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Correlates of Condom Use Among Somali and Ethiopian Immigrants in the U.S.

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Abstract

The study examined correlates of consistent condom use in steady heterosexual relationships among Somali and Ethiopian immigrants in Minnesota. Study participants (n = 205) responded to questions on attitudes, social norms, perceived behavioral control, self-efficacy, behavioral intention, and self-reported male condom use. Participants were neither for, nor against using condoms, and the same was true for social influence and self-efficacy; however, reported moderately favorable attitude toward condom use and little difficulties in using condoms. Self-efficacy emerged as the factor with the strongest direct influence on behavioral intention to use condoms. In turn, behavioral intention was a significant predictor of self-reported condom use. Increasing male condom use self-efficacy among Somali and Ethiopian immigrants is suggested as a main component of public health intervention seeking to curb the spread of HIV and other STIs in Minnesota.

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References

  1. Centers for Disease Control and Prevention. HIV surveillance report: diagnoses of HIV Infection and AIDS in the United States and dependent areas. 2011;23. https://doi.org/www.cdc.gov/hiv/library/reports/surveillance/2011/surveillance_report_vol_23.html. Accessed 26 June 2014.

  2. Prosser AT, Tang T, Hall HI. HIV in persons born outside the United States, 2007–2010. JAMA. 2012;308(6):601–7.

    PubMed  Google Scholar 

  3. Kerani PR, Kent JB, Sides T, Dennis G, Ibrahim AR, Cross H, et al. HIV among African-born persons in the United States: a hidden epidemic. Acquir Immune Defic Syndr. 2008;49(1):102–6.

    Google Scholar 

  4. Minnesota Department of Health. Epidemiological profile of HIV/AIDS in Minnesota. Risk populations: African-born persons. https://doi.org/www.health.state.mn.us/divs/idepc/diseases/hiv/epiprofile/africanborn.html. Accessed 24 June 2014.

  5. Washington State Department of Health. HIV among foreign-born blacks. 2010. https://doi.org/www.doh.wa.gov/cfh/hiv/statistics/docs/fs12-10fb.pdf. Accessed 30 June 2014.

  6. Washington State Department of Health. Washington State HIV fact sheet. HIV among foreign-born blacks. 2014. https://doi.org/www.doh.wa.gov/Portals/1/Documents/Pubs/150-046-HIVAmongForeignBornBlacks.pdf. Accessed 3 March 2015.

  7. Minnesota HIV/AIDS Epidemiological profile—African-born (n. d.). https://doi.org/www.health.state.mn.us/divs/idepc/diseases/hiv/epiprofile/africanborn.pdf. Accessed 3 March 2015.

  8. Harawa NT, Bingham TA, Cochran SD, Greenland S, Cunningham WE. HIV prevalence among foreign-and US-born clients. Am J Public Health. 2002;92:1958–63.

    PubMed  PubMed Central  Google Scholar 

  9. Blanas DA, Nichols K, Bekele M, Lugg A, Kerani RP, Horowitz CR. HIV/AIDS among African-born residents in the United States. J Immigr Health. 2013;15(4):718–24.

    Google Scholar 

  10. Minnesota Department of Health. Companion text for the Minnesota HIV/AIDS prevalence and mortality report, 2010 slide set. 2010. https://doi.org/www.health.state.mn.us/divs/idepc/diseases/hiv/stats/pmtext2010.pdf. Accessed 4 July 2014.

  11. Minnesota Department of Health. HIV/AIDS surveillance. https://doi.org/www.health.state.mn.us/divs/idepc/diseases/hiv/hivstatistics.html. Accessed 9 Aug 2014.

  12. Cartwright CP. The changing epidemiology of HIV/AIDS at a Minnesota Hospital: impact of demographic change and viral diversity. J Med Virol. 2006;78:S19–21.

    PubMed  Google Scholar 

  13. Beckwith CG, DeLong AK, Desjardins SF, et al. HIV infection in refugees: a case-control analysis of refugees in Rhode Island. Int J Infect Dis. 2009;13:186–92.

