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Assessing Spatial Relationships between Race, Inequality, Crime, and Gonorrhea and Chlamydia in the United States

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Abstract

Incidence rates of chlamydia and gonorrhea reached unprecedented levels in 2015 and are concentrated in southern counties of the USA. Using incidence data from the Center for Disease Control, Moran’s I analyses assessed the data for statistically significant clusters of chlamydia and gonorrhea at the county level in 46 states of the USA. Lagrange multiplier diagnostics justified selection of the spatial Durbin regression model for chlamydia and the spatial error model for gonorrhea. Rates of chlamydia (Moran’s I = .37, p < .001) and gonorrhea (Moran’s I = .38, p < .001) were highly clustered particularly in the southern region of the USA. Logged percent in poverty (B = .49, p < .001 and B = .48, p < .001) and racial composition of African-Americans (B = .16, p < .001 and B = .40, p < .001); Native Americans (B = .12, p < .001 and B = .20, p < .001); and Asians (B = .14, p < .001 and B = .09, p < .001) were significantly associated with greater rates of chlamydia and gonorrhea, respectively, after accounting for spatial dependence in the data. Logged rates of rates violent crimes were associated with chlamydia (B = .053, p < .001) and gonorrhea (B = .10, p < .001). Logged rates of drug crimes (.052, p < .001) were only associated with chlamydia. Metropolitan census designation was associated with logged rates of chlamydia (B = .12, p < .001) and gonorrhea (B = .24, p < .001). Spatial heterogeneity in the distribution of rates of chlamydia and gonorrhea provide important insights for strategic public health interventions in the USA and inform the allocation of limited resources for the prevention of chlamydia and gonorrhea.

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References

  1. Chesson H. The expected lifetime cost of chlamydia and gonorrhea per infant born in the United States. In 2016 National STD Prevention Conference. CDC. 2016. Atlanta, GA.

  2. Centers for Disease Control. Incidence prevalence and cost of sexually transmitted infections in the United States. 2013. Atlanta, GA.

  3. Center for Disease Control. Sexually transmitted diseases surveillance. 2016a Atlanta, GA.

  4. Owusu-Edusei K Jr, Chesson HW, Gift TL, Tao G, Mahajan R, Ocfemia MCB, et al. The estimated direct medical cost of selected sexually transmitted infections in the United States, 2008. Sex Transm dis. 2013;40(3):197–201.

  5. Center for Disease Control. CDC fact sheet: reported STDs in the United States: 2015 national data for chlamydia, gonorrhea and syphilis. 2016b. Retrieved 10/2/2016 from https://www.cdc.gov/nchhstp/newsroom/docs/factsheets/std-trends-508.pdf.

  6. Adimora AA, Ramirez C, Schoenbach VJ, Cohen MS. Policies and politics that promote HIV infection in the southern United States. AIDS (London, England). 2014;28(10):1393.

    Article  Google Scholar 

  7. Aral SO, O'leary A, Baker C. Sexually transmitted infections and HIV in the southern United States: an overview. Sex Transm dis. 2006;33(7):S1–5.

    Article  PubMed  Google Scholar 

  8. Farley TA. Sexually transmitted diseases in the southeastern United States: location, race, and social context. Sex Transm dis. 2006;33(7):S58–64.

    Article  PubMed  Google Scholar 

  9. Reif S, et al.. “HIV/AIDS epidemic in the South reaches crisis proportions in last decade.” Duke Center for Health Policy and Inequalities Research. 2011. Retrieved 10/2/2016 from: http://chpir.org/wpcontent/uploads/2012/11/HIVAIDS-Epidemic-in-the-South-Reaches-Crisis-Proportions-in-Last-Decade.pdf.

  10. Thomas JC, Kulik AL, Schoenbach VJ. Syphilis in the south: rural rates surpass urban rates in North Carolina. Am J Public Health. 1995;85(8_Pt_1):1119–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Reif SS, Whetten K, Wilson ER, McAllaster C, Pence BW, Legrand S, et al. HIV/AIDS in the southern USA: a disproportionate epidemic. AIDS Care. 2014;26(3):351–9.

