Insulin Resistance and the Reset: What the Markers Mean

Your labs can read "normal" while the thing you care about is already moving

A patient brings in a recent blood panel. This is a composite of a conversation providers have constantly, not one person's chart. Fasting glucose 96. A1c 5.5. Everything printed in the normal column, no flags, no follow-up requested. And yet the afternoon crashes are real, the last fifteen pounds have not moved in two years, and the waistband keeps telling a different story than the lab report.

Nothing was missed. The panel was measuring the right system at the wrong stage. Fasting glucose is a late signal, and it is late by design: the body works hard to keep blood sugar in range, and it succeeds for years by producing more insulin. Glucose only drifts once that compensation starts running out. If you look only at glucose, you are looking at the moment the compensation failed, not the years it was working.

This post walks through the markers a provider actually reads when the question is insulin resistance, what each one can and cannot tell you, and which ones respond to the work you do in a reset. It is not a diagnostic guide and it does not replace your physician. It is meant to make the numbers on your own report legible.

The evidence that the markers move years ahead of the diagnosis

The clearest picture of the sequence comes from the Whitehall II study, which followed 6,538 British civil servants who did not have diabetes at baseline. Over a median follow-up of 9.7 years, 505 of them were diagnosed with type 2 diabetes. Because the cohort was tested repeatedly, the researchers could work backward and reconstruct what each marker had been doing in the years before that diagnosis.^[1]

The order matters. Insulin sensitivity, estimated by the HOMA method, declined steeply across the five years before diagnosis. Fasting glucose rose slowly and linearly for years, then turned sharply upward only about three years out, going from 5.79 mmol/L to 7.40 mmol/L, roughly 104 mg/dL to 133 mg/dL. Two-hour post-load glucose did the same thing on the same three-year timeline, from 7.60 mmol/L to 11.90 mmol/L, roughly 137 mg/dL to 214 mg/dL. Beta-cell function actually rose between four and three years before diagnosis, to 92.6 percent, before falling to 62.4 percent by the time of diagnosis.^[1]

Read that last sentence again, because it is the whole story in one line. The insulin-producing cells worked harder first. Blood sugar only moved when they could not keep it up. The authors describe changes appearing three to six years before diagnosis.^[1]

Two honest caveats. This cohort was 71 percent male and 91 percent white British civil servants, so the exact timeline is not automatically your timeline. And the group being described was on its way to a diagnosis, which most people reading this are not. The transferable finding is the sequence, not the schedule.

Marker by marker: what each number is actually telling you

Fasting glucose

What it is: the amount of sugar in your blood after eight or more hours without food. It is on every basic panel, it is cheap, and it is well standardized.

What it tells you: whether your body is currently succeeding at holding the line. That is genuinely worth knowing. What it does not tell you is how much effort that is taking, which is the part of the picture the Whitehall II trajectories make visible.^[1] A stable fasting glucose maintained by rising insulin output and a stable fasting glucose maintained easily look identical on this one line of the report.

Fasting insulin

What it is: how much insulin is circulating in that same fasted sample. It is not on a standard panel. It has to be requested.

What it tells you: roughly how much pressure the system is under to hold glucose where it is. Higher fasting insulin with normal glucose is the pattern that fasting glucose alone hides.

The important caveat is measurement. Insulin assays are not standardized across laboratories the way glucose is, which is a limitation the researchers who studied these markers named directly. In a study of 258 non-diabetic overweight volunteers whose insulin resistance was measured against a reference method, fasting insulin had an optimal cut-point of 109 pmol/L with 57 percent sensitivity and 85 percent specificity, and the authors concluded that in the absence of a standardized insulin assay, the more practical everyday approach was to use blood fats instead.^[2]

In plain terms: fasting insulin is informative, and a single result from one lab is not a verdict. Compare it against itself over time, at the same lab, rather than against a number you read online.

HOMA-IR

What it is: not a test at all. It is a calculation that combines your fasting glucose and your fasting insulin into a single estimate of insulin resistance. If you have both numbers, you have this one.

The model was published in 1985, and it was validated against the euglycemic clamp, the laboratory reference standard for measuring insulin sensitivity. The correlation was strong, with a rank correlation of 0.88.^[3] That is why the calculation is still in use four decades later.

The same paper was candid about the limits. The coefficient of variation for the insulin resistance estimate was 31 percent, and the authors stated plainly that this low precision limits its use.^[3] A later review by the same group described where the model belongs and where it does not: it is well suited to cohort and epidemiological work, it has the real advantage of needing only one blood draw, and it should not be used to judge beta-cell function in isolation. Their closing point applies to any single patient reading their own number, which is that the input data have to be robust and the result has to be interpreted carefully.^[4]

Practically, that means a HOMA-IR that moves from 3.4 to 2.1 across two draws several months apart is a signal worth discussing. A HOMA-IR that moves from 2.2 to 2.0 is noise.

