Metabolic Syndrome Incidence In Patients Consuming A Processed Food Diet
Metabolic syndrome (MetS) is a collection of metabolic abnormalities, including insulin resistance, hypertension, abdominal obesity, and dyslipidemia, which significantly elevate the risk of developing type 2 diabetes mellitus and cardiovascular disease.
The global incidence of MetS has surged, largely due to lifestyle factors like sedentary behavior and obesity. While the exact cause remains uncertain, environmental, metabolic, and genetic factors are thought to contribute. Dietary habits are identified as key modifiable factors in managing and preventing MetS. Ultra-processed foods (UPFs), known for their high levels of unhealthy ingredients and poor nutritional value, have seen a notable increase, displacing healthier dietary options.
Research indicates a link between UPF consumption and various health issues, including noncommunicable diseases, obesity, and overweight. Despite some investigations into the association between MetS and UPFs, findings have been inconsistent across different populations. This study aims to examine the relationship between UPF intake and MetS within an Iranian context, considering potential differences in dietary patterns and lifestyle factors.
Methods
In this cross-sectional study, conducted as part of the Prospective Epidemiological Research Studies in Iran (PERSIAN) cohort, residents of Fasa, a small city in the Fars province of Iran, were surveyed. The research included 11,097 individuals aged 35 to 70 from the rural area of Sheshdeh, near Fasa City, as well as participants from 24 neighboring villages. The study was approved by the Shiraz University of Medical Sciences Ethics Committee (IR.SUMS.REC.1401.363).
Data on demographic details, socioeconomic status, physical measurements, dietary habits, and medical history were collected at the outset by trained personnel. Dietary habits were evaluated using a modified food frequency questionnaire (FFQ) tailored to include Iranian food items. Individuals with daily caloric intake below 800 or above 4200 kcal/day were excluded from the analysis. After excluding 2256 participants due to insufficient physical activity data or energy intake estimation issues, the final sample comprised 8841 individuals.
The study gathered data on individuals’ demographics (age, gender), lifestyle factors (physical activity, education, smoking, alcohol consumption, medication use), living situation, dietary habits, and body measurements.
The study evaluated participants’ dietary intake using a modified 125-item food frequency questionnaire (FFQ) over a one-year period (Farjam et al., 2016). Initially, the frequency and portion sizes of each food item were converted to grams using Iranian home scales. Subsequently, nutrient and energy intake were computed using Nutritionist IV software (Nutritionist, 1998).
Participants were assessed for noncommunicable diseases (NCDs), alcohol and smoking habits, and physical activity using checklists. They were also asked to bring their medications for accurate recording of their medical history during the interview. Physical activity levels were determined using a standard questionnaire, which calculated the metabolic equivalent of task (MET) based on time spent on various activities such as work, sleep, walking, and exercise.
To gauge ultra-processed food (UPF) consumption, the study employed the NOVA food group classification, which categorizes foods into four classes based on their level of processing (Petrus et al., 2021). This classification method allowed for the selection of various beverages and food items, including processed meats, salty and fried snacks, sweetened milk-based beverages, ice cream, industrial fruit drinks, soft drinks, cakes, biscuits, sweets, pastries, dressings, sauces, margarine, packaged bread, and buns. The energy content of each UPF item was then calculated. Finally, to determine total UPF consumption, the average daily intake of UPFs was divided by the overall daily intake and multiplied by 100.
Statistical Analysis
The data analysis for this study was conducted using SPSS version 26.0. Statistical significance was determined with a p-value threshold of less than .05. The normality of study variables was assessed using the Kolmogorov–Smirnov test. Participants were initially divided into quartiles based on their energy intake from ultra-processed food (UPF) items, and subsequent analyses were performed accordingly. Baseline characteristics between groups were compared using analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables.
The association between UPF intake quartiles and the odds of metabolic syndrome (MetS), its components, and covariates was assessed using univariate logistic regression. Additionally, multivariate analysis using the backward LR method was employed to account for confounding factors, with variables exhibiting a p-value of less than .25 in the univariate analysis included in the multivariate model.
