Factors associated with travel to non-local genitourinary medicine clinics for gonorrhoea: an analysis of patients diagnosed in London,2009

Abstract

We analysed factors associated with travelling to non-local genitourinary medicine clinics for gonorrhoea care in London. We used surveillance data on London residents attending genitourinary medicine clinics in 2009–10 and calculated distances between patients’ areas of residence and both the nearest genitourinary medicine clinic and the clinic attended. Non-local clinics were attended by 5408 (46.7%) patients. Men having sex with men attended non-local services more than heterosexuals (OR 3.83, p < 0.001). Among heterosexual men, black Africans and black Caribbeans were more likely, and South Asians less likely, to attend non-local services compared to whites (OR [95%CI] 1.33 [1.04–1.72], 1.36 [1.11–1.67] and 0.46 [0.31–0.70] respectively). Similar associations, although not statistically significant, were found in women. People were more likely to attend local services if their local clinic provided walk-in and young people’s services, weekend consultations and long opening hours. These findings could help design services meeting local population needs and facilitate prompt and equitable access to care.

Keywords

Sexually transmitted infection Gonorrhoea (Neisseria gonorrhoeae)Europe Epidemiology service access travel

Introduction

Sexually transmitted infections (STIs) are a major public health concern in the UK, placing a significant burden on health services.¹ Increased rates of STIs in England in the last decade have resulted in increasing pressure on genitourinary medicine (GUM) clinics, particularly in London where the rate of STIs, including gonorrhoea, is particularly high.^1,2

Specialist treatment in London is provided by 32 GUM clinics that are free of charge and freely accessible through self-referral. Timely and appropriate access to sexual health services is the cornerstone of STI prevention and control as it facilitates early treatment and partner notification, reduces individual complications and decreases risk of onward transmission.^3–5 With the likelihood of greater financial and staff constraints on sexual health services, STI control will increasingly rely on efficient services tailored to the needs of the population they serve.

Although timely GUM access has improved in the UK,⁶ patients may choose to travel beyond their local clinic for care. A study in London found that patients travel on average 7.7 km from their residence to a GUM clinic, with central London clinics serving patients from a wider catchment area than outer London clinics.⁷

Understanding how far people travel to seek care, what the characteristics are of patients likely not to seek care locally, and what service characteristics increase local service attendance (or not) is important to help improve local service design and commission local services tailored to the resident population needs.

In this study, we investigated how far patients with gonorrhoea travel to seek care in London, using individual anonymous data from all GUM clinics in London newly available through the GUM Clinical Activity Dataset (GUMCAD) surveillance system.⁸ We chose to limit our study to patients with gonorrhoea for several reasons. Given that genital infection with gonorrhoea usually presents as an acute infection, particularly in men, travel patterns are likely to represent how appropriate services respond to an urgent demand for STI care. Furthermore, although the diagnosis and treatment of STIs is increasingly being provided by local enhanced services, including contraceptive and sexual health services and primary care,⁹ most gonorrhoea diagnoses are made in GUM settings as shown by recent evidence (97% in men and 87% in women).¹⁰ The British Association for Sexual Health and HIV and Health Protection Agency (HPA) also recommend that all gonorrhoea diagnoses made in non-GUM settings are referred for confirmation, treatment and partner notification to a GUM clinic.¹¹ Given this, an analysis of those presenting with gonorrhoea at GUM clinics should provide a reasonably comprehensive picture of service access for acute STI care.

Materials and methods

Data sources

We conducted an observational study based on enhanced individual-based surveillance data, area-based (‘ecological’) census data and data on the characteristics of GUM clinics.

Data on all gonorrhoea diagnoses in London residents from 1 January 2009 to 31 December 2010 were extracted from GUMCAD, including area of residence, age, sexual orientation, ethnic group and country of birth.⁸ London residents were defined as any individual living in the former London Strategic Health Authority, which comprises a population of about 7.5 million people.¹² We excluded non-London residents attending London GUM clinics, as the aim of this study was to focus on a defined population, but considered all GUM clinics attended by London residents, including those outside of London. We also excluded episodes of repeat infections (defined as two episodes of infection in the same person >6 weeks apart) as we wanted to explore factors associated with first attendance.

