European Journal of Cardiovascular Medicine

Ischemic heart disease (IHD) continues to be the leading cause of morbidity and mortality worldwide, accounting for an estimated 17.9 million deaths annually and representing nearly one-third of all global deaths [1]. The rising prevalence of early-onset IHD, defined as the occurrence of coronary events before 55 years in men and 65 years in women, is particularly concerning in low- and middle-income countries where lifestyle transitions and urbanization have accelerated cardiovascular risk accumulation [2]. Among the modifiable determinants, hypertension, dyslipidemia, and central obesity form a triad of interrelated metabolic abnormalities that significantly contribute to the pathogenesis of premature atherosclerosis and coronary artery disease [3].

Hypertension causes mechanical stress on vascular endothelium, promoting arterial stiffness, intimal thickening, and left ventricular hypertrophy, which collectively heighten myocardial oxygen demand [4]. Dyslipidemia, marked by elevated low-density lipoprotein cholesterol (LDL-C) and reduced high-density lipoprotein cholesterol (HDL-C), leads to lipid deposition and plaque instability, key precursors of ischemic events [5]. Central obesity, characterized by increased visceral fat, is an independent predictor of cardiovascular disease through its pro-inflammatory and insulin-resistant milieu [6]. The simultaneous presence of these risk factors exerts a synergistic effect, amplifying the risk of IHD far beyond their individual contributions [7].

South Asian populations, particularly Indians, demonstrate a distinctive pattern of metabolic clustering at a younger age, often developing IHD nearly a decade earlier than Western counterparts due to genetic susceptibility, abdominal adiposity, and suboptimal lipid profiles [8]. Identifying the coexistence of hypertension, dyslipidemia, and central obesity as a composite predictor of early-onset IHD can enhance risk stratification and guide preventive strategies targeted at younger adults who may otherwise remain asymptomatic.

Despite the well-established role of individual cardiovascular risk factors, there is limited regional evidence evaluating their combined predictive impact on early-onset IHD. Understanding this coexistence could inform more effective screening, early interventions, and resource prioritization in preventive cardiology. The present study aims to evaluate the coexistence of hypertension, dyslipidemia, and central obesity as predictors of early-onset ischemic heart disease and to determine their collective influence on premature cardiovascular morbidity.

Study Design and Setting

This hospital-based observational cross-sectional study was conducted in the Department of General Medicine, SVS Medical College and Hospital, Mahbubnagar, Telangana, over a six-month period from January 2021 to June 2021. The study aimed to evaluate the coexistence of hypertension, dyslipidemia, and central obesity as predictors of early-onset ischemic heart disease (IHD) among adult patients presenting with clinical or electrocardiographic evidence suggestive of IHD. Ethical clearance was obtained from the Institutional Ethics Committee prior to initiation of the study, and written informed consent was obtained from all participants in accordance with the Declaration of Helsinki (2013).

Study Population

The study population comprised adult patients aged ≤55 years in men and ≤65 years in women who were newly diagnosed with IHD (angina pectoris, acute coronary syndrome, or myocardial infarction) confirmed by clinical assessment, ECG changes, cardiac enzyme elevation, or echocardiographic findings [9]. Patients with secondary causes of dyslipidemia (e.g., nephrotic syndrome, hypothyroidism, chronic liver disease), endocrine disorders such as Cushing’s syndrome, and those on lipid-lowering or antihypertensive therapy for more than three months were excluded to minimize confounding.

Sample Size Calculation

The sample size was calculated based on the formula for estimating proportions in cross-sectional studies:

Where:

                n = required sample size

                Z = standard normal deviate at 95% confidence (1.96)

                p = estimated prevalence of coexistence of hypertension, dyslipidemia, and central obesity in early-onset IHD

                d = allowable error (precision)

Based on previous Indian studies reporting a prevalence of combined metabolic risk factors in young IHD patients of approximately 50% [10,11], the calculation was as follows:

To account for potential non-responses and incomplete data, the sample size was increased by 10%, giving a final sample size of 106 participants.

Data Collection and Procedures

Participants were evaluated using a structured case record form designed to capture demographic characteristics, clinical history, and anthropometric and biochemical measurements. Data were collected by trained medical residents under supervision.

Clinical Assessment

A detailed clinical history was recorded, including age, sex, smoking status, alcohol use, physical activity, and family history of premature IHD. Blood pressure was measured in the sitting position using a calibrated mercury sphygmomanometer after a minimum of 5 minutes of rest. Two readings were taken at 5-minute intervals, and the average was considered for analysis [12].

Definition of Hypertension

Hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg, or current use of antihypertensive medication, according to JNC-8 guidelines [13].

