Metabolic syndrome and cardiovascular risk factors among bank employees in iran: a cross-sectional study

Abstract

Background

Metabolic syndrome (MetS) and cardiovascular disease (CVD) are growing occupational health concerns, particularly among sedentary and high-stress professions. This study investigates the prevalence of MetS and related cardiovascular risk factors among Iranian bank employees.

Methods

This cross-sectional study included 1,661 bank employees in Tehran, enrolled between January and March 2023. Participants completed physician interviews, provided fasting blood samples, and underwent clinical assessments. Demographic and occupational data, smoking status, blood pressure, and biochemical markers were collected. MetS was defined using ATP III criteria, and 10-year ASCVD risk was calculated using the 2019 ACC/AHA Pooled Cohort Equations. Data analysis was performed with SPSS 27.

Results

Among participants, the mean age was 43.4 (5.9) years, and a body mass index of 27.3 (4) kg/m² (73.5% men; 91.8% non-smokers) were included. The prevalence of MetS was 26.2% (95% confidence interval [95%CI]: 24.1–28.3), with low HDL cholesterol as the most frequent component. Compared to operational staff, management employees had significantly higher odds of key MetS components, including high blood pressure (52.7% vs. 44.1%; OR: 1.41, 95% CI: 1.16–1.71; P = 0.001), elevated triglycerides (33.4% vs. 26.2%; odds ratio [OR]: 1.41, 95% CI: 1.14–1.75; P = 0.002), elevated FBS (10.9% vs. 5.5%; OR: 2.09, 95% CI: 1.45–3.01; P < 0.001), low HDL (82.3% vs. 70.4%; OR: 1.96, 95% CI: 1.54–2.49; P < 0.001), and abdominal obesity (26.9% vs. 18.5%; OR: 1.62, 95% CI: 1.28–2.05; P < 0.001). Older age (adjusted OR: 1.03, 95% CI: 1.01–1.05; P < 0.001) and managerial roles (adjusted OR: 0.71, 95% CI: 0.56–0.91; P < 0.001) were significant determinants of MetS. The median ASCVD risk score was higher in men than women (2.2 [IQR: 1.4–3.7] vs. 0.6 [0.4–0.9]; P < 0.001) and in management staff compared to operational staff (2.2 [1.3–3.7] vs. 0.3 [0.7–2.4]; P < 0.001). Age (adjusted OR: 1.17, 95% CI: 1.14–1.20; P < 0.001) and management position (adjusted OR: 2.24, 95% CI: 1.70–2.95; P < 0.001) were independently associated with increased ASCVD risk.

Conclusion

MetS is prevalent among Iranian bank employees, with older age, male sex, and managerial positions identified as significant associated factors. These findings underscore the need for targeted workplace health interventions and further research to evaluate cardiometabolic risk across occupational settings.

Introduction

Cardiovascular diseases (CVD) remain a leading cause of global morbidity and mortality, contributing to approximately 32% of deaths worldwide annually [1]. CVD comprises both non-modifiable risk factors, such as male gender, old age, and family history, and modifiable risk factors, including hypertension, dyslipidemia, smoking, diabetes, obesity, and sedentary lifestyle [2]. Sedentary behavior, a defining characteristic of many administrative and financial roles, has adversely affected cardiometabolic health by promoting insulin resistance, metabolic dysfunction, and unfavourable lipid profiles [3, 4]. In recent decades, growing attention has been directed toward occupational risk factors that predispose individuals to CVD, particularly in sedentary work environments such as office-based professions. Among these, banking occupations are of specific concern due to prolonged sitting, physical inactivity, and elevated occupational stress [5]. Consequently, prolonged sitting reduces energy expenditure and disrupts lipid metabolism, contributing to elevated triglyceride (TG) levels and decreased high-density lipoprotein (HDL) cholesterol concentrations [4].

