Merzenich et al, BMC Public Health 2010, 10:24 http://www.biomedcentral.com/1471-2458/10/24 ity and were therefore "considered to represent the nor- mal male population". It is well known that, due to the personal and poten- tially embarrassing manner of collection, men are reluc- tant to provide semen samples unless currently concerned about their fertility. In other words, highly selected volunteers constitute a biased sample of the pop- ulation with regard to their perceived fertility [18]. Fur- thermore, the socio-demographic profile of sperm donors is commonly shifted to more educated classes [19]. As a result, studies of men providing semen samples involve mainly self-selected volunteers with various non- neutral motivations. Hence, in most studies on human semen characteristics the populations under study are insufficiently defined and the study participants are not a representative population sample. The former meta-analyses [1-3] included study participants who were examined before vasectomy; some were recruited while their partners were attending ante- natal clinics; some were volunteer donors participating in artificial insemination programmes; and some were recruited as part of an occupational study; others were recruited from infertility clinics but were included only if their partners subsequently became pregnant. Data from such study populations cannot be legitimately extrapo- lated to their apparent source population unless they originate or constitute a representative sample of that ref- erence population. The "normal male population" included fertile, subfer- tile as well as infertile men. The lack of external validity of studies using data from self-selected volunteers might further question the hypothesis of a decline in sperm quality with time. Confounding bias Two important factors influencing semen characteristics are age and duration of sexual abstinence (prior to semen donation). Older age contributed significantly to a decline in sperm concentration and sperm motility. The variable for the year of semen donation is composite because it combined each man's age at the time of donation with his year of birth. The relation of each semen characteristic to these independent variables (age at donation and year of birth) has to be tested with multiple regression analysis. Greater sexual abstinence is associated both with age and an increase in the sperm concentration and a decrease in the percentage of motile spermatozoa [10]. In general, sperm concentrations reflect sperm production, age and abstinence time [16]. In the former meta-analyses [1-3], the important information on age was not extracted from the original publications and hence has not been consid- ered in the statistical analysis. It has been shown that sperm counts in volunteers vary with abstinence time [20]. It has been shown that only 66% of the men investigated had complied with the Page 3 of 5 required abstinence time of three to five days [10]. Thus, if a secular trend in sperm production is to be analyzed, well-controlled abstinence times are a prerequisite. Measurement bias WHO recommends non-manual methods for semen analysis such as haemocytometer or so called counting chambers [21], since manual methods rely on subjective judgements and are not reliable. WHO has laid the foun- dation for such quality control by introducing a labora- tory manual for semen analysis, currently in its fourth edition [22]. WHO recommendations for laboratory techniques are slowly becoming accepted as the interna- tional standard, but are not yet universally applied. All data obtained in early studies, as considered in the former meta-analyses [1-3], were not subjected to quality con- trol. Furthermore, reports on external quality control have shown noticeable variations in the determination of semen characteristics between laboratories related to dif- ferences in technique [23]. Consequently, it is very diffi- cult, to compare data from different laboratories if subtle changes in sperm concentration are to be detected [16]. Statistical considerations Olsen et al. [24] presented different statistical approaches to the data suggesting that alternative models including the quadratic, spline fit and stair step provided a better fit than the linear regression used by Carlsen et al. and might lead to different interpretations. For example, the use of linear or quadratic models tends to suggest that any change in semen quality is gradual and may be con- tinuing, whereas the stair-step model tends to suggest an isolated event or set of events which is not continuing after say 1970. A sudden apparent fall in semen quality may be due to substantial changes in analytical method- ology, subject selection criteria, study selection criteria or widespread introduction of a global environmental factor. Goldstandard in measurements of semen quality The definition of a "normal" sperm concentration has changed from 60 million/ml in 1940 to the present value of 20 million/ml [1,17]. In order to avoid bias, Carlsen et al. restricted their study to men with proven fertility (39 studies) or to "normal" men of unknown fertility (22 stud- ies). It was speculated that much of the apparent change in semen quality could be accounted for by a change in the "accepted" definition of the lower limits of "normal" from around from 60 million/ml in 1940 to values of 20 million/ml accepted today. This change might have led to the exclusion of men with sperm concentration of 20-60 million/ml in the earlier studies, as these studies set out to include "normal men" with sperm counts not below 60 million/ml. This possibility is underlined by a theoretical calculation showing that such a change of the reference data would indeed result in a drop in average sperm con- centration. This predicting is in good accordance with the