A1C is often described as a three-month average of blood sugar. That description is useful, but it is incomplete enough to create confusion.
An A1C result is not a report card on how someone ate, exercised, or managed stress over the previous 90 days. It is a laboratory measurement of glucose that has attached to hemoglobin, the oxygen-carrying protein inside red blood cells.
That distinction matters because the result depends on more than glucose.
The American Diabetes Association’s 2026 standards continue to make an important point: A1C is an indirect measure of glucose exposure. When A1C and glucose results substantially disagree, the disagreement is information. It may point to a testing interference, a difference in red blood cell turnover, or a limitation in what either measurement can capture.
What A1C actually measures
Red blood cells circulate for roughly 120 days, carrying hemoglobin with them. As glucose circulates in the blood, some attaches to that hemoglobin. A1C reports the proportion of hemoglobin that is glycated, or has glucose attached.
Because red blood cells are continuously being made and cleared, A1C is not an equal-weight average of every day in the last three months. More recent glucose exposure contributes more to the result than exposure farther back in time.
A1C also does not show the shape of glucose patterns. Two people can have a similar A1C while having very different day-to-day experiences. One may have relatively steady glucose values. Another may have wider rises and falls that happen to average out similarly over time.
That is not a flaw in the test. It is a reminder that a summary statistic is still a summary statistic.
What people commonly infer
It is easy to look at an A1C and assume it gives a precise, complete account of average glucose and metabolic health. It does not.
It does not directly measure fasting glucose, insulin, glucose variability, post-meal patterns, or episodes of low glucose. It does not identify why a value is higher or lower. And it does not, by itself, establish whether a short-term change reflects a lasting trend.
It also does not measure motivation, discipline, or personal effort. A laboratory result can be clinically useful without becoming a judgment about the person attached to it.
Why red blood cells change the interpretation
A1C depends on two moving parts: glucose exposure and the lifespan of red blood cells.
If red blood cells circulate for less time than expected, they have less time to accumulate glucose. The A1C can read lower than the glucose exposure alone might suggest. Blood loss, hemolysis, transfusion, some anemias, kidney disease, pregnancy, and treatments that affect red blood cell production can all change this relationship.
The opposite problem can occur as well. Iron deficiency, for example, has been associated with falsely higher A1C results in some settings. The exact direction and size of an effect depend on the underlying situation, which is why a simple list of “things that raise A1C” is not enough for interpretation.
There is a second issue: analytical interference. Some inherited hemoglobin variants can interfere with particular laboratory methods. This is different from red blood cell lifespan. One is a problem with how a method detects the marker. The other is a problem with what the marker represents biologically.
The National Glycohemoglobin Standardization Program tracks whether specific A1C methods are affected by common hemoglobin variants. That detail may sound technical, but it represents a larger laboratory-literacy lesson: the name of a test does not tell us everything about how the result was produced.
Standardized does not mean context-free
A1C is one of the better-standardized laboratory tests in common use. Laboratories performing it for diagnosis are expected to use methods aligned with the National Glycohemoglobin Standardization Program.
Standardization is valuable. It means results have a shared analytical framework. But it does not erase biological variation, sample issues, assay-specific limitations, or the fact that different tests answer different questions.
A fasting glucose result is a measurement from one point in time. An oral glucose tolerance test looks at the response to a glucose challenge. A1C summarizes glucose exposure through hemoglobin over time. These are related measurements, not interchangeable versions of the same fact.
One result may be more informative than another in a particular clinical context. None should be asked to answer questions it was not designed to answer.
When results do not line up
Discordance is often treated as a nuisance. It can be more useful to see it as a question.
If A1C and glucose data do not seem to tell the same story, possibilities include ordinary variability, timing, changes in red blood cells, a hemoglobin variant, illness, medication effects, or limitations in the glucose data being compared. It does not automatically mean that one result is wrong.
The meaningful question is not simply, “Which number should I believe?” It is, “What does each number measure, and what assumptions would have to be true for these numbers to match?”
That is a better use of laboratory data. Not more certainty than the test can provide. More clarity about what the number represents.
Written for Dr. Teralyn Sell, PhD
Psychology · Brain Health · Human Behavior