Prior observational studies have demonstrated that individuals with high levels of sedentary behaviour have a significantly increased risk (up to 73%) of developing metabolic syndrome (MetS), a cluster of interrelated conditions associated with elevated CVD risk [6]. Beyond physical inactivity, psychosocial stress within the workplace is increasingly recognised as a critical risk factor for metabolic and cardiovascular disorders. High job demands, particularly in managerial or supervisory roles, have been associated with hormonal dysregulation, central adiposity, and increased cardiometabolic burden [7–9]. Chronic exposure to occupational stress has been linked to a twofold increase in the likelihood of developing MetS, particularly in professions characterized by high responsibility and limited autonomy [10, 11].

In Iran, the prevalence of CVD is on the rise, primarily attributed to rapid urbanization, changes in dietary habits, and reduced physical activity levels [12]. MetS, a significant precursor of CVD, affects nearly 30.4% of the Iranian population, exceeding global averages [13]. The burden of its constituent risk factors, including central obesity, hyperglycemia, hypertension, and dyslipidemia, is especially pronounced in urban populations engaged in predominantly sedentary work. Although some studies have explored MetS among Iranian occupational groups, comprehensive assessments among bank employees remain limited, despite indications that they may face heightened cardiometabolic risk due to their work environment [14, 15].

As a result, risk-based tools such as the Atherosclerotic Cardiovascular Disease (ASCVD) can be utilized to develop personalized prevention strategies and categorize individuals in relation to future cardiovascular risk [16]. This instrument consists of demographic and clinical parameters to estimate 10-year risk and is widely recommended for clinical decision-making in primary prevention settings [17, 18]. Despite its public health relevance, limited research has been conducted on the cardiometabolic health of bank employees in Iran. To address this gap, the present study aims to assess the prevalence of MetS and estimate 10-year ASCVD risk in a large sample of Iranian bank workers.

Materials and methods

Study design and setting

From January to March 2023, this cross-sectional study was conducted among employees of various bank branches across Tehran, Iran.

Sample size and eligibility

The required sample size was calculated based on an estimated 30% prevalence of MetS, a 95% confidence level, a 3% margin of error, and a design effect of 1.5 for clustering, yielding a minimum of 1,346 participants. To allow for incomplete data, 1,661 employees were ultimately enrolled. Calculations were performed using G*Power (version 3.1.9.7, Universität Düsseldorf). Eligible participants were bank employees aged 23–67 with at least one year of continuous employment and the ability to provide informed consent. Individuals with incomplete demographic or laboratory data were excluded.

Sampling method

A stratified cluster sampling approach with random selection was utilized, stratifying bank branches by administrative level (regional headquarters vs. local branches). Employees were randomly selected within each stratum to ensure balanced representation across job categories. The design effect was incorporated into sample size calculation and statistical analyses to account for clustering.

Data collection and procedures

Demographic and occupational characteristics

Demographic data, including age, sex, and smoking status, were collected using a standardized checklist. Smoking status was categorized into three groups: non-smoker, current smoker, and quitter. According to hierarchical roles and responsibilities, job titles were classified as management or operational staff.

Anthropometric and clinical measurements

• Body Mass Index: Calculated as weight (kg) divided by height squared (m²) and categorized according to the World Health Organization (WHO) guidelines as underweight (< 18.5), normal (18.5–24.9), overweight (25–29.9), or obese (≥ 30).

• Blood Pressure: A trained physician performed BP measurements using a digital Omron M2 sphygmomanometer (Omron, Japan). Two blood pressure measurements were taken at one-minute intervals after participants rested for five minutes. Measurement was recorded as the mean of two readings. According to ATP III guidelines, elevated blood pressure is defined as systolic blood pressure of 130 mmHg or diastolic blood pressure of 85 mmHg or the use of antihypertensive medication.

• Waist circumference: To measure waist circumference (WC), a non-stretchable measuring tape should be positioned parallel to the floor without compressing the skin. Ensure that participants stand upright, exhale normally, and wear minimal clothing when measuring. The WC values are recorded to the closest 0.1 cm. Abdominal obesity is defined as ≥ 102 cm in men and ≥ 88 cm in women, based on ATP III criteria, while accounting for ethnic-specific cut-offs when applicable.

