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Health cost that may be associated
with Endocrine Disrupting Chemicals

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An inventory, evaluation and way forward to assess the potential
socio-economic impact of EDC-associated health effects in the EU

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Ingrid Rijk, MSc
Dr. Majorie van Duursen, ERT
Prof. Dr. Martin van den Bercr, ERT

Health costs that may be associated
with Endocrine Disrupting Chemicals
An inventory, evaluation and way forward to assess the potential
socio-economic impact of EDC-associated health effects in the EU

Authors:
Ingrid Rijk, MSc
Dr. Majorie van Duursen, ERT
Prof. Dr. Martin van den Berg, ERT

©IRAS 2016

Final report d.d. April 11, 2016

Colofon

http://www.uu. nul RAS
ISBN: 978-90-393-6538-0

This report is commissioned by the Dutch Ministry of lnfrastructure and the Environment (lenM). On
request of the Ministry of lenM, the report has been prepared under guidance of Julia Verhoeven,
MSc and Dr. Betty Hakkert of the National Institute for Public Health and the Environment (RIVM).
The views expressed in this publication reflect the views of the authors (IR, MvD, MvdB). RIVM is not
responsible for the content of this report.

Contact:
Prof. Dr. Martin van den Berg, ERT
Dr. Majorie van Duursen, ERT

m.vandenberguu.nl
rn.vanduursen@uu.nl

Universiteit Utrecht
Institute for Risk Assessment Sciences (IRAS), Toxicology Division
Yalelaan 104, 3584 CM, Utrecht
P.O.Box 80.178, 3508 TD, Utrecht

2

Publiekssamenvatting
Er is steeds meer aandacht voor mogelijke gezondheidsschadelijke effecten door hormoon
verstorende stoffen. Dit rapport geeft een overzicht van ziektebeelden die in bestaande literatuur in
verband worden gebracht met blootstelling aan hormoonverstorende stoffen. Het resultaat is een
overzicht van meer dan 80 ziekten verdeeld over 6 categorieën. De auteurs hebben de bewijslast
rondom de link tussen ziekten en hormoonverstorende stoffen niet geëvalueerd. Wel wordt
geconstateerd dat dit een punt is van intensieve discussie. Vervolgens zijn eerder verschenen studies
vergeleken waarin de mogelijke kosten zijn berekend van ziekten door hormoonverstorende stoffen.
Ondanks verschillende benaderingen van deze studies, komen de kostenschattingen redelijk goed
overeen. Daarnaast zijn er aanvullende kosten voor 3 ziektebeelden in kaart gebracht, te weten
endometriose, neuraalbuisdefecten en astma. In totaal zijn kostenschattingen voor 16 van de ruim
80 ziektebeelden meegenomen. De totale schatting is dat blootstelling aan hormoonverstorende
stoffen mogelijk resulteert in zo’n 46-288 miljard € per jaar aan ziektekosten in Europa
(EU28). Er zijn echter veel onzekerheden rondom deze schatting, met name op het gebied van
causaliteit en berekening van kosten. In de ziektekostenschattingen zijn naast directe zorgkosten (bv.
behandelingen en medicijnen) ook indirecte kosten meegenomen (zoals productiviteitsverlies) en
voor sommige ziektebeelden immateriële schade (bv. verloren Ievensjaren). De kostenschatting
bestaat daarmee slechts voor een deel uit werkelijke kosten die gemaakt worden door de
maatschappij. De auteurs concluderen dat het belangrijk is een goed inzicht te krijgen in
ziektekostenopbouw om een vollediger inzicht te krijgen in de ziektekosten die mogelijk worden
veroorzaakt door hormoonverstorende stoffen. Hiervoor stellen ze een modulaire aanpak voor
waarmee kosten voor ontbrekende ziektebeelden kunnen worden aangevuld. In dit rapport wordt
deze modulaire aanpak voor een vijftal ziektebeelden geïllustreerd.
Dit rapport laat zien dat de ziektekosten in Europa door hormoonverstorende stoffen mogelijk
aanzienlijk kunnen zijn. Een beter inzicht in deze kosten, zoals hier is gegeven, kan helpen bij het
prioriteren van beleidsmaatregelen en verder onderzoek naar hormoonverstorende stoffen.