Anthropometric Measurements and Central Obesity

Body weight and height were recorded with participants in light clothing and without shoes. Waist circumference was measured midway between the lowest rib margin and the iliac crest using a non-stretchable tape at the end of normal expiration. Central obesity was defined as a waist circumference ≥90 cm in men and ≥80 cm in women, based on WHO and IDF Asian-specific criteria [14,15]. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters.

Biochemical Evaluation and Dyslipidemia Definition

After an overnight fast of 10–12 hours, 5 mL of venous blood was collected for estimation of fasting plasma glucose and lipid profile (total cholesterol, triglycerides, HDL-C, and LDL-C). Analysis was performed using an automated chemistry analyzer (Erba XL-640, Transasia Bio-Medicals Ltd., India). Dyslipidemia was defined according to NCEP-ATP III guidelines as:

·         Total cholesterol ≥200 mg/dL, or

·         LDL-C ≥130 mg/dL, or

·         HDL-C <40 mg/dL in men or <50 mg/dL in women, or

·         Triglycerides ≥150 mg/dL [16].

5. Diagnosis of Ischemic Heart Disease

IHD was diagnosed based on the presence of ischemic symptoms (angina, chest pain) along with any of the following criteria:

·         Electrocardiographic changes (ST-segment elevation/depression or T-wave inversion),

·         Elevated cardiac biomarkers (troponin I or CK-MB), or

·         Echocardiographic evidence of regional wall motion abnormalities.

Diagnosis and classification followed the Fourth Universal Definition of Myocardial Infarction (2018) [9].

Statistical Analysis

Data were entered into Microsoft Excel and analyzed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation (SD) and compared using the Student’s t-test, while categorical variables were expressed as percentages and compared using the Chi-square test. Binary logistic regression analysis was performed to assess the independent predictive value of hypertension, dyslipidemia, and central obesity for early-onset IHD. A p-value <0.05 was considered statistically significant. Multicollinearity was assessed using the variance inflation factor (VIF), and model calibration was evaluated using the Hosmer–Lemeshow goodness-of-fit test.

Table 1 presents the sociodemographic and clinical characteristics of the study cohort. A total of 106 patients diagnosed with early-onset ischemic heart disease were included in the final analysis. The mean age of the participants was 49.6 ± 6.4 years, with 72 (67.9%) males and 34 (32.1%) females, resulting in a male-to-female ratio of approximately 2.1:1. Most participants (58.5%) belonged to the 46–55-year age group. A positive family history of premature coronary artery disease was present in 38 (35.8%) individuals.

The mean body mass index (BMI) of the study population was 27.8 ± 3.5 kg/m², indicating that the majority were overweight or obese. The mean waist circumference was 94.6 ± 8.2 cm in men and 87.3 ± 7.5 cm in women.

Table 1. Baseline Characteristics of the Study Population (n = 106)

Table 2 summarizes the distribution of the three major risk factors among the study participants. Hypertension was present in 62 (58.5%) patients, dyslipidemia in 70 (66.0%), and central obesity in 75 (70.8%). The coexistence of all three risk factors was identified in 48 (45.3%) of participants, while 24 (22.6%) had any two, 18 (17.0%) had only one, and 16 (15.1%) had none of the three major risk factors.

Mean systolic blood pressure was 142.3 ± 14.5 mmHg, and mean diastolic pressure was 89.6 ± 8.1 mmHg. The mean total cholesterol level was 214.5 ± 36.8 mg/dL, LDL-C was 139.2 ± 27.6 mg/dL, HDL-C was 41.8 ± 8.9 mg/dL, and triglycerides averaged 182.6 ± 45.7 mg/dL.

Table 2. Distribution of Major Cardiometabolic Risk Factors

Table 3 shows the gender-wise comparison of major risk factors. Male patients had a higher prevalence of hypertension (61.1%) and dyslipidemia (68.0%) than females (52.9% and 61.8%, respectively), though these differences were not statistically significant (p > 0.05). Central obesity was more frequent among females (76.5%) compared with males (68.1%). The coexistence of all three factors was noted in 47.2% of males and 41.2% of females.

Table 3. Gender-wise Distribution of Risk Factors

Binary logistic regression was performed to identify independent predictors of early-onset IHD severity (NSTEMI/STEMI vs. stable angina) using age, sex, hypertension, dyslipidemia, central obesity, smoking, and coexistence of all three risk factors as independent variables (Table 4). The model showed good fit (Hosmer–Lemeshow p = 0.62) and no multicollinearity (VIF < 2.0). The coexistence of hypertension, dyslipidemia, and central obesity was a significant independent predictor of severe early-onset IHD (adjusted OR = 3.82; 95% CI 1.54–9.47; p = 0.004). Among individual factors, hypertension (aOR = 2.01; 95% CI 1.08–4.63; p = 0.037) and dyslipidemia (aOR = 2.44; 95% CI 1.22–5.29; p = 0.015) were independently associated with severe disease, while central obesity showed a borderline association (aOR = 1.81; 95% CI 0.91–3.78; p = 0.082).

