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

Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
z Scores and Area Under the Curve01:17

z Scores and Area Under the Curve

z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of zero.
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Central Limit Theorem01:14

Central Limit Theorem

The central limit theorem, abbreviated as clt, is one of the most powerful and useful ideas in all of statistics. The central limit theorem for sample means says that if you repeatedly draw samples of a given size and calculate their means, and create a histogram of those means, then the resulting histogram will tend to have an approximate normal bell shape. In other words, as sample sizes increase, the distribution of means follows the normal distribution more closely.
The sample size, n, that...
Normal Distribution01:11

Normal Distribution

The normal, a continuous distribution, is the most important of all the distributions. Its graph is a bell-shaped symmetrical curve, which is observed in almost all disciplines. Some of these include psychology, business, economics, the sciences, nursing, and, of course, mathematics. Some instructors may use the normal distribution to help determine students’ grades. Most IQ scores are normally distributed. Often real-estate prices fit a normal distribution. The normal distribution is extremely...
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...

You might also read

Related Articles

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

Sort by
Same author

Navigating the Grey Zone: A Mixed-Methods Study to Evaluate a Decision Support Tool in the SOGC Late Preterm Antenatal Corticosteroids Guideline.

Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC·2026
Same author

Pregnancy Weight Gain and Longer-Term Maternal Cardiometabolic Conditions.

Hypertension (Dallas, Tex. : 1979)·2026
Same author

Development and Validation of a Prediction Model for Cardiovascular Risk in Reproductive-Aged Women.

JACC. Advances·2026
Same author

Clinical Considerations for Implementing Placental Growth Factor-Based Testing in Urban and Rural Regions in Canada.

Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC·2026
Same author

Severe maternal morbidity is associated with increased risk of cerebral palsy in offspring.

American journal of obstetrics and gynecology·2026
Same author

Maternal Diabetes and Risk of Epilepsy in Offspring.

Pediatrics·2026

Related Experiment Video

Updated: Jun 6, 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

The case against customised birthweight standards.

Jennifer A Hutcheon1, Xun Zhang, Robert W Platt

  • 1Department of Obstetrics & Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada.

Paediatric and Perinatal Epidemiology
|December 8, 2010
PubMed
Summary
This summary is machine-generated.

Customised birthweight standards improve perinatal outcome prediction, but benefits stem from estimated fetal weight (EFW) rather than maternal factors. Adjusting for maternal characteristics offers little predictive value for individual birthweights.

More Related Videos

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
07:56

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

Related Experiment Videos

Last Updated: Jun 6, 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

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts
07:56

Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

Area of Science:

  • Perinatal Medicine
  • Neonatology
  • Obstetrics

Background:

  • Customised birthweight standards are recognized for improving adverse perinatal outcome prediction over conventional charts.
  • The benefits of customised standards are primarily attributed to the inclusion of intrauterine-based estimated fetal weight (EFW) reference values, particularly at preterm ages.

Discussion:

  • Maternal characteristics explain population-level birthweight variations but are weak individual predictors.
  • Maternal factors account for a small percentage of total birthweight influences, making population averages the best individual estimates.
  • Customised percentiles cannot differentiate pathological from physiological maternal influences on birthweight.

Key Insights:

  • The predictive advantage of customised birthweight standards is linked to EFW incorporation, not maternal characteristic adjustment.
  • Individual birthweight prediction is minimally improved by accounting for maternal characteristics.
  • There is limited justification for customising birthweight percentiles based on maternal characteristics.

Outlook:

  • Future research may explore alternative methods for incorporating relevant individual factors beyond maternal characteristics.
  • Focus may shift towards refining EFW-based prediction models for enhanced perinatal outcome assessment.
  • Further investigation into the complex interplay of genetic and environmental factors influencing birthweight is warranted.