Abstract
Surveillance studies monitor the prevalence and incidence of HIV, and this information is used by policy makers to design prevention programs and facilitate care for people living with HIV (PLWHIV). Although most of these studies monitor the presence of PLWHIV in the general population or specific communities, some assess the presence of PLWHIV in organizations. One type of organization that has not been examined, yet could potentially play a large role in caring for PLWHIV, is the religious congregation. In this study, we estimate the proportion of US religious congregations that have PLWHIV and examine whether congregations that are in contact with populations with high HIV prevalence and incidence rates are more likely to have PLWHIV using data from a nationally representative sample of congregations and the 2000 Census. Over 10,000 congregations have PLWHIV, and congregations containing, open to, or located in areas with populations with high HIV prevalence and incidence rates are more likely to have them. This study offers new insight into the presence of HIV in the United States and provides information about which congregations may be amenable to serving as sites of HIV programs.
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Notes
This strategy exploits the insight that the organizational affiliations of a representative sample of people constitute a representative sample of organizations (McPherson 1982). Thus, one can develop a nationally representative sample of US congregations from a nationally representative sample of Americans.
Key informant reports are widely used in organizational research as a way to obtain accurate information about the features of organizations (cf. Frenk et al. forthcoming; Marsden and Rohrer 2001; McPherson and Rotolo 1995).
The question is, “Is there anyone in your congregation who has publicly acknowledged his or her infection with the virus that causes AIDS? That is, is there anyone who is openly HIV-positive?”
Chaves and Anderson (2009) provide an example to help explain this issue, “Suppose that the universe contains only two congregations, one with 1,000 regular attenders and the other with 100 regular attenders. Suppose further that the 1,000-person congregation supports a food pantry and the 100-person congregation does not. We can express this reality in one of two ways. We can say that 91 percent of the people are in a congregation that supports a food pantry (1,000/1,100), or we can say that 50 percent of the congregations support a food pantry (1/2). Both of these are meaningful numbers. Ignoring the over-representation of larger congregations, a percentage or mean from the NCS is analogous to the 91 percent in this example. Weighted inversely proportional to congregational size, a percentage or mean is analogous to the 50 percent in this example. The first number views congregations from the perspective of the average attender, which gives greater weight to congregations with more people in them; the second number views them from the perspective of the average congregation, ignoring size differences.”
Because we collected congregations’ addresses, we were able to attach data from the 2000 Census Summary File 3 to the NCS data file. Based on previous research examining the level of measurement to use when assessing health variables, we attach block group level data (Krieger et al. 2002).
Because of the small proportion of congregations that have PLWHIV, we run a sensitivity analysis using the RELOGIT program in STATA to assess the robustness of the coefficients produced in the regression model (King and Zeng 1999a; King and Zeng 1999b; Tomz et al. 1999). The model produced by RELOGIT does not vary significantly from the model that appears in the paper.
References
Bozzette, S. A., Berry, S. H., Duan, N., Frankel, M. R., Leibowitz, A. A., Lefkowitz, D., et al. (1998). The care of HIV-infected adults in the United States. New England Journal of Medicine, 339(26), 1897–1904.
Buehler, J. W. (2008). Surveillance. In K. J. Rothman, S. Greenland, & T. L. Lash (Eds.), Modern epidemiology (3rd ed., pp. 459–480). Philadelphia, PA: Lippincott Williams and Wilkins.
US Census Bureau (2002). Census 2000 Summary File 3—United States [Data file].
Campbell, M. K., Hudson, M. A., Resnicow, K., Blakeney, N., Paxton, A., & Baskin, M. (2007). Church-based health promotion interventions: evidence and lessons learned. Annual Review of Public Health, 28, 213–234.
Carlin, J. B., Galati, J. C., & Royston, P. (2008). A new framework for managing and analyzing multiply imputed data in Stata. Stata Journal, 8(1), 49–67.
Centers for Disease Control and Prevention. (2008). HIV prevalence estimates—United States, 2006. Morbidity and Mortality Weekly Report, 57(39), 1073–1076.
Centers for Disease Control and Prevention. (2009). HIV/AIDS surveillance report, 2007, 19 Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention; Retrieved from http://www.cdc.gov/hiv/topics/surveillance/resources/reports/.
Chaves, M. (2004). Congregations in America. Cambridge: Harvard University Press.
Chaves, M., & Anderson, S. L. (2008). Continuity and change in American congregations: introducing the second wave of the National Congregations Study. Sociology of Religion, 69(4), 415–440.
Chaves, M., & Anderson, S. L. (2009). National Congregations Study cumulative codebook for waves I and II (1998 and 2006–2007). Durham: Duke University, Sociology Department.
Chaves, M., & Tsitsos, W. (2001). Congregations and social services: what they do, how they do it, and with whom. Nonprofit and Voluntary Sector Quarterly, 30(4), 660–683.
Davis, J. A., Smith, T. W., & Marsden, P. V. (2007). General Social Surveys, 1972–2006: cumulative codebook. Chicago: National Opinion Research Center.
Dean, H. D., Lansky, A., & Fleming, P. L. (2002). HIV surveillance methods for the incarcerated population. AIDS Education and Prevention, 14(5), 65–74.
DeHaven, M. J., Hunter, I. B., Wilder, L., Walton, J. W., & Berry, J. (2004). Health programs in faith-based organizations: are they effective? American Journal of Public Health, 94(6), 1030–1036.
Frenk, S. M., Anderson, S. L., Chaves, M., & Martin, N. (forthcoming). Assessing the validity of key informant reports about congregants’ demographic characteristics. Sociology of Religion.
Hadaway, C. K., & Marler, P. L. (2005). How many Americans attend worship each week? An alternative approach to measurement. Journal for the Scientific Study of Religion, 44(3), 307–322.
