What initiates chemical intolerance? Findings from a large population-based survey of U.S. adults

Abstract

Background
Worldwide observations point to a two-stage theory of disease called Toxicant-Induced Loss of Tolerance (TILT): Stage I, Initiation by an acute high-level or repeated lower-level chemical exposures, followed by Stage II, Triggering of multisystem symptoms by previously tolerated, structurally diverse chemical inhalants, foods/food additives and drugs. Until recently, there was no known biological mechanism that could explain these observations. In 2021, we published a plausible and researchable two-stage biomechanism for TILT involving mast cells: Stage I, Initiation via mast cell sensitization; Stage II, Triggering of mast cell degranulation by previously tolerated exposures, resulting in the release of thousands of mediators, including histamine and a host of inflammatory molecules. The objective of this study was to identify common TILT initiators.

Methods
A randomized, population-based sample of 10,981 U.S. adults responded to a survey which included items concerning medical diagnoses, personal exposures, antibiotic use, and several possible initiators of Chemical Intolerance (CI). CI was assessed using the internationally validated Quick Environmental Exposure and Sensitivity Inventory (QEESI). Participants identified as chemically intolerant were asked to recall when their intolerances began and what they felt had initiated their condition.

Results
Twenty percent met QEESI criteria for TILT, approximately half of whom identified one or more initiating exposures. Initiators in order of frequency were mold (15.6%), pesticides (11.5%), remodeling/new construction (10.7%), medical/surgical procedures (11.3%), fires/combustion products (6.4%), and implants (1.6%). Protracted antibiotic use for infections involving the prostate, skin, tonsils, gastrointestinal tract, and sinuses were strongly associated with TILT/CI (OR > 2).

Discussion
Participants identified two broad classes of TILT initiators: 1) fossil fuel-derived toxicants (i.e., from coal, oil, natural gas), their combustion products, and/or synthetic organic chemical derivatives, e.g., pesticides, implants, drugs/antibiotics, volatile organic compounds (VOCs); and 2) biogenic toxicants, e.g., particles and VOCs from mold or algal blooms. One in four primary care patients suffers from Medically Unexplained Symptoms (MUS). Doctors in primary care, neurology, psychiatry, psychology, occupational medicine, and allergy/immunology would be well-advised to include TILT in their differential diagnosis of patients with so-called MUS. Because 20% of U.S. adults meet QEESI criteria for CI, the role of contemporary exposures in initiating and exacerbating these conditions via mast cells needs our immediate attention. There is a concomitant need for policies and practices that reduce initiating exposures as well as ubiquitous and often unavoidable triggers such as fragranced personal care, cleaning, and laundry products in multi-occupant housing, workplaces, medical settings, schools, places of worship, and all public buildings—literally anywhere air is shared. Fossil fuels are assaulting humans and other animal species both from within via mast cell sensitization, and from without via climate change.

Full text

Milleretal. Environmental Sciences Europe (2023) 35:65
https://doi.org/10.1186/s12302-023-00772-x
RESEARCH Open Access
© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
Environmental Sciences Europe
What initiates chemical intolerance?
Findings fromalarge population-based survey
ofU.S. adults
Claudia S. Miller1, Raymond F. Palmer1*, David Kattari2, Shahir Masri3, Nicholas A. Ashford4, Rodolfo Rincon1,
Roger B. Perales1, Carl Grimes2 and Dana R. Sundblad2
Abstract
Background Worldwide observations point to a two-stage theory of disease called Toxicant-Induced Loss of Toler-
ance (TILT): Stage I, Initiation by an acute high-level or repeated lower-level chemical exposures, followed by Stage
II, Triggering of multisystem symptoms by previously tolerated, structurally diverse chemical inhalants, foods/food
additives and drugs. Until recently, there was no known biological mechanism that could explain these observa-
tions. In 2021, we published a plausible and researchable two-stage biomechanism for TILT involving mast cells: Stage
I, Initiation via mast cell sensitization; Stage II, Triggering of mast cell degranulation by previously tolerated exposures,
resulting in the release of thousands of mediators, including histamine and a host of inflammatory molecules. The
objective of this study was to identify common TILT initiators.
Methods A randomized, population-based sample of 10,981 U.S. adults responded to a survey which included items
concerning medical diagnoses, personal exposures, antibiotic use, and several possible initiators of Chemical Intoler-
ance (CI). CI was assessed using the internationally validated Quick Environmental Exposure and Sensitivity Inventory
(QEESI). Participants identified as chemically intolerant were asked to recall when their intolerances began and what
they felt had initiated their condition.
Results Twenty percent met QEESI criteria for TILT, approximately half of whom identified one or more initiating
exposures. Initiators in order of frequency were mold (15.6%), pesticides (11.5%), remodeling/new construction
(10.7%), medical/surgical procedures (11.3%), fires/combustion products (6.4%), and implants (1.6%). Protracted anti-
biotic use for infections involving the prostate, skin, tonsils, gastrointestinal tract, and sinuses were strongly associated
with TILT/CI (OR > 2).
Discussion Participants identified two broad classes of TILT initiators: 1) fossil fuel-derived toxicants (i.e., from coal,
oil, natural gas), their combustion products, and/or synthetic organic chemical derivatives, e.g., pesticides, implants,
drugs/antibiotics, volatile organic compounds (VOCs); and 2) biogenic toxicants, e.g., particles and VOCs from mold
or algal blooms. One in four primary care patients suffers from Medically Unexplained Symptoms (MUS). Doctors
in primary care, neurology, psychiatry, psychology, occupational medicine, and allergy/immunology would be well-
advised to include TILT in their differential diagnosis of patients with so-called MUS. Because 20% of U.S. adults meet
QEESI criteria for CI, the role of contemporary exposures in initiating and exacerbating these conditions via mast
cells needs our immediate attention. There is a concomitant need for policies and practices that reduce initiating
*Correspondence:
Raymond F. Palmer
palmerr@uthscsa.edu
Full list of author information is available at the end of the article
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 2 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
exposures as well as ubiquitous and often unavoidable triggers such as fragranced personal care, cleaning, and laun-
dry products in multi-occupant housing, workplaces, medical settings, schools, places of worship, and all public build-
ings—literally anywhere air is shared. Fossil fuels are assaulting humans and other animal species both from within
via mast cell sensitization, and from without via climate change.
Keywords Chemical intolerance (CI), Toxicant-induced
loss of tolerance (TILT), Multiple chemical sensitivity (MCS),
Idiopathic environmental intolerance (IEI), Pesticides,
mold, antibiotics, combustion products, volatile organic
compounds (VOCs), Microbiome, prevention, breast
implant illness, mast cells, environment, exposures, mast
cell activation syndrome (MCAS), Toxicity, sensitization,
electromagnetic fields (EMF)
Introduction
Chemical Intolerance (CI) is characterized by multisys-
tem symptoms triggered by everyday exposures to chem-
icals, foods, and drugs [2, 4]. Symptoms often include
fatigue, headaches, weakness, rash, mood changes,
musculoskeletal pain, gastrointestinal and respiratory
problems, as well as difficulties with attention and con-
centration often described as “brain fog” [2, 4, 38, 76,
117]. CI is a rapidly rising international public health
concern. Prevalence estimates range from 8 to 33% in
population-based surveys [5, 20, 27, 66, 87]. In both
Japan [53] and the U.S. [103], surveys conducted a dec-
ade apart revealed substantial increases in CI. is paper
builds upon our earlier report for this cohort which doc-
umented that 20% of U.S. adults fulfill criteria for CI as
measured by the Quick Environmental Exposure and
Sensitivity Inventory (QEESI) [89].
Over the past 35 years, despite numerous proposed
case definitions for the condition, no consensus has
emerged [2, 4, 28, 29]. e published literature often
refers to CI as multiple chemical sensitivity (MCS) or idi-
opathic environmental intolerance (IEI). We no longer
use MCS or IEI, because they are too limiting and over-
look the two-stage TILT process. As we have shown [72]
and show once again in this paper, there are well-docu-
mented and well-characterized exposures which initiate
illness in large groups of individuals exposed to chemi-
cals, e.g., during the Gulf War, breast implants, pesti-
cides, and VOCs during new construction or remodeling.
A recent comprehensive epidemiologic and diagnostic
review indicates that assessing CI most often involves
the QEESI [97]. First published in 1999 [82], the QEESI
is now widely used in lieu of a case definition and is con-
sidered the reference standard for assessing CI. To date,
researchers in more than 16 countries on five continents
have used the QEESI in their studies [43, 46, 52, 60, 101].
e QEESI is a validated questionnaire derived by factor
analysis from symptoms and intolerances to chemicals,
foods, and/or drugs reported by individuals who said
they became ill following exposure to either an organo-
phosphate pesticide or new construction/remodeling [81,
98]. Subsequent studies of groups who reported devel-
oping chronic illness following exposures to other toxi-
cants, including Gulf War veterans and breast implant
recipients, further demonstrated the QEESI’s utility as
a measure of CI. e QEESI offers high sensitivity and
specificity in differentiating CI individuals from the gen-
eral population, making it useful for clinical and research
applications [52, 81, 82].
e present paper builds on our two prior publica-
tions that focused on TILT as a global phenomenon [80],
and mast cell activation and mediator release as a plau-
sible underlying biomechanism for TILT [80]. Here we
attempt to differentiate between TILT initiators (Stage
I of TILT) and TILT triggers (Stage II), the latter being
more readily observable both by affected individuals and
their medical providers. Patients and clinicians who are
unaware of the two-stage nature of the condition often
mistake the myriad triggers in Stage II of TILT as causal
and overlook Stage I (relating to what initiated TILT).
ere is great value in using self-reported questionnaires
to better understand the types of events or exposures
which affected individuals recall as having preceded CI.
eir recollections may help guide future research and
help predict and prevent TILT in the future.
TILT asanunderlying mechanism forCI
Individuals with CI often attribute onset of their illness
to specific exposure events such as the Gulf War, the
World Trade Center collapse, or exposures to pesticides,
VOCs associated with new construction or remodeling,
implants, and/or mold [72, 77, 91]. e fact that those
who share the same initial exposure frequently exhibit
different manifestations complicates diagnosis. For
example, an entire family may be exposed to mold in
their home. Some members may experience headaches,
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 3 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
others nausea, while still others have cognitive difficul-
ties. Some may report no symptoms at all. Moreover, if
family members see different doctors, a pattern of new-
onset, environmentally initiated illnesses may be missed.
First proposed by [75, 76], TILT is a two-stage disease
process: Stage I, called initiation, and Stage 2, triggering
[2, 4, 76]. Initiation begins with exposure to a particular
chemical or combination of chemicals, often at levels
below so-called “safe” occupational or environmental
exposure limits. TILT can develop rapidly (e.g., after a
pesticide exposure), or gradually over a period of months
(e.g., in a “sick” building) (see Fig.1). Initiating events
commonly go unrecognized and therefore unreported,
leaving triggers and symptoms as the only documented
components. is has thwarted our understanding of the
etiology of TILT. Further, our failure to ask patients about
possible initiating events has caused confusion con-
cerning the origins of other comorbid conditions such
as ADHD, autism, asthma, irritable bowel syndrome,
migraine headaches, depression, anxiety, brain fog and
other cognitive and mood difficulties. In addition, it has
led to a slew of non-etiologic diagnoses including MCS
and IEI.
Masking often obscures awareness of both initiators
and triggers. Masking results from the overlapping of
symptoms triggered by multiple ongoing exposures [2,
4, 78]. Routine use of nicotine-containing products; xan-
thines (e.g., chocolate, coffee, tea); alcoholic beverages;
certain medications; scented personal care; cleaning or
laundry products; and exposure to combustion products
from a gas stove or heating system often mask or hide
the relationship between exposures and symptoms. A
10-item Masking Index (which is not a scale) is therefore
included in the QEESI to assess ongoing exposures that
may otherwise be difficult for patients to recognize. For a
detailed discussion of masking, see [2, 4] and [78]. A per-
son with a high masking score on the QEESI is less able
to recognize symptom triggers [53, 81]. A very low mask-
ing score suggests that a person may have been avoiding
triggering exposures for such a long time that they no
longer recognize specific triggers.
