Colorectal cancer screening participation: Exploring relationship heterogeneity and scale differences using multiscale geographically weighted regression

Submitted: 12 December 2020
Accepted: 3 April 2021
Published: 11 May 2021
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Scotland has an organised colorectal cancer screening programme; however, despite proactively offering screening opportunities 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.

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Brunsdon C, Fotheringham AS, Charlton ME, 1996. Geographically weighted regression: A method for exploring spatial non-stationarity. Geogr Anal 28:281-98. DOI: https://doi.org/10.1111/j.1538-4632.1996.tb00936.x
Carstairs V, Morris R, 1989. Deprivation: explaining differences in mortality between Scotland, England and Wales. Br Med J 299:886-9. DOI: https://doi.org/10.1136/bmj.299.6704.886
Carstairs V, Morris R, 1991. Deprivation and health in Scotland. Aberdeen University Press, 350 pp.
Chapple A, Ziebland S, Hewitson P, McPherson A, 2008. What affects the uptake of screening for bowel cancer using a faecal occult blood test (FOBt): A qualitative study. Soc Sci Med 66:2425-35. DOI: https://doi.org/10.1016/j.socscimed.2008.02.009
Cheng EMY, Atkinson PM, Shahani AK, 2011. Elucidating the spatially varying relation between cervical cancer and socio-economic conditions in England. Int J Health Geogr 10:51. DOI: https://doi.org/10.1186/1476-072X-10-51
Clark G, Strachan JA, Carey FA, Godfrey T, Irvine A, McPherson A, Brand J, Anderson AS, Fraser CG, Steele RJC, 2021. Transition to quantitative faecal immunochemical testing from guaiac faecal occult blood testing in a fully rolled-out population-based national bowel screening programme. Gut 70:106-13. DOI: https://doi.org/10.1136/gutjnl-2019-320297
Cupido K, Fotheringham, AS, Jevtic, P, 2021. Local modelling of U.S. mortality rates: A multiscale geographically weighted regression approach. Popul Space Place 27:e2379. DOI: https://doi.org/10.1002/psp.2379
da Silva AR, Fotheringham AS, 2016. The multiple testing issue in geographically weighted regression. Geogr Anal 48:233-47. DOI: https://doi.org/10.1111/gean.12084
Feldacker C, Emch M, Ennett S, 2010. The who and where of HIV in rural Malawi: exploring the effects of person and place on individual HIV status. Health Place 16:996-1006. DOI: https://doi.org/10.1016/j.healthplace.2010.06.004
Fotheringham AS, Brunsdon C, Charlton M, 2002. Geographically weighted regression: the analysis of spatially varying relationships. Wiley, New York, USA, 284 pp.
Fotheringham AS, Yang WB, Kang W, 2017. Multiscale geographically weighted regression (MGWR). Ann Am Assoc Geogr 107:1247-65. DOI: https://doi.org/10.1080/24694452.2017.1352480
Gebreab SY, Diez Roux AV, 2012. Exploring racial disparities in CHD mortality between blacks and whites across the United States: a geographically weighted regression approach. Health Place 18:1006-14. DOI: https://doi.org/10.1016/j.healthplace.2012.06.006
Healthcare Improvement Scotland, 2015. Bowel Screening Standards: March 2015. Available from: http://www.healthcareimprovementscotland.org/our_work/standards_and_guidelines/stnds/bowel_screening_standards.aspx Accessed: 23 November 2020.
Honein-AbouHaidar GN, Kastner M, Vuong V, Perrier L, Daly C, Rabeneck L, Straus S, Baxter NN, 2016. Systematic review and meta-study synthesis of qualitative studies evaluating facilitators and barriers to participation in colorectal cancer screening. Cancer Epidemiol Biomarkers Prev 25:907-17. DOI: https://doi.org/10.1158/1055-9965.EPI-15-0990
ISD (Information Services Division, NHS National Services Scotland), 2011. Scottish Bowel Screening Programme. Key Performance Indicators Report: May 2011 data submission. Invitations between 1 November 2016 and 31 October 2018. Available from: https://www.isdscotland.org/Health-Topics/Cancer/Bowel-Screening/KPI_Report_publishedAug11.pdf Accessed: 15 September 2020.
ISD, 2018. Scottish Bowel Screening Programme Statistics. For invitations between 1 November 2015 and 31 October 2017. Available from: https://www.isdscotland.org/Health-Topics/Cancer/Publications/2018-08-07/2018-08-07-Bowel-Screening-Publication-Report.pdf Accessed: 23 November 2020.
ISD, 2019. Scottish Bowel Screening Programme. Key Performance Indicators Report: May 2019 data submission. Invitations between 1 November 2016 and 31 October 2018. Available from: https://www.isdscotland.org/Health-Topics/Cancer/Publications/2019-02-05/2019-02-05-Bowel-Screening-KPI-Report.xlsx Accessed: 23 November 2020.
Klabunde C, Blom J, Bulliard JL, Garcia M, Hagoel L, Mai V, Patnick J, Rozjabek H, Senore C, Tornberg S, 2015. Participation rates for organized colorectal cancer screening programmes: an international comparison. J Med Screen 22:119-26. DOI: https://doi.org/10.1177/0969141315584694
Li ZQ, Fotheringham AS, Oshan TM, Wolf LJ, 2020. Measuring bandwidth uncertainty in multiscale geographically weighted regression using Akaike weights. Ann Am Assoc Geogr 110:1500-20. DOI: https://doi.org/10.1080/24694452.2019.1704680
