Marker or mechanism? Medical imaging utilisation and population life expectancy in 38 OECD countries, 2000 to 2024 year.

Background. Medical imaging is central to modern diagnosis and treatment, yet its contribution to population level survival has rarely been quantified, and the few existing estimates have been interpreted as evidence that imaging directly extends life. Whether national imaging utilisation reflects a distinct clinical mechanism or a broader process of health system development has not been formally tested. Methods. Longitudinal ecological panel study of 38 OECD countries, 2000 to 2024 (950 possible country years). CT and MRI availability and utilisation were linked to life expectancy at birth, treatable and preventable mortality, and seven cause specific mortality outcomes. Two-way fixed-effects models with country and year fixed effects and country clustered standard errors were adjusted sequentially for log GDP per capita, log health expenditure per capita, population aged [≥]65 years, physician density and smoking prevalence. Three falsification families were specified: lead-exposure (placebo) models regressing current life expectancy on future imaging utilisation; negative control exposures with no diagnostic-imaging pathway to survival; and wild cluster bootstrap inference. Results. In the principal adjusted model, CT utilisation at a three year lag was associated with higher life expectancy ({beta} = 0.85 years per 100 additional examinations per 1,000 inhabitants, 95% CI 0.16 to 1.54; cluster robust p = 0.015; bootstrap p = 0.034; n = 339, 29 countries). Scanner availability showed weaker, generally non-significant associations. All three falsification analyses failed to support a modality-specific effect. Future CT utilisation predicted current life expectancy as strongly as past utilisation (three year lead {beta} = 0.86, 95% CI 0.15 to 1.57, p = 0.017), consistent with high within-country autocorrelation of the exposure (r = 0.64 at three years). Radiotherapy equipment density, a therapeutic rather than diagnostic technology, showed an equal and more precise association ({beta} = 0.85 per 10 units per million, 95% CI 0.32 to 1.38, p = 0.0017), as did PET scanner density and health expenditure, whereas physician density showed none. Associations were stronger for preventable ({beta} = -43.3 per 100,000, p = 0.0002) than treatable mortality ({beta} = -13.5, p = 0.19), and all were attenuated to the null under country specific linear trends. Conclusions. National CT utilisation is a robust ecological correlate of life expectancy but does not behave as a causal determinant under falsification. It is best understood as a marker of health system capital development. Claims that imaging adds years of life are not supportable on ecological evidence of this kind.