Table 4. Binary Logistic Regression Analysis for Predictors of Severe Early-Onset IHD

                                         *Statistically significant at p < 0.05

A horizontal forest plot displayed adjusted odds ratios with 95% confidence intervals for each risk factor (Figure 3). The plot highlighted significant associations for hypertension, dyslipidemia, and triple coexistence, with the line of null effect (OR = 1.0) crossed only by central obesity, age, and smoking, indicating non-significant associations.

The present study investigated the coexistence of hypertension, dyslipidemia, and central obesity as predictors of early-onset ischemic heart disease (IHD) in adults attending SVS Medical College, Mahbubnagar. Nearly half of the participants exhibited simultaneous presence of all three risk factors, and this clustering significantly increased the likelihood of more severe forms of IHD such as non-ST elevation myocardial infarction (NSTEMI) and ST elevation myocardial infarction (STEMI). The results highlight the synergistic impact of multiple cardiometabolic risk factors on premature coronary atherosclerosis in the Indian population.

Our results are in line with findings from other Indian cohorts where central obesity and dyslipidemia predominated among young myocardial infarction patients [17]. The magnitude of triple-risk coexistence (45%) observed here parallels prior studies reporting 40–50% prevalence of metabolic clustering in early CAD [18,19]. The strong association observed in our study between waist circumference, triglyceride levels, and systolic blood pressure mirrors earlier evidence from Indian populations emphasizing the pivotal role of visceral adiposity in metabolic risk clustering. Notably, Misra et al. (2006) demonstrated that increased waist circumference is a superior anthropometric marker for predicting metabolic syndrome components, including elevated triglycerides, raised blood pressure, and reduced HDL-C, compared with body mass index among Asian Indian [20]. Together, these studies depict a consistent picture: premature IHD in India is primarily metabolic rather than purely atherosclerotic, calling for early lifestyle correction and risk-factor synergy control.

Epidemiological Perspective

Globally, IHD remains the leading cause of mortality, accounting for more than nine million deaths annually [21]. The Global Burden of Disease data and Indian registries reveal that South Asians develop coronary artery disease (CAD) nearly a decade earlier than Western populations due to higher prevalence of metabolic risk factors and genetic susceptibility [22]. The mean age of onset in this study (49.6 ± 6.4 years) corroborates previous Indian reports, confirming a shift toward earlier presentation of coronary events. The INTERHEART study demonstrated that abdominal obesity, hypertension, and abnormal lipids collectively accounted for over 80% of myocardial infarction risk across diverse populations [7], underscoring the importance of these modifiable determinants.

Hypertension and Coronary Risk

In this cohort, 58.5% of patients had hypertension. Elevated blood pressure accelerates endothelial dysfunction, vascular remodeling, and left ventricular hypertrophy, promoting ischemia through increased myocardial oxygen demand [4]. The Framingham Heart Study established hypertension as one of the strongest independent predictors of coronary events, showing that a 20 mmHg rise in systolic pressure doubles cardiovascular mortality [23]. Comparable Indian data indicate that hypertension prevalence is increasing across urban and rural settings, with suboptimal control rates [24]. The independent association of hypertension with severe IHD in our regression analysis reaffirms the need for early detection and intensive management of blood pressure among younger adults.

Dyslipidemia and Atherogenic Patterns

Dyslipidemia was present in two-thirds of study participants, consistent with Indian epidemiological trend [25]. Elevated LDL-cholesterol and triglycerides facilitate plaque formation, while reduced HDL-cholesterol impairs reverse cholesterol transport and antioxidant activity [5,26]. Meta-analysis by the Cholesterol Treatment Trialists’ Collaboration confirmed that each 1 mmol/L reduction in LDL-C lowers vascular events by about 23% [27]. The current study also noted a high prevalence of “atherogenic dyslipidemia” — low HDL with high triglycerides — a hallmark of the South Asian phenotype characterized by insulin resistance and visceral adiposity [28]. This pattern increases myocardial infarction risk even when total cholesterol is not markedly elevated [29]. Therefore, lipid management strategies in South Asians should address not only LDL-C reduction but also HDL and triglyceride optimization.

Central Obesity as a Unifying Link

Central obesity was the most frequent risk factor (70.8%), showing positive correlations with systolic blood pressure and triglycerides, and a negative correlation with HDL-C. These findings align with prior studies demonstrating that visceral adiposity is a stronger predictor of cardiovascular risk than body-mass index (BMI) [6]. Abdominal fat promotes secretion of inflammatory cytokines such as tumor necrosis factor-α and interleukin-6, which contribute to insulin resistance, oxidative stress, and vascular dysfunction [30]. The use of Asian-specific waist-circumference cut-offs (≥90 cm for men, ≥80 cm for women) was appropriate, as metabolic complications in this population occur at lower BMI and waist thresholds than in Western groups [31]. The strong correlations observed in this study reinforce the pathophysiological role of visceral fat as a driver of metabolic clustering.

