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Related Concept Videos

Life Tables01:22

Life Tables

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,...
Applications of Life Tables01:22

Applications of Life Tables

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...
Actuarial Approach01:20

Actuarial Approach

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,...
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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 Cox...
Life Histories01:29

Life Histories

Constrained by limited energy and resources, organisms must compromise between offspring quantity and parental investment. This trade-off is represented by two primary reproductive strategies; K-strategists produce few offspring but provide substantial parental support, whereas r-strategists produce much progeny that receives little care. These strategies are related to an organism’s survival likelihood across its lifespan, which is represented by a survivorship curve. Three general types of...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

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Related Experiment Video

Updated: Jul 10, 2026

Measurement of Lifespan in Drosophila melanogaster
10:00

Measurement of Lifespan in Drosophila melanogaster

Published on: January 7, 2013

Mortality differences according to living arrangements.

Seppo Koskinen1, Kaisla Joutsenniemi, Tuija Martelin

  • 1National Public Health Institute, Department of Health and Functional Capacity, Helsinki, Finland. seppo.koskinen@ktl.fi

International Journal of Epidemiology
|November 1, 2007
PubMed
Summary
This summary is machine-generated.

Living arrangements significantly impact mortality risk, especially for working-aged adults. Cohabiting, living alone, or with non-partners shows higher mortality rates, partly due to socioeconomic factors and alcohol consumption.

Related Experiment Videos

Last Updated: Jul 10, 2026

Measurement of Lifespan in Drosophila melanogaster
10:00

Measurement of Lifespan in Drosophila melanogaster

Published on: January 7, 2013

Area of Science:

  • Demography
  • Public Health
  • Sociology

Background:

  • Mortality rates vary across different marital statuses and societies.
  • Changing living arrangements (e.g., consensual unions, living alone) necessitate a more detailed classification.

Purpose of the Study:

  • To analyze mortality differences based on detailed living arrangements.
  • To investigate the impact of partnership status and household composition on mortality.
  • To identify causes of death associated with specific living arrangements.

Main Methods:

  • Analysis of mortality by cause-of-death in the Finnish population aged 30+ (1996-2000).
  • Utilized a linked register dataset covering 15.7 million person-years and 210,139 deaths.

Main Results:

  • Working-aged cohabiters faced nearly 70% higher mortality than married individuals.
  • Men living alone or with non-partners had triple the mortality of married men; women in similar situations had comparable mortality to cohabiters.
  • Excess mortality was linked to alcohol-related causes, accidents, and lung cancer, and was exacerbated by having no children.

Conclusions:

  • Significant mortality disparities exist based on living arrangements, particularly in the working-aged population.
  • Socioeconomic factors partially explain these mortality differences.
  • Excessive alcohol use is identified as a key contributor to mortality variations.