Following TILT initiation, affected individuals report
an inability to tolerate everyday exposures to a wide
range of chemically diverse substances (including but not
limited to the initiator itself) at levels that never bothered
them previously and do not bother most people. Trigger-
ing exposures can include structurally unrelated ingest-
ants, inhalants, and skin contactants. Common triggers
include fragrances, nail polish/remover, hairspray, pesti-
cides, mothballs, cleaning products, fresh paint, tobacco
smoke, organic solvents, diesel or gas engine exhaust, as
well as foods/food additives and medications (see Fig.2)
[2, 4, 39, 40, 117].
Understanding TILT andinitiating events
Our understanding that chemical exposures can cause
new-onset intolerances (often perceived as “allergies”
for chemicals, foods, and drugs) evolved from interviews
with physicians in nine European countries who reported
seeing patients with heightened multisystem symptoms
along with sensitivities to odors, solvents, and sometimes
foods, often following a single major chemical exposure
or repeated lower level exposures [3, 79]. In both Europe
and the United States, commonly reported initiators
included pesticides, paints and lacquers/organic sol-
vents, formaldehyde, anesthetic agents, and hairdressing
chemicals.
e first systematic study of initiating events was pub-
lished in 1995 by [77]. ey compared two groups who
reported developing intolerances following distinctly
different exposures: a well-characterized organophos-
phate pesticide exposure (n = 37) and an exposure related
to new construction or remodeling (n = 75). Although
these exposures involved entirely different chemical
classes, individuals in both groups reported strikingly
similar patterns of chemical and food intolerances [77].
Subsequently, [81] studied symptoms and intolerances
reported by Gulf War veterans (n = 72), breast implant
recipients (n = 87), and individuals suffering from MCS
who attributed onset of their illness to various exposures
(n = 96) [81].
Recently we reviewed and summarized initiating expo-
sure events reported by eight well-documented groups
of individuals who had shared the same initial expo-
sures and subsequently developed CI [72]. ese groups
included: (1) EPA workers exposed following new carpet
installation; (2) Gulf War veterans; (3) casino workers
Fig. 1 Iceberg depicting two-stage process underlying
Toxicant-Induced Loss of Tolerance (TILT)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 4 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
exposed to organophosphate pesticides; (4) pilots and
cabin crews exposed to aircraft oil fumes (“fume events”);
(5) World Trade Center first responders and others in
close proximity to the disaster; (6) breast and other
implant recipients; (7) individuals exposed to mold in
their homes; and 8) tunnel workers exposed to gasoline
vapors (benzene) in a confined space.
ese studies have helped elucidate the phenomenol-
ogy of TILT (see Fig.1), but until now, there have been
no population-based data to help us understand which
exposures people most often view as having initiated
their intolerances. In the present study, we draw upon
our previously described population-based sample of
more than 10,000 U.S. adults to answer the following key
research questions:
A) What percentage of U.S. adults meet the QEESI cri-
teria for CI?
B) Among those with CI, which initiators do they most
commonly implicate?
C) Does exposure to multiple initiators increase the risk
of CI?
D) Do repeated or protracted courses of antibiotics over
the lifespan increase the risk of CI?
While pesticides are frequently reported CI initiators,
both antibiotics and pesticides are known to disrupt the
microbiome [22, 104], hence our fourth research ques-
tion. Digestive difficulties and food intolerances are com-
mon in all TILT exposure groups [77, 81]. Further, as
we previously reported, our gastrointestinal tracts are
densely populated with mast cells, which are our ancient
immune systems’ first responders to foreign substances
[80]. In the GI tract, mast cells protect us against the
largest quantity of xenobiotics we encounter—the food
we eat. We reasoned that disruption of the microbiome
might play a prominent role in the development of CI.
Consequently, we included exploratory questions con-
cerning antibiotic use. Finally, it should be noted that
the majority of antibiotics today are themselves synthetic
chemical derivatives of petroleum [47].
Methods
Sample population
We conducted a population-based survey of U.S. adults
aged 18 years and older. e survey was deployed
between June 1–2, 2020, using the SurveyMonkey audi-
ence platform (2020). SurveyMonkey recruitment pro-
cedures are available here: www. surve ymonk ey. com/ mp/
audie nce. 10,981 respondents were randomly selected
from nearly 3 million online users of the SurveyMonkey
platform. e survey had an abandonment rate of 10.1%
and took an average of approximately 5min to complete.
e modeled error estimate for this survey was ± 1.4%.
TOXICANT-INDUCED
LOSS OF TOLERANCE
Indoor Air Volale Organic
Compounds (VOCs)
•New carpet
•Plascizers
•Formaldehyde
•Fragrances
•Mold VOCs
Solvents
•Glues
•Paints
•Gasoline, other fuels
•Nail polish/remover
Drugs/Medical Devices
•Vaccines
•Anesthecs
•Implants
•Anbiocs
Combuson Products
•Engine exhaust
•Tobacco smoke
•Oil well fire smoke
•Natural gas
•Tar/asphalt
•Burn pits
•Soldering/welding
•Building fires
Pescides
•Organophosphates
•Carbamates
•Pyridosgmine bromide
•Pentachlorophenol
•Pyrethrins/pyrethroids
•DEET
•Airline “fume events”
(tricresyl phosphate)
Oil and Petroleum
Products
•Oil spills
•Fracking
•Refinery or occupaonal exposure
Cleaning Agents
•Ammonia
•Bleach
•Disinfectants
Fig. 2 TILT initiators and triggers
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 5 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Data were weighted based on the population sizes of all
50 states plus the District of Columbia, as well as by gen-
der, age, race, and education within each census region to
match the U.S. Census Bureau’s 2015 American Commu-
nity Survey (ACS) targets.
Survey
Respondents answered an 80-item survey we called the
Personal Exposure Inventory which included several
items concerning individuals’ medical diagnoses and
personal exposures including antibiotic use and several
possible initiating exposures. CI was assessed using the
QEESI Chemical Intolerance and Symptom Scales [81]
(see supplement section for list of worldwide studies
using the QEESI, now considered the reference stand-
ard for screening CI). Scores greater than or equal to 40
on both scales are considered to be very suggestive of CI.
Scores from 20 to 39 on one or both scales are suggestive
of CI. Scores less than 20 on both scales are not sugges-
tive of CI [81]. Of the total sample, 281 (2.5%) could not
be classified for CI and were excluded from the analysis
because they did not complete both QEESI scales.
All respondents were queried concerning protracted
antibiotic use: “Over your lifetime,have youtakena pro-
longed course ofantibiotics for any persistent, difficult-
to-treat infection(s)? (Check all that apply).” A series of
“yes” or “no” check boxes followed, inquiring about spe-
cific sites or types of infections: ear, tonsils, sinus, dental,
lungs, gastrointestinal, skin, genitourinary, wound, fun-
gal; plus, two gender-specific sites, vagina and prostate.
e Brief Environmental Exposure Sensitivity Inven-
tory (BREESI) is a validated three-question screen-
ing survey that has shown excellent predictive value
against the QEESI’s CI categories [87]. Individuals with
a positive screen on the BREESI (i.e., those reporting
adverse responses to chemicals, foods, and/or drugs)
were asked what they thought had initiated their CI
(see the flowchart in Fig. 3). Participants responded
“yes” or “no” to a series of check-box items: “Was there
a particular exposure(s) that initiated your chemical
intolerances/sensitivities?” Respondents who answered
affirmatively were asked to select which of the fol-
lowing potential initiators applied to them: Medical/
Aesthetic Implants, Pesticides, Combustion Products,
Mold, Surgical/Medical Procedures, or New Construc-
tion/Remodeling. We included the question about sur-
gical/medical procedures because we wanted to learn
whether procedures other than implants might be
implicated.
Statistical analysis
Data quality
measure Data quality
dimension Denition
Any NULL chemical
Score Completeness Any record having
at least 1 NULL value
in the QEESI chemical
score
Any NULL symptom
Score Completeness Any record having
at least 1 NULL value
in the QEESI symptom
score
Same non-0 chemical
Score Accuracy Any record having
the same non-0 QEESI
chemical score
Fig. 3 Study participant flow
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 6 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Data quality
measure Data quality
dimension Denition
Same non-0 symptom
Score Accuracy Any record having
the same non-0 QEESI
symptom score
Gender mismatch Validity Any record submit-
ted with the gender
questions not matching
the survey monkey
panel gender
Male & vaginitis Validity Any record indicating
male gender and vagi-
nitis
Female & prostate Validity Any record indicat-
ing female gender
and prostate cancer
Male & breast
Implants Validity Any record indicating
male gender and breast
implants
Too Fast Accuracy Any record indicating
survey completion
in 2 min or less
The 10,981 survey records were assessed for data qual-
ity (DQ). A list of data conditions that could pose com-
pleteness, validity, or accuracy concerns was created.
Any record with these DQ concerns was excluded from
the analytic data set. Some of the measures could tech-
nically be accurate (e.g., “Male & Breast Implants”),
but out of an abundance of caution were excluded. The
same could be said for the “Too Fast” measure: with
a survey length of between 15 and 22 questions, it is
very unlikely that a respondent could read and respond
accurately to all questions in under two minutes. By
omitting any records that violated one or more DQ
measures, 2985 records were excluded (27.2%). The
largest single DQ measure contributing to exclusion
was “Too Fast” with 1,616 records, and the second
largest was “Gender Mismatch” with 614 records. We
have taken this approach to help ameliorate some well-
known DQ issues associated with web-based surveys,
including response probabilities and biases [11, 25].
Our final analytic sample was N = 7997.
Binary logistic regressions were conducted to deter-
mine the extent to which initiating events and pro-
tracted antibiotic use were predictive of CI risk. The
binary outcome variable compared not suggestive to
very suggestive QEESI categories. We first used initi-
ating exposure events and protracted antibiotic use as
continuous variables (based on the number of identi-
fied exposures) in separate models which included age,
gender, and household income as covariates (Table4,
Models 1 and 2). In Models 3 and 4 (Table4), initiat-
ing events and antibiotics were used as independent
dichotomous (individual yes/no) predictors of CI. A
final model combined both the initiating event and
antibiotics items (Table4, Model 5) in the form of a
multivariate model. All models were adjusted for gen-
der, age, and household income. In this study, we used
a p-value 0.05 threshold to determine statistical sig-
nificance. Analyses were conducted using JMP (1989–
2019) and SAS software (2014) [61, 98].
Table 1 Descriptive statistics for total population sample
(N = 7997)
Variables in logistic models predicting CI %
Demographics N = 7997
% Female 4580 57.3
Age > 60 1827 22.9
Household income
< $50,000 2843 35.6
$50,000-$100,000 2586 32.3
> $100,000 1802 22.5
Missing 766 10.0
CI assessment by QEESI N = 7997
Not suggestive of CI 1745 21.8
Suggestive of CI 4605 57.6
Very suggestive of CI 1647 20.6
CI initiators (see Fig. 1)N = 5576 69.7
Mold 975 17.5
Pesticides 772 13.8
Remodeling/construction 669 12.0
Medical/surgical procedures 705 12.6
Combustion 403 7.2
Other 416 7.5
Implants 102 1.8
Don’t know or none 3406 61.1
Protracted antibiotics N = 7997
Infection site
Sinus 1990 24.9
Ear 1541 19.3
Dental 1503 18.8
Pneumonia 1402 17.5
Urinary tract 1231 15.4
Wound 811 10.1
Tonsil 744 9.3
Gastrointestinal 665 8.3
Skin 608 7.6
Fungal 551 6.9
Vaginal 238 3.0
Prostate 114 1.4
Other 207 2.6
None 3007 37.6
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 7 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Results
Descriptive statistics
Table1 provides descriptive statistics for the entire sur-
vey population. e number and percentages of QEESI
scores, initiating events, and protracted antibiotic
courses are shown. Figure3 depicts respondent flow and
shows the numbers and percentages who completed sur-
vey items for initiating events. Only individuals with a
positive BREESI screen (79.2%) were asked about initiat-
ing exposure events. Approximately half of those with a
positive BREESI screen (54.5%) did not identify an ini-
tiating event. In order of frequency, initiators specified
by participants who identified any initiating event were
Mold (15.6%), Pesticides (11.5%), Medical/Surgical Pro-
cedures (11.3%), Remodeling/New Construction (10.7%),
other (6.7%), Combustion Products (6.4%), and Implants
(1.6%). Table2 shows the overlapping responses for the
initiator items. e initiators most frequently selected
together were Mold, Pesticides, and Remodeling/
Construction.