Laboratory assessments

After a 12-hour overnight fast, fasting blood samples (10 mL) were taken from participants. An analysis of biochemical parameters, including total cholesterol, TG, HDL, LDL, and fasting blood sugar (FBS), was performed using a Roche Hitachi 912 Chemistry Analyzer (GMI, Japan). The following criteria were used to define abnormal values based on ATP III [19]:

• Elevated TG: ≥ 150 mg/dL.

• Low HDL cholesterol: < 40 mg/dL in men and < 50 mg/dL in women.

• Elevated FBS: ≥ 100 mg/dL.

• Abdominal obesity: Waist circumference ≥ 102 cm in men and ≥ 88 cm in women.

Definition of metabolic syndrome

According to ATP III guidelines [19], MetS is the presence of at least three of the following components: abdominal obesity, elevated TG, low HDL cholesterol, elevated BP, or elevated FBS.

Atherosclerotic cardiovascular disease (ASCVD) risk score

The 10-year risk of ASCVD was calculated using the Pooled Cohort Equations from the 2019 ACC/AHA guideline [20], implemented through the ASCVD Risk Calculator (© QxMD Software Inc., 2020), which incorporates age, sex, systolic BP, total cholesterol, HDL cholesterol, smoking status, and diabetes status. The score ranges from 0 to > 30%, with ≥ 7.5% indicating elevated risk for primary prevention purposes.

Statistical analysis

Continuous variables were tested for normality using the Kolmogorov–Smirnov test. Moreover, normally distributed data were reported as mean (standard deviation [SD]), and skewed variables as median [interquartile range]. Also, independent t-tests or Mann–Whitney U tests (for non-normal distributions) and chi-square tests were used for group comparisons. Before modeling, assumptions for normality, homogeneity of variance, absence of multicollinearity, and lack of influential outliers were assessed. In addition, logistic regression models were applied to assess associations between MetS components and job categories, with odds ratios (ORs) and 95% confidence intervals (CIs) reported. In detail, multivariable logistic regression was controlled for age, sex, smoking status, and job title as confounders. A forward stepwise approach was used, considering the complex sampling design. Furthermore, Spearman’s rho was utilized to assess the correlation between age and ASCVD risk score, given the non-normal distribution of the data. Additionally, participants with missing key variables required for MetS or ASCVD calculation were not excluded immediately. Sensitivity analysis was conducted using complete case and available case approaches. Patterns of missingness were assessed; missing data were deemed missing at random (MAR), and imputation was not applied due to low missing rates (< 5%). A p-value of < 0.05 was also considered statistically significant. All statistical analyses were performed using SPSS software (version 27.0.1.0, IBM Corp., Armonk, NY, USA.).

Results

Baseline characteristics of study participants

A total of 1,661 bank employees were included in the analysis, with a mean age of 43.4 (5.9) years and an average BMI of 27.3 (4) kg/m², indicating an overall overweight population. The majority of participants (73.5%) were men, and most (91.8%) were non-smokers. Operational staff and management staff accounted for 59.8% and 40.2% of participants, respectively (Table 1).

Table 1.

Baseline characteristics of the study population

Characteristicsa	Total population (n = 1661)
Gender (Male), n (%)	1221(73.5)
Age, Mean ± SD	43.4 ± 5.9
Body mass index, Mean ± SD	27.3 ± 4
Job title, n (%)
Operational staff	993(59.8)
Management staff	668 (40.2)
Smoking, n (%)
No	1512 (91.8)
Current	111 (6.7)
Quited	24 (1.5)

^aData are presented as mean ± standard deviation for continuous and number (Percentage calculated for rows) for categorical variables

