Year of birth and sperm count in 10 Danish occupational studies. 1998

J P Bonde, and T Kold Jensen, and S Brixen Larsen, and A Abell, and T Scheike, and N H Hjollund, and H A Kolstad, and E Ernst, and A Giwercman, and N E Skakkebaek, and N Keiding, and J Olsen
Department of Occupational Medicine, Aarhus University Hospital, Denmark. J.P.Bonde@usa.net

OBJECTIVE Several reports indicate a secular decline of human sperm counts. It is still not known if these findings are artifacts related to shortcomings in the data and applied methodologies. Even less is known about possible mechanisms, but it has been proposed that potential changes may be related to disruption of the hormonal regulation of testicular development in prenatal life. The objective of this study was to examine whether sperm count was related to year of birth. METHODS An analysis was made of the sperm count of 1196 men participating in 10 cross-sectional occupational sperm studies in 3 regions of Denmark from 1986 through 1995. RESULTS The median sperm concentration was 63 million per milliliter for men born in 1937-1949 and 52 million per milliliter for men born in 1970 or later, and the median total sperm was 206 million and 117 million, respectively. The inverse relationship between sperm concentration and year of birth was statistically significant even after adjustment for duration of sexual abstinence, season of the year, and study population. However, bias because of differential participation related to age and fertility or lack of comparability across the populations cannot be ruled out. CONCLUSIONS The apparent decline of sperm count with increasing year of birth is compatible with the hypothesis of a common risk factor for male reproductive health operating in prenatal life or early childhood, but the evidence is circumstantial. Age-related selection bias is an alternative and perhaps not a less likely explanation.

UI MeSH Term Description Entries
D008297 Male Males
D009790 Occupations Crafts, trades, professions, or other means of earning a living. Vocations,Occupation,Vocation
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D003718 Denmark A country in northern Europe, bordering the Baltic Sea and the North Sea. The capital is Copenhagen. Faeroe Islands,Faroe Islands
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000375 Aging The gradual irreversible changes in structure and function of an organism that occur as a result of the passage of time. Senescence,Aging, Biological,Biological Aging
D012661 Semen The thick, yellowish-white, viscid fluid secretion of male reproductive organs discharged upon ejaculation. In addition to reproductive organ secretions, it contains SPERMATOZOA and their nutrient plasma. Seminal Plasma,Plasma, Seminal
D013076 Sperm Count A count of SPERM in the ejaculum, expressed as number per milliliter. Sperm Number,Count, Sperm,Counts, Sperm,Number, Sperm,Numbers, Sperm,Sperm Counts,Sperm Numbers
D016014 Linear Models Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression. Linear Regression,Log-Linear Models,Models, Linear,Linear Model,Linear Regressions,Log Linear Models,Log-Linear Model,Model, Linear,Model, Log-Linear,Models, Log-Linear,Regression, Linear,Regressions, Linear

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