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August 2003, Vol 93, No. 8 | American Journal of Public Health 1271-1274
© 2003 American Public Health Association


RESEARCH AND PRACTICE

Sociocultural Correlates of Breast Cancer Knowledge and Screening in Urban African American Women

Susan N. Lukwago, PhD, RD, Matthew W. Kreuter, PhD, MPH, Cheryl L. Holt, PhD, Karen Steger-May, MA, Dawn C. Bucholtz, MA, MPH and Celette Sugg Skinner, PhD

Susan N. Lukwago, Matthew W. Kreuter, Cheryl L. Holt, and Dawn C. Bucholtz are with Health Communication Research Laboratory, School of Public Health, Saint Louis University, St. Louis, Mo. Susan N. Lukwago is also with the St. Louis County Department of Health, St. Louis. Karen Steger-May is with Washington University School of Medicine, Division of Biostatistics, St. Louis. Celette Sugg Skinner is with Duke University Comprehensive Cancer Center, Durham, NC.

Correspondence: Requests for reprints should be sent to Matthew W. Kreuter, PhD, MPH, Health Communication Research Laboratory, Department of Community Health, School of Public Health, Saint Louis University, 3545 Lafayette Ave, Suite 428, St. Louis, MO 63104 (e-mail: kreuter{at}slu.edu).


    INTRODUCTION
 TOP
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
African American women are more likely to die of breast cancer than women of any other racial or ethnic group,1 even though national surveys report that mammography rates are higher for African Americans than for other groups.2 At least part of this discrepancy has been attributed to delayed diagnosis.3,4 Identifying sociocultural factors that influence timely screening and incorporating them into health messages for African American women may help reduce this disparity. This study examined associations between 5 such factors—collectivism, spirituality, racial pride, and present and future time orientation—and breast cancer–related knowledge, barriers to mammography, and mammography use and stage of change among urban African American women.


    METHODS
 TOP
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
Study Population
African American women aged 18 to 65 (N = 1241) were recruited from 10 public health centers in the city of St. Louis, Mo, were provided informed consent, completed a baseline questionnaire, and received $20 for participating. Fourteen women were removed from the sample because they did not provide personal identification information (n = 2), were age ineligible (n = 2), or enrolled twice (n = 10); the final sample was 1227. Of these, all women aged 40 years and older (n = 435) are included in the current analyses.

Measures
Sociocultural constructs. Sociocultural constructs were measured with scales developed by the project team and found to perform well in psychometric testing in a pilot sample of 72 African American women from lowincome urban housing communities.5 Internal consistency and temporal stability (2-week test–retest interval) on these scales were, respectively, collectivism (6 items; {alpha} = .93; r = 0.85; P = .001), spirituality (9 items; {alpha} = .88; r = 0.89; P = .001), racial pride (7 items; {alpha} = .84; r = 0.52; P = .001), present time orientation (5 items; {alpha} = .73; r = 0.52; P = .01), and future time orientation (5 items; {alpha} = .72; r = 0.54; P = .07).

Breast cancer–related knowledge. Based on previous research with African American women,6–9 measures of mammography knowledge (5 items), breast cancer knowledge (6 items), and breast cancer treatment knowledge (3 items) were developed. All items used a yes/no/not sure response format, and test–retest reliability for the measures was acceptable: r = 0.62; P < .001 (mammography); r = 0.63; P < .001 (breast cancer); and r = 0.45, P < .01 (treatment). Correct responses were summed to form an index variable for each measure with values of 0–5 (mammography), 0–6 (breast cancer), and 0–3 (treatment).

Barriers to mammography. A yes/no/not sure response format was used to assess whether women perceived each of 7 barriers to mammography as applying to them. Responses indicating the presence of a barrier were summed to form an index variable used in analyses, with possible values ranging from 0 to 7. Test–retest reliability for these items was acceptable (r = 0.70; P < .01).

Mammography use and stage of change. Three items assessed mammography use and stage of change. The first identified time of last mammogram (<=12 months ago; > 12 months ago; never). Test–retest reliability for this item was adequate (rs = 0.72; P < .001); for analyses, it was dichotomized into ever or never having a mammogram. The second assessed thinking about having a mammogram in the next 6 months (i.e., stage of change10). Test–retest reliability for this item was poor (r = 0.13; P = .60). The third assessed having an appointment for a mammogram in the next 6 months. Test–retest reliability for this item was strong (r = 0.78; P < .001). Women were classified as (1) precontemplators if they had not had a mammogram in the last 12 months, were not thinking about having one, and had no appointment for one; (2) contemplators if they were thinking about having one; (3) in preparation if they had an appointment for one; and (4) in action/maintenance if they had had a mammogram in the last 12 months. Family history of breast cancer, recommendation from a doctor or nurse to get a mammogram, age, years of school completed, work status (full time, part time, not working), and income also were assessed.

Statistical methods. Missing values for each sociocultural scale (2%–5% of respondents) were imputed by multiplying the sum of answered items by the ratio of items unanswered on the scale. Scale scores were dichotomized into high or low because of limited variability. This stratification was based on decisions from the larger intervention trial to create equal-sized groups of women who were high and low on each construct. Cutpoints approximated a median split.

