How and why do South Asians attend GUM clinics? Evidence from contrasting GUM clinics across England

Background: Improving access to sexual healthcare is a priority in the UK, especially for ethnic minorities. Though South Asians in the UK report low levels of sexual ill health, few data exist regarding their use of genitourinary medicine (GUM) services. Objectives: To describe reasons for attendance at GUM clinics among individuals of South Asian origin relative to patients of other ethnicities. Methods: 4600 new attendees (5% South Asian; n=226) at seven sociodemographically and geographically contrasting GUM clinics across England completed a questionnaire between October 2004 and March 2005, which were linked to routine clinical data. Results: South Asians were more likely than other groups to be signposted to the GUM clinic by another health service-for example, in women 14% versus 8% respectively (p=0.005) reported doing so from a family planning clinic. These women also reported that they would be less likely to go to the clinic if their symptoms resolved spontaneously compared with other women (51% vs 31%, p=0.024). However, relative to other clinic attendees, no differences in the proportions of South Asians who had acute STI(s) diagnosed at clinic were noted. Furthermore, South Asian men were more likely to report as their reason for attendance that they wanted an HIV test (23.4% vs 14.8%, p=0.005). Conclusion: Despite having similar STI care needs to attendees from other ethnic groups, South Asians, especially women, may be reluctant to seek care from GUM clinics, especially if their symptoms resolve. Sexual health services need to develop locally-delivered and culturally-appropriate initiatives to improve care pathways

Change from Baseline at Week 12 in Fasting Lipids (Modified Intent To Treat Analysis Set.

<p>^aDelayed Switch to EFV/FTC/TDF column includes subjects who were randomized to continue ABC/3TC+EFV at baseline and had at least 1 dose of EVF/FCT/TDF after switch at Week 12.</p><p>^bThe p-value for comparison between EFV/FTC/TDF and ABC/3TC +EFV at study Week 12 is from Wilcoxon rank sum test.</p><p>^cThe 95% confidence interval for the difference (EFV/FTC/TDF vs. ABC/3TC+EFV) is based on normal approximation.</p><p>^dThe p-value for within treatment group comparison is from Wilcoxon signed rank test.</p><p>Change from Baseline at Week 12 in Fasting Lipids (Modified Intent To Treat Analysis Set.</p

Subject Disposition at Week 24 (Treated Analysis Set).

<p>*Adverse events leading to study drug discontinuation: </p><p></p><p></p><p>Immediate Switch: emergent to EFV/FTC/TDF—anxiety; insomnia; night sweats</p><p></p><p></p><p>Delayed Switch: emergent to ABC/3TC + EFV (baseline to Wk12)—depression</p><p></p><p></p><p>Delayed Switch: emergent to EFV/FTC/TDF (Wk 12 to Wk 24)—sleep disorder; urticaria</p><p></p><p></p> The proportion of subjects discontinuing due to adverse events at week 12 was the same in both groups (n = 1; 1.3%)<p></p><p>Immediate Switch: emergent to EFV/FTC/TDF—anxiety; insomnia; night sweats</p><p>Delayed Switch: emergent to ABC/3TC + EFV (baseline to Wk12)—depression</p><p>Delayed Switch: emergent to EFV/FTC/TDF (Wk 12 to Wk 24)—sleep disorder; urticaria</p><p>Subject Disposition at Week 24 (Treated Analysis Set).</p

Fasting Total Cholesterol by NCEP Thresholds (Treated Analysis Set).

<p>Fasting Total Cholesterol by NCEP Thresholds (Treated Analysis Set).</p

Changes in Lipid fractions from Baseline (Treated Analysis Set).

<p>Significant declines from baseline were seen in the Immediate Switch group but not in the Delayed Switch group.</p

Demographics and Baseline Characteristics (Treated Analysis Set).

<p>Demographics and Baseline Characteristics (Treated Analysis Set).</p

Flow diagram of progress through the study phases (All Subjects).

<p>Flow diagram of progress through the study phases (All Subjects).</p

How much do delayed health care seeking, delayed care provision and diversion from primary care contribute to the transmission of STIs

Objectives: To explore the changing pattern of condom use from 1990 to 2000; to identify sociodemographic and behavioural factors associated with condom use; and reasons for condom use in 2000. Methods: Large probability sample surveys administered among those resident in Britain aged 16–44 (n = 13 765 in 1990, n = 11 161 in 2000). Face to face interviews with self completion components collected sociodemographic, behavioural, and attitudinal data. Results: Condom use in the past year among sexually active 16–24 year old men increased from 61.0% in 1990 to 82.1% in 2000 (p<0.0001), and from 42.0% to 63.2% (p<0.0001) among women of the same age, with smaller increases among older age groups. Among individuals reporting at least two partners in the previous 4 week period, approximately two thirds reported inconsistent or no condom use (63.1% (95% CI 55.9% to 69.8%) of the men and 68.5% (95% CI 57.6% to 77.7%) of the women). Conclusions: Rates of condom use increased substantially between 1990 and 2000, particularly among young people. However, inconsistent condom use by individuals with high rates of partner acquisition may contribute significantly to the recent resurgence in STIs. This group is an important target for intensive and specific sexual health interventions