Next Article in Journal
Impact of Sarcopenia and Functional Relationships Between Balance and Gait After Total Hip Arthroplasty
Previous Article in Journal
A Dynamic Multimodality Imaging Assessment of Right Ventricular Thrombosis in a Middle-Aged Man with Lymphocytic Interstitial Pneumonia: The Additive Role of Tissue Doppler Imaging
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 14
Issue 6
10.3390/jcm14062034
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Description of the Risk Factors for Ischemic Stroke in the Lebanese Population: Their Association with Age at First Stroke Incidence and the Predictors of Recurrence

by
Jad El Masri
1,2,3,4,*,
Diala El Masri
5,6,
Maya Ghazi
3,6,7,
Ahmad Afyouni
3,6,
Hani Finge
8,
Jad El Ahdab
9,
Maryam Tlayss
10,
Soltan Al Chaar
11,
Wassim Abou-Kheir
4,
Pascale Salameh
3,7,12,13,14,† and
Hassan Hosseini
1,15,†
1
INSERMU955-E01, Institut Mondor de Recherche Biomédicale, Université Paris-Est Créteil, 94000 Créteil, France
2
École Doctorale Sciences de la Vie et de la Santé, Université Paris-Est Créteil, 94010 Créteil, France
3
Faculty of Medical Sciences, Lebanese University, Beirut 1533, Lebanon
4
Department of Anatomy, Cell Biology and Physiological Sciences, Faculty of Medicine, American University of Beirut, Beirut 1107, Lebanon
5
Faculty of Medicine, University of Balamand, Koura 1100, Lebanon
6
Faculty of Medical Sciences, Neuroscience Research Center (NRC), Lebanese University, Beirut 1533, Lebanon
7
School of Medicine, Lebanese American University, Byblos 1102, Lebanon
8
Department of Neurology, Faculty of Medical Sciences, Lebanese University, Beirut 1533, Lebanon
9
Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
10
Faculty of Arts and Sciences, University of Balamand, Koura 1100, Lebanon
11
Doctoral School of Science and Technology, Lebanese University, Beirut 1533, Lebanon
12
Faculty of Pharmacy, Lebanese University, Beirut 1533, Lebanon
13
Department of Primary Care and Population Health, University of Nicosia Medical School, 2417 Nicosia, Cyprus
14
INSPECT-LB (Institut National de Sant e Publique, d’Épidemiologie Clinique et de Toxicologie-Liban), Beirut 1103, Lebanon
15
RAMSAY SANTÉ, HPPE, 94500 Créteil, France
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Clin. Med. 2025, 14(6), 2034; https://doi.org/10.3390/jcm14062034
Submission received: 3 March 2025 / Revised: 12 March 2025 / Accepted: 15 March 2025 / Published: 17 March 2025
(This article belongs to the Section Clinical Neurology)
Browse Figures
Versions Notes

Abstract

:
Background: Stroke is the third most common cause of death in Lebanon. With many preventive strategies identified, stroke remains a national burden, especially in developing countries, where risk factors and epidemiological states are understudied. This study aims to investigate the association of sociodemographic factors and health-related risk factors with age at first ischemic stroke and its recurrence in the Lebanese population. Methods: A retrospective study including 214 ischemic stroke cases was carried out. Sociodemographic characteristics and health-related risk factors were assessed, in addition to disability levels (modified Rankin score (mRS)), age at first ischemic stroke incidence, and number of ischemic strokes. Data were analyzed using SPSS software version 25, including descriptive, bivariate, and multivariate analyses. Results: This study showed that stressful factors were significantly associated with a younger age at first ischemic stroke, such as having no partner (p < 0.001), having employment (p < 0.001), and having migraines (p < 0.001). However, metabolic risk factors were associated with an older age of ischemic stroke, such as hypertension (p < 0.001) and hyperlipidemia (p < 0.001). Moreover, having a partner (OR: 2.136), having a family history of stroke (OR: 2.873), having hyperlipidemia (OR: 3.71), and having atrial fibrillation (OR: 2.521) were associated with ischemic stroke recurrence. Conclusions: Many modifiable factors are associated with age at first ischemic stroke and its recurrence. This study sheds light on the necessity of increasing knowledge and awareness of well-known risk factors in the Lebanese population. These results suggest implementing targeted preventive strategies and highlight the importance of complying with early detection and follow-up measures.

1. Introduction

Stroke is a clinically defined syndrome of acute, focal neurological deficit attributed to vascular injury of the central nervous system [1]. According to the Global Burden of Disease Study 2021, stroke remained the second most common cause of death and the third most common cause of disability-adjusted life years (DALYs) among non-communicable disorders globally [2]. Ischemic stroke is the most common type, making up around 90% of total cases [3]. Prevalence in Lebanon is unknown, and some related factors are understudied. In addition, recommended guidelines were not found to be uniformly applied for all patients and in all hospitals [4].
Ischemic stroke risk factors are divided into non-modifiable and modifiable [5]. Non-modifiable risk factors include increased age, African race, male gender, family history, and genetic predisposition [2,6], while modifiable risk factors include hypertension, dyslipidemia, atrial fibrillation, myocardial infarction, smoking, and others [7,8,9,10,11].
In the Middle East, the incidence and prevalence rates for all strokes ranged between 22.7 and 250 per 100,000 population per year and between 508 and 777 per 100,000 population respectively. The mean age of stroke lies within the sixth and the seventh decade, and hypertension was the most reported risk factor. The overall case-fatality rate within one month was 12–32% [12]. In Lebanon, a study conducted in 2019 showed that the cumulative mortality rates were 14.1% at 1 month and 22% at 1 year [13].
In Lebanon, a lower–middle-income country in the Eastern Mediterranean Region, data on the prevalence of stroke subtypes and their associations with risk factors are limited [14]. Despite that, WHO classified stroke as the third leading cause of death in 2021 in Lebanon (40.9 per 100,000 population) [15]. Moreover, due to low socioeconomic status and the aging population, stroke is considered a major health problem [16]. Furthermore, modifiable risk factors also have a high prevalence in the Lebanese population [17].
Several studies addressed ischemic stroke risk factors in Lebanon, yet none addressed the age at first stroke and the recurrence [18,19,20,21,22]. Therefore, identifying key factors associated with onset and recurrence can help healthcare workers optimize their preventive strategies and interventions. This study aims to investigate the association between sociodemographic factors, health-related risk factors, and the age of first ischemic stroke and its recurrence in the Lebanese population.

