Environmental Drivers
of Complex Chronic IllnessScott Daniska
Manhattan's skyline and the East River almost entirely obscured by heavy smog, 1973.
A century of findings
  1. 2026 PM2.5, NO2 Lewy body dementia Aarhus cohort, JAMA Netw Open 2026
  2. 2025 Ambient trichloroethylene Parkinson’s disease risk Krzyzanowski et al., Neurology 2025
  3. 2025 Microplastics, brain tissue ~50% higher than 2016 samples Nihart et al., Nat Med 2025
  4. 2024 Microplastics, arterial plaque 4.5× cardiovascular events Marfella et al., NEJM 2024
  5. 2023 Suspected endocrine disruptors Sperm counts down >50% since 1970s Levine et al., Hum Reprod Update 2023
  6. 2022 Microplastics First detected in human blood Leslie et al., Environ Int 2022
  7. 2022 Sarin, PON1 variant Gulf War illness Haley et al., EHP 2022
  8. 2022 Microplastics, fecal Correlates with IBD severity Yan et al., Environ Sci Technol 2022
  9. 2020 Air pollution Identified as a modifiable dementia risk factor Livingston et al., Lancet Commission 2020
  10. 2020 Aluminum Co-located with amyloid-β plaques Mold et al., J Alzheimers Dis 2020
  11. 2019 Engineered stone dust Accelerated silicosis Leso et al., IJERPH 2019
  12. 2018 Organic solvents Associated with multiple sclerosis Hedström et al., Neurology 2018
  13. 2018 Low-level lead Cardiovascular mortality Lanphear et al., Lancet Public Health 2018
  14. 2017 Traffic-related air pollution Associated with dementia Chen et al., Lancet 2017
  15. 2015 DDT, in utero Breast cancer in daughters Cohn et al., JCEM 2015
  16. 2013 Heat stress, agrochemicals Chronic kidney disease of unknown origin Wesseling et al., Am J Public Health 2013
  17. 2013 Outdoor air pollution Group 1 carcinogen classification Loomis et al., Lancet Oncol 2013
  18. 2012 Trichloroethylene Parkinson’s, 6× in exposed twin Goldman et al., Ann Neurol 2012
  19. 2012 PFAS Reduced vaccine antibody response Grandjean et al., JAMA 2012
  20. 2012 PFOA Kidney/testicular cancer, colitis, thyroid disease C8 Science Panel
  21. 2011 Paraquat Associated with Parkinson’s disease Tanner et al., EHP 2011
  22. 2010 Cadmium, low-level Associated with chronic kidney disease Ferraro et al., BMC Public Health 2010
  23. 2010 PBDE flame retardants Neurodevelopmental deficits Herbstman et al., EHP 2010
  24. 2010 Traffic-related air pollution Childhood asthma incidence McConnell et al., EHP 2010
  25. 2008 Arsenic Associated with type 2 diabetes Navas-Acien et al., JAMA 2008
  26. 2007 World Trade Center dust Sarcoid-like granulomatous lung disease Izbicki et al., Chest 2007
  27. 2006 Industrial chemicals Developmental neurotoxicity Grandjean & Landrigan, Lancet 2006
  28. 2006 Persistent organic pollutants Associated with type 2 diabetes Lee et al., Diabetes Care 2006
  29. 2005 Residential radon Lung cancer Darby et al., BMJ 2005
  30. 2005 Phthalates, in utero Shortened anogenital distance Swan et al., EHP 2005
  31. 2004 Formaldehyde Nasopharyngeal carcinoma IARC classification
  32. 2002 PM2.5 Lung cancer, CV mortality Pope et al., JAMA 2002
  33. 2002 Diacetyl (flavoring) Bronchiolitis obliterans Kreiss et al., NEJM 2002
  34. 2001 Manganese, welding fumes Parkinsonism Racette et al., Neurology 2001
  35. 2000 Arsenic in groundwater Skin, bladder cancer Smith et al., Bull WHO 2000
  36. 1993 Fine particulates (PM2.5) Cardiopulmonary mortality Dockery et al., NEJM 1993
  37. 1993 Dioxin, chronic exposure Endometriosis, rhesus monkeys Rier et al., Fundam Appl Toxicol 1993
  38. 1986 Radioiodine, Chernobyl Childhood thyroid cancer Cardis et al., JNCI 2005
  39. 1983 MPTP Chronic parkinsonism Langston et al., Science 1983
  40. 1979 Lead Cognitive deficits, children Needleman et al., NEJM 1979
  41. 1977 Benzene Leukemia Infante et al., Lancet 1977
  42. 1976 Dioxin release, Seveso Chloracne, excess mortality Bertazzi et al., Am J Epidemiol 2001
  43. 1974 Vinyl chloride Hepatic angiosarcoma Creech & Johnson, J Occup Med 1974
  44. 1971 DES, in utero Vaginal adenocarcinoma Herbst et al., NEJM 1971
  45. 1971 Coal dust Coal workers’ pneumoconiosis Jacobsen et al., Nature 1971
  46. 1968 Cadmium Bone, kidney disease (itai-itai) Japan MHW; Nogawa et al., 2004
  47. 1968 Hardwood dust Nasal adenocarcinoma Acheson et al., BMJ 1968
  48. 1960 Crocidolite asbestos Mesothelioma Wagner et al., Br J Ind Med 1960
  49. 1957 Silica dust Associated with systemic sclerosis Erasmus, S Afr J Lab Clin Med 1957
  50. 1956 Methylmercury Neurological disease (Minamata) Japan MHW; Harada, 1995
  51. 1955 Asbestos Lung cancer Doll, Br J Ind Med 1955
  52. 1954 Aromatic amine dyes Bladder cancer Case et al., Br J Ind Med 1954
  53. 1950 Tobacco smoking Lung cancer Doll & Hill, BMJ 1950
  54. 1946 Beryllium Chronic beryllium disease Hardy & Tabershaw, J Ind Hyg Toxicol 1946
  55. 1929 Radium dial painting Bone sarcoma Martland & Humphries, Arch Pathol 1929
C1 — Environmental exposures have been found to induce many diseases over the past 100 years, and we're only discovering more as time goes on.

