ArticlePopulation health metrics2026
Social inequalities in cause-specific premature mortality in rural and urban France: a pre-pandemic population attributable fraction analysis.
Article in Population health metrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSocial inequalities remain a major determinant of mortality across Europe. This study aimed first to quantify cause-specific premature mortality across urban and rural areas in mainland France during the pre-pandemic period, taking into account social inequalities, and second to assess the extent of these social inequalities using the population attributable fraction (PAF) approach.
methodsCause-specific deaths were identified from the French national mortality database and linked to municipality-level deprivation quintiles using French-European Deprivation Index (F-EDI). Residual life expectancy at age of death was defined according to the Global Burden of Disease (GBD) 2019 reference life table. Age-standardized years of life lost rates (ASYRs) were calculated by sex, deprivation quintile, and rural-urban setting. Social inequalities in mortality were assessed using absolute and relative gaps between the least and most deprived quintiles (Q1-Q5) and PAF, with Q1 as the reference.
resultsASYRs for Level 1 GBD causes increased consistently with area deprivation in both urban and rural mainland France. Non-communicable diseases accounted for most premature mortality (85-90% of total YLL) in both sexes, followed by injuries and communicable, maternal, neonatal, and nutritional causes. In urban areas, 18-31% of cause-specific premature mortality was attributed to social inequalities, compared with 8-20% in rural areas, with higher contributions among males. The absolute difference in ASYRs was slightly larger in rural than urban areas for both sexes (females: 2,854 vs. 2,463; males: 6,607 vs. 5,618). Relative inequalities were similar across both settings (females: 1.30; males: 1.39, comparing Q5 with Q1). By cause, breast cancer showed the largest inequality among females (11-12% higher in Q5), while lung cancer exhibited the highest disparity among males (75% higher in Q5 in urban areas and 43% in rural areas).
conclusionsSocial inequalities substantially contributed to cause-specific premature mortality in pre-pandemic mainland France. ASYRs increased with deprivation in both urban and rural areas and were consistently higher among males. The persistent deprivation gradient and higher PAFs highlight the particularly marked impact of social inequalities in urban areas. These findings provide a pre-pandemic baseline for evaluating post-COVID-19 trends in premature mortality and health disparities in France.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.