Why are reference intervals not universal across populations, and what should laboratories do to ensure appropriate interpretation?

• A. Intervals are universal and should be applied globally.
• B. Intervals vary with age, sex, ethnicity, and pregnancy; laboratories should establish population-specific reference intervals.
• C. Intervals vary only with geography; labs should use neighboring population values.
• D. Intervals vary with time of day and should be sampled at noon.

Answer: (B)

Reference intervals track what is normal in a healthy population, and they are not universal because biology varies across people and life stages. As we age, organ function and physiology change, so what counts as “normal” for an analyte shifts. Sex differences—such as muscle mass and hormonal influences—also alter baseline levels. Ethnicity can reflect genetic and environmental factors that influence biomarker distributions, and pregnancy introduces substantial physiological changes that modify many laboratory values. Because of these differences, a value considered normal in one population or at one life stage may be outside the reference range in another, leading to misinterpretation if universal intervals are used.

Labs should establish or validate reference intervals that reflect their specific population and analytical method. This means developing population-specific intervals—often with separate ranges for different ages, sexes, and, when relevant, pregnancy status—using local healthy individuals and appropriate statistical methods. It’s important to document the basis of the interval (method, instrument, population characteristics) and to reassess intervals whenever assay methods or populations change. When direct establishment isn’t feasible, labs should at least validate applicable, demographically matched intervals for their patient population and clearly indicate any limitations during reporting.