Related Experiment Video
Updated: May 18, 2026

10:00
Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
Reproductive history patterns and long-term mortality rates: a Danish, population-based record linkage study.
Priscilla K Coleman1, David C Reardon, Byron C Calhoun
1Human Development and Family Studies, Bowling Green State University, Bowling Green, OH 43403, USA. pcolema@bgnet.bgsu.edu
European Journal of Public Health
|September 8, 2012
Summary
Pregnancy outcomes significantly impact mortality risk. Induced abortions and natural losses, especially in combination, increase mortality rates, while multiple births show decreased risk. Further research into underlying mechanisms is needed.
Area of Science:
- Reproductive Health
- Epidemiology
- Public Health
Background:
- Inconsistent definitions and incomplete data obscure pregnancy-related mortality risks.
- Population-based record-linkage studies offer accurate maternal mortality rate data.
Purpose of the Study:
- To examine associations between pregnancy resolution patterns and long-term mortality risks.
- To provide accurate maternal mortality data using a population-based approach.
Main Methods:
- Danish population-based study of 1,001,266 women born between 1962 and 1993.
- Analysis of mortality rates across 25 years linked to pregnancy resolution patterns.
- Statistical controls for parity, birth year, and age at last pregnancy.
Main Results:
- Combined induced abortion(s) and natural loss(es) showed over three times higher mortality than birth(s) alone.
- Increased mortality risks observed for women with induced abortions or natural losses compared to birth(s) only.
- Women never pregnant had over six times higher mortality risk than those with birth(s) only; multiple births correlated with decreased risk.
Conclusions:
- Reproductive history significantly influences mortality rates.
- Findings highlight the need for further research into the mechanisms underlying these associations.
- This study provides a comprehensive view of reproductive history and mortality.
Related Concept Videos
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...
Longitudinal Studies
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Life Histories
Overview
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...
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,...
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,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...