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Cancer Causes & Control

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19.08.2019 | Original Paper

US urban–rural disparities in breast cancer-screening practices at the national, regional, and state level, 2012–2016

verfasst von: Lam Tran, Phoebe Tran

Erschienen in: Cancer Causes & Control | Ausgabe 10/2019

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Abstract

Purpose

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.

Methods

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.

Results

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%).

Conclusions

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.

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

National Cancer Institute (2019) Breast cancer—patient version. https://www.cancer.gov/types/breast

Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018. CA 68(1):7–30

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

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

American Cancer Society (2017) Limitations of Mammograms. https://www.cancer.org/cancer/breast-cancer/screening-tests-and-early-detection/mammograms/limitations-of-mammograms.html.

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

Drukteinis JS, Mooney BP, Flowers CI, Gatenby RA (2013) Beyond mammography: new frontiers in breast cancer screening. Am J Med 126(6):472–479. https://doi.org/10.1016/j.amjmed.2012.11.025 CrossRefPubMedPubMedCentral

Orwat J, Caputo N, Key W, De Sa J (2017) Comparing rural and urban cervical and breast cancer screening rates in a privately insured population. Social Work Public Health 32(5):311–323. https://doi.org/10.1080/19371918.2017.1289872 CrossRef

10.

Heller SL, Rosenkrantz AB, Gao Y, Moy L (2018) County-level factors predicting low uptake of screening mammography. Am J Roentgenol 211(3):624–629. https://doi.org/10.2214/AJR.18.19541 CrossRef

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 CrossRefPubMed

12.

Stanley E, Lewis MC, Irshad A, Ackerman S, Collins H, Pavic D, Leddy RJ (2017) Effectiveness of a mobile mammography program. Am J Roentgenol 209(6):1426–1429. https://doi.org/10.2214/AJR.16.17670 CrossRef

13.

Berkowitz Z, Zhang X, Richards TB, Sabatino SA, Peipins LA, Holt J (2014) White MC (2019) Multilevel regression for small-area estimation of mammography use in the United States. Cancer Epidemiol Biomark Prev 28(1):32–40. https://doi.org/10.1158/1055-9965.Epi-18-0367 CrossRef

14.

Doescher MP, Jackson JE (2009) Trends in cervical and breast cancer screening practices among women in rural and urban areas of the United States. J Public Health Manag Pract 15(3):200–209. https://doi.org/10.1097/PHH.0b013e3181a117da CrossRefPubMed

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

16.

Coughlin SS, Thompson TD, Hall HI, Logan P, Uhler RJ (2002) Breast and cervical carcinoma screening practices among women in rural and nonrural areas of the United States, 1998–1999. Cancer 94(11):2801–2812. https://doi.org/10.1002/cncr.10577 CrossRefPubMed

17.

Engelman KK, Hawley DB, Gazaway R, Mosier MC, Ahluwalia JS, Ellerbeck EF (2002) Impact of geographic barriers on the utilization of mammograms by older rural women. J Am Geriatr Soc 50(1):62–68CrossRefPubMed

18.

Henry KA, McDonald K, Sherman R, Kinney AY, Stroup AM (2014) Association between individual and geographic factors and nonadherence to mammography screening guidelines. J Women's Health 23(8):664–674CrossRef

19.

Vang S, Margolies LR, Jandorf L (2018) Mobile mammography participation among medically underserved women: a systematic review. Prev Chronic Dis 15:E140. https://doi.org/10.5888/pcd15.180291 CrossRefPubMedPubMedCentral

20.

Coughlin SS, King J (2010) Breast and cervical cancer screening among women in metropolitan areas of the United States by county-level commuting time to work and use of public transportation, 2004 and 2006. BMC Public Health 10(1):146CrossRefPubMedPubMedCentral

21.

Nuño T, Gerald JK, Harris R, Martinez ME, Estrada A, García F (2012) Comparison of breast and cervical cancer screening utilization among rural and urban Hispanic and American Indian women in the Southwestern United States. Cancer Causes Control 23(8):1333–1341CrossRefPubMed

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

32.

Harding C, Pompei F, Burmistrov D, Welch HG, Abebe R, Wilson R (2015) Breast cancer screening, incidence, and mortality across US counties. JAMA Inter Med 175(9):1483–1489. https://doi.org/10.1001/jamainternmed.2015.3043 CrossRef

33.

Verdial FC, Etzioni R, Duggan C, Anderson BO (2017) Demographic changes in breast cancer incidence, stage at diagnosis and age associated with population-based mammographic screening. J Surg Oncol 115(5):517–522. https://doi.org/10.1002/jso.24579 CrossRefPubMedPubMedCentral

34.

Rauscher GH, Allgood KL, Whitman S (2002) Conant E (2012) Disparities in screening mammography services by race/ethnicity and health insurance. J Women's Health 21(2):154–160. https://doi.org/10.1089/jwh.2010.2415 CrossRef

35.

Ayanian JZ, Landon BE, Zaslavsky AM, Newhouse JP (2013) Racial and ethnic differences in use of mammography between Medicare Advantage and traditional Medicare. J Natl Cancer Inst 105(24):1891–1896. https://doi.org/10.1093/jnci/djt333 CrossRefPubMedPubMedCentral

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 CrossRefPubMed

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 CrossRefPubMed

38.