    PubMed  Google Scholar 

  14. Johnson A, Hu X, Dean HD. Epidemiologic differences between native-born and foreign-born black people diagnosed with HIV infection in 33 U.S. states, 2001–2007. Public Health Rep. 2010;4(125):61–9.

    Google Scholar 

  15. UNAIDS. Annual report 2009. https://doi.org/www.hivpolicy.org/Library/HPP001865.pdf. Accessed 1 July 2014.

  16. Barrett HR, Mulugeta B. Human immunodeficiency virus (HIV) and migrant “risk environments”: the case of the Ethiopian and Eritrean immigrant community in the West Midlands of the U.K. Psychol Health Med. 2010;15(3):357–69.

    PubMed  Google Scholar 

  17. Lazarus JV, Himedan HM, Ostergaard LR, Liljestrad J. HIV/AIDS knowledge and condom use among Somali and Sudanese immigrants in Denmark. Scand J Public Health. 2006;34:92–9.

    PubMed  Google Scholar 

  18. Rosenthal L, Scott DP, Kelleta Z, et al. Assessing the HIV/AIDS health services needs of African immigrants to Houston. AIDS Educ Prev. 2003;15(6):570–80.

    PubMed  Google Scholar 

  19. Tompkins M, Smith L, Jones K, Swindells S. HIV education needs among Sudanese immigrants and refugees in the Midwestern States. AIDS Behav. 2006;10(3):319–23.

    PubMed  Google Scholar 

  20. Fishbein M. The role of theory in HIV prevention. AIDS Care. 2000;12(3):273–8.

    CAS  PubMed  Google Scholar 

  21. Fishbein M, Yzer MC. Using theory to design effective health behavior interventions. Commun Theory. 2003;13(2):164–83.

    Google Scholar 

  22. Institute of Medicine. Speaking of health: assessing health communication strategies for diverse populations. Committee for behavior change in the 21st Century: improving the health of diverse populations, Board on Neuroscience and Behavioral Health. 2002. https://doi.org/www.nap.edu/catalog/10018.html. Accessed 15 Aug 2014.

  23. Montano DE, Kasprzyk D. Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and Health education: theory, research and practice. San Francisco: Jossey-Bass; 2008. p. 67–92.

    Google Scholar 

  24. Ajzen I. The theory of planned behavior. Organ Behav Hum Dec. 1991;50:179–211.

    Google Scholar 

  25. Ajzen I, Madden TJ. Prediction of goal directed behavior: attitudes, intentions, and perceived behavioral control. J Exp Soc Psychol. 1986;22:453–74.

    Google Scholar 

  26. Bandura A. Social foundations of thoughts and action: a social cognitive theory. Englewood Cliffs: Prentice Hall; 1986.

    Google Scholar 

  27. Bandura A. Social cognitive theory and exercise of control over HIV infection. In: DiClemente RJ, Peterson JL, editors. Preventing AIDS: theories and methods of behavioral interventions. New York: Plenum Press; 1994. p. 25–60.

    Google Scholar 

  28. Ajzen I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. J Appl Soc Psychol. 2002;32:665–83.

    Google Scholar 

  29. Boer H, Mashamba MT. Psychosocial correlates of HIV protection motivation among Black adolescents in Venda, South Africa. AIDS Educ Prev. 2005;17(6):590–602.

    PubMed  Google Scholar 

  30. Molla M, Astrom AN, Brehane Y. Applicability of the theory of planned behavior to intended and self-reported condom use in a rural Ethiopian population. AIDS Care. 2007;19(3):425–31.

    CAS  PubMed  Google Scholar 

  31. Sutton S, French PD, Hennings SJ, et al. Eliciting salient beliefs in research on the theory of planned behavior: the effect of question wording. In: Armitage CJ, Christian J, editors. Planned behavior: the relationship between human thoughts and action. New Brunswick: Transaction Publisher; 2004.

