How should be statistics on scientific papers read? Let's take this research published on Plos ONE

Increasing carbohydrate intake was associated with increasing stroke
  risk (HR = 2.01, 95%CI = 1.04–3.86 highest vs. lowest quintile; p for
  trend 0.025).
Multivariable Cox modeling estimated adjusted hazard ratios (HRs) of
  stroke with 95% confidence intervals (95%CI).

How should people read those values? What does it mean confidence interval for example? 
Do you know any resource explaining the interpretation of the statistical part of those scientific papers?
 A: I'll take a stab at the portion of the question asking about interpreting these specific results (and I'm going to try to be non-technical about it):
The hazard ratio (HR) of 2.01 suggests that over the course of the study, those in the focal group (in this case, those with increased carbohydrate intake) were about 2 times as likely to experience the outcome of interest (in this case, stroke). Put another way, they had twice the stroke risk of those in the comparison group.
The confidence interval suggests that we can conclude, with 95% certainty, that the true hazard rate in the population could fall anywhere between 1.04 and 3.86. In the broader population, the stroke risk associated with increased carbohydrate consumption could be as high as 3.86 times or as low as 1.04 times that of the comparison group. One thing to note is that this range does not include 1 (although it comes close), suggesting that there is probably a relationship between carbohydrate intake and stroke in the broader population. If 1 were included, this would mean that we would not be justified in concluding that the hazard ratio was different from equal (1:1). 
The p value can be interpreted as the probability of finding a result equal to, or more extreme, than these results in the population by chance alone. Typically, a p value lower than .05 suggests that the results are significant- they are extreme enough to suggest that it is an actual effect, not chance, that is accounting for the results. In this case, the p value is .025, which would allow you to conclude that these results are significant and suggest a relationship between your variables in the population. 
