Related Experiment Video
Updated: Oct 26, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Income-related differences in survival across disease categories in Sweden: a retrospective population-based register
Vincent Mougin1,2, Authia Gray1,2, Mohsen Naghavi2
1Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
Background:
Lower income is consistently associated with poorer survival after disease diagnosis, even in countries with universal healthcare such as Sweden. While income-related survival differences have been documented for specific conditions, comparative evidence across a range of disease categories with long-term follow-up is lacking. We quantify income-related differences in survival across 100 disease categories focussing on leading non-communicable diseases (NCDs).
Methods:
All individuals aged 16-95 years registered in Sweden between 2001 and 2023 were followed from first diagnosis until death or the end of 2023. By disease category cohort, individuals were matched to five general population controls (no prior diagnosis of that category) on birth year, sex, and income quartile. Flexible parametric models were used to estimate standardised survival curves for diagnosed individuals and their matched controls.
Findings:
For all 100 disease categories, estimated 10-year survival was lower for the lowest income quartile (Q1) than higher quartiles. For 37 conditions, the Q1 vs Q4 10-year survival gap exceeded 10 percentage points; the largest gaps were for other pharynx cancer (10-year survival 34.2% [95% CI 32.5-35.7] in Q1 vs 58.2% [56.3-60.1] in Q4), larynx cancer, mouth cancer, COPD, and endocarditis. Income-related survival disparities accounted for 6.2 million (95% CI 5.9-6.6 million) person-years of survival loss within 10 years of diagnosis across all cohorts compared to a high-income survival counterfactual, with cardiovascular diseases accounting for the largest share for Q1 (1.3 million). Survival loss after diagnosis relative to undiagnosed controls was significantly greater for Q1 compared to Q4 for 73 of 100 conditions.
Interpretation:
Substantial income-related disparities in survival persist in Sweden across all the most prevalent NCDs. Policies addressing income inequality alongside targeted disease-specific interventions are likely required to reduce income disparities in survival.
Funding:
Swedish Research Council for Health, Working Life and Welfare.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Cancer Survival Analysis
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Assumptions of Survival Analysis
Life Tables