Enhancing population-wide administrative data to better understand mortality risk in underserved groups

BackgroundUnderserved groups (USGs) face significant health inequalities, but studying these populations is often limited by small sample sizes and low participation in voluntary studies. Population-wide Census data provides an important opportunity to address some of these challenges. This study examined mortality outcomes among multiple USGs in Northern Ireland using Census-linked mortality data.MethodsWe conducted a population-wide cohort study using the Northern Ireland Mortality Study 2021, linking Census data to death records for all individuals aged ≥16 years (n = 1,463,459) from 21 March 2021 to 31 December 2023. USGs included ethnic minorities, migrants, those with limited English, LGB+ (lesbian, gay, bisexual, and other sexual minorities) individuals, religious minorities, and Irish Travellers. Outcomes included all-cause mortality, avoidable mortality, and deaths of despair (comprising suicide, alcohol-related deaths, and drug-related deaths), with suicide also examined as a separate outcome. Cox proportional hazards models were used to estimate associations with sequential adjustment for sociodemographic and health-related factors.ResultsOf 1,463,459 cohort members, 414,540 (28.3%) belonged to at least one USG. During follow-up, 36,525 (2.5%) individuals died. In unadjusted models, ethnic minorities, migrants, those with limited English, and religious minorities had lower all-cause mortality risk, whilst LGB + individuals had elevated risk (HR 1.24, 95% CI 1.20-1.29). After full adjustment, estimates remained below 1.00 for all groups except LGB + individuals. For LGB + individuals, all-cause mortality was attenuated towards the null, but deaths of despair remained elevated (HR 1.21, 95% CI 1.02-1.43).ConclusionsMost USGs had lower mortality risks than their reference populations. However, LGB + individuals had elevated risk of deaths of despair. These findings demonstrate the value of population-wide data for understanding heterogeneity in mortality across USGs.