Prevalence of MetS components

According to ATP III criteria, management staff depicted a higher prevalence of key MetS components than operational staff (Table 2; Fig. 1). In the details, high BP was present in 52.7% of management staff versus 44.1% of operational staff (P = 0.001; OR: 1.41, 95% CI: 1.16–1.71), while elevated TG levels were observed in 33.4% and 26.2%, respectively (P = 0.002; OR: 1.41, 95% CI: 1.14–1.75). FBS was raised in 10.9% of management staff compared to 5.5% of operational staff (P < 0.001; OR: 2.09, 95% CI: 1.45–3.01). Low HDL cholesterol was prevalent in 82.3% of management staff versus 70.4% of operational staff (P < 0.001; OR: 1.96, 95% CI: 1.54–2.49). Abdominal obesity was observed in 26.9% of management staff compared to 18.5% of operational staff (P < 0.001; OR: 1.62, 95% CI: 1.28–2.05).

Table 2.

Crude odds ratios for MetS components between job categories (management versus operational staff) based on ATP III criteria

Metabolic syndrome components (ATP III)	Operational staff (n = 993)	Management staff (n = 668)	Crude Odds ratio (95%CI)	P-value*
High blood pressure	438 (44.1)	352 (52.7)	1.41 (1.16–1.71)	0.001
High triglyceride	260 (26.2)	223 (33.4)	1.41 (1.14–1.75)	0.002
High fasting blood sugar	55(5.5)	73 (10.9)	2.09 (1.45–3.01)	< 0.001
High waist circumference	184 (18.5)	180 (26.9)	1.62 (1.28–2.05)	< 0.001
Low HDL	699 (70.4)	550 (82.3)	1.96 (1.54–2.49)	< 0.001

Abbreviation: CI Confidence interval; High-density lipoprotein

All odds ratios are unadjusted, and operational staff is used as the reference group.

*P < 0.05 was considered statistically significant.

Fig. 1.

The prevalence of metabolic syndrome (MetS) according to ATP III criteria, along with the frequency of each component, was illustrated among the study population

Association of MetS with demographic and Job-Related factors

Participants with MetS were older than those without MetS (adjusted OR: 1.03, 95% CI: 1.01–1.05, P < 0.001; Table 3). In addition, men had higher odds of MetS compared to women (32.8% vs. 7.8%; unadjusted OR: 5.8, 95% CI: 4.0–8.4), and this association remained significant after adjusting for age, job title, and smoking status (adjusted OR: 5.8, 95% CI: 4.0–8.4, P < 0.001). In detail, both crude and adjusted ORs for age and gender were similar, indicating strong independent associations with MetS. Furthermore, smoking status showed no significant association after adjustment (adjusted OR: 0.96, 95% CI: 0.71–1.31). Job title remained a significant determinant, with management staff showing higher odds of MetS than operational staff (adjusted OR: 0.71, 95% CI: 0.56–0.91, P < 0.001).

Table 3.

Association of demographic and occupational variables with MetS (Unadjusted and adjusted odds ratios)

Variables	MetS negative (n = 1226)	MetS positive (n = 435)	Unadjusted OR (95% CI)	P-value*	Adjusted OR (95% CI)	P-value
Age, mean ± SD	42.9 ± 6	44.9 ± 5.5	1.03 (1.01–1.05)	< 0.001	1.03 (1.01–1.05)	< 0.001
Gender, n (%)				< 0.001		< 0.001
Female	403 (92.2)	34 (7.8)	Ref		Ref
Male	820 (67.2)	401 (32.8)	5.8 (4-8.4)		5.8 (4.0–8.4)
Smoking, n (%)				0.017		< 0.001
No	1123 (74.3)	389 (25.7)	Ref		Ref
Yes	103 (69.1)	46 (30.9)	1.3 (0.9–1.8)		0.96 (0.71–1.31)
Job title, n (%)				< 0.001		< 0.001
Operational staff	778 (78.3)	215 (21.7)	Ref		Ref
Management staff	448 (67.1)	220 (32.9)	1.8 (1.4–2.1)		0.71(0.56–0.91)
Univariate and multivariable logistic regression models report odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted models included age, sex, smoking status, and job title. Abbreviation: MetS Metabolic syndrome *P < 0.05 was considered statistically significant

