The Journal of Primary Prevention

, Volume 37, Issue 3, pp 215–230 | Cite as

Community Characteristics Associated With Seeking Medical Evaluation for Suspected Child Sexual Abuse in Greater Houston

  • Christopher Spencer Greeley
  • Ching-Yi Chuo
  • Min Ji Kwak
  • Sally S. Henin
  • Marcella Donnaruma-Kwoh
  • Jamie Ferrell
  • Angelo Peter Giardino
Original Paper


Child sexual abuse (CSA) affects over 62,000 children annually in the United States. A primary obstacle to the success of a public health prevention strategy is the lack of knowledge around community level risk factors for CSA. We evaluated community level characteristics for children seeking care for suspected CSA in the Greater Houston area for 2009. There was a total incidence rate of medical evaluations for suspected CSA of 5.9/1000 children. We abstracted the medical charts of 1982 (86 %) children who sought a medical evaluation for suspected CSA at three main medical systems in the Greater Houston area for 2009. We evaluated 18 community level variables from the American Community Survey for the 396 zip codes these children lived in. The mean number of cases per Greater Houston zip code was 2.77 (range 0–27), with 62 % of zip codes not having a case at any of the three sites surveyed. Zip codes with a higher than Houston average rate of vacant houses, never married females and unemployed labor force with high family poverty rate, were associated with an increased rate of children seeking care for suspected CSA. We demonstrated zip codes level characteristics which were associated with an increased rate of children seeking care for suspected CSA. Our modelling process and our data have implications for community based strategies aimed at improved surveillance or prevention of CSA. The process of identifying locally specific community level factors suggests target areas which have particular socioeconomic characteristics which are associated with increased rate of seeking CSA evaluations.


Child abuse Sexual Primary prevention Geographic mapping 



Dr. Greeley is supported by Award Number K23HD065872 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development or the National Institutes of Health.

Compliance With Ethical Standards

Conflict of Interest

The authors have no conflicts of interest to declare.

Supplementary material

10935_2016_416_MOESM1_ESM.pdf (99 kb)
Supplementary material 1 (PDF 98 kb)


