Skip to main content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
W V Med J. Author manuscript; available in PMC 2016 Jun 7.
Published in final edited form as:
W V Med J. 2014 Mar-Apr; 110(2): 20–26.
PMCID: PMC4896067
NIHMSID: NIHMS789859
PMID: 24902464

Predictors of Self-reported Adherence to Mammography Screening Guidelines in West Virginia Women Visiting a Stationary Facility

Ami Vyas, MS, Suresh Madhavan, PhD, Kimberly Kelly, PhD, Aaron Metzger, PhD, Judith Schreiman, MD, and Scott Remick, MD
Author information Copyright and License information PMC Disclaimer

Abstract

The objectives of this study are to describe the characteristics of women age 40 years and above who utilize a stationary mammography facility and to determine the predictors of self-reported adherence to mammography screening guidelines. Data were analyzed using the expanded version of Andersen Behavioral Model of Healthcare Utilization. Of the 1,104 women included in the analysis, 1,019 women (92.3%) reported having had a mammogram in the past two years. In logistic regression after adjusting for all the variables, older age, having health insurance, not having delayed medical care due to transportation problem, being adherent to clinical breast exam (CBE), Pap test and other routine screenings and having positive views about mammography screening significantly predicted adherence to mammography screening. Adherence to mammography screening was very high in this sample, and enabling and need-related factors and positive views about mammography screening predicted adherence to mammography screening guidelines.

Introduction

West Virginia (WV) is the only state that lies completely within Appalachia and 34 out of its 55 counties are classified as rural.1,2 Appalachia is a largely rural, medically underserved region in the country with high levels of poverty, low levels of education, high rates of chronic disease, and poor health behaviors.3–6 WV has a lower incidence but higher rates of advanced and unstaged breast cancer (BC).2,7–11 This discrepancy has been attributed to low mammography screening rates among WV women.2,12 A study on BC screening in WV using Behavioral Risk Factor and Surveillance System (BRFSS) reported that as compared to the national estimate of 76.6%, 74.5% of WV women had a mammogram in the previous two years.12 Another recent study indicated that less than 40% of WV Medicaid fee-for-service women had a mammogram related billing in 2007–2008 within the previous two years although mammography screening is covered by WV Medicaid.13 The authors of this study suggested that there may be factors other than insurance coverage and financial constraints, such as lack of knowledge about mammography, views and attitudes about mammography screening, lack of physician recommendation, lack of transportation, which may influence screening rates in the WV Medicaid population.13 Thus, there is a vital need to determine the predictors of adherence to mammography screening guidelines in WV women who routinely utilize stationary mammography facilities to get mammograms. Hence, the objectives of this research study are to describe the characteristics of women age 40 years and above who utilize a stationary mammography facility and to determine the predictors of self-reported adherence to mammography screening guidelines by comparing women who are adherent with those who are not.

Conceptual Framework

The ‘expanded’ version of Andersen Behavioral Model for Health Services Utilization (Andersen model) was utilized as the conceptual model for this study (Figure-1).14 This model includes psychosocial factors to the basic Andersen model comprising of predisposing, enabling and need-related factors. Previous studies have reported that psychosocial factors have a strong influence on health prevention and maintenance behaviors and are widely studied in the cancer screening behavior.15,16 Hence, the ‘expanded’ version of Andersen model which includes psychosocial factors, was utilized for the study as it provided a strong theoretical framework to identify the factors that influence adherence to mammography screening guidelines in WV women.

An external file that holds a picture, illustration, etc. Object name is nihms789859f1.jpg

Conceptual model illustrating the constructs of expanded version of Andersen Behavioral Model of Healthcare Services Utilization in predicting adherence to screening mammography guidelines.