2. Methods

2.1. Study Design

A retrospective cohort study was carried out to assess the effect of risk factors on the age of the first ischemic stroke incidence and the number of incidents. All participants provided informed consent, which outlined the study’s objectives and potential concerns, and ensured the confidentiality of the data collected. Participation was completely voluntary, and data were gathered from patients’ medical records between February and December 2023.

2.2. Participants

All included cases were Lebanese individuals admitted to Sahel General Hospital or Al Rassoul Al Azam Hospital in Beirut due to an ischemic stroke. All patients admitted to the neurology department were targeted to assess eligibility to include them. However, some eligible patients were excluded due to refusal, early discharge or transfer, or missing information.
Inclusion criteria: All included patients were 18 years old or older, with confirmed ischemic stroke by computed tomography (CT) and/or magnetic resonance imaging (MRI). In addition, diagnosis was confirmed clinically in all included patients [3].
Exclusion criteria: Patients without radiological or clinical confirmation of ischemic stroke were excluded. In addition, patients with CVA other than ischemic stroke were excluded, such as transient ischemic attack or hemorrhagic stroke [23].

2.3. Variables and Data Source Measures

Patients’ medical records were screened for all studied factors:
-
Sociodemographic characteristics: Age, gender, marital status, educational level, employment, governorate, income level, and area of residency;
-
Previous health-related conditions: smoking, family history of stroke, hypertension (defined as having systolic blood pressure >130 mm Hg and/or diastolic blood pressure >80 mm Hg [24]), hyperlipidemia (defined as having elevated lipid levels [25]), deep vein thrombosis (DVT) or pulmonary embolism (PE) (defined as having blood clots in venous circulation or in pulmonary circulation [26]), atrial fibrillation (defined as having cardiac electricity disturbance [27]), migraine (defined as having a specific type of headache [28]), and myocardial infarction (MI) (defined as having a decreased blood flow to the myocardium [29]);
-
Level of disability: the modified Rankin scale was used to classify patients depending on disability levels. It ranges from 0 (no disability) to 6 (death) [30].

2.4. Ethical Considerations

Ethical approval was obtained from the Institutional Review Board (IRB) of Sahel General Hospital (ID number: 1/2023; approval date: 10 January 2023) at the hospitals involved, assuring that this study respects confidentiality and anonymity.

2.5. Statistical Analysis

Data were analyzed using SPSS software version 25. Descriptive analysis was performed using frequencies and percentages for categorical variables and means and standard deviations for continuous variables. A bivariate analysis was performed to identify the association between sociodemographics and health-related risk factors with the age at first stroke and number of stroke events. A Student’s test (in symmetrical data) or a Wilcoxon test (in asymmetrical data) was used to compare means between two groups, and an ANOVA test (in symmetrical data) or Kruskal–Wallis test (in asymmetrical data) was used to compare means between more than two groups. Chi-square and Fisher exact tests were used to compare percentages between groups. A p < 0.05 was considered statistically significant.
A generalized linear model (GLM) was used to investigate the association (beta and 95% CI) of marital status, educational level, employment, smoking, family history, hypertension, hyperlipidemia, atrial fibrillation, and myocardial infarction with the age at first stroke incidence. A binomial logistic regression model was performed to investigate the adjusted odds ratio (ORa) with a 95% CI of marital status, educational level, employment, smoking, family history, hypertension, hyperlipidemia, atrial fibrillation, myocardial infarction, and number of stroke events. The Hosmer–Lemeshow test was non-significant, demonstrating the test’s adequacy. The decision tree model was used to identify the significant factors influencing age at first ischemic stroke and stroke recurrence. All covariates with a p < 0.2 in the bivariate analysis were included in the regression models. The CI was set at 95%, and a value of p < 0.05 was considered significant.

