Public attitudes toward pharmacy-based HIV PrEP in the UK: a national cross-sectional study of 15,000 NHS patients

Public attitudes toward pharmacy-based HIV PrEP in the UK: a national cross-sectional study of 15,000 NHS patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Public attitudes toward pharmacy-based HIV PrEP in the UK: a national cross-sectional study of 15,000 NHS patients Austen El-Osta, Emmanouil Bagkeris This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8466343/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background HIV pre-exposure prophylaxis (PrEP) is highly effective, yet uptake in the UK remains suboptimal. Community pharmacies could be accessible venues for PrEP delivery but public acceptability is poorly understood. We examined awareness, attitudes and support for pharmacy-based provision among NHS patients. Methods We conducted a national cross-sectional online survey of 15,071 adults recruited through general practices in England (October 2022-October 2023). The questionnaire captured demographics, PrEP awareness, attitudes and preferences for access. Descriptive statistics, multivariable logistic regression and joint correspondence analysis (JCA) were used to assess predictors of PrEP awareness and support for pharmacy-based delivery. Findings Overall, 37·2% of all respondents had heard of PrEP only 1·8% reported use and 66·9% did not know that PrEP can prevent HIV. Awareness was lower among heterosexual individuals (adjusted odds ratio [aOR] 0·36, 95% CI 0·31, 0·42), women (aOR 0·56, 0·49, 0·65) and older adults (≥ 65 years: aOR 0·41, 0·33, 0·51). Nearly two-thirds (63·5%) expressed interest in learning more about PrEP. Pharmacies were rated the most convenient access point by 51·2% of respondents and 60·8% supported pharmacy-based provision. JCA revealed a polarity between a “traditional” cluster (older, heterosexual, White, partnered men; low awareness and support) and a “diverse” cluster (younger, non-binary, bisexual or pansexual, single individuals; high awareness and support). Interpretation Despite low baseline awareness, there is strong public interest in PrEP and substantial support for pharmacy-based provision. Expanding PrEP through community pharmacies could reduce access barriers and advance equity, particularly for groups underserved by sexual health clinics. These findings support policy reforms enabling pharmacists to deliver PrEP as part of the UK’s HIV elimination strategy. Preventive Medicine HIV pre-exposure prophylaxis (PrEP) Community pharmacy Public perceptions PrEP uptake Healthcare accessibility HIV prevention strategies Barriers to PrEP PrEP facilitators Stigma Health equity Figures Figure 1 Figure 2 Research in context Evidence before this study We searched PubMed, Embase and Google Scholar for studies published between Jan 1, 2012 and Jan 1, 2023, using combinations of “HIV pre-exposure prophylaxis”, “PrEP”, “community pharmacy”, “public attitudes” and “United Kingdom”. Previous research has established PrEP as a highly effective HIV prevention tool, but uptake in the UK remains uneven and largely concentrated among men who have sex with men (MSM). Several pilot programmes in high-income countries have shown that pharmacies can deliver PrEP, yet studies of public acceptability are scarce. UK-based work has mostly focused on key populations, with little evidence on attitudes across the wider public. No large-scale UK study has examined general population awareness and support for pharmacy-based PrEP delivery. Added value of this study This national survey of over 15,000 NHS patients is the largest UK general population study to explore awareness, attitudes and acceptability of PrEP delivery through community pharmacies. By combining multivariable regression with joint correspondence analysis, we go beyond descriptive reporting to identify intersectional clusters of demographic identities and attitudinal profiles. We show that awareness remains low among women, heterosexual individuals and older adults, but that a majority of the public support pharmacy-based provision, particularly younger, sexually diverse and non-binary respondents. Implications of all the available evidence Our findings demonstrate that pharmacies represent an underutilised but viable access point for PrEP in the UK. Expanding PrEP delivery beyond sexual health clinics to community pharmacies could normalise use, reduce stigma and advance equity in HIV prevention. Implementation should focus on raising awareness in underinformed groups and equipping pharmacies with the regulatory authority, training and infrastructure to deliver safe and effective PrEP services as part of the UK’s HIV elimination strategy. Introduction Pre-exposure prophylaxis (PrEP) is a highly effective HIV prevention strategy involving the use of antiretroviral medication by HIV-negative individuals to reduce the risk of infection. 1 , 2 Clinical trials and real-world evidence consistently demonstrate that PrEP can reduce HIV transmission by more than 90% when taken as prescribed. ​ 3 , 4 ​Although the number of individuals receiving PrEP globally rose by 35% from 2022 to 2023, uptake remains well below the UNAIDS target of 10 million users by 2025. 5 , 6 This gap highlights that many at-risk populations including heterosexual individuals, women, people who inject drugs and those from Black African and other underserved communities may not yet be benefiting from PrEP. In the UK, PrEP has been available from sexual health services since 2020 following the NHS' decision to fund it for high-risk populations. 7 Despite this, 65% of individuals who want PrEP in England cannot access the prophylaxis and 57% of those who could obtain PrEP had to wait over 12 weeks for an appointment. 8 Additionally, initiation or continuation of PrEP among those with a PrEP need in England was highest in gay, bisexual and men who have sex with men (MSM) at 75·4% compared to only 39·0% in heterosexual men and 40·9% in heterosexual and bisexual women. 9 Barriers to PrEP uptake include lack of awareness 10 , perceived stigma 11 – 13 and the misconception that PrEP is only for certain populations such as men who have sex with men (MSM). 14 , 15 Structural barriers, including the cost of PrEP 16 , 17 when not covered by health services and difficulty accessing sexual health clinics 10 further complicate PrEP uptake​. In the UK, public knowledge of PrEP remains low, even among high-risk groups. (18) Recent findings highlight that inequities in PrEP access persist due to a failure to scale provision beyond specialist sexual health services. 18 This study called for urgent exploration of alternative delivery models, particularly in primary care & community pharmacy, yet no large-scale studies have assessed public perceptions of these routes in the general population. 19 , 20 While sexual health clinics (SHCs) remain the primary access point for PrEP, recent discussions have highlighted the potential for alternative delivery models to improve access. 21 Community pharmacies, due to their wide reach, accessibility and the trusted role of pharmacists in healthcare, are a potential setting for PrEP provision.​ 22,23 The pervasiveness of community pharmacies is high and many are often located in areas underserved by sexual health services. Community pharmacies are therefore well placed to potentially mitigate many logistical barriers to accessing PrEP such as limited clinic hours or geographic distance; thereby expanding access to at-risk populations. The competent and highly respected pharmacy workforce has the potential to play a crucial role in disseminating health information, reducing stigma associated with HIV prevention and facilitating adherence to PrEP regimens. 24 – 26 Globally, there are examples of pharmacies successfully offering a sexual health advisory services, including contraceptive advice and HIV testing࿼࿼ ​ In the US, -pharmacy-based PrEP delivery models have reduced barriers to access, yet the evidence base remains limited࿼࿼ ​ To date, no large-scale studies in the UK have explored the potential for pharmacies to provide PrEP, despite the growing recognition of this approach’s feasibility࿼࿼ Understanding the attitudes, beliefs and potential public concerns regarding pharmacy-based PrEP provision is essential for informing future health policies aimed at increasing access. Moreover, existing research has largely focused࿼࿼, with limited attention to other populations who could benefit from PrEP, including heterosexual individuals, women, people who inject drugs and those from diverse cultural backgrounds​ - specifically Black African. To date, most research on PrEP acceptability has focused on specific key populations (such as men who have sex with men) or small-scale pilot studies of pharmacy delivery. Large-scale general population surveys remain rare, particularly in the UK and existing evidence is fragmented across narrow demographic groups. Our study addresses this gap by surveying more than 15,000 NHS patients nationwide, the largest general population dataset on PrEP awareness and attitudes in the UK and by combining multivariable regression with joint correspondence analysis. This dual analytic approach provides both robust estimates of demographic predictors and a visual mapping of intersectional identity clusters that shape PrEP attitudes. By integrating scale with intersectional insight, our study moves beyond descriptive surveys to offer a population-level evidence base for pharmacy-led PrEP expansion. The aim of this study was to examine public perceptions of PrEP and its potential availability in community pharmacies. Specifically, we sought to (i) assess levels of awareness and knowledge about PrEP among the general public within the UK, (ii) identify primary barriers and facilitators that affect access to PrEP particularly through community pharmacies. The study also sought to examine demographic differences in use of PrEP and public awareness of PrEP as a prophylactic and the public attitudes towards (a) seeking information for PrEP and (b) accessing PrEP from community pharmacy; with attention to differences among participants of different gender, sexual orientation and educational background. Methods Study design and participants We conducted a UK-wide cross-sectional study to assess public awareness, attitudes and perceptions regarding HIV PrEP, with a particular focus on community pharmacy-based provision. The survey was administered online using the Imperial College Qualtrics XM platform, open from 29 October 2022 to 29 October 2023. Participants were recruited via NHS general practices through Short Messaging Service (SMS) invitations, which included a link to the electronic survey and a participant information sheet. Additional dissemination occurred through personal and professional networks. Participation was voluntary and anonymous. Respondents were eligible if they were adults (≥ 18 years) residing in the UK. Completion of the survey implied informed consent. Data were stored securely at Imperial College London and pseudo-anonymised using unique identifiers. Survey instrument The survey consisted of 28 questions, including demographic characteristics (age, gender, ethnicity, education, sexuality, relationship status, region), awareness and attitudes towards PrEP and preferences for obtaining PrEP. Questions were informed by existing literature and refined through expert review and cognitive interviews with public health and HIV prevention specialists, including advisors from the Terrence Higgins Trust. The final version was piloted for clarity and internal consistency. Most items were closed-ended and conditional based on prior responses. To minimise duplication, respondents were prevented from completing the survey more than once using Qualtrics cookies and digital fingerprinting. Technical functionality was tested prior to launch. The survey ( Appendix p 2–15 ) was accessible using a personal computer or smartphone. Data analysis Descriptive statistics were used to summarise participant characteristics and key outcomes. Attitudinal questions were summarised by calculating the proportion of respondents who either agreed or strongly agreed with each statement. Univariable and multivariable logistic regression models assessed associations between demographic variables and (i) awareness of PrEP, (ii) use of PrEP, (iii) interest in learning about PrEP and (iv) attitudes toward pharmacy-based access. Multivariable models adjusted for age, gender, sexuality, ethnicity, education and relationship status. Results are presented as adjusted odds ratios with 95% confidence intervals (CI). Joint Correspondence Analysis To explore patterns of association across key socio-demographic variables, we conducted a Joint Correspondence Analysis (JCA) using five categorical variables: gender, age group, ethnicity, sexual orientation and relationship status. This technique allows for the visualisation of latent structures in multivariate categorical data by projecting category-level coordinates onto two principal dimensions. The JCA was conducted using principal normalisation and results were displayed as a joint correspondence plot. As Dimension 1 and Dimension 2 explained 59·2% and 20·2% of the total inertia respectively, they together accounted for 79·4% of the variance in the data. This analysis enabled identification of subgroups with similar demographic patterns. We selected JCA over multiple correspondence analysis (MCA) and latent class analysis (LCA) because our aim was to visualise relationships between