European Journal of Cardiovascular Medicine

Metabolic syndrome (MetS) represents a cluster of interrelated metabolic abnormalities including central obesity, insulin resistance, hypertension, dyslipidemia, and elevated fasting glucose, which collectively increase the risk of cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), and all-cause mortality worldwide. The prevalence of metabolic syndrome has escalated alarmingly in recent decades, paralleling the global rise in obesity and sedentary lifestyles, imposing a significant burden on healthcare systems ^[1].

Metabolic syndrome is clinically defined by criteria such as those from the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the International Diabetes Federation (IDF), or the World Health Organization (WHO), which emphasize central adiposity and two or more of the associated metabolic risk factors. The pathophysiology underlying MetS is multifactorial, with insulin resistance playing a central role, modulated by genetic predisposition and environmental factors ^[2].

Dietary habits constitute one of the most influential modifiable environmental factors contributing to the development of metabolic syndrome. Over recent years, the Westernization of diets—characterized by high intake of refined carbohydrates, saturated fats, sugars, and processed foods—has been implicated in the rising prevalence of MetS. Conversely, dietary patterns rich in fruits, vegetables, whole grains, lean proteins, and unsaturated fats, such as the Mediterranean diet or DASH diet, have demonstrated protective effects against the metabolic syndrome and related cardiovascular outcomes ^[3].

Understanding the association between dietary patterns and MetS is essential for formulating effective public health strategies aimed at prevention and management. Unlike isolated nutrient studies, dietary pattern analysis considers the overall diet and synergistic interactions among various food components, providing a more holistic assessment of dietary exposure. Multiple observational studies worldwide have reported divergent dietary patterns influencing MetS risk, including the detrimental impacts of "Western" diets and the beneficial effects of "prudent" or "healthy" diets ^[4].

Epidemiological evidence indicates that the Mediterranean diet, characterized by high consumption of olive oil, nuts, legumes, fruits, vegetables, moderate fish and poultry, and low red meat intake, is associated with lower risk of metabolic syndrome components, including insulin resistance and abdominal obesity. Similarly, adherence to dietary approaches like the DASH diet, emphasizing fruits, vegetables, low-fat dairy, and reduced sodium intake, has been linked to improved blood pressure and lipid profiles in MetS patients ^[5].

The mechanistic pathways connecting diet and metabolic syndrome involve modulation of insulin sensitivity, inflammatory responses, oxidative stress, and endothelial function. Diets rich in antioxidants, fiber, and unsaturated fatty acids can reduce systemic inflammation and improve lipid metabolism, while diets high in saturated fats and simple sugars can exacerbate metabolic disturbances^[6].

Aim

To analyze the association between dietary patterns and the incidence of metabolic syndrome in adults through a cross-sectional study.

Objectives

1. To identify and categorize prevailing dietary patterns among the study population.
2. To determine the prevalence of metabolic syndrome and its components within the study group.
3. To assess the relationship between specific dietary patterns and the risk of developing metabolic syndrome.

Source of Data

Data were collected from adult patients attending outpatient departments and health screening camps at [Institution/Hospital Name] during the study period. Participants were selected from the general population residing in and around the study location.

Study Design

This was a descriptive, observational, cross-sectional study.

Study Location

The study was conducted at the Department of Community Medicine, Government Medical College, Jalgaon.

Study Duration

The study was conducted over a period of one year.

Sample Size

A total of 200 adult participants aged 20–60 years were enrolled based on sample size calculations to achieve adequate statistical power.

Inclusion Criteria

• Adults aged 20–60 years.
• Individuals willing to provide informed consent.
• Participants who had fasted for at least 8 hours before sample collection.

Exclusion Criteria

• Pregnant and lactating women.
• Individuals with known chronic illnesses such as cancer, chronic kidney disease, or severe hepatic disorders.
• Participants on medications affecting lipid or glucose metabolism (e.g., statins, corticosteroids).
• Individuals with incomplete dietary or clinical data.

Procedure and Methodology

After obtaining written informed consent, participants were subjected to a structured interview to record sociodemographic data and detailed dietary history using a validated Food Frequency Questionnaire (FFQ) covering major food groups and consumption frequency over the past month. Anthropometric measurements including weight, height, waist circumference, and blood pressure were recorded using standard techniques.

Fasting blood samples were collected for biochemical analysis including fasting plasma glucose, serum triglycerides, high-density lipoprotein cholesterol (HDL-C), and other relevant metabolic parameters.

Metabolic syndrome was diagnosed according to the NCEP ATP III criteria, requiring the presence of at least three of the following: waist circumference >102 cm in men or >88 cm in women, triglycerides ≥150 mg/dL, HDL cholesterol <40 mg/dL in men or <50 mg/dL in women, blood pressure ≥130/85 mmHg, fasting glucose ≥100 mg/dL.

