US urban–rural disparities in breast cancer-screening practices at the national, regional, and state level, 2012–2016
- 45 Downloads
Previous studies suggesting that rural US women may be less likely to have a recent mammogram than urban women are limited in either scope or granularity. This study explored urban–rural disparities in US breast cancer-screening practices at the national, regional, and state levels.
We used data from the 2012, 2014, and 2016 Behavioral Risk Factor Surveillance Systems surveys. Logistic models were utilized to examine the impact of living in an urban/rural area on mammogram screening at three geographic levels while adjusting for covariates. We then calculated average adjusted predictions (AAPs) and average marginal effects (AMEs) to isolate the association between breast cancer screening and the urban/rural factor.
At all geographic levels, AAPs of breast cancer screening were similar among urban, suburban, and rural residents. Regarding “ever having a mammogram” and “having a recent mammogram,” urban women had small but significantly higher adjusted probabilities (AAP: 94.6%, 81.1%) compared to rural women (AAP: 93.5%, 80.2%).
While urban–rural differences in breast cancer screening are small, they can translate into tens of thousands of rural women not receiving mammograms. Hence, there is a need to continue screening initiatives in these areas to reduce the number of breast cancer deaths.
KeywordsBreast cancer screening Mammogram Average adjusted predictions Average marginal effects Urban–rural disparity
- 1.American Cancer Society (2019) Cancer facts & figures 2018. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2018.html
- 2.National Cancer Institute (2019) Breast cancer—patient version. https://www.cancer.gov/types/breast
- 3.Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA 68(1):7–30Google Scholar
- 4.American Cancer Society (2018) Estimated number of deaths for the four major cancers by sex and age group, 2018. https://www.cancer.org/content/dam/cancer-org/research/cancer-facts-and-statistics/annual-cancer-facts-and-figures/2018/estimated-number-of-deaths-for-the-four-major-cancers-by-sex-and-age-group-2018.pdf
- 5.American Cancer Society (2019) Survival rates for breast cancer. https://www.cancer.org/cancer/breast-cancer/understanding-a-breast-cancer-diagnosis/breast-cancer-survival-rates.html
- 6.American Cancer Society (2017) Limitations of Mammograms. https://www.cancer.org/cancer/breast-cancer/screening-tests-and-early-detection/mammograms/limitations-of-mammograms.html.
- 7.American Cancer Society (2018) American Cancer Society guidelines for the early detection of cancer. https://www.cancer.org/healthy/find-cancer-early/cancer-screening-guidelines/american-cancer-society-guidelines-for-the-early-detection-of-cancer.html
- 11.Zhang P, Too G, Irwin KL (2000) Utilization of preventive medical services in the United States: a comparison between rural and urban populations. J Rural Health 16(4):349–356. https://doi.org/10.1111/j.1748-0361.2000.tb00485.x CrossRefGoogle Scholar
- 15.Peppercorn JM, Houck K, Wogu AF, Villagra V, Lyman GH, Wheeler SB (2013) National survey of breast cancer screening in rural America. J Clin Oncol 31(26_suppl):13–13. https://doi.org/10.1200/jco.2013.31.26_suppl.13
- 22.Centers for Disease Control and Prevention (2013) Behavioral risk factor surveillance system 2012 codebook report land-line and cell-phone data. https://www.cdc.gov/brfss/annual_data/2012/pdf/CODEBOOK12_LLCP.pdf
- 23.Centers for Disease Control and Prevention (2015) Behavioral risk factor surveillance system 2014 codebook report land-line and cell-phone data. https://www.cdc.gov/brfss/annual_data/2014/pdf/CODEBOOK14_LLCP.pdf
- 24.Centers for Disease Control and Prevention (2017) Behavioral risk factor surveillance system overview: BRFSS 2016. https://www.cdc.gov/brfss/annual_data/2016/pdf/overview_2016.pdf
- 25.Centers for Disease Control and Prevention (2019) BRFSS questionnaires. https://www.cdc.gov/brfss/questionnaires/index.htm
- 26.Centers for Disease Control and Prevention (2013) Overview: BRFSS 2011. https://www.cdc.gov/brfss/annual_data/2011/overview_11.pdf
- 27.North Dakota Department of Health (2017) Methodology. https://www.ndhealth.gov/brfss/?id=57
- 28.Centers for Disease Control and Prevention (2016) Breast cancer screening guidelines for women. https://www.cdc.gov/cancer/breast/pdf/breastcancerscreeningguidelines.pdf
- 29.Montana Department of Public Health & Human Services (2015) Interpreting and reporting BRFSS data. https://dphhs.mt.gov/Portals/85/publichealth/documents/BRFSS/Factors/2015Factors2.pdf
- 30.North Carolina Department of Health and Human Services (2012) Technical Notes 2012. https://schs.dph.ncdhhs.gov/data/brfss/2012/technical.htm.