  12. Jennings JM, Curriero FC, Celentano D, Ellen JM. Geographic identification of high gonorrhea transmission areas in Baltimore, Maryland. Am J Epidemiol. 2005;161(1):73–80.

    Article  PubMed  Google Scholar 

  13. Hoover KW, Tao G, Nye MB, Body BA. Suboptimal adherence to repeat testing recommendations for men and women with positive chlamydia tests in the United States, 2008–2010. Clin Infect dis. 2013;56(1):51–7.

    Article  PubMed  Google Scholar 

  14. Becker KM, Glass GE, Brathwaite W, Zenilman JM. Geographic epidemiology of gonorrhea in Baltimore, Maryland, using a geographic information system. Am J Epidemiol. 1998;147(7):709–16.

    Article  CAS  PubMed  Google Scholar 

  15. Bernstein KT, Curriero FC, Jennings JM, Olthoff G, Erbelding EJ, Zenilman J. Defining core gonorrhea transmission utilizing spatial data. Am J Epidemiol. 2004;160(1):51–8.

    Article  PubMed  Google Scholar 

  16. Hardwick D, Patychuk D. Geographic mapping demonstrates the association between social inequality, teen births and STDs among youth. Can J hum Sex. 1999;8(2):77.

    Google Scholar 

  17. Marotta P. Assessing spatial relationships between rates of crime and rates of gonorrhea and chlamydia in Chicago. J Urban Health. 2012;2016:1–13.

    Google Scholar 

  18. Mayer JD. Geography, ecology and emerging infectious diseases. Soc Sci Med. 2000;50(7):937–52.

    Article  CAS  PubMed  Google Scholar 

  19. Owusu-Edusei K Jr, Chesson HW. Using spatial regression methods to examine the association between county-level racial/ethnic composition and reported cases of chlamydia and gonorrhea: an illustration with data from the state of Texas. Sex Transm Dis. 2009;36(10):657–64.

    Article  PubMed  Google Scholar 

  20. Holtgrave DR, Crosby RA. Social capital, poverty, and income inequality as predictors of gonorrhoea, syphilis, chlamydia and AIDS case rates in the United States. Sex Transm Infect. 2003;79(1):62–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kposowa AJ. Relative deprivation, sexually transmitted diseases and HIV and AIDS mortality: a multilevel analysis. Am J Infect Dis Microbiol. 2014;2(3):55–62.

    Google Scholar 

  22. Morenoff JD, Sampson RJ, Raudenbush SW. Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology. 2001;39(3):517–58.

    Article  Google Scholar 

  23. Sampson RJ, Groves WB. Community structure and crime: testing social-disorganization theory. Am J Sociol. 1989:774–802.

  24. Biello KB, Niccolai L, Kershaw TS, Lin H, Ickovics J. Residential racial segregation and racial differences in sexual behaviours: an 11-year longitudinal study of sexual risk of adolescents transitioning to adulthood. J Epidemiol Community Health. 2013;67(1):28–34.

    Article  PubMed  Google Scholar 

  25. Biello KB, Kershaw T, Nelson R, Hogben M, Ickovics J, Niccolai L. Racial residential segregation and rates of gonorrhea in the United States, 2003–2007. Am J Public Health. 2012;102(7):1370–7.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Datta SD, Sternberg M, Johnson RE, Berman S, Papp JR, McQuillan G, et al. Gonorrhea and chlamydia in the United States among persons 14 to 39 years of age, 1999 to 2002. Ann Intern Med. 2007;147(2):89–96.

  27. Henderson L. Racial isolation and chlamydia rates in US counties. Race Soc Probl. 2015;7(2):111–22.

    Article  Google Scholar 

  28. Pugsley RA, Chapman DA, Kennedy MG, Liu H, Lapane KL. Residential segregation and gonorrhea rates in US metropolitan statistical areas, 2005–2009. Sex Transm Dis. 2013;40(6):439–43.