Context

An overview of the facts around the dramatic rise in chronic illness rates in the United States, and the need for environmental research as it directly drives this staggering rise.

East River and Manhattan skyline in heavy smog, May 1973 — EPA Documerica, Chester Higgins Jr. Public domain, National Archives.

Something is causing chronic illness rates to skyrocket.The data is in front of us.
The only remaining barrier is the desire to face it.

This page exists to answer a question independent of anything that happened to me personally: is there reason to think environmental exposure drives chronic illness at scale? I think it's completely impossible to avoid the truth of the matter anymore.

How much more common chronic illness has become

Chronic illness is no longer the exception in America; it is the norm. By 2023, about three in four American adults reported at least one chronic condition (Watson et al., 2025, shown in the chart below), and chronic conditions now account for most illness, disability and death in the country. Ninety percent of the nation's $5.3 trillion in annual health care spending goes to people with chronic or mental health conditions (CDC).

The medical bills are only part of the cost. Counting lost work and productivity, chronic disease cost the U.S. economy an estimated $3.7 trillion in 2016 alone, nearly a fifth of the entire economy (Waters & Graf, Milken Institute, 2018). ME/CFS by itself costs an estimated $36–51 billion a year, much of it in lost earnings, because so many patients can no longer work (Jason & Mirin, 2021), and the total cost of Long COVID has been estimated at $3.7 trillion (Cutler, 2022).

And the rate is rising, a lot and quickly. In the mid-1930s, roughly one in six Americans reported a chronic illness; today it is most adults. Human genetics doesn't change that fast. Something in the way we live has changed over the past hundred years to drive the rate this high, and that is the question the rest of this site is about.

Reported prevalence of chronic illness among Americans, 1935–2023

All ages Adults 18+ 100% 80% 60% 40% 20% 0% 1935–36 ~16–17% · all ages* 1962–63 44.5% · all ages 2000 ~44% · all ages 2013 72.3% · adults 18+ 2014 ~60% · adults 2023 76.4% · adults 18+ * Same 1935–36 National Health Survey already cited below (unfiltered reading — see “How these figures compare”), not a separate source. Sources: National Health Survey/Weisz 2011 · NCHS Series 10 No. 5, 1964 · Partnership for Solutions, 2002. Watson et al., Prev Chronic Dis 2025 (BRFSS) · RAND/Buttorff et al., 2017 (MEPS). Line is a linear trend (least-squares slope, anchored to end at the 2023 point) — it shows the overall direction, not each individual report. 1935–36 — National Health Survey (Weisz, 2011) 23 million Americans — about 16–17% — reported with any chronic disease, orthopedic impairment, or hearing/vision defect. Same source as the 7.5% figure below. 1962–63 — NCHS, Current Estimates from the Health Interview Survey Series 10 No. 5 (1964). Covers acute and chronic illness in the US civilian population, July 1962 to June 1963 — 44.5% reported some chronic condition. 2000 — Partnership for Solutions (Anderson & Horvath, 2002) Johns Hopkins / Robert Wood Johnson Foundation. 125 million Americans reported with a chronic condition — about 44% of the population — percentage back-calculated against 2000 Census population. 2013 — Watson et al., Prev Chronic Dis 2025 Behavioral Risk Factor Surveillance System (BRFSS) phone survey. 72.3% of adults 18+ reported at least one of 12 named chronic conditions. 2014 — RAND Corporation (Buttorff, Ruder & Bauman, 2017) Analysis of Medical Expenditure Panel Survey (MEPS) data. About 60% of adults reported at least one chronic health condition. 2023 — Watson et al., Prev Chronic Dis 2025 Same paper and method as 2013, same 12-condition BRFSS list, ten years later — 76.4% reported at least one condition, the most directly comparable pair of the six points.
C2 — Six reported estimates of chronic-illness prevalence among Americans, 1935–36 to 2023, from six different sources using six different survey methods and populations (Weisz, 2011; NCHS, 1964; Anderson & Horvath, 2002; Watson et al., 2025; Buttorff et al., 2017; Watson et al., 2025) — not a single consistent time series. See "How these figures compare" below for the 1935-vs-now comparison in more depth.

