Why weeks, not scores
Most health platforms hand you a score — a number between 0 and 100 that means whatever the app decides it means. NewLegacy uses weeks instead, because a week is a unit everyone already understands, and because a projection stated in time can be checked against real published research rather than an internal scoring formula.
Your calendar starts with a baseline projection drawn from the SSA 2023 period life table — Your calendar starts with a baseline projection drawn from the SSA 2023 period life table — the U.S. Social Security Administration's actuarial data for remaining life expectancy by age and sex. From there, it adjusts up or down as your own inputs come in, using coefficients traced to published longevity and healthcare-cost studies.
What feeds the baseline
Your baseline projection starts with the U.S. Social Security Administration's 2023 period life table — the same actuarial data used in insurance, pension, and public-health planning. It gives actuarially estimated remaining years by age and sex, and sets your starting calendar before any behavioral factor is applied.
Exercise, sleep, alcohol, diet quality, smoking, social connection, sense of purpose, chronic stress, ikigai, and dog ownership each adjust the SSA baseline up or down. Every coefficient traces to a named, published study. Nothing is invented or internally fitted.
Exercise, sleep, alcohol, diet, and smoking use years-of-life figures reported directly by the underlying studies. Social connection, sense of purpose, chronic stress, ikigai, and dog ownership use mortality hazard ratios — converted to an approximate years figure using a published epidemiological heuristic — and are clearly labeled ≈ in the calculator.
Dollar figures in this platform reflect tangible market projections — direct consumption spending, medical costs, or healthcare-system costs — nothing more. Financial-economic factors are treated as an enabler of the two health domains (biological-ecological and psycho-sociocultural), not as a third health domain. The value of time with the people you love is priceless and is not modeled here.
If you connect lab values, Phenotypic Age (Levine et al., Aging 2018) provides a biomarker-based biological age estimate from nine routine blood markers. It is kept separate from behavioral years to avoid double-counting overlapping effects. It is a population-referenced research measure, not a diagnosis.
Self-reported habits drive the calculator today. Optionally, connecting lab values, wearable data, or activity data from services you choose sharpens the projection over time. Nothing beyond what you actively provide is ever pulled in.
The Ecological Footprint section shows three separate outputs — GHG (kg CO₂eq/year), agricultural land use (m²/year), and freshwater withdrawals (liters/year) — computed from Poore & Nemecek (Science, 2018), a meta-analysis of 38,700 farms in 119 countries. These are parallel measurements to health years and are never combined with them. Ecological and health impact do not always move in the same direction; the purpose of showing both is to let you see each axis independently.
What this is not
This is not a diagnosis, a prognosis, or medical advice. The week figures are population-level estimates, applied to your inputs for illustration and motivation — not a prediction of what will happen to you specifically. If you have a health concern, talk to a clinician, not your calendar.
The calendar also does not assign a week-count to anyone in your household or social circle. The research on household spillover effects is real — the Your Circle section on the Ledger covers what the studies actually say, which tier of evidence each finding sits in, and where the methodological dispute lies — but individual-level attribution from population-level data would misrepresent what any of it can say about a specific person. Your Circle section on the Ledger covers what the studies actually say, which tier of evidence each finding sits in, and where the methodological dispute lies.
On "Your Circle"
The Ledger's Your Circle section covers two tiers of research on household and social health. One tier is settled: secondhand smoke has a direct causal mechanism — 41,000+ U.S. nonsmoker deaths annually, 25-30% higher coronary heart disease risk, no established safe exposure level. This is not a statistical association open to reinterpretation.
A second tier is genuinely contested. The Christakis & Fowler social-network clustering studies — showing that obesity, smoking cessation, and alcohol use cluster within social networks in the Framingham Heart Study data — were real, peer-reviewed, widely cited findings. They were also challenged on methodological grounds by Cohen-Cole & Fletcher (BMJ 2008) and by mathematician Russell Lyons, who showed that the same statistical approach produces similar-looking "contagion" patterns for traits that plainly cannot spread person-to-person, like height or acne. VanderWeele (2011) found the smoking and obesity clustering relatively more robust to that critique than some other traits studied the same way — but "more robust than the weakest examples" is not the same as settled.
We present both tiers on the Ledger, labeled by confidence, with the dispute stated in the card itself — not buried in a footnote. We do not pick a side, manufacture a per-person day-count for anyone else, or present the contested findings with the same confidence as the established ones.
Privacy, in plain terms
Opt-in, always
Every data source beyond your basic profile is something you actively connect. Nothing is pulled by default.
Yours to delete
You can disconnect a data source or delete your calendar entirely, at any time, from your account settings.
Not sold
Your health and activity data is used to run your calendar. It is not sold to third parties.
