Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-05T03:59:38.475Z Has data issue: false hasContentIssue false
  • English
  • Français

IDENTIFYING INDIVIDUALS ENGAGING IN RISKY SEXUAL BEHAVIOUR FOR CHLAMYDIA INFECTION IN THE UK: A LATENT CLASS APPROACH

Published online by Cambridge University Press:  01 October 2009

BETH STUART  and
ANDREW HINDE
BETH STUART
Affiliation:
School of Social Sciences and Southampton Statistical Sciences Research Institute, University of Southampton, UK
ANDREW HINDE
Affiliation:
School of Social Sciences and Southampton Statistical Sciences Research Institute, University of Southampton, UK
Get access Rights & Permissions [Opens in a new window]

Summary

Chlamydia trachomitis is the most common sexually transmitted infection in the UK and the number of cases diagnosed each year continues to rise. Although much is known about the risk factors for chlamydia from previous observational studies, less is known about how individuals put themselves at risk. Do they engage in just one risky type of behaviour or are certain individuals ‘risky’, engaging in multiple risky behaviours? This paper uses latent class analysis, applied to the National Survey of Sexual Attitudes and Lifestyles II (2000–2001), to determine whether a subgroup of high-risk individuals can be identified and explores which features of their behaviour distinguish them from other groups of lower risk individuals. A 3-class solution was obtained, splitting the sample on the basis of the number of sexual partners in the past year. Those with no sexual partners in the past year (8%) and one sexual partner in the past year (71%) were much less likely to have engaged in any of the other behaviours known to increase chlamydia risk. However, the group who had two or more sexual partners in the past year (21%) were much more likely to have also engaged in other risky behaviours. The number of partners in the past year is therefore a useful marker for identifying those at increased risk of chlamydia infection. Individuals under 25 years old, males and those who were single or previously married were more likely to be allocated to the risky group. However, in spite of observed higher incidence of chlamydia infection, individuals in the black ethnic minority groups did not show an increased prevalence of risky behaviour, after controlling for age, sex and marital status.

