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Goal Setting 

The Sugar Experiment:

Primary and Secondary Outcomes

Each experiment in the Lifestyle Experiment (Sugar, Fitness, Sleep, and Food) includes primary and secondary outcomes to measure changes over time.

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Primary outcomes are usually short-term, responsive metrics that are the most likely to change as a result of the intervention.  Good choices for the Sugar Experiment include:

Primary Outcomes for the Sugar Experiment ✅ Frequency of glucose spikes above 160 mg/dL (measured using a CGM) ✅ Average blood glucose level (measured using a CGM) ✅ Fasting Glucose ✅ Fasting Insulin Level

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Secondary outcomes are usually long-term health indicators that may or may not change within the proposed timeframe but if they do, its a bonus.  Good secondary outcome choices for the sugar experiment include:

✅ HbA1c (long-term blood sugar control) ✅ Triglyceride Level ✅ Body Fat Percentage ✅ Waist Circumference ✅ LDL Cholesterol (bad cholesterol) ✅ hsCRP (inflammation marker)

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The Sugar Hypothesis

Now, you need to write out your hypothesis statement. It is important to do this formally so that you will know if you have achieved your experimental goals at the end of this experiment. A reasonable hypothesis for the sugar experiment is as follows: My baseline glucose monitor and initial assessment show that I have prediabetes and I am particularly sensitive to fruit juice, pasta and bread. With this in mind, I believe that I can lower my average glucose on the monitor from 111 to 100 and I can eliminate all spikes to more than 170 by eliminating those foods from my diet. If I maintain that elimination diet I can keep my average glucose at that level and ultimately reduce my HbA1c to 5.6 and reduce my waist circumference from 38 to 34 inches over 3 months. This is a good hypothesis statement, because it shows that this person has evaluated his/her own monitor, made observations about the problems that it showed and then made an achievable goal for the experiment. Here is another hypothesis for the sugar experiment: Knowing that I am female and have metabolic syndrome with fasting Triglyceride level of 225 mg/dl, a HbA1c of 6.0 and a waist circumference of 37 inches: I can reduce my triglyceride level to less than 150, my A1c to less than 5.8 and my waist circumference to 35 inches by using an elimination diet low in carbohydrates and doing that for 3 months. This is an excellent hypothesis statement for a longer term experiment. Instead of using the short term metrics as the primary outcome, she is using the longer term metrics because she is confident that she can use the monitor to maintain her elimination diet and she will get longer term results. Notice how she takes an ambitious approach with triglycerides and a more modest approach with A1c and waist circumference. This is a very reasonable thing to do, because triglyceride tends to change quickly when you address carbohydrates and simple sugars. Waist circumference is a great metric to use when you are lowering your blood glucose level and addressing insulin resistance. The normal waist circumference for an adult woman should be 35 inches or less. Here is one more hypothesis statement for this experiment: Knowing that I do not have diabetes, prediabetes or metabolic syndrome, but my blood glucose does routinely spike to 180 or more when I eat certain foods, I can eliminate all blood glucose spikes above 160 and I can lower my average blood glucose to less than 100 by following an elimination diet and sustaining it for 2 weeks. This is the classic experiment for someone with no current evidence of insulin resistance, but who wants to do the experiment. It is reasonable in this circumstance to run the experiment for a shorter period of time using the glucose monitor to guide your dietary choices.

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