.184 -40.174 0.000 0.000 0.000 0.000 -
America 13 0.184 0.114 0.284 -5.168 0.000 99.99 1.033 0.607
Asia 1 0.081 0.075 0.088 -53.819 0.000 0.000 0.000 -
Europe 14 0.177 0.120 0.254 -6.545 0.000 99.24 0.869 0.875
Gender Male 12 0.161 0.110 0.228 -7.489 0.000 0.000 98.99 0.745 0.011
Female 12 0.125 0.092 0.168 -11.076 0.00 97.79 0.575 0.447
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Discussion

After combining the data obtained from 29 articles included in the meta-analysis with more than three million sample size, the present study estimated the prevalence of MI in the elderly to be 17.6% using systematic review and meta-analysis. The highest quality assessment score, based on the JBI checklist, was attributed to a Turkish study with a score of 9, which reported the prevalence of MI in the elderly as 6.7%16. This was followed by studies conducted in Colombia, the USA (38%), and Italy (6.4) with a score of 8. Given that the study conducted in Colombia was a retrospective cohort study, the results of the other two studies can provide a more accurate representation of the prevalence of myocardial infarction in the population.

Meta-analysis studies have reported that the prevalence of MI varies in different populations. This variation may be attributed to factors such as the structure of the study population, underlying and concomitant diseases, sample size, and physiological changes occurring in the cardiovascular system of individuals with aging or certain diseases. The prevalence of MI is reported to be 5.03% in pregnancy47, 1.7% in patients with multiple sclerosis48, and 34% in occluded culprit artery (OCA)49. The risk of MI is estimated to be 1.72 in patients with COPD, 1.69 in patients with rheumatoid arthritis, 1.47 in patients with gout, 1.41 in patients with psoriatic arthritis, and 1.24 in patients with ankylosing spondylitis50,51.

The results of the meta-regression indicated that the prevalence of MI increases with age. Subtle physiological changes gradually occur in the cardiovascular system with age. The aging process of the heart is associated with myocardial stiffness, due to an increase in the size of the ventricular muscle cells and a decrease in the number of these cells. Furthermore, the intercellular matrix and collagen increase, and the heart muscle becomes fibrous. These structural changes gradually lead to an increase in the thickness of the left ventricular wall52. Left Ventricular Hypertrophy (LVH) occurs in the elderly independent of concomitant hypertension. LVH is independently associated with an increased risk of coronary heart disease (CHD), sudden cardiac death, MI, and stroke53.

With age, the thickness of the arterial wall increases, primarily due to the enhancement of collagen fibers and the destruction of elastin fibers in the middle layer of vessels and its calcification54,55. As a result, vascular compliance decreases, leading to the dilation of the artery, increased pulse pressure, and increased pulse wave velocity. This condition predisposes the elderly to isolated systolic hypertension, the most common type of hypertension in this age group56. Increased intima-media thickness (IMT) is a significant indicator of the risk of atherosclerosis, and the predictive value of increased IMT for future acute cardiovascular events is equal to or greater than the classic cardiovascular risk factors57.

Based on the results of the meta-regression, the prevalence of MI in the elderly increased from 1987 to 2022. This increase can be attributed to factors such as decreased mobility and physical activity, increased obesity, depression, and diabetes in recent years58-60. Therefore, it is crucial for health officials and policymakers to implement measures to promote weight loss, increase physical activity, and prevent cardiovascular disease, depression, and diabetes.

Given the variations in population structure, culture, diet, mobility and physical activity, genetics, stress, anxiety, depression, etc. across different countries and geographical areas, a subgroup analysis was performed based on different continents. Although the number of studies conducted in Asia was limited, the lowest prevalence rate of MI was reported in the elderly Asian population. This could be attributed to factors such as the traditional Asian diet (TAD) 61, and lower rates of depression in the elderly58, among others.

