Methodology

Unit of Output

Each page represents one analyte, one demographic group, and one data source. Percentiles are not pooled across sources unless explicitly stated. Where multiple sources exist for the same analyte, each is presented and attributed separately.

What We Do

For each analyte and demographic group, we identify a suitable published dataset, apply defined and documented inclusion and exclusion criteria, and compute percentile values (P5, P25, P50, P75, P95) from the participant-level microdata. The same computation and filtering approach is applied consistently across pages unless explicitly stated otherwise. The source, criteria, and sample size are stated on every data page. All values can be independently reproduced from the stated source, survey cycle, and exclusion criteria.

Source Selection

We only use sources that are:

• Peer-reviewed and publicly available
• Based on a defined population with documented sampling methodology
• Measured using standardized laboratory methods
• Of sufficient sample size for the demographic group
• Representative of a defined measurement context (for example, fasting vs. non-fasting, clinical vs. general population)
• Free from obvious conflicts of interest

Sources vary by analyte. Each is documented in full on its reference page. No assumption is made that values from different sources are directly comparable.

How Percentiles Are Computed

Percentiles are computed from participant-level microdata using unweighted quantile estimation. Where a source uses a complex survey design, we do not apply survey weights. Those weights are designed for national prevalence inference, not distributional reference. Unweighted quantiles are transparent, reproducible, and appropriate for our purpose. Users requiring nationally representative estimates should consult the source dataset's published analyses.

We report P5, P25, P50 (median), P75, and P95 for each demographic group and survey cycle.

Reference Populations

The reference population varies by analyte. Some pages use the full survey population for a demographic group; others apply additional filters (for example, excluding pregnant participants or restricting to fasting samples). Criteria are chosen to match the measurement protocol of the source dataset. There is no universal reference definition applied across all analytes. Exclusion criteria are listed on each data page.

What a Percentile Means

A value at P50 is the median: half the reference population measured above it, half below. A value at P5 means 95% of the reference population measured higher.

Percentiles reflect measured values, not biological absolutes. A result is influenced by pre-analytic conditions (fasting status, sample handling, time of day), assay method, and calibration. The distributions here reflect those real-world conditions as documented in the source study.

Percentiles describe distributions. They do not define what is healthy, normal, or optimal. The same value can carry different clinical significance depending on context, symptoms, and other factors only a clinician can assess.

Limitations

• Not nationally representative. Unweighted percentiles from complex survey datasets do not account for sampling design and should not be cited as national prevalence estimates.
• Population scope. Much of the current data is drawn from US surveys and may not generalize to other countries or underrepresented populations.
• Cross-sectional. Survey data is a snapshot. Values from older cycles may not reflect current distributions.
• Measured, not biological. Distributions reflect what was measured under source study conditions. Pre-analytic variation, assay differences, and calibration shifts are not corrected for.
• Assay variability. Methods and calibrations differ between studies. Values from different sources are not always directly comparable.
• Small subgroups. Narrow demographic cuts may rest on small samples, reducing the stability of P5 and P95.
• No clinical validation. These are descriptive statistics, not validated diagnostic thresholds.
• Source heterogeneity. Sources vary in population, design, and measurement standards. Each is evaluated individually; no claim is made that values across sources are directly comparable.

What This Site Does Not Do

LabNorms does not diagnose, interpret results clinically, define healthy or optimal ranges, personalize results, or give advice of any kind. Individual lab results should always be interpreted by a qualified clinician.