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Related Concept Videos

Obesity01:24

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 adipocytes...
Hypodermis01:02

Hypodermis

The hypodermis (the subcutaneous layer or superficial fascia) is present directly below the dermis. It connects the skin to the underlying fascia (fibrous tissue) of the bones and muscles. It is not strictly a part of the skin, although the border between the hypodermis and dermis can be difficult to distinguish. The hypodermis consists of well-vascularized, loose, areolar connective tissue and adipose tissue, which functions as a mode of fat storage and provides insulation and cushioning for...
Pharmacokinetics in Obese Patients: Drug Absorption and Distribution01:25

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...
Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion01:20

Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion

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...
Regulation of Food Intake01:30

Regulation of Food Intake

Short-term regulation of food intake primarily involves neural signals from the gastrointestinal (GI) tract, blood nutrient levels, and GI tract hormones. Communication between the gut and brain via vagal nerve fibers plays a significant role in evaluating the contents of the gut. Clinical studies have shown that protein ingestion produces a more prolonged response in these nerve fibers compared to an equivalent amount of glucose. Additionally, the activation of stretch receptors caused by GI...
Functional Brain Systems: Limbic System01:15

Functional Brain Systems: Limbic System

The limbic system, often called the "emotional brain," is a complex set of structures located deep within the brain. The intricate network of the limbic system supports a wide range of psychological functions, from emotional regulation to memory formation and sensory processing. This functional brain region encompasses specific parts of the diencephalon and the cerebrum, integrating the higher mental functions of the cerebral cortex with the primitive emotional responses of the deep brain...

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Related Experiment Video

Updated: Jun 21, 2026

Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Brain structure and obesity.

Cyrus A Raji1, April J Ho, Neelroop N Parikshak

  • 1Department of Pathology, University of Pittsburgh, Pennsylvania, USA.

Human Brain Mapping
|August 8, 2009
PubMed
Summary
This summary is machine-generated.

Obesity is linked to brain atrophy in cognitively normal elderly individuals. Higher Body Mass Index (BMI) correlates with reduced brain volume, particularly in frontal and temporal regions, indicating potential long-term neurological consequences.

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Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
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Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography

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Related Experiment Videos

Last Updated: Jun 21, 2026

Control of Eating Behavior Using a Novel Feedback System
04:48

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Published on: May 8, 2018

Exploring Adipose Tissue Structure by Methylsalicylate Clearing and 3D Imaging
10:10

Exploring Adipose Tissue Structure by Methylsalicylate Clearing and 3D Imaging

Published on: August 19, 2020

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
13:09

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography

Published on: April 4, 2012

Area of Science:

  • Neuroimaging
  • Gerontology
  • Metabolic Health

Background:

  • Obesity and Type II Diabetes Mellitus (DM2) are linked to cardiovascular issues, which in turn increase dementia risk.
  • The specific association between obesity, DM2, and patterns of brain atrophy in cognitively normal elderly individuals remains unclear.

Purpose of the Study:

  • To investigate the relationship between obesity, Type II Diabetes Mellitus (DM2), and fasting plasma insulin (FPI) levels with brain atrophy patterns in elderly subjects.
  • To identify specific brain regions affected by obesity and DM2 in a cognitively normal aging population.

Main Methods:

  • Tensor-based morphometry (TBM) was used to analyze gray matter (GM) and white matter (WM) volumes in 94 cognitively normal elderly subjects.
  • Statistical analyses included bivariate correlations, multiple regression, and ANCOVA, controlling for age, gender, and race.

Main Results:

  • Higher Body Mass Index (BMI) was significantly associated with gray matter atrophy in frontal, temporal, and subcortical regions.
  • Obese individuals (BMI > 30) exhibited atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus.
  • Overweight individuals (BMI 25-30) showed atrophy in the basal ganglia and corona radiata; overall brain volume did not differ between overweight and obese groups.

Conclusions:

  • Obesity is associated with detectable brain volume deficits in cognitively normal elderly individuals.
  • Higher BMI is a significant predictor of brain atrophy, even in the absence of cognitive impairment.
  • These findings highlight the neurobiological impact of obesity on the aging brain.