Area-level covariates were obtained from the Office for National Statistics (ONS) for each of the 4765 lower super output areas (LSOA) in London. This is the smallest geographic level (median population size 1500) at which patient information is recorded in GUMCAD. To explore the influence of work patterns on service use, data on the unemployment rate and the average distance travelled to work by LSOA of residence were obtained from the 2001 census.¹³ LSOA-level deprivation was assessed using the 2010 Index of Multiple Deprivation (IMD).¹³ The IMD is an index combining seven indicators covering income, employment, education, housing, health, crime and living environment.¹⁴

For each GUM clinic, details on opening schedules, young people’s clinics and clinic type (walk-in or booked) were collected from the Internet or by telephone survey conducted in May 2011.

Definitions of outcome and explanatory variables

Outcome variables

ArcGIS 9.3 (ArcGIS 9.3, ESRI) was used to calculate straight-line distances between each patient’s LSOA’s centroid and the GUM clinic attended, as well as the nearest clinic if different. Local GUM services were defined as the nearest GUM clinic and any other GUM clinic located within a 1-km radius of the nearest clinic (Figure 1). This arbitrary threshold was used to account for the uncertainty around the use of LSOAs’ centroids as a proxy for patients’ address and the uncertainty around distance estimated through straight lines. A sensitivity analysis was also performed considering distances of 1.0 km, 1.5 km, 2.0 km and 2.5 km from the nearest GUM clinic to separate local from non-local services.

Figure 1.

Illustration of how local services were defined.

Explanatory variables

Each LSOA in London was ranked according to its IMD score and categorised into quintiles. The percentage unemployment by LSOA in London and the average distance to work were also both split into five quintiles. Quintiles of percentage unemployment were rounded up to the nearest 0.5% point for clarity.

Duration of opening for consultations was calculated by summing the weekly opening hours of each clinic, including walk-in and appointment-only sessions. This excluded consultation slots for specific conditions such as HIV care. Evening clinics were defined as those offering consultations for at least 1 h/week after 7 pm.¹⁵ Weekend clinics were defined as consultations for at least one hour every weekend. Young peoples’ clinics were consultations for at least 1 h/week dedicated to people aged ≤20 years.

Analysis

All analyses were performed in STATA Intercooled 12.0 (College Station, Texas, USA). Crude and adjusted odds ratios (ORs) for not attending local services were obtained through univariable and multivariable logistic regression analysis. Model selection was based on backwards selection of variables using a Wald test of significance at p < 0.05. Likelihood ratio tests were used to test for interaction and interaction was considered significant at p < 0.05.

Results

Descriptive analysis

A total of 12,452 gonorrhoea episodes were recorded among London residents over the two-year period. After excluding 861 repeat infections (6.9%), 11,591 cases remained for the analysis.

Patients’ median age was 27 years (range 13–78 years). Nearly three-quarters were men, of whom nearly half (45.6%) were men who have sex with men (MSM). Half of patients (50.4%) were white, 14.9% were black Caribbean, 7.0% were black African and 3.6% were South Asian, which included those of Indian, Pakistani and Bangladeshi ethnicity. Almost a third lived in the most deprived areas of London and 60% lived in LSOAs where the average distance to work was under 10 km. Further details on the study population are given in Table 1.

Table 1.

Characteristics of London residents diagnosed with gonorrhoea in GUM clinics in London between January 2009 and December 2010.

Variable	Number	% of total
Age group (years)
13–15	109	0.9
16–19	1572	13.5
20–24	2978	25.7
25–29	2544	21.9
30–34	1629	14.1
35–39	1160	10.0
40–59	1520	13.1
≥60	78	0.7
Gender
Men	8464	73.0
Women	3090	26.7
Unknown	37	0.3
Sexual orientation (men)
Heterosexual	3109	36.7
MSM	3855	45.6
Not recorded	1500	17.7
Ethnic group
White	5846	50.4
Black African	811	7.0
Black Caribbean	1733	14.9
Other black background	638	5.5
South Asian	420	3.6
Mixed Black Caribbean/White	457	4.0
All other	1124	9.7
Unknown	562	4.9
Percentage unemployed in patient’s LSOA of residence
0.0–2.4%	721	6.2
2.5–3.4%	1,244	10.7
3.5–4.4%	1,848	45.9
4.5–5.9%	3,227	27.9
6% or more	4,399	37.8
Unknown	151	1.3
Average distance to work by LSOA of residence
3.5–8.5 km	4143	35.7
8.5–9.6 km	2808	24.2
9.7–10.7 km	2016	17.4
10.8–12.0 km	1475	12.7
12.1–23.1 km	998	8.6
Unknown	151	1.3
Index of multiple deprivation (IMD) quintile
1 (most deprived)	3,639	31.4
2	3,194	27.5
3	2,316	20.0
4	1,561	13.5
5 (least deprived)	730	6.3
Attended local GUM clinic
Yes	6,033	52.0
No	5,409	46.7
Not recorded	152	1.3

