Framingham Risk Calculator
The formula
What the framingham 10-y risk tells you
The original offspring-cohort risk engine: six variables through published Cox coefficients to a ten-year coronary-disease probability.
Calculation: Anderson 1991 Framingham Cox function → 10-year CHD risk. Enter your inputs and every substitution is shown below the result.
Reading the result
Framingham underestimates risk when it comes to lifetime accumulation and misses South Asian ancestry — it is a floor, not a ceiling.
Rules of thumb: ATP III: ≥20% high, 10–20% moderate
Limitations and best practice
Framingham requires total cholesterol, not LDL — using the wrong input shifts the output; and it was calibrated on 1970s–80s Framingham, MA.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Is Framingham obsolete?
Does it predict stroke?
Source & methodology
Anderson Circulation 1991.
Framingham Risk explained: formula, worked example and honest limits
You are here because you need a specific number, and you want to see how it was produced before you rely on it. Framingham Risk is the kind of number people argue about from memory. This page ends that argument with arithmetic you can watch happen: enter your figures, get 10-year CHD risk in real time, and see every substitution printed below.
Trends beat snapshots. Framingham Risk measured once tells you where you stand today; measured monthly against Age tells you which way the needle is moving — and direction is the actionable information in Clinical Calculators.
A calculation like this one is worth roughly as much as a careful sentence: it forces several vague considerations into one comparable quantity. Once Framingham Risk is on the table, the argument can stop being about impressions.
Nothing below is stock text pasted around a number: the worked example computes 10-year CHD risk = 0.5% from this tool’s own defaults, and the sensitivity section ranks the inputs that move the result — HDL first, at ≈604.5 % of the headline for a ten-percent error either way in that input — which is the thread the rest of this guide pulls on.
Inside the Framingham Risk calculation: formula and every input
One formula, published in full: Anderson 1991 Framingham Cox function → 10-year CHD risk. Anything you can read, you can reproduce in a spreadsheet, and that reproducibility is the whole point of printing it rather than hiding it behind a button.
Age (example value 55) is a quantity rather than a category — precision here is cheap and worth having. Use the value as of today, not as of the last time you looked — time fields drift silently.
Total cholesterol (mg/dL) (example value 300) is a measured number in the unit named by the label; the formula does not convert for you. Double-check that the unit on your source matches the unit this field expects before typing.
HDL (mg/dL) (example value 44) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Figures of this kind carry safety consequences; when in doubt, use the conservative value and confirm with a professional.
Systolic BP (mmHg) (example value 135) is a measured number in the unit named by the label; the formula does not convert for you. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
On BP treatment? (0/1) (example value 0) is a quantity rather than a category — precision here is cheap and worth having. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Smoker? (0/1) (example value 1) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Sex (example value Male) is a branching choice rather than a figure you measure; the per-option effects are computed below. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
What each “Sex” choice actually does: Male → 0.5% · Female → 0.0% These figures are computed from this engine, not estimated — switch the dropdown above and you will land on exactly these numbers.
Framingham Risk on the example inputs: the complete substitution
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Age, Total cholesterol (mg/dL), HDL (mg/dL), Systolic BP (mmHg). The endpoint of that chain is 0.5% of 10-year CHD risk, sitting in the “A 0.5% ten-year risk is below the 10% action line (original Framingham adult CHD, not total CVD)” band.
- Cox linear predictor from age, TC, HDL, SBP (treated/untreated), smoking — coefficients from Anderson 1991
- 10-year probability = 1 − S0^exp(LP), S0 = 0.8833
- Result 0.5%
Points-style band — <10%. Compare it against the main result of 0.5% before drawing conclusions.
Smoking effect — included (roughly doubles). Read next to the headline, this is the figure that shows the shape of the trade-off.
BP treated adjustment — no. Compare it against the main result of 0.5% before drawing conclusions.
HDL credit — neutral. If your inputs change, this is usually the first companion figure to move.
Re-running with your own figures is instant; re-running by hand once is the best way to know the tool is telling you the truth.