Stepwise multiple logistic regression (for mammography use and stage of change) and stepwise multiple linear regression (for barriers and knowledge) were conducted for variables that had a P value less than .10 in bivariate comparisons to the outcome. Sociocultural variables and demographics (age, education, income, employment, and family history) were independent variables in both analyses, and physician or nurse recommendation and each knowledge scale were added as independent variables for the mammography use and stage of change analyses. Independent variables were sequentially selected for inclusion or exclusion from the model based on entry criteria of .10 and removal criteria of .15. Data were analyzed with SAS, Version 8.2 (SAS Institute Inc, Cary, NC).


    RESULTS
 TOP
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
Demographic Characteristics
Participants ranged in age from 40 to 65, with a mean age of 48.60 years (SD = 6.46). The mean years of education were 12.37 (SD = 2.19) and ranged from 3 to 20 years. About 43% (n = 188) were single, 18.9% (n = 82) were married, 27.1% (n = 118) were separated or divorced, and 8.7% (n = 38) were widowed (9 [2.1%] were missing data). About 44% (n = 193) were employed full time, 13.1% (n = 57) worked part time, and 40.2% (n = 175) were not employed at the time of enrollment (10 [2.3%] were missing data). The median household income before taxes was in the $10 001 to 20 000 bracket, with a range from less than $5000 to more than $60 000 per year.

Knowledge About Mammography, Breast Cancer, and Its Treatment
Women who had a present time orientation were younger, were less educated, had lower incomes, and had less mammography knowledge. Those who were less educated and had lower incomes had less knowledge about breast cancer. Those who had a present time orientation, were younger, were less educated, had lower incomes, were not employed, and did not have a family history of breast cancer had less knowledge about breast cancer treatment (Table 1Go).


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TABLE 1— Knowledge Scores, by Demographic and Sociocultural Characteristics, With Multiple Linear Regression Results (N = 379)
 
Barriers to Mammography
Women who had a present time orientation reported more barriers to mammography than did those who scored low on present time orientation (ß = 0.29 [SE = 0.11]; P < .01). Income was negatively associated with barriers (ß = -0.21 [SE = 0.07]; P < .01).

Mammography Use and Stage of Change
Present time orientation was negatively associated with ever having a mammogram, and age and mammography knowledge were positively associated. Age, employment, physician or nurse recommendation to get a mammogram, and mammogram knowledge were positively associated with mammography stage of change (Table 2Go).


View this table:
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TABLE 2— Percentage of Respondents in Each Stage of Change for Mammography and Mammography History With Adjusted Odds Ratios (ORs) for Associations With Demographic and Sociocultural Characteristics (N = 379)
 
Missing Data
Respondents not reporting key demographic information needed for analyses were excluded (n = 56). Excluded respondents had fewer years of education (10.8 vs 12.3; P = .01), were less likely to be employed (41% vs 61%; P = .01), and were more likely to score high on racial pride (78% vs 62%; P = .03). By conducting analyses with and without demographic variables of interest, we examined whether these differences affected the associations and found that statistical significance did not change in either direction for any association (data not reported).


    DISCUSSION
 TOP
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
Present time orientation (i.e., a focus on immediate or short-term consequences vs planning for the future) was negatively associated with breast cancer–related knowledge and mammography and positively associated with perceived barriers to mammography. Because getting a mammogram suggests thinking about the future in the absence of symptoms, this finding is consistent with definitions of present time orientation and findings reported in previous research.11–13 Having a present time orientation is probably more closely linked to income than race,14–16 and we believe it reflects life circumstance more than individual disposition. Still, effects of present time orientation persisted after adjusting for income, education, and employment, 3 indicators of social circumstance.

The pattern of association between racial pride and these same outcomes was also consistent but in the opposite direction and not reaching statistical significance. Our racial pride scale captures a type of race-related activism (e.g., "Black women should keep up with issues that are important to the Black community"), conscientiousness (e.g., "Racial pride is important for developing strong Black families"), and connectedness (e.g., "I feel a strong connection to other Black women") that may reflect heightened awareness about issues affecting African American women and could translate into personal action on health-related matters.

Receiving a recommendation from a health care provider has been shown to be an important predictor of mammography17,18 and was found to be so again in this study. Unlike many studies of breast cancer screening in underserved women, we did not find an association between education, income, and mammography. This may reflect the relatively minimal variation in socioeconomic status in our sample or a growing awareness among women that programs exist to pay for mammograms if you cannot afford one.

Public health practitioners working to promote mammography might consider integrating present time orientation and racial pride into their approaches for African American women. In our work in health communication, this means developing messages and materials that validate and build on a woman’s status on these variables. Previous research has shown that "tailoring"19 messages in this way can enhance their effectiveness.20,21 As this study progresses, we will test for the first time the effects of health messages that are tailored for African American women specifically on sociocultural variables. We encourage others to experiment with these constructs in hopes of enhancing interventions promoting breast cancer screening among African American women and helping eliminate health disparities.


