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Obesity

Obesity

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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In the United States, obesity is a prominent concern. It is linked to heightened mortality rates due to increased occurrences of conditions such as hypertension, atherosclerosis, coronary artery disease, and diabetes compared to nonobese individuals. A patient is classified as obese if their actual body weight surpasses the ideal or desirable body weight by 20%, based on Metropolitan Life Insurance Company data. Ideal body weights consider average weights and heights for males and females...

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Pharmacokinetics in Obese Patients: Drug Absorption and Distribution

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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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...

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Related Experiment Video

Updated: Feb 2, 2026

Multidisciplinary Approach to Obesity Management: A Case Report

Multidisciplinary Approach to Obesity Management: A Case Report

Published on: May 30, 2025

Obesity and dyslipidemia.

Jelena Vekic¹, Aleksandra Zeljkovic¹, Aleksandra Stefanovic¹

¹Department of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia.

Metabolism: Clinical and Experimental

|November 18, 2018

Summary

Obesity is linked to dyslipidemia, but this varies individually. Some metabolically healthy obese individuals show less severe or absent dyslipidemia, highlighting unique mechanisms and potential new biomarkers.

Keywords:

Adipokines Insulin resistance MicroRNA PCSK9 Small, dense LDL Sphingosine-1-phosphate Vitamin D

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Area of Science:

Endocrinology
Metabolic Syndrome
Cardiovascular Risk

Background:

Obesity is a global pandemic strongly associated with dyslipidemia.
Dyslipidemia in obesity is primarily driven by insulin resistance and pro-inflammatory adipokines.
Obesity-induced dyslipidemia exhibits distinct characteristics influenced by individual factors, with some metabolically healthy obese individuals showing less pronounced or absent dyslipidemia.

Purpose of the Study:

To review the main characteristics and mechanisms of dyslipidemia development in obesity.
To identify areas for further investigation to improve understanding and management of obesity-related dyslipidemia and cardiometabolic risk.
To discuss novel lipid biomarkers, including PCSK9, S1P, and microRNAs, for obesity-associated dyslipidemia.

Main Methods:

Literature review focusing on obesity, dyslipidemia, insulin resistance, adipokines, and lipid biomarkers.
Analysis of recent evidence on individual variations in obesity-induced dyslipidemia.
Exploration of emerging biomarkers such as PCSK9, S1P, and microRNAs.

Main Results:

Dyslipidemia in obesity is not uniform and varies based on individual factors.
Metabolically healthy obese individuals may present with less severe or absent dyslipidemia.
Novel biomarkers like PCSK9, S1P, and microRNAs show potential for understanding and diagnosing obesity-associated dyslipidemia.

Conclusions:

Understanding the heterogeneity of obesity-induced dyslipidemia is crucial for personalized cardiometabolic risk management.
Further research into novel biomarkers is needed to develop targeted prevention and treatment strategies.
MicroRNAs may serve as valuable biomarkers for obesity-associated dyslipidemia.