How long will you live? Nobody actually knows, but the data says something useful. This calculator starts with a national baseline for your sex from WHO 2022 and CDC National Vital Statistics data across 30+ countries — and that baseline alone spans more than 13 years depending on where you were born. Japan and Switzerland sit near the top, Russia and the Philippines sit much lower, the US sits somewhere in the middle, and healthcare access is called out explicitly for each country because it changes the shape of the risk curve. From that baseline, the model adds and subtracts years based on 15 lifestyle, medical, and family-history factors: smoking, alcohol, exercise, diet, sleep, stress, occupation, healthcare access, a few supplement flags, diagnosed conditions, and parental longevity.
The output is a projected age at death, the remaining years, the disability-free subset of those years (important — lifespan ≠ healthspan), a vs-country-average delta, a letter grade, and most importantly a Top 3 Actions list ranked by reversible years gained. The point isn't to predict your exact date; it's to surface which single change in your current lifestyle would move the number most, and the model is honest about telling you when you've already outperformed its prediction — if you're 74 and the model says 72, that's a sign of resilience, not an error. Defaults load on first open; change the inputs to match your real life for a result that matters to you.
The first number the calculator uses is the male or female life expectancy at birth for the country you select, pulled from WHO 2022 and CDC National Vital Statistics. This matters more than most people realize. Japan and Switzerland sit at 81–82 for men. The US sits around 76. Russia sits below 68. The Philippines sits at 68. That's more than a decade of spread before a single lifestyle factor is entered, and it's not a rounding error — it's a combination of healthcare system quality, food environment, alcohol culture, and road safety that the model can't capture through the other inputs. Each country in the dropdown carries a short healthcare access note (universal coverage vs out-of-pocket-heavy, wait times, preventive care emphasis) so you can see why the number is what it is. If you've lived in multiple countries, pick the one where you've spent most of your adult life — the one whose healthcare system has shaped your risk profile. The "US" baseline is also notably sex-specific: US men live ~76, US women ~81, which is why the sex toggle matters.
The calculator's model weighting isn't a democracy. Smoking is the single biggest variable — a lifelong heavy smoker loses more years than almost any other combination of factors can add back, and quitting shows up as the #1 action in the Top 3 for anyone who smokes. The next tier is exercise, diet, and sleep, which are roughly comparable and interact with each other (good sleep makes exercise more effective, exercise improves diet adherence). Alcohol is a U-shape — zero intake is slightly worse than light-to-moderate at the population level, but heavy and daily drinking is clearly worse than both, so don't read the moderate advantage as "more is better." Stress, occupation, and healthcare access are smaller individual levers but matter for men with chronic conditions. Supplements (omega-3, vitamin D, magnesium) are included as small positive flags where the evidence supports them, and they're weighted accordingly — small additions, not multipliers. Expect most of your total adjustment to come from 3–4 factors, not evenly from all 15. The Top 3 Actions ranks these by reversible years — which means a factor you can't change (family history, country) won't appear there even if it's dragging your number down.
Section 1 has a unit toggle (Imperial ⇄ Metric) that rewires the height and weight steppers between ft/in + lbs and cm + kg. The underlying calculation uses metric internally and converts your input regardless of which toggle you pick, so the result is identical — use whichever you actually know your body in. Don't fudge — the BMI derived from height and weight feeds into the weight adjustment, and BMI is one of the factors where men systematically underestimate themselves. If you weighed yourself honestly this month, use that number; if the last honest weigh-in was 6 months ago and you've been "around the same," use that with a 3–5 lb buffer upward. The calculator doesn't shame you for a high BMI, and weight-related adjustments are modest compared to smoking or exercise — but the number does have to be real for the Top 3 to point at the right lever.
Section 6 asks about diagnosed conditions: diabetes, heart disease, cancer history, and mental health. Diabetes and heart conditions have tiered options — "no" / "controlled" / "uncontrolled" — and the distinction matters a lot. "Controlled" means you have the diagnosis and you're actively managing it with medication, lifestyle, or both, and your last labs or follow-ups were in the target range. "Uncontrolled" means either you're not in treatment, you're in treatment but the numbers aren't landing, or you haven't seen a doctor about it in over a year. The model treats "controlled diabetes" as a modest risk factor and "uncontrolled diabetes" as a major one, because that's how the clinical risk literature actually shapes outcomes. Don't pick "controlled" because it feels nicer — pick it only if you'd pass a specialist's review of your current management. A "no" for any of these means you've never been diagnosed, not that you've never had symptoms. If your doctor has mentioned any of these as a possibility but you haven't been formally diagnosed, the honest answer is still "no" for the calculator's purposes, and the Top 3 will likely still include a "get screened" action.
Section 7 asks about parental longevity, and it's the one factor you can't change. The model weights it modestly: parents who lived unusually long adds a small bonus; parents who died young from non-accidental causes subtracts a small amount. It's not given the leading role some popular-science articles suggest, because the data doesn't actually support that. Danish twin studies and contemporary heritability research put the genetic contribution to human lifespan at about 15–25% — meaningful, but not destiny, and smaller than smoking or exercise alone. What this means practically: a man with two parents who died at 70 and a current lifestyle grade of A will still have a higher projection than a man with two parents who lived to 95 and a current lifestyle grade of F. Family history tilts the starting point slightly. Lifestyle moves the number.
If you're older than the age the model predicts you'll reach, the tool returns a specific message: "You're outperforming the model." This isn't a calculator bug — it's a feature. A 74-year-old man with a heavy-smoker lifestyle and a predicted age of 72 has, by definition, beaten the base-rate risk profile and is operating above the model's expectation. The honest interpretation is that you have resilience factors the model can't see (genetics, luck, environment, something about your specific health profile that the 15 factors don't capture), and that the same risk factors still compound from here, so lifestyle changes now still add meaningful years. The calculator will still give you a Top 3 in this case, because the levers it suggests are still real — just applied from a position of already having outperformed.
Below your projected age, the calculator shows remaining years and disability-free remaining years separately. The gap between those two numbers is what aging researchers call the morbidity compression window — the years you'll likely spend dealing with a chronic condition, mobility limit, or cognitive decline before the end. For most American men, this gap is roughly 8–12 years, which means a projected age of 82 typically includes 8–10 years of impaired living. The point of the calculator isn't just to maximize total years — it's to push the disability-free number as close to your total as possible. The interventions that compress morbidity best (exercise, sleep, BP control, muscle mass) often show up in the Top 3 for exactly this reason. If you're going to take one metric home from this tool, take healthspan, not lifespan.
This is a population-level estimate applied to an individual, which is always imprecise. The model uses the best publicly-available sources (WHO 2022, CDC, peer-reviewed lifestyle-factor weights) but no model can predict any specific person's age at death — it predicts the average outcome for someone with your inputs. A 55-year-old male non-smoker with good habits has an average projection, but real individuals land anywhere from their 60s to their 100s around that average. Race and ethnicity aren't in this version of the model beyond what's already baked into country baselines, which is a real limitation for multi-ethnic populations. Cause-of-death data also varies in quality across countries. Treat the result as a directional signal — "am I pointed in a better or worse direction than I was last year" — not an appointment on a calendar. If the calculator returns a severe result and you haven't seen a primary care doctor in several years, the most valuable single action isn't in the Top 3 list — it's making that appointment.