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Lecture 2

NFS284 Lecture 2.docx

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University of Toronto St. George
Nutritional Science
Debbie Gurfinkel

NFS284 Lecture 2 Chapter 1: Food for Health  1.4 Understanding Science Helps Us Understand Nutrition: The Scientific Method o Hypothesis o Experiment to test hypothesis o Results analyzed o Conclusion:  Hypothesis supported or hypothesis rejected o Publication of results in a peer-reviewed scientific journal o Publication sparks interest and more experiments are conducted to test hypothesis o Reproducibility strengthens the hypothesis  1.5 Nutrition Research o Observational Studies  Determines an association or correlation between diet and health (some aspect)  Eg. high intake saturated fats associated w/ CVD  2 types:  Prospective cohorts study  Case control study (not as reliable)  What is a cohort? A description of group or population o Intervention Trial  Determines causation (or establishes a causal link) between diet and health)  Eg. association of birth rate and number of TVs but no causal link  Can test o Observational studies  Association/Correlation  Direct or positive  Increase intake of dietary component o Eg. intake of saturated fats increase, CVD increase o Directions are the same Intake of dietary component Number of disease cases Low Low High High  Association/ Correlation  Inverse or negative  Increase intake of dietary component o Eg. increase PUFA, CVD decreases  Decrease disease risk Intake of dietary component Number of disease cases Low High High Low o Limitation of observation studies  Increase vegetable intake -> decrease cancer risk Vegetable intake Cancer cases Low High High Low  Other factors that lead to diff confounding factors  Confounding factors  Confounding factor: related to both the outcome being investigated (cancer cases) and a factor that might influence outcome (dietary intake)  Eg. socioeconomic factors  What if low vegetable intake is a characteristic of an older population? o How do you determine if you are measuring the effect of vegetable intake or age? o Statistical adjustment for confounding factors  Eg. age adjustment  Problems  Can only correct for confounders that are identified and measured  Uncorrected or unknown confounding -> residual confounding o Eg. some genetic factors  Get info, only need to check in and give info  Collect lots of info then can test other hypotheses  Age influences disease risk  May be other factors affecting this o Prospective cohort study  starts w/ cohort , correct for confounding factors to determine if difference in disease, see if hypotheses is supported o Intervention Trial  Control group  Diet typical of the population; may continue typical diet  Intervention or treatment group  Substantial change in the diet  Randomization  Assignment to the control group or treatment group is purely by chance  Implications of randomization: o Confounding factors are equally distributed between control and treatment group, eg. genetic factors o The only difference between control and treatment groups is the treatment or intervention  If treatment is ineffective in altering outcome, then causation is indicated or a causal link is made  Randomly divided into 2 groups o Intervention trial  Large sample, totally randomize  Considered best study to do o Intervention Trials: Characteristics  Placebo  Dummy treatment given to control group to eliminate the effect of participant expectations  Blinding of study  Whether the participant is assigned to control or treatment group is unknown to o Both participant and researcher = double blind study o Either the participant or researcher = single blind study  Strengths  Shows causation  Evidence from intervention trials considered stronger than observational studies  Limitations  Difficult to sustain especially if you are making substantial changes to the diet  CT: Using Scientific Method o Pg 26
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