These six points aren't one continuous survey — they're six separate measurements, from six different sources, using six different methods, taken over 88 years. Three counted the whole population; the other three counted only adults. None of them define "chronic illness" quite the same way. Comparing any two of these numbers directly is comparing apples to a slightly-different apple, and I don't think you should read this chart (C2) as a single clean trend by itself.

The straight line is a genuine statistical trend fit through all six points, anchored to end exactly at the most recent (2023) figure — it's there to show the overall direction, not to claim each point sits exactly where the line does. It doesn't pass through the other five points, and it isn't supposed to.

The 1935–36 point is the same National Health Survey already cited below as the source of the 7.5% figure — shown here unfiltered (the raw "more than one in six" count), rather than run through the 45%-true-prolonged-illness filter that produces 7.5%. It's one source, not two.

The 2000 figure is back-calculated: Partnership for Solutions reported 125 million Americans with a chronic condition, not a percentage — the ~44% here is that count divided by the 2000 Census population, not something the original report stated directly.

The most solid pair on this chart is 2013 and 2023: same paper, same 12-condition BRFSS methodology, ten years apart, nothing else changed. If you want the one comparison here I'd actually stand behind as apples-to-apples, that's it — a rise from 72.3% to 76.4% of U.S. adults in a single decade, using one consistent measure.

The rest of the page explains why an aging population and improving medicine don't account for a rise this size. This chart is here to establish that the rise itself isn't just an artifact of one bad measurement — it shows up, in some form, in six independent attempts to count it, across nine decades of very different survey methods.

How these figures compare

The 1935 figure (7.5%) is derived, not directly reported: the original survey found 23 million Americans — more than one in six — with some chronic disease, orthopedic impairment, or serious defect of hearing or vision, of whom, on Weisz's reading of the underlying reports, only about 45% had true prolonged illness (three months or more of disability) rather than something milder or transient (National Health Survey, Bulletin 6, 1938/rev. 1939, p. 12; cited in Weisz, 2011). The two figures are not a like-for-like comparison: 1935 surveyed households in 19 states, not a national sample; it counted the whole population, where 2023 counts adults only; and it used a disability-duration threshold, where 2023 counts 12 named chronic conditions by phone survey (BRFSS). The direction of change is not in doubt — the size of the gap is partly an artifact of definition.

A roughly tenfold rise in reported chronic illness over ninety years, even accounting for definitional drift, is not what you'd expect if the underlying biology of the population were static and the only thing that changed was diagnosis. Something in the environment people live in has to be part of that story.

A common objection is that this is just demographics: fewer infants dying and people living longer means more people surviving into the ages where chronic illness is common, not that the population has actually gotten sicker. I don't think the numbers support that as a sufficient explanation. US infant mortality fell from roughly 100 per 1,000 births in the 1910s to about 6 per 1,000 today, and life expectancy at birth rose from about 47 years to about 79 over the twentieth century (CDC/NCHS, 2020). But even in the extreme case where every single one of those additional infant survivors went on to develop a chronic illness, that alone could only shift population-wide prevalence by a matter of single-digit percentage points — nowhere near the roughly 69-point rise the 1935-to-now comparison shows. And most of that 32-year gain in life expectancy reflects fewer deaths in infancy and childhood, not adults living dramatically longer once they'd already reached adulthood — someone who survived to 20 in 1900 already had a real chance of living into old age. An aging population plausibly explains some of the rise. It does not explain a tenfold one.

The same problem shows up from the other direction. Over the same century, medicine gained pharmaceuticals, surgical technique, diagnostic imaging and lab testing, sanitation and hygiene, and nutrition science that didn't exist in 1935. If anything, that should have pushed chronic illness rates down, or at least held them flat against a growing and aging population — not let them rise tenfold alongside it. Whatever is driving this rise is outpacing everything medicine has gained across the same period.

How neglected complex chronic illness is

For how common and how disabling these illnesses are, they receive remarkably little attention. About 1.3% of U.S. adults, roughly 3.3 million people, had ME/CFS in 2021–2022 (Vahratian et al., NCHS Data Brief No. 488, 2023) (C3), and the National Academy of Medicine estimated that as many as 84–91% of people with ME/CFS have never been diagnosed (Institute of Medicine, 2015). That puts it on a par with epilepsy (C3).

People with ME/CFS are more limited in their physical functioning than people with lung disease, osteoarthritis, heart disease, rheumatoid arthritis, cancer, diabetes or depression (C4).

Research funding hasn't come close to matching that burden. Measured against disability-adjusted life years, the standard measure of disease burden, ME/CFS receives less NIH funding relative to its burden than any other disease studied: roughly a fourteenth of what its burden would warrant (Mirin, Dimmock & Jason, 2020). Inflammatory bowel disease and asthma, with comparable burdens, each received more than ten times as much. Measured against what its burden would warrant, NIH's annual shortfall for ME/CFS was about $189 million before the pandemic, and may be as much as $458 million today (C5).

