The idea that a null hypothesis is "a general statement or default position that there is no relationship between two measured phenomena, or no association among groups" assumes that the purpose of the study is to demonstrate that such a relationship or association exists. However that is not always the case, and the null hypothesis ought to be the hypothesis that is to be "nullified" in order to be in a reasonable position to promulgate your alternative (or research hypothesis), i.e. the thing you don't want to be true. Without this, NHSTs do not enforce the self-skepticism that is their main purpose.
For example, climate skeptics often claim that there has been a pause in the underlying rate of global warming (as measured by global mean surface temperatures - GMSTs). However the evidence they use for this is a lack of a statistically significant trend since some (usually cherry picked to coincide with El-Nino) starting point. However in doing so, they are using a null hypothesis that there is no warming, which is also the alternative hypothesis for which they are arguing. This totally eliminates the value of NHSTs in making us question the evidential support from the data. Of course what they should do is assume a null hypothesis that states that warming has continued at the same rate predicted by the climate models and try and see if that H0 can be rejected (it can't at the moment, as far as I am aware).
Similarly, in the case of the vitamin study, it depends what the authors were trying to argue. If they were arguing that vitamins do cause, then a H0 corresponding to "no effect" would be more appropriate, however I think the real problem in this case is more likely to be limited power of the test? "Vitamin rich diet does cause weight gain" I don't think this is true, if you had a diet of only vitamin pills, I'm pretty sure you would loose weight quite rapidly.
Incidentally, a paper worth reading is
Gerd Gigerenzer, Stefan Krauss, and Oliver Vitouch, "The Null Ritual
What You Always Wanted to Know About Significance Testing but Were Afraid to Ask", in D. Kaplan (Ed.). (2004), The Sage handbook of quantitative methodology for the social sciences, (pp. 391–408). (pdf)
An element of the "null ritual" that they are criticizing is:
1) Set up a statistical null hypothesis of “no mean difference” or
“zero correlation.” Don’t specify the predictions of your research
hypothesis or of any alternative substantive hypotheses.
So H0 is not automatically the assumption of "no effect/difference/correlation/association", it's definition depends on your research definition. If you don't say what you are trying to argue for you are in no position to state your null hypothesis.