Maida M, Macaluso FS, Ianiro G, Mangiola F, Sinagra E, Hold G, Maida C, Cammarota G, Gasbarrini A, Scarpulla G, 2017. Screening of colorectal cancer: present and future. Expert Rev Anticancer Ther 17:1131-46. DOI: https://doi.org/10.1080/14737140.2017.1392243
Marek L, Hobbs M, McCarthy J, Wiki J, Tomintz M, Campbell M, Kingham S, 2020. Investigating spatial variation and change (2006-2017) in childhood immunisation coverage in New Zealand. Soc Sci Med 264:113292. DOI: https://doi.org/10.1016/j.socscimed.2020.113292
Mollalo A, Vahedi B, Rivera KM, 2020. GIS-based spatial modeling of COVID-19 incidence rate in the continental United States. Sci Total Environ 728:138884. DOI: https://doi.org/10.1016/j.scitotenv.2020.138884
Ndiath MM, Cisse B, Ndiaye JL, Gomis JF, Bathiery O, Dia AT, Gaye O, Faye B, 2015. Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site. Malar J 14:463. DOI: https://doi.org/10.1186/s12936-015-0976-9
O’Carroll RE, Chambers JA, Brownlee L, Libby G, Steele RJC, 2015. Anticipated regret to increase uptake of colorectal cancer screening (ARTICS): A randomised controlled trial. Soc Sci Med 142:118-27. DOI: https://doi.org/10.1016/j.socscimed.2015.07.026
Oshan TM, Li ZQ, Kang W, Wolf LJ, Fotheringham AS, 2019. MGWR: A Python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale. ISPRS Int J Geo-Inf 8 [Epub ahead of print]. DOI: https://doi.org/10.3390/ijgi8060269
Oshan TM, Smith JP, Fotheringham, AS, 2020. Targeting the spatial context of obesity determinants via multiscale geographically weighted regression. Int J Health Geogr 19 [Epub ahead of print]. DOI: https://doi.org/10.1186/s12942-020-00204-6
Rawla P, Sunkara T, Barsouk A, 2019. Epidemiology of colorectal cancer: incidence, mortality, survival, and risk factors. Gastroenterol Rev-Prz Gastroenterol 14:89-103. DOI: https://doi.org/10.5114/pg.2018.81072
Simpson L, 2014. How has ethnic diversity changed in Scotland? Centre on Dynamics of Ethnicity, University of Manchester, 4 pp.
Steele RJC, Kostourou I, McClements P, Watling C, Libby G, Weller D, Brewster DH, Black R, Carey FA, Fraser C, 2010a. Effect of repeated invitations on uptake of colorectal cancer screening using faecal occult blood testing: analysis of prevalence and incidence screening. Br Med J 341:c5531. DOI: https://doi.org/10.1136/bmj.c5531
Steele RJC, Kostourou I, McClements P, Watling C, Libby G, Weller D, Brewster DH, Black R, Carey FA, Fraser C, 2010b. Effect of gender, age and deprivation on key performance indicators in a FOBT-based colorectal screening programme. J Med Screen 17:68-74. DOI: https://doi.org/10.1258/jms.2010.009120
Tabb LP, McClure LA, Quick H, Purtle J, Diez Roux AV, 2018. Assessing the spatial heterogeneity in overall health across the United States using spatial regression methods: the contribution of health factors and county-level demographics. Health Place 51:68-77. DOI: https://doi.org/10.1016/j.healthplace.2018.02.012
Vogt V, Siegel M, Sundmacher L, 2014 Examining regional variation in the use of cancer screening in Germany. Soc Sci Med 110:74-80. DOI: https://doi.org/10.1016/j.socscimed.2014.03.033
von Wagner C, Baio G, Raine R, Snowball J, Morris S, Atkin W, Obichere A, Handley G, Logan RF, Rainbow S, Smith S, Halloran S, Wardle J, 2011. Inequalities in participation in an organized national colorectal cancer screening programme: results from the first 2.6 million invitations in England. Int J Epidemiol 40:712-8. DOI: https://doi.org/10.1093/ije/dyr008
Walsh D, Bendel N, Jones R, Hanlon P, 2010. It’s not ‘just deprivation’: why do equally deprived UK cities experience different health outcomes? Public Health 124:487-95. DOI: https://doi.org/10.1016/j.puhe.2010.02.006
Walsh D, McCartney G, Collins C, Taulbut M, Batty GD, 2017. History, politics and vulnerability: explaining excess mortality in Scotland and Glasgow. Public Health 151:1-12. DOI: https://doi.org/10.1016/j.puhe.2017.05.016
Wools A, Dapper EA, de Leeuw JRJ, 2016. Colorectal cancer screening participation: a systematic review. Eur J Public Health 26:158-68. DOI: https://doi.org/10.1093/eurpub/ckv148
Yang TC, Matthews SA, 2012. Understanding the non-stationary associations between distrust of the health care system, health conditions, and self-rated health in the elderly: A geographically weighted regression approach. Health Place 18:576-85. DOI: https://doi.org/10.1016/j.healthplace.2012.01.007
Yu HC, Fotheringham AS, Li ZQ, Oshan T, Kang W, Wolf LJ, 2020. Inference in multiscale geographically weighted regression. Geogr Anal 52:87-106. DOI: https://doi.org/10.1111/gean.12189

How to Cite

Geddes, A., Fotheringham, A. S., Libby, G., & Steele, R. J. (2021). Colorectal cancer screening participation: Exploring relationship heterogeneity and scale differences using multiscale geographically weighted regression. Geospatial Health, 16(1). https://doi.org/10.4081/gh.2021.967

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