Food and Nutrition Inquiry and Research
What you must know
This domain covers how nutritional knowledge is generated and judged. You need to recognise research designs - randomised controlled trials, cohort studies, case-control studies, cross-sectional surveys, and laboratory or animal studies - and understand the strengths and limits of each. Know the meaning of reliability (consistency of results on repetition) and validity (whether a method measures what it claims). Understand sampling: sample size, representativeness, random and stratified sampling, and how bias (selection, recall, observer, publication) can distort findings. You should be able to read simple data presentations (tables, bar and line charts, food labels) and interpret them accurately, and to distinguish correlation from causation.
Traps to watch
A very common trap is treating a single study or a small sample as conclusive proof. Another is confusing correlation with cause: two things rising together does not mean one causes the other. Beware of questions that swap reliability and validity - repeating a flawed measurement gives reliable but invalid data. Watch for leading survey questions, self-reported intake under-reporting, and the fact that animal studies cannot be assumed to apply directly to humans. Always ask who was studied, how many, how the data were collected, and whether a control group existed.
Worked example
A survey finds that people who eat breakfast daily report lower body weight. Before concluding breakfast causes weight loss, check: Is the sample representative? Was intake self-reported? Could a third factor (e.g. overall lifestyle) explain both? Is the design cross-sectional, which cannot establish cause? Rule of thumb: for a causal claim, look for controlled trials or strong cohort evidence, not a single snapshot survey.