The incidence of skin melanoma in Gran Canaria (Canary Islands, Spain) is lower than expected in Southern Europe despite high-risk environmental conditions: an island-wide cross-sectional study

Grau‐Pérez, Mercè; Carretero, G.; Almeida, Pablo; Castro-González, Elena; de-la-Rosa-del-Rey, María del Pilar; González-Martín, Jesús María; Borrego, Leopoldo

doi:10.1007/s10552-021-01403-7

Cited by 6 publications

(10 citation statements)

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“…Finally, this study relies on the assumption that all incident skin melanoma cases diagnosed in Gran Canaria residents in the study period were considered. Because of how the dataset was elaborated, we have certainty that all cases diagnosed in the public healthcare system (CIHS) were included, but a few cases diagnosed in private practices might have been missed [ 13 ]. The CIHS covers about 87% of all healthcare in the region, and cases diagnosed in private clinics in our dataset represented 15.8%, that is, more than expected [ 13 , 15 ].…”

Section: Discussionmentioning

confidence: 99%

“…Because of how the dataset was elaborated, we have certainty that all cases diagnosed in the public healthcare system (CIHS) were included, but a few cases diagnosed in private practices might have been missed [ 13 ]. The CIHS covers about 87% of all healthcare in the region, and cases diagnosed in private clinics in our dataset represented 15.8%, that is, more than expected [ 13 , 15 ]. Therefore, the plausible number of missing cases is unlikely to have meaningfully biased the results.…”

Section: Discussionmentioning

confidence: 99%

“…The Gran Canaria skin melanoma dataset used in this study has been previously described in detail [ 13 ]. It includes demographic, clinical, and histological information of all invasive skin melanoma cases evaluated at the CIHS among GC residents, diagnosed between January 2007 and December 2018.…”

Section: Methodsmentioning

confidence: 99%

“…For the selection of covariates, based on previous evidence we decided a priori that an adjustment for age, sex, and SES needed to be included in the final model, apart from the effect of environmental variables that we aimed to test [ 3 , 13 ]. Age was accounted for by modeling age-adjusted SIR, and sex by adjusting for percent of females per CT. For the other predictors, we explored the distribution of each covariate and fitted univariable models using simple Poisson regression without accounting for random effects.…”

Section: Methodsmentioning

confidence: 99%

“…The Canary Islands are a Spanish archipelago located in the Atlantic Ocean off the coast of North-western Africa, with a subtropical climate. The population in the islands is exposed to a high environmental risk for the development of skin cancers [ 12 ], yet unexpectedly the incidence of skin melanoma in the region is among the lowest in Spain and below the estimates provided by the World Health Organization for Southern Europe [ 1 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the effect of environmental and socio-economic factors on skin melanoma incidence: an island-wide spatial study in Gran Canaria (Spain), 2007–2018

Grau‐Pérez

Borrego

Carretero

et al. 2022

Cancer Causes Control

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Introduction Skin melanoma incidence has risen in the last decades becoming a major public health problem in many regions of the world. Geographic variation of rates is not well understood. Purpose To assess the spatial distribution of skin melanoma in Gran Canaria Island (Canary Islands, Spain) and to evaluate the role of environmental, socio-economic, and demographic factors in this distribution. Methods We performed a small-area study with disease mapping at the census-tract level (CT) in Gran Canaria between 2007 and 2018. After testing for spatial autocorrelation, we integrated individual-level health data with census-based demographic and socio-economic indicators, and satellite-based environmental data. Finally, we assessed the role of demographic, socio-economic and environmental factors on skin melanoma incidence using a Bayesian analytical framework, with options for non-spatial and spatial random effects. Results 1058 patients were diagnosed with invasive skin melanoma in the study period and geolocated to a CT (number of CT in Gran Canaria = 565). We found evidence of global spatial autocorrelation in skin melanoma incidence (Moran’s I = 0.09, pseudo p-value = 0.001). A few hotspots were detected, fundamentally in urban northern tracts. A radial pattern of high values was also observed in selected ravines with historical isolation. Multivariable conditional autoregressive models identified urbanicity, percent of females, and a high socio-economic status as risk factors for disease. Solar radiation did not show a significant role. Conclusion Urbanicity and a high socio-economic status were identified as the main risk factors for skin melanoma. These associations might reflect differential melanoma susceptibilities or be explained by health inequalities in detection. This study also uncovered high-risk areas in particular ravines. Future targeted research in these regions might help better understand the role of genetic and toxic factors in melanoma pathogenesis.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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