Interdisciplinary community-based participatory health research across the industrial region of the Étang de Berre : The EPSEAL Fos Crau study

Jeanjean, Maxime; Lees, Johanna; Allen, Barbara L.; Cohen, Alison K.

doi:10.1016/j.respe.2021.04.141

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…We preferred the second option, which enables us to have a more accurate measurement of pollution in the population's living spaces (Map No 1), and this, all the more so since some IRISes are vast and their population sometimes gathered in a single area, as can be seen on map No 1. 3 International Classification of Diseases ICD-10 organised in 21 chapters, covering the full range of morbid conditions classified by organ or functional system: http://www.departement-information-medicale.com/wpcontent/uploads/2017/06/CIM10_2017_sts_20170009_0001_000.pdf T to t4…”

Section: Air Pollution Datamentioning

confidence: 99%

“…First came the REVELA study conducted by Santé Publique France between 2013 and 2016, focused on kidney and bladder cancers and acute myeloid leukaemia, that showed incidence rates for bladder cancers higher than those observed in mainland France [1]. Then, the FOS EPSEAL [2,3] study launched in 2015 and conducted in Fos-sur-Mer and Port-Saint-Louis-du-Rhône attracted considerable attention because health data were collected on a random sample of inhabitants (participatory study), [4]. Nevertheless, the study revealed that chronic diseases and acute symptoms were a health experience shared in both cities.…”

Section: Introductionmentioning

confidence: 99%

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Contribution of Bayesian Networks to Environmental Health Issues, Application to Etang de Berre

Pérez

Labaume²,

Mathiot³

et al. 2021

Preprint

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Background: The aim of this study is to examine in detail the potential links between proven pathologies in the population and the atmospheric pollution to which this population is exposed, in an industrial context (Etang de Berre) and an abundant cocktail of pollutants, in connection with the diversity of emitting sources within that space (petrochemical industry, steel industry, refining, energy production, cement works, road, sea and air transport).Methods: A total of 178 variables of various natures (health, environmental and socio-economic) on a fine territorial scale (infracommunal) have been mobilised and simultaneously integrated within a Bayesian model based on artificial intelligence. Various unsupervised and supervised algorithms, and also sensitivity analyses provide the means to discover the links between these variables and the inhabitants’ living space.Results: By mobilising a high number of variables, broken up on a fine territorial scale, and by resorting to an appropriate tool to report on existing links between these variables, we were able to bring to the fore a number of relations between exposure and proven pathologies. For example, between cadmium and diabetes in the over 65 year-olds, or between vanadium and respiratory diseases. Threshold effects have also been revealed, notably for SO 2 which appears from a very low exposure threshold (6µg/m 3 ), therefore far below standard, which is set at 50µg/m 3 . It is also the case with hydrofluoric acid (HF), the effect of which is already felt from the 0.0028 μg/m 3 threshold. Also, exposure to cadmium in its particle phase, for an exposure between 0.214 and 0.250 μg/m 3 , disrupts insulin metabolism in the over 65. Finally, as soon as Benzo[k]fluoranthene (particle phase) exceeds the 0.672 μg/m 3 threshold, it results in a higher number of hospital stays for respiratory diseases in the 15-65 age group. A vulnerability differentiated according to age groups also appeared. Comorbidities known in literature have been found (respiratory and heart diseases). Also found was the influence of socio-economy on some pathologies (single-parent families and those without qualification at 15). Finally, diffuse PCBs pollution has been observed in the study area.Conclusion: The study has brought forward differentiated health profiles between the various IRISes 1 constituting the Pays de Martigues territory, and this should lead to the deployment of health services better suited to the needs of the population from a prevention perspective, and even to promote consultations with some specialists. For example, with a cardiologist, in those IRISes where the number of unqualified 15 year-olds is significant, since a relation has been found at that level, a relation most probably due to more difficult living and/or working conditions for these people. Likewise, prevention and social support measures should be taken to the benefit of single-parent families. At the same time, companies should go ahead with the desulfurization process of their installations, and even reduce their emissions concerning some noxious pollutants.Trial registration: Decision DE-2017-413 authorising the Métropole d’Aix Marseille Provence to carry out the processing of personal health data for a retrospective and local environmental health study titled “Air-Health study in the Pays de Martigues territory.” (Authorisation application No. 917120)

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Section: Air Pollution Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Contribution of Bayesian Networks to Environmental Health Issues, Application to Etang de Berre

Pérez

Labaume²,

Mathiot³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…But, while environmental health focuses mainly on environmental factors that may affect health (e.g., air pollution causing respiratory diseases), the notion of vulnerability also focuses on people who would suffer from the threats or tangible effects of port development as a potential or real effect which would therefore affect public health. This distinction is important to understanding how, today, the health question in a port context cannot be separated from the environmental question and must be considered in an encompassing manner (Jeanjean et al, 2021) When it comes to health and ports, studies were conducted at the global scale dealing with ship emissions and mortality (Corbett et al, 2007). The literature includes several health impact studies of industrial activities but with no specific mention of ports (Martuzzi et al, 2014;Mudu et al, 2014;Domingo et al, 2020;Marquès et al, 2020).…”

Section: Introductionmentioning

confidence: 99%