Table3 shows the distribution of the total numbers and
percentages reported for initiating events and protracted
antibiotic use.
Figure 4 shows the initiating exposure items. In
descending order, the initiating events with the high-
est average QEESI scores were Implants, Pesticides,
Combustion Products and Medical/Surgical Exposures.
Figure5 breaks down the initiator responses by QEESI
category. As might be expected, the very suggestive CI
group identified the most initiators, followed by the sug-
gestive group which in turn identified more than the not
suggestive group. Figure6 depicts the mean number of
initiating events by QEESI category, suggesting a linear
relationship.
Statistical modeling results
Model 1: Initiating exposure events asacontinuous predictor
variable
Results from the logistic regression model that used initi-
ating events as a count variable are presented in Table4.
e model R2 was 0.16. Initiator count, gender, and age
were significant contributors to the model (p < 0.01). To
assess a non-linear association, a squared term for Initi-
ating Exposures count was added and was not significant
(p = 0.31). Interactions between gender and age were also
evaluated and were not significant, nor was household
income (p = 0.07). Females were twice as likely to have
QEESI scores very suggestive of CI. Respondents older
than 60years were approximately half as likely to have
scores very suggestive of CI compared to respondents
under 60. Notably, for every initiating exposure event
reported by respondents, the odds of their belonging to
the very suggestive category nearly tripled, increasing by
2.9 on average.
Model 2: Antibiotics asacontinuous predictor variable
Results from the logistic regression model that used
the number of protracted antibiotic exposures appear
in Table4. To assess a non-linear association, a squared
Table 2 Percentage of multiple initiators chosen among those choosing more than one initiator (N = 966)
Diagonal percentages indicate the percentage of participants choosing only that single initiating event
Construction % Medical % Implants % Pesticide % Combustion % Mold %
Construction 19.9 14.9 5.4 20.8 14.7 26.8
Medical 26.0 4.5 18.9 11.2 25.1
Implants 1.8 2.7 3.5 3.2
Pesticide 18.2 19.8 38.2
Combustion 6.5 18.2
Mold 27.7
Other
Table 3 Lifetime protracted antibiotic courses and initiating
events
Antibiotic courses N Percent
0 3382 42.29
1 1752 21.91
2 1125 14.07
3 749 9.37
4 425 5.31
5 251 3.14
6 + 313 3.92
Initiating events N Percent
0 5856 73.23
1 1175 14.69
2 593 7.42
3 268 3.35
4 + 105 1.31
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 8 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Fig. 4 QEESI chemical intolerance and symptom scores by reported exposure initiators. Combustion products, implants, medical/surgical
procedures, and pesticides are most associated with the QEESI chemical intolerance and symptom severity scales
Fig. 5 Percent reporting varying degrees of chemical intolerance by QEESI initiating event and QEESI category
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 9 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
0
0.2
0.4
0.6
0.8
1
1.2
Not Suggestive of CI Suggestive of CI Very Suggestive of CI
Mean Number of Initiating Events
QEESI Categories
Fig. 6 Mean number of initiating events by QEESI category
Table 4 Logistic regression models initiators and antibiotics predicting chemical intolerance
Model 1 Model 2 Model 3 Model 4 Model 5
Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI) Odds ratio (95% CI)
Number of initiating events 2.9 (2.5–3.4) – –
Number of antibiotic exposures – 1.8 (1.7–1.9) –
Female 2.3 (1.9–2.8) 2.0 (1.7–2.4) 2.3 (1.9–2.8) 2.1 (1.8–2.4) 2.1 (1.7–2.6)
Age > 60 0.51 (0.4–0.6) 0.52 (0.4–0.6) 0.48 (0.38–0.61) 0.51 (0.42–0.62) 0.55 (0.43–0.70)
Household income 0.93 (0.90–0.96) 0.93 (0.90–0.95) 0.93 (0.90–0.96) 0.92 (0.90–0.95) 0.93 (0.90 –0.97)
Implants – – 3.6 (1.2–10.5) – 2.9 (0.9–8.5)ns
Pesticides – – 5.5 (3.5–8.6) – 4.8 (3.1–7.5)
Combustion products – – 2.7 (1.5–4.6) – 2.3 (1.3–4.0)
Mold – – 2.9 (2.1–4.0) – 2.3 (1.7–3.3)
Surgical/medical procedure – – 2.2 (1.6–3.1) – 1.9 (1.3–2.6)
New construction – – 2.3 (1.6–3.3) – 2.2 (1.5–3.2)
Prostate – – – 2.3 (1.1–4.9) 1.6 (0.6–4.5)ns
Skin – – – 3.0 (2.1–4.3) 1.7 (1.2–2.6)
Tonsils – – – 1.9 (1.4–2.6) 1.6 (1.1–2.4)
Gastrointestinal – – – 2.4(1.7–3.2) 1.9 (1.3–2.9)
Sinus – – – 2.2 (1.8–2.7) 1.8 (1.4–2.4)
Wound – – – 2.2 (1.6–3.0) 1.8 (1.2–2.7)
Fungal – – – 1.5 (1.1–2.2) 1.1 (0.7–1.7)ns
Pneumonia – – – 1.7 (1.4–2.2) 1.5 (1.1–2.0)
Ear – – – 1.5 (1.2–1.8) 1.2 (0.9–1.5)ns
Dental – – – 1.5 (1.2–1.9) 1.4 (1.1–1.9)
Vaginal – – – 0.99 (0.57–1.7)ns 0.90 (0.5–1.8)ns
Urinary tract – – – 1.5(1.2–1.9) 1.7 (1.2–2.3)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 10 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
term for antibiotic exposure count was added. Both the
linear and non-linear terms for antibiotic count, as well
as gender, income, and age were all significant contribu-
tors to the model (p < 0.01). e interaction between
gender and age was significant (p = 0.01), but the overall
effect estimate was small, indicating that females over
60 years of age were slightly less likely to have scores
very suggestive of CI. e model reported an R2 of 0.21.
Importantly, for every initiating exposure reported by a
respondent, the odds of having scores very suggestive of
CI increased by 1.9 on average. When including the sig-
nificant non-linear trend, the odds ratio (OR) showed a
2.4 increase for each initiator.
Model 3: Initiating exposure events asbinary predictors
Results from the logistic regression model that included
Initiating Exposures as individual binary exposure vari-
ables are also presented in Table4 (Model 3). e model
reported an R2 of 0.16. Gender and age were signifi-
cant contributors (p < 0.01), unlike household income
(p = 0.06). Each of the six initiating exposures contrib-
uted significantly to the model (p < 0.01). Ranked in order
are the ORs for each class of initiating exposures: Breast
Implants (OR = 7.5), Pesticides (OR = 4.4), Combu stion
Products (OR = 3.6), Mold (OR = 2.9), Surgical/Me dical
Procedures (OR = 2.4), New Construction/Remodeling
(OR = 2.2).
Model 4: Antibiotics asbinary predictors
Results from the logistic regression model that included
antibiotic exposures as individual binary exposure vari-
ables are presented in Table4. e model reported an
R2 of 0.20. Gender, income, and age were significant
contributors to the model (p < 0.01). All protracted anti-
biotic exposures contributed significantly to the model
(p < 0.04). Ranked in order are the ORs for protracted
antibiotic use by infection site/type: prostate (OR = 3.0),
skin (OR = 2.8), tonsils (OR = 2.7), gastrointestinal tract
(OR = 2.5), sinuses (OR = 2.2), wounds (OR = 1.9), fungal
(OR = 1.8), pneumonia (OR = 1.7), ear (OR = 1.7), dental
(OR = 1.7), vagina (OR = 1.6), urinary tract (OR = 1.6).
Model 5: Initiating exposures andantibiotics asbinary
predictors
Results from the logistic regression model that consid-
ered Initiating Exposures and Protracted Antibiotic Use
as individual binary exposure variables are presented
in Table4. e model reported an R2 of 0.22 with good
fit. As in the other models, gender and age remained
significant contributors to the model (p < 0.01), while
household income did not. All six initiating exposures
significantly contributed to this model (p < 0.01). Nine of
the 12 antibiotic exposures contributed significantly to
this model (p < 0.05). Model 5 fit the data well (p = 1.0 for
lack of fit).
Ranked in order, the ORs for both protracted antibi-
otic use and exposure events are as follows: Pesticides
(OR = 4.8), Breast Implants (OR = 2.9), Combustion
Products (OR = 2.3), Mold (OR = 2.3), Remodeling/New
Construction (OR = 2.2), and Surgical/Medical Proce-
dure (OR = 1.9). For antibiotics, the ranked order was:
Gastrointestinal (OR = 1.9), Sinus Infection (OR = 1.8),
Wound (OR = 1.8), Skin (OR = 1.7), Urinary Tract
(OR = 1.7), Tonsils (OR = 1.6), Pneumonia (OR = 1.5),
Dental (OR = 1.4), Fungal (OR = 1.1).
Discussion
Identifying initiators
Approximately two-thirds of our sample (n = 5576/7997,
70%) had a positive BREESI screen (answered “yes” to
one or more of the three BREESI items), indicative of at
least some degree of chemical, food, and/or drug intoler-
ance. Approximately 40% of these individuals attributed
onset of their illness to an initiating exposure event or
multiple events. Further, a lifetime history of protracted
antibiotic use was associated with chemical intolerance.
Specifically, we found that with every additional initiating
exposure event, the odds of reporting CI nearly tripled. We
also demonstrated that prolonged courses of antibiotics
were associated with increased risk of CI, and with every
additional course of antibiotics the odds of CI nearly dou-
bled. at discrete exposure events were associated with
CI is consistent with findings from of our prior published
study showing that CI is frequently preceded by identifi-
able toxicant exposures such as new carpet installation,
pesticide use, combustion/pyrolysis emissions, occupy-
ing a moldy home, occupational exposures to VOCs, and
breast implants [72]).
Women tended to have higher scores on the QEESI, a
finding consistent with other studies which have shown
the prevalence of CI among females across various pop-
ulations ranged from 69 to 80% [32, 54, 66, 103]. is
difference may be biologically based or stem from dif-
ferences in exposures, e.g., women repeatedly exposed
to fragranced cosmetics, soaps, sprays and personal
care products, as well as fragranced cleaning and laun-
dry products, all of which commonly are used in poorly
ventilated spaces. In addition, it is well-established that
males and females differ in their immune responses to
foreign and self-antigens. For instance, elevated humoral
immunity (immunoglobulins) in females compared to
males is physiologically conserved, perhaps imparting an
adaptive advantage for transferring protective antibod-
ies in utero to a fetus [33]. Anatomic differences between
males and females also may affect vulnerability to CI
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 11 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
[88]. For example, mast cells in the nose can be sensi-
tized by inhaled VOCs, mold, or combustion products.
Subsequent exposures can trigger mast cell degranula-
tion releasing a cascade of mediators causing swelling of
the nasal mucosa and occluding sinus openings, which
are smaller on average in females. Cutting off air to the
sinuses results in an anaerobic condition and chronic
infections, likely leading to repeated or prolonged
courses of antibiotics.
In general, the strength of the association between
antibiotic use and CI suggests a potential causal role of
antibiotics in CI initiation. Although this question cannot
be answered by this single study, in part due to the limi-
tations to be discussed later, it nonetheless supports the
hypothesis that alterations in the gut microbiome may
be associated with the development of CI [12, 26], sug-
gesting the need to restore normal gut flora. Importantly,
however, it is not clear from this analysis nor from prior
literature in which direction a potential causal associa-
tion may lie. at is, it is unclear how antibiotic use may
contribute to the development of CI: Do antibiotics com-
promise the gut microbiome? And/or do CI individuals
take more antibiotics?
Regarding protracted antibiotic use for specific types
of infections among those with scores very suggestive of
CI, antibiotics prescribed for infections categorized as
Skin, Tonsils, Gastrointestinal, Prostate, Sinuses, Wound,
and Pneumonia were most strongly associated with CI
(OR > 1.5). Early evidence of an association between the
gut microbiome and CI was previously documented by
[77] who showed a direct relationship between the num-
ber of intolerances for chemical inhalants and the num-
ber of food intolerances reported by people who said they
became ill after organophosphate or remodeling expo-
sures [77]. Further, organophosphate exposures, such as
exposures to the common agricultural pesticide chlor-
pyrifos (now banned for household use) are known to
disrupt the gut microbiome [31, 67, 121, 123]. Similarly,
antibiotics alter the gut microbiome [94]. Adding further
weight to this association is evidence of reduced food
intolerances among individuals following treatment with
probiotics [70, 90, 109, 110].