Chart from CrunchME: an estimated 3.1 million U.S. adults have ME/CFS, about the same as epilepsy (3.1 million) and more than type 1 diabetes, HIV, Parkinson's disease, multiple sclerosis, lupus or ALS.
C3 — Estimated U.S. Population Affected by ME/CFS and Selected Other Conditions. CrunchME, October 19, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.
Chart from CrunchME: people with ME/CFS score 26.8 on the SF-36 physical component score, lower (worse) than lung disease, osteoarthritis, heart disease, rheumatoid arthritis, cancer, diabetes or depression (38.3–45.7), against 50 for the general population.
C4 — SF-36 Physical Component Score for ME/CFS vs. Select Other Diseases. CrunchME, April 16, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.
Chart from CrunchME: NIH funding for ME/CFS averaged $14 million a year in 2020–24, against $203 million commensurate with its disease burden before COVID and $472 million including COVID: a shortfall of $189 million, up to potentially $458 million.
C5 — NIH Research Funding for ME/CFS in the U.S.: Actual vs. Commensurate. CrunchME, March 1, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.

ME/CFS costs more healthy years of life in the US each year than Parkinson's disease, HIV, multiple sclerosis and type 1 diabetes (CrunchME). Yet it has had only 54 registered US clinical trials, against 784–1,438 for each of those comparison diseases (CrunchME), and only 157 worldwide, against 1,781–3,785 for each (C6).

Recent estimates put its total cost to the US economy at $149–362 billion a year, up to about 1.4% of GDP (C7).

Long COVID, which often looks the same, now affects an estimated 14–17 million American adults, 5–6% of the adult population, according to the CDC's Household Pulse Survey (C8).

Chart from CrunchME: ME/CFS has had 157 registered interventional clinical trials, against 1,781 for epilepsy and 2,308–3,785 for rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease, type 1 diabetes and Parkinson's disease.
C6 — Registered Clinical Trials for ME/CFS and Comparator Diseases. CrunchME, August 31, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.
Chart from CrunchME: published estimates of the total economic cost of ME/CFS to the U.S. as a share of GDP have generally risen over time, from about 0.07% ($9 billion) in Reynolds et al. 2004 to 0.58–1.41% ($149–362 billion) in Mirin et al. 2022, the most recent estimate reaching or exceeding 1% of U.S. GDP.
C7 — Economic Cost Estimates for ME/CFS in the U.S. as a % of GDP. CrunchME, April 27, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.
Chart from CrunchME: in the CDC Household Pulse Survey, the share of U.S. adults currently experiencing Long COVID fell from about 7.5% in mid-2022 to around 5–6% through 2024, or 14 to 17 million adults.
C8 — CDC Household Pulse Survey Estimates 5% to 6% of U.S. Adults Are Experiencing Long COVID. CrunchME, February 13, 2026, crunchme.org/visuals. Licensed under CC BY 4.0. Unmodified.

Multiple chemical sensitivity is even more neglected. In a nationally representative survey, 25.9% of U.S. adults reported being sensitive to everyday chemical exposures, and 12.8% reported a medical diagnosis of MCS — increases of over 200% and 300% respectively in about a decade. Among those with MCS, 76% reported disabling health effects from fragranced products, and 61% had lost workdays or a job in the past year because of fragranced products in the workplace (Steinemann, 2018). Despite that, MCS has no category of its own in NIH's public research-funding reports, and there is no dedicated federal research program for it.

Weighing The Root Causes of Disease

When we look for what is driving this rise, there are only three places the root cause of a disease can come from: genetics (what we inherit), the environment (what we're exposed to), and infection, which is really part of the environment but is often treated separately. Every chronic illness comes down to some mix of the three. The rest of this page weighs how much each one plausibly contributes to complex chronic illness: genetics in this section, environment in the sections on our homes and on precedent in other diseases, and infection in the section on viral persistence.

Genetics can't explain the rise itself. Chronic illness has gone from about one in six Americans to most adults in under a century, far faster than the genetic makeup of a population can change. And for ME/CFS specifically, the genetic contribution has now been measured, and it is small. DecodeME, the largest genetic study of ME/CFS to date, found that common genetic variants explain only about 9.5% of the risk of developing it (DecodeME Collaboration, 2025). That is in the same range as asthma (about 10%), arthritis (about 12%) and type 2 diabetes (about 13%), none of which anyone considers primarily genetic, and nowhere near a strongly genetic risk like the APOE4 variant in Alzheimer's disease. Put another way, about nine out of ten of the reasons one person develops ME/CFS and another doesn't are not explained by the common DNA differences the study measured.

The eight genetic regions the study identified each shift risk only slightly, by roughly 7–8%. The variants in those regions are common: they turned up in about 15% to 65% of people with ME/CFS, but also in 14% to 63% of people without it, usually a difference of only one or two percentage points. Huge numbers of healthy people carry the same variants, and huge numbers of patients don't. The findings are useful for pointing to which body systems are involved in risk, but they are not strong predictors of who gets sick. As Jack Hadfield, an ME/CFS and Long COVID researcher and co-founder of Amatica Health, put it, the recent genetic findings “rather prove it is not primary genetic disease” (Hadfield, 2026; Hadfield, 2025).