    Article  PubMed  Google Scholar 

  29. Census Bureau 2010. Retrieved on 10/1/2016 Retrieved from https://www.census.gov/prod/cen2010/briefs/c2010br-06.pdf.

  30. Walker FJ, Llata E, Doshani M, Taylor MM, Bertolli J, Weinstock HS, et al. HIV, chlamydia, gonorrhea, and primary and secondary syphilis among American Indians and Alaska Natives within Indian Health Service areas in the United States, 2007–2010. J Community Health. 2015;40(3):484–92.

  31. Center for Disease Control. Indian health surveillance report: sexually transmitted diseases, 2011. 2012. Retrieved 10/2/2016 https://www.cdc.gov/std/stats/ihs/ihs-surv-report-2011_062314.pdf.

  32. Patterson-Lomba O, Goldstein E, Gómez-Liévano A, Castillo-Chavez C, Towers S. Per capita incidence of sexually transmitted infections increases systematically with urban population size: a cross-sectional study. Sex Transm Infect. 2015;91(8):610–4.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Cattley C, Massari P, Genco CA. Incidence of gonorrhea and chlamydia in urban settings: the case for neighborhood level analysis in Boston. Adv Infect Dis. 2015;5(04):162.

    Article  Google Scholar 

  34. Sampson RJ, Raudenbush SW, Earls F. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science. 1997;277(5328):918–24.

    Article  CAS  PubMed  Google Scholar 

  35. Sampson RJ, Raudenbush SW. Seeing disorder: neighborhood stigma and the social construction of Bbroken windows^. Soc Psychol Q. 2004;67(4):319–42.

    Article  Google Scholar 

  36. Chesson HW, Owusu-Edusei K, Leichliter JS, Aral SO. Violent crime rates as a proxy for the social determinants of sexually transmissible infection rates: the consistent statelevel correlation between violent crime and reported sexually transmissible infections in the United States, 1981–2010. Sex Health. 2013;10(5):419–23.

    Article  PubMed  Google Scholar 

  37. Jennings JM, Taylor RB, Salhi RA, Furr-Holden CDM, Ellen JM. Neighborhood drug markets: a risk environment for bacterial sexually transmitted infections among urban youth. Soc Sci Med. 2012;74(8):1240–50.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jennings JM, Woods SE, Curriero FC. The spatial and temporal association of neighborhood drug markets and rates of sexually transmitted infections in an urban setting. Health Place. 2013;23:128–37.

    Article  PubMed  Google Scholar 

  39. Porter KA, Thomas JC, Emch ME. Variations in the effect of incarceration on community gonorrhea rates, Guilford County, North Carolina, 2005–2006. Int J STD AIDS. 2010;21(1):34–8.

    Article  CAS  PubMed  Google Scholar 

  40. Stoltey JE, Li Y, Bernstein KT, Philip SS. Ecological analysis examining the association between census tract-level incarceration and reported chlamydia incidence among female adolescents and young adults in San Francisco. Sex Transm Infect. 2015;91(5):370–4.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Thomas JC, Sampson LA. High rates of incarceration as a social force associated with community rates of sexually transmitted infection. J Infect Dis. 2005;191(Supplement 1):S55–60.

    Article  PubMed  Google Scholar 

  42. Dauria EF, Elifson K, Arriola KJ, Wingood G, Cooper HL. Male incarceration rates and rates of sexually transmitted infections: results from a longitudinal analysis in a southeastern US City. Sex Transm Dis. 2015;42(6):324.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Clear TR. Imprisoning communities: how mass incarceration makes disadvantaged neighborhoods worse. Oxford, United Kingdom.: Oxford University Press; 2009.

  44. Thomas JC, Clark M, Robinson J, Monnett M, Kilmarx PH, Peterman TA. The social ecology of syphilis. Soc Sci Med. 1999;48(8):1081–94.

    Article  CAS  PubMed  Google Scholar 

  45. Hogben M, Leichliter JS. Social determinants and sexually transmitted disease disparities. Sex Transm Dis. 2008;35(12):S13–8.