  1. American Community Survey (ACS). (2010). ACS 1-year estimates. Accessed 22 September 2013.
  2. Administration for Children and Families, Administration on Children, Youth and Families, Children’s Bureau. (2012). Child maltreatment 2012. Washington, DC: U.S. Department of Health and Human Services.Google Scholar
  3. Appleyard, K., Berlin, L. J., Rosanbalm, K. D., & Dodge, K. A. (2011). Preventing early child maltreatment: Implications from a longitudinal study of maternal abuse history, substance use problems, and offspring victimization. Prevention Science, 12(2), 139–149. doi: 10.1007/s11121-010-0193-2.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Bursik, R. J, Jr, & Webb, J. (1982). Community change and patterns of delinquency. American Journal of Sociology, 88(1), 24–42. doi: 10.2307/2779402.CrossRefGoogle Scholar
  5. Coulton, C. J., Crampton, D. S., Irwin, M., Spilsbury, J. C., & Korbin, J. E. (2007). How neighborhoods influence child maltreatment: A review of the literature and alternative pathways. Child Abuse and Neglect, 31(11–12), 1117–1142. doi: 10.1016/j.chiabu.2007.03.023.CrossRefPubMedGoogle Scholar
  6. Coulton, C. J., Korbin, J. E., & Su, M. (1999). Neighborhoods and child maltreatment: A multi-level study. Child Abuse and Neglect, 23(11), 1019–1040.CrossRefPubMedGoogle Scholar
  7. Dalziel, K., & Segal, L. (2012). Home visiting programmes for the prevention of child maltreatment: Cost-effectiveness of 33 programmes. Archives of Disease in Childhood, 97(9), 787–798. doi: 10.1136/archdischild-2011-300795.CrossRefPubMedGoogle Scholar
  8. Dubowitz, H., Lane, W. G., Semiatin, J. N., Magder, L. S., Venepally, M., & Jans, M. (2011). The safe environment for every kid model: Impact on pediatric primary care professionals. Pediatrics, 127(4), e962–e970. doi: 10.1542/peds.2010-1845.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Finkelhor, D. (2009). The prevention of childhood sexual abuse. The Future of Children, 19(2), 169–194. doi: 10.2307/27795052.CrossRefPubMedGoogle Scholar
  10. Freisthler, B., Gruenewald, P. J., Remer, L. G., Lery, B., & Needell, B. (2007). Exploring the spatial dynamics of alcohol outlets and child protective services referrals, substantiations, and foster care entries. [Research Support, N.I.H., Extramural]. Child Maltreatment, 12(2), 114–124. doi: 10.1177/1077559507300107.CrossRefPubMedGoogle Scholar
  11. Garbarino, J., & Sherman, D. (1980). High risk neighborhoods and high risk families: The human ecology of child maltreatment. Child Development, 51(1), 188–198.CrossRefPubMedGoogle Scholar
  12. Kenny, M. C., & Wurtele, S. K. (2012). Preventing childhood sexual abuse: An ecological approach. [Introductory]. Journal of Child Sexual Abuse, 21(4), 361–367. doi: 10.1080/10538712.2012.675567.CrossRefPubMedGoogle Scholar
  13. King, G. (2013). A solution to the ecological inference problem: Reconstructing individual behavior from aggregate data. Princeton: Princeton University Press.Google Scholar
  14. Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics-Theory and methods, 26(6), 1481–1496.CrossRefGoogle Scholar
  15. Lery, B. (2009). Neighborhood structure and foster care entry risk: The role of spatial scale in defining neighborhoods. Children and Youth Services Review, 31(3), 331–337. doi: 10.1016/j.childyouth.2008.08.001.CrossRefGoogle Scholar
  16. Mikton, C., & Butchart, A. (2009). Child maltreatment prevention: A systematic review of reviews. Bulletin of the World Health Organization, 87(5), 353–361. doi: 10.2471/blt.08.057075.CrossRefPubMedPubMedCentralGoogle Scholar
  17. Moyer, V. A. (2013). Primary care interventions to prevent child maltreatment: U.S. Preventive Services Task Force recommendation statement. [Practice Guideline, Research Support, U.S. Gov’t, P.H.S.]. Annals of Internal Medicine, 159(4), 289–295. doi: 10.7326/0003-4819-159-4-201308200-00667.CrossRefPubMedGoogle Scholar
  18. Mustaine, E. E., Tewksbury, R., Corzine, J., & Huff-Corzine, L. (2014a). Differentiating single and multiple victim child sexual abuse cases: A research note considering social disorganization theory. Journal of Child Sexual Abuse, 23(1), 38–54. doi: 10.1080/10538712.2014.863260.CrossRefPubMedGoogle Scholar