If inherited risk explains so little of who gets sick, and nothing in our genes changed fast enough to explain the rise, then most of the explanation has to lie elsewhere. That makes it far more likely that the environmental component is large.

One pattern points toward the environment from a different angle. Both ME/CFS and Long COVID become sharply less common after about age 65. If these illnesses were driven by something that builds up with age, the opposite should be true. My suspicion is that this is a birth-cohort or period effect: something about the environment a person was born into or grew up with, rather than a biological effect of aging. I don't have a specific exposure to point to yet, and this is speculation I haven't tested.

What changed in our homes

Most people's exposure to the environment is really exposure to their indoor environment. Americans spend around 90% of their time indoors, and the air in that indoor space is not simply a diluted version of the air outside — the EPA's Total Exposure Assessment Methodology (TEAM) studies found roughly a dozen common organic pollutants at concentrations 2 to 5 times higher indoors than outdoors, in both rural and heavily industrial areas alike, and up to 1,000 times higher for a period during and after activities like paint stripping (C9).

Five of the riskiest air pollutants in US homes, compared with outdoor air

Outdoor air = 1×

Naphthalene home 0.9 · outdoor 0.1 µg/m³

9×

Formaldehyde home 18 · outdoor 2.5 µg/m³

7×

Chloroform home 1.2 · outdoor 0.2 µg/m³

6×

1,3-Butadiene home 0.3 · outdoor 0.1 µg/m³

3×

Benzene home 2.1 · outdoor 1.8 µg/m³

1.2×

Typical levels, not worst cases. Naphthalene values come from different studies than the other four.

Source: Loh et al., Environ Health Perspect, 2007 (compiled US exposure studies)

C9 — Three of these five come mainly from sources inside the home, and even benzene, which mostly drifts in from outside, runs higher indoors. These are typical homes on ordinary days, before any acute exposure event.

The chemical and material environment inside a home is not what it was a few decades ago either, and the scale of that change is measurable, not anecdotal. More than 350,000 distinct chemicals and mixtures are now registered for production and use worldwide — up to three times more than earlier estimates had found, once national inventories were compared against each other directly for the first time.

Labeling doesn't fully capture it, either. A 2026 nontargeted chemical analysis of 113 personal care and cleaning products — including many marketed as "natural," "non-toxic" or "organic" — found that 98% contained at least one chemical not disclosed on the label, 85% contained at least one chemical with a known or suspected health hazard, and products averaged 51 detected chemicals against 16 listed. You cannot avoid an exposure you don't know is there.

Cleaning products have been measured against a benchmark most people would recognize. In a European cohort of more than 6,000 adults followed for over 20 years, women who cleaned at home, or who cleaned for a living, lost lung function faster than women who did not clean — a decline the authors likened to smoking 20 cigarettes a day for 10 to 20 years. Asthma was more common in both cleaning groups (12.3% at home, 13.7% at work) than among women who did not clean (9.6%) (Svanes et al., Am J Respir Crit Care Med, 2018).

Plastics tell a similar story. As of 2015, 8,300 million metric tons of virgin plastic had been produced since mass manufacturing began, most of it within the preceding two decades. Of the 6,300 Mt that had already become waste, only 9% had ever been recycled; 12% was incinerated; the remaining 79% was sitting in landfills or loose in the environment. Production has not slowed since — global output doubled again between 2000 and 2019, to 460 Mt a year, and waste generation more than doubled over the same period, to 353 Mt, with the recycled share still stuck at around 9% (C10).

Plastics entering US municipal waste, per year Million tons 010203040 35.7 Mt 0.39 Mt 1960198020002018 Source: US EPA, Advancing Sustainable Materials Management: Facts and Figures, 1960–2018.
C10 — Plastics entering American municipal waste each year, from 0.39 million tons in 1960 to 35.7 million tons in 2018.

Clothing carries its own exposure. PFAS ("forever chemicals") have been detected in the majority of school uniforms tested across North America, cotton included, applied for stain and water resistance. Separately, a 2025 Consumer Reports investigation tested 23 popular protein powders and shakes and found more than two-thirds carried more lead in a single serving than their food-safety experts consider safe for an entire day — some by more than tenfold, with plant-based powders the worst offenders, since plants draw heavy metals up from soil as they grow.

This is not an abstraction happening somewhere else. A 2022 Dutch study analyzing blood from 22 anonymous, healthy volunteers found microplastic particles in 17 of them — about 77% — with polyethylene terephthalate (PET, used in bottles and food packaging), polystyrene and polyethylene among the types detected. Whatever is accumulating in the home environment is not staying in the home environment; it is already circulating in most people's bloodstream, healthy or not.

Microplastic concentration in human brain tissue 2016 2024 ~+50% in 8 years Source: Nihart et al., Nat Med, 2025. Illustrative — relative concentration, not absolute units.
C11 — Microplastic and nanoplastic concentration in decedent human brain tissue, 2016 samples versus 2024 samples from the same tissue bank.