Triglycerides and the triglyceride to HDL ratio

What it is: two numbers already sitting on the standard lipid panel you have almost certainly had done, plus one division.

This is the sleeper marker, and it is the one most likely to be available to you right now at no additional cost. In that same study of 258 overweight non-diabetic adults, the researchers tested which routine markers best identified the people who were genuinely insulin resistant. Triglyceride concentration, the triglyceride to HDL ratio, and insulin came out on top. The optimal cut-points were 1.47 mmol/L, about 130 mg/dL, for triglycerides, and 3.0 in the traditional units used on a US lab report for the ratio. Sensitivity and specificity were 67 and 71 percent for triglycerides, and 64 and 68 percent for the ratio.^[2]

For context, the authors compared those simple cut-points against the full Adult Treatment Panel III criteria for metabolic syndrome, which performed at 52 percent sensitivity and 85 percent specificity. Two numbers you already have did about as well as a formal multi-criteria definition.^[2]

Note what those percentages mean, though. Sensitivity in the sixties is not a test that finds everyone. It is a flag that raises a question, and the question goes to your physician.

Hemoglobin A1c

What it is: a measure of how much sugar has attached to hemoglobin in your red blood cells, usually described as a three-month average of blood glucose.

What it tells you: a longer view than a single fasting draw, which is exactly why it is useful. The description as an average, though, quietly assumes that everyone's red blood cells live the same length of time. They do not. Researchers who labeled and tracked red cells directly found that the mean age of circulating red cells ranged from 38 to 60 days in people without diabetes, and from 39 to 56 days in people with diabetes. That range was wide enough, they concluded, to cause clinically important differences in HbA1c for the same average blood glucose.^[5]

That study was small, twelve people in total, so treat it as a reason for humility about a single A1c rather than as a reason to dismiss the test. The practical takeaway is that when A1c disagrees with the other markers, the disagreement itself is information, and neither number automatically wins.

Waist circumference

What it is: a tape measure. No lab, no fasting, no cost.

It belongs on this list because a consensus statement from the International Atherosclerosis Society and the International Chair on Cardiometabolic Risk working group on visceral obesity argued that waist circumference gives information that is both independent of and additive to BMI for predicting morbidity and risk of death, and that it is still not routinely measured in clinical practice. That group recommended treating it as a vital sign, recommended reductions in waist circumference as an important treatment target, and noted that meaningful reductions can be achieved through routine moderate-intensity exercise or dietary change.^[6]

For a reset, this matters for a specific reason: it is the only marker on this list you can check yourself, monthly, without ordering anything. We covered why the tape often moves before the scale does in better ways to measure progress.

Which of these actually respond, and how fast

The reason to read the markers at all is that several of them move in response to things you can do. Three findings are worth knowing.

Modest weight loss moves insulin sensitivity in several organs at once. In a randomized controlled trial, adults with obesity who lost about 5 percent of body weight improved insulin sensitivity in adipose tissue, liver, and muscle, and improved beta-cell function, all at the 5 percent mark. Losing more produced further gains in muscle insulin sensitivity and beta-cell function.^[7] Five percent is 9 pounds for a 180-pound person, which is a nearer target than the number most people set for themselves.

When you walk matters, not just whether you walk. In a randomized crossover study of 41 adults with type 2 diabetes, two weeks of walking 10 minutes after each main meal was compared with two weeks of walking 30 minutes once a day. Both met physical activity guidelines. The post-meal pattern produced lower post-meal glucose, with a ratio of geometric means of 0.88, and the effect was largest after the evening meal at 0.78, the meal that carried the most carbohydrate.^[8] These participants had diagnosed type 2 diabetes, so the size of the effect will not transfer exactly, but the timing principle is cheap to apply.

Short sleep degrades glucose handling quickly. When 11 young men were restricted to 4 hours in bed for 6 consecutive nights, glucose tolerance was measurably lower than after 6 nights of extended sleep, evening cortisol was raised, and sympathetic nervous system activity was increased.^[9] Six nights. That is one hard week at work, and it is the reason a provider asks about your sleep before concluding that your eating plan stopped working. We go deeper into that mechanism in sleep, cortisol, and the metabolic reset.

Read them as a set, never one at a time

No single marker on this page is strong enough to carry a conclusion by itself. Each one has a specific blind spot: fasting glucose is late, fasting insulin is assay-dependent, HOMA-IR inherits both of those plus its own imprecision, the triglyceride ratio misses a third of the people it is looking for, and A1c assumes a red cell lifespan you have not measured.

Read together, those blind spots stop overlapping. A normal fasting glucose with high fasting insulin, a triglyceride to HDL ratio above 3,^[2] and a waist that has grown two inches in three years is a coherent picture, and no one line of it would have raised a flag alone. That is the actual argument for a provider reviewing a panel with you rather than a portal showing you which values fell outside a reference range.

