Commentary: predictors of colorectal cancer screening in two underserved u.s. populations: a parallel analysis

A Commentary on
Predictors of Colorectal Cancer Screening in Two Underserved U. S. Populations: A Parallel Analysis

by Bernardo, B. M., Gross, A. L., Young, G., Baltic, R., Reisinger, S., Blot, W. J., et al. (2018). Front. Oncol. 8: 230. doi: 10. 3389/fonc. 2018. 00230

Introduction

The authors contribute to the literature on geographic colorectal cancer disparities by examining two different populations located in the major colorectal cancer incidence (CRC) hotspots of the Lower Mississippi Delta, West Central Appalachia, and Eastern Virginia/North Carolina regions ( 1 ). However, this study could be improved by incorporating more measures reflective of the neighborhood deprivation literature, such as fruit and vegetable consumption (which may decrease colon cancer risk) and extensively underscore the role of the gut microbiome in colon cancer risk ( 2 – 5 ). For example, fruit and vegetable consumption has been shown to reduce the risk of colon cancer ( 6 , 7 ). In one study, fruit consumption and only one vegetable category, legumes, was inversely associated with colon cancer risk ( 6 ). Another study found that consumption of green and white vegetables and fruits was inversely associated with colon cancer risk in men. Simultaneously, consumption of green, red/purple, and white vegetables and fruits was inversely associated with colon cancer risk in women ( 7 ). However, in the same study, consumption of orange/yellow vegetables and fruits in men was associated with increased colon cancer risk (e. g., citrus fruits and ginger) ( 7 ). Furthermore, diversifying the gut microbiome can aid in preventing colon cancer ( 8 ). For instance, eating red meat—a known carcinogen and an inflammatory agent in the bowel—is a common activity in the United States, and largely so in the Midwest and Deep South ( 8 , 9 ).

Geographical Differences of Colorectal Cancer Hotspots

While there was elaboration on the characteristics of CRC hotspots, the characteristics of CRC non-hotspot areas were not as detailed. For example, the study may have benefited from communicating how cancer incidence and mortality varies within the CRC non-hotspot and hotspot areas ( 10 ). Secondly, the fact that some men may hold machismo health beliefs (such as the belief that they can delay healthcare because of their capacity for pain) is an important health belief consideration for explaining the observed differences between men and women in CRC ( 11 ). For men, hyper-masculinity ideals may delay or deter them from seeking preventive healthcare services, and, in particular, colonoscopy ( 11 ).

In a hotspot-originating analysis, mortality rates for African-American (AA) males in the Lower Mississippi Delta Region (comprising 94 counties across Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee) have remained unchanged, while all other race/gender groups have declined in the last 25 years ( 12 ). In this study, traditional risk factors such as AA race and unemployment were linked to higher adjusted relative odds of being within screening guidelines. Interestingly, this gender disparity (38% males within guidelines), is seen in screening in the Southern Community Cohort (SCCS) study, which comprised the subject of this commentary ( 1 , 13 ).

Opportunities for Interventions

While the authors highlighted the importance of future interventions in underserved areas to increase CRC screenings, specific recommendations regarding how the study’s findings translate into specific health behavior change interventions were not provided. Lack of health insurance, low income, and smoking are well-documented colon cancer risk factors screening as well as viable opportunities for preventative intervention ( 14 – 16 ). Furthermore, the Community Guide recommends multicomponent interventions to increase screening for colorectal cancer, and the National Cancer Institute (NCI) provides a list of research-tested intervention programs (RTIPs) specifically aimed at increasing colorectal cancer screening ( 17 , 18 ). For example, Targeting Cancer in Blacks (TCiB) is a multicomponent, community-based intervention focused on awareness building and behavior modification in unscreened and under-screened AA adults ( 19 ). This 18-month intervention, which was disseminated through historically black colleges and universities (HBCUs), resulted in increased cancer screening among AAs in the Southeast United States. An intervention in a rural Washington state community of Hispanic individuals found that use of a promotora cultural worker increased colon cancer screening awareness, knowledge, and screening use in that population ( 20 ).