Methods

Mammography screening stationary facility

There are 70 mammography screening centers in WV of which the Betty Puskar Breast Care Center (BPBCC, a stationary facility) is the largest mammography screening stationary facility in WV and hence is selected as the representative stationary facility. The center screens approximately 10,000–12,000 women each year from 35 out of 55 WV counties such as Monongalia, Doddridge, Calhoun, Pocahontas, Greenbrier, Harrison, and southern counties such as Raleigh and Wyoming, to name a few.

Participants

Participants for this research study comprised of women who had mammography screening at the BPBCC at least once in the past ten years and completed the ‘Mammography Screening and Preventive Care Survey’. Out of 16,687 women age 40 years and above who utilized the BPBCC to get a screening mammogram at least once in the past ten years (from August 2001 to July 2011), 2,255 women were randomly selected and were mailed the survey. 1,104 women (48.96%) completed and returned the survey.

Survey Instrument, Survey Administration & Data Collection

Data were collected via the West Virginia University Institutional Review Board approved Mammography Screening and Preventive Care Survey. The survey has several sections including personal health history, menstrual and pregnancy history, family history of cancer, cancer risk assessment and screening history, views on BC screening, BC awareness, preventive care and wellness history, and demographics. The details about the survey development are explained elsewhere.17

A survey, a cover letter and a prepaid business reply envelope were mailed to the 2,255 randomly selected women who had mammography screening at the BPBCC at least once in the past ten years. Two rounds of the survey were sent to these women at three-week intervals to maximize the response rate. A $5 gift-card was mailed to all women who completed and returned the survey to acknowledge their participation and time.

Dependent variable - Self-reported on-schedule adherence to mammography screening guidelines

The main outcome of interest was self-reported on-schedule adherence to mammography screening guidelines, defined as having had a mammogram in the past one to two years.18 The dependent variable was dichotomized into adherent and non-adherent groups. For this study, the United States Preventive Services Task Force (USPSTF) 2002 recommendations were utilized which advocates mammography screening every one to two years for women age 40 years and above.19,20 This is also in general agreement with the current recommendations from various professional organizations such as the Centers for Disease Control & Prevention, Healthy People 2010 & 2020 objectives, and National Cancer Institute.

Independent variables

Table 1 provides the independent variables included in the study. These include predisposing factors such as age, education level, and employment status, body mass index (BMI), smoking status, and alcohol consumption; enabling factors such as marital status, household income, health insurance, visit to physician and OB/GYN in the past year, and delay in medical care due to transportation. Need-related factors included were self-reported health status, family history of BC, breast problems in the past, breast biopsy in the past, adherence to clinical breast exam (CBE), adherence to Pap test, having had any cancer, and a composite score of having had other screening tests such as blood glucose test, bone mineral density test, cholesterol test, high blood pressure test (possible scores 0, 1, 2, 3, or 4). The composite score was grouped into two groups, those with scores 0–3 and those with the score 4. A woman who had all the four screening tests in previous two years was given a score of 4 while a woman who did not have any of these screening tests in the previous two years was given a score of 0. A woman was considered adherent to CBE if she had CBE in the previous one year as per recommended guidelines and adherent to Pap test if she had Pap test within the previous two years as per recommended guidelines.21 Perceived five-year risk and perceived lifetime risk of developing BC (lower, similar, higher), views towards mammography screening, and knowledge about BC and mammography screening comprised the psychosocial factors. The details of the assessment of positive and negative views towards mammography screening, knowledge about BC and mammography screening are described elsewhere.17

Table 1

Description of the Study Sample of WV Women age 40 and above. Stationary Mammography Facility (Betty Puskar Breast Care Center)