In the present analysis, the initiating exposures
reported most frequently (> 10% of respondents who
identified an initiating event) were Mold, Remodeling/
New Construction, Medical/Surgical Procedures, and
Pesticides, while exposures to Combustion Products,
Implants, and others were less frequently reported. e
ranking of initiating events based on odds ratios differed
from that of their frequencies, with Pesticides, Breast
Implants, Mold, and Combustion Products showing the
highest odds ratios (OR > 2), followed in order by Surgi-
cal/Medical Procedures (OR = 1.9). It is important to
note that the rankings of initiating events may be influ-
enced by, and therefore partially reflect, the obviousness
of an exposure event from the perspective of a survey
participant. For instance, since occupants are apt to see
and/or smell mold indoors, as opposed to invisible or
non-odorous airborne VOCs and pesticides, participants
may have implicated mold disproportionately.
Evidence andimplications ofinitiating exposures
e concept that the exposures and exposure events
reported in this analysis have the potential to initiate CI is
supported by well-documented reports in peer-reviewed
papers describing the initiation of CI among groups of
individuals who shared the same initial exposure events,
several of which are summarized in our prior work [72,
81], as well as reports of CI-related symptoms that abate
following the removal of certain exposures, e.g., breast
implants. [114]. Notwithstanding, mold was the most fre-
quently implicated exposure (17.1%) in our study. Mold
spores, mold VOCs and debris can concentrate in the air
where fresh air ventilation is poor, giving rise to adverse
health effects [65]. Evidence of mold-related CI was well-
documented in the case of nine Finnish family members
who moved into a moisture-damaged house where they
subsequently developed a range of symptoms including
eye irritation, cough, congestion, shortness of breath, and
chemical intolerances. eir symptoms abated only when
the family moved to a different home [106].
Finland is located in a subarctic region where snow
melt, leaking roofs, and winter storms lead to water
intrusion, mold growth and mold-related health prob-
lems in homes, workplaces, and schools. Based upon
clinical experience with more than 1000 patients with
“Dampness and Mold Hypersensitivity Syndrome”, Finn-
ish physician Ville Valtonen reported that approximately
half of such patients ultimately developed CI and related
symptoms [108]. Likewise, researchers in Tampere, Fin-
land [85] used the QEESI to assess patients referred for
respiratory and/or voice symptoms associated with work-
place moisture damage. Compared to randomly selected
controls from the Finnish Population Information Sys-
tem, the patients had significantly higher scores on the
Chemical Intolerance (39% vs. 23%, p < 0.001), Symptom
Severity (60% vs. 27%, p < 0.001) and Life Impact scales
(53% vs. 20%, p < 0.001). Scandinavian researchers have
also identified exposures to both electromagnetic fields
(EMF) and mold as potentially altering mast cells and
underlying CI [37, 62, 63, 92, 93, 112, 113].
Similarly, Kilburn [64] compared symptomatic adults
living in moldy homes to individuals who became ill
following exposure to various chemicals (e.g., diesel
exhaust, organophosphate insecticides, glutaraldehyde,
and cleaning agents) to asymptomatic controls. Applying
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 12 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
a comprehensive battery of neurobehavioral tests, he
found a more than fivefold higher incidence of abnor-
malities in the two exposed groups relative to controls
[64]. Interestingly, the 1995 publication concerning CI
in European countries conducted by one of the present
authors did not identify mold as an initiator [3], nor was
mold mentioned in the 1989 New Jersey Report or sub-
sequent book by [2, 4]. In recent years, global warming
has led to more rainfall, floods, hurricanes, roof leaks,
and water intrusion, resulting in increased mold growth
indoors.
While mold spores and particles can be toxic via inges-
tion or inhalation and can irritate any exposed part of
the body, inhaling low molecular weight mold VOCs
(mVOCs) may constitute an important initiating expo-
sure that has been largely overlooked [10]. Supporting
this possibility is an experiment in which developing fruit
flies exposed to mVOCs at levels comparable to those
reported in moldy buildings [65] exhibited Parkinson’s
disease-like symptoms [55, 56]. Importantly, when wet,
any organic materials such as carpets, fabrics, paper, ply-
wood, compressed wood, and gypsum board can grow
mold within 48–72h. Careless removal of moldy mate-
rials and/or applying chemicals such as cleaning agents,
bleach, or disinfectants further exposes workers and
occupants. MVOCs vary greatly in toxicity as demon-
strated by [122] who compared the toxicities of mVOCs
from 24 fungal species isolated from mold colonies cul-
tured following Hurricane Sandy on fruit fly larvae in a
shared test tube atmosphere [122].
In the present study, exposure to new construction/
remodeling was implicated by 12.0% of those fulfilling
QEESI criteria for CI. Strong evidence for a causal role
for new construction/remodeling-related chemical expo-
sures and CI arose in 1987 when approximately 27,000
square yards of new carpet were installed in the U.S. EPA
headquarters building in Washington, D.C., leading to
an estimated 124 of 2000 employees subsequently fall-
ing ill, eight of whom acquired CI, most often reacting to
fragrances, traffic exhaust, and tobacco smoke. ough
not the first evidence of CI, this event represents the first
widely acknowledged episode involving CI acquired in
a sizable group, many of whom were federal indoor air
scientists. e substance most implicated in these ill-
nesses was 4-phenylcyclohexene (4-PCH), an undesirable
byproduct with an odor of new carpet from the manufac-
ture of styrene-butadiene rubber (SBR) latex—an adhe-
sive used to attach carpets to their backing. A description
of this event and related indoor air testing can be found
elsewhere [2, 4, 51, 84].
Although initiation by medical/surgical procedures
was reported third most often, by 12.6% of those with CI,
diverse scenarios were involved, making it challenging
to isolate causal associations. However, potentially rel-
evant exposures included anesthetics, intravenous tub-
ing, chemotherapy and other cancer therapies. e best
documentation of CI in the context of medical or sur-
gical procedures relates to breast implant recipients
[114]. e present findings, and the fact that our survey
included questions concerning both implant- and non-
implant-related medical/surgical procedures, suggests
the need for further research to understand the potential
relationship between non-implant-related medical/surgi-
cal procedures and the development of CI. Studies of CI
related to anesthesia and chemotherapy may provide use-
ful insights, for example, by using the QEESI to evaluate
patients pre- and post-surgery or chemotherapy.
Surgical implants were identified as an initiating event
by just 1.8% of our CI participants. Following such pro-
cedures, many physicians have reported multisystem
symptoms in patients closely resembling chronic fatigue
syndrome and CI [15, 111]. Importantly, Wee etal. (2020)
reported significant improvements in symptoms such
as fatigue, memory, and, most notably food intolerances
among 750 breast implant patients whose implants were
removed. Similarly, Campbell etal. (1994) reported that
implant removal reversed symptoms in 40–60% of breast
implant patients. Potential exposures include silicone
which may leach slowly from intact breast implant mem-
branes [14, 16], producing inflammatory and immuno-
logical responses [16, 111], as well as metals which can
migrate into surrounding tissue [42] and processing
aids and peroxides used to facilitate the curing process
for implant gels. At increased risk were individuals with
autoimmune antibodies [111, 120], whose symptoms may
involve CI [14, 100]. Additional reported associations
between chemical intolerance and breast implants appear
elsewhere [2, 4, 57, 81].
Pesticides, implicated by 12% of our participants with
CI, have long been known to initiate CI, particularly
exposures to organophosphates and/or carbamates [2,
4, 77]. Pesticide exposures arise from domestic pesticide
use, commercial extermination, occupational use/pro-
duction, agricultural use, or community-wide spraying
[23]. Described in detail casino workers who developed a
“mystery illness” coinciding with the application of carba-
mate and pyrethroid pesticides in the employee café and
basement walls [23]. Subsequently, 12 of 19 workers who
were referred for medical evaluation developed CI, mani-
festing as new-onset “sensitivities” to perfumes, gasoline,
newsprint, cleaning materials, pesticides, and solvents.
In many communities, aerial pesticide spraying is a
regular occurrence, particularly during peak mosquito
seasons and in the wake of hurricanes and floods [30,
69, 71]. TILT may represent yet another adverse impact
related to climate change as global temperatures rise and
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 13 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
the populations and habitat ranges of pests such as ticks
and mosquitos increase [58, 73]. Safer approaches to pest
management, including organic gardening and farming,
the use of beneficial insects, sophisticated modeling to
better understand pest populations, and methods that
reduce pesticide resistance, can help protect the public
from pesticide-initiated CI.
Pesticides were widely applied to prevent vector-borne
disease among Gulf War troops. e U.S. Department of
Defense estimated that at least 40,000 service members
may have been overexposed to organophosphates [50,
96]. Following the war, over 200,000 individuals devel-
oped so-called “Gulf War Illness”, characterized by mul-
tiple symptoms which often included chemical, food,
and drug intolerances [35, 102, 107, 115]. Importantly,
research on wartime exposures has also implicated chem-
ical weapons released or present near military personnel
during the Gulf War as risk factors for CI, including the
organophosphate (OP) nerve agents sarin and cyclosa-
rin, which similarly inhibit the enzyme acetylcholinest-
erase (AChE). Further, pyridostigmine bromide, also a
carbamate, was administered in pill form to an estimated
250,000 U.S. soldiers as a pre-treatment against possible
nerve agent exposure [41]. Researchers have thoroughly
explored OP toxicity in terms of cholinesterase inhibi-
tion. With TILT, we appear to be dealing with an entirely
new mechanism for OP toxicity, that is, sensitization of
mast cells. is offers a new view of the multisystem,
often disabling symptoms and chemical, food, and drug
intolerances reported by OP-exposed individuals [80].
As early as 1996, physician and researcher Gunnar Heu-
ser postulated that chemical exposures can trigger a mast
cell disorder, which he felt could explain the underlying
mechanism of TILT [48, 49].
Miller and Mitzel [77] described 37 individuals who
reported multisystem symptoms and chemical and food
intolerances following OP pesticide extermination.
eirs was also the first paper to implicate OPs as likely
initiators of Gulf War Illness. Other researchers investi-
gating Gulf War Illness have shown that troops exposed
to petroleum fires, as well as chemical weapons contain-
ing sarin and cyclosarin developed symptoms of CI [41,
50, 115].
Combustion products (including pyrolysis products),
which were cited as initiators by over 7% of our CI par-
ticipants, similarly have been implicated as initiators of
CI. is was described by pilots, flight attendants, and
frequent flyers exposed to visible smoke/fumes and strong
odors followed by CI-like symptoms, a phenomenon
known as “aerotoxic syndrome”. Michaelis etal. [74] sur-
veyed British pilots about their experience with contami-
nated air aboard aircraft and found that 88% were aware
of cabin air contamination, with 34% reporting “frequent”
exposures, 7% reporting visible smoke or mist, and 53%
describing neurological symptoms including “chemi-
cal sensitivity” [74]. Similarly, following the collapse of
the World Trade Center (WTC), Dr. Steven Levin of the
Mount Sinai School of Medicine noted that some of his
patients “once away from Lower Manhattan have noticed
a general improvement in their symptoms but find that
exposure to cigarette smoke, vehicle exhaust, cleaning
solutions, perfume, or other airborne irritants provokes
reoccurrence of their symptoms in ways they never expe-
rienced before 9/11.” e WTC disaster exposed many
individuals to high concentrations of complex combustion
particles [72].
Possible mechanisms
ere is evidence linking CI to autoimmunity through
autoantibody production against myelin basic pro-
tein, myelin-associated glycoprotein, ganglioside GM1,
smooth muscle cells, and antinuclear autoantibod-
ies [1, 19, 44, 105]. Other proposed mechanisms for CI
involve olfactory-limbic kindling, that is, amplification
of reactivity to inhaled and ingested chemicals resulting
in persistent affective, cognitive, and somatic symptoms
[7–9, 17]. Building on this mechanism, [86] outlined a
plausible set of interacting synergistic biomechanisms
implicating an excess of N-methyl-D-aspartic acid or
N-methyl-D-aspartate (NMDA) activity effecting nitric
oxide-mediated stimulation of glutamate, decreased
cytochrome P450 metabolism, and ATP depletion, result-
ing in increased permeability of the blood–brain barrier,
thereby allowing organic chemicals to enter the central
nervous system and resulting in CI symptomatology [86].