- 31.Alaska Department of Health and Social Services (2018) Complete health indicator report of mental health—frequent mental distress—adults (18+). https://ibis.dhss.alaska.gov/indicator/complete_profile/FMD.html
- 36.Richardson LC, Henley SJ, Miller JW, Massetti G, Thomas CC (2016) Patterns and trends in age-specific black-white differences in breast cancer incidence and mortality - United States, 1999–2014. MMWR Morb Mortal Wkly Rep 65(40):1093–1098. https://doi.org/10.15585/mmwr.mm6540a1 CrossRefGoogle Scholar
- 37.Cunningham JE, Walters CA, Hill EG, Ford ME, Barker-Elamin T, Bennett CL (2013) Mind the gap: racial differences in breast cancer incidence and biologic phenotype, but not stage, among low-income women participating in a government-funded screening program. Breast Cancer Res Treat 137(2):589–598. https://doi.org/10.1007/s10549-012-2305-0 CrossRefGoogle Scholar
- 42.Centers for Disease Control and Prevention (2005) Breast cancer screening and socioeconomic status–35 metropolitan areas, 2000 and 2002. MMWR Morb Mortal Wkly Rep 54(39):981Google Scholar
- 49.Centers for Disease Control and Prevention (2014) Behavioral risk factor surveillance system 2013 codebook report land-line and cell-phone data. https://www.cdc.gov/brfss/annual_data/2013/pdf/CODEBOOK13_LLCP.pdf
- 50.SAS Institute Inc (2017) SAS 9.4. Cary, North CarolinaGoogle Scholar
- 51.Jann B (2013) Predictive margins and marginal effects in StataGoogle Scholar
- 53.StataCorp, (2017) Stata statistical software: release 15. StataCorp LLC, College StationGoogle Scholar
- 54.U.S. Census Bureau (2015 ) Census Bureau Regions and Divisions with State FIPS Codes. https://www2.census.gov/geo/docs/maps-data/maps/reg_div.txt
- 56.Farrance I, Frenkel R (2014) Uncertainty in measurement: a review of monte carlo simulation using microsoft excel for the calculation of uncertainties through functional relationships, including uncertainties in empirically derived constants. Clin Biochem Rev 35(1):37–61Google Scholar
- 57.US Census Bureau (2018) QuickFacts Illinois, US. https://www.census.gov/quickfacts/fact/table/il,US/PST045218
- 58.Centers for Disease Control and Prevention (2015) United states cancer statistics: data visualizations. https://gis.cdc.gov/Cancer/USCS/DataViz.html
- 60.Klompas M, Cocoros NM, Menchaca JT, Erani D, Hafer E, Herrick B, Josephson M, Lee M, Payne Weiss MD, Zambarano B, Eberhardt KR, Malenfant J, Nasuti L, Land T (2017) State and local chronic disease surveillance using electronic health record systems. Am J Public Health 107(9):1406–1412. https://doi.org/10.2105/ajph.2017.303874 CrossRefGoogle Scholar