Martinez ME, Unkart JT, Tao L, Kroenke CH, Schwab R, Komenaka I, Gomez SL (2017) Prognostic significance of marital status in breast cancer survival: a population-based study. PLoS ONE 12(5):e0175515. https://doi.org/10.1371/journal.pone.0175515 CrossRefPubMedPubMedCentral

39.

Parise C, Caggiano V (2018) The influence of marital status and race/ethnicity on risk of mortality for triple negative breast cancer. PLoS ONE 13(4):e0196134. https://doi.org/10.1371/journal.pone.0196134 CrossRefPubMedPubMedCentral

40.

Hanske J, Meyer CP, Sammon JD, Choueiri TK, Menon M, Lipsitz SR, Noldus J, Nguyen PL, Sun M, Trinh QD (2016) The influence of marital status on the use of breast, cervical, and colorectal cancer screening. Prev Med 89:140–145. https://doi.org/10.1016/j.ypmed.2016.05.017 CrossRefPubMed

41.

Agarwal S, Ying J, Boucher KM, Agarwal JP (2017) The association between socioeconomic factors and breast cancer-specific survival varies by race. PLoS ONE 12(12):e0187018. https://doi.org/10.1371/journal.pone.0187018 CrossRefPubMedPubMedCentral

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):981

43.

Albano JD, Ward E, Jemal A, Anderson R, Cokkinides VE, Murray T, Henley J, Liff J, Thun MJ (2007) Cancer mortality in the United States by education level and race. J Natl Cancer Inst 99(18):1384–1394. https://doi.org/10.1093/jnci/djm127 CrossRefPubMed

44.

Mouw T, Koster A, Wright ME, Blank MM, Moore SC, Hollenbeck A, Schatzkin A (2008) Education and risk of cancer in a large cohort of men and women in the United States. PLoS ONE 3(11):e3639. https://doi.org/10.1371/journal.pone.0003639 CrossRefPubMedPubMedCentral

45.

Rosenberg L, Wise LA, Palmer JR, Horton NJ, Adams-Campbell LL (2005) A multilevel study of socioeconomic predictors of regular mammography use among African-American women. Cancer Epidemiol Prev Biomark 14(11):2628–2633CrossRef

46.

Abdelsattar ZM, Hendren S, Wong SL (2017) The impact of health insurance on cancer care in disadvantaged communities. Cancer 123(7):1219–1227. https://doi.org/10.1002/cncr.30431 CrossRefPubMed

47.

Bitler MP, Carpenter CS (2016) Health insurance mandates, mammography, and breast cancer diagnoses. Am Econ J Econ Policy 8(3):39–68. https://doi.org/10.1257/pol.20120298 CrossRefPubMedPubMedCentral

48.

Niu X, Roche LM, Pawlish KS, Henry KA (2013) Cancer survival disparities by health insurance status. Cancer Med 2(3):403–411. https://doi.org/10.1002/cam4.84 CrossRefPubMedPubMedCentral

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 Carolina

51.

Jann B (2013) Predictive margins and marginal effects in Stata

52.

Williams R (2012) Using Stata’s margins command to estimate and interpret adjusted predictions and marginal effects. Stata J 12(2):308–331CrossRef

53.

StataCorp, (2017) Stata statistical software: release 15. StataCorp LLC, College Station

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

55.

Koehler E, Brown E, Haneuse SJPA (2009) On the assessment of Monte Carlo error in simulation-based statistical analyses. Am Stat 63(2):155–162. https://doi.org/10.1198/tast.2009.0030 CrossRefPubMedPubMedCentral

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):37–61PubMedPubMedCentral

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

59.

Bowlin SJ, Morrill BD, Nafziger AN, Jenkins PL, Lewis C, Pearson TA (1993) Validity of cardiovascular disease risk factors assessed by telephone survey: the behavioral risk factor survey. J Clin Epidemiol 46(6):561–571CrossRefPubMed

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 CrossRefPubMedPubMedCentral

61.

Schneider KL, Clark MA, Rakowski W, Lapane KL (2012) Evaluating the impact of non-response bias in the behavioral risk factor surveillance system (BRFSS). J Epidemiol Community Health 66(4):290–295. https://doi.org/10.1136/jech.2009.103861 CrossRefPubMed

Titel: US urban–rural disparities in breast cancer-screening practices at the national, regional, and state level, 2012–2016
verfasst von: Lam Tran
Phoebe Tran
Publikationsdatum: 19.08.2019
Verlag: Springer International Publishing
Erschienen in: Cancer Causes & Control / Ausgabe 10/2019
Print ISSN: 0957-5243
Elektronische ISSN: 1573-7225
DOI: https://doi.org/10.1007/s10552-019-01217-8

Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

US urban–rural disparities in breast cancer-screening practices at the national, regional, and state level, 2012–2016

Abstract

Purpose

Methods

Results

Conclusions

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Die Highlights vom Kongress des American College of Cardiology 2024

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusions

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