1. Introduction: A Single Number Does Not Tell the Whole Story

Imagine that you receive a laboratory test report and see that your hemoglobin value is given as a single number.
What does this number mean on its own? Is it high, low, or exactly as it should be?

The truth is that a single number is not clinically meaningful by itself. To be interpreted correctly, it must be compared with a reference point. In medicine, this reference point is called the reference interval.

Many people perceive the concept of a “normal value” as a single number. However, this is not correct. Because of natural biological variability among healthy individuals, laboratory test results are always evaluated as a range, not a single value.

Therefore, interpreting a test result means:
not just looking at the number,
but understanding where that number falls within the range defined for healthy individuals.

So, what are these ranges, and how are they determined?

2. What Is a Reference Interval and How Is It Determined?

A Reference Interval (RI) defines the range of values within which a laboratory test result is most likely to fall in individuals considered healthy, that is, without pathological conditions.

Traditional (Direct) Method

The classical approach is based on studies conducted in healthy volunteers:

1.     Selection of a Healthy Group
Individuals who are considered “apparently healthy” are selected according to predefined inclusion and exclusion criteria.

2.     Sample Analysis
Blood, urine, or other biological samples are analyzed in the laboratory.

3.     Statistical Calculation
The central 95% of the result distribution
(between the 2.5th and 97.5th percentiles) is defined as the reference interval.

Indirect Methods

Creating large groups of healthy volunteers is both difficult and costly. For this reason, indirect methods are increasingly used in modern laboratory medicine.

In this approach:

·       Tens of thousands, or even hundreds of thousands, of test results routinely collected in hospital information systems are analyzed.

·       Results from individuals known to have diseases are excluded using advanced statistical techniques.

·       The remaining “presumably healthy” population is used to establish the reference interval.

This method demonstrates how powerful existing healthcare data can be when reanalyzed appropriately.

However, one key question remains:
Are these reference intervals the same for all ages?

3. One of the Strongest Determinants of Change: Age

Laboratory results are influenced by several factors, known as covariates, that affect test outcomes. These include:

·       Sex

·       Ethnic background

·       Geographic region

Among these, age has a uniquely strong and continuous effect that cannot be compared with the others.

The human body is not static. Especially during:

·       Infancy

·       Childhood

·       Adolescence

·       Older age

biological systems undergo continuous change.

For this reason:
a value that is considered “normal” at 5 years of age
may no longer be considered “normal” at 15 years of age.

This dynamic nature becomes clearer when examined through specific biomarkers.

4. Biochemical Traces of Growth: Practical Examples

Some laboratory tests reflect growth and development almost like biochemical fingerprints.

4.1. Marker of Bone Development: Alkaline Phosphatase (ALP)

ALP is closely related to bone growth and shows distinct peaks throughout life:

·       First Peak (Infancy):
Rapidly increases after birth and reaches a peak at around 3–4 months of age.

·       Second Peak (Adolescence):
Rises again during the pubertal growth spurt.

o   In girls: approximately 11–13 years

o   In boys: approximately 13–15 years

·       Sex Difference:
In males, the peak is both higher and occurs at a later age.

4.2. Reflection of Muscle Mass: Creatinine

Creatinine is a product of muscle metabolism, and its age-related pattern is more continuous:

·       It increases gradually and steadily with age.

·       During adolescence, because muscle mass increases more rapidly in males:

o   The difference between males and females becomes more pronounced.

o   The increase continues for a longer period in males.

4.3. Oxygen-Carrying Capacity: Hemoglobin (Hb)

Hemoglobin levels undergo important adjustments throughout life:

·       They decrease during the first months after birth.

·       They gradually increase throughout childhood.

·       With adolescence:

o   Higher levels are observed in males.

o   A clear sex-related difference emerges.

4.4. Comparison of Growth Periods

Test	Infancy and Childhood	Adolescence
ALP	High due to rapid bone growth, with an early peak	Second peak during the growth spurt
Creatinine	Slow and continuous increase	Accelerated rise with increasing muscle mass (especially in males)

 

5. Visualizing Change: Discrete and Continuous Intervals

There are two main approaches to represent age-related changes in reference intervals.

Discrete (Stepwise) Intervals

·       Age groups are defined (e.g., 1–5, 6–12 years).

·       A fixed reference interval is assigned to each group.

·       Disadvantages:

o   Biologically unrealistic abrupt changes

o   A shift from “normal” to “abnormal” with only a one-day age difference

Continuous Intervals

·       Models such as GAMLSS or Fractional Polynomial Regression are used.

·       Changes are represented by smooth curves.

·       Advantages:

o   Reflect true biological processes

o   Allow calculation of z-scores

o   Precisely locate a value relative to age-matched peers

This approach follows the same principle as height and weight growth charts used in pediatrics.

6. Conclusion: The Key Word Is Context

Correct interpretation of a laboratory test result requires much more than simply looking at a number.

The three key messages from this guide are:

1.     “Normal” is not a single number, but a range.

2.     Reference intervals are dynamic,
especially with respect to age and sex.

3.     Interpretation requires context.
Results gain meaning only when compared with the correct age- and sex-specific reference interval.

Human biology is not static but continuously changing. Laboratory results should reflect this reality.