Last Updated: April 2026
At nutritionfactsdata.com, data accuracy is our core commitment. This page explains how we collect, process, verify, and update the nutritional profiles, caloric data, and macro breakdowns for 10,000+ foods and meals we publish.
Primary Data Sources
We source data from government databases (BLS, USDA, DOL, FRED), industry surveys, employer disclosures, and verified public datasets. International data uses local government equivalents where available.
How We Calculate Averages and Ranges
Where multiple sources report the same metric, we calculate a weighted average giving greater weight to larger sample sizes and more recent data. Experience brackets are standardized: Entry (0-2yr), Mid (3-5yr), Experienced (6-10yr), Senior (10+yr).
Update Frequency
Our database is reviewed monthly. Individual articles show a “Last Verified” date. Major annual updates publish each January with new government data. Significant market changes trigger out-of-cycle updates.
Limitations and Disclaimers
Our data represents aggregated averages and should be understood as benchmarks, not guarantees. Actual values vary based on individual circumstances. All figures presented in good faith based on available data at time of publication.
Reporting Errors
If you believe any figure is incorrect, contact us. We review every report and correct confirmed errors within 48 hours.
What We Do When Sources Disagree
Data conflicts are common in nutrition facts research. Government sources, industry surveys, and employer-reported data rarely agree perfectly — they use different sample sizes, different collection periods, and different definitions of the same variable. When we encounter conflicting figures, our process is: identify which source has the larger, more recent, and more representative sample; weight that source more heavily in our calculation; and note the discrepancy in the article so readers can evaluate it themselves.
We do not average conflicting sources blindly. If a government dataset of 50,000 employers says one thing and a voluntary survey of 200 professionals says another, those are not equivalent data points. We explain the difference rather than splitting it artificially down the middle.
Handling Estimates and Projections
Some figures on nutritionfactsdata.com are estimates derived from modeling rather than directly reported data. This happens when primary data is unavailable for a specific segment — a particular city, role, or niche market where no survey has sufficient coverage. In these cases, we use regression modeling based on related data points and clearly label the result as an estimate. We never present a modeled figure as if it were directly measured.
Projections — figures about future states — are labeled explicitly and based on historical trend extrapolation. We do not claim to predict markets. Projections are offered as a structured way to think about direction, not as forecasts.
Corrections and Accountability
When readers identify errors — and they do, regularly — we correct them promptly and transparently. Significant corrections are noted at the top of the affected article with the date of correction. Minor corrections (typos, formatting) are fixed silently. We maintain an internal corrections log that tracks every data change we make and why.
To report a potential error, use our contact form and include the article URL, the specific figure you believe is incorrect, and your source for the correct figure. We review every report and respond within 48 hours. Confirmed corrections are applied within the same business day.