Organophosphate pesticides (OPs), which bind irre-
versibly to cholinergic receptors, appear to be among
the most severe and permanently damaging CI ini-
tiators. Organophosphates can trigger degranulation of
human and animal mast cells [119]. In mice, repeated
oral administration of the OP malathion led to mast cell
degranulation at doses below those that inhibit cholinest-
erase. Malathion is widely used for mosquito control,
agriculture, and landscaping. Residues are present in
foods [6].
e parasympathetic nervous system also modulates
mast cell activity via a cholinergic pathway [34]. Mast
cells play pivotal roles in regulating cerebral blood flow
[68], directly affecting brain function. Notably, both mast
cell activation syndrome (MCAS) and CI patients com-
monly report cognitive difficulties, including “brain fog”.
A study by one of this paper’s authors (Miller) involving
low-level VOC (acetone) exposure in ill vs. asymptomatic
Gulf War vets demonstrated that cerebral blood flow
failed to increase to match the requirements of a difficult
cognitive task [18, 81].
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 14 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Some of the most severely “TILTed” individuals report
initiation by exposure to OPs [77]. Groups exposed to
OPs and at risk for TILT include agricultural workers,
sheep dippers, building occupants exposed to pesticides,
Gulf War soldiers, and airline crew members exposed
to “fume events” during which engine lubricants bleed
into cabin air [2, 4, 116]. OPs irreversibly bind acetylcho-
linesterase (ACHE). Activity of the enzyme paraoxonase,
or PON1, helps determine a person’s ability to detoxify
OPs [24, 36, 59] and may explain why certain individuals
are particularly susceptible to TILT. However, mast cell
sensitization helps explain the long-term illnesses and CI
that some individuals develop.
Finally, the role of oxidative stress (OS) must be consid-
ered. It has been established that reactive oxygen species
(ROS) are involved with intracellular signaling of various
proinflammatory cytokines regulating innate immunity,
including mast cells [21]. Several studies demonstrate
that over-production of ROS triggers proinflammatory
processes through activation of several regulatory pro-
teins [95].
OS in known to mediate various allergic disorders, such
as asthma, rhinitis, and atopic dermatitis. Understanding
the biopathways of OS along with the role that antioxidants
play, can help in the development of treatments of many
associated diseases [45]. Persistent OS can damage pro-
teins, lipids, and DNA as a result of inflammation initiated
from environmental exposures [13]—either from a single
high-level toxicant exposure, or from concurrent low-level
exposures from multiple sources, such as those initiating
exposures reported by the respondents in our survey.
TILT appears to involve alteration/sensitization of
our immune systems’ ancient first responders—mast
cells—so that individuals no longer tolerate previously
endured chemical inhalants, foods and drugs. In this way,
TILT resembles both allergy and toxicity. Both stages of
TILT—(I) initiation by a wide variety of toxicants and
(2) subsequent triggering by previously tolerated xeno-
biotics—appear to involve oxidative stress leading to the
generation of free radicals which can disrupt cell metab-
olism, gene expression, and signal transduction. TILT
initiation, for example, may result from DNA oxidation
causing instability of the genome byaffecting mast cell
DNA, either directly or epigenetically [21].
Taken together, our data support the idea that the
person who reports multiple symptoms, multiple intol-
erances, and recurrent infections as well as a history
of exposure events is sharing a cohesive narrative, one
that points to physiological (as opposed to psychoso-
matic) explanations of their oft-confusing complaints.
Patients with high QEESI scores may have experienced
one or several toxic exposures over time as well as mul-
tiple protracted antibiotic courses. Personal histories are
complex. For example, a water intrusion event that led to
mold growth may have been remediated using phenolic
disinfectants or bleach, with fragrances applied in order
to mask odors. Subsequent remodeling might include
demolition, installing new carpet, painting, applying
adhesives, and the introduction of new outgassing finish-
ing materials and furnishings (e.g., particleboard). ese
exposures irritate the airways and could lead to chronic
or recurrent sinus infections, for which doctors may pre-
scribe protracted courses of antibiotics. Both pesticides
and antibiotics can disrupt normal gastrointestinal flora
resulting in new food intolerances.
Our results suggest that exposures to antibiotics over
the life course and certain major environmental expo-
sures are predictive of CI. is is consistent with a recent
paper by [99] reporting an association between infection
and CI [99]. Although not reported in their manuscript,
it may be surmised that those with infections receive
antibiotic treatments. From this we might infer that there
may be a causal relationship between these exposures and
later intolerances that manifest as multisystem symptoms
which wax and wane in response to subsequent chemical,
food, and drug exposures. Future research should explore
the mechanism by which exposures and/or alterations in
the gut microbiome may compromise our ancient mast
cells and innate cell-mediated tolerance. Allergy and toxi-
cology as currently practiced appear to have overlooked
the two steps of TILT and the fact that toxic exposures
can sensitize mast cells.
Chemically intolerant individuals have few proven
treatment options other than avoiding exposures that
initiate and continue to trigger their symptoms. Many
remain on restrictive elimination diets for years. Pre- and
probiotics offer a potentially attractive option. In our
most recent study, we demonstrated that nearly 60% of
patients diagnosed with mast cell activation syndrome
(MCAS) met QEESI criteria for CI. is suggests that
therapies used to treat MCAS may also be useful for
treating CI/TILT, e.g., medications like cromolyn which
prevent mast cell degranulation and/or H1 and H2 anti-
histamines which block the action of histamine released
by mast cells on tissues [80, 83, 118].
Implications forfuture research
Our large population-based surveys have identified many
of the most frequently cited CI/TILT initiating exposures.
All of these exposures except for mold involve fossil fuels,
their combustion products and/or their synthetic chemi-
cal derivatives. Key culprits in both cases—VOCs from
mold and fossil fuels—appear to involve low molecular
weight VOCs such as terpenes in fragrances or short
chain volatiles released by molds identified by [122].
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 15 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
Further studies should address the following research
questions, which we believe to be high yield:
(1) Are fossil fuels exposures sensitizing our ancient
immune systems’ first responders, that is, mast
cells? (TILT Stage l, Initiation)
(2) Do sensitized mast cells release cascades of media-
tors (histamine, cytokines) when they subsequently
encounter structurally unrelated xenobiotics, for
example, nanograms of inhaled VOCs, or foods/
food additives in the GI tract? (TILT Stage 2, Trig-
gering).
Practical interventions for patients suspected of hav-
ing TILT now involve: (1) explaining to them, their fami-
lies, landlords and employers that they are now sensitive
to tiny quantities of particles and VOCs which may arise
from biological sources (mold, algae) or from fossil fuels,
their combustion products or synthetic chemical deriva-
tives and (2) discussing how these might be eliminated
from their home, school, and work environments (e.g.,
no exposure to fragrances, combustion products, no
attached garages, etc.). Living with restrictions like these
is a daunting challenge. Consequently, we recommend
that public health measures and medical counseling
should include recommendations to reduce or avoid ini-
tiating exposures as the first order of business.
One in four primary care patients suffers from MUS.
Doctors in primary care, neurology, psychiatry, psychol-
ogy, occupational medicine, and allergy/immunology
would be well-advised to incorporate the QEESI and an
individualized exposure history in their evaluation of
patients with MUS as well as those diagnosed with con-
ditions of unknown etiology such as myalgic encephalo-
myelitis/chronic fatigue syndrome (ME/CFS), asthma,
fibromyalgia, autism, ADHD, depression or other psy-
chological conditions. None of these are etiologic diag-
noses; CI and TILT are etiologic diagnoses. Practitioners
should not presume that any illness is psychosomatic
without exploring environmental initiators and triggers.
ey need to screen all patients using the BREESI/QEESI
and learn about CI and TILT. e GI tract is densely pop-
ulated with mast cells, and digestive difficulties and food
intolerances are prevalent in CI.e role of contempo-
rary exposures in initiating and exacerbating these con-
ditions via mast cell sensitization needs our immediate
attention.Mast cells evolved over 500 million years ago.
In contrast, our exposures to fossil fuels and combustion
products are new since the Industrial Revolution (less
than 300years ago), while exposures to fossil fuel-derived
synthetic chemicals have grown exponentially in recent
generations since WWII—less than 100years ago. Fos-
sil fuels are assaulting humans and other animal species
both from within via mast cell sensitization, and from
without via climate change.
Strengths andlimitations
e considerable number of randomly sampled sur-
vey participants (n > 10,000) is a strength of this study.
It improves the generalizability of our findings and
enhances our ability to understand the prevalence of CI
across the U.S. and across genders and age groups. It also
improves our understanding of exposures that may initi-
ate CI/TILT, thus extending our prior work, which was
limited to previously published case reports and others’
studies that were not population-based [72].
Also, the application of multivariate statistical methods
expands our understanding of the relative roles of vari-
ous xenobiotics in CI/TILT initiation, representing a step
forward in the literature. Lastly, our search for the under-
lying causes of CI represents a much-needed addition to
the CI/TILT literature whose principal focus has been on
so-called “triggers” that elicit CI symptoms from day-to-
day with no attempt to determine what initiated TILT.
is study also has important limitations. First, we
should note that event-driven analyses remain an inher-
ently more reliable indicator of what initiates CI/TILT.
However, in the absence of large cohorts who developed
TILT following well-characterized exposure events, the
use of population-based surveys, as employed in this
study, represents a valuable alternative for understand-
ing what initiates or truly underlies CI/TILT. Of note,
our findings mirror decades of observations in countries
on five continents by many thousands of patients, physi-
cians, and public health practitioners.
An additional limitation is that only about half of those
with positive QEESI screens recalled a specific expo-
sure that may have initiated their symptoms. However,
given the exponential increase in exposures to toxicants
derived from fossil fuels and biological sources, coupled
with reduced fresh air in buildings due to energy con-
servation efforts spurred by the 1973 Arab oil embargo,
TILT has become epidemic.
Another potential limitation is the absence of race/
ethnicity data for our participants, which prevents any
comparison of CI prevalence across different minority
populations. Although this analysis includes a diverse
survey population and substantial numbers of partici-
pants, we cannot rule out the possibility of selection
bias. us, it is useful to discuss the ways in which such
bias may have entered our study as well as its implica-
tions for our findings. Given that the completion of our
survey on a computer required active engagement and
therefore a minimum level of health and wellbeing, it
is likely that our survey under-sampled individuals
most affected by CI/TILT. Importantly, however, this
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 16 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
“healthy participant effect” (analogous to the healthy
worker effect) would tend to bias our results in the
direction of making our estimates of CI prevalence
overly conservative.
Such bias may have been more pronounced among
elderly survey participants, which may partly explain the
reduced prevalence of CI reported in this age group. Lack
of access to the Internet, a computer, or a smartphone, as
well as language limitations, also may have reduced the
generalizability of our findings across low-income and
minority populations. Lastly, a potential limitation inher-
ent in health-related surveys is so-called “recall bias”, in
which individuals most afflicted by an illness are more
apt to recall and report exposure-related details.
Conclusion
Using the internationally validated QEESI in a survey
of over 10,000 U.S. adults, we were able to document a
20% prevalence of CI, half of whom attributed onset of
their illness to an initiating exposure event or multiple
events. A lifetime history of protracted courses of anti-
biotics also was associated with CI/TILT, as were specific
prostate, skin, tonsil, gastrointestinal tract, and sinus-
related antibiotic uses. e initiating exposures most
frequently reported to be associated with CI/TILT were
mold, remodeling/new construction, medical/surgical
procedures, and pesticides, while combustion products,
implants, and others were less frequently reported. Initi-
ating events with the highest odds ratios included pesti-
cides, breast implants, mold, and combustion exposures,
followed in order by remodeling/new construction and
surgical/medical procedures. Overall, woman tended
to score higher on the QEESI than did men. is study
elucidates the types of exposure events that may initiate
CI/TILT, thereby providing useful insights into the ways
in which populations, including sensitive subgroups, can
avoid TILT in the future. Although certain exposures
such as medical/surgical procedures may be difficult to
avoid, reducing exposures to contaminants related to
pesticide use, new construction/remodeling, and mold
is possible and should be the focus of efforts to prevent
future CI/TILT. e fact that many patients report TILT
initiated by various drugs, implants, and surgical proce-
dures makes it important that all patients be screened for
CI using the BREESI/QEESI and whenever feasible, that
individual susceptibility be considered prior to medical
or surgical interventions.