Dietary patterns were extracted through principal component analysis (PCA) of the FFQ data, identifying dominant patterns such as "Western," "Prudent," and "Traditional" dietary habits. The prevalence of MetS was then compared across dietary pattern tertiles.

Sample Processing

Blood samples were collected in vacutainers after overnight fasting and transported immediately to the biochemistry laboratory. Plasma glucose was measured by the glucose oxidase method, triglycerides and HDL cholesterol by enzymatic colorimetric assays using an automated analyzer. Quality control procedures were maintained throughout.

Statistical Methods

Data were entered into Microsoft Excel and analyzed using SPSS version 25.0. Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range), and categorical variables as frequencies and percentages. Chi-square tests were used for categorical comparisons, and ANOVA or Kruskal-Wallis tests for continuous variables. Logistic regression analysis was performed to determine the association between dietary patterns and the presence of metabolic syndrome, adjusting for potential confounders such as age, sex, physical activity, and smoking status. A p-value <0.05 was considered statistically significant.

Data Collection

Data collection was conducted by trained researchers using pre-tested questionnaires and standard protocols for anthropometric and biochemical measurements. All data were anonymized to maintain participant confidentiality.

Table 1: Baseline Demographic and Clinical Characteristics of Study Participants (n=200)

Table 1 summarizes the baseline demographic and clinical characteristics of the 200 study participants, comparing those with metabolic syndrome (n=70) to those without (n=130). The mean age of the cohort was 44.7 years, with participants diagnosed with metabolic syndrome being significantly older (49.3 vs. 41.9 years, p<0.001). A higher proportion of males was found among the metabolic syndrome group (65.7% vs. 50.8%, p=0.042). Key clinical parameters differed markedly between groups: body mass index (BMI) was higher in the metabolic syndrome group (29.8 vs. 25.6 kg/m², p<0.001), as was waist circumference (101.5 cm vs. 86.1 cm, p<0.001), systolic blood pressure (140.3 vs. 121.9 mmHg, p<0.001), fasting glucose levels (115.4 vs. 90.2 mg/dL, p<0.001), and triglycerides (185.3 vs. 131.9 mg/dL, p<0.001). Conversely, HDL cholesterol was significantly lower in the metabolic syndrome group (38.2 vs. 49.1 mg/dL, p<0.001). Additionally, only 28.6% of those with metabolic syndrome reported moderate physical activity compared to 50.8% without (p=0.004), indicating a significant lifestyle difference.

Table 2: Dietary Patterns Identified Among Study Population (n=200)

Table 2 identifies dietary patterns within the study population and their distribution by metabolic syndrome status. The Western dietary pattern, characterized by higher processed food consumption, was notably more prevalent in the metabolic syndrome group (55.7%) compared to those without metabolic syndrome (25.4%, p<0.001). Conversely, the prudent or healthy dietary pattern was more common among participants without metabolic syndrome (53.1% vs. 21.4%). The traditional/local pattern showed no significant group difference. Regarding food intake, individuals with metabolic syndrome consumed fewer daily servings of fruit (1.4 vs. 2.7, p<0.001) and vegetables (2.0 vs. 3.1, p<0.001), while their processed food consumption was significantly higher (4.5 vs. 2.3 days/week, p<0.001).

Table 3: Prevalence of Metabolic Syndrome Components among Study Participants (n=200)

Table 3 presents the prevalence of metabolic syndrome components. Abdominal obesity was universally present in those with metabolic syndrome (100%) but only in 30.8% of those without (p<0.001). Elevated triglycerides, reduced HDL cholesterol, hypertension, and fasting hyperglycemia were all significantly more common among the metabolic syndrome group, with prevalence rates ranging from 80% to nearly 90%, compared to approximately 25–30% in those without metabolic syndrome (all p<0.001). These findings align with diagnostic criteria and highlight the metabolic disturbances defining the syndrome.

Table 4: Relationship between Dietary Patterns and Risk of Metabolic Syndrome (n=200)

*Adjusted for age, sex, BMI, physical activity, and smoking.

Table 4 explores the association between dietary patterns and metabolic syndrome risk. Using the Western dietary pattern as reference, adherence to the prudent/healthy pattern was associated with a 69% reduced odds of metabolic syndrome (adjusted OR 0.31, 95% CI 0.14–0.68, p=0.003). The traditional/local pattern also showed a protective effect (adjusted OR 0.39, 95% CI 0.17–0.89, p=0.025). Each additional daily serving of fruit and vegetables reduced metabolic syndrome odds by 28% and 23%, respectively, while increased processed food consumption raised risk by 48% (p=0.001). These adjusted results accounted for confounders such as age, sex, BMI, physical activity, and smoking.

