European Journal of Cardiovascular Medicine

Cardiovascular diseases (CVDs) remain the leading cause of death globally, with Acute Coronary Syndrome (ACS) being one of its most critical and life-threatening manifestations. ACS encompasses a spectrum of clinical presentations including ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), and unstable angina, all resulting from acute myocardial ischemia and infarction secondary to plaque rupture or erosion and subsequent thrombus formation [1]. Traditionally regarded as a condition of the elderly, recent epidemiological data suggests a rising incidence of ACS among young adults, especially in South Asian countries including India, which poses a significant challenge to healthcare systems already burdened with the dual load of communicable and non-communicable diseases [2].

The etiology of ACS in the elderly is predominantly attributed to long-standing atherosclerosis compounded by comorbidities such as hypertension, diabetes mellitus, and dyslipidemia [3]. In contrast, young patients with ACS often present with different risk profiles, including smoking, obesity, sedentary lifestyle, stress, and a strong familial predisposition. Notably, conventional cardiovascular risk scoring systems like the Framingham Risk Score or SCORE underestimate risk in the younger population due to their age weighting, thereby failing to capture individuals at high risk for premature coronary artery disease (CAD) [4].

India, being home to the second-largest population globally, has witnessed an alarming trend of early-onset coronary artery disease with the average age of first myocardial infarction nearly a decade earlier than Western counterparts [5]. Genetic predisposition, urbanization-associated dietary habits, tobacco use and inadequate physical activity have all been implicated in this phenomenon. According to a recent registry, up to 15–20% of ACS patients in urban Indian centers are below the age of 40 years [6]. This early presentation not only results in long-term morbidity but also incurs significant economic consequences due to loss of productive life years.

Older adults with ACS, on the other hand, often present with atypical symptoms, delayed hospital arrival, and a higher incidence of complications including heart failure, arrhythmias and mortality [7]. Age-related changes in vascular biology, endothelial dysfunction, and systemic inflammation also exacerbate plaque vulnerability and thrombotic potential in the elderly. Furthermore, the presence of multiple comorbidities complicates pharmacologic and interventional management, often leading to suboptimal outcomes.

Despite the growing recognition of age-related differences in ACS presentation and risk factors, comparative studies focusing on young versus elderly patients remain sparse, particularly in the Indian context. Understanding the distinct cardiovascular risk profiles between these age groups is crucial for optimizing screening, prevention and treatment strategies. While young patients require aggressive risk factor modification focused on lifestyle and early detection, elderly patients benefit from holistic management of comorbid conditions and individualized pharmacotherapy [8].

In young individuals, smoking remains the most prevalent modifiable risk factor. Multiple studies have demonstrated that smoking not only accelerates atherogenesis but also promotes thrombosis and endothelial injury, leading to premature ACS [9]. Conversely, in older adults, diabetes and hypertension have been shown to exert a cumulative and synergistic effect on cardiovascular risk, contributing significantly to plaque burden and adverse outcomes. Family history of premature CAD—though often under-recognized—plays a crucial role in both age groups, particularly in genetically predisposed populations [10].

Given these distinctions, this study aims to conduct a comparative analysis of cardiovascular risk factors in patients aged below 40 and above 60 years presenting with ACS at a tertiary care center in Eastern India. By delineating the risk profiles of these two cohorts, the study hopes to inform clinicians and public health policymakers to adopt age-tailored preventive and therapeutic strategies

Study design: Analytical study, Cross Sectional design

Place of study: Department of Cardiology, Nilratan Sircar Medical College and Hospital, 138 A.J.C. Bose Road, Kolkata 700014.

Period of study: 18 months from 1st March 2023 to 31st August 2024.

Study population: Adult patients of below 40 years and above 60 years age groups admitted in the department of cardiology at NRMCH with Acute coronary syndrome

Study Variables:

• Gender
• Types of ACS
• BMI
• Waist (cm)
• Smoking (pack years)
• Job pattern (time)
• Job pattern (type)
• Sleep duration (hours)
• Smoking (Time)

Sample size: 192 Patients diagnosed with Acute Coronary Syndrome (ACS).