How far Framingham Risk can reasonably move
The honest version of any estimate is a corridor, and this one is cheap to produce: Framingham Risk was recomputed at 5 points along the dominant input, with every other field left untouched.
| HDL setting | 10-year CHD risk |
|---|---|
| 80 % of the example value | 26.1% |
| 90 % of the example value | 3.3% |
| example inputs | 0.5% |
| 110 % of the example value | 0.1% |
| 120 % of the example value | 0.0% |
Across 5 settings of HDL, the result spans 0.0% to 26.1%. A decision that only works at one row of this table is a decision waiting for an input to move. Reproduce it in the form above by editing HDL alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Framingham Risk the most
This list was computed for this specific engine just now: each numeric input was nudged ±10 % while every other field held its example value, and the 10-year CHD risk was recalculated from scratch. Read it as a map of where Framingham Risk is fragile — drawn for the example inputs, which is the map you want when deciding what to measure carefully.
- Nudge HDL by ±10 % and Framingham Risk lands between 0.1% and 3.3% (sensitivity ≈604.5 %)
- Nudge Total cholesterol by ±10 % and Framingham Risk lands between 0.1% and 1.7% (sensitivity ≈261.5 %)
- Systolic BP: ten percent up gives 0.6%, ten percent down gives 0.4% — ≈29.7 % of the 10-year CHD risk either way
- Age +10 % → Framingham Risk = 0.5% · −10 % → 0.4% (the 10-year CHD risk shifts ≈9.3 %)
HDL is the dominant lever here: ten percent either way moves the result by about 604.5 %, from 0.1% to 3.3%. Measure that input from a document rather than from memory, and treat Total cholesterol as the second priority (≈261.5 % per ten percent). Everything below that can stay approximate, which is a licence to stop chasing data that would not change the decision.
What a Framingham Risk of 0.5% means in practice
Nobody acts on a bare figure — they act on a figure with a comparison attached. The default case lands in the “A 0.5% ten-year risk is below the 10% action line (original Framingham adult CHD, not total CVD)” band, and bands are deliberately wide because real situations overlap. The sensitivity list shows how far a modest input error moves you along that ladder: for HDL, ±10 % covers 0.1% to 3.3%. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
Related measures answer related questions, and the distinctions matter: Framingham Risk is the quantity, 10-year CHD risk is this tool’s reading of it, and the decision that follows belongs to neither of them separately.
How people get Framingham Risk wrong
Framingham requires total cholesterol, not LDL — using the wrong input shifts the output; and it was calibrated on 1970s–80s Framingham, MA. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Stopping at the first plausible answer. If the result surprises you, the productive question is which input would have to be wrong for the surprise to disappear — then go check that input.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows HDL dominating — a careful figure there beats false precision everywhere else.
The subtlest error is answering the wrong question precisely. Confirm that 10-year CHD risk is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
A quick check for any Framingham Risk figure
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Verify each input against its original source document, not memory.
- Check HDL before anything else: it is the measured dominant input, ≈604.5 % of Framingham Risk per ten percent.
- Compare the result with one independent method or published benchmark.
- Confirm the example values are plausible for your own situation before replacing them.
- Confirm the answer against one independent method or published benchmark for Framingham Risk.
How to use the Framingham Risk tool properly
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — start from evidence. The inputs behind Framingham Risk are age, total cholesterol (mg/dl), hdl (mg/dl), systolic bp (mmhg), on bp treatment? (0/1), smoker? (0/1) and the remaining fields listed above. Write them down with their source next to each one; if you cannot name where a figure came from, that is the input most likely to be wrong. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. Re-running a number costs seconds; retracting a decision costs considerably more.
Step 3 — change one input at a time. Nudge a single field by ten percent, watch the headline and its companions move, then undo it. Two or three fields will dominate — the sensitivity table above already ranks them for this engine. Estimates improve most when the worst case is written down in ink.
Step 4 — ask what would have to be true. Take the result you want and work backwards through the inputs until you find the assumption that produces it; then decide honestly whether that assumption is defensible. Numbers are cheap to produce and expensive to retract; the extra minute is the cheapest insurance available.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 0.5% output. Six months from now the context is what turns this figure into a trend. Suspiciously tidy answers deserve the same scrutiny as untidy ones.
From calculation to decision: where Framingham Risk earns its keep
Numbers earn their keep in conversations, and Framingham Risk is no exception. In Health & Medical discussions around Clinical Calculators, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. A result worth acting on survives having its two shakiest inputs halved.