Type
Research Article
Information
Journal of Biosocial Science , Volume 42 , Issue 1 , January 2010 , pp. 27 - 42
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, R., Garnett, G. & Geoffrey, P. (2000) Mathematical models of the transmission and control of sexually transmitted diseases. Sexually Transmitted Diseases 27, 636–643.CrossRefGoogle ScholarPubMed
Erens, B., McManus, S., Field, J., Korovessis, C., Johnson, A., Fenton, K. & Wellings, K. (2001) National Survey of Sexual Attitudes and Lifestyles II: Technical Report. National Centre for Social Research, London.Google Scholar
Fenton, K., Korovessis, C., Johnson, A., McCadden, A., McManus, S., Wellings, K. et al. (2001) Sexual behaviour in Britain: reported sexually transmitted infections and prevalent genital Chlamydia trachomatis infection. Lancet 358(1), 851–854.Google Scholar
Fenton, K., Mercer, C., McManus, S., Erens, B., Wellings, K., Macdowall, W. et al. (2005) Ethnic variations in sexual behaviour in Great Britain and risk of sexually transmitted infections: a probability survey. Lancet 365(1), 246–255.Google Scholar
Garson, G. D. (2008) Factor Analysis. URL: http://www2.chass.ncsu.edu/garson/pa765/factor.htm. (accessed 3rd August 2008).Google Scholar
Gott, M., Galena, E., Hinchliff, S. & Elford, H. (2004) “Opening a can of worms”: GP and practice nurse barriers to talking about sexual health in primary care. Family Practice 21, 528–536.Google Scholar
Health Protection Agency (2005) Mapping the Issues: HIV and other Sexually Transmitted Diseases in the United Kingdom 2005. Health Protection Agency Centre for Infections, London.Google Scholar
Jaccard, J., Macdonald, R., Wan, C., Guilamo-Ramos, V., Dittus, P. & Quinlan, S. (2004) Recalling sexual partners: the accuracy of self-reports. Journal of Health Psychology 9, 699–712.Google Scholar
Johnson, A., Wadsworth, J., Wellings, K., Field, J. & Bradshaw, S. (1994) Sexual Attitudes and Lifestyles. Blackwell Scientific Publications, Oxford.Google Scholar
Laumann, E. & Youm, Y. (1999) Racial/ethnic group differences in the prevalence of sexually transmitted diseases in the United States: a network explanation. Sexually Transmitted Diseases 26, 250–261.Google Scholar
Low, N., Sterne, J. & Barlow, D. (2001) Inequalities in rates of gonorrhoea and chlamydia between black ethnic groups in south east London: cross-sectional study. Sexually Transmitted Infections 77, 15–20.CrossRefGoogle Scholar
McCutcheon, A. (1987) Latent Class Analysis. Sage Publications, London.Google Scholar
McLachlan, G. & Peel, D. (2000) Finite Mixture Models. John Wiley & Sons, New York.Google Scholar
Magidson, J. & Vermunt, J. K. (2004a) Latent class analysis. In Lewis-Beck, M., Bryman, A. & Liao, T. F. (eds) The Sage Encyclopedia of Social Science Research Methods. Sage Publications, Thousand Oaks, CA, pp. 549–553.Google Scholar
Magidson, J. & Vermunt, J. K. (2004b) Latent class models. In Kaplan, D. (ed.) The Sage Handbook of Quantitative Methodology for the Social Sciences. Sage Publications, Thousand Oaks, CA, pp. 175–198.Google Scholar
National Institute for Health and Clinical Excellence (2007) Preventing sexually transmitted infections and reducing under-18 conceptions. URL: http://guidance.nice.org.uk/PHI3 (accessed 12th March 2007).Google Scholar
Office for National Statistics (2007) News release: 30th August 2007. URL: http://www.statistics.gov.uk/pdfdir/divorce0807.pdf (accessed 11th August 2008).Google Scholar
Radcliffe, K., Ahmad, S., Gilleran, G. & Ross, J. (2001) Demographic and behavioural profile of adults infected with chlamydia: a case-control study. Sexually Transmitted Infections 77, 265–270.Google Scholar
Sonkin, B. & Hinde, A. (2007) Defining Risky Sexual Behaviour in the UK: A Latent Class Approach. S3RI Applications & Policy Working Papers, A07/01Southampton Statistical Sciences Research Institute, Southampton.Google Scholar
Storr, C., Hongling, Z., Kung-Yee, L. & Anthony, J. (2004) Empirically derived latent classes of tobacco dependence syndromes observed in recent-onset tobacco smokers: epidemiological evidence from a national probability sample survey. Nicotine and Tobacco Research 6, 533–545.Google Scholar
Uebersax, J. S. (2001) Latent class analysis – frequently asked questions. URL: http://ourworld.compuserve.com/homepages/jsuebersax/local.htm (accessed 17th January 2006).Google Scholar
Van Duynhoven, Y., Nagelkerke, N. & Van de Laar, M. (1999) Reliability of self-reported sexual histories: test–retest and interpartner comparison in a sexually transmitted diseases clinic. Sexually Transmitted Diseases 26, 33–42.CrossRefGoogle Scholar
Vermunt, J. K. (1997) LEM: A General Program for the Analysis of Categorical Data. Department of Methodology and Statistics, Tilburg University, Tilburg.Google Scholar
Wadsworth, J., Johnson, A., Wellings, K. & Field, J. (1996) What's in a mean? An examination of the inconsistency between men and women in reporting sexual partnerships. Journal of the Royal Statistical Society, Series A 159, 111–123.Google Scholar
Winter, A. J., Sriskandabalan, P., Wade, A. A. H., Cummins, C. & Barker, P. (2000) Sociodemography of genital Chlamydia trachomatis in Coventry, UK 1992–1996. Sexually Transmitted Infections 76, 103–109.Google Scholar