Stationary facility
N (1,104)%
PREDISPOSING FACTORS
Age
 40–4921719.66
 50–6463057.07
 65 & above25723.28
Education
 Less than HS151.36
 Some HS/HS grad27324.73
 GED/Tech13512.23
 Some college/Graduate68161.68
Employment status
 Employed63557.52
 Unemployed46942.48
Body Mass Index
 Underweight/Normal weight35131.79
 Overweight to Morbidly Obese75368.21
Smoking status
 Never72966.03
 Former26724.18
 Current1089.78
Alcohol consumption
 Yes52647.64
 No57852.36
ENABLING FACTORS
Marital Status
 Married/Partnered84876.81
 Single25623.19
Household Income
 Less than $25,00023221.01
 $25,000–$50,00027024.46
 $50,000–$75,00022019.93
 More than $75,00038234.60
Health Insurance
 Yes1,04894.93
 No565.07
Visit to doctor in past year
 Yes80572.92
 No29927.08
Visit to OB/GYN in past year
 Yes58252.72
 No52247.28
Delayed care due to transportation problem
 Yes343.08
 No1,07096.92
NEED-RELATED FACTORS
Self-rated Health Status
 Fair/Poor16815.22
 Excellent/V.good/Good93684.78
Family History of BC
 Yes21619.57
 No88880.43
Breast problems
 Yes25923.46
 No84576.54
Breast biopsy in past
 Yes36833.33
 No73666.67
Adherence to CBE
 Yes69262.68
 No41237.32
Adherence to PAP test
 Yes77470.11
 No33029.89
History of Cancer
 Yes15013.59
 No95486.41
Total score of screenings
 0–375368.21
 435131.79
PSYCHOSOCIAL FACTORS
Perceived five-year risk
 Lower39135.42
 Similar54149.00
 Higher17215.58
Perceived Lifetime risk
 Lower33730.53
 Similar57151.72
 Higher19617.75
Knowledge
 Low756.79
 Moderate68361.87
 High34631.34
Views
 Positive ViewsMean1.975
 Negative ViewsMean5.822

HS: high school; V.good: very good, OB/GYN: obstetrician/gynecologist, ADL: activities of daily living; IADL: instrumental activities of daily living. For views, score 1 is equal to strongly agree and score 7 is equal to strongly disagree on the scale of 1 to 7.

Non-response bias assessment

Women who did not participate in the study may be different from those who participated, and hence non-response bias was assessed. The details of the non-response bias assessment are described elsewhere.22 Non-respondents were significantly more likely to be unemployed, and had less than college-level education.

Statistical Analyses

Descriptive statistics were used to describe the characteristics of the study sample. Chi-square tests for categorical variables and t-tests for continuous variables were used to determine significant differences between self-reported adherent and non-adherent groups. Logistic regression was performed to analyze the relationship between self-reported adherence with all the constructs of the Andersen model, after controlling for predisposing, enabling, need-related and psychosocial factors. ‘Non-adherent group’ was the reference group for the dependent variable. Resulting odds ratios and their corresponding 95% confidence intervals were examined. The findings that were significant with p-values less than 0.05 levels are discussed. SAS 9.2 software was used for the statistical analyses.

Results

Characteristics of the study cohort

Table 1 describes the characteristics of 1,104 women age 40 years and above who had at least one mammogram at the stationary mammography facility in the past ten years. A majority (57%) of the women were in the 50–64 age group, 23% were 65 and above and 20% were 40–49 years old. A majority were married or partnered (77%), had at least some college level education (62%), were employed (58%), overweight to morbidly obese (68%), had a household income more than $50,000 (55%), and were insured (95%). Seventy-three percent of women had visited a doctor in the past year, while 53% had visited an OB/GYN in the past year. Twenty percent of women reported a family history of BC, 73% had a Pap test in the past two years, and 63% had a CBE in the past year. A majority (62%) had moderate knowledge while 31% showed higher knowledge about BC and mammography screening. The mean score was 1.975 for the positive views statements and 5.822 for the negative views statements (on the scale of 1 = Strongly agree and 7 = Strongly disagree). Out of 1,104 women, 1,019 women (92.3%) reported adherence to mammography screening guidelines.

