The month of birth effect in multiple sclerosis: systematic review, meta-analysis and effect of latitude
- 1Queen Mary University of London, Blizard Institute, Barts and the London School of Medicine and Dentistry, London UK
- 2Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- 3Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
- Correspondence to Dr Ruth Dobson, Queen Mary University of London, Blizard Institute, Newark Street, London E1 2AT;
- Received 16 August 2012
- Revised 26 September 2012
- Accepted 8 October 2012
- Published Online First 14 November 2012
Background Month of birth has previously been described as a risk factor for multiple sclerosis (MS). This has been hypothesised to be related to maternal vitamin D levels during pregnancy, although conclusive evidence to support this is lacking. To date, no large studies of latitudinal variation in the month of birth effect have been performed to advance this hypothesis.
Methods Previously published data on month of birth from 151 978 MS patients were compared to expected birth rates. A linear regression model was used to assess the relationship between latitude and observed:expected birth ratio of MS patients for each month.
Results Analysis of all reported data demonstrated a significant excess of MS risk in those born in April (observed:expected 1.05, p=0.05) and reduction in risk in those born in October (0.95, p=0.04) and November (0.92 p=0.01). A conservative analysis of 78 488 patients revealed an excess MS risk in those born in April (1.07, p=0.002) and May (1.11, p=0.0006), and a reduced risk in those born in October (ratio 0.94, p=0.004) and November (0.88, p=0.0002). A significant relationship between latitude and observed:expected ratio was demonstrated in December, and borderline significant relationships in May and August.
Conclusions Month of birth has a significant effect on subsequent MS risk. This is likely to be due to ultraviolet light exposure and maternal vitamin D levels, as demonstrated by the relationship between risk and latitude.