3. Results

Table 1 represents a description of the sociodemographic characteristics of the sample included. A total of 214 ischemic stroke patients were included in this study. Around half of the sample were females (102, 48.13%). In total, 119 (55.6%) had a partner, and 95 (44.4%) did not have a partner. Around half had school education (99, 46.26%), and a quarter (51, 23.83%) were not educated. A total of 152 (71.03%) were unemployed, 31 (14.48%) were employed, and another 31 (14.48%) had a freelance profession. The majority had a moderate income (129, 60.3%), and around three-fourths lived in an urban area (159, 74.3%).
Table 2 represents a description of health-related risk factors in the sample included. Almost half of the sample were smokers (126, 58.88%), and around half had a family history of stroke (105, 49.06%). The majority had hypertension (194, 90.65%), and almost three-fourths had hyperlipidemia (151, 70.56%). The majority of patients did not have DVT or PE, atrial fibrillation, migraine, or myocardial infarction.
Figure 1A represents the distribution of age at first stroke incidence in the included sample. The majority of patients had an ischemic stroke between the ages of 58 and 85.
Figure 1B shows the number of stroke incidents in patients, where one hundred fifty-one (70.56%) had only one stroke, fifty-one (23.83%) had two strokes, ten (4.67%) had three strokes, and only two (0.93%) had four strokes.
Figure 1C shows the distribution of patients among disability levels, where the majority (111, 52%) had moderate disability, around two-fifths had mild disability (60, 28%), and one-fifth (43, 20%) had severe disability.
Table 3 shows the association between age at first stroke and number of stroke incidents with sociodemographic factors. Being without a partner was associated with a significantly younger age at first stroke incidence (p < 0.001). Having no education or having only school education was associated with an older age at stroke incidence (p < 0.001). Similarly, having no employment was associated with an older age at first stroke incidence compared to being employed or having a freelance profession (p < 0.001).
As for the number of ischemic stroke events and recurrence, being uneducated and having no employment were associated with a higher number of strokes (p < 0.001 and p = 0.004, respectively) and more recurrence (p = 0.027 and p = 0.004, respectively).
Figure 2 represents the decision tree model for the age at first ischemic stroke. Those not employed had a significantly older age at first stroke compared to others (p < 0.001). Among them, those having a partner had a significantly higher age at first stroke compared to those without a partner (p < 0.001).
Figure 3 represents the decision tree model for the number of ischemic stroke events. Those not employed had a significantly higher number of stroke events compared to other (p < 0.001). Among others, those having hyperlipidemia had a higher number of strokes compared to those not having hyperlipidemia (p = 0.023).
Table 4 shows the association between age at first stroke and number of stroke incidents with health-related risk factors. Smoking, family history of stroke, and migraine were associated with a younger age at first stroke incidence (p < 0.001, p = 0.016, and p < 0.001, respectively). Having hypertension, hyperlipidemia, DVT or PE, and myocardial infarction were associated with older age at first stroke incidence (p < 0.001, p < 0.001, p = 0.025, and p = 0.041, respectively). As for number of stroke incidents and recurrences, family history, hypertension, hyperlipidemia, DVT or PE, and atrial fibrillation were associated with a higher number of stroke incidents (p = 0.005, p = 0.012, p < 0.001, p = 0.041, and p = 0.001, respectively) and more recurrence (p = 0.006, p = 0.012, p = 0.001, p = 0.067, p = 0.001, respectively).
Table 5 shows the correlation between age at first stroke and number of stroke incidents with the level of disability. Younger age at first stroke was associated with milder levels of disability (p < 0.001), while a bigger number of stroke incidents was associated with more severe disability (p = 0.05).
Table 6 shows the generalized linear model taking the age at first stroke incidence with sociodemographic characteristics and health-related risk factors. Compared to having no partner, having a partner (beta = 6.058) was significantly associated with an older age at stroke incidence (p < 0.01). Being unemployed was significantly associated with an older age at first stroke incidence (beta = 7.98), as well as having hypertension (beta = 5.06) and hyperlipidemia (beta = 3.378). Having migraine was associated with a younger age at first stroke (beta = −9.10), as well as being a smoker (beta = −2.929).
Table 7 shows the binomial forward logistic regression regarding the recurrence of ischemic stroke (more than one incident versus one): being employed (OR: 9.591, CI 95% 1.976–46.56, p = 0.005) was associated with higher odds of having more than one stroke incident compared to being not employed. Similarly, having a partner (OR: 2.136, CI 95% 1.05–4.345, p = 0.036), having a family history of stroke (OR: 2.873, CI 95% 1.473–5.604, p = 0.002), having hyperlipidemia (OR: 3.71, CI 95% 1.515–9.085, p = 0.004), and having atrial fibrillation (OR: 2.521, CI 95% 1.272–4.999, p = 0.008) were associated with higher odds of having more than one stroke incidents.

4. Discussion

This study aimed to assess the effect of sociodemographic factors and health-related risk factors on the age at first ischemic stroke incidence and the number of ischemic stroke events. This study showed that stressful factors were significantly associated with a younger age at first ischemic stroke, such as having no partner (p < 0.001), having employment (p < 0.001), and having migraine (p < 0.001). However, metabolic risk factors were associated with an older age of ischemic stroke, such as hypertension (p < 0.001) and hyperlipidemia (p < 0.001). Moreover, being employed (ORa = 9.591), having no partner (OR = 2.136), having a family history of stroke (ORa = 3.251), hyperlipidemia (ORa = 3.71), and atrial fibrillation (ORa = 2.521) were associated with ischemic stroke recurrence.
Considering the effect of metabolic risk factors, Soto-Cámara R. et al. (2020) showed that hypertension was associated with an older age at first stroke event, which agrees with the results reached in this study [31]. This could be explained by the mechanistic pathway through which hypertension causes ischemic stroke. Hypertension, as well as some other diseases, such as hyperlipidemia, promotes intracranial atherosclerosis and stenoses, inducing smooth muscle hypertrophy, a reduction in the wall-to-lumen ratio, and a reduction in vessel wall compliances [32]. These processes are slow processes that are more prevalent at older ages [33]. Furthermore, it is worth mentioning that hypertensive and hyperlipidemic patients also have regular visits to physicians, which aids in the early detection and prevention of other stroke-related risk factors [25,34]. In Lebanon, where the healthcare system is suffering from multiple crises, this could offer indirect benefits to patients by offering frequent visits to healthcare individuals, which leads to better orientation in patients, and a chance to have a regular checkup [35,36]. Moreover, in several cases, antiplatelet therapy is used as secondary prevention for patients with hypertension, which prevents or at least delays the emergence of thrombotic events [37]. These facts sum up to explain the delay in stroke incidence to an older age.
As for the effect of stressful factors, several studies proved the link between stress and ischemic stroke [38,39,40]. This was suggested to result from the sudden sympathetic stimulation caused by acute stress, leading to transient ischemia and rupture of pre-formed thrombotic plaques [38]. Having no partner, which might indirectly indicate sexual activity, was associated with higher levels of stress [41]. In addition to being educated and having employment, especially in the healthcare field, this might help explain the association between younger ages and first stroke [42,43,44]. Similarly, migraine was considered a stress factor and was directly correlated to ischemic stroke [45]. As for smoking, it was found to worsen negative emotions and coping strategies, leading to elevated stress levels [46]. Furthermore, nicotine was found to increase platelet aggregation, elevate fibrinogen levels, reduce HDL cholesterol, and directly damage blood vessel walls, which all together lead to ischemic stroke [47].
Regarding the number of ischemic stroke events, both metabolic and stressful factors caused an increase in the number of strokes. Despite the fact that several stroke cases are associated with recurrence, the percentage of recurrent cases after 1 year decreased from 8% between 1995 and 1999 to 4.3% between 2015 and 2018, certainly after the development of several preventive measures [48,49]. In Lebanon, the low levels of awareness and the limited knowledge of warning signs, in addition to the poor knowledge of necessary lifestyle modifications aid against the prevention of stroke recurrence, explaining the significant recurrence rate in patients exposed to risk factors [50,51]. Similarly, social status was previously found to have a direct effect on stroke recurrence [52]. Other studies also assessed the timing of stroke recurrence, where a study on German found that the percentage of recurrent cases was 1.2% in the first 30 days, 3.4% within 90 days, and 7.4% within 1 year [53]. However, in Lebanon, no data are available on the timing of recurrence.
This study is not without its limitations. The central locations of the hospitals included may limit the generalizability of the results to all areas, as peripheral regions might have different access to healthcare facilities and exposure to risk factors. The limited sample size could reduce the power of statistical analyses, potentially leading to non-significant associations. Additionally, information bias is possible due to factors like social desirability in patient responses, recall bias—especially in severe stroke cases with cognitive impairment—and underdiagnosed conditions. Although this bias is likely non-differential and would only push results toward the null hypothesis, it remains a consideration. Furthermore, while two multivariable regression models were used to mitigate confounding, unmeasured confounders may still exist, leading to residual confounding. To address these limitations and confirm the findings, further prospective studies are recommended that take into account these weaknesses.

