What does an SMR of 100 mean?

An SMR of 100 means the observed mortality exactly equals the expected mortality based on the reference population. Values above 100 indicate more deaths than expected; values below 100 indicate fewer deaths than expected.

How are expected deaths calculated?

Expected deaths are calculated by applying age- (and sometimes sex-) specific mortality rates from a reference population (such as the national population) to the person-years of follow-up in the study group. The tool asks you to provide this pre-calculated figure.

What confidence interval method is used?

The tool uses the exact Poisson method (Byar's approximation for the 95% CI around the observed count), which is the standard approach when the observed count is small. The resulting CI bounds are then divided by expected deaths and multiplied by 100.

When is the SMR statistically significant?

The SMR is statistically significant at the 0.05 level when the 95% confidence interval does not include 100. If the lower CI bound is above 100, mortality is significantly elevated; if the upper bound is below 100, mortality is significantly lower than expected.

What are the limitations of the SMR?

The SMR assumes the reference population's mortality rates are applicable to the study group. It can be biased by the healthy worker effect in occupational studies, and it is sensitive to the choice of reference population. Direct standardization is preferred when comparing multiple groups to each other.

Standardized Mortality Ratio Calculator

Name: Standardized Mortality Ratio Calculator
Availability: InStock
Author: Nham Vu

Enter observed and expected deaths to calculate the SMR, its 95% confidence interval, and interpret whether mortality is higher, lower, or as expected.

SMR Inputs

Observed Deaths

Actual number of deaths recorded in the study group.

Expected Deaths

Deaths predicted from reference population rates.

Confidence Interval Level

SMR Interpretation

SMR < 100: Lower mortality than expected
SMR = 100: Mortality equals reference
SMR > 100: Higher mortality than expected

Enter observed and expected deaths, then click Calculate.

Results and 95% confidence interval will appear here.

Summary

Enter observed and expected deaths to calculate the SMR, its 95% confidence interval, and interpret whether mortality is higher, lower, or as expected.

How it works

Enter the number of observed deaths in the study population.
Enter the number of expected deaths based on a reference population.
The SMR is calculated as (Observed / Expected) × 100.
An SMR of 100 means mortality equals the reference population.
Values above 100 indicate excess mortality; below 100 indicates a deficit.
The 95% confidence interval uses the exact Poisson method for reliability.

Use cases

Assess excess mortality in an occupational cohort compared to the general population.
Evaluate mortality outcomes in a clinical trial or intervention study.
Compare mortality rates across different geographic regions or time periods.
Public health surveillance to detect elevated mortality in a community.
Determine whether a specific exposure is associated with increased mortality.
Report standardized outcomes in epidemiological research papers.

Frequently Asked Questions

Last updated: 2026-07-23 · Reviewed by Nham Vu