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The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
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Groups play a fundamental role in shaping individual behavior, as they establish norms that guide interactions and decision-making. Social psychology examines how individuals conform to group expectations, often adjusting their attitudes and actions to align with group norms. These norms can be formal, such as workplace policies, or informal, such as unspoken social expectations within a fraternity.Conformity and Social InfluenceConformity arises when individuals modify their behaviors or...
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Distinct Gut Microbiome Profiles Underlying Cardiometabolic Risk Phenotypes in Individuals with Obesity.

Iveta Nedeva1, Yavor Assyov2, Veselka Duleva3

  • 1Department of Epidemiology and Hygiene, Medical University Sofia, 1431 Sofia, Bulgaria.

Nutrients
|January 28, 2026
PubMed
Summary

Specific gut bacteria are linked to obesity-related heart and metabolic risks. Reduced Lachnospiraceae, Faecalibacterium, and increased Prevotella showed associations with metabolic syndrome, hypertension, and dyslipidemia, respectively.

Keywords:
cardiometabolic riskgut microbiomemetabolic syndromeobesity

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Area of Science:

  • Microbiology
  • Metabolic Health
  • Obesity Research

Background:

  • Obesity is linked to cardiometabolic disorders.
  • Gut microbiome alterations are implicated, but specific microbial signatures are unclear.

Purpose of the Study:

  • Investigate associations between gut bacterial taxa and cardiometabolic risk phenotypes in obese individuals.
  • Identify potential microbial biomarkers for metabolic syndrome, hypertension, and dyslipidemia.

Main Methods:

  • Cross-sectional study of 100 adults with obesity.
  • Gut microbiome analysis using targeted multiplex real-time PCR.
  • Correlation, ROC curve, and logistic regression analyses for associations.

Main Results:

  • Reduced Lachnospiraceae abundance linked to metabolic syndrome.
  • Lower Faecalibacterium abundance associated with arterial hypertension.
  • Increased Prevotella abundance correlated with dyslipidemia.

Conclusions:

  • Specific gut microbiome signatures are associated with cardiometabolic risk in obesity.
  • Findings are exploratory and require further validation in larger, longitudinal studies.