How it works
How Counted Health works
Counted Health takes health information the country already collects, brings it together for each person, and maps where the burden of invisible illness really falls. Here is how it does that — and, in one place at the end, exactly what the evidence shows and where we are careful about it.
What we look at
Everything comes from a large, trusted U.S. government health survey (NHANES). For each person it gathers far more than one doctor usually sees at once. We use three kinds of information about the same person:
- Their body — blood and other lab results.
- What their body does — about a week of activity from a wearable.
- How they feel — simple, standard questions about fatigue, mood, and health.
Normally these sit in separate places, so no one sees them together. We bring them into a single burden scorefor each person — the higher the score, the more these signals are off at once.
How we build the map
We line everyone up by their burden score, lowest to highest, and split the line into five equal groups. Group 1 is the lowest burden; group 5 is the highest. These are just groups along a scale — not diagnoses, and not something a computer decided on its own.We fixed the way we sort people up front, so it can’t be tuned to produce a flattering answer.
The evidence — and where we’re careful
Two findings stand out. First, chronic illness climbs steadily across the groups: in the lowest-burden group, about 1 in 3 people live with a diagnosed chronic condition; in the highest, it is closer to 3 in 4— more than double. That gap holds even when we compare people of the same age, sex, and body weight, so it is not simply that older people are sicker.
Second — and this is the strongest test — we matched these same people to official records of who later died, records the burden score never used. Over the next 6 years, people in the highest-burden group died at about 5 times the rate of those in the lowest, even after accounting for age, sex, and weight. When a map can tell you that, it is measuring something real.
The burden map predicts survival
We linked the same respondents to CDC death records — a federal dataset the score never used. Over 6 years (285 deaths in 3,915 adults), all-cause mortality climbs across every burden region. This is the check that matters most: the outcome is a hard endpoint, so the gradient cannot be an artifact of self-report.
View as table
| Region | n | Deaths | Crude mortality | Mean age |
|---|---|---|---|---|
| Region 1 | 782 | 12 | 1.5% | 42 |
| Region 2 | 783 | 27 | 3.4% | 47 |
| Region 3 | 783 | 34 | 4.3% | 49 |
| Region 4 | 784 | 73 | 9.3% | 54 |
| Region 5 | 783 | 139 | 17.8% | 57 |
| Comparison | Hazard ratio | 95% CI | p |
|---|---|---|---|
| Region 5 vs 1 | 5.01 | 2.72–9.23 | < 0.001 |
| Region 4 vs 1 | 2.82 | 1.51–5.27 | = 0.001 |
| Per region (trend) | 1.55 | 1.39–1.73 | < 0.001 |
| Severity per SD | 1.59 | 1.44–1.76 | < 0.001 |
| Objective-only per SD | 1.53 | 1.40–1.67 | < 0.001 |
Where we’re careful
- It maps burden; it does not diagnose. The groups are people sorted from lower to higher burden, never disease labels.
- It shows a strong link, not proof of cause. High burden goes with more illness and earlier death; it does not prove one causes the other.
- This data is from before the pandemic.So the pattern is everyday fatigue and difficulty — not Long COVID specifically.
- It is one national survey, and honest about its limits. Conditions are self-reported, and the numbers are weighted to stand in for the whole country. It is a starting map, not the last word.
The precise figures, for the record
That is the whole of the science on this site, in plain terms. The full statistical write-up — every dataset, variable, model, adjustment, confidence interval, and sensitivity check, plus how to reproduce it — is laid out on our methods & reproducibility page. Counted Health itself is built to be used, not read like a study. Where the data comes from →