Results of Bivariate Analyses

Self-reported adherence to mammography screening guidelines was higher in women who had at least some college-level education, were never smokers, were married/partnered, had higher household income, had health insurance, had visited a doctor and/or OB/GYN in the past year, had a breast biopsy in the past, were adherent to CBE and Pap test, perceived their lifetime risk of developing BC as higher, reported higher knowledge of BC and mammography screening and strongly agreed with the positive views, and strongly disagreed with the negative views about mammography screening (data not shown).

Results of Multivariate Analyses for the stationary facility study sample

Table 2 describes the adjusted odds ratio of self-reported adherence to mammography screening guidelines in women aged 40 years and above who utilized a stationary mammography facility, after controlling for all the predisposing, enabling, need-related and psychosocial factors (only significant variables are presented). Among predisposing factors, being older (age 65 and above) was a significant predictor of adherence to mammography screening guidelines (AOR = 2.803, 95% CI = 1.055–7.451). Among enabling factors, women who did not have health insurance remained significantly less likely to be adherent to mammography screening guidelines (AOR = 0.208, 95% CI = 0.087–0.499). Those who reported delayed medical care due to transportation problem were 73% less likely to be adherent to mammography screening guidelines (AOR = 0.274, 95% CI = 0.084–0.894). Furthermore, among need-related factors, women were not adherent to CBE and Pap test, and who did not have all the four screenings in the past two years were significantly less likely to be adherent to mammography screening guidelines. The AORs were 0.253 (95% CI = 0.124–0.514), 0.179 (95% CI = 0.094–0.342) and 0.349 (95% CI = 0.146–0.833), respectively. In addition, women whose level of agreement towards positive views about mammography screening reduced by one point on the agreement scale, were 31% less likely to be adherent to mammography screening guidelines (AOR = 0.691, 95% CI = 0.567–0.841).

Table 2

Adjusted Odds Ratios and 95% Confidence Interval from Logistic Regression Of Self-Reported Adherence to Mammography Guidelines

Stationary mammography facility
AOR95%CIp-valueSig
PREDISPOSING FACTORS
Age
 40–491
 50–641.918[0.942, 3.906]0.0725*
 65 & above2.803[1.055, 7.451]0.0388
ENABLING FACTORS
Health Insurance
 Yes1***
 No0.208[0.087, 0.499]0.0004
Delayed care due to transportation problem*
 Yes0.274[0.084, 0.894]0.0318
 No1
NEED-RELATED FACTORS
Adherence to CBE
 Yes1***
 No0.253[0.124, 0.514]0.0001
Adherence to PAP test
 Yes1***
 No0.179[0.094, 0.342]<0.0001
Total score of screenings*
 0–30.349[0.146, 0.833]0.0178
 41
PSYCHOSOCIAL FACTORS
Views***
 Positive Views0.691[0.567, 0.841]0.0002
 Negative Views1.061[0.871, 1.292]0.5573

Only significant variables are shown in the table. Bold values indicate reference category for each group.

The regressions also include intercept terms and parameter estimates for other variables controlled are not presented. Asterisks represent statistically significant group differences compared to the reference group. “Non-adherence to mammography screening” is the reference group for the dependent variable.

AOR: adjusted odds ratio; CI: confidence interval. For views, score 1 is equal to strongly agree and score 7 is equal to strongly disagree on the scale of 1 to 7.

***p < 0.001;
**0.001 =< p < 0.01;
*0.01 =< p < 0.05

Discussion

In this study, the characteristics of women age 40 years and above who utilized a stationary mammography facility and the predictors of self-reported adherence to mammography screening guidelines were examined. Overall, 92.3% of women in the study sample were adherent to mammography screening guidelines. This rate is substantially above the national Healthy People 2010 goals for mammography screening,23 and the national screening rate of 75.4% in 2010.24 This finding is also in contrast to a previous study on WV women12 and a recent study on WV Medicaid fee-for-service women.13 The high mammography screening rate among women who utilized stationary facility suggests that these women never have had or have already overcome the majority of the barriers to mammography screening. In addition, the screening facility is located in a university town which may introduce some bias in the selection of the sample which may have ultimately resulted in higher screening rates. The sample was more affluent and educated as compared to national averages which may have resulted in higher screening rates.