  19. Mustaine, E. E., Tewksbury, R., Huff-Corzine, L., Corzine, J., & Marshall, H. (2014b). Community characteristics and child sexual assault: Social disorganization and age. Journal of Criminal Justice, 42(2), 173–183. doi: 10.1016/j.jcrimjus.2013.06.016.CrossRefGoogle Scholar
  20. Nelson, G., & Caplan, R. (2014). The prevention of child physical abuse and neglect: An update. Journal of Applied Research on Children, 5(1), 1–49.Google Scholar
  21. Pereda, N., Guilera, G., Forns, M., & Gomez-Benito, J. (2009). The prevalence of child sexual abuse in community and student samples: A meta-analysis. [Meta-Analysis]. Clinical Psychology Review, 29(4), 328–338. doi: 10.1016/j.cpr.2009.02.007.CrossRefPubMedGoogle Scholar
  22. Prinz, R. J., Sanders, M. R., Shapiro, C. J., Whitaker, D. J., & Lutzker, J. R. (2009). Population-based prevention of child maltreatment: The U.S. Triple p system population trial. Prevention Science, 10(1), 1–12. doi: 10.1007/s11121-009-0123-3.CrossRefPubMedPubMedCentralGoogle Scholar
  23. Sampson, R. J., & Groves, W. B. (1989). Community structure and crime: Testing social-disorganization theory. American Journal of Sociology, 94(4), 774–802. doi: 10.2307/2780858.CrossRefGoogle Scholar
  24. Scribano, P. V. (2010). Prevention strategies in child maltreatment. Current Opinion in Pediatrics, 22(5), 616–620. doi: 10.1097/MOP.0b013e32833e1688.PubMedGoogle Scholar
  25. Shapiro, C. J., Prinz, R. J., & Sanders, M. R. (2010). Population-based provider engagement in delivery of evidence-based parenting interventions: Challenges and solutions. Journal of Primary Prevention, 31(4), 223–234. doi: 10.1007/s10935-010-0210-z.CrossRefPubMedGoogle Scholar
  26. Shaw, C. R., & McKay, H. D. (1969). Juvenile delinquency and urban areas Revised edition. Chicago, IL: The University of Chicago Press.Google Scholar
  27. Shenoi, R., Greeley, C. S., & Giardino, A. P. (2013). Child maltreatment prevention—finding common ground with unintentional injury prevention. Journal Of Applied Research on Children, 4(1), 8.Google Scholar
  28. Stoltenborgh, M., Bakermans-Kranenburg, M. J., Alink, L. R. A., & van Ijzendoorn, M. H. (2014). The prevalence of child maltreatment across the globe: Review of a series of meta-analyses. Child Abuse Review,. doi: 10.1002/car.2353.Google Scholar
  29. Stoltenborgh, M., van Ijzendoorn, M. H., Euser, E. M., & Bakermans-Kranenburg, M. J. (2011). A global perspective on child sexual abuse: Meta-analysis of prevalence around the world. [Comparative Study, Meta-Analysis, Research Support, Non-U.S. Gov’t]. Child Maltreatment, 16(2), 79–101. doi: 10.1177/1077559511403920.CrossRefPubMedGoogle Scholar
  30. Tewksbury, R., Mustaine, E. E., & Covington, M. (2010). Offender presence, available victims, social disorganization and sex offense rates. American Journal of Criminal Justice, 35(1–2), 1–14.CrossRefGoogle Scholar
  31. Texas Population. (2009). Texas Department of State Health Services.
  32. U.S. Census Bureau. (2010). Census Urban Area Reference Maps.
  33. Yahaya, I., Uthman, O. A., Soares, J., & Macassa, G. (2013). Social disorganization and history of child sexual abuse against girls in sub-Saharan Africa: A multilevel analysis. BMC International Health and Human Rights, 13(33), 33. doi: 10.1186/1472-698X-13-33.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Zollner, H. S., Fuchs, K. A., & Fegert, J. M. (2014). Prevention of sexual abuse: Improved information is crucial. Child Adolescent Psychiatry and Mental Health, 8(1), 5. doi: 10.1186/1753-2000-8-5.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Christopher Spencer Greeley
    • 1
  • Ching-Yi Chuo
    • 1
    • 2
  • Min Ji Kwak
    • 1
    • 2
  • Sally S. Henin
    • 4
  • Marcella Donnaruma-Kwoh
    • 3
  • Jamie Ferrell
    • 4
  • Angelo Peter Giardino
    • 5
  1. 1.Center For Clinical Research and Evidence-Based MedicineThe University of Texas Health Science Center at HoustonHoustonUSA
  2. 2.School of Public HealthThe University of Texas Health Science Center at HoustonHoustonUSA
  3. 3.Section of Emergency MedicineThe Texas Children’s HospitalHoustonUSA
  4. 4.Forensic Nursing ServicesThe Memorial Hermann Health SystemHoustonUSA
  5. 5.Section of Academic PediatricsThe Texas Children’s HospitalHoustonUSA

Personalised recommendations