socio-demographic categories and attitudinal outcomes simultaneously, rather than to reduce data dimensionality alone with MCA, or to assign participants to latent groups probabilistically. This JCA approach generates an interpretable biplot that complements regression results by showing how identity characteristics cluster together, thereby providing a transparent and intersectional lens on attitudinal variation across the population. Statistical significance was defined as p < 0·05. Analyses were conducted using Stata version 17 (StataCorp, College Station, TX, USA). The Checklist for Reporting Results of Internet ESurveys (CHERRIES) 31 was used to guide reporting; Appendix p16-17 . Ethics Ethical approval was obtained from the NHS Research Ethics Committee (REC#22/LO/0289) and the Health Research Authority (HRA #3043648; CPMS ID 52576). All procedures complied with the Declaration of Helsinki and institutional guidelines. Patient and public involvement Patient and public involvement including the development of the survey was supported by the Terrence Higgins Trust, a leading HIV and sexual health charity in the UK. Their input was instrumental in ensuring the relevance, appropriateness and inclusivity of survey items. The questionnaire underwent expert review, including feedback from public health professionals and HIV prevention specialists and was refined through a pilot phase that included cognitive interviewing and beta testing with a diverse group of individuals. This process helped to optimise the clarity, flow and cultural sensitivity of the survey before full-scale deployment. Results We collected data from 15,071 NHS patients across England. Participant characteristics The mean age was 47·8 years (SD 16·2); 54·2% identified as female (including trans women), 38·9% as male (including trans men), 1·1% as non-binary and 3·4% either preferred not to disclose or chose “other.” Most participants identified as heterosexual (76·9%), with smaller proportions identifying as homosexual (8·0%), bisexual (7·1%), or other identities. Over half (55·7%) had a university degree or higher. Ethnically, the cohort was predominantly White (81·2%), with representation from Asian (7·1%), Black (3·8%), Mixed (3·5%) and other ethnic groups (1·6%); Table 1 . Table 1 Respondent characteristics (N = 15,071) n % Age, mean 47·8 (16·2) Age in categories, n (%) < 25 1,184 (7·9) [25–45) 5,215 (34·6) [45–65) 5,757 (38·2) ≥ 65 2,464 (16·3) Missing 451 (3·0) Gender, n (%) Female (including trans woman) 8,175 (54·2) Male (including trans man) 5,862 (38·9) Non-binary 162 (1·1) Other (please specify) 311 (2·1) Prefer not to say 195 (1·3) Missing 366 (2·4) Educational level, n (%) A level / college 3,809 (25·3) Secondary school / high school 2,482 (16·5) University degree or higher 8,393 (55·7) Missing 387 (2·6) Relationship status, n (%) Married / partnered 7,171 (47·6) In a domestic relationship 3,112 (20·6) Other 442 (2·9) Single 3,955 (26·2) Missing 391 (2·6) Ethnicity, n (%) White 12,234 (81·2) Asian, Asian British or Asian Welsh 1,070 (7·1) Black, Black British, Black Welsh, Caribbean or African 573 (3·8) Mixed or Multiple ethnic groups 526 (3·5) Other ethnic group 240 (1·6) Missing 428 (2·8) Sexuality, n (%) Heterosexual 11,589 (76·9) Homosexual 1,202 (8·0) Bisexual 1,065 (7·1) Other (please specify) 244 (1·6) Pansexual 217 (1·4) Prefer not to say 383 (2·5) Missing 371 (2·5) Region, n (%) East Midlands 4,874 (32·3) East of England 328 (2·2) North Thames (London) 121 (0·8) North West Coast 3,214 (21·3) North West London 3,269 (21·7) Thames Valley and South Midlands 3,265 (21·7) Main survey findings The results of the main survey are shown in Appendix p18-21 PrEP Awareness and use Among respondents, 66·9% were unaware that PrEP prevents HIV and only 1·8% had used it. Of those aware of PrEP (n = 5,609), only 13·4% had ever considered using it and 8·0% reported current or past use. Awareness was highest among younger, male, non-heterosexual and more highly educated participants. PrEP information was predominantly derived from sexual health clinics (16·1%) and healthcare professionals (15·0%), while only 1·3% had heard of PrEP from pharmacists. Among respondents interested in learning more about PrEP (63·5%), healthcare professionals (62·9%) and sexual health clinics (38·2%) were their preferred sources; Table 2 . Table 2 PrEP Awareness among the study participants (N = 15,071) Have you ever heard about PrEP? Yes 5,609 (37·2) No 9,462 (62·8) Total 15,071 (100·0) How did you hear about PrEP? Please select one or more Friend or family member 1,170 (20·9) Television / radio 1,537 (27·4) Social media / online forums 1,410 (25·1) Healthcare professional / doctor / GP 840 (15·0) Pharmacist 79 (1·3) Sexual health clinic / organisation 904 (16·1) LGBTQI + organisation/s 1,106 (19·7) African organization/s 35 (0·6) Other 971 (17·3) Are you aware that PrEP could help to prevent being infected with HIV? Yes 4,782 (31·7) No 10,087 (66·9) Did not answer 202 (1·3) Would you be interested in seeking information about PrEP? Yes 9,570 (63·5) No 5,501 (36·5) Where would you most likely seek more information regarding PrEP? Friend or family member 454 (4·7) Television / radio 513 (5·4) Social media / online forums 2,175 (22·7) Pharmacist 1,435 (15·0) Healthcare professional / doctor / GP 6,018 (62·9) Sexual health clinic / organisation 3,654 (38·2) LGBTQI + organisation/s 930 (9·7) African organization/s 56 (0·6) Other 814 (8·5) I have enough information to take PrEP safely & effectively Strongly agree 1,036 (6·9) Agree 1,690 (11·2) Neither agree nor disagree 4,827 (32·0) Disagree 3,823 (25·4) Strongly disagree 3,112 (20·7) Did not answer 583 (3·9) I would be happy to obtain PrEP if it were available from my local pharmacy Strongly agree 3,027 (20·1) Agree 4,658 (30·9) Neither agree nor disagree 4,807 (31·9) Disagree 955 (6·3) Strongly disagree 974 (4·5) Did not answer 650 (4·3) I would feel comfortable to getting information about PrEP from pharmacist/pharmacy Strongly agree 3,297 (21·9) Agree 6,162 (40·9) Neither agree nor disagree 2,730 (18·1) Disagree 1,307 (8·7) Strongly disagree 767 (5·1) Did not answer 808 (5·4) Attitudes toward pharmacy-based provision Overall, 60·8% supported access to PrEP through community pharmacies, with 30·1% agreeing and 30·7% strongly agreeing. A similar proportion (62·8%) reported feeling comfortable discussing PrEP with pharmacists. Pharmacies were rated the most convenient access point by 51·2% of respondents, ahead of sexual health clinics (18·6%) and online sources (40·4%). Support for pharmacy-based provision was significantly higher among younger adults, non-heterosexual participants and those with higher educational attainment. Participants who were married, older or from certain ethnic groups were less likely to express support. Factors affecting the participant’s decision in accessing PrEP are shown in Appendix Fig. 1 (p22). Barriers to PrEP uptake Commonly reported barriers included lack of awareness (35·7%), insufficient information (32·0%), concerns about side effects (19·1%) and concerns about cost (44·5%). Cultural or religious conflict was cited by 10·1% and 23·1% reported stigma as a barrier. Predictors of PrEP use, awareness and pharmacy support Multivariable analysis showed that current/past PrEP use was significantly associated with male gender (aOR = 9·26, 95% CI; 6·22, 13·76), non-binary identity (aOR = 4·02, 95% CI; 1·89, 8·94) and homosexual (aOR = 48·24, 95% CI; 33·39, 69·68) or bisexual (aOR = 16·64, 95% CI; 10·78, 25·68) orientation. PrEP awareness was higher among those aged < 45, non-White ethnic groups and university-educated individuals. Support for pharmacy access was also higher among younger adults and bisexual/pansexual participants. Full regression models are presented in Appendix Tables 2–5 . A visual summary of demographic predictors is presented as a coefficient plot is shown in Fig. 1 and Table 3 contains the results of all multivariable analyses. Table 3 Participant characteristics and their association with use of PrEP, awareness of PrEP as a prophylactic, attitudes towards seeking information for PrEP and accessing PrEP from community pharmacy Use of PrEP Awareness of PrEP as prophylactic Seeking information for PrEP Accessing PrEP from community pharmacy AOR 95% CI p-value aOR 95% CI p-value aOR 95% CI p-value aOR 95% CI p-value Age ≥ 65 Ref. - - Ref. - - Ref. - - Ref – – < 25 2·22 (1·15, 4·26) 0·02 2·56 (2·13, 3·08) < 0·001 2·07 (1·73, 2·48) < 0·001 2·97 (2·24, 3·93) < 0·001 [25–45) 4·43 (2·57, 7·65) < 0·001 2·51 (2·19, 2·87) < 0·001 1·75 (1·57, 1·95) < 0·001 1·82 (1·57, 2·12) < 0·001 [45–65) 2·71 (1·57, 4·70) < 0·001 1·52 (1·33, 1·73) < 0·001 1·59 (1·44, 1·75) < 0·001 1·30 (1·14, 1·49) < 0·001 Gender Female Ref. - - Ref. - - Ref. - - Ref – – Male 9·26 (6·22, 13·76) < 0·001 1·17 (1·07, 1·28) < 0·001 0·82 (0·76, 0·89) < 0·001 1·15 (1·03, 1·28) 0·01 Non-binary 4·02 (1·81, 8·94) 0·01 1·51 (1·05, 2·18) 0·03 0·82 (0·56, 1·20) 0·30 1·43 (0·76, 2·69) 0·27 Other/Prefer not to say 3·40 (1·40, 8·22) < 0·001 0·92 (0·72, 1·18) 0·53 0·66 (0·54, 0·81) < 0·001 0·57 (0·45, 0·73) < 0·001 Ethnicity White Ref. - - Ref. - - Ref. - - Ref – – Asian* 1·57 (1·06, 2·34) 0·03 0·63 (0·54, 0·74) < 0·001 2·17 (1·86, 2·54) < 0·001 0·92 (0·75, 1·12) 0·41 Black ╫ 1·18 (0·55, 2·54) 0·68 1·54 (1·27, 1·85) < 0·001 2·94 (2·35, 3·67) < 0·001 0·78 (0·61, 1·00) 0·05 Mixed 1·30 (0·73, 2·31) 0·38 1·08 (0·88, 1·32) 0·45 1·41 (1·15, 1·72) 0·01 0·81 (0·65, 1·01) 0·12 Other 2·00 (1·05, 3·81) 0·04 1·10 (0·81, 1·48) 0·55 1·56 (1·16, 2·10) 0·01 0·65 (0·46, 0·93) 0·02 Education A level/college Ref. - - Ref. - - Ref. - - Ref – – Secondary school/high school 0·83 (0·55, 1·24) 0·37 0·85 (0·74, 0·98) 0·02 0·92 (0·83, 1·03) 0·14 1·12 (0·96, 1·31) 0·15 University degree or higher 1·11 (0·85, 1·45) 0·45 1·94 (1·76, 2·13) < 0·001 1·11 (1·02, 1·21) 0·01 1·00 (0·89, 1·12) 0·97 Sexuality Heterosexual Ref. - - Ref. - - Ref. - - Ref – – Bisexual 16·64 (10·78, 25·68) < 0·001 4·01 (3·49, 4·61) < 0·001 2·09 (1·78, 2·45) < 0·001 1·55 (1·21, 1·98) < 0·001 Homosexual 48·24 (33·39, 69·68) < 0·001 21·16 (17·52, 25·6) < 0·001 3·91 (3·29, 4·66) < 0·001 1·22 (0·99, 1·51) 0·06 Other (please specify) 7·74 (3·28, 18·30) < 0·001 2·16 (1·62, 2·87) < 0·001 0·97 (0·74, 1·28) 0·82 0·79 (0·53, 1·14) 0·26 Pansexual 13·04 (6·10, 27·89) < 0·001 4·12 (3·07, 5·53) < 0·001 3·47 (2·32, 5·19) < 0·001 2·04 (1·13, 3·71) 0·02 Prefer not to say 6·55 (3·04, 14·13) < 0·001 1·54 (1·20, 1·85) 0·001 1·24 (0·98, 1·58) 0·07 1·14 (0·83, 1·58) 0·42 Relationship status In a domestic relationship Ref. - - Ref. - - Ref. - - Ref – – Married / partnered 0·65 (0·47, 0·90) 0·01 0·83 (0·75, 0·93) 0·01 0·62 (0·56, 0·69) < 0·001 0·86 (0·75, 0·99) 0·04 Other 1·77 (0·92, 3·40) 0·07 1·13 (0·88, 1·46) 0·34 0·72 (0·58, 0·90) 0·01 0·89 (0·66, 1·20) 0·44 Single 1·54 (1·18, 2·01) 0·01 1·10 (0·99, 1·23) 0·09 1·09 (0·79, 1·21) 0·14 1·10 (0·94, 1·29) 0·22 *Includes Asian British or Asian Welsh, ╫ Includes Black British, Black Welsh, Caribbean or African Joint correspondence analysis We used Joint Correspondence Analysis (JCA) to examine the latent structure of socio-demographic patterns: gender identity, age group, ethnicity, sexual orientation and relationship status. The resulting biplot (Fig. 2 ) displays category-level associations across two principal dimensions, which together explained 79·4% of the total variance (Dimension 1 = 59·2%; Dimension 2 = 20·2%). Categories of age, gender, sexuality, ethnicity and relationship status are plotted in a two-dimensional space (Fig. 2 ). Dimension 1 (59·2% inertia) separates a traditional cluster of older, heterosexual, married respondents from a diverse cluster of younger, non-binary and sexually diverse respondents, while Dimension 2 (20·2% inertia) reflects secondary variation by gender and relationship status. Dimension 1 (horizontal axis) shows a strong polarity between two demographic groupings (Fig. 2 ). On the left, a traditional cluster emerged comprising older (≥ 45 years), White, heterosexual, married men. On the right, a more diverse cluster appeared, including younger (< 25 years), non-binary participants, bisexual or pansexual respondents and those who were single or in a relationship. This separation reflects contrasting identity profiles aligned with differences in PrEP awareness and receptivity to pharmacy-based provision, consistent with regression findings. Dimension 2 (vertical axis) adds further separation by age and gender. Younger women in relationships were located in the upper-right quadrant, whereas older men and non-normative gender groups clustered in the lower-left quadrant. Female participants and those in domestic relationships occupied more central positions, suggesting mixed profiles bridging traditional and non-traditional identities. Overall, the JCA visually reinforces the regression analyses by showing how intersecting demographic characteristics form distinct clusters linked to PrEP-related knowledge, attitudes and access preferences. The analysis highlights clear demographic patterning in PrEP awareness, interest and support for pharmacy-based provision, emphasising the value of intersectional approaches when designing targeted outreach and considering community pharmacy as a low-threshold access point. Discussion To our knowledge, this is the largest UK general population study examining public awareness and acceptability of PrEP and the first to apply joint correspondence analysis alongside regression modelling to capture intersectional attitudinal patterns. Whereas previous studies have provided either broad descriptive snapshots or small-scale evaluations of pharmacy feasibility, our findings uniquely demonstrate how demographic clusters align with divergent PrEP attitudes at scale. This methodological combination allows us to map both who remains excluded from PrEP messaging and who shows highest receptivity to decentralised access models, offering a new lens for policy and service planning. Principal findings Despite national commitments to end new HIV transmissions by 2030, fewer than one in three respondents (30·7%) reported awareness of PrEP. Awareness was lowest among older adults, heterosexual individuals and women, groups not traditionally targeted by PrEP campaigns, yet still at potential risk and critical to the equity of the HIV prevention response. Numerous responses highlighted issues related to the physical accessibility of sexual health clinics, including limited clinic locations and restricted appointment availability in line with our previous study. 