GUM: genitourinary medicine; LSOA: lower super output area; MSM: men who have sex with men.

The median duration of GUM clinics’ opening hours was 33 h (range 13–49 h) per week. Six (18.5%) clinics had only walk-in sessions and 15 (46.9%) had only appointments sessions. Evening consultations were available in eight clinics (25.0%), weekend consultations in three (9.4%) and 14 (43.8%) provided young people’s clinics (Table 2).

Table 2.

Characteristics of the 32 GUM clinics in London.

Variable	Number	% of total
Duration of opening (hours/week)
0–19	8	25.0
20–29	6	18.8
30–39	9	28.1
40–49	9	28.1
Walk-in clinic
Yes	26	81.5
No	6	18.5
Walk-in clinic (hours/week)
0–9	9	28.1
10–19	11	34.4
20–29	5	25.6
30–39	4	12.5
40–49	3	9.4
Evening clinic
Yes	8	25.0
No	24	75.0
Weekend clinic
Yes	3	9.4
No	29	90.6
Young people’s clinic
Yes	14	43.8
No	18	56.2

GUM: genitourinary medicine.

Information on LSOA of residence was missing for 151 (1.3%) patients. This proportion differed by local authority (LA) of residence, although no LA had more than 15.8% and only five of 32 LAs reported more than 3% of patients with missing LSOA codes. The patients with missing LSOA data did not differ from the others in terms of year of diagnosis (χ² test, p = 0.075), ethnic group (p = 0.332), age group (p = 0.070) or gender (p = 0.503).

The median distance to the clinic attended (whether or not nearest) was 3.5 km (IQR 1.8–6.2 km). More than half the patients (n = 6033 (52.0%) attended local GUM services, of which 5055 (83.8%) attended their nearest GUM clinic.

Factors associated with attending non-local services

Results from the final logistic regression model are presented in two different tables (Tables 3 and 4) for clarity, although individual variables in Table 3 were adjusted for each other and for ecological variables in Table 4 and vice versa. The best multivariable model included all variables except unemployment.

Table 3.

Univariable and multivariable logistic regression analysis of the individual factors associated with travelling to non-local services for gonorrhoea diagnosis and care. London, 2009–10.

N	% travelling non-locally	Crude OR (95% CI)	Adjusted OR (95% CI)
Individual characteristics
Age group (years)
<20	1640	30.5	Ref	Ref
20–24	2882	39.6	1.49 (1.31–1.70)	1.30 (1.13–1.49)
25–29	2489	51.7	2.44 (2.14–2.78)	1.82 (1.58–2.10)
30–39	2727	56.5	2.95 (2.59–3.36)	1.90 (1.64–2.21)
40+	1567	51.2	2.38 (2.06–2.75)	1.43 (1.22–1.69)
Sexual orientation
Heterosexual men	3026	37.2	Ref	Ref
Women	3022	33.9	0.86 (0.78–0.96)	1.10 (0.91–1.33)
MSM	3783	64.6	3.08 (2.78–3.40)	3.83 (3.24–4.520
Male unknown	1438	45.9	1.43 (1.26–1.62)	2.29 (1.86–2.82)
Male			Female
Ethnic group	Heterosexual	MSM	Unknown orient.
White	5687	52.1	Ref	Ref	Ref	Ref	Ref
Black African	792	38.6	0.86 (0.73–1.01)	1.33 (1.04–1.72)	0.74 (0.34–1.64)	0.30 (0.14–0.63)	1.20 (0.63–2.31)
Black Caribbean	1700	40.7	0.93 (0.82–1.06)	1.36 (1.11–1.67)	1.01 (0.54–1.91)	0.51 (0.28–0.92)	1.20 (0.73–1.98)
South Asian	415	31.6	0.63 (0.50–0.78)	0.46 (0.31–0.70)	0.59 (0.22–1.60)	0.79 (0.26–2.45)	0.62 (0.22–1.68)
Other	2167	42.3	1.48 (1.34–1.64)	1.33 (1.08–1.65)	0.93 (0.56–1.57)	0.68 (0.39–1.19)	1.01 (0.61–1.68)

MSM: men who have sex with men.

