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Clinician-led, not marketer-led
A person, not an app, confirms what is going on and decides what comes next. The score's only job is to get the right people in front of that clinician in time.
The score is built by
clinicians, not marketers.
Decades of research link everyday exposures to chronic disease. The Exposure Health Score turns that science into one number — and routes people to care before the damage becomes permanent.
Our mission
Reach the workers conventional screening was never built to see — and route them to care while the window is open.
Our approach
Three commitments hold the science accountable.
The Exposure Health Score does not diagnose. It flags and routes — and every consequential decision is confirmed by a clinician.
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Evidence-first, revalidated yearly
Built from validated instruments — ATS respiratory, Nordic skin, Q16 neurotoxicity, Agricultural Health Study — and re-checked every year by an independent board of doctors and scientists.
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Built for the exposed
Designed to reach people who never pass through an occupational clinic — farmers, miners, factory and field workers, on WhatsApp, in three minutes, with no clinic.
01The problem the score was built to solve
Exposure isn't the problem. Unmeasured exposure is.
Exposure is part of living and working. Pesticides protect crops. Sunlight keeps us healthy. Metals and solvents build daily life. The problem is not exposure itself — it is what happens when it builds up, unmeasured, over years.
By the time it reaches a clinic, it is often too late to reverse. Conventional health screening was built around a specific profile: older, heavier, sedentary, a smoker. It works for that profile. It misses the exposed worker who does not fit it.
A lean, active, never-smoking farmer reads as low-risk on the conventional model — precisely because that model was built on someone he is not.”
02The evidence for the under-ranking
Three studies. Three populations. The same pattern.
Indonesia Rice farmers · West Java
46% hypertensive
In 354 rice farmers, heat stress carried the signal (adjusted prevalence ratio 1.41, 95% CI 1.01–1.95). No personal or lifestyle characteristic — not obesity, smoking, alcohol, or diet — was significantly associated. The conventional model looked in the wrong place.
Sumartono et al. · Int J Environ Res Public Health, 2022
Read the study
DR Congo Charcoal workers
Young, lean still ill
Among 485 workers, charcoal workers had higher pulse pressure and more isolated systolic hypertension than farmers — despite being young, lean, and physically active. Exposure was not only predicting disease; it was associated with a particular form of it.
Lofuta Olenga Vuvu et al. · J Am Heart Assoc, 2024
Read the study
Uganda Biomass-exposed communities
~30% symptomatic
Respiratory symptoms appeared in ~30% of people while diagnosed COPD was ~2%. The conventional respiratory screen — tuned to the smoker — routed the never-smoking, biomass-exposed patient past the test that would find their disease.
North et al. · 2019
Read the study
All three are cross-sectional studies. They show association and point to where evaluation is warranted — not that exposure is the sole cause. The lesson for screening is the same in every case: a clean conventional profile is not reassuring in a heavily exposed person.
03The scale of the problem
1.9M
Deaths per year attributed to occupational risk factors alone.
WHO/ILO Joint Estimates, 2016
9M
Premature deaths linked to pollution annually.
Lancet Commission on Pollution & Health, 2018
95%
Of chronic diseases driven by environmental exposures — not genetics.
The heaviest burden falls on people who live and work near mines, farms, and factories — in heavy traffic and cooking smoke, handling chemicals day to day. These are the people most standard health programs were never built to reach.
04How the score is built
Two inputs. One number. One action.
Think of the Exposure Health Score as a smoke detector for the body.
Most exposures are useful — but they can build up unnoticed and worsen disease. The score senses that build-up, weighs it against your usual health risks, and sounds the alarm before disease sets in.
Measures cumulative exposure on its own — the part the usual check-up almost never captures.
No age, weight, or lifestyle factors enter it. One clean number for one thing, built from five categories:
ChemicalsMetalsDust & SmokeHeatLabor & Noise
Measures the usual health factors any clinician would weigh.