Inclusion Criteria:

• Patients giving consent to be a participant in this study
• Patients of at least 18 years of age
• Patients who are planned for coronary angiography

Exclusion Criteria:

• Patients with rheumatic heart diseases
• Patients with congenital heart diseases
• Patients with chronic stable angina
• Patients with deranged renal function
• Patients with deranged hepatic function

Statistical Analysis: Data has been put into the Microsoft office excel sheet and statistical calculation has been done using SPSS software version 23.  Continuous variables have been presented as Mean ± Standard deviation. Categorical variables have been given as number and percentage. Comparison between groups has been done by appropriate statistical tests and methods. P value <0.05 has been considered as statistically significant

Table 1: Distribution of gender in both age groups

Table 2: Distribution of type of ACS in both age groups

Table 3: Comparison of Cardiovascular Risk Parameters between Age Groups (<40 Years vs >60 Years)

Table 4: Distribution of job pattern (time) in both age groups

Table 5: Distribution of job pattern (type) in both age groups

Table 6: Distribution of sleep pattern in both age groups

Table 7: Distribution of smoking status in both age groups

Table 8: Comparison of Lifestyle and Clinical Risk Factors between Age Groups (<40 Years vs >60 Years)

Figure 1: Comparison of Cardiovascular Risk Parameters between Age Groups (<40 Years vs >60 Years)

Figure 2: Distribution of Cardiovascular Risk Factors in Patients Aged <40 Years and >60 Years

Figure 3: Comparison of Family History and Dietary Risk Factors in Patients Aged <40 Years and >60 Years

Figure 4: Comparison of Family History and Dietary Risk Factors Among Patients Aged <40 Years and >60 Years

In the present study, a total of 192 patients diagnosed with Acute Coronary Syndrome were included, comprising two age-based groups: those aged below 40 years and those above 60 years. In the <40 years age group, males constituted a predominant majority with 33 patients (84%), while females accounted for only 6 patients (16%). In contrast, among patients aged >60 years, males were 95 (62%) and females were 58 (38%). This indicates a significantly higher male predominance in the younger ACS cohort compared to the elderly group, suggesting that younger males are more commonly affected by ACS than their female counterparts.

Analysis of the types of Acute Coronary Syndrome (ACS) revealed notable differences between the two age groups. Among patients aged >60 years, the most common presentation was Non-ST-Elevation Myocardial Infarction (NSTEMI), seen in 56 patients (36%), followed by Anterior Wall Myocardial Infarction (AWMI) in 49 (32%), Inferior Wall Myocardial Infarction (IWMI) in 32 (21%), and Unstable Angina (UA) in 16 (11%). In contrast, the <40 years age group showed a different pattern, with IWMI being the most common type, occurring in 16 patients (41%), followed by AWMI in 15 (38%), while NSTEMI and UA were less common, seen in only 5 (13%) and 3 (8%) patients respectively.

The mean Body Mass Index (BMI) was similar in both groups, with elderly patients (>60 years) having a mean BMI of 24.97 ± 3.52 and younger patients (<40 years) having a mean BMI of 24.94 ± 5.00, showing no statistically significant difference (p = 0.9639). Waist circumference was slightly higher in the younger group (89.44 ± 10.66 cm) compared to the older group (85.03 ± 15.67 cm), though this difference did not reach statistical significance (p = 0.1039). However, a statistically significant difference was observed in smoking exposure. The mean smoking pack-years was markedly higher in the >60 years group (23.66 ± 5.83) compared to the <40 years group (6.5 ± 1.40), with a p-value of <0.0001.

The distribution of job pattern based on work timing showed that in the >60 years age group, a majority of patients (133, 87%) had day-time jobs, while 8 (5%) had night-shift jobs and 12 (8%) had mixed (rotational) shifts. In the <40 years group, 29 patients (74%) worked day shifts, 4 (10%) worked night shifts, and 6 (16%) had mixed shift patterns. Although a slightly higher proportion of younger patients were involved in night and mixed shift jobs compared to the elderly, the difference in job timing patterns between the two age groups was not statistically significant (p = 0.2664).

When comparing the type of job patterns, it was observed that among patients aged >60 years, 36 (23%) were engaged in office-based (sedentary) occupations, while a larger proportion, 117 (77%), were involved in manual or physically active jobs. In the <40 years age group, 12 patients (31%) had office-based jobs, and 27 (69%) were involved in manual labor. Although there was a slightly higher proportion of sedentary workers among younger patients, the difference in job type distribution between the two age groups was not statistically significant (p = 0.3032).

