@article{7e76c104ade840788c62d73e14576d68,
title = "Colorectal cancer screening participation: Exploring relationship heterogeneity and scale differences using multiscale geographically weighted regression",
abstract = "Scotland has an organised colorectal cancer screening pro-gramme; however, despite proactively offering screening opportu-nities free to the at-risk population, and also despite using a screening test which may be completed at home, screening participation levels are unequal. Understanding causal pathways linking participation with other population characteristics may be aided by identifying how relationships between the two patterns vary across different localities, and such knowledge may also inform decisions regarding geographical targeting of screening promotion efforts. In this analysis, models calibrated using multiscale geographically weighted regression enabled the assessment of spatial variations of determinants of screening participation levels. The models were calibrated for localities across west central Scotland (n=409), where participation levels were relatively low, using aggregated individual-level screening records within a two-year window (2009-2011). Area deprivation was found to have a strong negative impact on participation levels across the study area, and ethnic population concentration had a significant impact on male participation levels on localities within Glasgow city. Estimates of local intercepts pointed to a systemic difference in screening participation between the two health board regions in the study area. Overall the results suggest that work to increase screening participation was necessary. They also suggest that barriers to participation could be addressed locally, and that differences between health board regions required further investigation.",
keywords = "Cancer, Local, Modelling, Screening, Spatial",
author = "Alistair Geddes and Fotheringham, {A. Stewart} and Gillian Libby and Steele, {Robert J.C.}",
note = "Funding Information: This work was supported by the Chief Scientist Office (grant number CZH/4/926), Scottish Government Chief Medical Officer and Public Health Directorate. We are also grateful for guidance from the editor and anonymous reviewers. Funding Information: Key words: Cancer; screening; local; N spatial; modelling. Further research is required to address these knowledge gaps, on-commercial and in this paper we consider one possible avenue, drawing on the Acknowledgements: this work was supported by the Chief Scientist local spatial modelling technique first developed as geographical-Office (grant number CZH/4/926), Scottish Government Chief Medical ly weighted regression (GWR) (Brunsdon et al., 1996; Officer and Public Health Directorate. We are also grateful for guidance Fotheringham et al., 2002), and subsequently refined as multiscale from the editor and anonymous reviewers. GWR (MGWR) (Fotheringham et al., 2017; Oshan et al., 2019; Yu et al., 2020). GWR has been applied previously to several health topics, including cervical cancer incidence (Cheng et al., 2011), coronary heart disease (Gebreab & Diez Roux, 2012), child immunisation (Marek et al., 2020), elderly self-rated health (Yang & Matthews, 2012), longevity and quality of life (Tabb et al., 2018), malaria (Ndiath et al., 2015), and the human immunodefi-ciency virus (HIV) (Feldacker et al., 2010). The number of health-focussed applications of MGWR is also increasing, including for examining obesity levels (Oshan et al., 2020), general mortality rates (Cupido et al., 2021), and the coronavirus disease 2019 (COVID-19) incidence (Mollalo et al., 2020; Raymundo et al., 2021), although to our knowledge, this is the first time it has been used in examining health-related behaviours (to the extent that Publisher Copyright: {\textcopyright} Copyright: the Author(s), 2021 Licensee PAGEPress, Italy.",
year = "2021",
doi = "10.4081/gh.2021.967",
language = "English (US)",
volume = "16",
journal = "Geospatial Health",
issn = "1827-1987",
publisher = "University of Naples Federico II",
number = "1",
}