Space-time clusters of breast cancer using residential histories: A Danish case–control study

Abstract

BackgroundA large proportion of breast cancer cases are thought related to environmental factors. Identification of specific geographical areas with high risk (clusters) may give clues to potential environmental risk factors. The aim of this study was to investigate whether clusters of breast cancer existed in space and time in Denmark, using 33 years of residential histories.MethodsWe conducted a population-based case–control study of 3138 female cases from the Danish Cancer Registry, diagnosed with breast cancer in 2003 and two independent control groups of 3138 women each, randomly selected from the Civil Registration System. Residential addresses of cases and controls from 1971 to 2003 were collected from the Civil Registration System and geo-coded. Q-statistics were used to identify space-time clusters of breast cancer. All analyses were carried out with both control groups, and for 66% of the study population we also conducted analyses adjusted for individual reproductive factors and area-level socioeconomic indicators.ResultsIn the crude analyses a cluster in the northern suburbs of Copenhagen was consistently found throughout the study period (1971–2003) with both control groups. When analyses were adjusted for individual reproductive factors and area-level socioeconomic indicators, the cluster area became smaller and less evident.ConclusionsThe breast cancer cluster area that persisted after adjustment might be explained by factors that were not accounted for such as alcohol consumption and use of hormone replacement therapy. However, we cannot exclude environmental pollutants as a contributing cause, but no pollutants specific to this area seem obvious.

Disease cluster detection methods: recent developments and public health implications

“…A good example is the method of Q-statistics, developed by Jacquez and others (Jacquez et al 2006), that searches for clusters of disease cases compared to controls in space and time based on residential history data. Recent studies have used Q-statistics in identifying space-time clusters of breast cancer in Denmark (Nordsberg et al 2014), for example. These trajectory-based methods offer great possibilities for health research, but their application requires detailed data on people's migration trajectories that is not widely available in countries like the United States.…”

A Survey of Visual Analytics for Public Health

“…As an example, Nordsborg et al . [NME*14] provide a visual analysis of breast cancer data from the Danish cancer registry. In a similar way, Nordsborg et al .…”

Ambient UVR and Environmental Arsenic Exposure in Relation to Cutaneous Melanoma in Iowa

“…Residential histories have been used for geospatial modeling to estimate arsenic water source histories [23], arsenic concentrations in private well water based on the nearest neighbor [24], and satellite imagery as a proxy for farmland [25]. They have also been used to examine space time clusters of cancer [26][27][28][29]. Several CM studies have shown an association with early migration (childhood) to sunny places [30][31][32][33], but findings among studies using lifetime measures of UVR have been inconsistent due to varying exposure assessment methods for sun exposure or UVR [20,[34][35][36][37][38][39][40].…”