    Acknowledgments
 
This project was funded by the National Cancer Institute grant CA81872.

We gratefully acknowledge Ken Schechtman, PhD, for assistance with statistical analyses and Eddie Clark, PhD, and Debra Haire-Joshu, PhD, for their roles as co-investigators in the study. The authors also wish to thank Rashida Dorsey, Gail Garvey, Jasmine Hall, Lorna Haughton, Marian Ladipo, Jennifer Legardy, Sharyn Parks, Holly Patterson, and Kim Vaughn for their assistance in data collection for this project.

Human Participant Protection

This project was approved by the Saint Louis University institutional review board.


    Footnotes
 
Contributors

S. N. Lukwago, M. W. Kreuter, C. L. Holt, and K. Steger-May wrote the brief. M. W. Kreuter and C. S. Skinner designed the study. K. Steger-May and C. L. Holt designed and conducted the analyses. C. S. Skinner and D. C. Bucholtz critically reviewed and provided feedback on the brief.

Peer Reviewed

Accepted for publication November 25, 2002.


    References
 TOP
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
1. Healthy People 2010: Understanding and Improving Health. Washington, DC: US Dept of Health and Human Services; 2001.

2. Breen N, Wagener DK, Brown ML, et al. Progress in cancer screening over a decade: results of cancer screening from the 1987, 1992, and 1998 National Health Interview Surveys. J Natl Cancer Inst.2001;93:1704–1713.[Abstract/Free Full Text]

3. Caplan LS, May DS, Richardson LC. Time to diagnosis and treatment of breast cancer: results from the National Breast and Cervical Cancer Early Detection Program, 1991–1995. Am J Public Health.2000;90:130–134.[Abstract/Free Full Text]

4. Edwards BK, Howe HL, Ries L, et al. Annual report to the nation on the status of cancer, 1973–1999, featuring implications of age and aging on U.S. cancer burden. Cancer.2002;94:2766–2792.[ISI][Medline]

5. Lukwago SN, Kreuter MW, Bucholtz DC, et al. Development and validation of brief scales to measure collectivism, religiosity, racial pride, and time orientation in urban African American women. Fam Community Health. 2001;24:63–71.[ISI][Medline]

6. Champion VL, Scott CR. Reliability and validity of breast cancer screening belief scales in African American women. Nurs Res. 1997;46:331–337.[ISI][Medline]

7. Rimer BK, Keintz MK, Kessler HB, et al. Why women resist screening mammography: patient-related barriers. Radiology.1989;172:243–246.[Abstract/Free Full Text]

8. Skinner C, Sykes R, Monsees B, et al. Learn, Share, and Live: breast cancer education for older, urban minority women. Health Educ Behav. 1998;25:60–78.[Abstract]

9. Rimer BK, Trock B, Engstrom PF, et al. Why do some women get regular mammograms? Am J Prev Med. 1991;7:69–74.[ISI][Medline]

10. Rakowski W, Fulton JP, Feldman JP. Women’s decision making about mammography: a replication of the relationship between stages of adoption and decisional balance. Health Psychol.1993;12:209–214.[ISI][Medline]

11. Brown CM, Segal R. Ethnic differences in temporal orientation and its implications for hypertension management. J Health Soc Behav.1996;37:350–361.[ISI][Medline]

12. Zimbardo PG, Keough KA, Boyd JN. Present time perspective as a predictor of risky driving. Pers Individual Differences.1997;23:1007–1023.

13. Rothspan S, Read SJ. Present versus future time perspective and HIV risk among heterosexual college students. Health Psychol.1996;15:131–134.[ISI][Medline]

14. Leshan LL. Time orientation and social class. J Abnorm Soc Psychol. 1952;47:589–592.[ISI]

15. Bergadaa MM. The role of time in the action of the consumer. J Consumer Res.1990;17:289–302.

16. Akbar N. The evolution of human psychology for African Americans. In: Jones RL, ed. Black Psychology. 3rd ed. Berkeley, Calif: Cobb & Henry Publishers; 1991:99–123.

17. Fox S, Stein J. The effect of physician-patient communication on mammography utilization by different ethnic groups. Med Care.1991;29:1065–1082.[ISI][Medline]

18. Mickey RM, Vezina JL, Worden JK, et al. Breast screening behavior and interactions with health care providers among lower income women. Med Care.1997;35:1204–1211.[ISI][Medline]

19. Kreuter MW, Strecher VJ, Glassman B. One size does not fit all: the case for tailoring print materials. Ann Behav Med. 1999;21:276–283.[ISI][Medline]

20. Skinner CS, Strecher VJ, Hospers H. Physicians’ recommendations for mammography: do tailored messages make a difference? Am J Public Health. 1994;84:43–49.[Abstract/Free Full Text]

21. Campbell MK, DeVellis BM, Strecher VJ, et al. Improving dietary behavior: the effectiveness of tailored messages in primary care settings. Am J Public Health.1994;84:783–787.[Abstract/Free Full Text]




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