3

4

Executive summary
This report aims to provide an improved understanding on the potential socio-economic cost of
EDC-associated health effects. Gaps between the required and available information of adequate
quality that is relevant for health impact analysis and modelling of socio-economic cost in relation
to EDCs, are addressed. The available information from the scientific literature on EDC-related
health endpoints and existing modelled costs are summarized, compared and evaluated.
Uncertainties that are associated with the causal link between health effects and EDCs are not a
focus of the present report. A modular approach is introduced that can provide a method to
include additional calculations of potential socio-economic cost and be used to add relevant
information on EDC-related diseases. This approach is illustrated for five potentially EDC-related
health effects. According to currently available literature, the socio-economic burden of EDC
associated health effects for the EU may be substantial, ranging between € 46 288 billiori per
year. In view of the uncertainties with respect to causality with EDCs and corresponding health
related costs, these estimates should be interpreted with care. Nevertheless, this study iridicates
that exposure to EDC5 may lead to substantial societal costs. The outcome of this literature study
—

warrants further substantiation of the suggested associations as well as health costs for potential
EDC-related diseases.
Background
The endocrine system regulates and drives growth, development, homeostasis and reproduction.
There is now substantial toxicological evidence that certain chemicals have the ability to interfere
with and modulate the endocrine system. In addition, there is evidence that changes in the
endocrine system may lead to adverse health effects. WelI-known examples of chemicals that are
associated with endocrine disruption (so-called Endocrine Disrupting Chemicals or EDCs) inciude
polybrominated diphenylethers (PBDEs), organophosphorus pesticides (OPs), phthalates, bisphenol-A
(BPA) and their analogues, as well as the “older” persistent organic pollutants (POPs) such as
dichloordifenyltrichloorethaan (DDT), chiorinated dioxins and polychiorinated biphenyls (PCBs).
Exposure to many of these chemicals is still ubiquitous. Exposure to EDCs in humans has been
associated to a spectrum of diseases and deficits, including metabolic diseases, certain hormone-.
dependent tumors, neurobehavioral deficits and male reproductive deficits. Also, epidemiological
studies indicate that these adverse health effects have increased over the last decades in humans
and wildlife (Kortenkamp et al., 2012, UNEP/WHO, 2013, Gore et al., 2015).
The impact of (potential) EDCs on human health and the environment is an area of extensive debate
and includes discussion on the definition of an “endocrine disruptor”, the criteria to identify
chemicals as an EDC, types of related health effect, weight of evidence, mechanisms, methodology
for risk assessment and regulatory approach. Over the years, this debate has become more and more
polarized, which has slowed down regulatory action on (potential) EDCs in the EU. The observed
increase in incidence of endocrine-related diseases together with the yearly high production of
industrial chemicals (source: Eurostat) that may exhibit endocrine disrupting effects signify the need
for risk managers and regulators to be welI-informed on the consequences of the (lack of) regulatory
actions with respect to EDCs. The overall goal of this report is to improve understanding on the
extent of potential EDC-related health effects and related socio-economic cost in Europe.

5

Inventory of EDC-associated health effects
The past years, the EU, WHO, UNEP and other institutions and groups of scientist have published
leading reviews on EDCs that include overviews of (potential) EDC-related diseases, disorders and
conditions. These studies used different criteria to determine weight of evidence and/or causality to
establish a role for EDCs in specific health effects. Therefore, some differences exist in listed health
effects. In this report, an as much as possible complete and dear overview of EDC-associated health
endpoints was compiled using these authoritative reviews on EDCs and their effects. This has
resulted in a table with over 80 health effects that are associated with EDCs in the literature (Table 1
in the report). These endpoints can be clustered into six major categories: reproductive health,
hormonal cancers, neurodevelopmental syndromes and conditions, effects 0fl the metabolic system,
immune system disorders and one mixed group of “other” health endpoints. In order to retain the
possibility to compare studies, we used as much as possible the definitions of health effects as
defined in the reviews used. There is considerable agreement on the categories of health effects that
are associated to endocrine disruption. Most consistency among reviews seems to exist within the
group of reproductive health effects and group of hormonal cancers. Listing of specific health effects
is less consistent in the group of immune system disorders and the group of “other” disorders and
conditions.
Causality between EDCs and health effects has been addressed in the scientific studies that are
underlying this report. It should specifically be mentioned that we did not evaluate causation nor did
we apply an (additional) weight or rating for the weight of evidence (W0E) in drawing up the
overview of health effects. Considering that at present there is no accepted framework to judge
causation for EDCs or consensus on a WoE approach to assess EDCs, It is important to emphasize
here that the health endpoints included in this report are assumed potentially related or associated
to EDCs. For those chemicals that are currently in use and suspected of ED properties, a WoE
approach should ïdeally be applied that combines toxicological and epidemiological evidence.
However, this combined interpretation of toxicological and epidemiological evidence is complex and
challenging. Moreover, epidemiological evidence or data should not be a leading factor for
identification of new EDCs, because epidemiological evidence can only be generated for chemicals
that are already placed on the market, and is obviously not available for new chemicals. It is
important to note that several suggested EDC-related human adverse health effects, are not covered
within test guidelines for chemicals to obtain regulatory admission of chemicals to the market.
Together, these issues clearly hamper the assessment of EDC-related health effects.
Evaluation of studies that quantified socio-economic costs of EDC-associated health effects
Recently, three (series of) studies have been published that quantify costs of health effects
associated to exposure to EDCs: The Nordic Council report, commissioned by the Nordic Council of
Ministers (Olsson et al., 2014), Health and Environment Alliance (HEAL) published a report with
calculations performed by Bath University (HEAL, 2014) and thirdly, a peer-reviewed publication
series ed by L. Trasande, M.D. (NYU School of Medicine), was written by various Ieading scientists in
the field and published by the Endocrine Society (Bellanger, Demeneix, Grandjean, Zoeller, &
Trasande, 2015; Hauser et al., 2015; Legler et al., 2015; Trasande et al., 2015). In this report, these
three EDC-related socio-economic cost studies were compared with regard to their methodology to
quantify EDC-associated health cost and their resuits. All three aforementioned studies share a
common scope, currency and timing: they cover the EU28, and were published in 2014 and early
2015. In total, thirteen EDC-associated health effects were quantified in these studies. There is a
6