32 This includes challenges in booking appointments that fit work schedules and the general scarcity of SHCs. Importantly, we found strong latent demand; nearly two-thirds of respondents expressed interest in learning more about PrEP and half supported pharmacy-based provision. This suggests a readiness among the public for expanded, decentralised PrEP delivery models beyond specialist sexual health services. The Joint Correspondence Analysis reinforced and extended these insights by highlighting distinct demographic subpopulations with divergent PrEP attitudes. A traditional cluster (comprising older, heterosexual, White, male participants who were married or partnered) occupied one end of the identity spectrum and was associated with the lowest levels of awareness, interest and support. In contrast, a younger, diverse cluster (featuring non-binary individuals, bisexual and pansexual respondents and those under the age of 25, consistently aligned with higher awareness, greater interest and stronger endorsement of community pharmacy as a PrEP access point. These two groupings, visualised through the JCA biplot, captured a striking polarity in engagement with PrEP, illustrating how intersectional identities drive differentiated risk perception, trust in health services and openness to novel service models. Collectively these findings point to a mismatch between those who currently access PrEP and those who express willingness to use it if made more accessible, particularly via pharmacies. Community pharmacy, as a widely distributed and often underused touchpoint, holds unique potential to bridge this gap, provided that services are designed inclusively and with attention to the structural and cultural barriers that shape uptake. Comparison to existing literature Our findings align with previous research highlighting the underuse of PrEP globally​. Earlier studies 33 , 34 similarly report that barriers like stigma, cost and lack of information contribute to suboptimal PrEP uptake. Our findings also align with and extend prior research on PrEP delivery through non-traditional settings whilst also highlighting pharmacists’ confidence and infrastructure limitations. 35 Our study complements these insights by revealing from the general public’s perspective both latent demand and demographic divergence, specifically that younger and gender/sexuality-diverse groups are substantially more supportive of pharmacy-based models. More recent pharmacy staff surveys in London have reported readiness to offer PrEP, contingent on additional training and facility enhancements. 36 This echoes our JCA finding that traditional groups (older, heterosexual, male, married individuals) are less engaged, suggesting that pharmacist-led initiatives must address both provider and public confidence, especially among populations less familiar with PrEP. Our latent-profile findings also resonate with qualitative studies of youth attitudes in England, which highlight strong interest and openness to PrEP when framed in non-clinic environments. 37 The clear polarity we observed via JCA (traditional vs. progressive clusters) mirrors discourses around stigma and trust; younger, sexually minoritised respondents cluster with high support for decentralised care, reinforcing themes seen in social science research on sexual health empowerment. The findings also build on calls by the UK Parliament to commission pharmacies for PrEP delivery as part of broader clinical-service expansion. 38 By demonstrating public acceptability across diverse groups-and identifying clusters with particularly high receptivity-our data provide empirical foundations to inform policy decisions, beyond pilot or advocacy-driven models. That healthcare professionals are a primary source of PrEP information is consistent with earlier studies 39 ​ emphasising the unrealised potential of pharmacists in providing information about PrEP in the UK, contrasting to the more established pharmacy-based PrEP models in the US​. Finally, the intersectional approach using JCA supplies a novel quantitative complement to individual-level analyses. Unlike surveys that primarily report overall acceptability, our study maps engagement across intersecting demographic axes (age, gender, sexuality, ethnicity, relationship status) highlighting target groups for tailored messaging and service design. Intersectional patterns in PrEP attitudes: insights from joint correspondence analysis The joint correspondence analysis highlighted distinct demographic clusters shaping awareness and support for PrEP. A “traditional” cluster (of older, heterosexual, White men in partnered relationships) was consistently associated with the lowest levels of awareness and receptivity. In contrast, a younger and more diverse cluster (of non-binary, bisexual or pansexual individuals, often single and from mixed or minority ethnic backgrounds) showed markedly higher awareness, interest and endorsement of pharmacy-based access. These patterns emphasise that age, gender, sexuality and relationship status interact to create compound influences on HIV prevention attitudes. Awareness campaigns and delivery models that treat these factors in isolation risk overlooking the intersectional drivers of both engagement and exclusion. The findings also suggest that expanding PrEP beyond sexual health clinics to community pharmacies could particularly benefit populations already predisposed to innovation in care access, namely younger, sexually diverse and gender-diverse individuals. Conversely, the traditional cluster’s lower awareness and weaker support point to enduring gaps in outreach, stigma reduction and message framing. Tailored interventions for older and heterosexual men, emphasising prevention and equity rather than risk categorisation, will be necessary to avoid widening disparities. By linking demographic identity patterns to attitudinal differences, the analysis provides an empirical foundation for precision targeting in HIV prevention indicating where pharmacy-based PrEP may gain fastest uptake and where focused education is most needed. This intersectional perspective moves beyond demographic enumeration to show how social identity structures shape readiness for new delivery models and, ultimately, the reach of the HIV prevention agenda. Implications for policy and practice Three priorities emerge from these findings. First, PrEP awareness must expand beyond groups traditionally targeted by HIV prevention. Heterosexuals, women, older adults and racially minoritised populations remain poorly informed despite national availability. Public health messaging should normalise PrEP as a universal prevention option, using trusted channels in primary care, community settings and digital media rather than focusing primarily on men who have sex with men. Second, pharmacies are an underused but publicly supported access point since over 60% of respondents endorsed pharmacy-based provision, indicating readiness for decentralised models. Realising this requires regulatory change to enable pharmacist prescribing and monitoring supported by training, HIV/STI screening pathways and integration with NHS digital records. Consistent national commissioning is essential to avoid regional variation whereas pharmacy-led services should include referral routes for confirmatory testing, renal monitoring and adherence support to maintain clinical quality. Third, implementation must be grounded in intersectional equity. JCA indicated that younger, sexually diverse and gender-diverse groups are most receptive to pharmacy access, whereas older heterosexual men are least engaged. Commissioning should therefore combine universal availability with targeted outreach to populations at risk of exclusion. Embedding these principles within the NHS HIV-elimination strategy could normalise PrEP, reduce stigma and narrow prevention gaps. Pharmacy-led access should be paired with campaigns that build awareness and trust while ensuring linkage to care, adherence monitoring and safety oversight, thus aligning service delivery with the UK’s 2030 goal to end new HIV transmissions. Limitations The principal limitation of this study is the cross-sectional design which prevents causal inference between demographic factors and PrEP awareness or attitudes. Although the sample was large and diverse, the survey was available only in English and participants were disproportionately highly educated (56% with university degrees), which may limit generalisability to populations with lower health literacy. Recruitment through NHS practices and online methods likely underrepresented people with limited digital access or weaker links to primary care, groups that may face additional barriers to PrEP uptake. Further, because baseline awareness of PrEP was low, responses regarding acceptability or intent may reflect limited knowledge rather than stable attitudes. Self-selection bias cannot be excluded and survey responses may not translate into real-world behaviour. The Joint Correspondence Analysis provided valuable insight into intersectional patterns but remains exploratory and descriptive; interpretation of clusters should therefore be cautious. Although these limitations constrain representativeness and causal inference, the breadth of the sample and use of complementary analytic methods strengthen confidence in the robustness and policy relevance of the findings. Future research directions This study highlights several key priorities for future research to support equitable and scalable PrEP implementation. Particular attention should be given to evaluating the feasibility and effectiveness of delivering very brief advice (VBA) on PrEP during routine health and care interactions. 40 , 41 Such touchpoints, including GP consultations, pharmacy visits 24 , sexual health screenings, contraceptive counselling and chronic disease reviews, are opportunities to engage individuals who may benefit from PrEP but remain unaware or underserved. Evidence from other domains, such as smoking cessation and alcohol reduction, demonstrates that VBA can be an effective and scalable intervention within primary care and community settings. 42 , 43 Applying this approach to HIV prevention could help normalise PrEP discussions and reduce stigma associated with its use. Future studies should explore the acceptability of VBA on PrEP from both provider and patient perspectives, assess outcomes such as PrEP uptake or referrals and investigate the role of tailored messaging based on individual risk, cultural context, or health literacy level. 44 Research should also examine how PrEP-related prompts or decision aids can be integrated into electronic health records to support consistent, targeted delivery across care pathways. Future work should assess the impact of tailored communication strategies including digital campaigns, peer outreach and community-led messaging on PrEP awareness among underserved groups such as racially minoritised populations, women, older adults and those in rural or deprived areas. Conclusions Despite national PrEP availability, public awareness remains low, particularly among heterosexuals, women, older adults and racially minoritised groups. Yet support for pharmacy-based provision is strong, especially among younger and sexually diverse populations. This mismatch between need, awareness and access highlights an urgent opportunity: expanding PrEP through community pharmacies could reduce barriers, normalise use and advance equity. Achieving this will require targeted public education, pharmacist training and intersectional implementation strategies that centre inclusion and trust. Without such action, the benefits of PrEP will remain inequitably distributed. Declarations Contributors AEO conceptualised the study and was involved in study development, methodology, interpretation, writing the original manuscript draft and reviewing and editing the manuscript. EB was involved in methodology, data analysis, verification and interpretation and writing, reviewing and editing the manuscript. AA was involved in project administration, data collection, data curation, extraction and verification. MA and SL conceptualised the study and were involved in reviewing and editing the manuscript. SOS, AS, and DM were involved in data interpretation and reviewing and editing the manuscript. RB and AM were involved in reviewing and editing the manuscript. AEO, EB and AA had full access to and verified the data. All authors have read and approved the final version of the manuscript. This article is published under a CC BY 4.0 licence. AEO is the guarantor. Declaration of interests The authors declare no competing interests. Data sharing De-identified survey data and analysis code will be made available upon reasonable request to the corresponding author following institutional data access procedures at Imperial College London. Acknowledgments The authors thank Barrie Dwyer and the Terrence Higgins Trust for providing feedback on the data collection tool and for disseminating the survey Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.Austen El-Osta and Azeem Majeedare supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) North West London. The views expressed are those of the authors and not necessarily those of the NHS or the NIHR or the Department of Health and Social Care. X: @austenelosta @ImperialSCARU References Organization WHO HIV/ AIDS - Pre-exposure prophylaxis. https://www.who.int/hiv/topics/prep/en/ HIV.Gov, Pre-Exposure Prophylaxis (2020) 2020. https://www.hiv.gov/hiv-basics/hiv-prevention/using-hiv-medication-to-reduce-risk/pre-exposure-prophylaxis PeRPWatch, United Kingdom (2020). https://www.prepwatch.org/country/united-kingdom/ NHS England (2015) Clinical Commissioning Policy: Treatment as Prevention (TasP) in HIV infected adults UNIAIDS (2024) 2024 global AIDS report Lopez M, Dong B (2020) Implementing PrEP in the pharmacy. Pharm Today 26:39–53 Kirby T (2020) PrEP finally approved on NHS in England. Lancet 395(10229):1025 Trust NA (2022) Not PrEPared: Barriers to accessing HIV prevention drugs in England Lester J, Martin V, Shah A, Chau C, Mackay N, Newbigging-Lister A (2022) HIV testing, PrEP, new HIV diagnoses, and care outcomes for people accessing HIV services: 2022 report. 