What is an IGF-1 z-score?
A z-score is a way of answering one question: how does my result compare with healthy people who are the same age and sex as me?
It is easier to understand if you picture a bell curve. If you lined up the IGF-1 results of thousands of healthy adults the same age and sex as you, most results would cluster in the middle and fewer would sit far above or far below that middle. The middle of the curve is the average, or mean. The z-score tells you how many "steps" above or below that average your own result falls, where each step is a standard deviation — a fixed-size unit that describes how spread out the group is.
A z-score of zero means you sit right at the average for your age and sex. A z-score of +1 means you are one step above average. A z-score of −2 means you are two steps below. By convention, the range from −2 to +2 covers roughly 95% of a healthy reference population — so most people, most of the time, sit within that band.
The reason clinicians use z-scores for IGF-1 is that the raw number — a plain figure in ng/mL — is hard to read without knowing the reference range for your exact age, sex, and laboratory. A z-score bakes that context in for you automatically.
| Z-score | Where you sit in the reference group | What it generally signals |
|---|---|---|
| Below −2 | Markedly below average for age/sex | May warrant evaluation for GH deficiency, malnutrition, liver or thyroid issues |
| −2 to −1 | Mildly below average | Often still within the low-normal range; context matters |
| −1 to +1 | Close to average | Typical for a healthy person of your age and sex |
| +1 to +2 | Mildly above average | Often still within the high-normal range; not automatically a concern |
| Above +2 | Markedly above average for age/sex | May warrant evaluation for GH excess (acromegaly) or other causes |
Why use a z-score instead of the raw number?
The short answer is that IGF-1 changes so much with age that the raw number is nearly unreadable without extra context.
IGF-1 is highest when you are young. It peaks in your late teens, then gradually falls for the rest of your life. One large population study put the average decline at about 15% every ten years. So a raw IGF-1 of 120 ng/mL looks completely different depending on who you are: it might be low-normal for a healthy 25-year-old and perfectly typical for a healthy 65-year-old.
The z-score solves this by comparing you to people your own age, not to one fixed universal target. When you look at a z-score, the age adjustment is already done. A z-score of −1.2 at age 30 and a z-score of −1.2 at age 65 both mean the same thing: you sit modestly below the average for your age — whether that raw number is 180 or 85.
Sex matters too. Men and women tend to have slightly different IGF-1 distributions at the same age, which is why most reference populations are reported separately for each sex and why z-scores that account for sex are more informative than those that do not.
Clinicians also find z-scores useful for tracking changes over time. If your IGF-1 falls 30 points over three years, is that meaningful? It depends on where you started and how much natural decline to expect at your age. But if your z-score drops from −0.5 to −1.8 over the same period, that is a clear downward shift relative to your reference group — much easier to see and act on.
How is an IGF-1 z-score calculated?
The calculation is straightforward once you have the right reference data.
A laboratory — or the clinician using a standardized formula — takes three numbers: your raw IGF-1 result, the average IGF-1 for healthy people your age and sex using the same assay, and the standard deviation of that reference group. The z-score is then: (your result minus the reference mean) divided by the reference standard deviation.
As an example: say your result is 130 ng/mL. The mean for your age-sex group on that lab's assay is 160 ng/mL, and the standard deviation is 40 ng/mL. Your z-score is (130 − 160) ÷ 40 = −0.75. That puts you modestly below average but still within the typical range.
The critical ingredient is the reference data — the mean and standard deviation for your age-sex group. Those numbers come from studies that measured IGF-1 in hundreds or thousands of healthy volunteers and published the distributions. One of the foundational datasets in European populations is the Study of Health in Pomerania (SHIP), which measured 2,499 adults aged 20 to 79 and reported age- and sex-specific reference values. Reference datasets like SHIP are what give a z-score its meaning.
| Step | What you do | Example (made-up numbers) |
|---|---|---|
| 1 | Get your raw IGF-1 result | 130 ng/mL |
| 2 | Find the reference mean for your age and sex (from your lab or a published dataset) | 160 ng/mL |
| 3 | Find the reference standard deviation | 40 ng/mL |
| 4 | Subtract: your result minus the mean | 130 − 160 = −30 |
| 5 | Divide by the standard deviation | −30 ÷ 40 = −0.75 |
| 6 | That is your z-score | −0.75 (modestly below average, within typical range) |
What does a high or low z-score mean?
A z-score tells you where you sit in the reference population. It does not tell you why you sit there — that is a question for a clinician who can see your whole picture.
