Related Experiment Video

Updated: Mar 18, 2026

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

28.0K

Defining Obesity Using a Biological End Point in Sri Lankan Children

Vithanage Pujitha Wickramasinghe1, Carukshi Arambepola2, Priyantha Bandara3

  • 1Department of Pediatrics, Faculty of Medicine, University of Colombo, Kynsey Road, Colombo, Sri Lanka. pujithaw@yahoo.com.

Indian Journal of Pediatrics
|July 8, 2016
PubMed
Abstract

Keywords:
Fat massFat percentageMetabolic derangementsObesity diagnosisSri Lankan children

More Related Videos

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies14:56

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

5.3K
Intraperitoneal Glucose Tolerance Test, Measurement of Lung Function, and Fixation of the Lung to Study the Impact of Obesity and Impaired Metabolism on Pulmonary Outcomes08:30

Intraperitoneal Glucose Tolerance Test, Measurement of Lung Function, and Fixation of the Lung to Study the Impact of Obesity and Impaired Metabolism on Pulmonary Outcomes

Published on: March 15, 2018

14.8K

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...
1.5K
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...
332
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...
357
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...
269
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.5K