Distribution of ASCVD risk scores and determinants

The ASCVD risk score was considerably higher in men (Median: 2.2 [IQR: 1.4, 3.7] vs. Median: 0.6 [IQR: 0.4, 0.9] for women, P < 0.001) and in management staff (Median: 2.2 [IQR: 1.3, 3.7] vs. Median: 0.3 [IQR: 0.7, 2.4] in operational staff, P < 0.001). A strong positive correlation was also observed between age and ASCVD risk score (Spearman’s rho: 0.64, P < 0.001; Table 4). Multivariate analysis identified age and job title as significant determinants of high ASCVD risk (Table 5). Each additional year of age increased the odds by 3% (adjusted OR: 1.17, 95% CI: 1.14–1.20, P < 0.001). Management staff had more than double the risk of operational staff (adjusted OR: 2.24, 95% CI: 1.7–2.95, P < 0.001). Although men initially showed higher odds (OR: 3.95, 95% CI: 2.74–5.72), this was explained mainly by age and job-related factors after adjustment (adjusted OR: 0.31, 95% CI: 0.21–0.46, P < 0.001).

Table 4.

Distribution of ASCVD risk scores by gender, job title, and correlation with age

Variables#	Median [Interquartile range]	P-value*
Age (Spearman’s rho)	0.64	< 0.001
Gender		< 0.001
Female	0.6 [0.4, 0.9]
Male	2.2 [1.4, 3.7]
Job title		< 0.001
Operational staff	0.3 [0.7, 2.4]
Management staff	2.2 [1.3, 3.7]

*P < 0.05 was considered statistically significant

^#Continuous variables, such as age and ASCVD risk score, were reported as median [IQR], and Spearman’s rho was used for non-parametric correlation analysis

Table 5.

Association of demographic and occupational variables with ASCVD risk (Unadjusted and adjusted odds ratios)

Variables	ASCVD low score (n = 1312)	ASCVD High score (n = 349)	Unadjusted odds ratio (95% CI)	P-value*	Adjusted Odds ratio (95% CI)	P-value*
Age, mean ± SD	42.47 ± 5.65)	47.07 ± 5.82	1.17 (1.14–1.20)	< 0.001	1.17 (1.14–1.20)	< 0.001
Gender, n (%)				< 0.001		< 0.001
Female	402 (92)	35 (8)	Ref		Ref
Male	908 (74.4)	313 (25.6)	3.95 (2.74–5.72)		0.31(0.21–0.46)
Job title, n (%)
Operational staff	773(77.8)	220 (22.2)	Ref		Ref
Management staff	537(80.4)	131(19.6)	0.86 (0.67–1.09)	0.21	2.24 (1.7–2.95)	< 0.001

Univariate and multivariable logistic regression models report odds ratios (ORs) with 95% confidence intervals (CIs). Adjusted models included age, sex, smoking status, and job title

Abbreviations: ASCVD: atherosclerotic cardiovascular disease; CI: confidence interval; SD: standard deviation

*P < 0.05 was considered statistically significant

Discussion

CVD accounts for 27.0% of global mortality [21], with MetS representing a significant modifiable risk factor contributing to this burden revealed a 26.2% prevalence of MetS among bank employees in this study, aligning closely with global trends and similar occupational studies in Brazil [22] and Russia [14], where MetS prevalence was reported at 22.6% and 21.5%, respectively. These findings highlight the elevated cardiovascular risk associated with sedentary and stress-inducing occupations, such as banking [23].

MetS has a global prevalence of 25.0% [24], while in Iran, the prevalence is notably higher at 30.4% [13]. Early diagnosis, screening, treatment, and palliative care are the main parts of disease control. Since most of the risk factors of MetS are discovered and, if diagnosed in the early stages, are preventable, this study was designed to cover the research gap of CVD risk in the banking workforce in Iran.