5. Conclusions

This retrospective study offers a summary of ischemic stroke age at occurrence and recurrence risk factors in Lebanon. Metabolic risk factors, including hypertension and hyperlipidemia, were associated with an older age at first ischemic stroke, while stressful factors such as having no partner, being employed, and having migraine were associated with younger ages. Moreover, being employed and having a family history of stroke, hyperlipidemia, and atrial fibrillation were associated with ischemic stroke recurrence.
Overall, these results offer a new direction to explain the mechanism through which risk factors lead to ischemic stroke, which helps in implementing targeted preventive strategies. Furthermore, this study highlights the importance of complying with early detection and follow-up measures and sheds light on the necessity of increasing knowledge and awareness of well-known risk factors.

Author Contributions

All authors contributed to the study conception and design. Material preparation was performed by J.E.M., H.F., D.E.M. and M.G.; data collection was performed by H.F., J.E.M. and M.G.; and analyses were performed by J.E.M. and P.S. The first draft of the manuscript was written by J.E.M., D.E.M., A.A., M.G., J.E.A., M.T. and S.A.C. and revised by W.A.-K., P.S. and H.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was approved by the IRB committee at Sahel General Hospital, Beirut, Lebanon (IRB# 1/2023; approval date: 10 January 2023).

Informed Consent Statement

All patients included gave written consent to the hospital to use their medical records. Verbal consent was taken as an additional measure.

Data Availability Statement

Data are available upon request from the corresponding author.

Conflicts of Interest

The authors declare no competing interests.

