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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...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A higher...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's proficiency in drug...
Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results from...

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Related Experiment Video

Updated: Jun 22, 2026

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

Complex systems modeling for obesity research.

Ross A Hammond1

  • 1Center on Social and Economic Dynamics, Economic Studies Program, The Brookings Institution, 1775 Massachusetts Ave, NW, Washington, DC 20036, USA. rhammond@brookings.edu

Preventing Chronic Disease
|June 17, 2009
PubMed
Summary
This summary is machine-generated.

The obesity epidemic is a complex adaptive system, requiring novel approaches. Complexity science offers tools to better understand and combat this public health challenge.

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Development and Validation of a Methodology for Establishing Obese Rat Models with Typical Fatty Pancreas
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Development and Validation of a Methodology for Establishing Obese Rat Models with Typical Fatty Pancreas

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Last Updated: Jun 22, 2026

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

Published on: April 4, 2012

Development and Validation of a Methodology for Establishing Obese Rat Models with Typical Fatty Pancreas
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Development and Validation of a Methodology for Establishing Obese Rat Models with Typical Fatty Pancreas

Published on: November 11, 2025

Area of Science:

  • Public Health
  • Complexity Science
  • Systems Science

Background:

  • The global obesity epidemic presents a significant public health challenge.
  • Existing approaches struggle due to the epidemic's multifaceted nature.
  • There is a critical need for effective policy interventions to address obesity.

Purpose of the Study:

  • To identify the obesity epidemic as a complex adaptive system.
  • To advocate for the application of complexity science to obesity research and policy.
  • To introduce modeling techniques suitable for studying obesity dynamics.

Main Methods:

  • Characterizing the obesity epidemic by its scale, actor diversity, and mechanisms.
  • Applying principles of complex adaptive systems to understand obesity drivers.
  • Reviewing modeling techniques relevant to complex systems dynamics.

Main Results:

  • The obesity epidemic exhibits characteristics of a complex adaptive system.
  • Complexity science provides valuable frameworks for studying obesity.
  • Specific modeling techniques can illuminate obesity's intricate dynamics.

Conclusions:

  • Understanding obesity as a complex adaptive system is crucial for effective interventions.
  • Complexity science offers innovative tools for obesity research and policy development.
  • Advanced modeling can inform the design of targeted and effective obesity policies.