Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

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...
Sign Test for Nominal Data01:12

Sign Test for Nominal Data

The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
Drug Dosing: Obese Patients01:21

Drug Dosing: Obese Patients

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...
Dimensional Analysis03:40

Dimensional Analysis

Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
Range00:59

Range

The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Search for Light Pseudoscalar Bosons, Pair-Produced in Higgs Boson Decays in the Four-Electron Final State in Proton-Proton Collisions at sqrt[s]=13  TeV.

Physical review letters·2026
Same author

First Evidence for Mixing-Induced CP Violation in B_{s}^{0}→J/ψϕ(1020) Decays in pp Collisions at sqrt[s]=13  TeV.

Physical review letters·2026
Same author

Observation of Suppressed Charged-Particle Production in Ultrarelativistic Oxygen-Oxygen Collisions.

Physical review letters·2026
Same author

Measurement of D^{0} Meson Photoproduction in Ultraperipheral Heavy Ion Collisions.

Physical review letters·2026
Same author

Observation of tWZ Production at the CMS Experiment.

Physical review letters·2026
Same author

Prognostic impact of pathological complete response and response-adapted outcomes in patients with gastroesophageal adenocarcinoma treated with neoadjuvant or perioperative treatments: a multicentric cohort study.

ESMO open·2026

Related Experiment Video

Updated: Jul 5, 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

Relationship between analytic values and canine obesity.

C Peña1, L Suárez, I Bautista

  • 1Veterinary Medicine Service, Faculty of Veterinary Medicine, Las Palmas de Gran Canaria University, Las Palmas, Spain.

Journal of Animal Physiology and Animal Nutrition
|May 15, 2008
PubMed
Summary
This summary is machine-generated.

Canine obesity is linked to elevated serum lipid levels. This study found obese dogs had higher total cholesterol and triglycerides compared to normal-weight dogs.

More Related Videos

The Other End of the Leash: An Experimental Test to Analyze How Owners Interact with Their Pet Dogs
08:59

The Other End of the Leash: An Experimental Test to Analyze How Owners Interact with Their Pet Dogs

Published on: October 13, 2017

A Simple Fecal Flotation Method for Diagnosing Zoonotic Nematodes Under Field and Laboratory Conditions
03:46

A Simple Fecal Flotation Method for Diagnosing Zoonotic Nematodes Under Field and Laboratory Conditions

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Jul 5, 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

The Other End of the Leash: An Experimental Test to Analyze How Owners Interact with Their Pet Dogs
08:59

The Other End of the Leash: An Experimental Test to Analyze How Owners Interact with Their Pet Dogs

Published on: October 13, 2017

A Simple Fecal Flotation Method for Diagnosing Zoonotic Nematodes Under Field and Laboratory Conditions
03:46

A Simple Fecal Flotation Method for Diagnosing Zoonotic Nematodes Under Field and Laboratory Conditions

Published on: December 15, 2023

Area of Science:

  • Veterinary Medicine
  • Canine Health
  • Metabolic Disorders

Background:

  • Obesity is a prevalent health concern in domestic dogs.
  • Canine obesity can lead to various metabolic disturbances.
  • Understanding metabolic changes associated with canine body condition is crucial for preventative care.

Purpose of the Study:

  • To investigate the association between canine body condition and key metabolic parameters.
  • To compare serum lipid profiles, blood glucose, and alanine aminotransferase (ALT) levels in obese versus normal-weight dogs.
  • To establish a clearer link between obesity and metabolic health in dogs.

Main Methods:

  • A cohort of 127 dogs (42 males, 85 females) was evaluated during routine veterinary visits.
  • Body condition (BC) was assessed using the Laflamme scale, with scores over 6 indicating obesity.
  • Serum levels of total cholesterol, high-density lipoprotein cholesterol, triglycerides, basal glucose, and ALT were measured.

Main Results:

  • A significant proportion of the study cohort (66.1%) was classified as obese.
  • Obese dogs exhibited significantly higher levels of total cholesterol and triglycerides compared to normal-weight dogs (p < 0.05).
  • No significant differences were noted in basal glucose or ALT levels between obese and normal-weight groups (data not shown in abstract).

Conclusions:

  • Canine obesity is strongly associated with dyslipidemia, specifically elevated serum lipid levels.
  • These findings highlight the metabolic impact of excess weight in dogs.
  • Managing canine weight is essential for mitigating associated metabolic health risks.