Tracing the Genetic Footprints of the UK National Health Service

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.

💡 Research Summary

This paper investigates whether the introduction of the United Kingdom’s National Health Service (NHS) in July 1948 not only reduced early‑life mortality but also altered the genetic composition of surviving cohorts through selective survival. Using a regression discontinuity design (RDD) that treats month of birth as the running variable, the authors compare individuals born just before and just after the NHS launch, assuming local randomisation around the cutoff.

First, the study exploits newly digitised weekly death registers for England and Wales. The authors document a sharp decline in infant mortality rates (IMR) of 17 % (approximately 6.5 fewer deaths per 1,000 live births) and an 8 % reduction in stillbirths immediately after the NHS began. Cause‑specific analysis shows that the decline is driven primarily by reductions in deaths from diarrhoea (34 % drop among children under two) and congenital conditions, with smaller but meaningful decreases in premature birth, birth injuries, and haemolytic disorders. No substantial change in maternal mortality is observed.

Second, the paper links these demographic outcomes to genetic data from three large, nationally representative cohorts: the UK Biobank (UKB), the English Longitudinal Study of Ageing (ELSA), and Understanding Society (USoC). For each individual, polygenic indexes (PGIs) for a range of traits—derived from genome‑wide association studies—serve as fixed‑at‑conception measures of genetic propensity. Comparing pre‑ and post‑NHS birth cohorts, the authors find that post‑NHS cohorts have higher average PGIs for “contextually adverse” traits such as depression, chronic obstructive pulmonary disease (COPD), and preterm birth, and lower average PGIs for “contextually favourable” traits such as educational attainment, self‑rated health, and pregnancy length. Effect sizes reach up to 0.075 standard deviations, a magnitude comparable to the impact of major socioeconomic interventions.

Robustness checks include (i) family‑fixed‑effects models using sibling pairs in UKB, which confirm that the observed PGI shifts persist when controlling for shared parental background; (ii) exclusion of selective fertility mechanisms by showing no significant changes in crude birth rates, birth order, or sibling counts around the cutoff; (iii) heterogeneity analyses that reveal larger genetic shifts in regions with higher pre‑NHS infant mortality (i.e., more socio‑economically disadvantaged areas) and among male infants, consistent with the “male frailty” hypothesis.

The authors argue that these findings constitute direct evidence of selective survival: the NHS expanded access to medical care, allowing infants who would otherwise have died—particularly those with genetic predispositions to poorer health outcomes—to survive, thereby altering the genetic distribution of the population. This selection bias has important implications for any long‑term evaluation of early‑life policies, because subsequent outcomes measured only among survivors may be systematically distorted.

Methodologically, the paper combines high‑resolution historical mortality data with modern genomic datasets, applies rigorous RDD identification strategies, and validates results across multiple independent samples. Limitations include the context‑dependence of PGI interpretation (PGIs do not measure absolute “fitness”) and the inability to trace long‑term adult outcomes directly within the same framework. Nonetheless, the study provides the first causal estimate of a major health policy’s impact on the genetic makeup of a population, opening avenues for future research on policy‑induced genetic selection in other settings and over longer horizons.