Among predisposing factors, older age (65 and above) was associated with adherence to mammography screening guidelines, which is consistent with previous studies.25–30 As Medicare covers mammograms, women age 65 years and above may have regular access to screening services and hence are more likely to be adherent to mammography screening guidelines. Among enabling factors, having insurance was a significant predictor of adherence to mammography screening, which is consistent with the previous studies.25,30,31 This suggests that health insurance coverage is a very important access factor which supports women’s utilization of mammography screening services. Also, women who reported delay in medical care due to transportation problems were more likely to be non-adherent to mammography screening, suggesting that transportation problem is one of the key issues associated with non-adherence in the geographically challenging state of WV. Hence, although women have higher education levels and higher income levels, insurance coverage and transportation problems pose threats to their screening behaviors.

Among need-related factors, adherence to the CBE, Pap test and other tests for blood glucose, blood cholesterol, bone mineral density, and blood pressure strongly predicted adherence to mammography screening guidelines. This is consistent with a previous study which indicates that women who follow such preventative behaviors are sufficiently knowledgeable about the importance of preventive healthcare to overcome any barriers that they may encounter to screening.28 Among psychosocial factors, having strong positive views about mammography screening was associated with adherence to mammography screening. This finding is consistent with the previous study by Magai C et. al.32 Hence, the findings of this study are consistent with the previous studies which also indicated that lack of insurance, lack of transportation, younger age, and views about mammography screening restricted women from adhering to mammography screening guidelines.13,31 These findings may be helpful in developing interventions for women under 65 years of age, without health insurance coverage and who have transportation problems, and who are not adherent to other preventive behaviors, in order to increase screening rates in women who are not adherent to mammography screening guidelines.

There are several limitations of the study. One limitation is the response rate; 51% of women who utilized a stationary mammography facility did not respond to the surveys. A non-respondents analysis indicated that non-respondents were significantly more likely to be unemployed and with lower levels of education. Hence, these should be taken into consideration while extrapolating the findings of the study. Moreover, data is collected from only one stationary screening facility which is assumed to represent stationary screening facilities in WV. BPBCC is located in a university town from which a part of the sample was drawn. This may incorporate some selection bias. However, the area outside the 5-miles radius of the town is very rural and underserved and is considered to be a medically underserved area. Another limitation is that survey data is self-reported which may differ from mammography screening information obtained from medical records of healthcare providers. In addition, the findings of this study may not be generalized to women residing outside of WV.

Conclusion

Adherence to mammography screening was very high in women age 40 years and above who utilized a university town stationary mammography screening facility. Enabling and need-related factors and positive views about mammography screening predicted adherence to mammography screening guidelines in these women.

Acknowledgments

This research study is partially funded by Susan G. Komen For the Cure, Claude Worthington Benedum Foundation, and AHRQ grant # R24HS018622-02. The authors acknowledge the PhD students, Amit Raval, Parul Agarwal, Tricia Lee Wilkins, Traci LeMasters and Elvonna Atkins from the Department of Pharmaceutical Systems & Policy, West Virginia University, for helping in mailing out the surveys for the study.

Contributor Information

Ami Vyas, Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown, WV.

Suresh Madhavan, Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown, WV.

Kimberly Kelly, Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown, WV. Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV.

Aaron Metzger, Department of Psychology, West Virginia University, Morgantown, WV.

Judith Schreiman, Department of Radiology, School of Medicine, West Virginia University, Morgantown, WV.

Scott Remick, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV.