The prevalence of MetS varies by region, with rates of 27.93% in North america, 27.65% in South america, 21.27% in asia, 16.04% in africa, and 10.47% in Europe [25]. Our study found that the prevalence of MetS among bank employees is 26.2%. In comparison, MetS prevalence in other occupational groups in Iran varies: 34.0% among drivers [26], 21.0% among locomotive drivers [27], 16.2% among nurses [28], 13.4% among military personnel [29], and 4.4% among air guard forces. This discrepancy highlights stress, prolonged sedentary behavior, and workplace-related lifestyle factors specific to the banking industry. Moreover, compared with other occupational groups, the prevalence in our study was similar to the prevalence among University employees in Angola (27.8%) [30]; however, MetS prevalence in our study was higher than that reported among Ethiopian bank employees and teachers, which was 12.5% [31]. These discrepancies highlight the impact of regional, cultural, and occupational factors on MetS prevalence.

Our study identified a 32.8% prevalence of MetS among male employees, significantly higher than the 7.8% prevalence observed among female employees. This gender disparity aligns with findings from other research. For instance, a study among bank employees in St. Petersburg, Russia, reported a higher prevalence of MetS components in males than females [14]. Conversely, another investigation diagnosed a higher proportion of female African bank workers with MetS [32]. Besides, based on the ATP III criteria, the prevalence of MetS was 10.0% in men and 16.2% in women among bank employees in Ethiopia [31]. Interestingly, studies have shown that MetS is more prevalent among males in Lebanon [33] and among workers in Germany [34]. On the other hand, MetS is more prevalent among females in the general populations of Iran [35], Turkey [36], Oman [37], and Brazil [38]. The variations could be due to sex impacts such as hormonal differences [39], lifestyle behaviors [40], and occupational stress levels [39]. These gender disparities in MetS prevalence underscore the importance of considering sex-specific factors in public health strategies and interventions aimed at reducing the burden of MetS and associated cardiovascular risks.

Our study revealed that low HDL and high BP are the most prevalent components of MetS, following high TG and WC, which is in accordance with findings in the general population of Iran and Oman [35, 37, 41], indicating low HDL as the most frequent component. Sedentary occupations, such as banking, often involve prolonged periods of sitting, contributing to increased risk factors for MetS [42]. These findings were in line with research conducted among sedentary occupational populations. Similarly, a cross-sectional study involving 35,950 sedentary workers in China reported a high prevalence of dyslipidemia, with significant associations between sedentary behavior and elevated TG levels [43]. Additionally, hypertension was prevalent among this population. Further, research on sedentary workers in South Africa illustrated that prolonged sitting time was correlated with elevated blood pressure and adverse lipid profiles, including low HDL cholesterol levels [44]. The association between occupational sitting and increased cardiovascular risk has been well-documented. A systematic review highlighted that prolonged occupational sitting is associated with higher risks of CVD and mortality [45]. This underscores the importance of addressing sedentary behavior in workplace health programs.

The observed higher prevalence of MetS among smokers (30.9%) compared to non-smokers (25.7%) is consistent with studies linking smoking to increased MetS risk. Smoking has been associated with insulin resistance and central obesity, both of which are components of MetS [25]. The results of a cross-sectional study performed in Maracaibo City, Venezuela, demonstrated that the presence of metabolic syndrome and its components was correlated to cigarette smoking, with the exception of hyperglycemia [46]. Likewise, A cross-sectional study involving 808 young adults in South Korea found that current smokers had a 2.4-fold greater risk of developing MetS compared to non-smokers [47]. The study also highlighted significant associations between smoking and components of MetS, such as hypertriglyceridemia and low HDL cholesterol levels. Given the elevated prevalence of MetS among smokers, especially in sedentary occupations like banking, targeted intervention programs are essential.

