RT Journal Article
SR Electronic
T1 What are seasonal and meteorological factors are associated with the number of attendees at a sexual health service? An observational study between 2002–2012
JF Sexually Transmitted Infections
JO Sex Transm Infect
FD BMJ Publishing Group Ltd
SP 635
OP 640
DO 10.1136/sextrans-2013-051391
VO 90
IS 8
A1 Nimal Gamagedara
A1 Jane S Hocking
A1 Mathew Law
A1 Glenda Fehler
A1 Marcus Y Chen
A1 Catriona S Bradshaw
A1 Christopher K Fairley
YR 2014
UL http://sti.bmj.com/content/90/8/635.abstract
AB Background Open access to sexual health services may be inefficient if there are substantial unpredictable fluctuations in presentations. Our aim was to determine whether the number of presentations over the last 11 years was associated with certain factors. Methods This study involved all individuals presenting to Melbourne Sexual Health Centre (MSHC) from 2002 to 2012. The outcome measure was the number of presentations during a clinical session (half day). Results There were 270 070 presentations to the clinic among 86 717 individuals. The factors associated with the largest difference in mean presentations per session were morning or afternoon (60 vs 51 per session), days of the week (57–67 per session), months of the year (93–112 per day), year (77–131 per day), maximum temperatures of <15°C vs ≥30°C (56–62 per morning session) and 5 working days after holiday periods (61 vs 54). A multiple linear regression model using these factors explained 64% of the variation in attendances per session. Peak attendance rates (>90th centile) were also strongly correlated with these same variables. Higher-risk heterosexuals (≤25 years of age) attended more commonly in the afternoons (37% of heterosexuals) than in the mornings (30%). No factor other than year of attendance substantially influenced the proportion of higher-risk men who have sex with men (MSM) (≥10 partners per year) who attended. Conclusions A considerable proportion of the variability in presentations was explained by known factors that could predict client presentations to sexual health services and therefore allow optimal allocation of resources to match demand.