It is in the brain, too, and the amount is rising. A 2025 study examined decedent brain tissue and found microplastic and nanoplastic concentrations in 2024 samples running well above 2016 samples from the same tissue bank — roughly 50% higher — with brains carrying markedly more plastic, gram for gram, than liver or kidney from the same donors (C11). Brains from decedents with a dementia diagnosis carried the heaviest loads of all, though the study is explicit that this is a correlation, not proof that the plastic caused the dementia.

CV event rate by plaque microplastic status 4.5× increased risk the rate of heart attack, stroke or death in carotid- plaque patients with plastic detected versus those without. Source: Marfella et al., N Engl J Med, 2024. Composite endpoint: MI, stroke or death, ~34-month follow-up.
C12 — Composite rate of heart attack, stroke or death in carotid-plaque patients with versus without detectable microplastics and nanoplastics.

And it may not be inert once it's there. In a 2024 study, 304 patients undergoing carotid endarterectomy had their removed arterial plaque tested for microplastics and nanoplastics — found in almost 60% of them, polyethylene most commonly. Over roughly three years of follow-up, patients whose plaque contained detectable plastic had 4.5 times the rate of heart attack, stroke or death from any cause compared with patients whose plaque didn't (C12). The authors are clear that this doesn't prove the plastic caused the events — but a 4.5-times difference is not a subtle signal.

None of this proves an environmental cause for ME/CFS specifically. What it establishes is narrower but load-bearing for the case as a whole: the volume, diversity and durability of what off-gasses, sheds and accumulates in the spaces people spend nearly all their time in has grown enormously within a single generation, in a direction that adds exposure rather than removing it. Titanium dioxide, the particle the model focuses on, is one strand of that story — it is the whitening pigment in most matte white paint, itself a comparatively recent, low-cost building material.

Precedent in other diseases

An environmental root cause is not a fringe idea in medicine generally. It is becoming the accepted explanation for several diseases that were, until recently, treated as having no clear cause — and none of the six below involve allergy, immune dysfunction or chemical sensitivity as a diagnostic feature, which is exactly the objection I hear most about applying this kind of explanation to ME/CFS.

Each of these was, for decades, filed under "cause unknown" or attributed to genetics alone. In each case the actual driver turned out to be an environmental exposure interacting with the person's own biology — which is the same structure of claim the model makes about ME/CFS. None of it is evidence for my specific mechanism. It's evidence that the general shape of the argument — an environmental exposure producing a disease that looks, on the surface, unrelated to environment — keeps turning out to be right elsewhere in medicine.

What about viral persistence?

An infection is, by a wide margin, the most common thing patients report before ME/CFS or Long COVID begins — millions of people trace their illness back to a specific virus, and I'm not disputing that or asking anyone to. Viral persistence is real: some viruses do stay active in the body longer than expected, and for some patients that is almost certainly part of what's happening. What I don't think holds up is persistence as the explanation for who stays sick.

The split between “environmental” and “viral” is not as clean as it sounds. In lung lymph nodes from 84 non-smoking organ donors aged 11 to 93, inhaled particulates built up with age — the nodes are beige in children and black by middle age — and the immune cells holding those particles were measurably worse at engulfing anything else and at signaling the rest of the immune system (Ural et al., Nat Med, 2022). A lifetime of ordinary air changes how well the body answers an infection.

Here is the problem it doesn't solve. Two people are infected in the same outbreak, sometimes the same household, with what is by any measure the same virus. One recovers in two weeks. The other is bedbound a year later. If persistence of the original pathogen were what determined the outcome, you would expect it to track with who got sick and how badly — and the data consistently doesn't show that.

SARS-CoV-2 protein detected in blood, over time 31% 20% 5.4% 6–12 months 3% 0% 0% 18–24 months Long COVID Fully recovered Uninfected controls Source: Mateu et al., Clin Microbiol Infect, 2026. n=425.
C13 — Detectable SARS-CoV-2 protein converges toward zero across all three groups by two years, regardless of who was still sick.

A blinded two-year study followed 425 people — 167 with Long COVID, 148 who had fully recovered, and 110 who were never infected — testing their blood for SARS-CoV-2 protein at 6–12 months and again at 18–24 months. Protein turned up in the Long COVID group somewhat more often early on, but also in a fifth of the people who had completely recovered, and by two years it had faded to nearly nothing in every group — while plenty of people in the Long COVID group were still sick (C13). Detectable protein was not associated with symptom severity, antibody levels, or vaccination status.

The same pattern shows up elsewhere. A German study led by Carmen Scheibenbogen — one of the most active ME/CFS and Long COVID researchers in Europe — tested serum from 121 post-COVID patients, 72 of whom met ME/CFS criteria, for spike protein up to two years out. It turned up in about 10% of them, but at the same rate in healthy people, with no connection to symptom severity — "unlikely to play a role in ME/CFS," in her own words. A separate Stanford study screened blood from ME/CFS patients and healthy controls for 185 different human viruses and found the opposite of what a persistence model would predict (C14).