The results of the subgroup analysis revealed that the prevalence of MI is higher in men than in women. Men are exposed to MI much earlier than women during their lifetime. Estrogen provides more protection for women against heart disease before menopause. Consequently, the mean age of MI occurrence in women is higher than that in men22. Furthermore, the difference in the prevalence of MI between the male and female population can be attributed to other factors such as differences in lifestyle, smoking, hyperlipidemia, insulin resistance, obesity, diabetes, hypertension, etc. 16,30,37,44.

The high prevalence of MI in the elderly population and its increasing trend in recent years (Figure 6) in the present systematic review and meta-analysis study indicated the need for further investigations and follow-up for this disease. CVDs and the incidence of MI are considered as one of the most important public health problems, resulting in important health consequences, such as death, disability, and higher economic costs. The need to adopt policies and strategies focused on reducing and controlling risk factors can reduce the health and economic burden of disease in society in the long-term. However, identifying higher-risk populations and providing effective and quality periodic medical care can slow the progression of the disease and reduce the complications and death caused by MI.

Limitations

One of the limitations possibility of the lack of access to all articles and unpublished reports, lack of uniform reporting of articles, non-random selection of some samples, non-uniform study design, and lack of accurate and quality reporting in some studies. In addition, high heterogeneity among studies (more than 99%) led to perform subgroup analysis, which reduced a small amount of heterogeneity ,according to previous meta-analysis 62,63. However, there was still high heterogeneity in all subgroups, which may be due to sample size, demographic characteristics, and Study design.

Conclusions

The findings of this systematic review and meta-analysis study indicate that the prevalence rate of MI in the elderly is high and has been increasing with age in recent years. It is suggested to conduct systematic review and meta-analysis studies on the prevalence of other CVDs in the elderly, as well as the prevalence of MI in other subgroups and comorbid populations, such as youth and individuals with underlying conditions like diabetes and those undergoing hemodialysis. It is recommended that health officials and policymakers pay more attention to the prevention and control of this disease.

Acknowledgements

This study is the result of research project No. 50002369 approved by the Student Research Committee of Kermanshah University of Medical Sciences. We would like to thank the esteemed officials of that center for accepting the financial expenses of this study.

Conflict of Interest

The authors declare that they have no conflict of interest.

Funding

By Deputy for Research and Technology, Kermanshah University of Medical Sciences (IR) (50002369). This deputy has no role in the study process. This study was approved by the ethics committee of KUMS (IR.KUMS.REC.1402.103).

Author’s Contributions

M.K, F.R and M.R contributed to the design, M.K and F.R participated in most of the study steps. M.K, F.R and M.C prepared the manuscript. F.R, M.R and M.K assisted in designing the study, and helped in the, interpretation of the study. All authors have read and approved the content of the manuscript.

List of abbreviations:

WoS: Web of Science; MeSH: Medical Subject Headings; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analysis; CI: Confidence Interval; JBI: Joanna Briggs Institute; MI: Myocardial Infarction; WHO: World Health Organization; ECG: Electrocardiogram; DE-CMR: Delayed-Enhancement Cardiovascular Magnetic Resonance; COPD: Chronic Obstructive Pulmonary Disease.

