arXiv

Tracing the Genetic Footprints of the UK National Health Service

Nicolau Martin-Bassols, Pietro Biroli, Elisabetta De Cao
Feb 3, 2026·07:11··Original Paper
UK National Health Service (NHS)Infant Mortality ReductionSelective SurvivalPolygenic Indexes (PGIs)Socioeconomic DisparitiesPublic Healthcare Expansions

About This Paper

The establishment of the UK National Health Service (NHS) in July 1948 was one of the most consequential health policy interventions of the twentieth century, providing universal and free access to medical care and substantially expanding maternal and infant health services. In this paper, we estimate the causal effect of the NHS introduction on early-life mortality and we test whether survival is selective. We adopt a regression discontinuity design under local randomization, comparing individuals born just before and just after July 1948. Leveraging newly digitized weekly death records, we document a significant decline in stillbirths and infant mortality following the introduction of the NHS, the latter driven primarily by reductions in deaths from congenital conditions and diarrhea. We then use polygenic indexes (PGIs), fixed at conception, to track changes in population composition, showing that cohorts born at or after the NHS introduction exhibit higher PGIs associated with contextually-adverse traits (e.g., depression, COPD, and preterm birth) and lower PGIs associated with contextually-valued traits (e.g., educational attainment, self-rated health, and pregnancy length), with effect sizes as large as 7.5% of a standard deviation. These results based on the UK Biobank data are robust to family-based designs and replicate in the English Longitudinal Study of Ageing and the UK Household Longitudinal Study. Effects are strongest in socioeconomically disadvantaged areas and among males. This novel evidence on the existence and magnitude of selective survival highlights how large-scale public policies can leave a persistent imprint on population composition and generate long-term survival biases.