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Seattle, Washington Group K-RP, ONE-STEP PREP® HIV PREVENTION PILOT PROGRAM, FINDINGS (2015). https://www.kelley-ross.com/prep-pilot-program-findings/ Saberi P, Dong BJ, Johnson MO, Greenblatt RM, Cocohoba JM (2012) The impact of HIV clinical pharmacists on HIV treatment outcomes: a systematic review. Patient Prefer Adherence 6:297–322 Chisholm-Burns MA, Kim Lee J, Spivey CA et al (2010) US pharmacists' effect as team members on patient care: systematic review and meta-analyses. Med Care 48(10):923–933 Alter M, lakhani S, Alaa A, Karki M, Riboli-Sasco E, El-Osta A (2024) Investigating barriers and enablers to the routine provision of HIV PrEP in community pharmacies in London. Res Square Tung EL, Thomas A, Eichner A, Shalit P (2018) Implementation of a community pharmacy-based pre-exposure prophylaxis service: a novel model for pre-exposure prophylaxis care. Sex Health 15(6):556–561 Hoth AB, Shafer C, Dillon DB, Mayer R, Walton G, Ohl ME (2019) Iowa TelePrEP: A Public-Health-Partnered Telehealth Model for Human Immunodeficiency Virus Preexposure Prophylaxis Delivery in a Rural State. Sex Transm Dis 46(8):507–512 Faro EZ, Mantell JE, Gonzalez-Argoti T et al (2022) Implementing PrEP Services in Diverse Health Care Settings. J Acquir Immune Defic Syndr 90(S1):S114–s28 Update to Interim Guidance for Preexposure (2013) Prophylaxis (PrEP) for the Prevention of HIV Infection: PrEP for injecting drug users. MMWR Morb Mortal Wkly Rep 62(23):463–465 Eysenbach G (2004) Improving the quality of Web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). J Med Internet Res 6(3):e34–e Alaa A, Mujong D, Lakhani S, Alter M, El-Osta A (2024) Investigating the Potential Accessibility to HIV Pre-Exposure Prophylaxis viaCommunity Pharmacies and Sexual Health Clinics. A Scoping Review of Two Integrated Care Systems in London Mayer KH, Chan PA, Flash RRP, Krakower CA (2018) Evolving Models and Ongoing Challenges for HIV Preexposure Prophylaxis Implementation in the United States. J Acquir Immune Defic Syndr 77(2):119–127 Sun Z, Gu Q, Dai Y et al (2022) Increasing awareness of HIV pre-exposure prophylaxis (PrEP) and willingness to use HIV PrEP among men who have sex with men: a systematic review and meta-analysis of global data. J Int AIDS Soc 25(3):e25883 Harrison C, Family H, Kesten J et al (2024) Facilitators and barriers to community pharmacy PrEP delivery: a scoping review. J Int AIDS Soc 27(3):e26232 Alter M, Lakhani S, Alaa A, Karki M, Riboli-Sasco E, El-Osta A (2025) Investigating facilitators and barriers to the routine provision of HIV PrEP in community pharmacies in London. BMC Health Serv Res 25(1):312 Rathbone A, Cartwright N, Cummings L et al (2024) Exploring young people’s attitudes to HIV prevention medication (PrEP) in England: a qualitative study. BMJ Open 14(3):e077733 Committee HoCHaSC (2024) Pharmacy Third Report of Session 2023-24 Eaton LA, Kalichman SC, Price D, Finneran S, Allen A, Maksut J (2017) Stigma and Conspiracy Beliefs Related to Pre-exposure Prophylaxis (PrEP) and Interest in Using PrEP Among Black and White Men and Transgender Women Who Have Sex with Men. AIDS Behav 21(5):1236–1246 GOV.UK (2021) Chapter 11: Smoking and tobacco use nscot (2021) Very Brief Advice on Smoking (VBA+) Cheng CCW, He WJA, Gouda H et al (2024) Effectiveness of Very Brief Advice on Tobacco Cessation: A Systematic Review and Meta-Analysis. J Gen Intern Med 39(9):1721–1734 GOV.UK (2019) Screening and brief advice for alcohol and tobacco use in inpatient settings aidsmap. PrEP Information for young people (2024) https://www.aidsmap.com/about-hiv/prep Additional Declarations The authors declare no competing interests. Supplementary Files 3.APPENDIX.docx Appendix Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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(orange).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8466343/v1/717ffcf01ce6283d5329bcce.png"},{"id":99792396,"identity":"7e3ab911-7c14-436b-a43c-f8c1e2236b88","added_by":"auto","created_at":"2026-01-08 13:19:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":781484,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJoint correspondence analysis (JCA) of socio-demographic characteristics among NHS survey respondents.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8466343/v1/da5ff5176ba8859320bff83b.png"},{"id":99804102,"identity":"2784a8ba-a8de-43cc-8b98-a8df9a86bd8e","added_by":"auto","created_at":"2026-01-08 14:11:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2433373,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8466343/v1/2c317796-6c2c-429c-9a45-164fb996b132.pdf"},{"id":99792964,"identity":"d5c7a64e-8f53-41d9-8ddd-9408b5919a6e","added_by":"auto","created_at":"2026-01-08 13:30:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":351734,"visible":true,"origin":"","legend":"\u003cp\u003eAppendix\u003c/p\u003e","description":"","filename":"3.APPENDIX.docx","url":"https://assets-eu.researchsquare.com/files/rs-8466343/v1/13badff02c24c06cda85439a.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePublic attitudes toward pharmacy-based HIV PrEP in the UK: a national cross-sectional study of 15,000 NHS patients\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Research in context","content":"\u003cp\u003e\u003cstrong\u003eEvidence before this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe searched PubMed, Embase and Google Scholar for studies published between Jan 1, 2012 and Jan 1, 2023, using combinations of “HIV pre-exposure prophylaxis”, “PrEP”, “community pharmacy”, “public attitudes” and “United Kingdom”. Previous research has established PrEP as a highly effective HIV prevention tool, but uptake in the UK remains uneven and largely concentrated among men who have sex with men (MSM). Several pilot programmes in high-income countries have shown that pharmacies can deliver PrEP, yet studies of public acceptability are scarce. UK-based work has mostly focused on key populations, with little evidence on attitudes across the wider public. No large-scale UK study has examined general population awareness and support for pharmacy-based PrEP delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdded value of this study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis national survey of over 15,000 NHS patients is the largest UK general population study to explore awareness, attitudes and acceptability of PrEP delivery through community pharmacies. By combining multivariable regression with joint correspondence analysis, we go beyond descriptive reporting to identify intersectional clusters of demographic identities and attitudinal profiles. We show that awareness remains low among women, heterosexual individuals and older adults, but that a majority of the public support pharmacy-based provision, particularly younger, sexually diverse and non-binary respondents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications of all the available evidence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings demonstrate that pharmacies represent an underutilised \u0026nbsp;but viable \u0026nbsp;access point for PrEP in the UK. Expanding PrEP delivery beyond sexual health clinics to community pharmacies could normalise use, reduce stigma and advance equity in HIV prevention. Implementation should focus on raising awareness in underinformed groups and equipping pharmacies with the regulatory authority, training and infrastructure to deliver safe and effective PrEP services as part of the UK’s HIV elimination strategy.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003ePre-exposure prophylaxis (PrEP) is a highly effective HIV prevention strategy involving the use of antiretroviral medication by HIV-negative individuals to reduce the risk of infection.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Clinical trials and real-world evidence consistently demonstrate that PrEP can reduce HIV transmission by more than 90% when taken as prescribed.\u003csup\u003e​\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e​Although the number of individuals receiving PrEP globally rose by 35% from 2022 to 2023, uptake remains well below the UNAIDS target of 10\u0026nbsp;million users by 2025.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e This gap highlights that many at-risk populations including heterosexual individuals, women, people who inject drugs and those from Black African and other underserved communities may not yet be benefiting from PrEP. In the UK, PrEP has been available from sexual health services since 2020 following the NHS' decision to fund it for high-risk populations.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Despite this, 65% of individuals who want PrEP in England cannot access the prophylaxis and 57% of those who could obtain PrEP had to wait over 12 weeks for an appointment.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Additionally, initiation or continuation of PrEP among those with a PrEP need in England was highest in gay, bisexual and men who have sex with men (MSM) at 75\u0026middot;4% compared to only 39\u0026middot;0% in heterosexual men and 40\u0026middot;9% in heterosexual and bisexual women.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBarriers to PrEP uptake include lack of awareness\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, perceived stigma\u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and the misconception that PrEP is only for certain populations such as men who have sex with men (MSM).\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Structural barriers, including the cost of PrEP\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e when not covered by health services and difficulty accessing sexual health clinics\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e further complicate PrEP uptake​. In the UK, public knowledge of PrEP remains low, even among high-risk groups.\u003csup\u003e(18)\u003c/sup\u003e Recent findings highlight that inequities in PrEP access persist due to a failure to scale provision beyond specialist sexual health services.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e This study called for urgent exploration of alternative delivery models, particularly in primary care \u0026amp; community pharmacy, yet no large-scale studies have assessed public perceptions of these routes in the general population.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhile sexual health clinics (SHCs) remain the primary access point for PrEP, recent discussions have highlighted the potential for alternative delivery models to improve access.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Community pharmacies, due to their wide reach, accessibility and the trusted role of pharmacists in healthcare, are a potential setting for PrEP provision.​\u003csup\u003e22,23\u003c/sup\u003e The pervasiveness of community pharmacies is high and many are often located in areas underserved by sexual health services. Community pharmacies are therefore well placed to potentially mitigate many logistical barriers to accessing PrEP such as limited clinic hours or geographic distance; thereby expanding access to at-risk populations. The competent and highly respected pharmacy workforce has the potential to play a crucial role in disseminating health information, reducing stigma associated with HIV prevention and facilitating adherence to PrEP regimens.