distinct overlap between the endpoints that have been assessed in the study of HEAL and publication
series of Trasande and co-authors, while the Nordic Council only assessed effects on male
reproductive health. For each described EDC-associated health effect, a detailed evaluation was
carried out of the underlying cost-of-disease studies, calculations, data on numbers of cases of
disease (incidence/prevalence) and adjustment of costs. The detailed results on the evaluated
parameters are combined in a single spreadsheet, which is provided as Annex B of this report. A
summary of the main results and methodological approaches of the three studies is presented in
Table 5 of this report.
To quantify the contribution of EDCs to a certain health effect, it is essential to set an accurate
estimate for the etiological fraction (the attributable fraction, AF) or the % of the cases with a certain
disease that can be linked to EDCs. It is generally acknowledged that the exact contribution of EDCs
to the total disease burden is unknown, as is also often the case for other contributing genetic,
lifestyle and environmental factors. The published studies used two distinct methodologies to
establish an EDC-attributable fraction: HEAL and the Nordic Council both used fixed estimates (of
2/5% and 2/20/40%, respectively). In contrast, Trasande and co-authors calculated EDC-attributable
cost based on exposure-response relations (ERRs) from epidemiological studies for specific
compounds. This publication series also took the strength of evidence of combined strength of
toxicological and epidemiological evidence (causation) into account in modelling an overall cost
estimate.
For some health effects, the socio-economic cost estimates are similar, which is noteworthy given
the fact that different methodologies and input parameters were used to obtain these estimates. For
instance, the estimation for cryptorchidism-related costs is very similar among the three studies. For
male reduced fertility, however, the costs calculated by the studies of Trasande and co-authors are
more than an order of magnitude higher compared to the results of HEAL and the Nordic Council.
Similarly, Trasande’s calculated cost of AD(H)D are much higher compared to the calculation of HEAL,
while HEAL’s calculation of autism is very high compared to Trasande’s estimate. However,
irrespective of the quantitatively different outcomes, all three studies concluded that the estimated
socio-economic cost of EDC-associated health effects are substantial with best estimates in the range
of billions of euros for the whole EU28 on a yearly basis.
Assessment ofgaps and needs and way forward using a ‘modular approach’ on cost of EDC
associated health effects
In this report, more than 80 different (potentially) EDC-associated health endpoints were identified,
for 13 of which cost were quantified in aforementioned studies. This leaves a large part of the EDC
associated health effects unquantified. These mainly comprise of female reproductive effects,
immune-related disorders and “other” EDC-related disorders (such as thyroid effects and
neuroendocrine diseases).
To enhance interpretation and comparability between estimated cost of different health effects,
structure, transparency, uniformity and completeness of information on socio-economic cost
estimates is needed. Therefore, a so-called “modular approach” is proposed in this report that
consists of “building blocks” of information on EDC-associated diseases and their socio-economic
impacts. To set up the modular approach, information is proposed in this report that is deemed
relevant for the interpretation of cost. These include general information on the etiology and