Heatmap of virus detection across blood samples. The top bar shows each sample's group: blue for negative controls, pink for ME/CFS patients, green for healthy controls. Rows are individual viruses. Red cells mark detection. The healthy-control columns on the right show far more red cells than the ME/CFS columns in the middle.
C14 — Every red cell marks a virus detected in that sample. The healthy-control columns (right) are visibly redder than the ME/CFS columns (middle) — the opposite of what persistent infection driving the illness would predict.

More viral genetic material detected in healthy controls than in ME/CFS patients, across 17 viruses found in a 185-virus screening panel. No virus was found in all or even most ME/CFS samples.

A third line of evidence comes from treatment. If persistent spike protein were driving symptoms, clearing it should help. A 2026 study gave tixagevimab/cilgavimab, antibodies that bind the spike protein, to ten immunodeficient patients with Long COVID–associated ME/CFS and detectable circulating spike, nine of whom were followed up (Seidel et al., 2026). After 30 days, spike levels fell in five of the nine, but the change across the group was not significant (median 63 to 26 pg/ml, p = 0.63), and none of the assessed clinical outcomes changed significantly at group level. Changes in spike didn't track changes in any of the measured autoantibodies either. The authors are clear that this is preliminary: nine patients, no untreated control group, only 30 days of follow-up, and only immunodeficient patients. And because the antibodies didn't reliably clear the spike, the study can't fully test whether removing it would help. But it adds to the pattern: wherever spike protein is measured against how sick people are, the two don't move together.

Other treatment trials targeting persistence have not fared better. An antiviral trial of Paxlovid for Long COVID found no benefit over placebo (Geng et al., JAMA Intern Med, 2024), and three of the first five Long COVID trials in the NIH's RECOVER program to report results found no significant improvement over placebo. A UCSF trial of a monoclonal antibody aimed at clearing residual virus, presented at the 2025 PolyBio Long COVID Symposium, didn't move the needle on symptoms either — leading the study's own lead investigator to say the approach might be less promising than many had hoped. One Long COVID patient I spoke with, who had been on a monoclonal antibody herself and did see some benefit, put it this way: "I feel like it just delayed a path I was already headed down."

It's worth being precise about what I'm disputing. I separate the initiator (the virus or exposure that starts the disease state) from the driver (what sustains it). Weighted by duration against an acute infection's viral load, a low-level persistence running for years works out to roughly half the biological impact of the original infection: meaningful, but not obviously enough to explain a static disease state on its own. Viral persistence hasn't been ruled out, but the evidence for it as the driver is weak.

It also helps to remember how much microbial material a healthy body carries anyway. About 8% of the human genome is derived from ancient retroviruses. Mitochondria have their own genome because they were once bacteria coexisting with a eukaryotic cell. The colon alone holds roughly 38 trillion bacterial cells, about as many as the body's own cells (Sender et al., PLoS Biol, 2016). Around 30% of the population is infected with Toxoplasma gondii, which forms cysts in brain and muscle. Nearly everyone is infected with EBV and HHV-6, which infect brain, epithelial and immune cells. And healthy people show COVID antigen persistence too. So while spike protein persistence very likely has some degree of biological impact, having it is not immediately pathological — it is one research avenue among the many credible mechanisms Long COVID needs analyzed.

Because we have been caring for patients with post-acute infectious syndromes for years before COVID — as in "Long Mono," "Long Flu," "Long Lyme." Dr S. Blitshteyn, dysautonomia specialist and NIH RECOVER-TLC working group member, on why some clinicians weren't surprised Long COVID looked the way it did

That detail matters more than it first looks: mono, flu and Lyme are caused by unrelated pathogens — a herpesvirus, an influenza virus, a bacterium — that have nothing biologically in common with each other, let alone with SARS-CoV-2. If persistence of the specific pathogen were the driver, there's no reason those four completely different infections should produce a recognizably similar chronic illness afterward. A shared vulnerability in the person, rather than something shared between the pathogens, fits what's actually been observed a great deal better.

None of this means the virus was irrelevant. It means the virus was very often the initiator, not the driver — the event that started the damage, not the thing that has to keep circulating to sustain it. That distinction matters clinically: a mouse model of long-term post-COVID neurological deficits found the damage persisted for at least 60 days after the virus itself had become undetectable in the brain, the same pattern already documented in hamsters, where upper respiratory tract tissue stayed inflamed and epithelial cells kept dying for months after the infectious virus itself was gone (Liu et al., 2026). Barrier damage shows up directly in patients too: in one study, every Long COVID patient tested had impaired nasal epithelial barrier function, including near-total loss of occludin, one of the core proteins holding the tight junctions between epithelial cells together, compared with healthy controls (Baalbaki et al., 2026). Damage that outlasts its trigger is a very different thing from an infection that never cleared, and it's the pattern this model expects — an exposure, viral or chemical, damages a barrier, and the barrier stays damaged.

