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Related Concept Videos

Obesity01:24

Obesity

1.1K
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...
1.1K
Pharmacokinetics in Obese Patients: Drug Absorption and Distribution01:25

Pharmacokinetics in Obese Patients: Drug Absorption and Distribution

218
Obesity significantly alters the pharmacokinetic processes of drug absorption and distribution, presenting unique challenges in medical treatment. The increased fat tissue and decreased lean muscle in obese individuals can significantly affect how drugs are absorbed into the body and distributed across different tissues. This alteration can lead to variances in the effectiveness and safety of medications, necessitating adjustments in dosing or drug selection for obese patients.One notable...
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Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion01:20

Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion

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Drug metabolism, a critical process in the liver, involves two primary phases: Phase I reactions and Phase II conjugation. Obesity introduces significant alterations in this metabolic process, primarily due to fatty infiltration of the liver, leading to conditions such as nonalcoholic fatty liver disease (NAFLD). This condition can modify the activities of both Phase I and II enzymes, impacting how drugs are metabolized in obese patients.Phase I metabolism sees variable effects across...
153

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Multidisciplinary Approach to Obesity Management: A Case Report
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Multimodal (Bio)Markers and Risk of Obesity - A Comprehensive Scoping Review.

Farhad Vahid1, Alejandra Loyola-Leyva1, Josep Tur2

  • 1Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.

Advances in Nutrition (Bethesda, Md.)
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

Early obesity risk detection requires a multimodal approach, integrating various biomarkers and advanced tools like AI. This strategy is crucial for effective prevention and personalized intervention strategies.

Keywords:
dietemotionsgut microbiomemiRNAmulticlass markersmulticomponent markersmultidimensionaloverweight

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Area of Science:

  • Biomedical science
  • Public health
  • Preventive medicine

Background:

  • Obesity is a complex, multifactorial condition linked to chronic diseases, with prevalence rates remaining high despite global efforts.
  • Early detection of obesity risk is vital for timely intervention, but single biomarkers are insufficient for accurate risk stratification.
  • Numerous factors contribute to obesity, including genetics, lifestyle, psychological status, and gut microbiota.

Purpose of the Study:

  • To review the current advancements in obesity risk prediction using multimodal biomarker approaches.
  • To highlight novel strategies and assess the feasibility and effectiveness of these biomarkers in clinical settings.
  • To provide recommendations for future research and clinical applications in obesity prevention.

Main Methods:

  • Scoping review of existing literature on obesity biomarkers and risk prediction.
  • Analysis of multimodal approaches integrating classical markers, multi-omics data, behavioral factors, psychological traits, and gut microbiota.
  • Examination of the role of machine learning and artificial intelligence in interpreting complex biomarker data.

Main Results:

  • A multimodal approach, combining diverse data types and advanced analytics, shows promise for improved obesity risk prediction.
  • Integrating genetics, epigenetics, metabolomics, behavioral data, and gut microbiota offers a more comprehensive view of individual risk.
  • Machine learning and AI are essential for synthesizing complex datasets and enabling personalized risk stratification.

Conclusions:

  • Multimodal biomarker strategies are essential for accurate obesity risk assessment and personalized prevention.
  • Future research should focus on validating these integrated approaches in diverse populations and clinical trials.
  • The effective application of these biomarkers can lead to more targeted and successful obesity countermeasure initiation.