References

  • 1.Zhao M, Gao J, Li M, Wang K. Relationship between loneliness and frailty among older adults in nursing homes: the mediating role of activity engagement. J Am Med Dir Assoc. 2019;20(6):759–64. doi: 10.1016/j.jamda.2018.11.007. [DOI] [PubMed] [Google Scholar]
  • 2.Kalstad AA, Myhre PL, Laake K, Tveit SH, Schmidt EB, Smith P, et al. Effects of n-3 fatty acid supplements in elderly patients after myocardial infarction: a randomized, controlled trial. Circulation. 2021;143(6):528–39. doi: 10.1161/CIRCULATIONAHA.120.052209. [DOI] [PubMed] [Google Scholar]
  • 3.Whittington FJ, Kunkel SR, de Medeiros K. Global Aging-Comparative Perspectives on Aging and the Life Course. 2019. [Google Scholar]
  • 4.Sadeghiyan F, Raei M, Hashemi M, Amiri M, Chaman R. Elderly and health problems: A cross sectional study in the Shahroud township. Iran J Ageing. 2011;6(2):26–30. [Google Scholar]
  • 5.Michel J-P, Leonardi M, Martin M, Prina M. WHO’s report for the decade of healthy ageing 2021-30 sets the stage for globally comparable data on healthy ageing. Lancet Healthy Longev. 2021;2(3):e121–e2. doi: 10.1016/S2666-7568(21)00002-7. [DOI] [PubMed] [Google Scholar]
  • 6.Andreescu C, Lee S. Anxiety Disorders in the Elderly. Adv Exp Med Biol. 2020;1191:561–576. doi: 10.1007/978-981-32-9705-0_28. [DOI] [PubMed] [Google Scholar]
  • 7.Tang M, Wang S-H, Li H-L, Chen H, Sun X-Y, Bian W-W, et al. Mental health status and quality of life in elderly patients with coronary heart disease. Peer J. 2021;9:e10903. doi: 10.7717/peerj.10903. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Khatmi Nasab N, Shamshiri M, Zamani U. The study of oral health status and its related quality of life in elderly people supported by welfare organization in Ardabil city. J Health Care. 2019;21(4):308–18. [Google Scholar]
  • 9.Şahin B, İlgün G. Risk factors of deaths related to cardiovascular diseases in World Health Organization (WHO) member countries. Health Soc Care Community. 2022 ;30(1):73–80. doi: 10.1111/hsc.13156. [DOI] [PubMed] [Google Scholar]
  • 10.Musher DM, Abers MS, Corrales-Medina VF. Acute infection and myocardial infarction. N Engl J Med. 2019;380(2):171–6. doi: 10.1056/NEJMra1808137. [DOI] [PubMed] [Google Scholar]
  • 11.Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, et al. Fourth universal definition of myocardial infarction (2018) Eur Heart J. 2019;40(3):237–69. doi: 10.1093/eurheartj/ehy462. [DOI] [PubMed] [Google Scholar]
  • 12.Investigators S-H. Coronary CT angiography and 5-year risk of myocardial infarction. N Engl J Med. 2018;379(10):924–33. doi: 10.1056/NEJMoa1805971. [DOI] [PubMed] [Google Scholar]
  • 13.Trzos E, Uznańska B, Rechciński T, Krzemińska-Pakuła M, Bugała M, Kurpesa M. Myocardial infarction in young people. Cardiol J. 2009;16(4):307–11. [PubMed] [Google Scholar]
  • 14.Félix-Redondo FJ, Grau M, Fernández-Bergés D. Cholesterol and cardiovascular disease in the elderly Facts and gaps. Aging Dis. 2013;4(3):154–69. [PMC free article] [PubMed] [Google Scholar]
  • 15.Jackson CF, Wenger NK. Cardiovascular disease in the elderly. Rev Esp Cardiol (Engl Ed) 2011;64(8):697–712. doi: 10.1016/j.recesp.2011.05.001. [DOI] [PubMed] [Google Scholar]