Used properly this is a five-minute filter that saves weeks. Compute Framingham Risk, reject what fails, and only then bring in the expensive analysis for the survivors. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Re-running this page costs nothing and catches the slow drifts that never announce themselves. In Health & Medical the expensive mistakes are rarely sudden; they are small changes in Age that nobody recalculated for a year. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Quick answers: what searchers ask about Framingham Risk
What affects Framingham Risk the most?
The short answer: HDL. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the 10-year CHD risk recalculated — HDL moved it furthest, by roughly 604.5 % (0.1% to 3.3%).
Which matters more: total cholesterol or hdl?
For Framingham Risk, HDL wins the head-to-head (≈604.5 % against ≈261.5 % per ten-percent change). Knowing which input dominates is the difference between careful work and merely slow work.
How much does the “Sex” choice change the answer?
Across every option this tool offers, the 10-year CHD risk ranges from 0.0% (Female) to 0.5% (Male) with all other inputs held at their example values. The per-option table is printed in the inputs section — this is a decision that genuinely moves the number, not a cosmetic dropdown.
What is a typical Framingham Risk?
On the worked example above Framingham Risk comes out at 0.5%. Treat that as one point on a distribution rather than a norm: the bands, the companion outputs and the sensitivity ranking tell you how wide the plausible range really is.
How do I calculate Framingham Risk by hand?
Anderson 1991 Framingham Cox function → 10-year CHD risk is the entire method. Work the inputs in that order — Cox linear predictor from age, TC, HDL, SBP (treated/untreated), smoking — coefficients from Anderson 1991 — and you will reach 0.5% on the default figures, the same number this tool prints.
What happens to Framingham Risk if hdl changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 0.1% to 3.3% across the ten-percent probe, i.e. ≈604.5 % sensitivity on the 10-year CHD risk.
Is the Framingham Risk result of 0.5% good or bad?
The tool answers “what”, not “whether”: 0.5% carries the verdict “A 0.5% ten-year risk is below the 10% action line (original Framingham adult CHD, not total CVD)” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
How accurate is Framingham Risk for me personally?
The formula encodes averages; body-composition and measurement error typically shifts results by a few percent in either direction. Use ranges and trends, and treat any single 0.5% as approximate.
How do I calculate Framingham Risk manually?
Write down the inputs, then follow the printed steps in order — Anderson 1991 Framingham Cox function → 10-year CHD risk. A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
Is Framingham obsolete?
It remains validated, though ASCVD-PCE and QRISK are the current guideline engines.
Does it predict stroke?
The classic Framingham CHD function is coronary-only; separate stroke functions and total-CVD versions exist.
Do I need an account to use this Framingham Risk calculator?
No, and no data leaves the tab. The engine runs in the page itself, which is why the worked example, the bands and the sensitivity ranking all respond instantly to your keystrokes.
Key terms on this page
- Points-style band
- <10% for the Framingham Risk worked case; it sits next to the main result because it carries context the headline leaves out.
- Smoking effect
- included (roughly doubles) on the example inputs — a companion figure printed beside the headline of Framingham Risk so that no result is read in isolation.
- BP treated adjustment
- no for the Framingham Risk worked case; it sits next to the main result because it carries context the headline leaves out.
- 10-year CHD risk
- The primary output of this tool: 0.5% for the default inputs, computed exactly from Anderson 1991 Framingham Cox function → 10-year CHD risk.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The interpretation attached to a result (“A 0.5% ten-year risk is below the 10% action line (original Framingham adult CHD, not total CVD)” on these inputs), which turns a bare number into a position on a scale.
- Sensitivity (±10 %)
- How far the Framingham Risk moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Method, sources and what this tool cannot tell you
The model is published arithmetic implemented exactly as written: Anderson 1991 Framingham Cox function → 10-year CHD risk. Source of record: Anderson Circulation 1991. Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. Nothing is smoothed, weighted or adjusted behind the scenes; where judgement enters, this page says so and names the input responsible.
What to do with your Framingham Risk next
Re-run the calculation with your own figures, stress the two most sensitive inputs by ±10 %, and only then act on the result.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Health & Medical, a dated figure is a trend, and an undated one is a rumour.