References

1. Health Resource and Services Administration. [Accessed March 5, 2013];List of Rural Counties and Designated Eligible Census Tracts in Metropolitan Counties. 2009 ftp://ftp.hrsa.gov/ruralhealth/eligibility2005.pdf.
2. Lengerich EJ, Tucker TC, Powell RK, et al. Cancer incidence in Kentucky, Pennsylvania, and West Virginia: disparities in Appalachia. J Rural Health. 2005;21(1):39–47. [PubMed] [Google Scholar]
3. U.S. Census Bureau. Persons 25 years old and over with a bachelor’s degree or more, 2008. Washington, DC: U.S. Census Bureau; 2010. [Accessed March 5, 2013]. http://www.census.gov/compendia/statab/2010/ranks/rank19.html. [Google Scholar]
4. U.S. Census Bureau. Persons below the poverty level, 2008. Washington, DC: U.S. Census Bureau; 2010. [Accessed March 5, 2013]. http://www.census.gov/compendia/statab/2010/ranks/rank34.html. [Google Scholar]
5. Kaiser State Health Facts. Overweight and obesity rates for adults by sex, 2009. Menlo Park, CA: Kaiser Family Foundation; 2009. [Accessed March 5, 2013]. http://www.statehealthfacts.org. [Google Scholar]
6. Kaiser State Health Facts. Percent of adults who smoke by sex, 2008. Menlo Park, CA: Kaiser Family Foundation; 2008. [Accessed March 5, 2013]. http://www.statehealthfacts.org. [Google Scholar]
7. Wingo PA, Tucker TC, Jamison PM, et al. Cancer in Appalachia, 2001–2003. Cancer. 2007;112:181–192. [PubMed] [Google Scholar]
8. Lengerich EJ, Chase GA, Beiler J, Darnell M. Increased risk of unknown stage cancer from residence in a rural area: health disparities with poverty and minority status. Hershey, PA: Pennsylvania State University and the Penn State Cancer Institute, Department of Health Evaluation Sciences; 2006. [Google Scholar]
9. State Cancer Profiles. Incidence and mortality rate reports for West Virginia by county. Bethesda, MD: National Cancer Institute; 2006. [Accessed March 5, 2013]. http://statecancerprofiles.cancer.gov/ [Google Scholar]
10. United States Cancer Statistics (USCS) Rankings by state: 2006, male and female, all cancer sites combined. Atlanta, GA: Centers for Disease Control and Prevention (CDC); 2010. [Accessed March 5, 2013]. http://apps.nccd.cdc.gov/uscs/ [Google Scholar]
11. United States Cancer Statistics (USCS) State vs. national rates: 2006, female, West Virginia. Atlanta, GA: Centers for Disease Control and Prevention (CDC); 2012. [Accessed March 5, 2013]. http://apps.nccd.cdc.gov/uscs/ [Google Scholar]
12. Khanna R, Bhanegaonkar A, Colsher P, Madhavan S, Halverson J. Breast cancer screening, incidence and mortality in West Virginia. WV Med J. 2009:25–32. Special CME Issue. [PubMed] [Google Scholar]
13. Bhanegaonkar A, Madhavan S, Khanna R, Remick SC. Declining mammography screening in a State Medicaid Fee-for-Service Program: 1999–2008. J Womens Health. 2012;21(8):821–829. [PMC free article] [PubMed] [Google Scholar]
14. Bradley EH, McGraw SA, Curry L, et al. Expanding the Andersen Model: The role of psychosocial factors in long-term care use. Health Services Research. 2002;37(5):1221–1242. [PMC free article] [PubMed] [Google Scholar]
15. Allen J, Sorensen G, Stoddard A, Peterson K, Colditz G. The relationship between social network characteristics and breast cancer screening practices among employed women. Annals of Behavioral Medicine. 1999;21:193–200. [PubMed] [Google Scholar]
16. Suarez L, Ramirez A, Villarreal R, et al. Social networks and cancer screening in four US Hispanic groups. American Journal of Preventive Medicine. 2000;19:47–52. [PubMed] [Google Scholar]
