Small-area spatio-temporal analysis of cancer risk to support effective and equitable cancer prevention

Abstract

Cancer is rapidly increasing worldwide and urgent global action towards cancer control is required. Consistent with global trends, Canada is expected to experience a near doubling in new cases and cancer deaths between 2020-2040; population growth and ageing being the primary drivers. The projected increased cancer incidence and its associated costs is expected to further exacerbate socioeconomic inequities. Focused actions to prevent cancer, to detect it earlier when more treatable, and, to lower the risk of recurrence, must be prioritized. Almost half of all cancers are preventable, caused by risk factors that are potentially avoidable and modifiable. Integrating cancer prevention with care-based models is necessary and represents the most cost-effective and sustainable approach to control cancer. To be effective, prevention efforts must consider the cancers impacting local populations and understand how community and individual factors interact within the spatial and temporal contexts in which people live. This study is part of the Nova Scotia Community Cancer Matrix project which profiles the cancers impacting communities over time; measuring associations between cancer and socioeconomic status (SES); and determining how the joint spatial distribution of cancers can be used to address inequities, identify priority populations and strengthen prevention efforts. Using Bayesian inference to model spatio-temporal variations in 58,206 cases diagnosed in 301 communities between 2001-2017, across 10 preventable cancer types, we report significant disparities in cancer risk across communities based on sex and community SES. The work highlights the utility of small-area mapping to identify at-risk communities and understand how community-SES impacts risk. It also uncovers significant inequities rooted in the differential distribution of material and social capacity, operating beyond the control of individuals. The approach is implementable to other regions to inform and strengthen prevention efforts aiming at reducing the burden of cancer or that of other diseases.

Fig 1. Population density, Nova Scotia, Canada.

Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada [19].

Fig 2. Percent change in male and female cancer-specific posterior median relative risk (RR) in relation to time (A, B), MS (C, D) and SC (E, F).

Solid lines indicate statistically significant effects.

Fig 3. Posterior spatial random effects displaying median relative risk (RR) with overlay of exceedance probability (P_high≥ 0.8) for eight preventable cancers in males, Nova Scotia 2001-2017.

Insets A and B represent the densely populated areas of Halifax and Sydney, respectively. Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada. [19].

Fig 4. Posterior spatial random effects displaying median relative risk (RR) with overlay of exceedance probability (P_high≥ 0.8) for ten preventable cancers in females, Nova Scotia 2001-2017.

Insets A and B represent the densely populated areas of Halifax and Sydney, respectively. Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada. [19].

Fig 5. Posterior predictions displaying median relative risk (RR) with overlay of exceedance probability (P_high≥ 0.8) for eight preventable cancers in males, Nova Scotia 2014-2017.

Insets A and B represent densely populated areas of Halifax and Sydney, respectively. Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada [19].

Fig 6. Posterior predictions displaying median relative risk (RR) with overlay of exceedance probability (P_high≥ 0.8) for ten preventable cancers in females, Nova Scotia 2014-2017.

Insets A and B represent densely populated areas of Halifax and Sydney, respectively. Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada [19].

Fig 7. Percentage of communities (COMe) with significant increased cancer risk based on exceedance probabilities (P_high≥ 0.8) for the posterior predicted median relative risk (RR) estimated for each time period and cancer type, both sexes combined. Results are presented for all COMe (A), communities ranking in either the lowest (B) or highest (C) level of material security (MS) and those reporting both low levels of MS and social connectivity (SC), (D) or both high levels of MS and SC (E).

Fig 8. Sex-specific Composite Index of Cancer of spatial random effects (sCIC, A-B) and predictions (pCIC, C-D) based on 8 cancer types in males, and 10 in females. Negative values for sCIC (yellow shades) are associated with higher occurrence of bladder cancer and melanoma in males; and higher occurrence of bladder cancer in females. Positive values for sCIC (orange-red shades) are associated with higher occurrence of stomach, colorectal and pancreatic cancers in males; and higher occurrence of cervical, stomach and breast cancers in females. Negative values for pCIC (yellow shades) are associated with higher occurrence of melanoma in both males and females. Positive values for pCIC (orange-red shades) are associated with higher occurrence of lung and stomach in males; and higher occurrence of cervical and lung cancers in females. Insets (A) and (B) represent the densely populated areas of Halifax and Sydney, respectively. Base Map Source: Statistics Canada, Census Dissemination Areas Boundary File, 17 Nov 2021. Reproduced and distributed on an “as is” basis with the permission of Statistics Canada [19].

Fig 9. Scatterplot of the Composite Index of Cancer for posterior predictions (pCIC) and community socioeconomic status as measured with material security (A, B) or social connectivity (C, D), in males and females. Pearson partial correlations (pcor) and associated p-values are included to show the strength and significance of the associations.