In another view, our analysis illustrated that members of the management team exhibited a higher prevalence of MetS (32.0%) compared to operational staff (21.0%). Notably, elevated FBS and low HDL cholesterol were nearly twice as prevalent among managers. This trend aligns with findings from studies in other high-stress occupations, such as workers of a petrochemical enterprise [48]. Furthermore, a prospective cohort study investigated the association between work stress and MetS among British civil servants indicated that employees experiencing chronic work stress had more than double the risk of developing MetS compared to those without work stress, which emphasizes that higher employment grades, often associated with managerial roles, correlated with increased stress levels and MetS prevalence [10]. Another cross-sectional study involving 1,683 petrochemical workers in China assessed the correlation between occupational stress and MetS. The findings showed that high occupational stress was significantly associated with an increased risk of MetS and its components, including elevated FBS and low HDL cholesterol [48]. Moreover, previous Iranian reports indicated a higher prevalence of MetS in management teams compared to operational staff among military officers, with figures of 21.8% and 19.7%, respectively [49]. A similar trend was reported in firefighters, where the prevalence of MetS was 60.3% for management teams and 56.6% for operational staff [50]. More precisely, all the MetS components were 1.5-2 times more prevalent in the management team than in the operational staff.

Aside from other findings, higher scores of ASCVD risk were detected in the male gender and management team, similar to a study on a university staff in that men had a greater risk [51]. However, females referred to health centers in a previous study carried a greater cardiovascular risk than males. This disparity could be due to the fact that women are more likely to follow up on their health situation [52]. These findings underscore the importance of implementing targeted workplace interventions to mitigate MetS and ASCVD risks among management personnel and male employees. Strategies may include stress management programs, promoting physical activity, and regular health screenings to identify and address MetS components early. By addressing occupational stressors and encouraging healthy lifestyle choices, organizations can reduce the burden of MetS and associated cardiovascular risks among their employees.

Limitations and recommendations

This study’s cross-sectional design limits the ability to infer causal relationships. Longitudinal studies are recommended to explore the long-term impact of occupational stress and sedentary behavior on CVD risk. Additionally, expanding the research to include bank employees from different regions could provide a broader understanding of the factors influencing MetS and ASCVD risk. In the case of recommendations, our results highlight the need for targeted workplace interventions aimed at reducing cardiometabolic risk among bank employees. In light of this occupation’s sedentary nature, regular cardiovascular risk assessments, structured physical activity programs, and health education could facilitate early detection and effective prevention. By implementing these measures, this high-risk occupational group may be able to reduce the long-term burden of ASCVD.

Conclusion

This study highlights a substantial prevalence of MetS among Iranian bank employees, with approximately 26.2% of the population affected. Notably, the prevalence was higher among male employees and management staff, attributed to factors such as elevated stress levels, sedentary behavior, and job hierarchy. Low HDL cholesterol and hypertension emerged as the most prevalent MetS components, underscoring the critical need for targeted interventions. Furthermore, the higher ASCVD risk scores observed among men and managers suggest that specific demographic and occupational groups within the banking industry are at greater risk for cardiovascular conditions. These findings emphasize the necessity for proactive workplace health programs, including stress management, regular physical activity, and routine health screenings, to mitigate MetS and ASCVD risks. Future research should expand to include longitudinal studies across various regions to better understand the long-term impact of occupational stress and sedentary work environments on cardiovascular health. Tailored interventions should also address the unique occupational risks faced by bank employees to reduce the overall cardiovascular disease burden and improve workforce health outcomes.

Authors' contributions

NI and AH: Study concept, data cleaning, interpretation, analysis, data collecting, and drafting the initial manuscript; NH: drafting the initial manuscript, interpretation, and revision critically; GP: Study management, revised the study critically; YH: Conceptualization, study design, supervision, data cleaning, interpretation, and revision critically. All the authors approved the final version of the manuscript.

Funding

Not applicable.

Data availability

All the data generated or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The study protocol was reviewed and approved by the Ethics Committee of Tehran University of Medical Sciences, Tehran, Iran (Approval code: IR.TUMS.MEDICINE.REC.1402.409). All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all study participants before enrollment.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.