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

20.3K
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...
20.3K
Regression Toward the Mean01:52

Regression Toward the Mean

7.3K
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...
7.3K
Obesity01:24

Obesity

1.6K
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...
1.6K
Pharmacokinetics in Pediatric Patients: Drug Distribution01:17

Pharmacokinetics in Pediatric Patients: Drug Distribution

499
Drug distribution in the pediatric population exhibits unique challenges and considerations due to the physiological differences between children, particularly neonates and infants, and adults. A crucial aspect of pediatric pharmacology is understanding how these differences impact the pharmacokinetics of various drugs, necessitating age-specific dosing strategies to ensure efficacy and safety.Neonates and infants have a higher total body water content, ~75%–90% of their body weight,...
499
Overview of Protein Metabolism01:21

Overview of Protein Metabolism

4.8K
Proteins are broken down into amino acids during digestion. Unlike fats and carbohydrates, which are stored for later use, proteins are not. Instead, amino acids are either used to produce ATP through oxidation or contribute to the creation of new proteins for the growth and repair of the body. Any surplus amino acids from the diet are converted into glucose or triglycerides rather than excreted.
Amino acids play various roles in the body once they are absorbed into cells. They are restructured...
4.8K
Oxygen Requirements and Growth Patterns01:29

Oxygen Requirements and Growth Patterns

2.4K
Microorganisms exhibit diverse oxygen requirements and growth patterns driven by their metabolic strategies and environmental adaptations. Oxygen, while essential for many organisms, can also be toxic under certain conditions, shaping how microorganisms grow and survive.Oxygen Requirements of MicroorganismsMicroorganisms are classified based on their ability to use or tolerate oxygen:● Obligate aerobes like Mycobacterium tuberculosis need oxygen for energy production, as it serves as the...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Multifaceted Education Training Toward Data Quality.

Journal of registry management·2025
Same author

The threat of gambling to public health in Ghana: time to act.

Perspectives in public health·2024
Same author

Infection Is Not Associated With Plasma or Cryoprecipitate Transfusion Volumes in Trauma: A Retrospective Study Using the National Trauma Data Bank.

Surgical infections·2024
Same author

More than mateship: exploring how Australian male expatriates, longer-term and frequent travellers experience social support.

International journal of qualitative studies on health and well-being·2023
Same author

Drinking and swimming around waterways: The role of alcohol, sensation-seeking, peer influence and risk in young people.

PloS one·2022
Same author

<i>Lacticaseibacillus rhamnosus</i> GG DSM 33156 effects on pathogen defence in the upper respiratory tract: a randomised, double-blind, placebo-controlled paediatric trial.

Beneficial microbes·2021

Related Experiment Video

Updated: Apr 14, 2026

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

18.5K

Low birth weight in Kansas.

V James Guillory, Sue Min Lai, R Suminski

    Journal of Health Care for the Poor and Underserved
    |April 28, 2015
    PubMed
    Summary

    Lack of private insurance and inadequate prenatal care increase the risk of low birth weight (LBW) infants. Maternal health and insurance status are key factors influencing infant outcomes.

    Area of Science:

    • Public Health
    • Maternal and Child Health
    • Health Services Research

    Background:

    • Low birth weight (LBW) is a significant contributor to infant morbidity and mortality.
    • This study is the first to examine LBW in Kansas using vital statistics.
    • Investigated maternal and healthcare system factors linked to LBW.

    Purpose of the Study:

    • To determine associations between LBW and prenatal care.
    • To identify links between LBW and maternal socio-demographic factors.
    • To explore the relationship between LBW and maternal medical factors or insurance status.

    Main Methods:

    • Utilized birth certificate data merged with Medicaid eligibility information.
    • Employed logistic regression analysis to examine factors associated with LBW.

    More Related Videos

    Assessment of Perigenital Sensitivity and Prostatic Mast Cell Activation in a Mouse Model of Neonatal Maternal Separation
    09:49

    Assessment of Perigenital Sensitivity and Prostatic Mast Cell Activation in a Mouse Model of Neonatal Maternal Separation

    Published on: August 13, 2015

    9.9K
    Assessment of Intestinal Transcytosis of Neonatal Escherichia coli Bacteremia Isolates
    08:32

    Assessment of Intestinal Transcytosis of Neonatal Escherichia coli Bacteremia Isolates

    Published on: February 17, 2023

    1.8K

    Related Experiment Videos

    Last Updated: Apr 14, 2026

    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

    18.5K
    Assessment of Perigenital Sensitivity and Prostatic Mast Cell Activation in a Mouse Model of Neonatal Maternal Separation
    09:49

    Assessment of Perigenital Sensitivity and Prostatic Mast Cell Activation in a Mouse Model of Neonatal Maternal Separation

    Published on: August 13, 2015

    9.9K
    Assessment of Intestinal Transcytosis of Neonatal Escherichia coli Bacteremia Isolates
    08:32

    Assessment of Intestinal Transcytosis of Neonatal Escherichia coli Bacteremia Isolates

    Published on: February 17, 2023

    1.8K
  • Analyzed data from 37,081 single vaginal births in Kansas.
  • Main Results:

    • Overall LBW rate was 5.5%, with higher rates among African Americans (10.8%) compared to White Americans (5%).
    • Lacking private insurance was associated with a 34% increase in LBW infants, reduced prenatal care, and increased comorbidity.
    • Maternal medical comorbidity and prior adverse birth outcomes were also linked to LBW.

    Conclusions:

    • Insurance status, quality of prenatal care, and maternal health during pregnancy are significantly associated with LBW.
    • Private insurance correlated with better access to prenatal care and improved infant outcomes.
    • Findings have critical implications for healthcare reform and policy interventions aimed at reducing LBW.