The Hotel Study-Clinical and Health Service Effectiveness in a Cohort of Homeless or Marginally Housed Persons.

OBJECTIVE: The Hotel Study was initiated in Vancouver's Downtown East Side (DTES) neighborhood to investigate multimorbidity in homeless or marginally housed people. We evaluated the clinical effectiveness of existing, illness-specific treatment strategies and assessed the effectiveness of health care delivery for multimorbid illnesses. METHOD: For context, we mapped the housing locations of patients presenting for 552,062 visits to the catchment hospital emergency department (2005-2013). Aggregate data on 22,519 apprehensions of mentally ill people were provided by the Vancouver Police Department (2009-2015). The primary strategy was a longitudinal cohort study of 375 people living in the DTES (2008-2015). We analysed mortality and evaluated the clinical and health service delivery effectiveness for infection with human immunodeficiency virus or hepatitis C virus, opioid dependence, and psychosis. RESULTS: Mapping confirmed the association between poverty and greater number of emergency visits related to substance use and mental illness. The annual change in police apprehensions did not differ between the DTES and other policing districts. During 1581 person-years of cohort observation, the standardized mortality ratio was 8.43 (95% confidence interval, 6.19 to 11.50). Physician visits were common (84.3% of participants over 6 months). Clinical treatment effectiveness was highest for HIV/AIDS, intermediate for opioid dependence, and lowest for psychosis. Health service delivery mechanisms provided examples of poor access, poor treatment adherence, and little effect on multimorbid illnesses. CONCLUSIONS: Clinical effectiveness was variable, and illness-specific service delivery appeared to have little effect on multimorbidity. New models of care may need to be implemented.

Geographic variation in radon and associated lung cancer risk in Canada.

OBJECTIVE: Radon is an important risk factor for lung cancer. Here we use maps of the geographic variation in radon to estimate the lung cancer risk associated with living in high radon areas of Canada. METHODS: Geographic variation in radon was estimated using two mapping methods. The first used a Health Canada survey of 14,000 residential radon measurements aggregated to health regions, and the second, radon risk areas previously estimated from geology, sediment geochemistry and aerial gamma-ray spectrometry. Lung cancer risk associated with living in these radon areas was examined using a population-based case-control study of 2,390 lung cancer cases and 3,507 controls collected from 1994-1997 in eight Canadian provinces. Residential histories over a 20-year period were used in combination with the two mapping methods to estimate ecological radon exposures. Hierarchical logistic regression analyses were used to estimate odds ratios for lung cancer incidence, after adjusting for a comprehensive set of individual and geographic covariates. RESULTS: Across health regions in Canada, significant variation in average residential radon concentrations (range: 16-386 Bq/m3) and in high geological-based radon areas (range: 0-100%) is present. In multivariate models, a 50 Bq/m3 increase in average health region radon was associated with a 7% (95% CI: -6-21%) increase in the odds of lung cancer. For every 10 years that individuals lived in high radon geological areas, the odds of lung cancer increased by 11% (95% CI: 1-23%). CONCLUSIONS: These findings provide further evidence that radon is an important risk factor for lung cancer and that risks are unevenly distributed across Canada.

Risk-based indicators of Canadians' exposures to environmental carcinogens.

BACKGROUND: Tools for estimating population exposures to environmental carcinogens are required to support evidence-based policies to reduce chronic exposures and associated cancers. Our objective was to develop indicators of population exposure to selected environmental carcinogens that can be easily updated over time, and allow comparisons and prioritization between different carcinogens and exposure pathways. METHODS: We employed a risk assessment-based approach to produce screening-level estimates of lifetime excess cancer risk for selected substances listed as known carcinogens by the International Agency for Research on Cancer. Estimates of lifetime average daily intake were calculated using population characteristics combined with concentrations (circa 2006) in outdoor air, indoor air, dust, drinking water, and food and beverages from existing monitoring databases or comprehensive literature reviews. Intake estimates were then multiplied by cancer potency factors from Health Canada, the United States Environmental Protection Agency, and the California Office of Environmental Health Hazard Assessment to estimate lifetime excess cancer risks associated with each substance and exposure pathway. Lifetime excess cancer risks in excess of 1 per million people are identified as potential priorities for further attention. RESULTS: Based on data representing average conditions circa 2006, a total of 18 carcinogen-exposure pathways had potential lifetime excess cancer risks greater than 1 per million, based on varying data quality. Carcinogens with moderate to high data quality and lifetime excess cancer risk greater than 1 per million included benzene, 1,3-butadiene and radon in outdoor air; benzene and radon in indoor air; and arsenic and hexavalent chromium in drinking water. Important data gaps were identified for asbestos, hexavalent chromium and diesel exhaust in outdoor and indoor air, while little data were available to assess risk for substances in dust, food and beverages. CONCLUSIONS: The ability to track changes in potential population exposures to environmental carcinogens over time, as well as to compare between different substances and exposure pathways, is necessary to support comprehensive, evidence-based prevention policy. We used estimates of lifetime excess cancer risk as indicators that, although based on a number of simplifying assumptions, help to identify important data gaps and prioritize more detailed data collection and exposure assessment needs.