Letter to the Editor, In studies that are based on secondary data, the authors usually have no control over how the data is collected; however, control does exist with regards to which studies the authors choose to use, and this choice should be exercised carefully. In this study, Raymond et al. used a secondary data analysis of three different studies to examine three identified populations: the National HIV Behavioural Surveillance System (2008) was used to analyze the white MSM (WMSM) population; the San Francisco Department of Public Health’s (SFDPH) Black Men Testing (BMT 2009) was used to analyze the black MSM (BMSM) population; and the SFDPH’s HIV Prevention Section had a program called Transfemales Empowered to Advance Community Health (TEACH 2010) that was used for the transfemale population [1]. The secondary data used to assess these three populations was a huge potential source of bias which the authors failed to address. The first issue is that the three data sets come from three different years (2008, 2009, 2010), making this data a little less reliable and comparable. In speculation, for example, if the recession beginning in 2008 caused SES to decrease and HIV to increase it might have had more of an effect on HIV acquisition in 2008 than 2010 which could bias a comparison between WMSM and transfemale populations. If these were the best or only sources the researchers could find, it should have been noted by the authors in the study [2]. A second issue is that the authors made a conclusion that for BMSM, stimulant use appeared to be the strongest factor in risky sexual behaviour and HIV acquisition; however, since the BMSMs data came from a study that recruited black men who were injection drug users (IDUs) it is possible that there was an overestimate in the correlation between BMSMs, HIV prevalence and stimulant used [1]. In conclusion, the secondary data chosen by the authors could have led to bias and an overestimation of correlation between factors and cohorts. Even if these data sources were the only sources available and thus the potential bias was unavoidable, it should have been declared as a study limitation [2]. By ignoring potential source of bias, the authors reduced the transparency of the study which made the findings appear to be less reliable [2].