7

treatment of the disease, information on the state of knowledge on suspected chemicals, ED
mechanisms and pathways, co-morbidities, current incidence or prevalence of the disease. Finally,
socio-economic cost estimates need to include published literature references and type of costs
taken into account (direct, indirect and intangible cost) in order to interpret completeness of the cost
data and compare results with other studies and health effects. By means of an explorative literature
search of cost-of-disease studies, we found 48 health effects that have ever been quantified,
irrespective of the link with EDCs. For 21 health endpoints, no or limited studies were identified that
quantified healthcare cost. Based on available data, a total cost estimate for a given disease can be
made and (where needed) extrapolated for EU28. Ultimately, the EDC-attributable fraction has to be
applied to calculate the annual EDC-attributable cost for EU28.
One of the challenges is to attribute a certain etiological (or attributable) fraction (AF) of the total
disease cost, to a single cause, in our case exposure to EDCs. This is challenging because exact causes
of disease development are usually not known, and often considered to be a complex interaction of
e.g. genetic, dietary, environmental, occupational and behavioral aspects. For our modular approach,
we used 1%, 2,5% and 10% as best estimate EDC-attributable fractions. The 1 and 2,5% point
estimates are within the (lower) environmental AF ranges presented in the papers of WHO and
OECD, both for general environmental factors as well as for the contribution of pollution or chemicals
specifically. We used a 10% as a high level estimate of the EDC-attributable fraction. This 1-10%
range accounts for uncertainties for the role of EDCs in disease development, yet recognizes that for
some diseases the role of environmental factors is stronger than for other diseases.
The modular approach was applied to a selected group of proposed EDC-associated health endpoints
that have not been modelled before (endometriosis, neural tube defects and asthma), and two
health endpoints quantified earlier (ADHD an ASD). The selection of these effects was based on
expert judgement and team discussions on severity of the disease, incidence or prevalence,
observations in the trends of incidence or prevalence, and availability of good-quality cost studies
and other cost expertise. As stated earlier, WoE for the causation between these health effects and
EDCs was not assessed. Literature searches were performed to select the best applicable cost studies
in terms of year of publication, relevance of country, inclusion of direct and indirect costs. As an
essential aspect of the modular approach, a breakdown of socio-economic cost for the three newly
calculated EDC-associated health effects is shown (Table 8 of the main report). Using the defined
EDC-attributable fractions of 1%, 2,5% and 10%, EDC-attributable costs for neural tube defects were
estimated to be € 19 (7,7-76,5) million, for endometriosis € 2 (0,8-7,8) billion, and for asthma € 0,4
(0,2-1,7) billion. Together, these three health effects add € 2,4 billion (€ 1-10 billion) to the earlier
estimated socio-economic costs of EDCs.
In this report, data is provided on potential EDC-attributable socio-economic cost that have (not)
been addressed in earlier studies, as well as information that is relevant for the interpretation of cost
estimates. The modular approach can help in further assessment of diseases that are associated with
EDCs and allows new diseases, disorders and conditions to be added to this overview, along with an
estimate of their potential socio-economic costs. We propose to visualize the information in a
structured manner by means of a factsheet per health effect. Over time and to meet specific needs,
different types of information (categories) could be added, deleted or changed on the factsheets.
Furthermore, the information on the factsheets should be updated on a regular basis to stay up-to
date and include the latest (scientific) insights. Consequently, our proposed modular approach will
8

