Socio-economic factors and late diagnosis of HIV in in the Royal Free cohort Socio-economic factors and late diagnosis of HIV in in the Royal Free cohort LS BURCH, N OAKES-MONGER, CJ SMITH, FC LAMPE, R TSINTAS, C CHALONER, AN PHILLIPS, MA JOHNSON UCL MEDICAL SCHOOL AND ROYAL FREE HOSPITAL NHS TRUST, LONDON, UK Late diagnosis of HIV in the UK continues to be a major problem: in % of all new diagnoses were late (CD4<350 cells/μL) and 26% were very late (CD4<200) 1 Little is known about the association between late diagnosis and socio-economic factors such as housing, education and employment We investigated the predictors of late diagnosis amongst newly diagnosed individuals attending the Royal Free Hospital, London, UK between April 2011 and May 2013 Data were collected via a patient registration form including information on presentation, risk behaviour, medical history and socio-economic characteristics. Late diagnosis was defined as a CD4<350 cells/μL at diagnosis. Associations between socio-economic factors and late diagnosis were assessed by logistic regression, adjusted for gender, mode of acquisition and age. A postcode-based measure of deprivation, the Indices of Multiple Deprivation (IMD), was calculated. The index is based on a weighted average of 7 domains of deprivation: income, employment, health and disabilities, education, barriers to housing, crime, and living environment 2. 45% (92/203) of newly-diagnosed individuals had CD4<350 cells/μL (29% CD4<200). Median CD4 at diagnosis was 373 (range 3 – 1672) cells/μL. Late diagnosis was seen more common amongst (Figures 1a-b): Females or heterosexual male Age >40 years Black African Parent Married individuals Not privately renting / owner-occupiers Less than university education Never previously tested for HIV There was no evidence of an association with employment or deprivation index. However, after adjustment only gender/mode of acquisition and age remained significant (Table 1). TABLE 1: FACTORS ASSOCIATED WITH LATE DIAGNOSIS (Results from logistic regression model adjusted for gender/ mode of acquisition and age ) Background Methods Results Conclusion FIGURE 1: PERCENT DIAGNOSED LATE (CD4<350 CELLS/μL) a: DEMOGRAPHIC FACTORS b: SOCIO-ECONOMIC FACTORS N Adjusted OR (95% CI) P Gender/MSM mode of acquisition Non-MSM men (1.53, 7.05) Women (1.56, 5.95) Age<30 years years (0.35, 2.39) years (0.60, 3.87) >50 years (0.97, 3.19) EthnicityWhite Black African (0.84, 4.45) Other (0.46, 2.13) ChildrenNo Yes (0.69, 3.41) Unknown (0.55, 2.51) Housing Own/private rent Other (0.44, 2.22) EducationUniversity Non- university (0.56, 2.60) EmployEmployed Unemployed (0.41, 2.11) HighNo deprivationYes (0.57, 2.17) Married/ Civil partnership No Yes (0.66, 3.34) Unknown (0.53, 2.04) Non-MSM men and women have over 3 times greater odds of being diagnosed late than MSM, and those aged >40 years have around twice the odds of individuals <40 years. When adjusted for these factors, the effect of all other demographic and socio-economic factors on the probability of late diagnosis were negligible. It is encouraging that late diagnosis is not found to be significantly associated with socio-economic status, however, we cannot exclude a modest relationship without a larger study population. Strategies to increase regular HIV testing remain a priority. JusTRI 12 th December This is a modified version for teaching purposes. For original poster, (and acknowledgements) see Poster 285, 3rd Joint Conference of the British HIV Association (BHIVA) with the British Association for Sexual Health and HIV (BASHH), Liverpool, UK, 1–4 April 2014