ArticleEuropean journal of epidemiology2016
Temporal association between childhood leukaemia and population growth in Swiss municipalities.
Article in European journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors at 2 institutions in 1 country.
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Abstract
The population mixing hypothesis proposes that childhood leukaemia (CL) might be a rare complication of a yet unidentified subclinical infection. Large population influxes into previously isolated rural areas may foster localised epidemics of the postulated infection causing a subsequent increase of CL. While marked population growth after a period of stability was central to the formulation of the hypothesis and to the early studies on population mixing, there is a lack of objective criteria to define such growth patterns. We aimed to determine whether periods of marked population growth coincided with increases in the risk of CL in Swiss municipalities. We identified incident cases of CL aged 0-15 years for the period 1985-2010 from the Swiss Childhood Cancer Registry. Annual data on population counts in Swiss municipalities were obtained for 1980-2010. As exposures, we defined (1) cumulative population growth during a 5-year moving time window centred on each year (1985-2010) and (2) periods of 'take-off growth' identified by segmented linear regression. We compared CL incidence across exposure categories using Poisson regression and tested for effect modification by degree of urbanisation. Our study included 1500 incident cases and 2561 municipalities. The incident rate ratio (IRR) comparing the highest to the lowest quintile of 5-year population growth was 1.18 (95 % CI 0.96, 1.46) in all municipalities and 1.33 (95 % CI 0.93, 1.92) in rural municipalities (p value interaction 0.36). In municipalities with take-off growth, the IRR comparing the take-off period (>6 % annual population growth) with the initial period of low or negative growth (<2 %) was 2.07 (95 % CI 0.95, 4.51) overall and 2.99 (1.11, 8.05) in rural areas (p interaction 0.52). Our study provides further support for the population mixing hypothesis and underlines the need to distinguish take-off growth from other growth patterns in future research.
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