The finding that two out of the three CRC hotspot regions exhibited increased odds of CRC screening is intriguing. However, it is also possible that biological differences in CRC severity in hotspot regions exacerbated by race/ethnicity, lower educational attainment, higher obesity prevalence, and unhealthy lifestyles may lead to increased colorectal cancer mortality ( 21 – 25 ). Therefore, future studies should examine potential biological differences in CRC patients who reside in hotspot and non-hotspot areas to improve patient care. Specifically, the potential differences in the gut microbiome matter for individuals at greater risk of colon cancer, especially for those who occupy multiple disadvantaged social profiles and those whose typical diet is more fatty in composition (e. g., black individuals who live in urban environments concentrated with fast food restaurants and low quality produce in grocery stores) as obesity increases colon cancer risk.

Health professional recommendations have a positive influence on CRC screening ( 26 ). A pivotal role in patient education and motivating screening adherence is played by nurses, given the extended time they spend with patients. Arnold et al. ( 27 ) conducted a nurse-led intervention aimed at increasing knowledge and self-efficacy for CRC screening with Fecal Occult Blood Test (FOBT). Nurses used motivational interviewing techniques to identify, solve barriers, and motivate patients to complete FOBTs. Among those receiving nurse support, self-efficacy increased significantly, with patients indicating they could obtain an FOBT, complete it and mail in results. Thus, future interventions aimed at improving CRC screening adherence among those residing in hotspot regions should consider a nurse-led approach.

In conclusion, we are heartened by the contribution of Bernardo et al. as it further elucidates our understanding of screening differences by geographical regions. By building further on this research, with an understanding of how to link efficacious interventions, multidisciplinary efforts can improve the health outcomes of the regions’ underserved populations. Additionally, research that focuses on geographical screening differences should be translatable into an interdisciplinary, behavioral-based intervention improving health outcomes.

Summary of Risk Factors for Colon Cancer

– Lifestyle and Diet ( 28 , 29 )

– Personal History and Genetics ( 21 , 30 )

– Racial/Ethnic Background ( 31 , 32 )

– Geographical Environment ( 33 , 34 ).

Author Contributions

Each member of the study team contributed portions of the earlier draft manuscripts. The corresponding author prepared the final draft of the manuscript and edited earlier versions of this manuscript.

Funding

The authors declare that the research conducted have no commercial or financial interests. National Cancer Institute (T32 CA047888) funds the activities of the Cancer Prevention and Control Training Program at the University of Alabama at Birmingham.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors acknowledge support from the National Cancer Institute: T32 CA047888.

References

1. Bernardo BM, Gross AL, Young G, Baltic R, Reisinger S, Blot WJ, et al. Predictors of colorectal cancer screening in two underserved U. S. Populations: a parallel analysis. Front Oncol . (2018) 8: 230. doi: 10. 3389/fonc. 2018. 00230

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Lee JE, Chan AT. Fruit, vegetables, and folate: cultivating the evidence for cancer prevention. Gastroenterology . (2011) 141: 16–20. doi: 10. 1053/j. gastro. 2011. 05. 020

PubMed Abstract | CrossRef Full Text | Google Scholar

3. Smith DM, Cummins S, Taylor M, Dawson J, Marshall D, Sparks L, et al. Neighbourhood food environment and area deprivation: spatial accessibility to grocery stores selling fresh fruit and vegetables in urban and rural settings. Int J Epidemiol . (2009) 39: 277–84. doi: 10. 1093/ije/dyp221

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Sharkey JR, Horel S, Dean WR. Neighborhood deprivation, vehicle ownership, and potential spatial access to a variety of fruits and vegetables in a large rural area in Texas. Int J Health Geogr . (2010) 9: 26. doi: 10. 1186/1476-072X-9-26

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Pruitt SL, Davidson NO, Gupta S, Yan Y, Schootman M. Missed opportunities: racial and neighborhood socioeconomic disparities in emergency colorectal cancer diagnosis and surgery. BMC Cancer . (2014) 14: 927. doi: 10. 1186/1471-2407-14-927

