Eat carbs in evening and gain fat?

[Heybales]

Trick topic - Personal preference is real answer, no bearing on fat or weight loss or gain by itself. You adhering to your diet is a different point potentially.

It's just one of those common myths you hear:

Don't eat after 6 pm.

Don't eat carbs after 6 pm.

Don't eat food (or carbs specifically) within 3 (or whatever) of bedtime.

Those things will just pack the fat on, because ...

Usually some wild reason that has no bearing on human physiology at all, let alone several studies that have been done already showing otherwise.

But here's a nice article by a very well respected Dr who is himself a lifter, Dr Layne Norton.

And he references those other studies.

Nail someone on their next bro-science comment or anecdotal research of 1 (themselves).

http://www.simplyshredded.com/carbs-at-night-fat-loss-killer-or-imaginary-boogeyman.html

snippet

"These researchers from Israel put people on a calorically restricted diet for 6 months and split them into two groups, a control group and an experimental group. Each group consumed the same amount of calories, protein, carbohydrates, and fat but they distributed their carbohydrate intake very differently. One group (control) ate carbs throughout the day, whereas the experimental group consumed the majority of their carbohydrate intake (approximately 80% of the total) at the night. What they found after 6 months may shock you.

Not only did the experimental group consuming the majority of their carbs at night lose significantly more weight and bodyfat than the control group, they also were better satiety and less hunger!"

[carl669]

for anyone interested, here's the full text of the study referenced in the article:

http://onlinelibrary.wiley.com/doi/10.1038/oby.2011.48/full

[Snowflakepdx]

Interesting topic and study.

Hard to say if this is meaningful information because we don't know if the sample size was even statically significant. 

I think the proven fact from most of this kind of research is that there just isn't a magic bullet that works for everyone.  Most of these clinical research studies on weight loss aren't really worthy of being published in a scientific journal. 

There are some ongoing studies on large sample sizes of maintainers/gainers over a period of years that tell us what anyone who has maintained their weight over a period of many years.  Those are the studies to look to.   

[Heybales]

Sadly those studies are based on self-assessments on exercise and food quantity and type, many times with checkups being months apart because of the huge sample size and length of time. I've seen the research on the potential inaccuracy of that self-logging from the fact they can tell reports for that long period of time were all done at the same time, ie day before (cramming for test syndrome).

And after seeing the studies on even nutritionists and dietitians logging food very badly, I'm not sure what to really trust there in those types of studies. You'd hope the sample size is sufficiently large to lose that kind of inaccuracy noise.

And that's why smaller sample sizes are just fine if they have more control. Now if they were just as sloppy as those bigger studies, then huge margin for error. But they aren't.

I'd trust this well laid out study for exactly what it was testing, carb eating levels either evening or daytime.

The only kicker here of course is the folks allowed in the study had no attempt at weight loss or none occur in prior year, and no disease. So outside of weight, no other health issues.

Of course any study is only as good as it's application in real world. And there I know the only ones I've heard tell of advice not to eat carbs after some early evening hour, always share their study of themselves and inabliity to only eat so many carbs as diet allows later. It's as if their personal issue with self-control and carbs is rightfully being assisted by their rule. But that doesn't mean the "rule" by itself is valid, unless you too have self-control issues.

But these studies are great to get rid of these myths that say "you will gain fat eating carbs after 6 pm" - which I've clearly seen and heard in magazines and comments from "respected personalities" in the health industry for many years.

As far as stat's. From the sudy link above.

Statistical analysis

Of the 78 subjects who met study criteria, 63 completed the program. This sample size was sufficient to detect a difference of 3 kg between mean weight reductions in the two groups with 75% power, assuming a standard deviation of 4.5 kg. Anthropometric parameters were expressed as an absolute reduction and as percent reduction. For analysis of biochemical changes, 12-h hormonal average, inflammatory and H-SSc parameters, values on day 90 and day 180 were expressed as percentage of baseline. For cholesterol parameters, as changes due to diet were expected to be long term, the average of day 0 and day 7 values were used as a more reliable baseline. Changes in scores for “urge to eat” and “preoccupation with food” (1 = none, 2 = mild, 3 = moderate, 4 = very strong) were analyzed ordinally and categorically (stronger/not stronger). All categorical variables were compared between groups by the χ2 test. Additional differences between the groups at baseline were analyzed by a t-test. For parameters where significant differences were discovered, the baseline value was used as a covariate in the ensuing analyses. Differences in anthropometric parameters were analyzed by two-way ANOVA (treatment, gender). For biochemical and inflammatory parameters, 12-h hormonal average and H-SSc, repeated measures ANOVA over days (and also over hours, for H-SSc) was used to compare treatments, with sex as an additional factor. Differences between groups on specific days (and specific hours, for H-SSc) were performed by preplanned contrast t-tests. Significance of difference from baseline was established using a t-test with standard error derived from the ANOVA model. Differences in ordinal scale variables were analyzed by the Wilcoxon Rank Sum test. Statistical significance was set at P < 0.05. In the description of the study population, we used standard deviation as a measure of dispersion. In reporting the results, we used the standard error to enable assessment of the difference between the group means.