gradually lead to a more complete understanding of the potential socio-economic costs of EDC
associated diseases and will help to prioritize (regulatory) actions and further research on the basis of
health impact and societal costs. This methodology could also be appiled in a broader perspective, to
analyze any other health impact, potentially causal agent, and associated socio-economic costs.
Overall evaluation of EDC-associated health effects and socio-econornic costs
This report provides an overall evaluation of the available data on EDC-associated health endpoints
and related socio-economic cost as well as new cost estimates. These cost estimates have been used
to determine a cost range for each health effect and a total range for the EU28. The total estimate of
socio-economic burden of EDC-associated health effects for the EU28 ranges between 46 and 288
billion € per year.
Although only a few of the suggested EDC-associated health effects have been quantified, this report
can help to prioritize future research and actions for the assessment of potential EDC related adverse
health effects and costs. Using a cost-based approach can also help in the priority setting of the
development and inclusion of test guidelines for EDCs that address certain types of diseases in
regulatory frameworks. Based on this report, these should at least include neurodevelopmental
toxicity, diabetes, obesity and immunological disorders. Neurodevelopmental and -behavioral
diseases and disorders comprise the largest contributors to the total EDC-associated socio-economic
cost estimates. This group of neurobehavioral disorders includes several pervasive disorders that
persist for a lifetime, thereby leading to in prolonged costs. Here, especially the contribution of lQ
loss (€ 32-184 billion) dominates the cost estimate. It was shown that almost every newborn child
could lose some IQ points due to (mostly) prenatal exposure to EDCs. It should be noted, however,
that socio-economic impact of 10 loss is calculated based on indirect loss, i.e. income loss due to
lower 10 and hence does not represent actual expenditures (such as medications and treatments).
Apart from 10 loss, the cost for other neurodevelopmental and -behavioral health effects are also
estimated to be relatively high compared to other groups of health effects that are associated with
EDCs. These cost largely comprise of direct healthcare cost, provided by specialized institutes and
residential care. The cost of the group of metabolic diseases is also estimated to be relatively high,
with € 1,6 to 17 billion for obesity and € 1,4 to 17 billion for diabetes type 2. This is especially due to
a large prevalence of diabetes and obesity within society. The group of immunological diseases,
disorders and conditions has not been sufficiently quantified yet, which hampers (EDC-associated)
socio-economic cost estimation. Especially considering the increasing incidence in immunological
diseases, such as asthma and allergies, and probable contribution of EDCs in these disease etiologies,
this clearly needs further study. However, at present, legislative frameworks for screening of
chemicals do not obligate to screen for (developmental) neurotoxicity nor metabolic or
immunological endpoints. Moreover, it would be very useful to evaluate if current chemical testing
guidelines even sufficiently cover endpoints related to these diseases.
This report indicates that even when taking the low-range estimates, the estimated EDC-associated
health costs may be substantial. In view of these substantial estimated socio-economic costs but also
considering the uncertainties surrounding the health effects of EDCs, more studies to identify EDC
related health effects, strength of evidence, endocrine mechanisms, mode of actions, and
attributable fractions to a specific health effect are desired. As such, this report should help
prioritization of actions on EDCs and areas for future research.

9

oi:

Table of Contents
Colofon

2

Publiekssamenvatting

3

Executive summary

5

1.

13

2.

3.

Introduction to Endocrine Disrupting Chemicals
1.1.

What are Endocrine Disrupting Chemicals?

13

1.2.

Current discussion on EDCs

13

1.3

Risk appraisal and socio-economic impacts of EDCs in the light of risk governance

14

1.4

Objectives of this report

15

Inventory of health effects potentially related to exposure to endocrine disrupting chemicals.. 17
2.1.

Scope for inventory of EDC-related health effects

17

2.2.

Methodology

17

2.3.

Resuits

18

Evaluation of EDC-related cost studies of The Nordic Council, HEAL, and Trasande et al

23

3.1.

Scopeofevaluation

23

3.2.

Methodology

23

3.3.

Quantified EDC-related health effects

26

3.4.

General comparison of methodology

26

3.5.

Comparison of total cost of EDC-related health effects

29

3.6.

Detailed evaluation of EDC-related cost per disease

29

3.6.1.

Reduced fertility

29

3.6.2.

Cryptorchidism

32

3.6.3.

Hypospadias

33

3.6.4.

Autism spectrum disorder, (ASD)

33

3.6.5.

Attention Deficit (Hyperactivity) Disorder, AD(H)D

35

3.6.6.

IQ loss

36

3.6.7.

Mental retardation

38

3.6.8.

Breast cancer

39

3.6.9.

Prostate cancer

40

3.6.10.

Testicular cancer

40

3.6.11.

Obesity

41

3.6.12.

Diabetes type 2

42

3.6.13.

Increment death rate

44

11

4.

5.

Gaps and needs in “cost of EDC” estimates: a way forward using a modular approach

45

4.1.

Why a modular approach
7

45

4.2.

Methodology

46

4.3.

Data gaps in cost of health effects

46

4.4.

Identification of relevant information for the set-up of a modular approach for EDCs .48

4.5.

Selection of health effects to test the modular approach

52

4.6.

Application of the modular approach

52

4.7.

Factsheets

53

Evaluation

59

5.1.

Range for EDC-attributable cost in EU28

59

5.2.

Avaiabiity and (un)certainty of data

60

5.3.

Highest cost and possible implications for priority setting

64

5.4.