References

  1. Murphy, S.J.; Werring, D.J. Stroke: Causes and Clinical Features. Med. Abingdon Engl. UK Ed. 2020, 48, 561–566. [Google Scholar] [CrossRef]
  2. Feigin, V.L.; Abate, M.D.; Abate, Y.H.; Abd ElHafeez, S.; Abd-Allah, F.; Abdelalim, A.; Abdelkader, A.; Abdelmasseh, M.; Abd-Elsalam, S.; Abdi, P.; et al. Global, Regional, and National Burden of Stroke and Its Risk Factors, 1990–2021: A Systematic Analysis for the Global Burden of Disease Study 2021. Lancet Neurol. 2024, 23, 973–1003. [Google Scholar] [CrossRef]
  3. Hui, C.; Tadi, P.; Khan Suheb, M.Z.; Patti, L. Ischemic Stroke. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2025. [Google Scholar]
  4. Malaeb, D.; Cherri, S.; Fahs, I.; Sacre, H.; Abdallah, E.; Salameh, P.; Hosseini, H. Management of Acute Stroke Among Lebanese Patients: Assessing Adherence to International Guidelines. Curr. Drug Saf. 2023, 18, 555–562. [Google Scholar] [CrossRef]
  5. Sabih, A.; Tadi, P.; Kumar, A. Stroke Prevention. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2025. [Google Scholar]
  6. O’Donnell, M.J.; Chin, S.L.; Rangarajan, S.; Xavier, D.; Liu, L.; Zhang, H.; Rao-Melacini, P.; Zhang, X.; Pais, P.; Agapay, S.; et al. Global and Regional Effects of Potentially Modifiable Risk Factors Associated with Acute Stroke in 32 Countries (INTERSTROKE): A Case-Control Study. Lancet Lond. Engl. 2016, 388, 761–775. [Google Scholar] [CrossRef]
  7. Tsivgoulis, G.; Safouris, A.; Kim, D.-E.; Alexandrov, A.V. Recent Advances in Primary and Secondary Prevention of Atherosclerotic Stroke. J. Stroke 2018, 20, 145–166. [Google Scholar] [CrossRef]
  8. Katsanos, A.H.; Filippatou, A.; Manios, E.; Deftereos, S.; Parissis, J.; Frogoudaki, A.; Vrettou, A.-R.; Ikonomidis, I.; Pikilidou, M.; Kargiotis, O.; et al. Blood Pressure Reduction and Secondary Stroke Prevention: A Systematic Review and Metaregression Analysis of Randomized Clinical Trials. Hypertens. Dallas Tex 1979 2017, 69, 171–179. [Google Scholar] [CrossRef]
  9. Bai, Y.; Deng, H.; Shantsila, A.; Lip, G.Y.H. Rivaroxaban Versus Dabigatran or Warfarin in Real-World Studies of Stroke Prevention in Atrial Fibrillation: Systematic Review and Meta-Analysis. Stroke 2017, 48, 970–976. [Google Scholar] [CrossRef]
  10. Kernan, W.N.; Ovbiagele, B.; Black, H.R.; Bravata, D.M.; Chimowitz, M.I.; Ezekowitz, M.D.; Fang, M.C.; Fisher, M.; Furie, K.L.; Heck, D.V.; et al. Guidelines for the Prevention of Stroke in Patients with Stroke and Transient Ischemic Attack: A Guideline for Healthcare Professionals from the American Heart Association/American Stroke Association. Stroke 2014, 45, 2160–2236. [Google Scholar] [CrossRef]
  11. Fitchett, D.H.; Goodman, S.G.; Langer, A. Ischemic Stroke: A Cardiovascular Risk Equivalent? Lessons Learned from the Stroke Prevention by Aggressive Reduction in Cholesterol Levels (SPARCL) Trial. Can. J. Cardiol. 2008, 24, 705–708. [Google Scholar] [CrossRef]
  12. El-Hajj, M.; Salameh, P.; Rachidi, S.; Hosseini, H. The Epidemiology of Stroke in the Middle East. Eur. Stroke J. 2016, 1, 180–198. [Google Scholar] [CrossRef]
  13. Abdo, R.; Abboud, H.; Salameh, P.; El Hajj, T.; Hosseini, H. Mortality and Predictors of Death Poststroke: Data from a Multicenter Prospective Cohort of Lebanese Stroke Patients. J. Stroke Cerebrovasc. Dis. Off. J. Natl. Stroke Assoc. 2019, 28, 859–868. [Google Scholar] [CrossRef]
  14. Lahoud, N. A Retrospective Analysis of 254 Acute Stroke Cases Admitted to Two University Hospitals in Beirut: Classification and Associated Factors. Funct. Neurol. 2017, 32, 41. [Google Scholar] [CrossRef]
  15. Lebanon. Available online: https://data.who.int/countries/422 (accessed on 1 March 2025).
  16. Gifford, A.; Biffi, A.; Gelaye, B.; Chemali, Z. Shedding Light on the Causes and Characteristics of Stroke in Lebanon: A Systematic Review of Literature. J. Geriatr. Psychiatry Neurol. 2022, 35, 655–662. [Google Scholar] [CrossRef]
  17. Kamal, H.; Assaf, S.; Kabalan, M.; El Maissi, R.; Salhab, D.; Rahme, D.; Lahoud, N. Evaluation of Stroke Pre-Hospital Management in Lebanon from Symptoms Onset to Hospital Arrival and Impact on Patients’ Status at Discharge: A Pilot Study. BMC Neurol. 2022, 22, 494. [Google Scholar] [CrossRef]
  18. Maalouf, E.; Hallit, S.; Salameh, P.; Hosseini, H. Depression, Anxiety, Insomnia, Stress, and the Way of Coping Emotions as Risk Factors for Ischemic Stroke and Their Influence on Stroke Severity: A Case-Control Study in Lebanon. Front. Psychiatry 2023, 14, 1097873. [Google Scholar] [CrossRef]
  19. Malek, E.G.; Elbejjani, M.; Abbas, R.; Abed Al Ahad, M.; Isma’eel, H.; Makki, A. TOAST Classification and Risk Factors of Ischemic Stroke in Lebanon. Acta Neurol. Scand. 2020, 141, 294–300. [Google Scholar] [CrossRef]
  20. El-Hajj, M.; Ajrouche, R.; Zein, S.; Rachidi, S.; Awada, S.; Al-Hajje, A. Evaluation of Risk Factors and Drug Adherence in the Occurrence of Stroke in Patients with Atrial Fibrillation. Pharm. Pract. 2020, 18, 1860. [Google Scholar] [CrossRef]
  21. El Masri, J.; Finge, H.; Afyouni, A.; Baroud, T.; Ajaj, N.; Ghazi, M.; El Masri, D.; Younes, M.; Salameh, P.; Hosseini, H. The Effects of Green Spaces and Noise Exposure on the Risk of Ischemic Stroke: A Case-Control Study in Lebanon. Int. J. Environ. Res. Public Health 2024, 21, 1382. [Google Scholar] [CrossRef]
  22. El Masri, J.; Finge, H.; Baroud, T.; Ajaj, N.; Houmani, M.; Ghazi, M.; Younes, M.; Salameh, P.; Hosseini, H. Adherence to Dietary Approaches to Stop Hypertension (DASH) Diet as a Protective Factor for Ischemic Stroke and Its Influence on Disability Level: A Case-Control Study in Lebanon. Nutrients 2024, 16, 3179. [Google Scholar] [CrossRef]
  23. Khaku, A.S.; Tadi, P. Cerebrovascular Disease. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  24. Iqbal, A.M.; Jamal, S.F. Essential Hypertension. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  25. Hill, M.F.; Bordoni, B. Hyperlipidemia. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  26. Office of the Surgeon General (US); National Heart, Lung, and Blood Institute (US). INTRODUCTION: Definitions of Deep Vein Thrombosis and Pulmonary Embolism. In The Surgeon General’s Call to Action to Prevent Deep Vein Thrombosis and Pulmonary Embolism; Office of the Surgeon General (US): Washington, DC, USA, 2008. Available online: https://www.ncbi.nlm.nih.gov/books/NBK44178/ (accessed on 1 March 2025).
