Epub: Munger et al. Childhood body mass index and multiple sclerosis risk: a long-term cohort study. Mult Scler. 2013 Apr.
BACKGROUND: Obesity in late adolescence has been associated with an increased risk of multiple sclerosis (MS); however, it is not known if body size in childhood is associated with MS risk.
METHODS: Using a prospective design we examined whether body mass index (BMI) at ages 7-13 years was associated with MS risk among 302,043 individuals in the Copenhagen School Health Records Register (CSHRR). Linking the CSHRR with the Danish MS registry yielded 774 MS cases (501 girls, 273 boys). We used Cox proportional hazards models to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs).
RESULTS: Among girls, at each age 7-13 years, a one-unit increase in BMI z-score was associated with an increased risk of MS (HRage 7=1.20, 95% CI: 1.10-1.30; HRage 13=1.18, 95% CI: 1.08-1.28). Girls who were ≥95th percentile for BMI had a 1.61-1.95-fold increased risk of MS as compared to girls <85th percentile. The associations were attenuated in boys. The pooled HR for a one-unit increase in BMI z-score at age 7 years was 1.17 (95% CI: 1.09-1.26) and at age 13 years was 1.15 (95% CI: 1.07-1.24).
CONCLUSION: Having a high BMI in early life is a risk factor for MS, but the mechanisms underlying the association remain to be elucidated.
The situation is more complex in children, where the BMI threshold of obesity varies with age and sex. Because of this, for children, BMI values are compared with reference values that are generally age and usually also sex specific and need to be further transformed in order to be put on a common footing. This is most often done by translating BMI-for-age into a Z-score or a percentile relative to some specified distribution of BMI-for-age. A Z-score represents the number of Standard deviation units above or below the mean, so that, e.g., a Z-score of 2 refers to a value that is 2 standard deviation above the mean. To give a sense of this 1.96 standard deviations around a normal population mean would include 95% of the population.