\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGlobally, there are examples of pharmacies successfully offering a sexual health advisory services, including contraceptive advice and HIV testing࿼࿼ ​ In the US, -pharmacy-based PrEP delivery models have reduced barriers to access, yet the evidence base remains limited࿼࿼ \u003csup\u003e​\u003c/sup\u003e To date, no large-scale studies in the UK have explored the potential for pharmacies to provide PrEP, despite the growing recognition of this approach\u0026rsquo;s feasibility࿼࿼ Understanding the attitudes, beliefs and potential public concerns regarding pharmacy-based PrEP provision is essential for informing future health policies aimed at increasing access. Moreover, existing research has largely focused࿼࿼, with limited attention to other populations who could benefit from PrEP, including heterosexual individuals, women, people who inject drugs and those from diverse cultural backgrounds​ - specifically Black African.\u003c/p\u003e \u003cp\u003eTo date, most research on PrEP acceptability has focused on specific key populations (such as men who have sex with men) or small-scale pilot studies of pharmacy delivery. Large-scale general population surveys remain rare, particularly in the UK and existing evidence is fragmented across narrow demographic groups. Our study addresses this gap by surveying more than 15,000 NHS patients nationwide, the largest general population dataset on PrEP awareness and attitudes in the UK and by combining multivariable regression with joint correspondence analysis. This dual analytic approach provides both robust estimates of demographic predictors and a visual mapping of intersectional identity clusters that shape PrEP attitudes. By integrating scale with intersectional insight, our study moves beyond descriptive surveys to offer a population-level evidence base for pharmacy-led PrEP expansion.\u003c/p\u003e \u003cp\u003eThe aim of this study was to examine public perceptions of PrEP and its potential availability in community pharmacies. Specifically, we sought to (i) assess levels of awareness and knowledge about PrEP among the general public within the UK, (ii) identify primary barriers and facilitators that affect access to PrEP particularly through community pharmacies. The study also sought to examine demographic differences in use of PrEP and public awareness of PrEP as a prophylactic and the public attitudes towards (a) seeking information for PrEP and (b) accessing PrEP from community pharmacy; with attention to differences among participants of different gender, sexual orientation and educational background.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eWe conducted a UK-wide cross-sectional study to assess public awareness, attitudes and perceptions regarding HIV PrEP, with a particular focus on community pharmacy-based provision. The survey was administered online using the Imperial College Qualtrics XM platform, open from 29 October 2022 to 29 October 2023. Participants were recruited via NHS general practices through Short Messaging Service (SMS) invitations, which included a link to the electronic survey and a participant information sheet. Additional dissemination occurred through personal and professional networks.\u003c/p\u003e \u003cp\u003eParticipation was voluntary and anonymous. Respondents were eligible if they were adults (\u0026ge;\u0026thinsp;18 years) residing in the UK. Completion of the survey implied informed consent. Data were stored securely at Imperial College London and pseudo-anonymised using unique identifiers.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSurvey instrument\u003c/h3\u003e\n\u003cp\u003eThe survey consisted of 28 questions, including demographic characteristics (age, gender, ethnicity, education, sexuality, relationship status, region), awareness and attitudes towards PrEP and preferences for obtaining PrEP. Questions were informed by existing literature and refined through expert review and cognitive interviews with public health and HIV prevention specialists, including advisors from the Terrence Higgins Trust. The final version was piloted for clarity and internal consistency.\u003c/p\u003e \u003cp\u003eMost items were closed-ended and conditional based on prior responses. To minimise duplication, respondents were prevented from completing the survey more than once using Qualtrics cookies and digital fingerprinting. Technical functionality was tested prior to launch. The survey (\u003cb\u003eAppendix p 2\u0026ndash;15\u003c/b\u003e) was accessible using a personal computer or smartphone.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarise participant characteristics and key outcomes. Attitudinal questions were summarised by calculating the proportion of respondents who either agreed or strongly agreed with each statement. Univariable and multivariable logistic regression models assessed associations between demographic variables and (i) awareness of PrEP, (ii) use of PrEP, (iii) interest in learning about PrEP and (iv) attitudes toward pharmacy-based access. Multivariable models adjusted for age, gender, sexuality, ethnicity, education and relationship status. Results are presented as adjusted odds ratios with 95% confidence intervals (CI).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eJoint Correspondence Analysis\u003c/h3\u003e\n\u003cp\u003eTo explore patterns of association across key socio-demographic variables, we conducted a Joint Correspondence Analysis (JCA) using five categorical variables: gender, age group, ethnicity, sexual orientation and relationship status. This technique allows for the visualisation of latent structures in multivariate categorical data by projecting category-level coordinates onto two principal dimensions. The JCA was conducted using principal normalisation and results were displayed as a joint correspondence plot. As Dimension 1 and Dimension 2 explained 59\u0026middot;2% and 20\u0026middot;2% of the total inertia respectively, they together accounted for 79\u0026middot;4% of the variance in the data. This analysis enabled identification of subgroups with similar demographic patterns.\u003c/p\u003e \u003cp\u003e We selected JCA over multiple correspondence analysis (MCA) and latent class analysis (LCA) because our aim was to visualise relationships between socio-demographic categories and attitudinal outcomes simultaneously, rather than to reduce data dimensionality alone with MCA, or to assign participants to latent groups probabilistically. This JCA approach generates an interpretable biplot that complements regression results by showing how identity characteristics cluster together, thereby providing a transparent and intersectional lens on attitudinal variation across the population.\u003c/p\u003e \u003cp\u003eStatistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0\u0026middot;05. Analyses were conducted using Stata version 17 (StataCorp, College Station, TX, USA). The Checklist for Reporting Results of Internet ESurveys (CHERRIES)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e was used to guide reporting; \u003cb\u003eAppendix p16-17\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eEthics\u003c/h3\u003e\n\u003cp\u003eEthical approval was obtained from the NHS Research Ethics Committee (REC#22/LO/0289) and the Health Research Authority (HRA #3043648; CPMS ID 52576). All procedures complied with the Declaration of Helsinki and institutional guidelines.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient and public involvement\u003c/h2\u003e \u003cp\u003ePatient and public involvement including the development of the survey was supported by the Terrence Higgins Trust, a leading HIV and sexual health charity in the UK. Their input was instrumental in ensuring the relevance, appropriateness and inclusivity of survey items. The questionnaire underwent expert review, including feedback from public health professionals and HIV prevention specialists and was refined through a pilot phase that included cognitive interviewing and beta testing with a diverse group of individuals. This process helped to optimise the clarity, flow and cultural sensitivity of the survey before full-scale deployment.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eWe collected data from 15,071 NHS patients across England.\u003c/p\u003e\n\u003ch3\u003eParticipant characteristics\u003c/h3\u003e\n\u003cp\u003eThe mean age was 47\u0026middot;8 years (SD 16\u0026middot;2); 54\u0026middot;2% identified as female (including trans women), 38\u0026middot;9% as male (including trans men), 1\u0026middot;1% as non-binary and 3\u0026middot;4% either preferred not to disclose or chose \u0026ldquo;other.\u0026rdquo; Most participants identified as heterosexual (76\u0026middot;9%), with smaller proportions identifying as homosexual (8\u0026middot;0%), bisexual (7\u0026middot;1%), or other identities. Over half (55\u0026middot;7%) had a university degree or higher. Ethnically, the cohort was predominantly White (81\u0026middot;2%), with representation from Asian (7\u0026middot;1%), Black (3\u0026middot;8%), Mixed (3\u0026middot;5%) and other ethnic groups (1\u0026middot;6%); Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRespondent characteristics (N\u0026thinsp;=\u0026thinsp;15,071)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, mean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u0026middot;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(16\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in categories, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e[25\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(34\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e[45\u0026ndash;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,757\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(38\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(16\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (including trans woman)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(54\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (including trans man)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(38\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-binary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (please specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA level / college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(25\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school / high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(16\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(55\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelationship status, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried / partnered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(47\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn a domestic relationship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(26\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(81\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian, Asian British or Asian Welsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack, Black British, Black Welsh, Caribbean or African\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed or Multiple ethnic groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther ethnic group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexuality, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(76\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (please specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePansexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast Midlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(32\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEast of England\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Thames (London)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West Coast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West London\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThames Valley and South Midlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMain survey findings\u003c/h2\u003e \u003cp\u003eThe results of the main survey are shown in \u003cb\u003eAppendix p18-21\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrEP Awareness and use\u003c/h2\u003e \u003cp\u003eAmong respondents, 66\u0026middot;9% were unaware that PrEP prevents HIV and only 1\u0026middot;8% had used it. Of those aware of PrEP (n\u0026thinsp;=\u0026thinsp;5,609), only 13\u0026middot;4% had ever considered using it and 8\u0026middot;0% reported current or past use. Awareness was highest among younger, male, non-heterosexual and more highly educated participants.\u003c/p\u003e \u003cp\u003ePrEP information was predominantly derived from sexual health clinics (16\u0026middot;1%) and healthcare professionals (15\u0026middot;0%), while only 1\u0026middot;3% had heard of PrEP from pharmacists. Among respondents interested in learning more about PrEP (63\u0026middot;5%), healthcare professionals (62\u0026middot;9%) and sexual health clinics (38\u0026middot;2%) were their preferred sources; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrEP Awareness among the study participants (N\u0026thinsp;=\u0026thinsp;15,071)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHave you ever heard about PrEP?\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(37\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(62\u0026middot;8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(100\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHow did you hear about PrEP? Please select one or more\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriend or family member\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelevision / radio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(27\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media / online forums\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(25\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare professional / doctor / GP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual health clinic / organisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(16\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGBTQI\u0026thinsp;+\u0026thinsp;organisation/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(19\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican organization/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(17\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAre you aware that PrEP could help to prevent being infected with HIV?