Related Experiment Video
Updated: Jan 10, 2026
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
15.0K
Mortality Risk Following a Household Suicide
Flávia Alves1,2, Elisângela da Silva Rodrigues1,3, Lidiane Toledo1
1Center of Data and Knowledge Integration for Health, Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil.
JAMA Network Open
|November 25, 2025
Summary
Household members exposed to suicide face significantly higher mortality risks, including a fourfold increase in suicide risk. These findings highlight the critical need for postvention strategies in suicide prevention efforts.
Area of Science:
- Public Health
- Epidemiology
- Sociology
Background:
- Mortality risks for household members after a suicide are not well understood, especially in low- and middle-income countries.
- Suicide has profound and lasting impacts on surviving family members.
Purpose of the Study:
- To estimate the risk of all-cause and cause-specific mortality among household members following a suicide.
- To identify individual and contextual factors associated with increased mortality risk after a household suicide.
Main Methods:
- Nationwide cohort study using data from the 100 Million Brazilian Cohort linked to the Mortality Information System (2001-2018).
- Multivariate, time-varying Cox regression analysis to calculate adjusted hazard ratios for mortality.
- Analysis of risk factors including index case characteristics, survivor demographics, household conditions, and time since suicide.
Main Results:
- Household members exposed to suicide had a 32% higher risk of all-cause mortality (aHR, 1.32).
- The risk of suicide among exposed individuals was over 4 times higher (aHR, 4.42), with 44% occurring within 2 years.
- Elevated risks were observed for other external and non-external causes of death. Mortality risk was highest when the index case was younger and female, and among male survivors aged 25-59.
Conclusions:
- Exposure to suicide within the household significantly increases all-cause and suicide-specific mortality among survivors.
- Findings emphasize the urgent need for targeted postvention strategies integrated into suicide prevention programs.
- Improved household conditions were associated with reduced mortality risks.
Related Concept Videos
01:20Actuarial Approach
280
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,...
280
01:22Life Tables
481
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,...
481
01:11Hazard Rate
383
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...
383
01:15Assumptions of Survival Analysis
388
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
388
01:12Relative Risk
1.8K
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
1.8K
01:24Kaplan-Meier Approach
541
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,...
541