  27. Nesheiwat, Z.; Goyal, A.; Jagtap, M. Atrial Fibrillation. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  28. Pescador Ruschel, M.A.; De Jesus, O. Migraine Headache. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  29. Ojha, N.; Dhamoon, A.S. Myocardial Infarction. In StatPearls; StatPearls Publishing: Treasure Island, FL, USA, 2024. [Google Scholar]
  30. Pożarowszczyk, N.; Kurkowska-Jastrzębska, I.; Sarzyńska-Długosz, I.; Nowak, M.; Karliński, M. Reliability of the Modified Rankin Scale in Clinical Practice of Stroke Units and Rehabilitation Wards. Front. Neurol. 2023, 14, 1064642. [Google Scholar] [CrossRef]
  31. Soto-Cámara, R.; González-Bernal, J.J.; González-Santos, J.; Aguilar-Parra, J.M.; Trigueros, R.; López-Liria, R. Age-Related Risk Factors at the First Stroke Event. J. Clin. Med. 2020, 9, 2233. [Google Scholar] [CrossRef]
  32. Webb, A.J.S.; Werring, D.J. New Insights Into Cerebrovascular Pathophysiology and Hypertension. Stroke 2022, 53, 1054–1064. [Google Scholar] [CrossRef]
  33. Oliveros, E.; Patel, H.; Kyung, S.; Fugar, S.; Goldberg, A.; Madan, N.; Williams, K.A. Hypertension in Older Adults: Assessment, Management, and Challenges. Clin. Cardiol. 2020, 43, 99–107. [Google Scholar] [CrossRef]
  34. Guthmann, R.; Davis, N.; Brown, M.; Elizondo, J. Visit Frequency and Hypertension. J. Clin. Hypertens. 2007, 7, 327–332. [Google Scholar] [CrossRef]
  35. Machaalani, M.; Seifeddine, H.; Ali, A.; Bitar, H.; Briman, O.; Chahine, M.N. Knowledge, Attitude, and Practice Toward Hypertension Among Hypertensive Patients Residing in Lebanon. Vasc. Health Risk Manag. 2022, 18, 541–553. [Google Scholar] [CrossRef]
  36. Bou Sanayeh, E.; El Chamieh, C. The Fragile Healthcare System in Lebanon: Sounding the Alarm about Its Possible Collapse. Health Econ. Rev. 2023, 13, 21. [Google Scholar] [CrossRef]
  37. Griffin, G. Antiplatelet Therapy and Anticoagulation in Patients with Hypertension. Am. Fam. Physician 2005, 71, 897–899. [Google Scholar]
  38. Prasad, M.; Khanna, P.; Katyal, V.K.; Verma, R. Acute Psychological Stress Is a Trigger for Stroke: A Case-Crossover Study. J. Stroke Cerebrovasc. Dis. 2020, 29, 104799. [Google Scholar] [CrossRef]
  39. Reddin, C.; Murphy, R.; Hankey, G.J.; Judge, C.; Xavier, D.; Rosengren, A.; Ferguson, J.; Alvarez-Iglesias, A.; Oveisgharan, S.; Iversen, H.K.; et al. Association of Psychosocial Stress With Risk of Acute Stroke. JAMA Netw. Open 2022, 5, e2244836. [Google Scholar] [CrossRef]
  40. Guiraud, V.; Touzé, E.; Rouillon, F.; Godefroy, O.; Mas, J.-L. Stressful Life Events as Triggers of Ischemic Stroke: A Case-Crossover Study. Int. J. Stroke Off. J. Int. Stroke Soc. 2013, 8, 300–307. [Google Scholar] [CrossRef]
  41. Adamczyk, K. Voluntary and Involuntary Singlehood and Young Adults’ Mental Health: An Investigation of Mediating Role of Romantic Loneliness. Curr. Psychol. 2017, 36, 888–904. [Google Scholar] [CrossRef]
  42. Le, H.T.; Lai, A.J.X.; Sun, J.; Hoang, M.T.; Vu, L.G.; Pham, H.Q.; Nguyen, T.H.; Tran, B.X.; Latkin, C.A.; Le, X.T.T.; et al. Anxiety and Depression Among People Under the Nationwide Partial Lockdown in Vietnam. Front. Public Health 2020, 8, 589359. [Google Scholar] [CrossRef]
  43. Rink, L.C.; Oyesanya, T.O.; Adair, K.C.; Humphreys, J.C.; Silva, S.G.; Sexton, J.B. Stressors Among Healthcare Workers: A Summative Content Analysis. Glob. Qual. Nurs. Res. 2023, 10, 23333936231161127. [Google Scholar] [CrossRef]
  44. Soto-Cámara, R.; González-Bernal, J.; Aguilar-Parra, J.M.; Trigueros, R.; López-Liria, R.; González-Santos, J. Factors Related to Prehospital Time in Caring for Patients with Stroke. Emergencias 2021, 33, 454–463. [Google Scholar]
  45. Stubberud, A.; Buse, D.C.; Kristoffersen, E.S.; Linde, M.; Tronvik, E. Is There a Causal Relationship between Stress and Migraine? Current Evidence and Implications for Management. J. Headache Pain 2021, 22, 155. [Google Scholar] [CrossRef]
  46. Lawless, M.H.; Harrison, K.A.; Grandits, G.A.; Eberly, L.E.; Allen, S.S. Perceived Stress and Smoking-Related Behaviors and Symptomatology in Male and Female Smokers. Addict. Behav. 2015, 51, 80–83. [Google Scholar] [CrossRef]
  47. Hawkins, B.T.; Brown, R.C.; Davis, T.P. Smoking and Ischemic Stroke: A Role for Nicotine? Trends Pharmacol. Sci. 2002, 23, 78–82. [Google Scholar] [CrossRef]
  48. Oza, R.; Rundell, K.; Garcellano, M. Recurrent Ischemic Stroke: Strategies for Prevention. Am. Fam. Physician 2017, 96, 436–440. [Google Scholar]
  49. Flach, C.; Muruet, W.; Wolfe, C.D.A.; Bhalla, A.; Douiri, A. Risk and Secondary Prevention of Stroke Recurrence. Stroke 2020, 51, 2435–2444. [Google Scholar] [CrossRef]
  50. Saade, S.; Hallit, S.; Salameh, P.; Hosseini, H. Knowledge and Response to Stroke Among Lebanese Adults: A Population-Based Survey. Front. Public Health 2022, 10, 891073. [Google Scholar] [CrossRef]
  51. Saade, S.; Kobeissy, R.; Sandakli, S.; Malaeb, D.; Lahoud, N.; Hallit, S.; Hosseini, H.; Salameh, P. Medication Adherence for Secondary Stroke Prevention and Its Barriers among Lebanese Survivors: A Cross-Sectional Study. Clin. Epidemiol. Glob. Health 2021, 9, 338–346. [Google Scholar] [CrossRef]
  52. Busch, M.A.; Schienkiewitz, A.; Nowossadeck, E.; Gößwald, A. Prevalence of stroke in adults aged 40 to 79 years in Germany: Results of the German Health Interview and Examination Survey for Adults (DEGS1). Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2013, 56, 656–660. [Google Scholar] [CrossRef]
  53. Stahmeyer, J.T.; Stubenrauch, S.; Geyer, S.; Weissenborn, K.; Eberhard, S. The Frequency and Timing of Recurrent Stroke. Dtsch. Ärztebl. Int. 2019, 116, 711–777. [Google Scholar] [CrossRef]
Jcm 14 02034 g001
Figure 1. Distribution of patients by age at diagnosis (A), number of stroke incidents (B), and disability level (C).
Figure 1. Distribution of patients by age at diagnosis (A), number of stroke incidents (B), and disability level (C).
Jcm 14 02034 g001
Jcm 14 02034 g002
Figure 2. Decision tree model for age at first ischemic stroke incidence.
Figure 2. Decision tree model for age at first ischemic stroke incidence.
Jcm 14 02034 g002
Jcm 14 02034 g003
Figure 3. Decision tree model for number of ischemic stroke events.
Figure 3. Decision tree model for number of ischemic stroke events.
Jcm 14 02034 g003
Table 1. Sociodemographic characteristics of the sample included.
Table 1. Sociodemographic characteristics of the sample included.
FactorCategoryNumberPercentage
AgeMean ± SD68.589 ± 13.436