Recommendations

67

Financing and acknowledgements

69

List of Abbreviations

71

References

73

Annex A

References to health effects (potentially) related to EDCs

79

Detailed evaluation of parameters relating to EDC-attributable cost per disease

81

Annex B

—

—

12

1. Introduction to Endocrine Disrupting Chemicals

1.1.

What are Endocrine Disrupting Chemicals?

Our endocrine system regulates and drives growth, development, homeostasis and reproduction
(amongst others). The endocrine system consists of various hormone producing glands and hormone
producing organs and tissues, such as kidney, Ijver, heart, gonads and body fat. Physiological effects
of hormones and feedback pathways towards hormone producing glands, organs and tissues is
provided via receptors, which induce a cascade of effects often via interaction with the DNA.
The endocrine system is very sensitive and hormones already act at very low concentrations. There is
now substantial toxicological and epidemiological evidence that certain chemicals have the ability to
interfere with and modulate the endocrine system in humans and wildlife. Although there is ongoing
discussion within the EU on the exact definition of a (potential) Endocrine Disruptive Chemical (EDC),
the definition by the World Health Organization and the International Programme on Chemical
Safety (WHO/IPCS) from 2002 is stili most commonly used: “An endocrine disruptor is an exogenous
substance or mixture that alters function(s) of the endocrine system and consequently causes adverse
health effects in an in tact organism, or its progeny, or (sub) populations. A potential endocrine
disruptor is an exogenous substance or mixture that possesses properties that might be expected to
lead to endocrine disruption in an intact organism, or its pro geny, or (sub) populations.”(Damstra T.,
Barlow S., Bergman A., Kavlock R., & Van Der Kraak G., 2002).
Exposure to EDCs in humans has been related to a whole spectrum of diseases and deficits, including
metabolic diseases, certain hormone-dependent tumors, neurobehavioral deficits and male
reproductive deficits (A. Gore et al., 2015). However, the weight of evidence for a causal relationship
is still a topic of intense scientific debate.
Well-known examples of chemicals that are associated with endocrine disruption (ED) inciude
polybrominated diphenylethers (PBDE5), organophosphorus pesticides (OPs), phthalates, bisphenol-A
(BPA) and their analogues, as well as the “older” persistent organic pollutants (POPs) such as
dichloordifenyltrichloorethaan (DDT), chlorinated dioxins and polychlorinated biphenyls (PCBs).
Exposure to many of these chemicals is still ubiquitous. Numerous papers have shown that these
chemicals can be detected in e.g. our body fat, breast milk, blood, cord blood, and urine. However, it
has also been demonstrated that remedial actions for certain compounds by governments and/or
from manufacturers over the past decades has resulted in a decreased body burden in humans for
these specific compounds, e.g. for dioxin-like compounds (Rylander, Rignell-Hydbom, Tinnerberg, &
Jönsson, 2014). As part of this remedial process, alternative chemicals have been introduced on the
market, but for many of these novel compounds it is not known whether these can have a
modulating effect on the endocrine system (Rylander et al., 2014). As a result, present exposure to
potential EDCs is still subject to uncertainty and a substantial scientific and public debate and
concern.

1.2.

Current discussion 011 EDCs

The impact of (potential) EDCs on human health and the environment is an area of extensive debate
and includes discussions on the definition of an “endocrine disruptor”, the criteria to identify
chemicals as an EDC, type of related health effects, weight of evidence, mechanisms, methodology
13

