Related Experiment Video
Updated: Jul 28, 2026
07:02
Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy
Published on: January 19, 2019
[Occupational mortality in the population employed at 1991 Census]
C Mamo1, A d'Errico, O Pasqualini
1Servizio regionale di Epidemiologia ASL 5, Regione Piemonte, Grugliasco (TO). carlo.mamo@epi.piemonte.it
La Medicina Del Lavoro
|May 6, 2005
Summary
Occupational mortality data, despite limitations, can reveal health disparities among jobs. This study used Italian census and mortality records to assess cause-specific mortality, highlighting risks for certain occupations over time.
Area of Science:
- Public Health
- Epidemiology
- Occupational Medicine
Context:
- Occupational surveillance systems using mortality data have limitations.
- Mortality from specific causes is a key indicator of occupational health differences.
- Evaluating the utility of Italian Central Statistics Institute (ISTAT) data for occupational mortality surveillance is crucial.
Purpose:
- To assess the potential of an occupational mortality surveillance system using linked census and mortality data from ISTAT.
- To evaluate cause-specific mortality risks across different occupations.
- To compare current findings with previous analyses from 1981 census data.
Summary:
- Linked 1991 Italian census and mortality records for 18-64 year olds were analyzed.
- Cause-specific mortality odds ratios were calculated using a cross-sectional model.
- Elevated risks for liver cirrhosis (caretakers, janitors, cleaning staff) and breast cancer (teachers) were noted.
Impact:
- Highlights socio-economic disparities in premature mortality within the employed population.
- Identifies potential occupational health trends over time.
- Provides a basis for refining occupational health surveillance strategies.
Related Concept Videos
01:22Life 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,...
01:20Actuarial 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,...
01:22Applications 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...
01:11Hazard Rate
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
01:12Hazard Ratio
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...
For example, in a clinical trial evaluating a...
01:09Truncation in Survival Analysis
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are observed.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are observed.