GenderFemale10348.13
Male11151.86
Marital statusWith a partner11955.6
Without a partner9544.4
GovernorateNorth 115.1
Beirut 9946.3
South 5726.6
Mount Leb 209.3
Bekaa 2712.6
EducationNot educated5123.83
School education9946.26
University education6429.91
EmploymentNot employed15271.03
Employed3114.48
Freelance profession3114.48
IncomeLow7133.2
Moderate12960.3
High286.5
Residency locationRural5525.7
Urban15974.3
Table 2. Description of health-related risk factors in the sample included.
Table 2. Description of health-related risk factors in the sample included.
FactorCategoryNumberPercentage
SmokingYes12658.88
No8841.12
Family historyYes10549.06
No10950.94
HypertensionYes19490.65
No209.35
HyperlipidemiaYes15170.56
No6329.44
DVT or PEYes2711.21
No18787.39
Atrial fibrillationYes7434.58
No14065.42
MigraineYes2813.08
No18686.92
Myocardial infarctionYes4922.9
No16577.1
Table 3. Bivariate analysis of age at first stroke and number of strokes.
Table 3. Bivariate analysis of age at first stroke and number of strokes.
FactorCategoryAge at 1st StrokeNumber of StrokesStroke Recurrence
Mean ± SDp-ValueMean ± SDp-ValueYesNop-Value
GenderFemale68.75 ± 14.0390.2811.34 ± 0.57 0.88430 (23.07%)73 (76.93%)0.923
Male66.77 ± 12.5331.38 ± 0.66133 (29.73%)78 (70.27%)
Marital statusWith a partner74.87 ± 11.508 <0.001 *1.37 ± 0.62 0.89128 (29.47%)67 (70.53%)0.992
Without a partner62.02 ± 11.7931.35 ± 0.619 35 (29.41)84 (70.59%)
GovernorateNorth70.45 ± 12.421 0.151.18 ± 0.4050.381 2 (18.18%)9 (81.82%)0.317
Beirut68.34 ± 13.3131.39 ± 0.66731 (31.31%)68 (68.69%)
South69.63 ± 12.0591.28 ± 0.5912 (21.05%)45 (78.95%)
Mount Lebanon 63.95 ± 13.8471.35 ± 0.4897 (35%)13 (65%)
Bekaa63.11 ± 14.8131.48 ± 0.643 11 (40.74%)16 (59.26%)
EducationNot educated75.92 ± 9.718<0.001 * 1.67 ± 0.887<0.001 *22 (43.1429 (56.86%)0.027 *
School education69.13 ± 10.5581.3 ± 0.50428 (28.28%)71 (71.72%)
University education59.02 ± 14.6221.2 ± 0.40613 (20.31%)51 (79.69%)
EmploymentNot employed72.76 ± 10.299 <0.001 *1.44 ± 0.6680.004 *54 (35.53%)98 (64.47%)0.004 *
Employed51.13 ± 12.0051.23 ± 0.4257 (22.58%)24 (77.42%)
Freelance profession59.61 ± 9.6251.1 ± 0.396 2 (6.45%)29 (93.55%)
IncomeLow67.83 ± 10.1910.151.41 ± 0.6670.76723 (32.39%)48 (67.61%)0.799
Moderate68.02 ± 14.0611.33 ± 0.59136 (27.91%)93 (72.09%)
High64.5 ± 14.8671.36 ± 0.6334 (28.57%)10 (71.43%)
Residency locationRural66.49 ± 12.9930.421.45 ± 0.6890.24119 (34.55%)36 (65.45%)0.335
Urban68.15 ± 13.3981.33 ± 0.5944 (27.67%)115 (72.33%)
*: Statistically significant.
Table 4. Bivariate association between age at first stroke and number of stroke incidents with health-related risk factors.
Table 4. Bivariate association between age at first stroke and number of stroke incidents with health-related risk factors.
FactorCategoryAge at First StrokeNumber of StrokesStroke Recurrence
Mean ± SDp-ValueMean ± SDp-ValueYesNop-Value
SmokingYes64.5 ± 11.43<0.001 * 1.33 ± 0.6450.17632 (25.4%)94 (74.6%)0.121
No72.34 ± 14.4141.4 ± 0.578 31 (35.23%)57 (64.77%)
Family historyYes65.5 ± 14.6850.016 * 1.48 ± 0.6810.005 * 40 (38.1%)65 (61.9%)0.006 *
No69.87 ± 11.4421.25 ± 0.53 23 (21.1%)86 (78.9%)
HypertensionYes69.42 ± 11.267<0.001 *1.39 ± 0.6370.012 * 62 (31.96%)132 (68.04%)0.012 *
No51.25 ± 19.3361.05 ± 0.224 1 (5%)19 (95%)
HyperlipidemiaYes71.15 ± 10.471<0.001 *1.46 ± 0.681<0.001 *55 (36.42%)96 (63.57%)0.001 *
No59.51 ± 15.6141.13 ± 0.336 8 (12.7%)55 (87.3%)
DVT or PEYes73.07 ± 12.7640.025 *1.63 ± 0.839 0.041 * 51 (44.44)136 (55.56%)0.067
No66.95 ± 13.2131.32 ± 0.57112 (27.27%)15 (72.73)
Atrial fibrillationYes69.95 ± 10.9940.0751.57 ± 0.76 0.001 * 31 (43.24%)109 (56.76%)0.001 *
No66.55 ± 14.2461.25 ± 0.49632 (22.14%)42 (77.86%)
MigraineYes54.71 ± 14.616<0.001 *1.25 ± 0.441 0.472 56 (25%)130 (75%)0.58
No69.68 ± 11.9391.38 ± 0.6397 (30.1%) 21 (69.9%)
Myocardial infarctionYes71.12 ± 9.4820.041 *1.45 ± 0.679 0.22045 (36.73%)120 (63.27%)0.202
No66.72 ± 14.0861.33 ± 0.59818 (27.27) 31 (72.73)
*: Statistically significant.
Table 5. Bivariate association between age at first stroke and number of stroke incidents with disability levels.
Table 5. Bivariate association between age at first stroke and number of stroke incidents with disability levels.
FactorCategoryAge at First StrokeNumber of StrokesStroke Recurrence
Mean ± SDp-ValueMean ± SDp-ValueYesNop-Value
mRS categoryMild disability or no symptoms62.7 ± 15.66<0.001 *1.18 ± 0.390.05 *11 (18.33%)49 (81.66%)0.082
Moderate disability68.43 ± 11.7431.42 ± 0.6438 (34.23%)73 (65.77%)
Severe disability or death72.91 ± 11.1561.44 ± 0.76514 (32.56%)29 (67.44%)
*: Statistically significant.
Table 6. Multivariable analysis: correlates of age at first stroke incidence with risk factors.
Table 6. Multivariable analysis: correlates of age at first stroke incidence with risk factors.
ParameterBStd. Errorp-Value95% Confidence Interval
Lower BoundUpper Bound
Intercept54.7532.7330.00049.36560.141
Marital status
With partner vs. no partner *6.0581.3850.0003.3268.789
Education
Not educated vs. university education *5.5121.8280.0031.9069.117
School vs. university education *2.2461.5610.152−0.8325.324
Employment status
Not employed vs. freelancer *7.9831.8960.0004.24411.721
Employed vs. freelancer *−4.5182.2460.046−8.947−0.088
Other lifestyle factors and comorbidities
Smoking−2.9291.3160.027−5.525−0.334
Family history of stroke−2.3031.1700.050−4.6110.004
Hypertension5.0642.2560.0260.6159.513
Hyperlipidemia3.3781.4550.0210.5096.248
DVT or PE−0.9391.8080.604−4.5042.626
Atrial fibrillation−1.3371.2710.294−3.8441.170
Migraine−9.1091.8170.000−12.693−5.525
Myocardial infarction2.4771.4340.086−0.3515.304
*: reference; dependent variable: age at first stroke.
Table 7. Multivariable analysis: forward logistic regression taking the recurrence of stroke incidents with sociodemographic and risk factors.
Table 7. Multivariable analysis: forward logistic regression taking the recurrence of stroke incidents with sociodemographic and risk factors.
Parameterp-ValueORa
[Exp(B)]		95% Confidence Interval
LowerUpper
Employment status0.018
Employed vs. Not employed *0.0059.5911.97646.56
Freelancer vs. Not employed *0.0446.0361.05334.61
Partner vs. No partner *0.0362.1361.054.345
Family history of stroke0.0013.2511.6256.505
Hyperlipidemia0.0043.7101.5159.085
Atrial fibrillation0.0082.5211.2724.999
Constant0.0000.011
*: reference category; dependent variable: stroke recurrence.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