In the analysis of sleep duration patterns across different age groups, a statistically significant difference was observed (p = 0.0421). Among individuals over 60 years of age, the majority (48%) reported sleeping 6 to 9 hours, followed closely by 44% sleeping 3 to 6 hours. Very few elderly participants slept less than 3 hours (5%) or more than 9 hours (3%). In contrast, participants below 40 years of age showed a stronger tendency toward optimal sleep, with 69% sleeping 6 to 9 hours. Short sleep durations (3 to 6 hours) were reported by 21%, while only 3% slept less than 3 hours and 7% exceeded 9 hours of sleep.

An age-wise comparison of smoking history revealed notable differences between younger and older participants. Among individuals over 60 years of age, 23% were current smokers, 14% had a history of smoking in the past, and 63% had never smoked. In contrast, a higher proportion (36%) of participants under 40 years were current smokers, while none reported past smoking, and 64% had never smoked.

A comparative analysis of cardiovascular risk factors and dietary habits between individuals aged <40 years and those >60 years revealed several statistically significant differences. The prevalence of hypertension (28% vs. 35%, p = 0.0441), diabetes mellitus (21% vs. 48%, p = 0.0391), and lipid disorders (13% vs. 32%, p = 0.01725) was significantly higher among the elderly. While history of stroke was rare and comparable (p = 0.4729), a family history of acute coronary syndrome (ACS) was notably more common in younger individuals (59% vs. 31%, p = 0.0009), as was a family history of premature atherosclerosis (26% vs. 12%, p = 0.0232). The intake of trans fats (36% vs. 54%, p = 0.0324) and use of extra salt (62% vs. 36%, p = 0.0023) were significantly more frequent in the younger group and older group respectively. Other factors like consumption of saturated fats, fast food, red meat, fruits, and vegetables did not show statistically significant differences between the age groups. The use of other tobacco products (p = 0.311) and regular intake of vegetables (p = 0.0915) also showed no significant variation..

In this study, young adults (<40 years) with Acute Coronary Syndrome (ACS) demonstrated a higher male predominance (84%) compared to the elderly group (>60 years, 62%), which aligns with findings from several Indian and global studies indicating that premature coronary artery disease (CAD) predominantly affects males due to greater exposure to risk factors such as smoking and occupational stress [11,12]. A higher prevalence of Inferior Wall Myocardial Infarction (IWMI) in the younger cohort and Non-ST-Elevation Myocardial Infarction (NSTEMI) in the elderly mirrors observations by Kumar et al. and Prasad et al., where younger ACS patients often presented with ST-elevation events, likely due to plaque rupture on relatively soft plaques in otherwise non-calcified vessels [13,14]. Despite a similar mean BMI between groups, younger patients exhibited a higher waist circumference, hinting at central obesity—a known independent risk factor for premature atherosclerosis [15]. Smoking history showed notable contrasts, with younger patients having higher rates of current smoking (36%) while elderly patients had a significantly higher cumulative exposure (pack-years), reinforcing the cumulative vascular damage associated with prolonged tobacco use [16]. Notably, hypertension, diabetes, and dyslipidemia were significantly more prevalent in the elderly group, a pattern consistent with findings from large-scale Indian studies including the ICMR-INDIAB and Kerala ACS Registry [17,18]. Conversely, a strong family history of ACS and premature atherosclerosis was significantly more common among the younger group, supporting the notion that genetic predisposition plays a critical role in early-onset CAD [19]. Dietary patterns revealed age-specific differences, with elderly individuals consuming extra salt more frequently, while younger individuals showed higher intake of trans fats, indicating an urbanized lifestyle and dietary westernization. Such trends were also highlighted in the INTERHEART and PURE studies, which emphasized the growing burden of poor dietary habits in young South Asians [20]. These results underline the need for targeted preventive strategies tailored to age-specific risk profiles

The present study highlights significant age-related differences in the clinical profile, risk factors, and presentation of Acute Coronary Syndrome (ACS). Younger patients (<40 years) were predominantly male and showed higher rates of current smoking, family history of premature atherosclerosis, and consumption of unhealthy dietary components such as trans fats. In contrast, older patients (>60 years) exhibited a greater burden of comorbidities including hypertension, diabetes, and dyslipidemia, with NSTEMI being the most common presentation. Although BMI was similar across age groups, central obesity was more prominent in the younger cohort.

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