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

Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion01:20

Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion

115
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...
115
Drug Dosing: Obese Patients01:21

Drug Dosing: Obese Patients

161
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...
161
Pharmacokinetics in Obese Patients: Drug Absorption and Distribution01:25

Pharmacokinetics in Obese Patients: Drug Absorption and Distribution

162
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...
162
Obesity01:24

Obesity

1.0K
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...
1.0K
Cholesterol: Significance and Regulation01:29

Cholesterol: Significance and Regulation

1.2K
Although not a source of energy, cholesterol plays a significant role as a foundational structure for bile salts, steroid hormones, and vitamin D, as well as being a crucial component of plasma membranes. Approximately 15% of blood cholesterol is derived from our diet, with the remainder synthesized from acetyl CoA by the liver and intestines. Cholesterol is eliminated from the body through its conversion into bile salts, which are eventually discarded in the feces.
Considering cholesterol and...
1.2K
Hypodermis01:02

Hypodermis

7.1K
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...
7.1K

You might also read

Related Articles

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

Sort by
Same author

Intratumoral CD39<sup>+</sup>CD8<sup>+</sup> T Cells Predict Response to Programmed Cell Death Protein-1 or Programmed Death Ligand-1 Blockade in Patients With NSCLC.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer·2021
Same author

Improving Albino Tea Quality by Foliar Application of Glycinebetaine as a Green Regulator under Lower Temperature Conditions.

Journal of agricultural and food chemistry·2021
Same author

Neuroprotective Pentapeptide, CN-105, Improves Outcomes in Translational Models of Intracerebral Hemorrhage.

Neurocritical care·2021
Same author

Maternal and Fetal Outcomes in Systemic Lupus Erythematosus Pregnancies.

Annals of the Academy of Medicine, Singapore·2021
Same author

A novel Q93H missense mutation in DCTN1 caused distal hereditary motor neuropathy type 7B and Perry syndrome from a Chinese family.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2021
Same author

Enhancer-derived long non-coding RNAs CCAT1 and CCAT2 at rs6983267 has limited predictability for early stage colorectal carcinoma metastasis.

Scientific reports·2021

Related Experiment Video

Updated: Dec 19, 2025

Author Spotlight: Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration
10:37

Author Spotlight: Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration

Published on: June 9, 2023

3.8K

Association between hyperuricemia and nontraditional adiposity indices.

Xing Zhen Liu1, Hui Hua Li2, Shan Huang3

  • 1Army Convalescence Area, Hangzhou Sanatorium of People's Liberation Army, Hangzhou, China.

Clinical Rheumatology
|December 1, 2018
PubMed
Summary

Lipid accumulation product (LAP) and cardiometabolic index (CMI) show a strong association with hyperuricemia in adults. These adiposity indices may help monitor hyperuricemia in overweight and obese individuals.

Keywords:
Adiposity indicesHyperuricemiaObesity

More Related Videos

Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

27.6K
Localization, Identification, and Excision of Murine Adipose Depots
08:53

Localization, Identification, and Excision of Murine Adipose Depots

Published on: December 4, 2014

41.8K

Related Experiment Videos

Last Updated: Dec 19, 2025

Author Spotlight: Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration
10:37

Author Spotlight: Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration

Published on: June 9, 2023

3.8K
Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

27.6K
Localization, Identification, and Excision of Murine Adipose Depots
08:53

Localization, Identification, and Excision of Murine Adipose Depots

Published on: December 4, 2014

41.8K

Area of Science:

  • Metabolic Health
  • Obesity Research
  • Cardiovascular Risk Factors

Background:

  • The relationship between novel adiposity indices and hyperuricemia remains unclear.
  • Overweight and obesity are significant risk factors for hyperuricemia.
  • Understanding these associations can aid in managing hyperuricemia.

Purpose of the Study:

  • To investigate the association between various adiposity indices and hyperuricemia.
  • To identify reliable indicators for hyperuricemia management in overweight/obese populations.

Main Methods:

  • Cross-sectional study of 174,698 adults.
  • Analysis of body adiposity index (BAI), conicity index (CI), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), lipid accumulation product (LAP) index, and cardiometabolic index (CMI).
  • Multivariate logistic analysis and receiver operating characteristic (ROC) curve analysis were employed.

Main Results:

  • Lipid accumulation product (LAP) and cardiometabolic index (CMI) demonstrated the strongest association with hyperuricemia.
  • The odds ratio for hyperuricemia in the highest quartile of LAP was 2.049 and for CMI was 4.332.
  • Area under the curve (AUC) values were 0.632 for LAP and 0.687 for CMI, indicating predictive power.

Conclusions:

  • LAP and CMI are strongly associated with hyperuricemia, outperforming other indices.
  • These indices, combining waist circumference and lipid parameters, can serve as potential monitoring tools.
  • LAP and CMI may be valuable indicators for managing hyperuricemia in overweight and obese individuals.