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Vogtmann E, Xiang YB, Li HL, Levitan EB, Yang G, Waterbor JW, et al. Fruit and vegetable intake and the risk of colorectal cancer: results from the Shanghai Men’s Health Study. Cancer Causes Control.(2013) 24: 1935–45. doi: 10. 1007/s10552-013-0268-z

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Lee J, Shin A, Oh JH, Kim J. Colors of vegetables and fruits and the risks of colorectal cancer. World J Gastroenterol . (2017) 23: 2527–38. doi: 10. 3748/wjg. v23. i14. 2527

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Rea D, Coppola G, Palma G, Barbieri A, Luciano A, Del Prete P, et al. Microbiota effects on cancer: from risks to therapies. Oncotarget . (2018) 9: 17915–27. doi: 10. 18632/oncotarget. 24681

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Chan DS, Lau R, Aune D, Vieira R, Greenwood DC, Kampman E, et al. Red and processed meat and colorectal cancer incidence: meta-analysis of prospective studies. PLoS ONE . (2011) 6: e20456. doi: 10. 1371/journal. pone. 0020456

PubMed Abstract | CrossRef Full Text | Google Scholar

10. Simon MS, Thomson CA, Pettijohn E, Kato I, Rodabough RJ, Lane D, et al. Racial differences in colorectal cancer incidence and mortality in the women’s health initiative. Cancer Epidemiol Biomark Prev . (2011) 20: 1368. doi: 10. 1158/1055-9965. EPI-11-0027

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Springer KW, Mouzon DM. “ Macho Men” and preventive health care: implications for older men in different social classes. J Health Soc Behav.(2011). 52: 212–27. doi: 10. 1177/0022146510393972

PubMed Abstract | CrossRef Full Text | Google Scholar

12. Siegel RL, Sahar L, Robbins A, Jemal A. Where can colorectal cancer screening interventions have the most impact? Cancer Epidemiol Biomark Prev . (2015) 24: 1151. doi: 10. 1158/1055-9965. EPI-15-0082

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Signorello LB, Hargreaves MK, Blot WJ. The Southern Community Cohort Study: investigating health disparities. J Health Care Poor Underserved.(2010) 21(1 Suppl.): 26–37. doi: 10. 1353/hpu. 0. 0245

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Robinson CM, Cassells AN, Greene MA, Beach ML, Tobin JN, Dietrich AJ. Barriers to colorectal cancer screening among publicly insured urban women: no knowledge of tests and no clinician recommendation. J Natl Med Assoc . (2011) 103: 746–53. doi: 10. 1016/S0027-9684(15)30414-4

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Nagelhout E, Comarell K, Samadder NJ, Wu YP. Barriers to colorectal cancer screening in a racially diverse population served by a safety-net clinic. J Community Health . (2017) 42: 791–6. doi: 10. 1007/s10900-017-0319-6

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Knight JR, Kanotra S, Siameh S, Jones J, Thompson B, Thomas-Cox S. Understanding barriers to colorectal cancer screening in Kentucky. Prev Chronic Dis . (2015) 12: E95. doi: 10. 5888/pcd12. 140586

PubMed Abstract | CrossRef Full Text | Google Scholar

17. Guide TC. Cancer Screening: Multicomponent Interventions—Colorectal Cancer (2016).

Google Scholar

18. National Institutes of Health National Cancer Institute. Colorectal Cancer Screening Intervention Programs (2017).

Google Scholar

19. Blumenthal DS, Fort JG, Ahmed NU, Semenya KA, Schreiber GB, Perry S, et al. Impact of a two-city community cancer prevention intervention on African Americans. J Natl Med Assoc . (2005) 97: 1479–88.

PubMed Abstract | Google Scholar

20. Briant KJ, Sanchez JI, Ibarra G, Escareño M, Gonzalez NE, Jimenez Gonzalez V, et al. Using a culturally tailored intervention to increase colorectal cancer knowledge and screening among hispanics in a rural community. Cancer Epidemiol Biomark Prev . (2018) 27: 1283–8. doi: 10. 1158/1055-9965. EPI-17-1092

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Haggar FA, Boushey RP. Colorectal cancer epidemiology: incidence, mortality, survival, and risk factors. Clin Colon Rectal Surg . (2009) 22: 191–7. doi: 10. 1055/s-0029-1242458