    Article  PubMed  Google Scholar 

  46. Semaan S, Sternberg M, Zaidi A, Aral SO. Social capital and rates of gonorrhea and syphilis in the United States: spatial regression analyses of state-level associations. Soc Sci Med. 2007;64(11):2324–41.

    Article  PubMed  Google Scholar 

  47. Sullivan AB, Gesink DC, Brown P, Zhou L, Kaufman JS, Fitch M, et al. Are neighborhood sociocultural factors influencing the spatial pattern of gonorrhea in North Carolina? Ann Epidemiol. 2011;21(4):245–52.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Ellen JM, Jennings JM, Meyers T, Chung SE, Taylor R. Perceived social cohesion and prevalence of sexually transmitted diseases. Sex Transm Dis. 2004;31(2):117–22.

    Article  PubMed  Google Scholar 

  49. Baral S, Logie CH, Grosso A, Wirtz AL, Beyrer C. Modified social ecological model: a tool to guide the assessment of the risks and risk contexts of HIV epidemics. BMC Public Health. 2013;13(1):1.

    Article  Google Scholar 

  50. DiClemente RJ, Salazar LF, Crosby RA, Rosenthal SL. Prevention and control of sexually transmitted infections among adolescents: the importance of a socio-ecological perspective—a commentary. Public Health. 2005;119(9):825–36.

    Article  CAS  PubMed  Google Scholar 

  51. Mayer K, Pizer HF, Venkatesh KK. The social ecology of HIV/AIDS. Med Clin N Am. 2008;92(6):1363–75.

    Article  PubMed  Google Scholar 

  52. National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Centers for Disease Control and Prevention. Atlas Database, 2016 Retrieved on 10/1/2016 from: https://www.cdc.gov/nchhstp/atlas/.

  53. United States Department of Justice. Federal Bureau of Investigation. Uniform crime reporting program data: offenses known and clearances by arrest, 2014. ICPSR36391-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [Dataset] retrieved on 10/1/2016 from: https://doi.org/10.3886/ICPSR36391.v1.

  54. Census Bureau, American Community Survey. 2015. Technical Documentation Retrieved 10/1/2016 from https://www.census.gov/programs-surveys/acs/.

  55. United States Department of Agriculture Economic Research Service. Rural-urban influence codes, documentation 2013. Retrieved on 10/1/2016 from: https://www.ers.usda.gov/data-products/urban-influence-codes/.

  56. Open Source Geospatial Foundation Project. Quantum Geographic Information System. 2013. Retrieved10/2/2016 from http://www.qgis.org/en/site/.

  57. Moran PA. Notes on continuous stochastic phenomena. Biometrika. 1950;37(1/2):17–23.

    Article  CAS  PubMed  Google Scholar 

  58. Li H, Calder CA, Cressie N. Beyond Moran’s I: testing for spatial dependence based on the spatial autoregressive model. Geogr Anal. 2007;39(4):357–75.

    Article  Google Scholar 

  59. Waldhör T. The spatial autocorrelation coefficient Moran’s I under heteroscedasticity. Stat Med. 1996;15(7–9):887–92.

    Article  PubMed  Google Scholar 

  60. Tiefelsdorf M. Modelling spatial processes: the identification and analysis of spatial relationships in regression residuals by means of Moran’s I (Vol. 87). New York, NY: Springer; 2006.

  61. Anselin L, Syabri I, Kho Y. Geo Da: an introduction to spatial data analysis. Geogr Anal. 2006;38(1):5–22.

    Article  Google Scholar 

  62. Bivand R, Spatial dependence: weighting schemes, statistics and models 2016. Retrieved on 10/1/2016 from https://rdrr.io/rforge/spdep/.

  63. The Census Bureau. Census regions and divisions of the United States. 2016. Retrieved from 10/2/2016 from: https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf.

  64. Benoit K. Linear regression models with logarithmic transformations. London: London School of Economics; 2011. London, United Kingdom

    Google Scholar 

  65. Christensen R. Log-linear models and logistic regression. New York, NY: Springer Science & Business Media; 2006.

  66. Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001;20(4):461–94.