Acknowledgements
We thank the Marilyn Brachman Hoffman Foundation for generously funding
this study and Marilyn Hoffman for her prescient bequest prioritizing research
on Toxicant-Induced Loss of Tolerance. We are deeply grateful to the patients
who participated in this groundbreaking study.
Author contributions
CSM and RFP: conception and design of this work. All authors contributed to
the survey design and DK was responsible for data acquisition. RFP and DK
were responsible for the data analysis and interpretation as well as the first
draft. Subsequent editing of the drafts was done by SM, NA, RR, RP, CG and
DRS. CSM and RFP were responsible for final revisions of the work. All the
authors read and approved the final manuscript.
Funding
This research was funded by the Marilyn Brachman Hoffman Foundation, Fort
Worth, TX.
Availability of data and materials
The dataset analyzed during the current study is available from the corre-
sponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Institutional Review Board Statement: the study was conducted according to
the guidelines of the Declaration of Helsinki and approved by the University of
Texas Health Science Center San Antonio Institutional Review Board (Approval
Number HSC20200718N). Written informed consent was waived due to com-
pletely anonymous volunteer participation.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests associated with this manuscript.
The funders had no role in the design of the study, in the collection, analysis,
or interpretation of data, in the writing of the manuscript, or in the decision to
publish the results.
Author details
1 University of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio,
TX 78229, USA. 2 Hayward Score, Carmel, CA, USA. 3 Department of Envi-
ronmental and Occupational Health, Program in Public Health, University
of California- Irvine, Irvine, CA, USA. 4 Massachusetts Institute of Technology,
Cambridge, MA, USA.
Received: 7 February 2023 Accepted: 28 July 2023
References
1. Abou-donia MB, Lieberman A, Curtis L (2018) Neural autoantibodies in
patients with neurological symptoms and histories of chemical/mold
exposures. Toxicol Ind Health 34(1):44–53. https:// doi. org/ 10. 1177/
07482 33717 733852
2. Ashford NA, Miller CS (1998) Low-level chemical exposures: a challenge
for science and policy. Environ Sci Technol 32(21):508A
3. Ashford N, Heinzow B, Lütjen K, Marouli C, Mølhave L, Mönch B,
Papadopoulos S, Rest K, Rosdahl D, Siskos P, Velonakis E (1995) Chemi-
cal sensitivity in selected european countries: an exploratory study. A
Report to the European Commission, Athens
4. Ashford N, Miller C (1998) Chemical exposures: low levels and high
stakes. Wiley, Hoboken
5. Azuma K, Uchiyama I, Katoh T, Ogata H, Arashidani K, Kunugita N (2015)
Prevalence and characteristics of chemical intolerance: a Japanese
population-based study. Arch Environ Occup Health 70(6):341–353.
https:// doi. org/ 10. 1080/ 19338 244. 2014. 926855
6. Bajwa U, Sandhu KS (2014) Effect of handling and processing on
pesticide residues in food- a review. J Food Sci Technol 51(2):201–220.
https:// doi. org/ 10. 1007/ s13197- 011- 0499-5
7. Bell IR (1996) Clinically relevant EEG studies and psychophysiological
findings: possible neural mechanisms for multiple chemical sensitivity.
Toxicology 111(1–3):101–117. https:// doi. org/ 10. 1016/ 0300- 483X(96)
03395-1
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 17 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
8. Bell IR, Rossi J, Gilbert ME, Kobal G, Morrow LA, Newlin DB, Sorg BA,
Wood RW (1997) Testing the neural sensitization and kindling hypoth-
esis for illness from low levels of environmental chemicals. Environ
Health Perspect 105(SUPPL. 2):539–547. https:// doi. org/ 10. 1289/ ehp.
97105 s2539
9. Bell IR, Miller CS, Schwartz GE (1992) An olfactory-limbic model of mul-
tiple chemical sensitivity syndrome: possible relationships to kindling
and affective spectrum disorders. Biol Psychiatry. 32(3):218–242. https://
doi. org/ 10. 1016/ 0006- 3223(92) 90105-9
10. Bennett JW, Inamdar AA (2015) Are some fungal volatile organic com-
pounds (VOCs) mycotoxins? Toxins 7(9):3785–3804. https:// doi. org/ 10.
3390/ toxin s7093 785
11. Biffignandi S, Bethlehem J (2021) Handbook of web surveys. Wiley,
Hoboken
12. Borody TJ, Nowak A, Finlayson S (2012) The GI microbiome and its role
in chronic fatigue syndrome: a summary of bacteriotherapy. J Australas
Coll Nutr Environ Med 31(3):3–8
13. Bowler RP, Crapo JD (2002) Oxidative stress in allergic respiratory dis-
eases. J Allergy Clin Immunol 110(3):349–356. https:// doi. org/ 10. 1067/
mai. 2002. 126780
14. Brautbar N, Campbell A (1995) Silicone implants and immune dysfunc-
tion—scientific evidence for causation. Int J Occup Med Tox 4:3–13
15. Brautbar N, Vojdani A, Campbell AW (1992) Multiple chemical sensitivi-
ties—fact or myth. Toxicol Ind Health 8:5–8
16. Brautbar N, Vojdani A, Campbell A (1994) Silicone breast implants and
autoimmunity: causation or myth? Arch Environ Health 49(3):151–153.
https:// doi. org/ 10. 1080/ 00039 896. 1994. 99403 73
17. Brown-DeGagne A-M, McGlone J (1999) Multiple chemical sensitivity: a
test of the olfactory-limbic model. J Occup Environ Med 41(5):366–377
18. Bunegin L, Mitzel HC, Miller CS, Gelineau JF (2001) Cognitive perfor-
mance and cerebrohemodynamics associated with the Persian Gulf
Syndrome. Toxicol Ind Health. https:// doi. org/ 10. 1191/ 07482 33701
th100 oa
19. Andrew W. Campbell, Jack D. Thrasher, Roberta A. Madison, Aristo
Vojdani, Michael R. Gray, Al Johnson (2003) Neural autoantibodies and
neurophysiologic abnormalities in patients exposed to molds in water-
damaged buildings. Arch Environ Health: Int J 58(8):464–474. https://
doi. org/ 10. 3200/ AEOH. 58.8. 464- 474
20. Caress SM, Steinemann AC (2004) Prevalence of multiple chemical sen-
sitivities: a population-based study in the Southeastern United States.
Am J Public Health 94(5):746–747. https:// doi. org/ 10. 2105/ AJPH. 94.5.
746
21. Chelombitko MA, Fedorov AVI, Ilyinskaya OP et al (2016) Role of reac-
tive oxygen species in mast cell degranulation. Biochem Moscow
81:1564–1577. https:// doi. org/ 10. 1134/ S0006 29791 61201 8X
22. Chiu K, Warner G, Nowak RA, Flaws JA, Mei W (2020) The impact of envi-
ronmental chemicals on the gut microbiome. Toxicol Sci 176(2):253–
284. https:// doi. org/ 10. 1093/ toxsci/ kfaa0 65
23. Cone JE, Sult TA (1992) Acquired intolerance to solvents following pes-
ticide/solvent exposure in a building: a new group of workers at risk for
multiple chemical sensitivities? Toxicol Ind Health 8(4):29–39. https://
doi. org/ 10. 1177/ 07482 33792 00800 404
24. Costa LG, Cole TB, Vitalone A, Furlong CE (2005) Measurement of
paraoxonase (PON1) status as a potential biomarker of susceptibility to
organophosphate toxicity. Clin Chim Acta 352(1–2):37–47
25. Couper M (2000) Web surveys: a review of issues and approaches.
Public Opin Q 64(4):464–494
26. Cryan JF, O’Riordan KJ, Sandhu K, Peterson V, Dinan TG (2020) The gut
microbiome in neurological disorders. Lancet Neurol 19(2):179–194.
https:// doi. org/ 10. 1016/ S1474- 4422(19) 30356-4
27. Cui X, Lu X, Hiura M, Oda M, Hisada A, Miyazaki W, Omori H, Katoh
T (2014) Prevalence and interannual changes in multiple chemical
sensitivity in Japanese workers. Environ Health Prev Med 19(3):215–219.
https:// doi. org/ 10. 1007/ s12199- 014- 0378-6
28. Cullen MR (1987) The worker with multiple chemical sensitivities: an
overview. Occup Med 2(4):655–662
29. Damiani G, Alessandrini M, Caccamo D, Cormano A, Guzzi G, Maz-
zatenta A, Micarelli A, Migliore A, Piroli A, Bianca M, Tapparo O, Pigatto
PDM (2021) Italian expert consensus on clinical and therapeutic man-
agement of multiple chemical sensitivity (MCS). Int J Environ Res Public
Health 18(21):1–19. https:// doi. org/ 10. 3390/ ijerp h1821 11294
30. Duprey Z, Rivers S, Luber G, Becker A, Barr D, Weerasekera G, Kieszak S,
Dana W, Rubin C, Blackmore C, Barr D, Weerasekera G, Kieszak S, Flan-
ders WD, Rubin C (2008) Community aerial mosquito control and Naled
exposure. J Am Mosq Control Assoc 24(1):42–46
31. Fang B, Li JW, Zhang M, Ren FZ, Pang GF (2018) Chronic chlorpyrifos
exposure elicits diet-specific effects on metabolism and the gut micro-
biome in rats. Food Chem Toxicol 111:144–152
32. Fitzgerald DJ (2008) Studies on self-reported multiple chemical sensitiv-
ity in South Australia. Environ Health 8(3):33–39
33. Fink AL, Klein SL (2018) The evolution of greater humoral immunity in
females than males: implications for vaccine efficacy. Curr Opin Physiol.
6–20. https:// doi. org/ 10. 1016/j. cophys. 2018. 03. 010. Epub 2018 Mar 29.
PMID: 30320243; PMCID: PMC6181235
34. Forsythe P. (2015) The parasympathetic nervous system as a regulator
of mast cell function. Methods Mol Biol;1220:141–154. https:// doi. org/
10. 1007/ 978-1- 4939- 1568-2_9MID: 25388249
35. Fukuda K, Nisenbaum R, Stewart G, Thompson W, Robin L, Washko R,
Noah D, Barrett D, Randall B, Herwaldt B, Mawle A, Reeves W (1998)
Chronic Multisymptom illness affecting air force veterans of the Gulf
War. J Am Med Assoc 280:981–988
36. Furlong CE (2000) PON1 status and neurologic symptom complexes in
Gulf War veterans. Genome Res 10(2):153–155. https:// doi. org/ 10. 1101/
gr. 10.2. 153
37. Gangi S, Johansson O (2000) A theoretical model based upon mast cells
and histamine to explain the recently proclaimed sensitivity to electric
and/or magnetic fields in humans. Med Hypotheses 54(4):663–671.
https:// doi. org/ 10. 1054/ mehy. 1999. 0923
38. Genuis SJ (2010) Sensitivity-related illness: the escalating pandemic
of allergy, food intolerance and chemical sensitivity. Sci Total Environ
408(24):6047–6061. https:// doi. org/ 10. 1016/j. scito tenv. 2010. 08. 047
39. Gibson PR, Vogel VM (2008) Sickness-related dysfunction in persons
with self-reported multiple chemical sensitivity at four levels of severity.
J Clin Nurs 18(1):72–81
40. Glinton GJ (2005) Multiple-chemical sensitivity. Medsurg Nurs
14(6):365–369
41. Golomb BA (2008) Acetylcholinesterase inhibitors and Gulf War ill-
nesses. Proc Natl Acad Sci USA 105(11):4295–4300. https:// doi. org/ 10.