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(31\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(66\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWould you be interested in seeking information about PrEP?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(63\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(36\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhere would you most likely seek more information regarding PrEP?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFriend or family member\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTelevision / radio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(5\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media / online forums\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(22\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare professional / doctor / GP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(62\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexual health clinic / organisation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(38\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGBTQI\u0026thinsp;+\u0026thinsp;organisation/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(9\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican organization/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI have enough information to take PrEP safely \u0026amp; effectively\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly agree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(11\u0026middot;2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeither agree nor disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(32\u0026middot;0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(25\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI would be happy to obtain PrEP if it were available from my local pharmacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly agree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(20\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(30\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeither agree nor disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(31\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4\u0026middot;5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4\u0026middot;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eI would feel comfortable to getting information about PrEP from pharmacist/pharmacy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly agree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(40\u0026middot;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeither agree nor disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(18\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8\u0026middot;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrongly disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(5\u0026middot;1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDid not answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(5\u0026middot;4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAttitudes toward pharmacy-based provision\u003c/h2\u003e \u003cp\u003e Overall, 60\u0026middot;8% supported access to PrEP through community pharmacies, with 30\u0026middot;1% agreeing and 30\u0026middot;7% strongly agreeing. A similar proportion (62\u0026middot;8%) reported feeling comfortable discussing PrEP with pharmacists. Pharmacies were rated the most convenient access point by 51\u0026middot;2% of respondents, ahead of sexual health clinics (18\u0026middot;6%) and online sources (40\u0026middot;4%). Support for pharmacy-based provision was significantly higher among younger adults, non-heterosexual participants and those with higher educational attainment. Participants who were married, older or from certain ethnic groups were less likely to express support.\u003c/p\u003e \u003cp\u003eFactors affecting the participant\u0026rsquo;s decision in accessing PrEP are shown in \u003cb\u003eAppendix Fig.\u0026nbsp;1 (p22).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eBarriers to PrEP uptake\u003c/h2\u003e \u003cp\u003eCommonly reported barriers included lack of awareness (35\u0026middot;7%), insufficient information (32\u0026middot;0%), concerns about side effects (19\u0026middot;1%) and concerns about cost (44\u0026middot;5%). Cultural or religious conflict was cited by 10\u0026middot;1% and 23\u0026middot;1% reported stigma as a barrier.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of PrEP use, awareness and pharmacy support\u003c/h2\u003e \u003cp\u003eMultivariable analysis showed that current/past PrEP use was significantly associated with male gender (aOR\u0026thinsp;=\u0026thinsp;9\u0026middot;26, 95% CI; 6\u0026middot;22, 13\u0026middot;76), non-binary identity (aOR\u0026thinsp;=\u0026thinsp;4\u0026middot;02, 95% CI; 1\u0026middot;89, 8\u0026middot;94) and homosexual (aOR\u0026thinsp;=\u0026thinsp;48\u0026middot;24, 95% CI; 33\u0026middot;39, 69\u0026middot;68) or bisexual (aOR\u0026thinsp;=\u0026thinsp;16\u0026middot;64, 95% CI; 10\u0026middot;78, 25\u0026middot;68) orientation. PrEP awareness was higher among those aged\u0026thinsp;\u0026lt;\u0026thinsp;45, non-White ethnic groups and university-educated individuals. Support for pharmacy access was also higher among younger adults and bisexual/pansexual participants. Full regression models are presented in \u003cb\u003eAppendix Tables\u0026nbsp;2\u0026ndash;5\u003c/b\u003e. A visual summary of demographic predictors is presented as a coefficient plot is shown \u003cb\u003ein\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e contains the results of all multivariable analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant characteristics and their association with use of PrEP, awareness of PrEP as a prophylactic, attitudes towards seeking information for PrEP and accessing PrEP from community pharmacy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUse of PrEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAwareness of PrEP\u003c/p\u003e \u003cp\u003eas prophylactic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eSeeking information\u003c/p\u003e \u003cp\u003efor PrEP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eAccessing PrEP from community pharmacy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eaOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eaOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eaOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026middot;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;15, 4\u0026middot;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u0026middot;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2\u0026middot;13, 3\u0026middot;08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026middot;07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;73, 2\u0026middot;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u0026middot;97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(2\u0026middot;24, 3\u0026middot;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e[25\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026middot;43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2\u0026middot;57, 7\u0026middot;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u0026middot;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2\u0026middot;19, 2\u0026middot;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;57, 1\u0026middot;95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(1\u0026middot;57, 2\u0026middot;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e[45\u0026ndash;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026middot;71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;57, 4\u0026middot;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;33, 1\u0026middot;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;44, 1\u0026middot;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(1\u0026middot;14, 1\u0026middot;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u0026middot;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6\u0026middot;22, 13\u0026middot;76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;07, 1\u0026middot;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;76, 0\u0026middot;89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(1\u0026middot;03, 1\u0026middot;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-binary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026middot;02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;81, 8\u0026middot;94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;05, 2\u0026middot;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;56, 1\u0026middot;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;76, 2\u0026middot;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther/Prefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026middot;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;40, 8\u0026middot;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026middot;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;72, 1\u0026middot;18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;54, 0\u0026middot;81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;45, 0\u0026middot;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;06, 2\u0026middot;34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026middot;63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;54, 0\u0026middot;74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026middot;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;86, 2\u0026middot;54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;75, 1\u0026middot;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003csup\u003e╫\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;55, 2\u0026middot;54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;27, 1\u0026middot;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026middot;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(2\u0026middot;35, 3\u0026middot;67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;61, 1\u0026middot;00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;73, 2\u0026middot;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;88, 1\u0026middot;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;15, 1\u0026middot;72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;65, 1\u0026middot;01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026middot;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;05, 3\u0026middot;81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;81, 1\u0026middot;48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;16, 2\u0026middot;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;46, 0\u0026middot;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA level/college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school/high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026middot;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;55, 1\u0026middot;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026middot;85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;74, 0\u0026middot;98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;83, 1\u0026middot;03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;96, 1\u0026middot;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;85, 1\u0026middot;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;76, 2\u0026middot;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;02, 1\u0026middot;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;89, 1\u0026middot;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexuality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u0026middot;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(10\u0026middot;78, 25\u0026middot;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(3\u0026middot;49, 4\u0026middot;61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u0026middot;09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1\u0026middot;78, 2\u0026middot;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(1\u0026middot;21, 1\u0026middot;98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u0026middot;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(33\u0026middot;39, 69\u0026middot;68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21\u0026middot;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(17\u0026middot;52, 25\u0026middot;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u0026middot;91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(3\u0026middot;29, 4\u0026middot;66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;99, 1\u0026middot;51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (please specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026middot;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;28, 18\u0026middot;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u0026middot;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;62, 2\u0026middot;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;74, 1\u0026middot;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;53, 