How We Verify Our Numbers

The studies use one calculation framework, but not one source list. Grocery foods and restaurant menu items have separate provenance and verification rules below.

Page last updated July 30, 2026.

When we publish a number like "black beans give you 10.4 grams of fiber per dollar," that grocery number comes from a USDA nutrition record divided by a documented shelf price. A fast-food number starts somewhere else: the restaurant chain's published nutrition data and a documented menu-price observation. This page explains both tracks, the math they share, and what happens when we get one wrong.

Two grocery rankings run often enough that we gave them names: the Fiber per Dollar Index (53 foods scored on dietary fiber grams per dollar) and the Protein per Dollar Index (49 sources scored on protein grams per dollar). They use the grocery rules below and a scheduled quarterly price re-audit. Their files sit on the data page.

Where the data comes from

The grocery as-purchased rule

Grocery calculations use the food as it sits in your cart, not as it sits on a lab bench. Dry lentils are priced and measured dry. Canned beans are measured drained, because nobody eats the can liquid on purpose. If a grocery study compares cooked values, it says so explicitly and shows the conversion. Mixing "per 100g cooked" with "per 100g dry" is how you get rankings that look impressive and mean nothing, so we don't do it.

Grocery edible-fraction adjustments

A pound of oranges is not a pound of orange. Peels, pits, rinds, and bones come out of the math before anything gets ranked. We apply USDA refuse percentages to adjust the price to the part you actually eat. This matters more than people expect: skipping this step quietly flatters foods with heavy waste, like avocados and winter squash.

Verification status by source class

Grocery studies: the study page states the date and scope of any documented nutrition or price recheck. The July 4, 2026 fiber audit, for example, rechecked the published fiber values against FoodData Central and corrected six affected foods. We don't turn that documented audit into a blanket verification claim for every grocery row.

Restaurant studies: the fast-food study uses chain-published nutrition sources recorded in its CSV. The CSV documents independent second-source checks for 2 of the top 5 items. One additional top-five item was checked against a second endpoint from the same chain, which isn't an independent source. We don't claim independent checks for the other rows.

Protein-quality study: every published DIAAS row exposes its diaas_method, diaas_score, diaas_source, and any proxy limitation in notes. A field-level citation documents provenance; it doesn't mean we independently reproduced the underlying digestibility study.

Who is responsible for the review

David Miller, the site's founder and editor, runs the data checks and documents the sources. He isn't a registered dietitian or medical professional. This methodology is designed to make food-price and nutrient calculations inspectable; it doesn't turn a cost ranking into personal nutrition advice. Claims that depend on health guidance should point to a primary government or clinical source, and readers should use a qualified healthcare professional for decisions specific to them.

This page covers the math and source rules for original research. The editorial standards cover authorship, recipes, explainers, tools, automation, and the sitewide correction process.

Every study ships its raw data

Each data study publishes its comparison rows as a public CSV. Grocery files include the fields their math needs, such as food, nutrient value, package price, edible fraction, and grams per dollar. The fast-food file instead records chain, menu item, protein, observed price, grams per dollar, nutrition source, and price basis. The field sets differ because the inputs differ. The protein-quality file adds DIAAS method, score, field-level source, adjusted value, and proxy notes. No "data available on request." The rows used for the rankings are right there.

You're welcome to reuse the data. Our original selection, arrangement, calculations, field descriptions, and explanatory material are available under CC BY 4.0, while third-party source material keeps its own status and terms. The data reuse page has the exact scope and copy-ready attribution.

When we get it wrong

We correct errors publicly, in the study itself, with a dated note. We don't quietly swap numbers and hope nobody noticed.

Real example: on July 4, 2026, an adversarial audit of the fiber per dollar study caught six values that needed correcting. We fixed them, re-ranked the affected foods, and published a correction note in the article. The audit process that caught them is now part of the standard pre-publish checklist.

How often the numbers get refreshed

The studies this applies to

Browse the complete collection and every available download on the research hub.

Questions about the data, or spotted something that looks off? Tell us. Getting corrected beats being wrong.