Aggregated research only
If your data ever contributes to research or population-level insights, it's de-identified and aggregated first.
Full references
U.S. Social Security Administration, "Period Life Table, 2023, as used in the 2026 Trustees Report."
Moore SC et al., "Leisure Time Physical Activity of Moderate to Vigorous Intensity and Mortality: A Large Pooled Cohort Analysis." PLOS Medicine 2012. (n=654,827; exercise years figures.)
Matjasko JL et al., "Inadequate Aerobic Physical Activity and Healthcare Expenditures in the United States: An Updated Cost Estimate." American Journal of Health Promotion 2025. (n=76,000+; exercise cost figure.)
Liu TZ et al., "Nighttime sleep duration, 24-hour sleep duration and risk of all-cause mortality among adults: a meta-analysis of prospective cohort studies." Scientific Reports 2016. (35 studies, 1.5M+ participants.)
Franco OH et al., "Does Physical Activity Increase Life Expectancy? A Review of the Literature." Journal of Aging Research 2012. (Hazard-ratio to years-of-life conversion heuristic.)
Wood AM et al., "Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599,912 current drinkers in 83 prospective studies." The Lancet 2018.
Lv Y et al., "Healthy dietary patterns, longevity genes, and life expectancy." Science Advances 2026. (UK Biobank, n=103,649; diet years figures.)
Jardim TV et al., "Cardiometabolic disease costs associated with suboptimal diet in the United States." PLOS Medicine 2019. (Diet annual cost figure.)
U.S. Department of Health and Human Services, "Smoking Cessation: A Report of the Surgeon General," 2020.
Holt-Lunstad J et al., "Social Relationships and Mortality Risk: A Meta-analytic Review." PLOS Medicine 2010. (148 studies, n=308,849; social connection years figure — approximate.)
Joo J & Liu Y, "Association between social isolation and healthcare costs." JMIR 2023. (Social isolation annual cost figure. Primary source under verification.)
Boyle PA et al., "Purpose in Life Is Associated With Mortality Among Community-Dwelling Older Persons." Psychosomatic Medicine 2009.
Alimujiang A et al., "Association Between Life Purpose and Mortality Among US Adults Older Than 50 Years." JAMA Network Open 2019.
Hill PL & Turiano NA, "Purpose in Life as a Predictor of Mortality Across Adulthood." Psychological Science 2014.
Kivimäki M et al., "Work stress and risk of death in men and women with and without cardiometabolic disease: a multicohort study of 102,633 individuals." Lancet Diabetes & Endocrinology 2018.
Steptoe A & Kivimäki M, "Stress and cardiovascular disease." Nature Reviews Cardiology 2012.
Levine ME et al., "An epigenetic biomarker of aging for lifespan and healthspan." Aging (Albany NY) 2018;10(4):573–591.
CDC, "Health Problems Caused by Secondhand Smoke," 2024-2025, citing the 2014 U.S. Surgeon General's Report.
Christakis NA & Fowler JH, "The spread of obesity in a large social network over 32 years." NEJM 2007;357(4):370–379.
Christakis NA & Fowler JH, "The collective dynamics of smoking in a large social network." NEJM 2008;358(21):2249–2258.
Fowler JH & Christakis NA, "Dynamic spread of happiness in a large social network." BMJ 2008;337:a2338.
Rosenquist JN et al., "The spread of alcohol consumption behavior in a large social network." Annals of Internal Medicine 2010;152(7):426–433.
Cohen-Cole E & Fletcher JM, "Detecting implausible social network effects in acne, height, and headaches." BMJ 2008.
Lyons R, "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis." Statistics, Politics and Policy 2011.
VanderWeele TJ, "Sensitivity analysis for contagion effects in social networks." Sociological Methods & Research 2011.
Sone T et al., "Sense of Life Worth Living (Ikigai) and Mortality in Japan: Ohsaki Study." Psychosomatic Medicine 2008;70(6):709–715.
Mandic I et al., "Dog ownership and the risk of cardiovascular disease and death." Scientific Reports 2017.
Kramer CK et al., meta-analysis of 10 studies. "Dog ownership and survival." Circulation: Cardiovascular Quality and Outcomes 2019.
Hofmann SG et al., "The Efficacy of Cognitive Behavioral Therapy: A Review of Meta-analyses." Cognitive Therapy and Research 2012.
Jenkinson CE et al., "Is volunteering a public health intervention? A systematic review and meta-analysis." BMC Public Health 2013.
Okun MA et al., "Volunteering by Older Adults and Risk of Mortality: A Meta-Analysis." Psychology and Aging 2013;28(2):564–577.
Cheung C et al. (review, 2023). Evidence for nonviolent communication (NVC) in empathy and relationship outcomes. No mortality figure exists.