17. Vyas A, Madhavan S, Lemasters T, et al. Factors influencing adherence to mammography screening guidelines in Appalachian Women participating in a mobile mammography program. J Comm Health. 2012;37(3):632–646. [PubMed] [Google Scholar]
18. Gierisch JM, Reiter PL, Rimer BK, Brewer NT. Standard definitions of Adherence for infrequent yet repeated health behaviors. Am J Health Behav. 2010;34(6):669–679. [PMC free article] [PubMed] [Google Scholar]
19. U S. Preventive Services Task Force. Screening for breast cancer: recommendations and rationale. Ann Intern Med. 2002;137(5):344–346. [PubMed] [Google Scholar]
20. Humphrey LL, Helfand M, Chan BK, Woolf SH. Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002;137(5 part 1):347–360. [PubMed] [Google Scholar]
21. Smith RA, Cokkinides V, Brawley O. Cancer screening in the United States, 2012: A review of current American Cancer Society Guidelines and current issues in cancer screening. CA:A Cancer Journal for Clinicians. 2012;62:129–142. [PubMed] [Google Scholar]
22. Vyas A, Madhavan S, Kelly KM, et al. Do Appalachian women attending a mobile mammography program differ from those visiting a stationary mammography facility? Journal of Community Health. 2013 Accepted for publication, February 2013. [PMC free article] [PubMed] [Google Scholar]
23. United States Department of Health and Human Services. Healthy people 2010: Understanding and improving health. Washington DC: US department of Health and Human Services; 2010. [Google Scholar]
24. National Cancer Institute. [Accessed March 5, 2013];State cancer profiles screening and risk factors report 2010, 2010. 2010 http://progressreport.cancer.gov/doc_detail.asp?pid=1&did=2009&chid=92&coid=916&mid=
25. Rahman SMM, Digman MB, Shelton BJ. Factors influencing adherence to guidelines for screening mammography among women aged 40 years and older. Ethn Disp. 2003;13(4):477–484. [PMC free article] [PubMed] [Google Scholar]
26. Gierisch JM, Earp JA, Brewer NT, Rimer BK. Longitudinal predictors of non-adherence to maintenance of mammography. Cancer Epidemiol Biomarkers Prev. 2010;19(4):1103–1111. [PMC free article] [PubMed] [Google Scholar]
27. Meissner HI, Breen N, Taubman ML, Vernon SW, Graubard BU. Which women aren’t getting mammograms and why? (United States) Cancer Causes Control. 2007;18:61–70. [PubMed] [Google Scholar]
28. Coughlin SS, Uhler RJ, Hall I, Briss PA. Non adherence to Breast and Cervical cancer screening: What are the linkages to chronic disease risk? Prev Chronic Dis. 2004;1(1):A04. [PMC free article] [PubMed] [Google Scholar]
29. Borrayo EA, Hines L, Byers T, et al. Characteristics associated with mammography screening among both Hispanic and non-hispanic white women. J Womens Health. 2009;18(10):1585–1594. [PMC free article] [PubMed] [Google Scholar]
30. Zapka JG, Stoddard A, Maul L, Costanza ME. Interval adherence to mammography screening guidelines. Medical Care. 1991;29(8):697–707. [PubMed] [Google Scholar]
31. Rakowski W, Meissner H, Vernon SW, Breen N, Rimer B, Clark MA. Correlates of Repeat and recent mammography for women ages 45 to 75 in the 2002 to 2003 Health Information National Trends Survey (HINTS 2003) Cancer Epidemiol Biomarkers Prev. 2006;15(11):2093–2101. [PubMed] [Google Scholar]
32. Magai C, Consedine N, Neugut AI, Hershman DL. Common psychosocial factors underlying breast cancer screening and breast cancer treatment adherence: a conceptual review and synthesis. J Womens Health. 2007;16(1):11–23. [PubMed] [Google Scholar]