A markedly low z-score (roughly below −2) means your IGF-1 is much lower than would be expected for a healthy person your age and sex. The most common explanations are not exotic: eating too little or losing significant weight lowers IGF-1, because the liver makes less of it when the body is short on fuel. Problems with the thyroid or the liver can lower it too. Only after weighing those everyday causes would a clinician consider a rarer diagnosis like growth hormone deficiency, which usually requires additional, more specific testing — not a z-score alone.
A markedly high z-score (roughly above +2) means your IGF-1 is much higher than expected. The main condition a clinician wants to rule out is acromegaly — a rare disease in which the pituitary gland makes too much growth hormone over years, causing real harm if untreated. A clearly elevated z-score alongside symptoms like joint pain, enlargement of hands or feet, or changes in facial features is a reason to see an endocrinologist. A z-score just slightly above +2, with no symptoms, is usually a "look at the full picture" situation rather than an emergency.
A z-score in the typical range (−1 to +1) does not rule out every problem, but it is a reassuring starting point. In the right clinical context it suggests the growth-hormone–IGF-1 axis is likely functioning within normal limits for your age and sex.
One caution worth stating plainly: large population studies have found that people with naturally higher IGF-1 have a modestly higher association with certain cancers, such as prostate cancer and premenopausal breast cancer. A Lancet meta-analysis of 22 studies put the odds ratio at about 1.49 for prostate cancer and 1.65 for premenopausal breast cancer comparing the highest with the lowest IGF-1 quartiles. That is an association across populations, not a verdict on any one person. But it is the reason "push your IGF-1 z-score as high as possible" is not sound advice, and why clinicians treat a markedly elevated z-score as something to evaluate rather than celebrate.
Why z-scores still depend on which lab you use
Even z-scores are not fully portable from one lab to another, and this surprises people who expected the z-score to solve the lab-variability problem entirely.
Here is the issue. The z-score is calculated using a reference mean and standard deviation from a specific population, measured on a specific assay. If two labs use different assays — different machines, different chemistry — their reference populations may sit at different absolute levels. The same blood sample, run through six different commercial IGF-1 tests, produced similar lower limits but markedly different upper limits across the assays in one head-to-head study. In plain terms: what counts as +2 standard deviations above average on Lab A's assay may correspond to a different raw number than +2 on Lab B's assay, because the two assays calibrate differently.
This is not a small problem. Researchers who tested the same blood samples on multiple assays in the same study found "noteworthy differences" in the reference intervals, with the same healthy volunteer sometimes reading as normal on one test and high on another.
The practical consequence is the same as for raw numbers: use the same lab and the same assay each time your IGF-1 is measured, especially if a clinician is tracking a trend. The z-score from one lab is not directly comparable to the z-score from another lab without knowing whether both used the same assay and the same reference population. This is why guidelines recommend using the same assay throughout a patient's follow-up.
How z-scores are used in practice
Endocrinologists use IGF-1 z-scores in two main clinical settings: evaluating someone for possible growth hormone deficiency and monitoring someone already known to have a growth-hormone disorder such as acromegaly.
In the evaluation of possible GH deficiency, a markedly negative z-score — combined with symptoms and, usually, a GH stimulation test — is part of the picture that supports a diagnosis. A single low z-score on its own is not sufficient; it is one piece of evidence that gets weighed against the clinical picture and other tests.
In the monitoring of acromegaly treatment, the z-score is useful because it tracks a moving target. As successful treatment brings GH secretion back toward normal, the IGF-1 should fall — and watching the z-score over time shows whether it is moving toward the typical range and whether treatment is hitting its goal.
The z-score is also useful for comparing findings described in research publications. When different studies use different assays with different absolute values, a z-score can make the findings easier to compare across papers, because it expresses each result in relative rather than absolute terms.
Outside of those clinical and research contexts, a one-off z-score without a clinical question attached is just a number. What it means depends entirely on why the test was ordered and what the rest of the picture looks like. That interpretation belongs with a licensed clinician, not an article.
Keeping track of IGF-1 trends with PeptidePanel
Nothing here is medical advice, and PeptidePanel does not sell, supply, prescribe, or recommend anything. What an IGF-1 z-score means for you, and what to do about it, is a conversation for a licensed clinician who can see your complete health picture.
What PeptidePanel does is keep the record straight over time. If a clinician has you monitoring IGF-1 at regular intervals, PeptidePanel stores each result, plots the trend, and displays each number next to the reference range printed on your lab report — so a slow drift across years is just as visible as a single out-of-range reading. That organized record is what a clinician looks at when they want to know whether a z-score is stable, improving, or drifting in a direction worth discussing at your next appointment.