Hall, H. I., Song, R., Rhodes, P., Prejean, J., An, Q., Lee, L. M., et al. (2008). Estimation of HIV incidence in the United States. Journal of the American Medical Association, 300(5), 520–529.
Herek, G. M., & Capitanio, J. P. (1999). AIDS stigma and contact with persons with AIDS: effects of direct and vicarious contact. Journal of Applied Social Psychology, 27(1), 1–36.
Hernández, E. I., Burwell, R., & Smith, J. (2007). Answering the call: how Latino churches can respond to the HIV/AIDS epidemic. Notre Dame: University of Notre Dame, Institute for Latino Studies.
Hicks, K. E., Allen, J. A., & Wright, E. M. (2005). Building holistic HIV/AIDS responses in African American urban faith communities: a qualitative, multiple case study analysis. Family & Community Health, 28(2), 184–205.
Kaiser Commission on Medicaid and the Uninsured/Urban Institute. (2007). Health insurance coverage in the US, 2006. The Henry J. Kaiser Family Foundation. Retrieved from http://facts.kff.org/chart.aspx?ch=477. 2007.
Kennedy, P. (2008). A guide to econometrics (6th ed.). Malden, MA: Blackwell.
King, G., & Zeng, L. (1999a). Logistic regression in rare events data. Cambridge, MA: Harvard University, Department of Government. Retrieved from http://GKing.Harvard.Edu.
King, G., & Zeng, L. (1999b). Estimating absolute, relative, and attributable risks in case-control studies. Cambridge, MA: Harvard University, Department of Government. Retrieved from http://GKing.Harvard.Edu.
Krieger, N., Chen, J. T., Waterman, P. D., Soobader, M., Subramanian, S. V., & Carson, R. (2002). Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter? The Public Health Disparities Geocoding Project. American Journal of Epidemiology, 156(5), 471–482.
Latkin, C. A., Tobin, K. E., & Gilbert, S. H. (2002). Shun or support: the role of religious behaviors and HIV-related health care among drug users in Baltimore, Maryland. AIDS and Behavior, 6(4), 321–329.
Marsden, P. V., & Rohrer, L. H. (2001). Organizational and informant differences in the reliability of survey reports on organization size and age. Paper presented at the American Sociological Association meetings. Los Angeles, CA.
McBridge, D. C., McCoy, C. B., Chitwood, D. D., Inciardi, J. A., Hernandez, E. L., & Mutch, P. M. (1994). Religious institutions as sources of AIDS information for street injection drug users. Review of Religious Research, 35(4), 324–334.
McGrew, C. A., Dick, R. W., Schniedwind, K., & Kikas, P. (1993). Survey of NCAA institutions concerning HIV/AIDS policies and universal precautions. Medicine and Science in Sports and Exercise, 25(8), 917–921.
McPherson, J. M. (1982). Hypernetwork sampling: duality and differentiation among voluntary organizations. Social Networks, 3(4), 225–249.
McPherson, J. M., & Rotolo, T. (1995). Measuring the composition of voluntary groups—a multitrait-multimethod analysis. Social Forces, 73(3), 1097–1115.
McRoberts, O. (2003). Streets of glory: church and community in a black urban neighborhood. Chicago: University of Chicago Press.
Moore, R. D., & Chaisson, R. E. (1999). Natural history of HIV infection in the era of combination antiretroviral therapy. AIDS, 13(14), 1933–1942.
Palella, F. J., Delaney, K. M., Moorman, A. C., Loveless, M. O., Fuhrer, J., Satten, G. A., et al. (1998). Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. New England Journal of Medicine, 338(13), 853–860.
Royston, P. (2007). Multiple imputation of missing values: further update of ice, with an emphasis on interval censoring. Stata Journal, 7(4), 445–464.
StataCorp. (2007). Stata Statistical Software: Release 10. College Station, TX: StataCorp LP.
Tomz, M., King, G., & Zeng, L. (1999). RELOGIT: rare events logistic regression, Version 1.1. Cambridge, MA: Harvard University. Retrieved from http://gking.harvard.edu/.
Trinitapoli, J., Ellison, C. G., & Boardman, J. D. (2009). US religious congregations and the sponsorship of health-related programs. Social Science & Medicine, 68(12), 2231–2239.
Trubo, R. (2004). CDC initiative targets HIV research gaps in black and Hispanic communities. Journal of the American Medical Association, 292(21), 2563–2564.
Visser, M. J., Makin, J. D., & Lehobye, K. (2006). Stigmatizing attitudes of the community towards people living with HIV/AIDS. Journal of Community & Applied Social Psychology, 16(1), 42–58.
Winship, C., & Radbill, L. (1994). Sampling weights and regression analysis. Sociological Methods & Research, 23(2), 230–257.
Acknowledgement
The project was funded by a grant from the National Science Foundation (#0452269) as well as grants from the Lilly Endowment, Inc. (2006-1675-000), the Kellogg Foundation (P0118042), and the Louisville Institute (2005105). These grants supported the collection, management, analysis, and interpretation of the data. Data collection was handled by the National Opinion Research Center at the University of Chicago, and the data were cleaned at Duke University, Durham, NC. The authors would like to thank Kim Blankenship, Brad Fulton, and Steven Foy for their helpful comments on earlier versions of the manuscript.
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Data for this paper are drawn from the second wave of the National Congregations Study.
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Frenk, S.M., Chaves, M. Proportion of US Congregations that have People Living with HIV. J Relig Health 51, 371–380 (2012). https://doi.org/10.1007/s10943-010-9379-y
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DOI: https://doi.org/10.1007/s10943-010-9379-y