Although a family history of schizophrenia is the best-established risk factor for schizophrenia. environmental factors such as the place and season of birth may also be important. Using data from the Civil Registration System in Denmark, we established a population-based cohort of 1.75 million persons whose mothers were Danish women born between 1935 and 1978. We linked this cohort to the Danish Psychiatric Central Register and identified 2669 cases of schizophrenia among cohort members and additional cases among their parents. Results: the respective relative risks of schizophrenia for persons with a mother, father, or sibling who had schizophrenia were 9.31 {95 percent confidence interval, 7.24 to 11.96), 7.20 {95 percent confidence interval, 5.10 to 10.16), and 6.99 {95 percent confidence interval, 5.38 to 9.09), as compared with persons with no affected parents or siblings. The risk of schizophrenia was associated with the degree of urbanisation of the place of birth {relative risk for the capital vs. rural areas, 2.40; 95 percent confidence interval, 2.13 to 2.70). The risk was also significantly associated with the season of birth; it was highest for births in February and March and lowest for births in August and September. The population- attributable risk was 5.5 percent for a history of schizophrenia in a parent or sibling, 34.6 percent for urban place of birth, and 10.5 percent for the season of birth. Conclusions: Although a history of schizophrenia in a parent or sibling is associated with the highest relative risk of having the disease, the place and season of birth account for many more cases on a population basis. {N Engl J Med 1999;340:603-8.) {Copyright 1999, Massachusetts Medical Society.)

A re-assessment of Jung’s astrological test of synchronicity provides no convincing reason to believe in either. Nevertheless, precisely because of this, Jung’s results still provide food for thought.

J. F. Ruis compared birth frequencies between males and females of ordinary people (Gauquelin data) across planetary sectors and claimed that certain frequencies differed significantly. Since the dates of birth in his male and female sub samples had not been matched, the result might be due to an astronomical-demographical artefact. The present study tries to replicate Ruis’ result using the same data with male and female sub samples matched for date of birth (n+ 7,593) each. Each sub sample was divided using the median birth day as the dividing point, into two successive cohorts. For each cohort the male proportion of births, indicating the gender difference, was determined across 36 sectors of 5 planets. If gender differences exist they should be stable across successive cohorts, but gender differences in the first cohort did not reoccur in the subsequent cohort. This was revealed by correlations. The observed lack of stable differences cannot be attributed to the method since the same method successfully demonstrated stability in identifying Mars-prone professionals and ordinary people. The finding of Ruis is thus most probably due to an astronomical-demographical artefact.