Table 4.

Univariable and multivariable logistic regression analysis of the characteristics of the area of residence and GUM clinic characteristics associated with non-local service attendance. London 2009–10.

N	% attending non-local clinic	Crude odds ratio (95% CI)	Adjusted odds ratio (95% CI)
Characteristics of LSOA of residence
Quintiles of deprivation
1 (most deprived)	3601	45.1	Ref	Ref
2	3165	47.6	1.10 (1.00–1.22)	0.93 (0.83–1.03)
3	2293	48.9	1.16 (1.05–1.29)	0.94 (0.83–1.06)
4	1532	45.6	1.03 (0.91–1.16)	0.82 (0.71–0.94)
5 (least deprived)	714	44.1	0.96 (0.82–1.13)	0.69 (0.57–0.83)
Unemployment quintiles
0–2.4%	703	44.2	Ref
2.5–3.4%	1219	43.6	0.97 (0.81–1.17)
3.5–4.4%	1824	46.9	1.11 (0.94–1.33)
4.5–5.9%	3201	49.0	1.21 (1.03–1.43)
6.0% and more	4358	46.0	1.07 (0.91–1.26)
Average distance to work (quintiles)
3.8–8.5 km	4112	46.7	Ref	Ref
8.5–9.6 km	2779	47.4	1.02 (0.93–1.13)	1.19 (1.07–1.34)
9.7–10.7 km	1986	45.0	0.93 (0.83–1.04)	1.18 (1.04–1.35)
10.8–12.0 km	1459	46.9	1.00 (0.89–1.13)	1.29 (1.12–1.48)
12.1–23.1 km	969	47.0	1.01 (0.88–1.15)	1.31 (1.11–1.55)
Characteristics of the local GUM clinic
Opening hours
0–19	1590	47.2	Ref	Ref
20–29	1637	44.8	0.91 (0.79–1.05)	0.79 (0.68–0.92)
30–39	4073	44.1	0.88 (0.78–0.99)	0.81 (0.70–0.94)
40–49	4006	49.8	1.11 (0.99–1.25)	0.71 (0.60–0.85)
Evening opening
No	7359	45.9	Ref	Ref
Yes	3947	48.1	1.09 (1.01–1.17)	1.14 (1.02–1.27)
Weekend opening
No	1021	46.9	Ref	Ref
Yes	1094	44.3	0.90 (0.80–1.02)	0.76 (0.79–0.86)
Young people's clinic
No	6339	49.2	Ref	Ref
Yes	4967	43.4	0.79 (0.74–0.86)	0.90 (0.80–1.01)
Walk-in clinic
No	9360	47.2	Ref	Ref
Yes	1946	43.9	0.81 (0.75–0.87)	0.90 (0.80–1.03)

GUM: genitourinary medicine.

Male sexual orientation was strongly associated with seeking care in non-local services, with MSM (adjusted OR (aOR) 3.8, 95%CI 3.2–4.5) and men with unrecorded sexual orientation (aOR 2.3, 95%CI 1.9–2.8) more likely than heterosexual men to travel to non-local clinics (Table 3). No difference was observed between heterosexual men and women. Those aged over 20 years were more likely to travel to non-local services.

We found an association with ethnicity modified by sexual orientation. Among heterosexual men, black Africans and black Caribbeans were more likely, and south Asians less likely, to travel to non-local services compared to whites (aOR [95%CI] 1.3 [1.0–1.7], 1.4 [1.1–1.7] and 0.5 [0.3–0.7]). A similar pattern was seen for heterosexual women, but this was not statistically significant (Table 3). Among MSM there were no significant differences between ethnic groups. Of those men whose sexual orientation was not recorded, white men were more likely than black Africans and black Caribbeans to travel to non-local services (Table 3).

