Related Experiment Video
Updated: Jan 2, 2026
06:55
Assessment of Maternal Vascular Remodeling During Pregnancy in the Mouse Uterus
Published on: December 5, 2015
14.0K
Using census data to measure maternal mortality: A review of recent experience
Kenneth Hill1, Peter Johnson2, Kavita Singh3
1Independent researcher, USA.
Demographic Research
|December 12, 2019
Summary
National censuses offer valuable, though imperfect, data for tracking maternal mortality in countries without robust statistics. Careful analysis and adjustments are needed to derive reliable maternal mortality ratio estimates.
Area of Science:
- Demography
- Public Health
- Reproductive Health
Background:
- The Sustainable Development Goals necessitate accurate maternal mortality measurement.
- Countries with limited statistical systems face challenges in data collection.
- National population censuses have been explored as a data source since the 1990s.
Purpose of the Study:
- To evaluate the utility of census data for monitoring maternal mortality.
- To assess maternal mortality data from the 2010 round of censuses in multiple countries.
Main Methods:
- Evaluation of birth, death, and pregnancy-related death data from 10 countries' censuses.
- Application of standard methods and adjustments to reported census figures.
Main Results:
- Censuses generally underreported births and deaths, with pregnancy-related death proportions appearing plausible.
- Adjusted estimates of the pregnancy-related mortality ratio (PRMR) were often higher than those from other sources.
- Census data provides imperfect but valuable insights into maternal mortality.
Conclusions:
- Census data requires careful assessment and adjustment for reliable maternal mortality estimation.
- Despite limitations, census data can be a useful tool in countries lacking civil registration.
- Estimates derived from census data often carry significant uncertainty.
Related Concept Videos
01:24Kaplan-Meier Approach
518
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,...
518
01:52Regression Toward the Mean
6.8K
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...
6.8K
01:22Applications of Life Tables
293
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...
293
01:25Statistical Methods for Analyzing Epidemiological Data
848
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:
848
01:09Censoring Survival Data
481
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
481
01:21Cancer Survival Analysis
610
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
610