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

Life Tables01:22

Life Tables

582
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
582
Applications of Life Tables01:22

Applications of Life Tables

394
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
394
Actuarial Approach01:20

Actuarial Approach

344
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
344
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

677
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
677
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

472
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
472
Bone Disorders01:29

Bone Disorders

5.8K
Aging and its effect on bone remodeling is the most common cause of bone disorders. In young and healthy people, bone deposition and resorption happen at an equal rate to maintain optimal bone health.
Bone deposition is also affected by the levels of sex hormones like estrogen and testosterone that promote osteoblast activity and bone matrix synthesis. When the level of these hormones decreases due to aging, it causes a reduction in bone deposition. As a result, bone resorption by osteoclasts...
5.8K

You might also read

Related Articles

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

Sort by
Same author

Why has medicine expanded? The role of consumers.

Social science research·2015
Same author

Outcomes of antiretroviral treatment in HIV-infected adults: a dynamic and observational cohort study in Shenzhen, China, 2003-2014.

BMJ open·2015
Same author

[Optimal solution and analysis of muscular force during standing balance].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2015
Same author

Acupuncture for functional constipation: protocol of an individual patient data meta-analysis.

BMJ open·2015
Same author

Psora-4, a Kv1.3 Blocker, Enhances Differentiation and Maturation in Neural Progenitor Cells.

CNS neuroscience & therapeutics·2015
Same author

Systems mapping for hematopoietic progenitor cell heterogeneity.

PloS one·2015
Same journal

Brief Report: State Policy Contexts and Disability Risks Among Midlife Working-Age Latino Adults in the U.S.: Variation by Nativity and Citizenship Status.

Population research and policy review·2026
Same journal

Changes in the Education-Health Gradient Within U.S. States, 1993-2019.

Population research and policy review·2026
Same journal

Material Hardship Among Affluent and Poor Households in the United States.

Population research and policy review·2026
Same journal

Bearing the Reproductive Load? Unequal Reproductive Careers Among U.S. Women.

Population research and policy review·2026
Same journal

Life Course Timing of Mortality Exposure and Fertility Behavior.

Population research and policy review·2026
Same journal

The Future Availability of Family Caregivers: Implications for Late-Life Care Gaps.

Population research and policy review·2026
See all related articles

Related Experiment Video

Updated: Mar 8, 2026

Measurement of Lifespan in Drosophila melanogaster
10:00

Measurement of Lifespan in Drosophila melanogaster

Published on: January 7, 2013

35.7K

Age-Specific Variation in Adult Mortality Rates in Developed Countries.

Hui Zheng, Y Claire Yang, Kenneth C Land

    Population Research and Policy Review
    |January 31, 2017
    PubMed
    Summary
    This summary is machine-generated.

    Mortality variation in developed countries has increased since 1980, driven by young and middle-aged adults, not older populations. This study analyzes adult mortality rates and their variations over two centuries.

    Keywords:
    Hierarchical Age-Period-Cohort—Variance Function Regression Modelagingepidemiologic transitionmortality ratemortality selectionmortality variation

    More Related Videos

    Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
    08:53

    Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

    Published on: January 26, 2024

    1.7K
    Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography
    03:35

    Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography

    Published on: December 1, 2023

    790

    Related Experiment Videos

    Last Updated: Mar 8, 2026

    Measurement of Lifespan in Drosophila melanogaster
    10:00

    Measurement of Lifespan in Drosophila melanogaster

    Published on: January 7, 2013

    35.7K
    Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
    08:53

    Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine

    Published on: January 26, 2024

    1.7K
    Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography
    03:35

    Determining Gender-Based Differences in Retinal and Choroidal Thickness in Underweight Individuals via Swept-Source Optical Coherence Tomography

    Published on: December 1, 2023

    790

    Area of Science:

    • Demography
    • Epidemiology
    • Population Health

    Background:

    • Understanding historical trends in adult mortality variation is crucial for public health.
    • Developed countries have experienced significant demographic shifts over the past two centuries.

    Purpose of the Study:

    • To investigate historical changes in adult mortality rates and their variation within age intervals.
    • To analyze these changes across 15 developed countries over the last 200 years.

    Main Methods:

    • Application of an integrated Hierarchical Age-Period-Cohort-Variance Function Regression Model.
    • Utilizing data from the Human Mortality Database for comprehensive analysis.

    Main Results:

    • Mortality variation within age intervals generally increased across the life course, with some exceptions at advanced ages.
    • Significant declines in mortality variation were observed for cohorts born after the early 20th century.
    • While variation declined for much of the last two centuries, it has substantially increased since 1980, primarily due to young and middle-aged adults.

    Conclusions:

    • Recent increases in mortality variation are linked to younger adult age groups, not solely to aging populations or specific disease trends.
    • The findings highlight a complex, evolving pattern of mortality variation in developed nations.
    • Further research is needed to understand the drivers of increased mortality variation in younger adult populations.