El Masri, J.; El Masri, D.; Ghazi, M.; Afyouni, A.; Finge, H.; El Ahdab, J.; Tlayss, M.; Al Chaar, S.; Abou-Kheir, W.; Salameh, P.; et al. Description of the Risk Factors for Ischemic Stroke in the Lebanese Population: Their Association with Age at First Stroke Incidence and the Predictors of Recurrence. J. Clin. Med. 2025, 14, 2034. https://doi.org/10.3390/jcm14062034

AMA Style

El Masri J, El Masri D, Ghazi M, Afyouni A, Finge H, El Ahdab J, Tlayss M, Al Chaar S, Abou-Kheir W, Salameh P, et al. Description of the Risk Factors for Ischemic Stroke in the Lebanese Population: Their Association with Age at First Stroke Incidence and the Predictors of Recurrence. Journal of Clinical Medicine. 2025; 14(6):2034. https://doi.org/10.3390/jcm14062034

Chicago/Turabian Style

El Masri, Jad, Diala El Masri, Maya Ghazi, Ahmad Afyouni, Hani Finge, Jad El Ahdab, Maryam Tlayss, Soltan Al Chaar, Wassim Abou-Kheir, Pascale Salameh, and et al. 2025. "Description of the Risk Factors for Ischemic Stroke in the Lebanese Population: Their Association with Age at First Stroke Incidence and the Predictors of Recurrence" Journal of Clinical Medicine 14, no. 6: 2034. https://doi.org/10.3390/jcm14062034

APA Style

El Masri, J., El Masri, D., Ghazi, M., Afyouni, A., Finge, H., El Ahdab, J., Tlayss, M., Al Chaar, S., Abou-Kheir, W., Salameh, P., & Hosseini, H. (2025). Description of the Risk Factors for Ischemic Stroke in the Lebanese Population: Their Association with Age at First Stroke Incidence and the Predictors of Recurrence. Journal of Clinical Medicine, 14(6), 2034. https://doi.org/10.3390/jcm14062034

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop