Soybeans Glycemic Index and Calculate Your Own Glucose Response

No — not meaningfully alone. Across 177 meals where members ate soybeans without other foods, the average glucose peak was +28.5 mg/dL, with only 32.2% of responses exceeding +30 mg/dL. In our single-item cohort of 177 soybean logs, the median peak was +23 mg/dL and 43.5% of responses registered as low-spike (under +20 mg/dL). That places soybeans at the flattest end of the legume family — GI 15, the lowest Harvard-table value for any bean. Two levers do move the needle: total carb load at the meal (a ≥60g build raises peaks 55% above baseline, p<0.001) and meal timing (morning logs averaged 27.5% lower than the cohort mean). Eaten alone with low total carbs, soybeans are about as glucose-neutral as a substantial legume gets. These are observational findings, not causal.

• ▸Carb load dominates: meals with ≥60g total carbs spiked 55% higher than lighter builds (p<0.001, n=672 vs n=1,559) — the single largest modifier in the dataset.
• ▸Morning timing cut peaks 27.5% below the cohort mean (p<0.001, n=160) — the second-largest lever, ahead of any food pairing.
• ▸Carb escalation is steep: moving from a light (0–40g) to a very heavy (110g+) meal widens average peaks from +28.6 to +47.8 mg/dL — a 67% increase.
• ▸Adding leafy greens (spinach / kale / bok choy) held peaks ~5 mg/dL lower vs. no vegetables (n=199, medium confidence) — a modest but real vegetable benefit.

Three citable insights from this recipe's data

This meal stacks 3 independent spike drivers — together they account for +34 mg/dL.

Why this happens, physiologically

Soybeans are nutritionally unusual among legumes: roughly 17g protein and 9g fat per 1/2 cup cooked, with only ~13g net carbs in single-item logs. That macronutrient profile slows gastric emptying and blunts the rate of glucose entry into the bloodstream — the likely explanation for GI 15 (Harvard) and a single-item mean of +28.5 mg/dL across 177 logged meals. The two largest modifiers in the cohort are both contextual: total carb load (≥60g raises peaks 55%, p<0.001, n=672) and meal timing (morning logs average 27.5% lower than the cohort mean, p<0.001, n=160). The soybean's own carb content is a minor driver; what surrounds it is not. These are observational findings.

Calorie band and pairings (member-measured)

Frequently Asked Questions

Methodology

This page draws on Signos production CGM data logged between March 2025 and April 2026, covering 2,790 meals containing soybeans across 1,500 unique members (broader cohort), with a single-item sub-cohort of 177 meals (143 unique members) where soybeans were logged without other foods. Statistical comparisons use Welch's t-test on matched pairs; all modifier effects cited carry p<0.001 unless noted. Cohort filtering restricts to meals with a measured glucose rise between 0 and 100 mg/dL (ppgr_case='regular'). We report mean peak glucose rise across a right-skewed distribution; the single-item median (+23 mg/dL) is notably lower than the mean (+28.5 mg/dL). Soybean meals were identified via regex matching on logged food names, with explicit exclusions for soybean oil, soy sauce, and soy milk. A minimum cohort confidence of 'medium' (n≥100) is required for a food to publish; this food is at medium confidence.

Limitations

• Single-item cohort of n=177 logs (143 unique members) is medium-confidence — directional findings are reliable but point estimates carry wider uncertainty than high-confidence foods (n≥500).
• Dry-roasted soybean (soy nut) and soy-burger form options have very small sub-cohorts (n=9 and n=3 respectively) — those slots are directional only and not statistically meaningful.
• Self-reported portion sizes introduce noise — 'soybeans' in member logs may refer to varying serving sizes and preparations not fully distinguished in the regex.
• Cohort skews health-motivated; members using CGMs tend to be more metabolically aware than the general population, so average peaks may be lower than a representative sample would show.
• The morning timing effect (−27.5%, n=160) is observational — members who eat soybeans in the morning may have different baseline metabolic profiles than those who eat them at dinner.
• Soy sauce, soy milk, edamame, and tofu are excluded by regex; meal logs containing these alongside soybeans may have been partially excluded or partially included, creating some cohort boundary uncertainty.