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

z Scores and Area Under the Curve01:17

z Scores and Area Under the Curve

11.4K
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...
11.4K
Coefficient of Correlation01:12

Coefficient of Correlation

6.4K
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...
6.4K
Nature and Nurture01:10

Nature and Nurture

20.8K
Many human characteristics, like height, are shaped by both nature—in other words, by our genes—and by nurture, or our environment. For example, chronic stress during childhood inhibits the production of growth hormones and consequently reduces bone growth and height. Scientists estimate that 70-90% of variation in height is due to genetic differences among individuals, and 10-30% of variation in height is due to differences in the environments that individuals experience,...
20.8K
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.8K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.8K
Introduction to z Scores01:06

Introduction to z Scores

10.0K
A z score (or standardized value) is measured in units of the standard deviation. It 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 zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
10.0K
Introduction to Developmental Psychology01:27

Introduction to Developmental Psychology

527
Developmental psychology explores the changes and continuities in human abilities throughout life, encompassing physical, cognitive, linguistic, and social dimensions. Human development is not restricted to growth, but includes aspects of decline, particularly in physical abilities as individuals age. Developmental psychologists seek to understand how people change as they age and how their mental and social skills evolve.Developmental MilestonesA key concept in developmental psychology is...
527

You might also read

Related Articles

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

Sort by
Same author

Temperature and heat-load exposure effects on preterm births: Insights from a population-based study using distributed lag non-linear models.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics·2026
Same author

Paracetamol exposure during pregnancy, the risk of major congenital malformations, and perinatal and postnatal outcomes: a population-based cohort study.

Human reproduction open·2026
Same author

First-trimester nonsteroidal anti-inflammatory drugs exposure and risk of major congenital malformations: A retrospective register-based cohort study.

PLoS medicine·2026
Same author

Early 60-Day Morbidity after Sleeve Gastrectomy Versus One-Anastomosis Gastric Bypass: A Propensity-Matched Single-Center Cohort of 2,382 Patients.

Obesity surgery·2026
Same author

Exposure to pseudoephedrine during pregnancy and major congenital malformations: Findings from a large population-based cohort of pregnancies.

British journal of clinical pharmacology·2025
Same author

Exposure to pseudoephedrine during pregnancy and major congenital malformations: Findings from a large population-based cohort of pregnancies.

British journal of clinical pharmacology·2025

Related Experiment Video

Updated: Sep 13, 2025

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers
09:16

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Published on: March 14, 2018

10.3K

Residential Socio-Demographic Scoring and Child Growth.

Ornit Cohen1,2, Natalya Bilenko2,3, Eytan Israel4,5

  • 1Research and Innovation Authority, Wolfson Medical Center, Holon, Israel.

Paediatric and Perinatal Epidemiology
|August 2, 2025
PubMed
Summary

Children in lower socioeconomic residential areas show impaired growth trajectories, highlighting the need to identify at-risk regions for targeted interventions to improve child development outcomes.

Keywords:
child developmentshort staturesocioeconomic statusstuntingwasting

More Related Videos

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
11:29

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Published on: June 20, 2020

9.3K
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

27.2K

Related Experiment Videos

Last Updated: Sep 13, 2025

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers
09:16

Use of a Video Scoring Anchor for Rapid Serial Assessment of Social Communication in Toddlers

Published on: March 14, 2018

10.3K
Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
11:29

Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools

Published on: June 20, 2020

9.3K
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

27.2K

Area of Science:

  • Pediatric Health
  • Socioeconomic Determinants of Health
  • Child Development

Background:

  • Individual socioeconomic factors are well-studied in child growth.
  • Broader, area-level socio-demographic characteristics of residential areas lack thorough assessment in relation to child growth.

Purpose of the Study:

  • To examine associations between area-level socio-demographic features of residential areas and child growth trajectories.
  • Investigate the impact of neighborhood socioeconomic status on child development.

Main Methods:

  • Population-based retrospective cohort study of 1,485,198 children born in Israel (2004-2018).
  • Utilized Mother and Child Health Clinics (MCHC) data for postnatal follow-up and developmental assessments up to age 6.
  • Socio-demographic scoring from the Israel Bureau of Statistics was linked to residential areas (rural and urban micro-geographical areas).
  • Calculated height-for-age (HAZ) and weight-for-age (WAZ) z-scores from MCHC visit data.

Main Results:

  • Children in low socioeconomic status (SES) areas exhibited consistently lower HAZ and WAZ scores compared to those in higher SES areas.
  • Significant differences in birth HAZ and WAZ scores were observed between high and low SES areas (β=0.3 and β=0.1, respectively).
  • Growth trajectories showed early advantages in higher SES groups, followed by a plateau and later acceleration.

Conclusions:

  • Evidence of impaired child growth in lower socio-demographic areas supports the importance of area-level analysis.
  • Identifying regions based on global attributes is crucial for pinpointing areas prone to child growth impairment, especially in developed countries.