Vohra K et al., "Global mortality from outdoor fine particle pollution generated by fossil fuel combustion." Environmental Research 2021.
World Health Organization, "Burden of disease attributable to unsafe drinking-water, sanitation and hygiene: 2019 update," 2023.
Barabási AL, Gulbahce N, Loscalzo J, "Network medicine: a network-based approach to human disease." Nature Reviews Genetics 2011;12(1):56–68.
Union of Concerned Scientists, "The $11 Trillion Reward: How Fruits and Vegetables Could Save U.S. Lives and Dollars," 2013.
UN Food and Agriculture Organization, "The State of Food and Agriculture 2023" (154-country analysis).
Li K et al., "Lifestyle risk factors and residual life expectancy at age 40: a German cohort study." BMC Medicine 2014. (EPIC-Heidelberg, n=22,469; sex-specific smoking and processed meat bands.)
Rohrmann S et al., "Meat consumption and mortality — results from the European Prospective Investigation into Cancer and Nutrition." BMC Medicine 2013. (EPIC, n=448,568; HR 1.18 per 50 g/day processed meat after measurement-error correction.)
Pan A et al., "Red Meat Consumption and Mortality: Results From 2 Prospective Cohort Studies." JAMA Internal Medicine 2012. (Nurses' Health Study + HPFS; HR 1.13 per daily serving unprocessed red meat.)
Dehghan M et al. (PURE study), "Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE)." Lancet 2017. (n=134,297, 21 countries; HR 0.93 for unprocessed red meat, not significant.)
Johnston BC et al. (NutriRECS), "Unprocessed Red Meat and Processed Meat Consumption: Dietary Guideline Recommendations From the NutriRECS Consortium." Annals of Internal Medicine 2019. (Overall evidence quality for red meat and mortality rated LOW.)
Poore J & Nemecek T, "Reducing food's environmental impacts through producers and consumers." Science 2018;360(6392):987-992. (38,700 farms, 119 countries; GHG, land, and freshwater per kg food product. Data via Our World in Data.)
Fadnes LT et al., "Estimating impact of food choices on life expectancy: A modeling study." PLOS Medicine 2022. (Optimal diet modeling; vegan and Mediterranean CI overlap substantially.)
Barnard ND et al., "A Mediterranean diet and low-fat vegan diet to improve body weight and cardiometabolic risk factors: A randomized, cross-over trial." Journal of the American College of Nutrition 2022. (Metabolic endpoints; not a mortality study.)
Martínez-González MA et al., "A provegetarian food pattern and reduction in total mortality in the Prevención con Dieta Mediterránea (PREDIMED) study." Am J Clin Nutr 2014. (More plant-forward within Mediterranean, not vegan vs. Mediterranean head-to-head.)
Chen R et al., "Association between e-cigarette use and all-cause and cause-specific mortality in the United States." Preventive Medicine 2024. (n=145,390 NHIS-NDI; dual-use confers no mortality benefit over cigarettes only; no vaping-only years figure.)
Levy DT et al., "Potential deaths averted in USA by replacing cigarettes with e-cigarettes." Tobacco Control 2018. (Assumes vaping's excess risk = 5% of smoking — optimistic bound.)
Lee PN & Thornton AJ, "Epidemiological evidence relating snus to health — an updated review based on recent publications." Archives of Toxicology 2021. (5–40% of smoking risk range for vaping — basis for pessimistic bound.)
LoParco CR et al., "Estimating the mean price of alcoholic beverages by alcohol content." Alcoholism: Clinical and Experimental Research 2022. (On-premise drink prices across 403 bars; basis for 80/20 off/on-premise cost blend.)
Aristotle, Categories and Metaphysics (c. 350 BC). Philosophical origin of the quality/quantity distinction; the two categories are used as the structural frame for why this platform measures both healthspan and lifespan.
René Descartes, Principles of Philosophy (1644). Establishes extension — measurable dimension — as the defining attribute of physical substance; the historical basis for modern science's emphasis on quantifiable outcomes over qualitative ones.
Fries JF, "Aging, natural death, and the compression of morbidity." New England Journal of Medicine 1980;303(3):130–135. Foundational statement of compression of morbidity: the goal is to push the period of disability and decline as close to the end of life as possible, so that healthspan and lifespan converge.
Max-Neef MA, Elizalde A, Hopenhayn M. Human Scale Development: Conception, Application and Further Reflections. New York: The Apex Press; 1991. Separates fundamental human needs (finite, universal, constant across cultures) from satisfiers (the culturally variable ways needs get met). Economic goods are explicitly a subset of satisfiers, not needs themselves -- the same argument as this platform's financial-economic framing: money expands access to what health domains require but is not itself a health domain. Used to ground the Rings of Influence in a non-hierarchical needs framework.
See Your Own Numbers.
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