    Google Scholar 

  32. Kline RB. Principles and practices of structural equation modeling. New York: Guilford; 2005.

    Google Scholar 

  33. Weston R, Chan F, Gore PA, Catalano D. An introduction to using structural equation models in rehabilitation psychology. Rehab Psychol. 2008;53(3):340–56.

    Google Scholar 

  34. Fishbein M, Ajzen I. Belief, attitude, intention, and behavior: an introduction to theory and research. Reading: Addison-Wesley; 1975.

    Google Scholar 

  35. Francis JJ, Eccles MP, Johnston M, et al. Constructing questionnaires on theory of planned behavior. A manual for health service researches. 2004. Center for Health Services Research. University of New Castle. UK. https://doi.org/pages.bangor.ac.uk/~pes004/exercise_psych/downloads/tpb_manual.pdf. Accessed 1 Feb 2012.

  36. Tabachnick BG, Fidell LS. Using multivariate statistics. 5th ed. Boston: Allyn and Bacon; 2007.

    Google Scholar 

  37. Acock AC. Working with missing data. J Marriage Fam. 2005;67:1012–28.

    Google Scholar 

  38. Myers TA. Goodbye, listwise deletion: presenting hot deck imputation as an easy and effective for handling missing data. Commun Methods and Meas. 2011;5(4):297–310.

    Google Scholar 

  39. Muthen LK, Muthen BO. Mplus user’s guide. 7th ed. Los Angeles: Muthen & Muthen; 1998–2012.

  40. Byrne B. Structural equation modeling with Mplus: basic concepts, application, and programming. New York: Taylor & Francis Group; 2011.

    Google Scholar 

  41. Raykov T, Marcoulides GA. First course in structural equation modeling. 2nd ed. New Jersey: Lawrence Erlbaum Associate, Inc.; 2006.

    Google Scholar 

  42. Hu LT, Benter PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6:1–55.

    Google Scholar 

  43. Iacobucci D. Structural equation modeling: fit indices, sample size, and advanced topics. J Consum Psychol. 2010;20:90–8.

    Google Scholar 

  44. Hooper D, Coughlan J, Mullen MR. Structural equation modeling: guidelines for determining model fit. Electron J Bus Res Methods. 2008;6(1):53–60.

    Google Scholar 

  45. Browne MW, Cudeck R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, editors. Testing structural equation models. Newbury Park: Sage; 1993. p. 136–62.

    Google Scholar 

  46. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 7th ed. New Jersey: Pearson Prentice Hall; 2010.

    Google Scholar 

  47. Sorensen HE, Slater SF. Development and empirical validations of symmetric component measures of multidimensional constructs: customer and competitor orientation. Psychol Rep. 2008;103:199–213.

    PubMed  Google Scholar 

  48. Belachew BA. Factors affecting accessibility and utilization of condom in Ethiopia. International conference on AIDS. 2002. Addis Ababa, Ethiopia. [Abstract].

  49. Cherutich P, Brentlinger P, Nduati R, Kiarie MJ, Farquhar C. Condom use among sexually active Kenyan female adolescents at risk for HIV-1 infection. AIDS Behav. 2008;12:923–9.

    PubMed  Google Scholar 

  50. Maharaj P, Cleland J. Condom use within marital and co-habiting partnerships in KwaZulu-Natal-Natal, South Africa. Stud Fam Plan. 2004;35(2):116–24.

    Google Scholar 

  51. Selassie G, Deyessa N, Tesfaye G. Intention to use condom among students in Agena preparatory school, Guraghe Zone, Ethiopia. With the application of health belief model. Arch Public Health. 2013;71:23–31.

    Google Scholar 

  52. Bogale GW, Boer H, Seydel ER. Condom use among low-literate, rural females in Ethiopia: the role of vulnerability to HIV infection, condom attitude, and self-efficacy. AIDS Care. 2010;22(7):851–7.

    CAS  PubMed  Google Scholar 

  53. Warren M, Philpott A. Expanding safer sex options: introducing the female condom into national programs. Reprod Health Matter. 2003;11(21):130–9.

