Using any awk in any shell on every Unix box and without creating new fields in each record (which is inefficient as it causes awk to re-build the record every time you change a field) and without updating the input record (which is inefficient as it causes awk to re-split the record into fields every time you change the record) and designed to work for any number of value input columns in any order:

$ cat tst.awk
BEGIN { FS=OFS="\t" }
{ printf "%s%s", $0, OFS }
NR==1 {
    for (i=3; i<=NF; i++) {
        printf "Total_%s%s", $i, OFS
        tags[i] = $i
    }
    print "Percentage"
    next
}
{
    delete tot
    for (i=3; i<=NF; i++) {
        tag = tags[i]
        n = split($i,vals,",")
        for (j in vals) {
            tot[tag] += vals[j]
        }
        printf "%s%s", tot[tag], OFS
    }
    printf "%0.3f%s", (tot["Weight"] ? tot["Height"] / tot["Weight"] : 0), ORS
}

$ awk -f tst.awk file
Name    type    Age     Weight  Height  Total_Age       Total_Weight    Total_Height    Percentage
Xxx     M       12,34,23        50,30,60,70     4,5,6,5.5       69      210     20.5    0.098
Yxx     F       21,14,32        40,50,20,40     3,4,5,5.5       67      150     17.5    0.117

$ awk -f tst.awk file | column -t
Name  type  Age       Weight       Height     Total_Age  Total_Weight  Total_Height  Percentage
Xxx   M     12,34,23  50,30,60,70  4,5,6,5.5  69         210           20.5          0.098
Yxx   F     21,14,32  40,50,20,40  3,4,5,5.5  67         150           17.5          0.117

To show the functional advantages of the above approach, imagine you need to add more values like ShoeSize and/or rearrange the order of the columns, e.g.:

$ column -t file
Name  type  ShoeSize  Height     Age       Weight
Xxx   M     12,8,10   4,5,6,5.5  12,34,23  50,30,60,70
Yxx   F     9,7,8     3,4,5,5.5  21,14,32  40,50,20,40

Now run the above script and notice you get Total_ columns added for every original column and you still get the same Percentage column of Height/Weight added to the end:

$ awk -f tst.awk file | column -t
Name  type  ShoeSize  Height     Age       Weight       Total_ShoeSize  Total_Height  Total_Age  Total_Weight  Percentage
Xxx   M     12,8,10   4,5,6,5.5  12,34,23  50,30,60,70  30              20.5          69         210           0.098
Yxx   F     9,7,8     3,4,5,5.5  21,14,32  40,50,20,40  24              17.5          67         150           0.117

Here is a Ruby which is a little easier for multiple data fields such as this:

ruby -F"\t" -lane '
if ($.==1) 
    puts "Name\ttype\tAge\tWeight\tHeight\tTotal_Age\tTotal_Weight\tTotal_Height\tPercentage"
    next 
end
fields=$F.clone
$F.each{|f| fields.append(f.split(/,/).map(&:to_f).sum) if f[/^[\d,.]+$/] && f[/,/]}
fields.append((fields[-1]/fields[-2]).round(3))
puts fields.join("\t")' file | column -t

Prints:

Name  type  Age       Weight       Height     Total_Age  Total_Weight  Total_Height  Percentage
Xxx   M     12,34,23  50,30,60,70  4,5,6,5.5  69.0       210.0         20.5          0.098
Yxx   F     21,14,32  40,50,20,40  3,4,5,5.5  67.0       150.0         17.5          0.117

The advantage here is that sums of columns of n.nn,n.nn,... are flexibly added to the end of the row in the order they are found.

I would use GNU AWK's function split for this task as follows. Consider following simple example, let file.txt content be

Name  type    Age     Weight       Height 
Xxx   M    12,34,23  50,30,60,70   4,5,6,5.5 
Yxx   F    21,14,32  40,50,20,40   3,4,5,5.5

then

awk 'BEGIN{OFS="\t"}NR==1{print "Age","Total"}NR>1{totalage=0;split($3,ages,",");for(a in ages){totalage+=ages[a]};print $3,totalage}' file.txt

output

Age Total
12,34,23    69
21,14,32    67

Explanation: Firstly I informed GNU AWK to use tab as output field seperator (OFS), then for first line I print headers, for every next line I: set totalage value to 0, split content of 3rd column into array ages at ,, traverse said array getting sum of its values and then print content of 3rd column and sum. Note that

Before splitting the string, split() deletes any previously existing elements in the arrays array and seps.

So it do not require resetting unlike totalage variable.

(tested in gawk 4.2.1)

With your shown samples please try following code.

awk '
FNR==1{
  print $0,"Total_Age Total_Weight Total_Height Percentage"
  next
}
FNR>1{
  totAge=totWeight=totHeight=0
  split($3,tmp,",")
  for(i in tmp){
    totAge+=tmp[i]
  }
  split($4,tmp,",")
  for(i in tmp){
    totWeight+=tmp[i]
  }
  split($5,tmp,",")
  for(i in tmp){
    totHeight+=tmp[i]
  }
  $(NF+1)=totAge
  $(NF+1)=totWeight
  $(NF+1)=totHeight
  $(NF+1)=$(NF-1)==0?"N/A":$NF/$(NF-1)
}
1' Input_file | column -t

OR adding a bit short version of above awk code:

awk '
BEGIN{OFS="\t"}
FNR==1{
  print $0,"Total_Age Total_Weight Total_Height Percentage"
  next
}
FNR>1{
  totAge=totWeight=totHeight=0
  split($3,tmp,",")
  for(i in tmp){
    totAge+=tmp[i]
  }
  split($4,tmp,",")
  for(i in tmp){
    totWeight+=tmp[i]
  }
  split($5,tmp,",")
  for(i in tmp){
    totHeight+=tmp[i]
  }
  $(NF+1)=totAge OFS totWeight OFS totHeight
  $0=$0
  $(NF+1)=( $(NF-1)==0 ? "N/A" : $NF/$(NF-1) )
}
1' Input_file | column -t

Explanation: Simple explanation would be, take sum of 3rd, 4th and 5th columns and assign them to last column of line. Accordingly add column value which has divide value of last and 2nd last columns as per OP's request. Using column -t to make it look better on output.

If you have to do the same operations multiple times, you might also use a function to sum the array values (given that the values are numbers separated by comma's).

Reusing some parts of the answer from @RavinderSingh13 and a massive thank you to @Ed Morton taking the time to provide great feedback improving the code:

awk '
function arraySum(field,      sum,arr,i) {
  split(field,arr,",")
  for (i in arr) sum += arr[i]
  return sum
}
FNR==1{
  print $0, "Total_Age", "Total_Weight", "Total_Height", "Percentage"
  next
}
NR > 1 {
  sumWeight = arraySum($4)
  sumHeight = arraySum($5)
  print $0, arraySum($3), sumWeight, sumHeight, (sumWeight ? sumHeight/sumWeight : 0)
}' file | column -t

Output

Name  type  Age       Weight       Height     Total_Age  Total_Weight  Total_Height  Percentage
Xxx   M     12,34,23  50,30,60,70  4,5,6,5.5  69         210           20.5          0.097619
Yxx   F     21,14,32  40,50,20,40  3,4,5,5.5  67         150           17.5          0.116667