    Article  CAS  PubMed  Google Scholar 

  67. Anselin L, Bera AK. Spatial dependence in linear regression models with an introduction to spatial econometrics. Stat Textbooks Monogr. 1998;155:237–90.

    Google Scholar 

  68. Anselin L. Spatial econometrics: methods and models (Vol. 4). New York, NY. Springer Science & Business Media.

  69. Roger S, Bivand RS, & Pebesma EJ. Applied spatial data analysis with R 2013.

  70. Ward MD, & Gleditsch KS. Spatial regression models (Vol. 155). Thousand Oaks, CA. 2008.

  71. Elhorst JP. Specification and estimation of spatial panel data models. Int Reg Sci Rev. 2003;26(3):244–68.

    Article  Google Scholar 

  72. Lee LF, Yu J. Identification of spatial Durbin panelmodels. J Appl Econ. 2016;31(1):133–62.

    Article  Google Scholar 

  73. Strathdee SA, Beletsky L, Kerr T. HIV, drugs and the legal environment. Int J Drug Policy. 2015;26:S27–32.

    Article  PubMed  Google Scholar 

  74. Riley ED, Gandhi M, Bradley Hare C, Cohen J, Hwang SW. Poverty, unstable housing, and HIV infection among women living in the United States. Curr HIV/AIDS Rep. 2007;4(4):181–6.

    Article  PubMed  Google Scholar 

  75. Gee GC, Ford CL. Structural racism and health inequities. Du Bois Rev: Soc Sci Res Race. 2011;8(01):115–32.

    Article  Google Scholar 

  76. Marmot M. Social determinants of health inequalities. Lancet. 2005;365(9464):1099–104.

    Article  PubMed  Google Scholar 

  77. Sanders RA, Ellen JM. Structural interventions with an emphasis on poverty and racism. In African Americans and HIV/AIDS. New York: Springer; 2010. p. 255–70.

    Google Scholar 

  78. Berry SA, Ghanem KG, Mathews WC, Korthuis PT, Yehia BR, Agwu AL, et al. Gonorrhea and chlamydia testing increasing but still lagging in HIV clinics in the United States. J Acquir Immune Defic Syndr 2015. 1999;70(3):–275.

  79. Leichliter JS, Seiler N, Wohlfeiler D. Sexually transmitted disease prevention policies in the United States: evidence and opportunities. Sex Transm dis. 2016;43(2S):S113–21.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Dolan K, Wirtz AL, Moazen B, Ndeffo-mbah M, Galvani A, Kinner SA, et al. Global burden of HIV, viral hepatitis, and tuberculosis in prisoners and detainees. Lancet. 2016;388(10049):1089–102.

    Article  PubMed  Google Scholar 

  81. Nijhawan AE. Infectious diseases and the criminal justice system. Am J Med Sci. 2016;352(4):399–407.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Freudenberg N, Heller D. A review of opportunities to improve the health of people involved in the criminal justice system in the United States. Annu rev Public Health. 2016;37:313–33.

    Article  PubMed  Google Scholar 

  83. Jürgens R, Csete J, Amon JJ, Baral S, Beyrer C. People who use drugs, HIV, and human rights. Lancet. 2010;376(9739):475–85.

    Article  PubMed  Google Scholar 

  84. El-Bassel N, Gilbert Goddard-Eckrich D, Chang M, Wu E, Hunt T, Witte S. Efficacy of a group-based multimedia HIV prevention intervention for drug-involved women under community supervision: Project WORTH. PLoS One. 2014;9(11):e111528.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The author gratefully acknowledges methodological and statistical support provided by Jeremy Porter, PhD at the Graduate Center, City University of New York (CUNY). Funding provided by the National Institute on Drug Abuse (1T32DA037801) supported the writing of this manuscript.

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Marotta, P. Assessing Spatial Relationships between Race, Inequality, Crime, and Gonorrhea and Chlamydia in the United States. J Urban Health 94, 683–698 (2017). https://doi.org/10.1007/s11524-017-0179-5

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