Problem: There remains uncertainty around cancer risk at lower levels of arsenic in drinking water. This study updates evidence from our previous review on the relationship between arsenic in drinking water and urinary bladder and kidney cancers (updated search January 2013 to February 2023). Method: Thirty-four studies were retained for review; six met criteria for inclusion in meta-analysis. Risk estimates for bladder and kidney cancer incidence and mortality were analyzed separately using Bayesian multilevel linear models. Results: For bladder cancer incidence, the estimated posterior mean relative risks (RRs) were 1.25 (0.92–1.73), 2.11 (1.18–4.22) and 3.01 (1.31–8.17) at arsenic concentrations of 10, 50 and 150 μg/L, respectively, with posterior probabilities of 92%, 99% and 100%, respectively, for the RRs to be >1. The corresponding RRs for kidney cancer were 1.37 (1.07–1.77), 1.95 (1.44–2.65) and 2.47 (1.74–3.52), with posterior probabilities of 100%. For bladder cancer, the posterior mean mortality ratios were 1.36 (0.35–6.39), 2.92 (1.24–7.82) and 4.88 (2.83–9.03) with posterior probabilities of 72%, 99% and 100%, respectively. Conclusions: The findings show increased bladder and kidney cancer risks at lower levels of arsenic in drinking water. Given that many people worldwide are exposed to lower levels of arsenic in drinking water, the public health impacts are substantial.

Globally, cancer is a leading cause of death and morbidity and its burden is increasing worldwide. It is established that medical approaches alone will not solve this cancer crisis. Moreover, while cancer treatment can be effective, it is costly and access to treatment and health care is vastly inequitable. However, almost 50% of cancers are caused by potentially avoidable risk factors and are thus preventable. Cancer prevention represents the most cost-effective, feasible and sustainable pathway towards global cancer control. While much is known about cancer risk factors, prevention programs often lack consideration of how place impacts cancer risk over time. Maximizing cancer prevention investment requires an understanding of the geographic context for why some people develop cancer while others do not. Data on how community and individual level risk factors interact is therefore required. The Nova Scotia Community Cancer Matrix (NS-Matrix) study was established in Nova Scotia (NS), a small province in Eastern Canada with a population of 1 million. The study integrates small-area profiles of cancer incidence with cancer risk factors and socioeconomic conditions, to inform locally relevant and equitable cancer prevention strategies. The NS-Matrix Study includes over 99,000 incident cancers diagnosed in NS between 2001 and 2017, georeferenced to small-area communities. In this analysis we used Bayesian inference to identify communities with high and low risk for lung and bladder cancer: two highly preventable cancers with rates in NS exceeding the Canadian average, and for which key risk factors are high. We report significant spatial heterogeneity in lung and bladder cancer risk. The identification of spatial disparities relating to a community's socioeconomic profile and other spatially varying factors, such as environmental exposures, can inform prevention. Adopting Bayesian spatial analysis methods and utilizing high quality cancer registry data provides a model to support geographically-focused cancer prevention efforts, tailored to local community needs.

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.