GLM for two quantitatives data as DV

Hello all,

I have the following data

res=structure(list(Zone = 1:12, Cat1 = c(0.5, 3.5, 1, 1, 2, 5.75,
9.33333333333333, 9, 11.6666666666667, 3.41666666666667, 4.58333333333333,
0), Other_cat = c(48.5, 45.5, 42, 52, 50, 42.25, 39.6666666666667,
34, 41.3333333333333, 42.5833333333333, 21.4166666666667, 34),
Person_sum = c(37L, 65L, 83L, 82L, 97L, 36L, 33L, 52L, 31L,
33L, 19L, 28L), Music = c("yes", "no", "yes", "no", "yes",
"no", "yes", "no", "no", "yes", "no", "yes")), .Names = c("Zone",
"Cat1", "Other_cat", "Person_sum", "Music"), row.names = c(NA,
-12L), class = "data.frame")
We want to evaluate density effect on behaviour :
-Zone : zone number
-Cat1 : represent number of people who want to stay in low density zone (behavior)
-Other_cat : represent number of people who stay in the space for other reasons (behavior)
-Person_sum : represent density per zone
-Music : presence or not of music in this zone.

I want execute GLM in two way :

(1) Dependant variables are quantitatives (Cat1,Other_cat) and I want to explain their variability by the density Person_sum :
I tried this , I didnt yet use GLM for quanititative data
anova(glm((Cat1,Other_cat) ~ Person_sum ),test="Chisq")
Dependants variables are quantitatives and explanatory data is categorical ; I want to explain variability in behaviour (Cat1,Other_cat) through Music prensence :
anova(glm((Cat1,Other_cat) ~ Music),test="Chisq")
Couldn't find the correct syntaxe. How to do this ?

If it's not possible with GLM, which test to use instead ?

Thanks a lot