Small-area spatio-temporal analyses of bladder and kidney cancer risk in Nova Scotia, Canada

BMC Public Health

Research Article

Nathalie Saint-Jacques¹  Louise Parker²  Jamie Stafford³  Jonathan S. W. Lee⁴  Patrick Brown⁴  Trevor J. B. Dummer⁵ 

[1] Cancer Care Nova Scotia, Surveillance and Epidemiology Unit, Room 560 Bethune Building, 1276 South Street, B3H 2Y9, Halifax, NS, Canada;Interdisciplinary PhD program, Dalhousie University, PO Box 15000, 6299 South Street, Room 314, B3H 4R2, Halifax, NS, Canada;Department of Pediatrics and Population Cancer Research Program, Dalhousie University, PO Box 15000, 1494 Carlton Street, B3H 4R2, Halifax, NS, Canada;Department of Statistical Sciences, University of Toronto, 100 St. George St., M5S 3G3, Toronto, ON, Canada;Department of Statistical Sciences, University of Toronto, 100 St. George St., M5S 3G3, Toronto, ON, Canada;Cancer Care Ontario, 620 University Ave, M5G 2 L7, Toronto, ON, Canada;The University of British Columbia, School of Population and Public Health, 2206 East Mall, V6T 1Z3, Vancouver, BC, Canada;

关键词: Small-area disease mapping;    BYM model;    Local-EM algorithm;    Bladder and kidney cancer risk;    Geostatistical analysis;    Spatial autoregressive analyses;   

DOI  :  10.1186/s12889-016-2767-9

 received in 2015-05-29, accepted in 2016-01-22,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundBladder and kidney cancers are the ninth and twelfth most common type of cancer worldwide, respectively. Internationally, rates vary ten-fold, with several countries showing rising incidence. This study describes the spatial and spatio-temporal variations in the incidence risk of these diseases for Nova Scotia, a province located in Atlantic Canada, where rates for bladder and kidney cancer exceed those of the national average by about 25 % and 35 %, respectively.MethodsCancer incidence in the 311 Communities of Nova-Scotia was analyzed with a spatial autoregressive model for the case counts of bladder and kidney cancers (3,232 and 2,143 total cases, respectively), accounting for each Community's population and including variables known to influence risk. A spatially-continuous analysis, using a geostatistical Local Expectation-Maximization smoothing algorithm, modeled finer-scale spatial variation in risk for south-western Nova Scotia (1,810 bladder and 957 kidney cases) and Cape Breton (1,101 bladder, 703 kidney).ResultsEvidence of spatial variations in the risk of bladder and kidney cancer was demonstrated using both aggregated Community-level mapping and continuous-grid based localized mapping; and these were generally stable over time. The Community-level analysis suggested that much of this heterogeneity was not accounted for by known explanatory variables. There appears to be a north-east to south-west increasing gradient with a number of south-western Communities have risk of bladder or kidney cancer more than 10 % above the provincial average. Kidney cancer risk was also elevated in various northeastern communities. Over a 12 year period this exceedance translated in an excess of 200 cases. Patterns of variations in risk obtained from the spatially continuous smoothing analysis generally mirrored those from the Community-level autoregressive model, although these more localized risk estimates resulted in a larger spatial extent for which risk is likely to be elevated.ConclusionsModelling the spatio-temporal distribution of disease risk enabled the quantification of risk relative to expected background levels and the identification of high risk areas. It also permitted the determination of the relative stability of the observed patterns over time and in this study, pointed to excess risk potentially driven by exposure to risk factors that act in a sustained manner over time.

【 授权许可】

CC BY   
© Saint-Jacques et al. 2016