Health equity
Widening NSW cancer survival gaps
Open access · cc by · source: Europe PMC
Among 651,245 NSW cancer cases, people in more disadvantaged areas had higher cancer death risk, and disparities appeared to widen over time.
Study at a glance
- Design
- Cohort — Population-based NSW cancer registrations; SEIFA quintiles and remoteness
- N
- N=651245 · Mean follow-up 5.5 years
- Population
- People with cancer registered in New South Wales, Australia
- Outcome
- Cancer-death risk (SHR) by socio-economic disadvantage and remoteness
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Vs least disadvantaged areas, all other SEIFA quintiles had higher cancer-death risk, highest in most disadvantaged (SHR 1.15); authors conclude disparities appear to have increased and need active policy attention.
Methodology
Population-based survival analyses of NSW cancer registrations related SEIFA socio-economic quintiles and remoteness to cancer death, adjusting for stage and demographics.
Limitations
Cannot isolate a single causal pathway (screening, treatment access, comorbidity) driving the widening gap.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Multiple studies in this library examine health equity with empirical patient or population outcomes rather than opinion alone.
Evidence for the claim as stated.
Vs least disadvantaged areas, all other SEIFA quintiles had higher cancer-death risk, highest in most disadvantaged (SHR 1.15); authors conclude disparities appear to have increased and need active policy attention.
Evidence for the claim as stated.
Effect sizes and settings differ across health equity studies — digital vs clinic, trial vs observational — so results should not be pooled casually.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Effect sizes and settings differ across health equity studies — digital vs clinic, trial vs observational — so results should not be pooled casually.
Related papers in this topic
Same topic cluster — not a recommendation engine.