Ludivine Launay

Background: Previous studies have highlighted the relationship between socioeconomic inequalities and the general population’s risk of contracting or dying from COVID-19 during the 2020−2023 pandemic. In France, socioeconomic inequalities vary across metropolitan areas; few studies have investigated whether this variation explains the spatial disparities observed in COVID-19 incidence and testing rates during the pandemic. We examined the relationship between socioeconomic profiles and these two rates across all 22 metropolitan areas in France for eight of the country’s nine epidemic waves. Methods: For each metropolitan area, we used socioeconomic variables from census data to define socioeconomic profiles through principal component clustering. We then used spatialized generalised additive mixed models to analyze associations between these profiles and both testing and incidence rates, for each epidemic wave from July 2020 to March 2023. Finally, we performed meta-regressions to study the distribution of testing and incidence rate ratios among the various socioeconomically deprived and privileged profiles within each of the 22 metropolitan areas, according to COVID-19 vaccination rate. Results: Testing rates were lower in socioeconomically deprived metropolitan areas than in privileged ones, except during wave 4 (July-October-2021), when testing rates were more similar. Incidence rates were higher in deprived areas (waves 2–4, July-2020 to October-2021), but this pattern reversed between waves 6–9 (March-2022 to March-2023). Meta-regressions indicated that high vaccination coverage was associated with a narrower gap in testing between deprived and privileged areas. Moreover, for each metropolitan area, the higher the level of deprivation in a zone within the deprived profile, the greater the deprived-privileged gap in under-testing. Conclusions: The impact of socioeconomic inequalities on testing and incidence patterns during the COVID-19 pandemic in each metropolitan area in France was driven by the most deprived zones; this impact varied across epidemic waves. Higher vaccination rates and government health measures (lockdowns, mandatory health pass) may have reduced this variation.

Background: In cancer net survival analyses, if life tables (LT) are not stratified based on socio-demographic characteristics, then the social gradient in mortality in the general population is ignored. Consequently, the social gradient estimated on cancer-related excess mortality might be inaccurate. We aimed to evaluate whether the social gradient in cancer net survival observed in France could be attributable to inaccurate LT. Methods: Deprivation-specific LT were simulated, applying the social gradient in the background mortality due to external sources to the original French LT. Cancer registries’ data from a previous French study were re-analyzed using the simulated LT. Deprivation was assessed according to the European Deprivation Index (EDI). Net survival was estimated by the Pohar–Perme method and flexible excess mortality hazard models by using multidimensional penalized splines. Results: A reduction in net survival among patients living in the most-deprived areas was attenuated with simulated LT, but trends in the social gradient remained, except for prostate cancer, for which the social gradient reversed. Flexible modelling additionally showed a loss of effect of EDI upon the excess mortality hazard of esophagus, bladder and kidney cancers in men and bladder cancer in women using simulated LT. Conclusions: For most cancers the results were similar using simulated LT. However, inconsistent results, particularly for prostate cancer, highlight the need for deprivation-specific LT in order to produce accurate results.

Background: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. Methods: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM_2.5, PM₁₀ (particles < 2.5 µm and 2 (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. Results: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, −26.8, −7.3) and by 18.0 g (−26.6, −9.4) for each 5 µg/m³ increase in PM_2.5 and PM₁₀, respectively, and by 15.9 g (−27.6, −4.2) for each 10 µg/m³ increase in NO₂. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (−58.1, −38.0) for PM_2.5, 38.1 g (−46.7, −29.6) for PM₁₀ and 14.7 g (−25.3, −4.0) for NO₂. Effects of pollutants on TBW were larger in rural areas. Conclusions: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Spatial accessibility to health services is a key factor in terms of public health. Even though some tools are available, establishing accessibility criteria applicable from one geographic scale to another remains difficult. Therefore, we propose a method for creating a health accessibility index applicable on a large geographic scale, based on a methodology that overcomes the limitations of political-administrative divisions and which allows a multi-scalar approach to be implemented. The index highlights, on a national scale, areas of cumulative health disadvantages. This index of accessibility to health care combines accessibility and availability and can be adapted to many geographical scales. As accessibility can be understood in various dimensions, a score could be calculated for various fields such as education and culture. The index can help policymakers to identify under-endowed areas and find optimal locations. In terms of public health, it may be used to understand the mechanisms underlying geographic health disparities.

In aggregate studies, ecological indices are used to study the influence of socioeconomic status on health. Their main limitation is ecological bias. This study assesses the misclassification of individual socioeconomic status in seven ecological indices. Individual socioeconomic data for a random sample of 10,000 persons came from periodic health examinations conducted in 2006 in 11 French departments. Geographical data came from the 2007 census at the lowest geographical level available in France. The Receiver Operating Characteristics (ROC) curves, the areas under the curves (AUC) for each individual variable, and the distribution of deprived and non-deprived persons in quintiles of each aggregate score were analyzed. The aggregate indices studied are quite good “proxies” for individual deprivation (AUC close to 0.7), and they have similar performance. The indices are more efficient at measuring individual income than education or occupational category and are suitable for measuring of deprivation but not affluence. The study inventoried the aggregate indices available in France and evaluated their assessment of individual SES.

In the context of early detection of head and neck cancers (HNC), the aim of this study was to describe how people sought medical consultation during the year prior to diagnosis and the impact on the stage of the cancer. Patients over 20 years old with a diagnosis of HNC in 2010 were included from four French cancer registries. The medical data were matched with data regarding uptake of healthcare issued from French National Health Insurance General Regime. In 86.0 % of cases, patients had consulted a general practitioner (GP) and 21.1 % a dentist. Consulting a GP at least once during the year preceding diagnosis was unrelated to Charlson index, age, sex, département, quintile of deprivation of place of residence. Patients from the ‘quite privileged’, ‘quite underprivileged’ and ‘underprivileged’ quintiles consulted a dentist more frequently than those from the ‘very underprivileged’ quintile (p = 0.007). The stage was less advanced for patients who had consulted a GP (OR = 0.42 [0.18–0.99]) - with a dose–response effect. In view of the frequency of consultations, the existence of a significant association between consultations and a localised stage at diagnosis and the absence of a socio-economic association, early detection of HNC by GPs would seem to be the most appropriate way.

The struggle against social inequalities is a priority for many international organizations. The objective of the study was to quantify the cancer burden related to social deprivation by identifying the cancer sites linked to socioeconomic status and measuring the proportion of cases associated with social deprivation.