1073/ pnas. 07119 86105
42. Gotman I (1997) Characteristics of metals used in implants. J Endourol
11(6):383–389
43. Gould Peek G, Wallace Lyon M (2014) Housing and health relationship:
multiple chemical sensitivity (MCS). Hous Soc 41(1):31–52. https:// doi.
org/ 10. 1080/ 08882 746. 2014. 11430 620
44. Gray MR, Thrasher JD, Crago R, Madison RA, Arnold L, Campbell AW,
Vojdani A (2003) Mixed mold mycotoxicosis: Immunological changes in
humans following exposure in water-damaged buildings. Arch Environ
Health 58:410–420
45. Han M, Lee D, Lee S, Kim TH (2021) Oxidative stress and antioxidant
pathway in allergic rhinitis. Antioxidants 10(8):1266
46. Heo Y, Kim SH, Lee SK, Kim HA (2017) Factors contributing to the self-
reported prevalence of multiple chemical sensitivity in public facility
workers and the general population of Korea. J UOEH 39(4):249–258.
https:// doi. org/ 10. 7888/ juoeh. 39. 249
47. Hess J, Bednarz D, Bae J, Pierce J (2011) Petroleum and health care:
Evaluating and managing health care’s vulnerability to petroleum
supply shifts. Am J Public Health 101(9):1568–1579. https:// doi. org/ 10.
2105/ AJPH. 2011. 300233
48. Heuser G (2000) Mast cell disorder to be ruled out in MCS. Arch Environ
Health 55(4):284–285
49. Heuser G, Kent P (1996) Mast cell disorder after chemical exposure.
124th Annual Meeting. Am Public Health Assoc, New York
50. Hilborne L, Golomb B, Marshall G, Davis L, Sherbourne C, Augerson
W, Spektor D, Harley N, Foulkes E, Hudson A, Anthony C, Cecchine G,
Marlowe D, Rettig R, Fricker R, Reardon E, Cotton S, Hawes-Dawson J,
Pace J, Hosek S (2020) Examining possible causes of Gulf War illness:
RAND policy investigations and reviews of the scientific literature.
RAND Corporation, Santa Monica. https:// doi. org/ 10. 7249/ rb7544
51. Hirzy JW, Morison R (1991) Carpet/4-phenylcyclohexene toxicity: the
EPA headquarters case. Anal Commun Percept Risk . https:// doi. org/ 10.
1007/ 978-1- 4899- 2370-7
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 18 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
52. Hojo S, Kumano H, Yoshino H, Kakuta K, Ishikawa S (2003) Application of
quick environment exposure sensitivity inventory (QEESI©) for Japanese
population: study of reliability and validity of the questionnaire. Toxicol
Ind Health 19(6):41–49. https:// doi. org/ 10. 1191/ 07482 33703 th180 oa
53. Hojo S, Mizukoshi A, Azuma K, Okumura J, Ishikawa S, Miyata M, Mizuki
M, Ogura H, Sakabe K (2018) Survey on changes in subjective symp-
toms, onset-trigger factors, allergic diseases, and chemical exposures in
the past decade of Japanese patients with multiple chemical sensitivity.
Int J Hyg Environ Health 221:1085–1096
54. Hutton Carlsen K, Topp AM, Skovbjerg S (2012) Living with a chemically
sensitive wife: a “We” situation. ISRN Public Health 2012:1–6. https:// doi.
org/ 10. 5402/ 2012/ 285623
55. Inamdar AA, Hossain MM, Bernstein AI, Miller GW, Richardson JR, Bennett
JW (2013) Fungal-derived semiochemical 1-octen-3-ol disrupts dopa-
mine packaging and causes neurodegeneration. Proc Natl Acad Sci USA
110(48):19561–19566. https:// doi. org/ 10. 1073/ pnas. 13188 30110
56. Inamdar AA, Masurekar P, Bennett JW (2010) Neurotoxicity of fungal
volatile organic compounds in Drosophila melanogaster. Toxicol Sci
117(2):418–426. https:// doi. org/ 10. 1093/ toxsci/ kfq222
57. Israeli E, Pardo A (2011) The sick building syndrome as a part of
the autoimmune (auto-inflammatory) syndrome induced by
adjuvants. Mod Rheumatol 21:235–239. https:// doi. org/ 10. 3109/
s10165- 010- 0380-9
58. Jaenson TGT, Hjertqvist M, Bergström T, Lundkvist Å (2012) Why is tick-
borne encephalitis increasing? A review of the key factors causing the
increasing incidence of human TBE in Sweden. Parasit Vectors 5(1):1–13.
https:// doi. org/ 10. 1186/ 1756- 3305-5- 184
59. Jansen K, Cole T, Park S, Furlong C, Costa L (2009) Paraoxonase 1 (PON1)
modulates the toxicity of mixed organophosphorus compounds. Toxi-
col Appl Pharmacol 236(2):1–26. https:// doi. org/ 10. 1016/j. taap. 2009. 02.
001. Parao xonase
60. Jeon B-H, Lee S-H, Kim H-A (2012) A validation of the Korean version of
QEESI© (The quick environmental exposure and sensitivity inventory).
Korean J Occup Environ Med 24(1):96. https:// doi. org/ 10. 35371/ kjoem.
2012. 24.1. 96
61. JMP® (1989) JMP, Version 15
62. Johansson O, Gangi S, Liang Y, Yoshimura K, Jing C, Liu P-Y (2002) Cuta-
neous mast cells are altered in normal healthy volunteers sitting in front
of ordinary TVs/PCs—results from open-field provocation experiments.
J Cutan Pathol 28(10):513–519
63. Karvala K, Sainio M, Palmquist E, Nyback MH, Nordin S (2018) Prevalence
of various environmental intolerances in a Swedish and Finnish general
population. Environ Res 161(July 2017):220–228. https:// doi. org/ 10.
1016/j. envres. 2017. 11. 014
64. Kilburn KH (2009) Neurobehavioral and pulmonary impairment in 105
adults with indoor exposure to molds compared to 100 exposed to
chemicals. Toxicol Ind Health 25(10):681–692. https:// doi. org/ 10. 1177/
07482 33709 348390
65. Korpi A, Järnberg J, Pasanen AL (2009) Microbial volatile organic com-
pounds. Crit Rev Toxicol 39(2):139–193. https:// doi. org/ 10. 1080/ 10408
44080 22914 97
66. Kreutzer R, Neutra RR, Lashuay N (1999) Prevalence of people reporting
sensitivities to chemicals in a population-based survey. Am J Epidemiol
150(1):1–12. https:// doi. org/ 10. 1126/ scien ce.4. 80. 55
67. Li JW, Fang B, Pang GF, Zhang M, Ren FZ (2019) Age- and diet-specific
effects of chronic exposure to chlorpyrifos on hormones, inflammation
and gut microbiota in rats. Pestic Biochem Physiol 159:68–79. https://
doi. org/ 10. 1016/j. pestbp. 2019. 05. 018
68. Lindsberg PJ, Strbian D, Karjalainen-Lindsberg ML (2010) Mast cells as
early responders in the regulation of acute blood-brain barrier changes
after cerebral ischemia and hemorrhage. J Cereb Blood Flow Metab
30(4):689–702. https:// doi. org/ 10. 1038/ jcbfm. 2009. 282
69. Livingston EH (2017) Safety of aerial pesticide spraying for mosquitoes.
J Am Med Assoc 310(3):333
70. Madden JAJ, Hunter JO (2002) A review of the role of the gut microflora
in irritable bowel syndrome and the effects of probiotics. Br J Nutr
88(S1):s67–s72. https:// doi. org/ 10. 1079/ bjn20 02631
71. Mann ME, Emanuel KA (2006) Atlantic hurricane trends linked to cli-
mate change. Eos 87(24):233–241. https:// doi. org/ 10. 1029/ 2006E O2400
01
72. Masri S, Miller CS, Palmer RF, Ashford N (2021) Toxicant-induced loss
of tolerance for chemicals, foods, and drugs: assessing patterns of expo-
sure behind a global phenomenon. Environ Sci Europe. https:// doi. org/
10. 1186/ s12302- 021- 00504-z
73. McMichael AJ, Woodruff RE, Hales S (2006) Climate change and human
health: present and future risks. Lancet 367(9513):859–869. https:// doi.
org/ 10. 1016/ S0140- 6736(06) 68079-3
74. Michaelis S, Burdon J, Howard C (2017) Aerotoxic syndrome: a new
occupational disease? Public Health Panorama 03(02):198–211
75. Miller CS. (1996) Chemical sensitivity: symptom, syndrome or mecha-
nism for disease? Toxicology 111(1-3):69–86. https:// doi. org/ 10. 1016/
0300- 483x(96) 03393-8. PMID: 8711750
76. Miller CS (1997) Toxicant-induced loss of tolerance--an emerging the-
ory of disease? Environ Health Perspect 105 (Suppl 2):445-453. https://
doi. org/ 10. 1289/ ehp. 97105 s2445. PMID: 9167978; PMCID: PMC1469811
77. Miller C, Mitzel H (1995) Chemical sensitivity attributed to pesticide
exposure versus remodeling. Arch Environ Health 50(2):119–129
78. Miller CS (2000) Toxicant-induced loss of tolerance. Addiction. https://
doi. org/ 10. 1080/ 09652 14002 00170 03
79. Miller CS, Ashford N (1995) Chemical sensitivity: perspectives from
North America and Europe. 1–19
80. Miller CS, Palmer RF, Dempsey TT, Ashford NA, Afrin LB (2021) Mast cell
activation may explain many cases of chemical intolerance. Environ Sci
Europe. https:// doi. org/ 10. 1186/ s12302- 021- 00570-3
81. Miller CS, Prihoda TJ (1999) A controlled comparison of symptoms and
chemical intolerances reported by Gulf War veterans, implant recipients
and persons with multiple chemical sensitivity. Toxicol Ind Health. 15(3-
4):386–397. https:// doi. org/ 10. 1177/ 07482 33799 01500 312
82. Miller CS, Prihoda TJ (1999) The environmental exposure and sensitivity
inventory (EESI): a standardized approach for measuring chemical
intolerances for research and clinical applications. Toxicol Ind Health
15(4):370–385. https:// doi. org/ 10. 1177/ 07482 33799 01500 311
83. Molderings GJ, Haenisch B, Brettner S, Homann J, Menzen M, Dumoulin
FL, Panse J, Butterfield J, Afrin LB (2016) Pharmacological treatment
options for mast cell activation disease. Naunyn-Schmiedeberg’s Arch
Pharmacol 389(7):671–694. https:// doi. org/ 10. 1007/ s00210- 016- 1247-1
84. National Federation of Federal Employees (1989) Indoor Air Quality and
Work Environment Study
85. Nynäs P, Vilpas S, Kankare E, Karjalainen J, Lehtimäki L, Numminen J,
Tikkakoski A, Kleemola L, Uitti J (2021) Clinical findings among patients
with respiratory symptoms related to moisture damage exposure at the
workplace—the samdaw study. Healthcare. https:// doi. org/ 10. 3390/
healt hcare 90911 12
86. Pall ML (2002) NMDA sensitization and stimulation by peroxynitrite,
nitric oxide, and organic solvents as the mechanism of chemical sensi-
tivity in multiple chemical sensitivity. FASEB J 16(11):1407–1417. https://
doi. org/ 10. 1096/ . 01- 0861h yp
87. Palmer RF, Jaén CR, Perales RB, Rincon R, Forster JN, Miller CS (2020)
Three questions for identifying chemically intolerant individuals in clini-
cal and epidemiological populations: the brief environmental exposure
and sensitivity inventory (BREESI). PLoS ONE 15(9 September):1–10.
https:// doi. org/ 10. 1371/ journ al. pone. 02382 96
88. Park SW, Choi J, Park HO, Lim YS, Lee KS, Kim NG, Kim JS (2004) Are gen-
der differences in external noses caused by differences in nasal septal
growth? J Cranio-Maxillo-Facial Surgery 42:11401147
89. Palmer RF, Walker T, Kattari D, Rincon R, Perales RB, Jaén CR, Grimes C,
Sundblad DR, Miller CS (2021) Validation of a brief screening instrument
for chemical intolerance in a large U.S. national sample. Int J Environ
Res Public Health 18(16):8714. https:// doi. org/ 10. 3390/ ijerp h1816 8714.
