Significant main effect in one-way, but not in two-way, MANOVA

I used a one-way MANOVA to study the effect of age groups on the average of height and weight and found that they were significant. Then I used a two-way MANOVA to study the effect of age groups and gender on the averages of height and weight and found that gender had an overall effect but not age groups.

Is there any logic in the result obtained using the above two methods?

Update. The data are of 75 males and 75 females and I randomly made age groups 18-25, 25-30, 30-35, 35-40 and 40+. The number of members in each group varies.

• Do you have the same number of subjects in different groups (particular age + particular gender), or substantially different? Commented Jul 25, 2014 at 13:09
• The data is of 75 males and 75 females and I randomly made age groups 18-25, 25-30, 30-35, 35-40 and 40+. The number of members in each group varies. Commented Jul 25, 2014 at 14:52
• This might be the reason. Imagine for example that males are higher than females, but you have a lot more young males than females. Then there will be no effect of age when you put both age and gender in the model (which is correct), but if you only look at age, then it will seem as if age makes a difference: young people are higher. This would be wrong, as there are simply more young males (in the sample), and they are higher. Commented Jul 25, 2014 at 15:53

As @amoeba suggests, you should plot all variables using something like the pairs function in R. If distributions of the variables look reasonable, I would ran a MANCOVA model with age as a continuous variable along with gender.