  • 16.Kılıç S, Aydın G, Çoner A, Doğan YK, Özlük ÖA, Çelik Y, et al. Prevalence and clinical profile of patients with myocardial infarction with non-obstructive coronary arteries in Turkey (MINOCA-TR): A national multi-center, observational study. Anatol J Cardiol. 2020;23(3):176–82. doi: 10.14744/AnatolJCardiol.2019.46805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Page M J, McKenzie J E, Bossuyt P M, Boutron I, Hoffmann T C, Mulrow C D, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi: 10.1136/bmj.n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid Based Health. 2015;13(3):147–53. doi: 10.1097/XEB.0000000000000054. [DOI] [PubMed] [Google Scholar]
  • 19.Sheifer SE, Gersh BJ, Yanez ND, Ades PA, Burke GL, Manolio TA. Prevalence, predisposing factors, and prognosis of clinically unrecognized myocardial infarction in the elderly. J Am Coll Cardiol. 2000;35(1):119–26. doi: 10.1016/s0735-1097(99)00524-0. [DOI] [PubMed] [Google Scholar]
  • 20.Rathore SS, Berger AK, Weinfurt KP, Schulman KA, Oetgen WJ, Gersh BJ, et al. Acute myocardial infarction complicated by atrial fibrillation in the elderly: prevalence and outcomes. Circulation. 2000;101(9):969–74. doi: 10.1161/01.cir.101.9.969. [DOI] [PubMed] [Google Scholar]
  • 21.Aronow WS. Prevalence of presenting symptoms of recognized acute myocardial infarction and of unrecognized healed myocardial infarction in elderly patients. Am J Cardiol. 1987;60(14):1182 . doi: 10.1016/0002-9149(87)90418-8. [DOI] [PubMed] [Google Scholar]
  • 22.Mehta RH, Rathore SS, Radford MJ, Wang Y, Wang Y, Krumholz HM. Acute myocardial infarction in the elderly: differences by age. J Am Coll Cardiol. 2001;38(3):736–41. doi: 10.1016/s0735-1097(01)01432-2. [DOI] [PubMed] [Google Scholar]
  • 23.Rathore SS, Gersh BJ, Berger PB, Weinfurt KP, Oetgen WJ, Schulman KA, et al. Acute myocardial infarction complicated by heart block in the elderly: prevalence and outcomes. Am Heart J. 2001;141(1):47–54. doi: 10.1067/mhj.2001.111259. [DOI] [PubMed] [Google Scholar]
  • 24.Lusiani L, Perrone A, Pesavento R, Conte G. Prevalence, clinical features, and acute course of atypical myocardial infarction. Angiology. 1994;45(1):49–55. doi: 10.1177/000331979404500107. [DOI] [PubMed] [Google Scholar]
  • 25.O’Neal WT, Sangal K, Zhang ZM, Soliman EZ. Atrial fibrillation and incident myocardial infarction in the elderly. Clin Cardiol. 2014;37(12):750–5. doi: 10.1002/clc.22339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Brugts JJ, Knetsch AM, Mattace-Raso FU, Hofman A, Witteman JC. Renal function and risk of myocardial infarction in an elderly population: the Rotterdam Study. Arch Intern Med. 2005;165(22):2659–65. doi: 10.1001/archinte.165.22.2659. [DOI] [PubMed] [Google Scholar]
  • 27.Nadelmann J, Frishman WH, Ooi WL, Tepper D, Greenberg S, Guzik H, et al. Prevalence, incidence and prognosis of recognized and unrecognized myocardial infarction in persons aged 75 years or older: the Bronx Aging Study. Am J Cardiol. 1990;66(5):533–7. doi: 10.1016/0002-9149(90)90477-i. [DOI] [PubMed] [Google Scholar]
  • 28.Duan Y, Mo J, Klein R, Scott IU, Lin H-M, Caulfield J, et al. Age-related macular degeneration is associated with incident myocardial infarction among elderly Americans. Ophthalmology. 2007;114(4):732–7. doi: 10.1016/j.ophtha.2006.07.045. [DOI] [PubMed] [Google Scholar]
  • 29.Dangelser G, Gottwalles Y, Huk M, De Poli F, Levai L, Boulenc J-M, et al. Infarctus du myocarde du sujet de plus de 75 ans: Données d’un registre multicentrique régional. Presse Med. 2005;34(14):983–9. doi: 10.1016/s0755-4982(05)84096-5. [DOI] [PubMed] [Google Scholar]