PMID: 34444461; PMCID: PMC8391803
90. Proctor C, Thiennimitr P, Chattipakorn N, Chattipakorn SC (2017) Diet,
gut microbiota and cognition. Metab Brain Dis 32(1):1–17. https:// doi.
org/ 10. 1007/ s11011- 016- 9917-8
91. Proctor SP (2000) Chemical sensitivity and gulf war veterans’ illnesses.
Occup Med 15(3):587–599
92. Rajkovic V, Matavulj M, Johansson O (2005) Histological characteristics
of cutaneous and thyroid mast cell populations in male rats exposed to
power-frequency electromagnetic fields. Int J Radiat Biol 81(7):491–499
93. Rajkovic V, Matavulj M, Johansson O (2010) Combined exposure of
peripubertal male rats to the endocrine-disrupting compound atrazine
and power-frequency electromagnetic fields causes degranulation of
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 19 of 19
Milleretal. Environmental Sciences Europe (2023) 35:65
cutaneous mast cells: a new toxic environmental hazard? Arch Environ
Contam Toxicol 59:334–341
94. Ramirez J, Guarner F, Bustos Fernandez L, Maruy A, Sdepanian VL,
Cohen H (2020) Antibiotics as major disruptors of gut microbiota. Front
Cell Infect Microbiol 10(November):1–10. https:// doi. org/ 10. 3389/ fcimb.
2020. 572912
95. Ranneh Y, Ali F, Akim AM et al (2017) Crosstalk between reactive oxygen
species and pro-inflammatory markers in developing various chronic
diseases: a review. Appl Biol Chem 60:327–338. https:// doi. org/ 10. 1007/
s13765- 017- 0285-9
96. Research Advisory Committee on Gulf War Veterans’ Illness (2008) Gulf
War Illness and the Health of Gulf War Veterans: Scientific Findings and
Recommendations
97. Rossi S, Pitidis A (2018) Multiple chemical sensitivity: review of the state
of the art in epidemiology, diagnosis, and future perspectives. J Occup
Environ Med 60(2):138–146. https:// doi. org/ 10. 1097/ JOM. 00000 00000
001215
98. SAS® (2014) SAS, 9.4, Third Edition
99. Schovsbo SU, Møllehave LT, Petersen MW, Ahrendt Bjerregaard A,
Eliasen M, Pedersen SB, Eplov LF, Kårhus LL, Fink P, Linneberg A, Dantoft
TM, Jørgensen T, Benros ME (2022) Association between infections and
functional somatic disorders: a cross-sectional population-based cohort
study. BMJ Open 12(11):e066037. https:// doi. org/ 10. 1136/ bmjop
en- 2022- 066037
100. Shoenfeld Y, Ryabkov VA, Scheibenbogen C, Brinth L, Martinez-Lavin
M, Ikeda S, Heidecke H, Watada A, Bragazzi NL, Chapman J, Churilov LP,
Amital H (2020) Complex syndromes of chronic pain, fatigue and cogni-
tive impairment linked to autoimmune autoimmune dysautonomia
and small fiber neuropathy. Clin Immunol 214:1–11
101. Skovbjerg S, Berg ND, Elberling J, Christensen KB (2012) Evaluation of
the quick environmental exposure and sensitivity inventory in a Danish
population. J Environ Public Health. https:// doi. org/ 10. 1155/ 2012/
304314
102. Steele L (2000) Prevalence and patterns of Gulf War illness in Kansas
veterans: association of symptoms with characteristics of person, place,
and time of military service. Am J Epidemiol 152(10):992–1002. https://
doi. org/ 10. 1093/ aje/ 152. 10. 992
103. Steinemann A (2018) National prevalence and effects of multiple
chemical sensitivities. J Occup Environ Med 60(3):e152–e156. https://
doi. org/ 10. 1097/ JOM. 00000 00000 001272
104. Syromyatnikov MY, Isuwa MM, Savinkova OV, Derevshchikova MI, Popov
VN (2020) The effect of pesticides on the microbiome of animals. Agri-
culture 10(3):1–14. https:// doi. org/ 10. 3390/ agric ultur e1003 0079
105. Tuuminen T (2020) The roles of autoimmunity and biotoxicosis in sick
building syndrome as a “Starting Point” for irreversible dampness and
mold hypersensitivity syndrome. Antibodies 9(2):26. https:// doi. org/ 10.
3390/ antib 90200 26
106. Tuuminen T, Rinne KS (2017) Severe sequelae to mold-related illness
as demonstrated in two Finnish cohorts. Front Immunol 8(APR):1–9.
https:// doi. org/ 10. 3389/ fimmu. 2017. 00382
107. Unwin C, Blatchley N, Coker W, Ferry S, Hotopf M, Hull L, Ismail K, Palmer
I, David A, Wessely S (1999) Health of UK servicemen who served in
Persian Gulf War. Lancet 353:169–178
108. Valtonen V (2017) Clinical diagnosis of the dampness and mold hyper-
sensitivity syndrome: review of the literature and suggested diagnostic
criteria. Front Immunol 8(1):1–6. https:// doi. org/ 10. 3389/ fimmu. 2017.
00951
109. Vanderhoof JA, Young RJ (2003) Role of probiotics in the management of
patients with food allergy. Ann Allergy Asthma Immonol 90:99–103
110. der Varrt IB, Heath MD, Guagnini F, Kramer MF (2016) In vitro evidence
for efficacy in food intolerance for the multispecies probiotic formula-
tion Ecologic. Beneficial Microbes 7(1):111–118
111. Vojdani A, Campbell A, Brautbar N (1992) Immune functional impair-
ment in patients with clinical abnormalities and silicone breast
implants. Toxicol Ind Health 8(6):415–429. https:// doi. org/ 10. 1177/
07482 33792 00800 606
112. Vuokko A, Karvala K, Lampi J, Keski-Nisula L, Pasanen M, Voutilainen R,
Pekkanen J, Sainio M (2018) Environmental intolerance, symptoms and
disability among fertile-aged women. Int J Environ Res Public Health
15(2):1–12. https:// doi. org/ 10. 3390/ ijerp h1502 0293
113. Vuokko A, Karvala K, Suojalehto H, Lindholm H, Selinheimo S,
Heinonen-Guzejev M, Leppämäki S, Cederström S, Hublin C, Tuisku
K, Sainio M (2019) Clinical characteristics of disability in patients
with indoor air-related environmental intolerance. Saf Health Work
10(3):362–369. https:// doi. org/ 10. 1016/j. shaw. 2019. 06. 003
114. Wee CE, Younis J, Isbester K, Smith A, Wangler B, Sarode AL, Patil N,
Grunzweig K, Boas S, Harvey DJ, Kumar AR, Feng LJ (2020) Understand-
ing breast implant illness, before and after explantation: a patient-
reported outcomes study. Ann Plast Surg 85(S1):S82–S86. https:// doi.
org/ 10. 1097/ SAP. 00000 00000 002446
115. White R, Steele L, O’Callaghan J, Sullivan K, Binns J, Golomb B, Bloom
F, Bunker J, Crawford F, Graves J, Hardie A, Klimas N, Knox M, Meggs
W, Melling J, Philber M, Grashow R (2016) Recent research on Gulf War
illness and other health problems in veterans of the 1991 Gulf War:
Effects of toxicant exposures during deployment. Cortex. https:// doi.
org/ 10. 1016/j. cortex. 2015. 08. 022. Recent
116. Winder C (2000) Aerotoxic Syndrome : adverse health effects following
exposure to jet oil mist during commercial flights. Towards a safe and
civil society. Proceedings of the international congress on occupational
health conference, September, 4–6. https:// bleed free. eu/ wp- conte nt/
uploa ds/ 2015/ 08/ 07_ winder_ aerot oxic_ syndr ome- kopie. pdf
117. Winder C (2002) Mechanisms of multiple chemical sensitivity. Toxicol
Lett 128:85–97
118. Wirz S, Molderings GJ (2017) A practical guide for treatment of pain
in patients with systemic mast cell activation disease. Pain Physician
20(6):E849–E861. https:// doi. org/ 10. 36076/ ppj. 20.5. e849
119. Xiong S, Rodgers K (1997) Effects of malathion metabolites on degranu-
lation of and mediator release by human and rat basophilic cells. J
Toxicol Environ Health 51(2):159–175. https:// doi. org/ 10. 1080/ 00984
10970 89840 19
120. Zandman-Goddard G, Blank M, Ehrenfeld M, Gilburd B, Peter J, Shoe-
nfeld Y (1999) A comparison of autoantibody production in asympto-
matic and symptomatic women with silicone. J Rheumatol 26(1):73–77
121. Zhang Y, Jia Q, Hu C, Han M, Guo Q, Li S, Bo C, Zhang Y, Qi X, Sai L, Peng
C (2021) Effects of chlorpyrifos exposure on liver inflammation and intes-
tinal flora structure in mice. Toxicol Res 10(1):141–149. https:// doi. org/ 10.
1093/ toxres/ tfaa1 08
122. Zhao G, Yin G, Inamdar AA, Luo J, Zhang N, Yang I, Buckley B, Bennett
JW (2017) Volatile organic compounds emitted by filamentous fungi
isolated from flooded homes after Hurricane Sandy show toxicity in a
Drosophila bioassay. Indoor Air 27(3):518–528. https:// doi. org/ 10. 1111/
ina. 12350
123. Zhao Y, Zhang Y, Wang G, Han R, Xie X (2016) Effects of chlorpyrifos on
the gut microbiome and urine metabolome in mouse (Mus musculus).
Chemosphere 153:287–293
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub-
lished maps and institutional affiliations.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1.
2.
3.
4.
5.
6.
Terms and Conditions
Springer Nature journal content, brought to you courtesy of Springer Nature Customer Service Center GmbH (“Springer Nature”).
Springer Nature supports a reasonable amount of sharing of research papers by authors, subscribers and authorised users (“Users”), for small-
scale personal, non-commercial use provided that all copyright, trade and service marks and other proprietary notices are maintained. By
accessing, sharing, receiving or otherwise using the Springer Nature journal content you agree to these terms of use (“Terms”). For these
purposes, Springer Nature considers academic use (by researchers and students) to be non-commercial.
These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal
subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription
(to the extent of the conflict or ambiguity only). For Creative Commons-licensed articles, the terms of the Creative Commons license used will
apply.
We collect and use personal data to provide access to the Springer Nature journal content. We may also use these personal data internally within
ResearchGate and Springer Nature and as agreed share it, in an anonymised way, for purposes of tracking, analysis and reporting. We will not
otherwise disclose your personal data outside the ResearchGate or the Springer Nature group of companies unless we have your permission as
detailed in the Privacy Policy.
While Users may use the Springer Nature journal content for small scale, personal non-commercial use, it is important to note that Users may
not:
use such content for the purpose of providing other users with access on a regular or large scale basis or as a means to circumvent access
control;
use such content where to do so would be considered a criminal or statutory offence in any jurisdiction, or gives rise to civil liability, or is
otherwise unlawful;
falsely or misleadingly imply or suggest endorsement, approval , sponsorship, or association unless explicitly agreed to by Springer Nature in
writing;
use bots or other automated methods to access the content or redirect messages
override any security feature or exclusionary protocol; or
share the content in order to create substitute for Springer Nature products or services or a systematic database of Springer Nature journal
content.
In line with the restriction against commercial use, Springer Nature does not permit the creation of a product or service that creates revenue,
royalties, rent or income from our content or its inclusion as part of a paid for service or for other commercial gain. Springer Nature journal
content cannot be used for inter-library loans and librarians may not upload Springer Nature journal content on a large scale into their, or any
other, institutional repository.
These terms of use are reviewed regularly and may be amended at any time. Springer Nature is not obligated to publish any information or
content on this website and may remove it or features or functionality at our sole discretion, at any time with or without notice. Springer Nature
may revoke this licence to you at any time and remove access to any copies of the Springer Nature journal content which have been saved.
To the fullest extent permitted by law, Springer Nature makes no warranties, representations or guarantees to Users, either express or implied
with respect to the Springer nature journal content and all parties disclaim and waive any implied warranties or warranties imposed by law,
including merchantability or fitness for any particular purpose.
Please note that these rights do not automatically extend to content, data or other material published by Springer Nature that may be licensed
from third parties.
If you would like to use or distribute our Springer Nature journal content to a wider audience or on a regular basis or in any other manner not
expressly permitted by these Terms, please contact Springer Nature at
onlineservice@springernature.com