for risk assessment and regulatory approach. Over the years, this debate has become more and more
polarized. At one side there are scientists who are concerned about EDCs, who point at increasing
evidence that current risk assessment methodologies are not sufficiently protecting human and
animal health, and calI for action partly based on precautionary principles as well as observational
health studies in humans and wildlife (Diamanti-Kandarakis et al., 2009; A. Gore et al., 2015; The
Berlaymont Declaration, 2013). A major concern is that EDCs may act at very low concentrations,
which is not sufficiently investigated in animal studies that typically use high-dose levels. Moreover,
low-dose effects might be different from high-dose effects. Additionally, several human-relevant
effects and sensitive periods of exposure and exposure to chemicals and mixtures of EDCs are not
adequately addressed in current hazard assessment practices. As a consequence, these scientist
argue that safe exposure levels for (potential) EDCs established using traditional risk assessment
processes are highly uncertain (The Berlaymont Declaration, 2013). On the other side, there are
scientists, who oppose the conclusions and concerns published in reviews on EDCs by the UNEP,
WHO and European Commission. These critics put emphasis on the uncertainty of causality and
suggested relationships with health effects of (potential) EDCs especially in humans. They also argue
that the current risk assessment approaches that use a no-effect threshold from animal studies is
also applicable to EDCs (Autrup et al., 2015; Lamb et al., 2014; Nohynek, Borgert, Dietrich, & Rozman,
2013). Subsequently, these publications have provoked rebuttals from scientists who have raised
their concerns about EDCs (A. Bergman et al., 2013; A. Bergman et al., 2015; A. C. Gore et al., 2014;
Kortenkamp, Martin et al., 2012; R. T. Zoeller et al., 2014). This discussion has further been
complicated by interference and statements from chemical industry (ACC, Cefic, CLA, CLC, CLI, ECPA,
2014; ECPA, 2014) and accusations for conflicts of interest due to relationships with industry (Horel &
Bienkowski, 2013).
This debate has hampered regulatory action on (potential) EDCs. Currently, the European
Commission is carrying out an impact assessment, which seems to slow down the process to set
criteria for identifying EDCs and phasing out existing chemicals on the market that might have
endocrine disruptive properties. In addition, the adequacy of current testing frameworks (e.g. under
REACH, PPPR and the Biocide Regulation) to capture an endocrine disruptive effects are being
questioned, while at the same time newly developed testing methodologies are not easily included in
legislative frameworks. Both the acceptance of such additional tests as the difficulty to include those
tests for endocrine disruption in the various legislative frameworks is bogging down possible
regulatory actions on chemicals with unknown potential ED properties that are already being
produced and used, and new market introductions. Considering the increasing trends in endocrine
related diseases (Kortenkamp, Evans et al., 2012; UNEP/WHO, 2013) and the yearly high production
of industrial chemicals with toxic and/or posibbie ED effects (Eurostat), risk managers and regulators
need to be weIl-informed on the potential consequences of the (lack of) regulatory actions with
respect to EDCs.

1.3

Risk appraisal and socio-economic impacts of EDCs in the light of risk
governance

So far, much attention went into the debate whether or not a causal relationship exists for EDCs and
various adverse health effects. However, this is only one part of the body of information on which
policy decisions can be made. The International Risk Governance Council (IRGC) states: “Policy
makers are often required to make decisions and take actions under considerable time pressure,

14

with incomplete information and often faced by conflicting advice. Even in situations of knowledge
deficit decisions must be made and action is often needed” (IRGC, 2012).
What 1f we look to “the issue of EDCs” as if It was any other risk? The IRGC framework, which aims to
understand, analyze and manage important risk issues, comprises five linked phases: pre
assessment, risk appraisal, characterization and evaluation, management, communication (IRGC,
2012). In our report, we will focus on (parts of) risk appraisal and characterization and evaluation as
defined bythe IRGC.
Risk appraisal develops and synthesizes the knowledge base for the decision on whether or not a risk
should be taken and, 1f so, how this risk can possibly be reduced or contained. As part of the risk
appraisal, a scientific assessment should be carried out as well as a concern assessment. Within the
scientific assessment, one of the key questions to be answered is “What are the potential damages
or adverse effects?” In this report, we will focus on this question.
Next, the phase of characterization and evaluation is intended to ensure that the evidence based on
scientific facts is combined with a thorough understanding of societal values when making the
sometimes contrçversial judgment of whether or not a risk is “acceptable”, “tolerable” or, in extreme
cases, “intolerable” and, if so, to be avoided. One of the questions in this phase is “What are the
societal, economic and environmental benefits and risks?”. From an industry point of view, additional
testing for endocrine disruption will have a financial burden, as well as other restriction
measurements arising from testing results. From a societal point of view, however, cost are carried if
adverse effects will contribute to the burden of disease. In this report, we alm to provide a better
insight in the potential socio-economic impacts of EDC-associated health effects.

1.4

Objectives of this report

Our overall goal is to provide improved understanding on the potential socio-economic cost of EDC
associated health effects. The assessment of a causal association between EDC exposure and health
effects is outside the scope of this report and will therefore not be discussed. Here, we aim to
identify and address gaps and needs in availability and quality of information that are relevant for
health impacts analysis and modelling of socio-economic cost that have been associated with EDCs.
As such, we summarize, compare and evaluate the available information on EDC-associated health
endpoints and existing modelled socio-economic costs. In order to deal with identified information
gaps, we propose a modular approach to include additional calculation of socio-economic cost and
add relevant information on EDC-related diseases. This approach is exemplified for five EDC
associated health effects.
This report consists of four major parts:
-

-

-

-

Inventory of EDC-associated health effects (Chapter 2);
Evaluation of studies that quantified socio-economic costs of EDC-associated health effects
(Chapter 3);
Assessment of gaps and needs and way forward using a ‘modular approach’ on cost of EDC
associated health effects (Chapter 4);
Overall evaluation of EDC-associated health effects and socio-economic costs (Chapter 5).