Although there was little evidence of a linear effect of deprivation in the univariable analysis, the adjusted OR for deprivation suggested that people from more deprived areas were more likely to attend non-local clinics than those living in less deprived areas (Table 4).

There was no association between the LSOA level of unemployment and non-local service attendance; however, there was a positive association between the average distance travelled to work and the proportion of individuals attending non-local services (Table 4).

Patients were less likely to travel to non-local services if their local clinic was open for longer hours or was open at the weekend (aOR 0.8 [0.7–0.9]) (Table 4). There was also some evidence that people were less likely to travel to non-local services if their local clinics offered walk-in consultations (aOR 0.9 [0.8–1.0]) or young peoples’ clinics (aOR 0.9 [0.8–1.0]). We also found that people were more likely to travel to non-local clinics if their local clinic was open in the evening (aOR 1.1 [1.0–1.3]).

Results of the sensitivity analysis considering distances of 1.0 km, 1.5 km, 2.0 km and 2.5 km from the nearest GUM clinic as the threshold separating local from non-local services showed no difference in the associations found, although standard errors increased with thresholds based on increasing distances.

Discussion

In this study, we provide a comprehensive London-wide population-based analysis of individual, geographic and service characteristics associated with non-local GUM clinic attendance based on a large number of patients attending GUM clinics over a two-year period. Geographic information at the small level (LSOA), which is only available though surveillance since GUMCAD was launched in 2008, enabled us to provide detailed estimates at the fine geographic scale.

The study shows that people aged 20 years or more, MSM, Black African or Black Caribbean heterosexual men, and those living in the more deprived areas of London, were significantly more likely to travel to non-local services to be treated for gonorrhoea. People were also more likely to travel to non-local services if their local clinic had shorter opening hours, was not open at the weekend or did not offer walk-in services or young people’s clinics.

Some of those findings are consistent with previous studies in London and elsewhere in England (16–20), although few specifically looked at patterns of STI care for gonorrhoea and few addressed GUM access for the population as a whole, focusing instead on particular population groups such as teenagers,¹⁶ MSM^17,18 or black ethnic minority groups.¹⁹ The finding that MSM tend to travel to non-local services is consistent with studies on HIV care in London and elsewhere in England, the majority of whom are MSM.^17,18 MSM travel to clinics that have more experience looking after MSM, and with experience of providing services tailored to their needs, especially for HIV care. Almost one in five MSM diagnosed with an acute STI are HIV co-infected.²⁰ Clinic choice among MSM is thus likely to be influenced by choice of service for HIV care.

Our results suggest that local service access could be improved by adapting opening hours, consultation modes and services targeting particular population groups such as young people. The latter is consistent with recent evidence which suggests that teenagers in England are more likely to use young people’s sexual health services than mainstream sexual health services, including both GUM and non-GUM services,¹⁶ even though standards of care, including easy access outside school or college hours, have been clearly defined.^6,21

Previous studies exploring consultation modes have shown that people often prefer walk-in to booked appointments even if the walk-in service results in longer waiting times at the clinic,^22,23 which is consistent with our findings. Certainly, GUM service access in England is timelier in clinics providing walk-in rather than booked appointments, regardless of age, gender, ethnicity and symptoms of attendees,^22,24 and our results suggest that the presence or absence of a walk-in service may influence whether or not people seek care locally.

While some of the study results were in line with previous studies, as discussed earlier, others provide new insights.

Although our data underestimate the true number of gonorrhoea infections, given that some infections may be asymptomatic and others treated in non-GUM settings, more than 90% of the symptomatic gonorrhoea diagnoses are made in GUM settings¹⁰ and our data therefore provide a fairly comprehensive picture of travel patterns for care in case of symptomatic infection.

Hence, we were able to compare travel patterns across individual characteristics such as age, gender, sexual orientation and ethnicity. We found a strong interaction between sexual orientation and ethnicity. Relative to other ethnic groups, South Asians tended to be diagnosed with gonorrhoea at local clinics, possibly because they are more likely to be referred to GUM clinics by their GP or family planning service.^22,25 Among heterosexual men and women, black Africans and black Caribbeans travelled to non-local services more than people from other ethnic groups. There remains a stigma associated with STIs which can exert considerable social pressure and a desire for anonymity,²⁶ but this may be heightened in certain socio-cultural communities contributing to differences in care-seeking behaviour.^27,28 In addition, as for MSM, the relatively high prevalence of HIV infection among black African heterosexuals¹⁶ may influence the type of service accessed.