  • 30.Barbier CE, Nylander R, Themudo R, Ahlström H, Lind L, Larsson E-M, et al. Prevalence of unrecognized myocardial infarction detected with magnetic resonance imaging and its relationship to cerebral ischemic lesions in both sexes. J Am Coll Cardiol. 2011;58(13):1372–7. doi: 10.1016/j.jacc.2011.06.028. [DOI] [PubMed] [Google Scholar]
  • 31.Khera S, Kolte D, Palaniswamy C, Mujib M, Aronow WS, Singh T, et al. ST-elevation myocardial infarction in the elderly-temporal trends in incidence, utilization of percutaneous coronary intervention and outcomes in the United States. Int J Cardiol. 2013;168(4):3683–90. doi: 10.1016/j.ijcard.2013.06.021. [DOI] [PubMed] [Google Scholar]
  • 32.Claussen PA, Abdelnoor M, Kvakkestad KM, Eritsland J, Halvorsen S. Prevalence of risk factors at presentation and early mortality in patients aged 80 years or older with ST-segment elevation myocardial infarction. Vasc Health Risk Manag. 2014 Dec;10:683–9. doi: 10.2147/VHRM.S72764. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Reiter M, Twerenbold R, Reichlin T, Haaf P, Peter F, Meissner J, et al. Early diagnosis of acute myocardial infarction in the elderly using more sensitive cardiac troponin assays. Eur Heart J. 2011;32(11):1379–89. doi: 10.1093/eurheartj/ehr033. [DOI] [PubMed] [Google Scholar]
  • 34.Goch A, Misiewicz P, Rysz J, Banach M. The clinical manifestation of myocardial infarction in elderly patients. Clin Cardiol. 2009;32(6):E45–50. doi: 10.1002/clc.20354. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Pastori D, Pignatelli P, Angelico F, Farcomeni A, Del Ben M, Vicario T, et al. Incidence of myocardial infarction and vascular death in elderly patients with atrial fibrillation taking anticoagulants: relation to atherosclerotic risk factors. Chest. 2015;147(6):1644–50. doi: 10.1378/chest.14-2414. [DOI] [PubMed] [Google Scholar]
  • 36.Sato K, Takahashi J, Hao K, Miyata S, Suda A, Shindo T, et al. Temporal trends in the prevalence and outcomes of geriatric patients with acute myocardial infarction in Japan-A report from the Miyagi AMI Registry Study. J Cardiol. 2020;75(5):465–72. doi: 10.1016/j.jjcc.2019.10.006. [DOI] [PubMed] [Google Scholar]
  • 37.Schelbert EB, Cao JJ, Sigurdsson S, Aspelund T, Kellman P, Aletras AH, et al. Prevalence and prognosis of unrecognized myocardial infarction determined by cardiac magnetic resonance in older adults. JAMA. 2012;308(9):890–6. doi: 10.1001/2012.jama.11089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Maynard C, Lowy E, Rumsfeld J, Sales AE, Sun H, Kopjar B, et al. The prevalence and outcomes of in-hospital acute myocardial infarction in the Department of Veterans Affairs Health System. Arch Intern Med. 2006;166(13):1410–6. doi: 10.1001/archinte.166.13.1410. [DOI] [PubMed] [Google Scholar]
  • 39.Amann U, Kirchberger I, Heier M, von Scheidt W, Kuch B, Peters A, et al. Acute myocardial infarction in the elderly: Treatment strategies and 28‐day‐case fatality from the MONICA/KORA myocardial infarction registry. Catheter Cardiovasc Interv. 2016;87(4):680–8. doi: 10.1002/ccd.26159. [DOI] [PubMed] [Google Scholar]
  • 40.DeLuca AJ, Kaplan S, Aronow WS, Sandhu R, Butt A, Akoybyan A, et al. Comparison of prevalence of unrecognized myocardial infarction and of silent myocardial ischemia detected by a treadmill exercise sestamibi stress test in patients with versus without diabetes mellitus. Am J Cardiol. 2006;98(8):1045–6. doi: 10.1016/j.amjcard.2006.05.026. [DOI] [PubMed] [Google Scholar]
