Month of birth and risk of multiple sclerosis in Kuwait: a population-based registry study

Mult Scler. 2015 Feb;21(2):147-54. doi: 10.1177/1352458514541578. Epub 2014 Aug 4.

Abstract

Background: Multiple sclerosis (MS) is a complex immune-mediated disorder of central nervous system with undefined etiology. This study examined the month of birth effect on subsequent MS risk later in the life in Kuwait.

Methods: The month of birth of MS patients enrolled in Kuwait MS Registry between 1 January 1950-30 April 2013 was compared with the month of births in the general population during the comparable period. Multivariable log-linear Poisson regression model was used to analyze the data.

Results: Data on 1035 confirmed MS patients were collected, of which 65.2% were female and 77.1% were Kuwaiti. The overall risk of MS births (per 10(5) births in general population) was 28.5 (95% confidence interval (CI): 26.8-30.3). Multivariable log-linear Poisson regression model showed a significant (p=0.004) peak in the number of MS births during December (θo=340(o)). During this month, the risk of MS birth was 1.3 times the risk of MS birth in the trough month after adjusting for the effects of gender and nationality (adjusted relative risk=1.3; 95% CI: 1.1-1.6). The amplitude (α±standard deviation: 0.13±0.014) of sinusoidal curve showed a significant (p=0.004) difference of 13% from the mean to maximum MS births during peak month.

Conclusions: This study showed a statistically significant month of birth effect on MS risk with 13% excess MS births during December in Kuwait. Future studies may contemplate ascertaining the seasonal factors eliciting the observed association. The insight gained by unraveling such factors may help curtail MS risk in this and other similar settings in the region.

Keywords: Kuwait; Multiple sclerosis; epidemiology; month of birth; registry; seasonality.

MeSH terms

  • Female
  • Humans
  • Kuwait / epidemiology
  • Male
  • Multiple Sclerosis / epidemiology*
  • Periodicity*
  • Registries / statistics & numerical data*
  • Risk