Related Experiment Video
Updated: Jun 22, 2026

04:57
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Estimating pregnancy-related mortality from census data: experience in Latin America
Kenneth Hill1, Bernardo L Queiroz, Laura Wong
1Harvard University, Cambridge, MA, USA. kenneth_hill@harvard.edu
Bulletin of the World Health Organization
|June 25, 2009
Summary
National population censuses can estimate maternal mortality in countries with poor death registration. While methods showed promise, uncertainty remains for more challenging settings.
Area of Science:
- Demography
- Public Health
- Epidemiology
Background:
- Accurate maternal mortality data is crucial for public health interventions.
- Many countries lack reliable birth and death registration systems.
- National population censuses offer a potential data source.
Purpose of the Study:
- To assess the feasibility of using national population censuses to measure maternal mortality.
- To evaluate census data quality for demographic analysis in Latin America.
Main Methods:
- Utilized demographic techniques like the general growth balance method.
- Evaluated completeness and coverage of census household death and birth data.
- Calculated pregnancy-related mortality ratios (PRMRs) as a proxy for maternal mortality.
Main Results:
- PRMRs were estimated for Honduras (168), Nicaragua (95), and Paraguay (178) per 100,000 live births.
- Adjustments were needed for over/underreporting of adult deaths in Nicaragua, Paraguay, and Honduras.
- Adjusted estimates aligned with existing maternal mortality data, with source-dependent variations.
Conclusions:
- Census data can serve as a proxy for maternal mortality measurement where death registration is poor.
- Method applicability in less statistically robust environments requires further investigation.
- Data evaluation and adjustment methods introduced uncertainty that needs quantification.
Related Concept Videos
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,...
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,...
Population Growth
Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.However, realistic environmental conditions limit the number of...
Kaplan-Meier Approach
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Statistical Methods for Analyzing Epidemiological Data
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods: