Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015.

Konstantinoudis, Garyfallos; Schuhmacher, Dominic; Ammann, Roland A.; Diesch, Tamara; Kuehni, Claudia E.; Spycher, Ben D. (2020). Bayesian spatial modelling of childhood cancer incidence in Switzerland using exact point data: a nationwide study during 1985-2015. International journal of health geographics, 19(1), p. 15. BioMed Central 10.1186/s12942-020-00211-7

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BACKGROUND

The aetiology of most childhood cancers is largely unknown. Spatially varying environmental factors such as traffic-related air pollution, background radiation and agricultural pesticides might contribute to the development of childhood cancer. This study is the first investigation of the spatial disease mapping of childhood cancers using exact geocodes of place of residence.

METHODS

We included 5947 children diagnosed with cancer in Switzerland during 1985-2015 at 0-15 years of age from the Swiss Childhood Cancer Registry. We modelled cancer risk using log-Gaussian Cox processes and indirect standardisation to adjust for age and year of diagnosis. We examined whether the spatial variation of risk can be explained by modelled ambient air concentration of NO2, modelled exposure to background ionising radiation, area-based socio-economic position (SEP), linguistic region, duration in years of general cancer registration in the canton or degree of urbanisation.

RESULTS

For all childhood cancers combined, the posterior median relative risk (RR), compared to the national level, varied by location from 0.83 to 1.13 (min to max). Corresponding ranges were 0.96 to 1.09 for leukaemia, 0.90 to 1.13 for lymphoma, and 0.82 to 1.23 for central nervous system (CNS) tumours. The covariates considered explained 72% of the observed spatial variation for all cancers, 81% for leukaemia, 82% for lymphoma and 64% for CNS tumours. There was weak evidence of an association of CNS tumour incidence with modelled exposure to background ionising radiation (RR per SD difference 1.17; 0.98-1.40) and with SEP (1.6; 1.00-1.13).

CONCLUSION

Of the investigated diagnostic groups, childhood CNS tumours showed the largest spatial variation. The selected covariates only partially explained the observed variation of CNS tumours suggesting that other environmental factors also play a role.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)
04 Faculty of Medicine > Department of Gynaecology, Paediatrics and Endocrinology (DFKE) > Clinic of Paediatric Medicine

UniBE Contributor:

Konstantinoudis, Garyfallos; Ammann, Roland; Kühni, Claudia and Spycher, Ben

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

1476-072X

Publisher:

BioMed Central

Funders:

[4] Swiss National Science Foundation ; [52] Cancer Research Switzerland

Language:

English

Submitter:

Andrea Flükiger-Flückiger

Date Deposited:

23 Apr 2020 11:19

Last Modified:

11 Mar 2021 23:40

Publisher DOI:

10.1186/s12942-020-00211-7

PubMed ID:

32303231

Uncontrolled Keywords:

Bayesian spatial modelling Cancer clusters Central nervous system cancer Childhood cancer Point processes

BORIS DOI:

10.7892/boris.143472

URI:

https://boris.unibe.ch/id/eprint/143472

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