PubMed Abstract | CrossRef Full Text | Google Scholar

22. Liu PH, Wu K, Ng K, Zauber AG, Nguyen LH, Song M, et al. Association of obesity with risk of early-onset colorectal cancer among women. JAMA Oncol . (2019) 5: 37–44. doi: 10. 1001/jamaoncol. 2018. 4280

PubMed Abstract | CrossRef Full Text | Google Scholar

23. Daniel CR, Shu X, Ye Y, Gu J, Raju GS, Kopetz S, et al. Severe obesity prior to diagnosis limits survival in colorectal cancer patients evaluated at a large cancer centre. Br J Cancer . (2016) 114: 103–9. doi: 10. 1038/bjc. 2015. 424

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Lathan CS, Cronin A, Tucker-Seeley R, Zafar SY, Ayanian JZ, Schrag D. Association of financial strain with symptom burden and quality of life for patients with lung or colorectal cancer. J Clin Oncol . (2016) 34: 1732–40. doi: 10. 1200/JCO. 2015. 63. 2232

CrossRef Full Text | Google Scholar

25. Kerr J, Anderson C, Lippman SM. Physical activity, sedentary behaviour, diet, and cancer: an update and emerging new evidence. Lancet Oncol . (2017) 18: e457–71. doi: 10. 1016/S1470-2045(17)30411-4

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Davis TC, Arnold CL, Rademaker AW, Platt DJ, Esparza J, Liu D, et al. FOBT completion in FQHCs: impact of physician recommendation, FOBT information, or receipt of the FOBT kit. J Rural Health . (2012) 28: 306–11. doi: 10. 1111/j. 1748-0361. 2011. 00402. x

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Arnold CL, Rademaker A, Liu D, Davis TC. Changes in colorectal cancer screening knowledge, behavior, beliefs, self-efficacy, and barriers among community health clinic patients after a health literacy intervention. J Community Med Health Educ . (2017) 7: 497. doi: 10. 4172/2161-0711. 1000497

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Aleksandrova K, Pischon T, Jenab M, Bueno-de-Mesquita HB, Fedirko V, Norat T, et al. Combined impact of healthy lifestyle factors on colorectal cancer: a large European cohort study. BMC Med . (2014) 12: 168. doi: 10. 1186/s12916-014-0168-4

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Hughes LAE, Simons CCJM, van den Brandt PA, van Engeland M, Weijenberg MP. Lifestyle, diet, and colorectal cancer risk according to (Epi)genetic instability: current evidence and future directions of molecular pathological epidemiology. Curr Colorectal Cancer Rep . (2017) 13: 455–69. doi: 10. 1007/s11888-017-0395-0

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Jasperson KW, Tuohy TM, Neklason DW, Burt RW. Hereditary and familial colon cancer. Gastroenterology . (2010) 138: 2044–58. doi: 10. 1053/j. gastro. 2010. 01. 054

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Ollberding NJ, Nomura AM, Wilkens LR, Henderson BE, Kolonel LN. Racial/ethnic differences in colorectal cancer risk: the multiethnic cohort study. Int J Cancer . (2011) 129: 1899–906. doi: 10. 1002/ijc. 25822

PubMed Abstract | CrossRef Full Text | Google Scholar

32. Theuer CP, Wagner JL, Taylor TH, Brewster WR, Tran D, McLaren CE, et al. Racial and ethnic colorectal cancer patterns affect the cost-effectiveness of colorectal cancer screening in the United States. Gastroenterology . (2001) 120: 848–56. doi: 10. 1053/gast. 2001. 22535

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Haselkorn T, Whittemore AS, Lilienfeld DE. Incidence of small bowel cancer in the United States and worldwide: geographic, temporal, and racial differences. Cancer Causes & Control . (2005) 16: 781–7. doi: 10. 1007/s10552-005-3635-6

PubMed Abstract | CrossRef Full Text | Google Scholar

34. Kamangar F, Dores GM, Anderson WF. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol . (2006) 24: 2137–50. doi: 10. 1200/JCO. 2005. 05. 2308

PubMed Abstract | CrossRef Full Text | Google Scholar