Broad and shallow — enough to route, not a full clinical workup:
AgeSexSmokingWeightBlood pressure historyFamily historyCurrent symptoms
What the two inputs produce together. A single number from 0 to 100. Higher is healthier — and neither input can cancel the other out.
0–100
The critical rule: neither input can cancel the other.
Low exposure
High exposure
High conventional risk
ConcerningSmoker is flagged either way
Most concerningBoth signals elevated
Low conventional risk
Least concerningBoth signals low
Still concerningExposed farmer isn't reassured
If a clean conventional profile could pull a high exposure burden toward the middle, the score would rebuild the exact under-ranking the Indonesia and Congo studies document. It does not.
05What the score measures
Five exposure categories, chosen for the evidence.
The Exposure Burden Score is built from the five categories that carry the strongest documented links to disease.
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Chemicals
Nerve, liver, and skin disease — pesticides, solvents, industrial and household chemicals.
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Metals
Heart, kidney, and nerve disease — lead, cadmium, welding fumes.
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Dust & Smoke
Chronic lung disease — silica, biomass smoke, organic dust, traffic fumes.
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Heat
Kidney and skin disease — repeated heat strain, long hours in strong sun.
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Labor & Noise
Hearing loss and joint and muscle disease — hard physical work, loud tools.
06Frequently asked
Questions about the score.
What do the colours on the score mean?
The colour is the part that matters most — a signal to act, not a verdict. A person, not an app, confirms what is going on and decides what comes next.
Green · High — low concern
Yellow · Middle — worth watching
Red · Low — we connect you to a clinician
What does a person see versus a clinician?
The person sees one number and a colour — no disease label, no sub-scores. As easy to read as a sleep score. “Your Exposure Health Score is 38. Red. We recommend evaluation.”
The clinician sees the anatomy: the Exposure Burden Score and Conventional Risk Score side by side, plus the drivers and the body systems they most affect. Every differential is phrased “to consider” — never “indicates.”
Does the score still matter after a diagnosis?
Yes — because the exposure doesn't end at diagnosis. A farmer found to have hypertension is still farming; a quarry worker with lung disease is still in the dust.
For a high-burden patient, the exposure context joins the care plan: exposure reduction where possible, earlier surveillance, closer follow-up. Not a claim that exposure caused the disease — a recognition that it is still part of the picture.
How do you keep it accurate and honest?
The score does not diagnose. It flags and routes — and a clinician confirms every consequential decision.
It is built from validated instruments — the ATS respiratory questionnaire, the Nordic Occupational Skin Questionnaire, the Q16 neurotoxicity questionnaire, and the Agricultural Health Study cohort instruments — on proven models (the Comprehensive Geriatric Assessment and PROMIS). An independent board of doctors and scientists re-validates the algorithm, thresholds, and categories every year.
Is the Exposure Health Score a diagnosis?
No. It is a patient-completed early-warning measure — designed to reach people who never pass through an occupational clinic and route them to confirmation before the window closes.
It is not a diagnosis. It is not a lab test. It does not replace a clinician. The evidence underneath it is associational, not causal. Its role is to make sure the right people reach that clinician in time.
What published evidence is it built on?
Every Exposure Score rests on decades of peer-reviewed research across occupational and pollution burden, exposure under-ranking, and specific exposure–disease links:
WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury, 2000–2016 — ~1.9M deaths.
Landrigan PJ et al. The Lancet Commission on pollution and health. Lancet. 2018.
Sumartono W et al. Hypertension amongst Rice Farmers, West Java. Int J Environ Res Public Health. 2022.
Lofuta Olenga Vuvu P et al. Pulse pressure in young biomass-exposed workers, DRC. J Am Heart Assoc. 2024.
North CM et al. Chronic obstructive pulmonary disease in southwestern Uganda. 2019.
Johnson RJ, Wesseling C, Newman LS. Chronic kidney disease of unknown cause. NEJM. 2019.
Howlett et al. Silica exposure among artisanal and small-scale miners. PLOS Global Public Health. 2023.
Thompson JN et al. Exposure-history questionnaire and primary-care documentation. J Occup Environ Med. 2000.