cumulative % explained in mca() library(MASS)

Hi, 
using mca function in library(MASS) I obtained the following result:

miacm=mca(factor.variables,abbrev=TRUE,nf=11)
miacm

Call:
mca(df = factor.variables, nf = 11, abbrev = TRUE)

Multiple correspondence analysis of 1000 cases of 3 factors

Correlations 0.605 0.599 0.586 0.577 0.577 0.577 0.571 0.555 0.546 0.000 0.000  
cumulative % explained  30.23  60.18  89.49 118.35 147.22 176.09 204.62 
232.37 259.69 259.69 259.69

Burt matrix is 12 by 12.

Does anyone know how can the percentage of explained variability be greater 
than 100?

Thank you,
Stefano Cabras
University of Cagliari (Italy)