  • 41.Ahto M, Isoaho R, Puolijoki H, Laippala P, Romo M, Kivelä S-L. Prevalence of coronary heart disease, associated manifestations and electrocardiographic findings in elderly Finns. Age Ageing. 1998;27(6):729–38. doi: 10.1093/ageing/27.6.729. [DOI] [PubMed] [Google Scholar]
  • 42.Kim HW, Klem I, Shah DJ, Wu E, Meyers SN, Parker MA, et al. Unrecognized non-Q-wave myocardial infarction: prevalence and prognostic significance in patients with suspected coronary disease. PLoS Med. 2009;6(4):e1000057. doi: 10.1371/journal.pmed.1000057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Figueroa-Triana JF, Mora-Pabón G, Quitian-Moreno J, Álvarez-Gaviria M, Idrovo C, Cabrera JS, et al. Acute myocardial infarction with right bundle branch block at presentation: Prevalence and mortality. J Electrocardiol. 2021;66:38–42. doi: 10.1016/j.jelectrocard.2021.02.009. [DOI] [PubMed] [Google Scholar]
  • 44.Gianfagna F, Veronesi G, Tozzi M, Tarallo A, Borchini R, Ferrario MM, et al. RoCAV (Risk of Cardiovascular diseases and abdominal aortic Aneurysm in Varese) Project Investigators Prevalence of Abdominal Aortic Aneurysms in the General Population and in Subgroups at High Cardiovascular Risk in Italy Results of the RoCAV Population Based Study. Eur J Vasc Endovasc Surg. 2018 ;55(5):633–9. doi: 10.1016/j.ejvs.2018.01.008. [DOI] [PubMed] [Google Scholar]
  • 45.Kohn MA, Kwan E, Gupta M, Tabas JA. Prevalence of acute myocardial infarction and other serious diagnoses in patients presenting to an urban emergency department with chest pain. J Emerg Med. 2005;29(4):383–90. doi: 10.1016/j.jemermed.2005.04.010. [DOI] [PubMed] [Google Scholar]
  • 46.Sajadieh A, Nielsen OW, Rasmussen V, Hein HO, Hansen JF. Prevalence and prognostic significance of daily-life silent myocardial ischaemia in middle-aged and elderly subjects with no apparent heart disease. Eur Heart J. 2005;26(14):1402–9. doi: 10.1093/eurheartj/ehi169. [DOI] [PubMed] [Google Scholar]
  • 47.Gibson P, Narous M, Firoz T, Chou D, Barreix M, Say L, et al. Incidence of myocardial infarction in pregnancy: a systematic review and meta-analysis of population-based studies. Eur Heart J Qual Care Clin Outcomes. 2017;3(3):198–207. doi: 10.1093/ehjqcco/qcw060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Tavallaei MJ, Tavallaei AH, Ebrahimi N, Ghoshouni H, Afshari-Safavi A, Badihian S, et al. The prevalence of Myocardial Infarction among Multiple Sclerosis Patients: a Systematic Review and Meta-analysis. Mult Scler Relat Disord. 2021;56:103292. doi: 10.1016/j.msard.2021.103292. [DOI] [PubMed] [Google Scholar]
  • 49.Hung CS, Chen YH, Huang CC, Lin MS, Yeh CF, Li HY, et al. Prevalence and outcome of patients with non-ST segment elevation myocardial infarction with occluded “culprit” artery - a systemic review and meta-analysis. Crit Care. 2018 Feb;22(1):34 . doi: 10.1186/s13054-018-1944-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Rothnie KJ, Yan R, Smeeth L, Quint JK. Risk of myocardial infarction (MI) and death following MI in people with chronic obstructive pulmonary disease (COPD): a systematic review and meta-analysis. BMJ Open. 2015;5(9):e007824 . doi: 10.1136/bmjopen-2015-007824. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Schieir O, Tosevski C, Glazier RH, Hogg-Johnson S, Badley EM. Incident myocardial infarction associated with major types of arthritis in the general population: a systematic review and meta-analysis. Ann Rheum. Dis. 2017;76(8):1396–404. doi: 10.1136/annrheumdis-2016-210275. [DOI] [PubMed] [Google Scholar]