Results
The study revealed a significant association between ultra-processed food (UPF) intake and the likelihood of metabolic syndrome (MetS) after adjusting for potential confounders. Specifically, individuals in the highest quartile of UPF consumption had significantly higher odds of MetS compared to those in the lowest quartile (odds ratio (OR) = 3.27; 95% confidence interval (CI): 2.76–3.89).
Furthermore, higher UPF intake was correlated with increased odds of elevated triglycerides (TG), blood pressure, and fasting blood sugar (FBS), as well as decreased levels of high-density lipoprotein cholesterol (HDL-C). Specifically, compared to individuals in the lowest quartile of UPF consumption, those in the highest quartile had significantly elevated odds of high TG (OR = 1.71; 95% CI: 1.49–1.97), blood pressure (OR = 1.53; 95% CI: 1.30–1.79), FBS (OR = 1.30; 95% CI: 1.10–1.54), and reduced HDL-C (OR = 1.22; 95% CI: 1.08–1.39).
The study also identified a negative correlation between education level and high waist circumference (WC), suggesting that lower educational attainment may significantly influence obesity-related behaviors, such as dietary choices and physical activity engagement. This finding is consistent with previous research findings (Hermann et al., 2011).
Moreover, a negative association was observed between physical activity and high WC, elevated triglycerides (TG), low high-density lipoprotein cholesterol (HDL-C) levels, and increased fasting blood sugar (FBS) concentration. Correspondingly, a recent meta-analysis affirmed that regular aerobic exercise contributes to reductions in waist circumference (Armstrong et al., 2022). Additional studies have highlighted the role of regular leisure-time physical activity in combating obesity among older adults. These studies revealed that individuals engaging in leisure-time physical activity are less susceptible to developing both overall and abdominal obesity, as evidenced by lower body mass index (BMI) and WC measurements (Cárdenas Fuentes et al., 2018).
Exercise has been shown to significantly enhance the activity of hormone-sensitive lipases (HSLs), leading to a more efficient conversion of TG to free fatty acids (Enevoldsen et al., 2001; Haemmerle et al., 2002; Ogasawara et al., 2010). Additionally, exercise can stimulate the secretion of adiponectin, a protein hormone primarily produced by adipocytes, which plays a key role in regulating glucose levels and fatty acid breakdown. Adiponectin has been found to increase the levels of ATP-binding cassette transporter A1 and lipoprotein lipase (LPL) while reducing the levels of hepatic lipase (Yanai & Yoshida, 2019)
These findings suggest that a diet high in UPFs may contribute to the development of MetS and its associated components, highlighting the potential link between UPF consumption and the prevalence of non-communicable diseases.
Final Thoughts
The findings of this cross-sectional study conducted within the Fasa cohort indicated a correlation between increased consumption of ultra-processed foods (UPFs) and a higher prevalence of metabolic syndrome (MetS). Moreover, the study revealed that higher UPF intake was associated with a notable decrease in high-density lipoprotein cholesterol (HDL-C) levels and an increase in blood pressure, fasting blood sugar (FBS), and triglycerides (TG).
The current investigation demonstrated that MetS prevalence was 26.6% among individuals in the highest quartile of UPF consumption, highlighting a positive link between MetS and UPF intake. These findings align with prior research. For instance, a cross-sectional study on Canadian adults revealed a significant association between MetS and UPF consumption. Similarly, research by Tavares et al. on Brazilian adolescents found that increased UPF intake was linked to higher odds of MetS.
Furthermore, a cross-sectional study involving US adults showed that MetS prevalence rose by 4% with a 10% increase in UPF intake. However, a cohort study of Brazilian adults did not find any association between UPF consumption and MetS risk. The discrepancies in sample demographics and study designs may explain the variation between these findings and those of previous studies and the current investigation. These results indicate that diets rich in UPFs may be associated with the incidence of non-communicable diseases (NCDs). Further research is required to validate these findings.
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