1\u0026middot;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePansexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u0026middot;04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6\u0026middot;10, 27\u0026middot;89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u0026middot;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(3\u0026middot;07, 5\u0026middot;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u0026middot;47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(2\u0026middot;32, 5\u0026middot;19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u0026middot;04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(1\u0026middot;13, 3\u0026middot;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026middot;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3\u0026middot;04, 14\u0026middot;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1\u0026middot;20, 1\u0026middot;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;98, 1\u0026middot;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;83, 1\u0026middot;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelationship status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn a domestic relationship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried / partnered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026middot;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;47, 0\u0026middot;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026middot;83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;75, 0\u0026middot;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;56, 0\u0026middot;69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026middot;001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;75, 0\u0026middot;99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0\u0026middot;92, 3\u0026middot;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;88, 1\u0026middot;46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u0026middot;72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;58, 0\u0026middot;90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u0026middot;89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;66, 1\u0026middot;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026middot;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1\u0026middot;18, 2\u0026middot;01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026middot;01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u0026middot;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0\u0026middot;99, 1\u0026middot;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u0026middot;09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u0026middot;09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0\u0026middot;79, 1\u0026middot;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u0026middot;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u0026middot;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0\u0026middot;94, 1\u0026middot;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u0026middot;22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e*Includes Asian British or Asian Welsh, \u003csup\u003e╫\u003c/sup\u003eIncludes Black British, Black Welsh, Caribbean or African\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eJoint correspondence analysis\u003c/h2\u003e \u003cp\u003eWe used Joint Correspondence Analysis (JCA) to examine the latent structure of socio-demographic patterns: gender identity, age group, ethnicity, sexual orientation and relationship status. The resulting biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) displays category-level associations across two principal dimensions, which together explained 79\u0026middot;4% of the total variance (Dimension 1\u0026thinsp;=\u0026thinsp;59\u0026middot;2%; Dimension 2\u0026thinsp;=\u0026thinsp;20\u0026middot;2%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCategories of age, gender, sexuality, ethnicity and relationship status are plotted in a two-dimensional space (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Dimension 1 (59\u0026middot;2% inertia) separates a traditional cluster of older, heterosexual, married respondents from a diverse cluster of younger, non-binary and sexually diverse respondents, while Dimension 2 (20\u0026middot;2% inertia) reflects secondary variation by gender and relationship status.\u003c/p\u003e \u003cp\u003eDimension 1 (horizontal axis) shows a strong polarity between two demographic groupings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). On the left, a traditional cluster emerged comprising older (\u0026ge;\u0026thinsp;45 years), White, heterosexual, married men. On the right, a more diverse cluster appeared, including younger (\u0026lt;\u0026thinsp;25 years), non-binary participants, bisexual or pansexual respondents and those who were single or in a relationship. This separation reflects contrasting identity profiles aligned with differences in PrEP awareness and receptivity to pharmacy-based provision, consistent with regression findings.\u003c/p\u003e \u003cp\u003eDimension 2 (vertical axis) adds further separation by age and gender. Younger women in relationships were located in the upper-right quadrant, whereas older men and non-normative gender groups clustered in the lower-left quadrant. Female participants and those in domestic relationships occupied more central positions, suggesting mixed profiles bridging traditional and non-traditional identities.\u003c/p\u003e \u003cp\u003eOverall, the JCA visually reinforces the regression analyses by showing how intersecting demographic characteristics form distinct clusters linked to PrEP-related knowledge, attitudes and access preferences. The analysis highlights clear demographic patterning in PrEP awareness, interest and support for pharmacy-based provision, emphasising the value of intersectional approaches when designing targeted outreach and considering community pharmacy as a low-threshold access point.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this is the largest UK general population study examining public awareness and acceptability of PrEP and the first to apply joint correspondence analysis alongside regression modelling to capture intersectional attitudinal patterns. Whereas previous studies have provided either broad descriptive snapshots or small-scale evaluations of pharmacy feasibility, our findings uniquely demonstrate how demographic clusters align with divergent PrEP attitudes at scale. This methodological combination allows us to map both who remains excluded from PrEP messaging and who shows highest receptivity to decentralised access models, offering a new lens for policy and service planning.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal findings\u003c/h2\u003e \u003cp\u003eDespite national commitments to end new HIV transmissions by 2030, fewer than one in three respondents (30\u0026middot;7%) reported awareness of PrEP. Awareness was lowest among older adults, heterosexual individuals and women, groups not traditionally targeted by PrEP campaigns, yet still at potential risk and critical to the equity of the HIV prevention response. Numerous responses highlighted issues related to the physical accessibility of sexual health clinics, including limited clinic locations and restricted appointment availability in line with our previous study.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e This includes challenges in booking appointments that fit work schedules and the general scarcity of SHCs. Importantly, we found strong latent demand; nearly two-thirds of respondents expressed interest in learning more about PrEP and half supported pharmacy-based provision. This suggests a readiness among the public for expanded, decentralised PrEP delivery models beyond specialist sexual health services.\u003c/p\u003e \u003cp\u003eThe Joint Correspondence Analysis reinforced and extended these insights by highlighting distinct demographic subpopulations with divergent PrEP attitudes. A traditional cluster (comprising older, heterosexual, White, male participants who were married or partnered) occupied one end of the identity spectrum and was associated with the lowest levels of awareness, interest and support. In contrast, a younger, diverse cluster (featuring non-binary individuals, bisexual and pansexual respondents and those under the age of 25, consistently aligned with higher awareness, greater interest and stronger endorsement of community pharmacy as a PrEP access point. These two groupings, visualised through the JCA biplot, captured a striking polarity in engagement with PrEP, illustrating how intersectional identities drive differentiated risk perception, trust in health services and openness to novel service models.\u003c/p\u003e \u003cp\u003eCollectively these findings point to a mismatch between those who currently access PrEP and those who express willingness to use it if made more accessible, particularly via pharmacies. Community pharmacy, as a widely distributed and often underused touchpoint, holds unique potential to bridge this gap, provided that services are designed inclusively and with attention to the structural and cultural barriers that shape uptake.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eComparison to existing literature\u003c/h2\u003e \u003cp\u003eOur findings align with previous research highlighting the underuse of PrEP globally​. Earlier studies \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e similarly report that barriers like stigma, cost and lack of information contribute to suboptimal PrEP uptake. Our findings also align with and extend prior research on PrEP delivery through non-traditional settings whilst also highlighting pharmacists\u0026rsquo; confidence and infrastructure limitations.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Our study complements these insights by revealing from the general public\u0026rsquo;s perspective both latent demand and demographic divergence, specifically that younger and gender/sexuality-diverse groups are substantially more supportive of pharmacy-based models. More recent pharmacy staff surveys in London have reported readiness to offer PrEP, contingent on additional training and facility enhancements.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e This echoes our JCA finding that traditional groups (older, heterosexual, male, married individuals) are less engaged, suggesting that pharmacist-led initiatives must address both provider and public confidence, especially among populations less familiar with PrEP. Our latent-profile findings also resonate with qualitative studies of youth attitudes in England, which highlight strong interest and openness to PrEP when framed in non-clinic environments.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e The clear polarity we observed via JCA (traditional vs. progressive clusters) mirrors discourses around stigma and trust; younger, sexually minoritised respondents cluster with high support for decentralised care, reinforcing themes seen in social science research on sexual health empowerment.\u003c/p\u003e \u003cp\u003eThe findings also build on calls by the UK Parliament to commission pharmacies for PrEP delivery as part of broader clinical-service expansion.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e By demonstrating public acceptability across diverse groups-and identifying clusters with particularly high receptivity-our data provide empirical foundations to inform policy decisions, beyond pilot or advocacy-driven models.\u003c/p\u003e \u003cp\u003eThat healthcare professionals are a primary source of PrEP information is consistent with earlier studies \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e​\u003c/sup\u003e emphasising the unrealised potential of pharmacists in providing information about PrEP in the UK, contrasting to the more established pharmacy-based PrEP models in the US​.\u003c/p\u003e \u003cp\u003eFinally, the intersectional approach using JCA supplies a novel quantitative complement to individual-level analyses. Unlike surveys that primarily report overall acceptability, our study maps engagement across intersecting demographic axes (age, gender, sexuality, ethnicity, relationship status) highlighting target groups for tailored messaging and service design.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIntersectional patterns in PrEP attitudes: insights from joint correspondence analysis\u003c/h2\u003e \u003cp\u003eThe joint correspondence analysis highlighted distinct demographic clusters shaping awareness and support for PrEP. A \u0026ldquo;traditional\u0026rdquo; cluster (of older, heterosexual, White men in partnered relationships) was consistently associated with the lowest levels of awareness and receptivity. In contrast, a younger and more diverse cluster (of non-binary, bisexual or pansexual individuals, often single and from mixed or minority ethnic backgrounds) showed markedly higher awareness, interest and endorsement of pharmacy-based access.\u003c/p\u003e \u003cp\u003eThese patterns emphasise that age, gender, sexuality and relationship status interact to create compound influences on HIV prevention attitudes. Awareness campaigns and delivery models that treat these factors in isolation risk overlooking the intersectional drivers of both engagement and exclusion. The findings also suggest that expanding PrEP beyond sexual health clinics to community pharmacies could particularly benefit populations already predisposed to innovation in care access, namely younger, sexually diverse and gender-diverse individuals.