Clustering of Risk Factors

The coexistence of hypertension, dyslipidemia, and central obesity was found in 45.3% of the cohort, increasing the odds of severe IHD nearly fourfold. This clustering reflects the underlying interplay of insulin resistance, neurohormonal activation, and low-grade inflammation that collectively accelerate atherogenesis. The Framingham Offspring Study demonstrated a similar fourfold rise in myocardial infarction risk among individuals with three or more metabolic abnormalities [32]. Such data indicate that these risk factors act synergistically rather than independently. Addressing them concurrently through integrated management offers greater cardiovascular protection than treating each in isolation.

Gender Differences

Men constituted two-thirds of the study population, but women showed a higher prevalence of central obesity (76.5%). Hormonal changes, particularly post-menopausal estrogen decline, promote visceral fat accumulation and dyslipidemia. Previous regional data have also highlighted that abdominal obesity and low HDL-C are stronger predictors of CAD in women under 55 years compared with men [7]. Though gender differences were not statistically significant here, the trend underscores the importance of gender-sensitive risk assessment.

Clinical Implications

From a clinical perspective, our findings emphasize the need for early, comprehensive screening for metabolic risk factors starting in the third decade of life. Routine evaluation of waist circumference, blood pressure, and lipid profile during primary-care visits can identify high-risk individuals before symptomatic CAD develops. Moreover, management must be multifactorial. The Steno-2 trial demonstrated that simultaneous control of blood pressure, lipids, and glucose reduced cardiovascular events by nearly half compared with conventional care [32]. Lifestyle interventions—weight reduction, salt restriction, increased physical activity, and smoking cessation—remain the foundation of prevention. However, pharmacologic measures such as early initiation of statins and ACE inhibitors should be considered in those with clustered risk profiles, even if absolute risk scores appear modest.

Pathophysiological Insights

The triad of hypertension, dyslipidemia, and central obesity likely represents different expressions of a single metabolic disturbance dominated by insulin resistance. Adipocyte dysfunction leads to increased release of free fatty acids, promoting hepatic overproduction of very-low-density lipoproteins and reduced HDL-C formation. The resulting lipid imbalance exacerbates endothelial injury. Hypertension further magnifies shear stress, while inflammatory cytokines from adipose tissue accelerate atheromatous changes [30]. This shared biological basis explains why multiple metabolic abnormalities often coexist, especially in South Asians who exhibit greater visceral fat deposition at lower body weights [28].

Public-Health Significance

At the population level, the findings highlight an urgent need to strengthen national prevention programs such as India’s NPCDCS (National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke). Screening for metabolic syndrome components in primary care, particularly in semi-urban and rural areas, should be prioritized. Public-health campaigns focusing on dietary modification, physical activity, and avoidance of tobacco and alcohol can significantly reduce the risk of early IHD. Implementation of workplace wellness and community-based lifestyle programs would further aid in curbing premature cardiovascular mortality.

Strengths and Limitations

The major strength of this study lies in its comprehensive evaluation of interrelated cardiometabolic factors in a well-defined cohort of early-onset IHD patients. The inclusion of anthropometric, biochemical, and hemodynamic parameters allowed meaningful correlation and regression analyses. However, its cross-sectional design precludes causality assessment. The hospital-based sample may not perfectly represent the community, and unmeasured confounders such as dietary intake, stress, and genetic polymorphisms were not evaluated. Despite these limitations, the findings contribute valuable regional evidence underscoring the interplay between hypertension, dyslipidemia, and central obesity in the pathogenesis of premature IHD.

Future Directions

Future multicentric, longitudinal studies are required to validate these associations and to quantify how simultaneous risk-factor control modifies outcomes. Incorporating inflammatory and genetic biomarkers could improve risk prediction models. Artificial-intelligence–based algorithms using clinical and behavioral data may also enable earlier identification of high-risk individuals. Policymakers should support preventive cardiology initiatives that integrate education, screening, and cost-effective pharmacotherapy to reduce premature cardiovascular morbidity and mortality.

The coexistence of hypertension, dyslipidemia, and central obesity strongly predicted the severity of early-onset ischemic heart disease in this South Indian cohort. The results confirm that cardiometabolic risk factors exert a synergistic, not additive, effect on early atherosclerosis. Early screening and integrated management of these interlinked conditions—through lifestyle modification, pharmacologic therapy, and public-health interventions—can significantly reduce the growing epidemic of premature coronary disease in India.

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