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Human Reproduction, Vol. 11, No. 12, pp. 2635-2639, 1996
© 1996 European Society of Human Reproduction and Embryology

research-article

Andrology: Statistical modelling reveals demography and time are the main contributing factors in global sperm count changes between 1938 and 1996

G. Bahadur1,3, K.L.E. Ling2 and M. Katz1

1UCLMS, Department of Obstetrics and Gynaecology 86-96 Chemes Mews, London WC1E 6HX 2UCLMS, Dept of Medicine ‘G’ Block, Archway Wing, Whittington Hospital, Archway Road, London N19 3UA, UK

Correspondence: 3To whom correspondence should be addressed

Declining sperm count reports have caused enormous concern to both the scientific community and to society. We reproduced the linear regression analysis and the quadratic model analysis using the 50 year sperm count data published in Carlsen's report and found that neither model adequately described the data. The reported decline in sperm count could be due to observational bias and overinterpretation of linear regression. In fact only 36% of the total variability in sperm count was explained by the linear model and 42% by the quadratic model. The linear model was no longer valid when three new European reports on sperm counts were included in the analysis. The quadratic model, however, suggested an upward trend of sperm count after 1975 (R2 = 0.48, P <0.0001). Factors other than the ‘passage of time’ may have contributed to the initial decline of sperm count. An immediate candidate was demography. Our analysis showed that sperm counts in USA were significantly higher in 1938–1956 compared with those in 1957–1974 and 1975–1988, but not in the European or Asian/African/South American countries. The variability of the USA sperm count (1938–1988) explained by the linear and quadratic models was found to be 71 and 70% respectively. The quadratic model importantly indicated that the sperm count in USA decreases asymptotically towards a limiting value and global sperm counts could be increasing since 1970. The non-uniform nature of the global sperm count change suggested that local variations in pollution, diet but not global warming were important determinants of reproductive health.

Key words: diet/global warming/sperm count decline/statistical modelling


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