Screenshot of a post by Scott Daniska quoting Dr Nancy Klimas, Director of Neuro-Immune Medicine: "I can't clinically tell a toxic injury trigger to start these kinds of illnesses, from a viral trigger." Below the text is a video still of Dr Klimas speaking into a microphone, dated 24 September 2024.
C15 — Dr. Nancy Klimas, Director of the Institute for Neuro-Immune Medicine, on why a toxic-injury trigger and a viral trigger look the same to her clinically.

Asked to distinguish a toxic-injury trigger from a viral one, Dr. Klimas, who has researched ME/CFS for decades, said that clinically, she can't (C15).

That is the same ambiguity this whole page is about: illness that looks viral-onset can still have an environmental toxin doing the work, because the clinical picture doesn't tell you which one you're looking at.

COVID directly affects respiratory tissue, so damage from the virus lands on the respiratory epithelial barrier — the barrier that keeps out common, airborne contaminants. That includes abrasive nanoparticles like titanium dioxide, which can cause connective tissue damage and blood vessel leakage; fibers like microplastics, which can clog lymphatics; mold and mycotoxins, which can cause malaise; and VOCs, which can perpetuate that barrier damage and prevent recovery. This explains both the strong heterogeneity in symptoms and why some people develop Long COVID and others don't.

A patient's public post: twenty-two years old, completely bedridden for almost two years with ME/CFS after a stomach bug, with a twin brother who had the same stomach bug a day earlier and is perfectly healthy, asking whether any researchers are interested. The poster's name, handle and photo are blurred out.
C16 — A patient's public post: bedridden almost two years with ME/CFS after a stomach bug, while his twin brother, who had the same bug a day earlier, stayed well. Name, handle and photo blurred.

I know people who have had COVID five, six, seven times and are healthy and working full time, and I know people who caught it once and developed Long COVID. Only a minority of infected people go on to develop Long COVID, so what is different about them?

The usual answer is “it's just genetics.” Some genetic associations have been found, but they are weak and explain only a small part of who gets sick (see Weighing The Root Causes of Disease, above). Cases like C16 show why genetics alone can't be the answer: two brothers, the same bug a day apart, and only one developed ME/CFS. Something besides the genes and the infection decides who goes on to develop a chronic illness.

The genetics fit the same picture. FOXP4's involvement in lung disease is in being a transcription factor that regulates epithelial cell differentiation — the same type of cell destroyed by COVID infections, and the same type of cell that protects the human body from airborne contaminants.

So why does the same virus, in the same outbreak, leave one person fine and another disabled? A persistence model has no answer, because persistence isn't reliably different between the two. A susceptibility model does: some barriers were more compromised going in, by whatever a person's own exposure history happened to be, environmental included. That is also why an infection-triggered illness doesn't rule out an environmental contribution. The two aren't competing explanations: one is often what tips a barrier over the edge, and the other is what decided how close to the edge it already was.

Are environmental exposures a problem for people with ME/CFS?

Dr. Anna Gil
I've never come across an ME/CFS patient who didn't have sensitivities of some kind. — Dr. Anna Gil, Department of Pathology, UMass Chan Medical School (personal communication). Photo: UMass Chan Medical School

One exception to the rule stated at the top of this page, that everything here is independent published research rather than my own observation: I don't know of a published, controlled study measuring how often people with ME/CFS also report environmental or chemical sensitivities, so the figure below is mine, not the literature's. Across three informal polls I ran in Facebook patient support groups, about 80% of people with ME/CFS self-report chemical or environmental sensitivities (C17). Given that I had no idea for four years that environment was involved in my own case, I suspect the true figure is higher still.

Self-reported overlap: chemical sensitivity, CFS/ME, MCS and EDS

CHRONIC ILLNESS in CHEMICAL SENSITIVITY

Groups defined by a chronic illness, asked whether they also have chemical sensitivities

ME & CFS Self Help Group — 6 Dec 2021

“for those who have CFS here, do you also have environmental/chemical sensitivities?”

80%(54 yes votes)

Ehlers-Danlos Syndrome Support Group — 22 Nov 2024

“how many people here self identify as having chemical sensitivities of some degree?”

92%(220 yes votes)

CHEMICAL SENSITIVITY in CHRONIC ILLNESS

The reverse direction: a group defined by chemical sensitivity, asked whether they also have chronic fatigue/ME-CFS

MCS/Mast Cell Disorder & Food Intolerance Support — 28 Jul 2023

“for those with Multiple Chemical Sensitivity, do you identify as also having chronic fatigue or ME/CFS?”

72%(32 yes votes)

Source: three self-selected Facebook support-group polls, not a scientific survey.

A poll about chemical sensitivity posted in a support group is answered disproportionately by people who have it — these figures are likely inflated and shouldn't be read as prevalence estimates.

C17 — Three separate Facebook support-group polls, three separate questions, three separate populations — shown together because they point the same direction, not because they're one dataset. A poll about chemical sensitivity posted in a support group draws disproportionately from people who have it, so these are likely inflated and shouldn't be read as prevalence estimates. Self-selected, self-reported, unpublished.

References

These are the published studies the model draws on. They are real and independent of me; the synthesis and the application to ME/CFS are my own.

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