It is also worth being clear about what a reference range is. It describes how results are distributed in the population the lab drew from. It is not a statement about what is optimal for you, and the sample it was drawn from is not necessarily a metabolically healthy one. "Within range" and "where you want to be" are two different questions, and only the first one is printed on the report.

Questions patients actually ask

"My doctor said my labs were fine. Are you saying they were wrong?"

No. A physician reading fasting glucose and A1c against diagnostic criteria is doing exactly the right job, which is deciding whether you meet the threshold for a disease. That is a different question from whether your metabolism is under strain. Both questions are legitimate, and the second one is the one a reset is aimed at. If you want the second question answered, the move is to ask for the additional markers, not to distrust the first answer.

"Should I ask for a fasting insulin test?"

That is a conversation with the clinician who orders your labs, and it is a reasonable request to bring. If you would rather start with what you already have, pull your most recent lipid panel and divide triglycerides by HDL. That ratio was one of the best-performing simple markers in the research above, and it costs nothing to calculate tonight.^[2]

"Do I need a continuous glucose monitor?"

Most people starting a reset do not, and one added at the start usually generates more anxiety than insight. The markers above are cheaper, better validated for this specific question, and easier to act on. If your provider suggests one later for a specific reason, that is a different conversation.

"How often should these be rechecked?"

Frequently enough to see a trend and rarely enough that you are seeing signal rather than noise. Given the 31 percent coefficient of variation reported for the HOMA-IR estimate, two draws a few weeks apart will not tell you much.^[3] Your ordering clinician sets the interval. Waist circumference is the one you can check monthly on your own.

What to bring to your next visit

If you want this to be a productive conversation rather than a general one, arrive with four things:

1. Your actual lab reports, not your memory of them. The trend across two or three panels is worth more than any single value, and only the documents carry the trend.
2. Your triglyceride to HDL ratio, already calculated. Both numbers are on any standard lipid panel you have had done.
3. Your waist measurement, taken the same way each time. Same point on the torso, same time of day, recorded with the date.
4. An honest account of your sleep. Not your intention. Your actual average over the last two weeks.

That set lets a provider see the pattern rather than one value, which is the entire premise of how a Practice Naturals program is structured. The framework behind it is laid out on our approach page, and the day-to-day mechanics of insulin and cravings are covered in insulin, cravings, and the blood sugar roller coaster. If you want to know why a generic calorie number tends to miss for the same reason a generic reference range does, that is in why generic calorie targets do not work.

Bottom line

Insulin resistance is not a number on a report. It is a strain on a system, and the markers are just the windows you get to look through. Glucose shows you the outcome after the compensation has failed. Insulin, the HOMA-IR calculation, the triglyceride to HDL ratio, A1c, and a tape measure each show you a different part of the effort it is taking to hold the line, and each one has a flaw the others partly cover.

The useful news is that the same markers respond to the same small set of inputs. Roughly 5 percent of body weight, walking after meals instead of only once a day, and protecting sleep all show up in the research on this page. None of that requires a new test to start.

If you want someone reading your numbers as a pattern instead of a pass-fail column, find a Practice Naturals provider near you and bring your last two lab reports to the first visit.

References

1. Tabák AG, Jokela M, Akbaraly TN, Brunner EJ, Kivimäki M, Witte DR. Trajectories of glycaemia, insulin sensitivity, and insulin secretion before diagnosis of type 2 diabetes: an analysis from the Whitehall II study. Lancet. 2009;373(9682):2215-2221. PubMed
2. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Annals of Internal Medicine. 2003;139(10):802-809. PubMed
3. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-419. PubMed
4. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004;27(6):1487-1495. PubMed
5. Cohen RM, Franco RS, Khera PK, et al. Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1c. Blood. 2008;112(10):4284-4291. PubMed
6. Ross R, Neeland IJ, Yamashita S, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nature Reviews Endocrinology. 2020;16(3):177-189. PubMed
7. Magkos F, Fraterrigo G, Yoshino J, et al. Effects of moderate and subsequent progressive weight loss on metabolic function and adipose tissue biology in humans with obesity. Cell Metabolism. 2016;23(4):591-601. PubMed
8. Reynolds AN, Mann JI, Williams S, Venn BJ. Advice to walk after meals is more effective for lowering postprandial glycaemia in type 2 diabetes mellitus than advice that does not specify timing: a randomised crossover study. Diabetologia. 2016;59(12):2572-2578. PubMed
9. Spiegel K, Leproult R, Van Cauter E. Impact of sleep debt on metabolic and endocrine function. Lancet. 1999;354(9188):1435-1439. PubMed

These statements have not been evaluated by the Food and Drug Administration. Practice Naturals products are not intended to diagnose, treat, cure, or prevent any disease. This article is for educational purposes only and is not a substitute for professional medical advice. Consult your licensed healthcare provider before beginning any wellness program. Individual results vary.