Age biases in a large HIV and sexual behaviour-related internet survey among MSM

BACKGROUND Behavioural data from MSM are usually collected in non-representative convenience samples, increasingly on the internet. Epidemiological data from such samples might be useful for comparisons between countries, but are subject to unknown participation biases. METHODS Self-reported HIV diagnoses from participants of the European MSM Internet Survey (EMIS) living in the Czech Republic, Germany, The Netherlands, Portugal, Sweden and the United Kingdom were compared with surveillance data, for both the overall diagnosed prevalence and for new diagnoses made in 2009. Country level prevalence and new diagnoses rates per 100 MSM were calculated based on an assumed MSM population size of 3% of the adult male population. Survey-surveillance discrepancies (SSD) for survey participation, diagnosed HIV prevalence and new HIV diagnoses were determined as ratios of proportions. Results are calculated and presented by 5-year age groups for MSM aged 15-64. RESULTS Surveillance derived estimates of diagnosed HIV prevalence among MSM aged 15-64 ranged from 0.63% in the Czech Republic to 4.93% in The Netherlands. New HIV diagnoses rates ranged between 0.10 per 100 MSM in the Czech Republic and 0.48 per 100 in The Netherlands. Self-reported rates from EMIS were consistently higher, with prevalence ranging from 2.68% in the Czech Republic to 12.72% in The Netherlands, and new HIV diagnoses rates from 0.36 per 100 in Sweden to 1.44 per 100 in The Netherlands. Across age groups, the survey surveillance discrepancies (SSD) for new HIV diagnoses were between 1.93 in UK and 5.95 in the Czech Republic, and for diagnosed prevalence between 1.80 in Germany and 4.26 in the Czech Republic.Internet samples of MSM were skewed towards younger age groups when compared to an age distribution of the general adult male population. Survey-surveillance discrepancies (SSD) for EMIS participation were inverse u-shaped across the age range. The two HIV-related SSD were u- or j-shaped with higher values for the very young and for older MSM. The highest discrepancies between survey and surveillance data regarding HIV-prevalence were observed in the oldest age group in Sweden and the youngest age group in Portugal. CONCLUSION Internet samples are biased towards a lower median age because younger men are over-represented on MSM dating websites and therefore may be more likely to be recruited into surveys. Men diagnosed with HIV were over-represented in the internet survey, and increasingly so in the older age groups. A similar effect was observed in the age groups younger than 25 years. Self-reported peak prevalence and peak HIV diagnoses rates are often shifted to higher age groups in internet samples compared to surveillance data. Adjustment for age-effects on online accessibility should be considered when linking data from internet surveys with surveillance data.