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Related Concept Videos

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...
Data Collection by Observations01:08

Data Collection by Observations

Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Observational Studies01:11

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Statistical Methods for Analyzing Epidemiological Data01:25

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:

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Related Experiment Video

Updated: Jul 15, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

A cohort mortality study of construction workers

J Sun1, E Shibata, N Hisanaga

  • 1Department of Hygiene, Nagoya University School of Medicine, Japan.

American Journal of Industrial Medicine
|July 1, 1997
PubMed
Summary

Construction workers in Japan experienced higher mortality rates from accidents and asbestos-related lung cancers. This study highlights significant risks associated with construction work, particularly concerning asbestos exposure.

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

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Last Updated: Jul 15, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Area of Science:

  • Occupational Health
  • Epidemiology
  • Environmental Health

Background:

  • Construction industry workers face unique occupational hazards.
  • Asbestos exposure is a known risk factor for various cancers.
  • Previous studies suggest a link between construction work and increased mortality.

Purpose of the Study:

  • To investigate mortality patterns among construction workers.
  • To assess the association between asbestos exposure levels and specific causes of death.
  • To evaluate the risk of cancer and accidental deaths in the construction industry.

Main Methods:

  • A mortality study was conducted on 17,344 members of the Construction Workers' Health Insurance Society in Mie Prefecture, Japan (1973-1993).
  • Age-specific mortality rates for Mie Prefecture were used as a standard comparison.
  • Workers were categorized into three groups based on estimated asbestos exposure frequency from job classifications.

Main Results:

  • Significantly elevated standardized mortality ratios (SMR) and proportionate mortality ratios (PMR) were found for "accidents and adverse effects."
  • Elevated PMRs were observed for all cancers and "cancers of trachea, bronchus and lung."
  • Higher asbestos exposure groups showed increased PMRs for all cancers and lung cancers, while lower exposure groups had elevated PMRs for accidents.

Conclusions:

  • Construction work is associated with increased risks of asbestos-related cancers and accidental deaths.
  • Asbestos exposure frequency correlates with elevated cancer risks, particularly lung cancer.
  • The findings support the hypothesis linking construction industry employment to heightened mortality risks.