    Google Scholar 

  54. Beyene Y. Potential HIV risk behaviors among Ethiopians and Eritreans in the Diaspora: a bird’s eye-view. Northeast Afr Stud. 2004;9(2):119–42.

    Google Scholar 

  55. Omorodion F, Gbadebo K, Ishak P. HIV vulnerability and sexual risk among African youth in Windsor, Canada. Cult Health Sex. 2007;9(4):429–37.

    PubMed  Google Scholar 

  56. Mulatu MS, Adamu R, Haile SI. Psychosocial and contextual determinants of past and intended condom use among Ethiopian secondary school students. Northeast Afr Stud. 2000;7(1):85–108.

    Google Scholar 

  57. Taffa N, Klepp KI, Bjune G. Psychosocial determinants of sexual activity and condom use intention among youth in Addis Ababa, Ethiopia. Int J STD AIDS. 2002;13(10):714–9.

    CAS  PubMed  Google Scholar 

  58. Bandura A. Health promotion from the perspective of social cognitive theory. Psychol Health. 1998;13(4):623–49.

    Google Scholar 

  59. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31(2):143–64.

    PubMed  Google Scholar 

  60. Casey MK, Timmermann L, Allen M, Krahn S, Turkiewicz KL. Response and self-efficacy of condom use: a meta-analysis of this important element of AIDS education and prevention. South Commun J. 2009;74:57–78.

    Google Scholar 

  61. DiIorio C, Dudley WN, Soet J, Watkins J, Maibach E. A social cognitive-based level model for condom use among college students. Nurs Res. 2000;49(4):208–14.

    Google Scholar 

  62. Sayles JN, Pettifor A, Wong MD, et al. Factors associated with self-efficacy for condom use and sexual negotiation among South African youth. Acquir Immune Defic Syndr. 2006;43(2):226–33.

    Google Scholar 

  63. Coffman DL, Smith EA, Flisher AJ, Caldwell LL. Effects of HealthWise South Africa on condom use self-efficacy. Prev Sci. 2011;12(2):162–72.

    PubMed  PubMed Central  Google Scholar 

  64. Majumdar B, Roberts J. AIDS awareness among women: the benefit of culturally sensitive educational programs. Health Care Women Int. 1998;19:141–53.

    CAS  PubMed  Google Scholar 

  65. Mahat G, Scoloveno MA, Ayres C. HIV/AIDS knowledge and self-efficacy among Nepalese adolescents: a peer education program. Res Theory Nurs Pract Int J. 2011;25(4):271–83.

    Google Scholar 

  66. Sloane BC, Zimmer CG. The power of peer health education. J Am Coll Health. 1993;41:241–5.

    CAS  PubMed  Google Scholar 

  67. Bond KC, Valente TW, Kendall C. Social network influences on reproductive health behaviors in urban northern Thailand. Soc Sci Med. 1999;49:1599–614.

    CAS  PubMed  Google Scholar 

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Acknowledgments

I would also like to express my special thanks and gratitude to study participants who willingly shared their experiences. I am thankful to the College of Health Sciences, University of Texas at El Paso, for funding the study.

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Authors and Affiliations

  1. Department of Public Health, Keimyung University, 1095 Dalgubeol-Daero, Dalseo-Gu, Daegu, 704-701, South Korea

    Nasser B. Ebrahim

  2. College of Health Sciences and School of Nursing, University of Texas at El Paso, El Paso, TX, 79968, USA

    Sharon Davis

  3. College of Health and Social Services, New Mexico State University, HSS Annex, Room 211, PO Box 30001, Las Cruces, NM, 88003-8001, USA

    Joe Tomaka

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  1. Nasser B. Ebrahim
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Correspondence to Nasser B. Ebrahim.

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Ebrahim, N.B., Davis, S. & Tomaka, J. Correlates of Condom Use Among Somali and Ethiopian Immigrants in the U.S.. J Immigrant Minority Health 18, 1139–1147 (2016). https://doi.org/10.1007/s10903-015-0244-7

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