Related Experiment Video
Updated: Jan 14, 2026
10:00
Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
35.4K
Employment quality and mortality in Canada
Faraz V Shahidi1,2, Alessandra T Andreacchi3,2, Anne E Fuller4,5
1Institute for Work and Health, Toronto, Ontario, Canada fshahidi@iwh.on.ca.
Journal of Epidemiology and Community Health
|October 22, 2025
Summary
Employment quality significantly impacts mortality risk. Precarious jobs show the highest mortality rates, while standard and portfolio jobs have the lowest, highlighting the need for nuanced job quality assessment.
Area of Science:
- Occupational Health
- Epidemiology
- Sociology of Work
Background:
- Non-standard employment is linked to poorer health outcomes compared to standard employment.
- Previous research has not adequately differentiated between types of non-standard employment quality.
- This study addresses this gap by examining diverse employment quality typologies and mortality in Canada.
Purpose of the Study:
- To investigate the association between a detailed typology of employment quality and mortality.
- To identify specific employment arrangements linked to increased mortality risk.
- To explore sex/gender differences in these associations.
Main Methods:
- Utilized the 2006 Canadian Health and Environment Cohort (n=2,805,550) linked to death records (2006-2019).
- Classified employment into five types: standard, portfolio, marginal, intermittent, and precarious.
- Employed Poisson regression to estimate covariate-adjusted mortality risks by employment type and sex/gender.
Main Results:
- A dose-response relationship was observed between employment quality and mortality.
- Workers in precarious employment faced the highest mortality rates.
- Standard and portfolio employment were associated with the lowest mortality rates, with marginal and intermittent employment in between. Sex/gender differences were noted, with greater inequalities among men.
Conclusions:
- Findings challenge a simple binary view of 'standard' vs. 'precarious' jobs.
- A nuanced understanding of employment arrangements and their health impacts is crucial.
- Policies promoting high-quality jobs and protecting vulnerable workers can improve population health and longevity.
More Related Videos
10:13Tailoring In Vivo Cytotoxicity Assays to Study Immunodominance in Tumor-specific CD8+ T Cell Responses
Published on: May 6, 2019
9.5K
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
15.0K
Related Concept Videos
01:22Applications of Life Tables
323
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...
323
01:22Life Tables
495
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,...
495
01:24Kaplan-Meier Approach
566
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,...
566
01:20Actuarial Approach
286
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,...
286
01:18Survival Curves
646
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
646
01:20Comparing the Survival Analysis of Two or More Groups
551
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
551