Table 1 presents baseline demographic and clinical characteristics of 200 participants categorized by the presence or absence of metabolic syndrome (MetS). Participants with MetS were significantly older (mean 49.3 vs. 41.9 years; p<0.001), consistent with existing evidence that MetS prevalence increases with age due to cumulative metabolic stress and declining insulin sensitivity over time Dipasquale S et al.(2013)^[7]. The higher proportion of males in the MetS group (65.7% vs. 50.8%; p=0.042) aligns with findings from Shin HJ et al.(2014)^[8], who highlighted sex differences in MetS risk attributed to hormonal and behavioral factors.

Anthropometric measures such as BMI and waist circumference were notably higher in MetS subjects, mirroring the central role of obesity, especially visceral adiposity, in metabolic dysregulation. Similar observations were reported by Cespedes EM et al.(2015)^[9], emphasizing abdominal obesity as a cardinal MetS component. Elevated systolic blood pressure, fasting glucose, and triglyceride levels, along with reduced HDL cholesterol, were significantly more prevalent among those with MetS (all p<0.001), reflecting the characteristic metabolic disturbances defined by NCEP ATP III criteria. The reduced moderate physical activity in MetS individuals (28.6% vs. 50.8%, p=0.004) underscores the protective role of physical activity against metabolic abnormalities Pucci G et al.(2017)^[10].

Table 2 details dietary patterns and their association with MetS. The Western dietary pattern, characterized by high processed food and saturated fat intake, was significantly more common in participants with MetS (55.7%) than those without (25.4%; p<0.001). This corroborates findings by Cena H et al.(2020)^[11], who documented the detrimental effects of Western diets on cardiometabolic health. The prudent or healthy dietary pattern—rich in fruits, vegetables, and whole grains—was predominant in the non-MetS group (53.1%), consistent with prior studies associating such diets with reduced MetS risk. Intake analyses showed lower fruit and vegetable consumption and higher processed food frequency in MetS participants, paralleling evidence linking diet quality to metabolic health outcomes de Toro-Martín J et al.(2017)^[12].

Table 3 shows the prevalence of MetS components. Abdominal obesity was present in all MetS subjects but only 30.8% of non-MetS participants (p<0.001), reaffirming the centrality of visceral fat in MetS pathogenesis. Similarly, elevated triglycerides, reduced HDL cholesterol, hypertension, and fasting hyperglycemia were markedly more frequent in the MetS group (p<0.001). These findings are in agreement with Kastorini CM et al.(2011)^[13], who emphasized these components’ synergistic roles in cardiovascular risk. The high prevalence of these abnormalities in the MetS group highlights the clustering effect that defines the syndrome.

Table 4 assesses dietary patterns’ influence on MetS risk via odds ratios. Compared to the Western pattern, adherence to the prudent/healthy diet reduced MetS odds by 69% (adjusted OR 0.31; p=0.003), and the traditional/local pattern also conveyed protection (adjusted OR 0.39; p=0.025). Incremental increases in fruit and vegetable intake further decreased MetS risk, while higher processed food consumption increased it by 48% (p=0.001). These results support the protective role of plant-based diets and the risk posed by processed foods, consistent with findings from Pérez-Martínez P et al.(2017)^[14] and Sánchez-Villegas A et al.(2013)^[15]. Adjustment for confounders enhances the validity of these associations, highlighting diet as a modifiable factor in MetS prevention.

The present cross-sectional study demonstrates a significant association between dietary patterns and the incidence of metabolic syndrome among adults. Participants adhering to Western dietary patterns characterized by high consumption of processed foods, saturated fats, and sugars exhibited a markedly higher prevalence of metabolic syndrome and its components. Conversely, adherence to prudent or healthy dietary patterns rich in fruits, vegetables, and whole grains was associated with a substantially lower risk of metabolic syndrome. These findings underscore the critical role of dietary habits in modulating metabolic health and suggest that promoting healthy eating behaviors may serve as an effective strategy to prevent or mitigate metabolic syndrome and its associated complications.

LIMITATIONS OF STUDY

1. Cross-Sectional Design: The study’s cross-sectional nature limits the ability to infer causal relationships between dietary patterns and metabolic syndrome incidence. Longitudinal studies are needed to establish temporality.
2. Self-Reported Dietary Data: Dietary intake was assessed using food frequency questionnaires, which are subject to recall bias and misreporting, potentially affecting the accuracy of dietary pattern classification.
3. Confounding Factors: Although adjustments were made for key confounders such as age, sex, BMI, physical activity, and smoking, residual confounding by unmeasured variables (e.g., socioeconomic status, genetic predisposition) cannot be excluded.
4. Sample Representativeness: The study sample was drawn from a specific geographic region and healthcare setting, which may limit the generalizability of findings to other populations with different cultural or dietary contexts.

Limited Nutrient Analysis: The study focused on dietary patterns rather than individual nutrient intake, which may overlook specific nutrient effects on metabolic outcomes

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