  • 52.Grishina I, Fenton A, Sankaran-Walters S. Gender differences, aging and hormonal status in mucosal injury and repair. Aging Dis. 2014 Apr;5(2):160–9. doi: 10.14336/AD.2014.0500160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Jovanovich A, Ix JH, Gottdiener J, McFann K, Katz R, Kestenbaum B, et al. Fibroblast growth factor 23, left ventricular mass, and left ventricular hypertrophy in community-dwelling older adults. Atherosclerosis. 2013;231(1):114–9. doi: 10.1016/j.atherosclerosis.2013.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Deyranlou A, Miller CA, Revell A, Keshmiri A. Effects of ageing on aortic circulation during atrial fibrillation; a numerical study on different aortic morphologies. Ann Biomed Eng. 2021;49(9):2196–213. doi: 10.1007/s10439-021-02744-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Komutrattananont P, Mahakkanukrauh P, Das S. Morphology of the human aorta and age-related changes: anatomical facts. Anat Cell Biol. 2019;52(2):109–14. doi: 10.5115/acb.2019.52.2.109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Bavishi C, Goel S, Messerli FH. Isolated systolic hypertension: an update after SPRINT. Am J Med. 2016;129(12):1251–8. doi: 10.1016/j.amjmed.2016.08.032. [DOI] [PubMed] [Google Scholar]
  • 57.van den Oord SC, Sijbrands EJ, Gerrit L, van Klaveren D, van Domburg RT, van der Steen AF, et al. Carotid intima-media thickness for cardiovascular risk assessment: systematic review and meta-analysis. Atherosclerosis. 2013;228(1):1–11. doi: 10.1016/j.atherosclerosis.2013.01.025. [DOI] [PubMed] [Google Scholar]
  • 58.Abdoli N, Salari N, Darvishi N, Jafarpour S, Solaymani M, Mohammadi M, et al. The global prevalence of major depressive disorder (MDD) among the elderly: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2022 Jan;132:1067–73. doi: 10.1016/j.neubiorev.2021.10.041. [DOI] [PubMed] [Google Scholar]
  • 59.Biswas T, Islam A, Rawal LB, Islam SM. Increasing prevalence of diabetes in Bangladesh: a scoping review. Public Health. 2016 Sep;138:4–11. doi: 10.1016/j.puhe.2016.03.025. [DOI] [PubMed] [Google Scholar]
  • 60.Rejeski WJ, Brubaker PH, Goff DC, Bearon LB, McClelland JW, Perri MG, et al. Translating weight loss and physical activity programs into the community to preserve mobility in older, obese adults in poor cardiovascular health. Arch Intern Med. 2011;171(10):880–6. doi: 10.1001/archinternmed.2010.522. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Hsu WC, Lau KH, Matsumoto M, Moghazy D, Keenan H, King GL. Improvement of insulin sensitivity by isoenergy high carbohydrate traditional Asian diet: a randomized controlled pilot feasibility study. PLoS One. 2014 Sep;9(9):e106851. doi: 10.1371/journal.pone.0106851. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Kazeminia M, Afshar ZM, Rajati M, Saeedi A, Rajati F. Evaluation of the Acceptance Rate of Covid-19 Vaccine and its Associated Factors: A Systematic Review and Meta-analysis. J Prev. 2022 Aug;43(4):421–67. doi: 10.1007/s10935-022-00684-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Ghavami T, Kazeminia M, Rajati F. The effect of lavender on stress in individuals: A systematic review and meta-analysis. Complement Ther Med. 2022 Sep;68:102832. doi: 10.1016/j.ctim.2022.102832. [DOI] [PubMed] [Google Scholar]

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