We explored several GUM clinic characteristics associated with non-local GUM clinic access. Perhaps not surprisingly, we found that extending clinic opening hours and offering weekend clinics could significantly improve service access and better meet local needs such that local services could be more likely to attract local residents.

The finding that people are more likely to travel beyond their local area if their local clinic provides evening consultations is perhaps unexpected and should be explored further. It suggests however that increasing the availability of evening clinics is unlikely, in itself, to boost attendance at local services.

The study has several limitations. First, we did not investigate referral pathways. For example, it is likely that GP referral or diagnosis through partner notification influences patients’ choice of clinic, and referral pathways are also likely to differ across population groups. For example, a recent study among male GUM attendees in London found that for black Caribbean men the most common way of finding out about a GUM service was through a friend whereas white and black African men were more often referred by their GP.¹⁹ Second, although we investigated factors associated with attending local or non-local services, we did not explore a number of other characteristics of providers which may explain some of the associations seen. Factors such as waiting times, booking mechanisms and characteristics of health professionals delivering the consultations (e.g. nurse or physician) are likely to influence patients’ provider choice.^29,30 A study in the UK²⁹ found that a web-based secure booking service with triage resulted in high patient satisfaction and was safe and efficient. In contrast, a ‘closed’ booking system, where people can only book an appointment 48 h in advance, may prevent patients from being seen promptly.³⁰

The ecological associations with area-level characteristics should be interpreted with care and do not necessarily reflect individual-level associations. In particular, further research is warranted to better understand the finding that people from less-deprived areas are more likely to attend local GUM services.

The association between workplace and GUM clinic attended was not fully explored and is a possible confounding factor which may have not been properly accounted for. Average distance to work was included as an ecological variable in the regression analysis to investigate the association between non-local service attendance and distance to work. Although the analysis showed a near-linear increase in the proportion of patients attending non-local services as distance to work increased, this did not tell us whether services attended were close to work or not, which should be further explored. Moreover, the straight-line distance was used as a proxy of the actual travel distance. This approach overlooked the possibility that clinics located further away might be more accessible through public transport than clinics located geographically closer to home. In addition, the period during which data on clinic characteristics were collected (May 2011) did not coincide with dates of gonorrhoea diagnosis, and schedules, consultation mode and opening hours may have changed during the two-year period.

Finally, further research is required to assess whether travel patterns found in London, and the various factors associated with them, are also seen elsewhere in the UK. More research should also be undertaken to better understand reasons behind the travel patterns found, and how these can be addressed when planning services. A limitation of this study is that we explored associations with a series of factors that we thought could be associated with travel patterns. Surveys among GUM clinic attendees about the reasons for their choice of clinic would enable us to better understand reasons behind the patterns observed.

In conclusion, we believe the results of this study are useful to improve GUM service planning. These results will be helpful to service providers and commissioners by providing a detailed description of patterns of service provision and accessibility, as well as clinic and patient factors associated with health-seeking behaviour for gonorrhoea, which are likely to be generalisable to other acute STIs. We recommend that the findings are taken into account when sexual health services are being commissioned and configured in London. Our results suggest that local services may not be providing accessible services for particular population groups, in particular MSM, and the reasons for this should be further explored.

Footnotes

Acknowledgements

We thank Maddy Gupta-Wright for her comments on the manuscript. We gratefully acknowledge the contribution from the HPA GIS team for their help in calculating distances between LSOAs of residence and clinics using ArcGIS. The authors are also grateful to all GUM clinic staff members who reported data through GUMCAD to the Health Protection Agency (now Public Health England).

Conflict of interest

The authors declare no conflict of interest.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Factors associated with travel to non-local genitourinary medicine clinics for gonorrhoea: an analysis of patients diagnosed in London,2009–10

Abstract

Keywords

Introduction

Materials and methods

Data sources

Definitions of outcome and explanatory variables

Outcome variables

Explanatory variables

Analysis

Results

Descriptive analysis

Factors associated with attending non-local services

Discussion

Footnotes

Acknowledgements

Conflict of interest

Funding

References