\u003c/p\u003e \u003cp\u003eConversely, the traditional cluster\u0026rsquo;s lower awareness and weaker support point to enduring gaps in outreach, stigma reduction and message framing. Tailored interventions for older and heterosexual men, emphasising prevention and equity rather than risk categorisation, will be necessary to avoid widening disparities.\u003c/p\u003e \u003cp\u003eBy linking demographic identity patterns to attitudinal differences, the analysis provides an empirical foundation for precision targeting in HIV prevention indicating where pharmacy-based PrEP may gain fastest uptake and where focused education is most needed. This intersectional perspective moves beyond demographic enumeration to show how social identity structures shape readiness for new delivery models and, ultimately, the reach of the HIV prevention agenda.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eImplications for policy and practice\u003c/h2\u003e \u003cp\u003eThree priorities emerge from these findings. First, PrEP awareness must expand beyond groups traditionally targeted by HIV prevention. Heterosexuals, women, older adults and racially minoritised populations remain poorly informed despite national availability. Public health messaging should normalise PrEP as a universal prevention option, using trusted channels in primary care, community settings and digital media rather than focusing primarily on men who have sex with men.\u003c/p\u003e \u003cp\u003eSecond, pharmacies are an underused but publicly supported access point since over 60% of respondents endorsed pharmacy-based provision, indicating readiness for decentralised models. Realising this requires regulatory change to enable pharmacist prescribing and monitoring supported by training, HIV/STI screening pathways and integration with NHS digital records. Consistent national commissioning is essential to avoid regional variation whereas pharmacy-led services should include referral routes for confirmatory testing, renal monitoring and adherence support to maintain clinical quality.\u003c/p\u003e \u003cp\u003eThird, implementation must be grounded in intersectional equity. JCA indicated that younger, sexually diverse and gender-diverse groups are most receptive to pharmacy access, whereas older heterosexual men are least engaged. Commissioning should therefore combine universal availability with targeted outreach to populations at risk of exclusion. Embedding these principles within the NHS HIV-elimination strategy could normalise PrEP, reduce stigma and narrow prevention gaps. Pharmacy-led access should be paired with campaigns that build awareness and trust while ensuring linkage to care, adherence monitoring and safety oversight, thus aligning service delivery with the UK\u0026rsquo;s 2030 goal to end new HIV transmissions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe principal limitation of this study is the cross-sectional design which prevents causal inference between demographic factors and PrEP awareness or attitudes. Although the sample was large and diverse, the survey was available only in English and participants were disproportionately highly educated (56% with university degrees), which may limit generalisability to populations with lower health literacy. Recruitment through NHS practices and online methods likely underrepresented people with limited digital access or weaker links to primary care, groups that may face additional barriers to PrEP uptake. Further, because baseline awareness of PrEP was low, responses regarding acceptability or intent may reflect limited knowledge rather than stable attitudes. Self-selection bias cannot be excluded and survey responses may not translate into real-world behaviour. The Joint Correspondence Analysis provided valuable insight into intersectional patterns but remains exploratory and descriptive; interpretation of clusters should therefore be cautious. Although these limitations constrain representativeness and causal inference, the breadth of the sample and use of complementary analytic methods strengthen confidence in the robustness and policy relevance of the findings.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eFuture research directions\u003c/h2\u003e \u003cp\u003eThis study highlights several key priorities for future research to support equitable and scalable PrEP implementation. Particular attention should be given to evaluating the feasibility and effectiveness of delivering very brief advice (VBA) on PrEP during routine health and care interactions.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Such touchpoints, including GP consultations, pharmacy visits\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, sexual health screenings, contraceptive counselling and chronic disease reviews, are opportunities to engage individuals who may benefit from PrEP but remain unaware or underserved. Evidence from other domains, such as smoking cessation and alcohol reduction, demonstrates that VBA can be an effective and scalable intervention within primary care and community settings.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Applying this approach to HIV prevention could help normalise PrEP discussions and reduce stigma associated with its use. Future studies should explore the acceptability of VBA on PrEP from both provider and patient perspectives, assess outcomes such as PrEP uptake or referrals and investigate the role of tailored messaging based on individual risk, cultural context, or health literacy level.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Research should also examine how PrEP-related prompts or decision aids can be integrated into electronic health records to support consistent, targeted delivery across care pathways. Future work should assess the impact of tailored communication strategies including digital campaigns, peer outreach and community-led messaging on PrEP awareness among underserved groups such as racially minoritised populations, women, older adults and those in rural or deprived areas.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eDespite national PrEP availability, public awareness remains low, particularly among heterosexuals, women, older adults and racially minoritised groups. Yet support for pharmacy-based provision is strong, especially among younger and sexually diverse populations. This mismatch between need, awareness and access highlights an urgent opportunity: expanding PrEP through community pharmacies could reduce barriers, normalise use and advance equity. Achieving this will require targeted public education, pharmacist training and intersectional implementation strategies that centre inclusion and trust. Without such action, the benefits of PrEP will remain inequitably distributed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAEO conceptualised the study and was involved in study development, methodology, interpretation, writing the original manuscript draft and reviewing and editing the manuscript. EB was involved in methodology, data analysis, verification and interpretation and writing, reviewing and editing the manuscript. AA was involved in project administration, data collection, data curation, extraction and verification. \u0026nbsp;MA and SL conceptualised the study and were involved in reviewing and editing the manuscript. SOS, AS, and DM were involved in data interpretation and reviewing and editing the manuscript. RB and AM were involved in reviewing and editing the manuscript. \u0026nbsp;AEO, EB and AA had full access to and verified the data. All authors have read and approved the final version of the manuscript. This article is published under a CC BY 4.0 licence. AEO is the guarantor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDe-identified survey data and analysis code will be made available upon reasonable request to the corresponding author following institutional data access procedures at Imperial College London.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Barrie Dwyer and the Terrence Higgins Trust for providing feedback on the data collection tool and for disseminating the survey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.Austen El-Osta and Azeem Majeedare supported by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration (ARC) North West London. The views expressed are those of the authors and not necessarily those of the NHS or the NIHR or the Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eX:\u0026nbsp;\u003c/strong\u003e@austenelosta @ImperialSCARU\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganization WHO HIV/ AIDS - Pre-exposure prophylaxis. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/hiv/topics/prep/en/\u003c/span\u003e\u003cspan address=\"https://www.who.int/hiv/topics/prep/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHIV.Gov, Pre-Exposure Prophylaxis (2020) 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.hiv.gov/hiv-basics/hiv-prevention/using-hiv-medication-to-reduce-risk/pre-exposure-prophylaxis\u003c/span\u003e\u003cspan address=\"https://www.hiv.gov/hiv-basics/hiv-prevention/using-hiv-medication-to-reduce-risk/pre-exposure-prophylaxis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeRPWatch, United Kingdom (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.prepwatch.org/country/united-kingdom/\u003c/span\u003e\u003cspan address=\"https://www.prepwatch.org/country/united-kingdom/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNHS England (2015) Clinical Commissioning Policy: Treatment as Prevention (TasP) in HIV infected adults\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNIAIDS (2024) 2024 global AIDS report\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez M, Dong B (2020) Implementing PrEP in the pharmacy. 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PrEP Information for young people (2024) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aidsmap.com/about-hiv/prep\u003c/span\u003e\u003cspan address=\"https://www.aidsmap.com/about-hiv/prep\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Imperial College London","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HIV pre-exposure prophylaxis (PrEP), Community pharmacy, Public perceptions, PrEP uptake, Healthcare accessibility, HIV prevention strategies, Barriers to PrEP, PrEP facilitators, Stigma, Health equity","lastPublishedDoi":"10.21203/rs.3.rs-8466343/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8466343/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHIV pre-exposure prophylaxis (PrEP) is highly effective, yet uptake in the UK remains suboptimal. Community pharmacies could be accessible venues for PrEP delivery but public acceptability is poorly understood. We examined awareness, attitudes and support for pharmacy-based provision among NHS patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a national cross-sectional online survey of 15,071 adults recruited through general practices in England (October 2022-October 2023). The questionnaire captured demographics, PrEP awareness, attitudes and preferences for access. Descriptive statistics, multivariable logistic regression and joint correspondence analysis (JCA) were used to assess predictors of PrEP awareness and support for pharmacy-based delivery.\u003c/p\u003e\u003ch2\u003eFindings\u003c/h2\u003e \u003cp\u003eOverall, 37\u0026middot;2% of all respondents had heard of PrEP only 1\u0026middot;8% reported use and 66\u0026middot;9% did not know that PrEP can prevent HIV. Awareness was lower among heterosexual individuals (adjusted odds ratio [aOR] 0\u0026middot;36, 95% CI 0\u0026middot;31, 0\u0026middot;42), women (aOR 0\u0026middot;56, 0\u0026middot;49, 0\u0026middot;65) and older adults (\u0026ge;\u0026thinsp;65 years: aOR 0\u0026middot;41, 0\u0026middot;33, 0\u0026middot;51). Nearly two-thirds (63\u0026middot;5%) expressed interest in learning more about PrEP. Pharmacies were rated the most convenient access point by 51\u0026middot;2% of respondents and 60\u0026middot;8% supported pharmacy-based provision. JCA revealed a polarity between a \u0026ldquo;traditional\u0026rdquo; cluster (older, heterosexual, White, partnered men; low awareness and support) and a \u0026ldquo;diverse\u0026rdquo; cluster (younger, non-binary, bisexual or pansexual, single individuals; high awareness and support).\u003c/p\u003e\u003ch2\u003eInterpretation\u003c/h2\u003e \u003cp\u003eDespite low baseline awareness, there is strong public interest in PrEP and substantial support for pharmacy-based provision. Expanding PrEP through community pharmacies could reduce access barriers and advance equity, particularly for groups underserved by sexual health clinics. These findings support policy reforms enabling pharmacists to deliver PrEP as part of the UK\u0026rsquo;s HIV elimination strategy.\u003c/p\u003e","manuscriptTitle":"Public attitudes toward pharmacy-based HIV PrEP in the UK: a national cross-sectional study of 15,000 NHS patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-06 10:51:00","doi":"10.21203/rs.3.rs-8466343/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c21953ee-b873-41ab-99d8-e037407d5342","owner":[],"postedDate":"January 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60292734,"name":"Preventive Medicine"}],"tags":[],"updatedAt":"2026-01-06T10:51:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-06 10:51:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8466343","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8466343","identity":"rs-8466343","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}