The best thing to do is to go to the original paper, which isn't too hard to find. There are also other studies cited in the FDA listing for this work which seem to corroborate the finding that exercise plus increased protein intake plus significant caloric reduction of diet will increase muscle mass while reducing fat. But all of these are small studies (6 to 38 participants total).
But when I read these papers I'm suspicious. Looking at the results commentary in the study referred to by CBC:
Results: As a result of the intervention, LBM increased (P < 0.05) in the PRO group (1.2 ± 1.0 kg) and to a greater extent (P < 0.05) compared with the CON group (0.1 ± 1.0 kg). The PRO group had a greater loss of fat mass than did the CON group (PRO: −4.8 ± 1.6 kg; CON: −3.5 ± 1.4kg; P < 0.05). All measures of exercise performance improved similarly in the PRO and CON groups as a result of the intervention with no effect of protein supplementation. Changes in serum cortisol during the intervention were associated with changes in body fat (r = 0.39, P = 0.01) and LBM (r = −0.34, P = 0.03).
Seems legit, but from a naive statistical point of view things don't seem to add up.
- How can lean body mass be statistically different in the two study groups when their ranges overlap significantly (LBMPro = 0.2 to 2.2 kg, LBMCon = -0.9 to 1.1kg)?
- Similar question around loss of fat mass (FatLossPro = -6.4 to -3.2kg, Fat LossCon = -4.9kg to -2.1kg)?
Maybe they used fancy stats that I wasn't trained in. Maybe the data isn't normally distributed (which then begs the question of why they included +- values as if the data was normally distributed...). Or maybe, like with a lot of scientific papers, the statistics are garbage and the peer-review process fails to address bad stats.