15

cl,

Ia

2. Inventory of health effects potentially related to exposure to
endocrine disrupting chemicals
The past years, the EU, WHO, UNEP and other institutions and groups of scientist have published
leading reviews on EDCs that include an overview of EDC-related diseases, disorders and conditions.
In addition, these reviews address mechanisms and modes of action (M0A) and strength of evidence
from a toxicological and epidemiological point of view (Â Bergman et al., 2013; Diamanti-Kandarakis
et al., 2009; European Environment Agency, 2012; Kortenkamp et al., 2012; The Berlaymont
Declaration, 2013; UNEP/WHO, 2013; WHO, 2014). There is substantial agreement on which
categories of health effects in which EDCs are considered to play a role, e.g. reproductive health
effects and neurodevelopmental effects. However, depending on the focus of the reviews and
requirements for inclusion, there are also differences in what specific health endpoints are
associated with EDC effects. In this chapter, we remove overlap and differences in specific health
effects mentioned in the prevailing literature, with the aim to provide an as much as possible
complete and dear overview of health endpoints relateci to exposure to (potential) EDCs.

2,1.

Scope for inventory of EDC-associated health effects

In this assessment, we focus on listing the potential adverse impacts of EDCs to give an as much as
possible complete overview of health effects (potentially) related to exposure to EDCs. Health effects
(also called health endpoints) could be diseases, disorders or conditions, yet these are not further
distinguished in this report.
The overview is generated based on the health effects mentioned in peer-reviewed literature
reviews on EDCs, and limited additional studies. Causality to each health effect is extensively
addressed in the underlying reviews and not further addressed in the overview in this report. In
drawing up the overview of health effects, we did not apply an (additional) weight or rating for
evidence (often referred to as weight of evidence, WoE). It is outside our scope of this report to
discuss the underlying epidemiological and toxicological evidence from peer-reviewed publications
used. However, we will discuss the issues concerning establishing a causal association in paragraph
2.3.
Taking into account the enormous amount of published studies on EDCs and the current speed of
progress in toxicological and epidemiological studies that focus on this field, such an overview of
EDC-related diseases should stili be considered tentative as new scientific evidence and insights seem
to develop continuously.

2.2.

Methodology

The list of scientific publications on EDCs and their (potential) effects and mechanisms is extensive,
with over 10.000 studies published and listed in search engines. Within the limited timeframe for
preparing this report, no systematic review could be performed of these studies. To provide an as
much as possible complete overview of EDC-related health endpoints, authoritative reviews on EDCs
and their effects, published in the past 6 years by institutions such as WHO, UNEP and the EU, were
used to provide a list of (potential) EDC-related health effects. These studies have assessed whether
a certain involvement of the hormone system is confirmed or biologically plausible, and if evidence
from toxicological and/or epidemiological studies is available to support a relation with EDCs. We
-

17

acknowledge that the studies used different criteria to determine weight of evidence and/or
causality to establish a role for EDCs in specific health effects. For more information, the reader is
referred to the original studies, as it is beyond our scope to evaluate these criteria. Considering that
at present there is no accepted framework to judge causation, it is important to emphasize here that
the included health endpoints in this report are assumed potentially related to EDCs.
The following reviews have been inciuded for the search for EDC-related health endpoints:
-

-

-

-

-

-

Diamanti-Kandarakis E et al., 2009. EDC-1: Endocrine-Disrupting Chemicals: An Endocrine
Society Scientific Statement. Endocrine Reviews 30(4):293-342
Gore A.C. et al., 2015. EDC-2: The Endocrine Society’s Second Scientific Statement on
Endocrine-Disrupting Chemicals. Endocrine Reviews 36(6):E1—E150
European Commission, 2012: Kortenkamp A et al., 2012. State of the art assessment of
endocrine disruptors. Annex 1: Summary of the state of science, revised version 2012.
European Commission Project Contract Num ber 070307/2009/550687/SER/D3
UNEP/WHO, 2013. State of the science of endocrine disrupting chemicals 2012 / edited
by Âke Bergman, Jerrold J. Heindel, Susan Jobling, Karen A. Kidd and R. Thomas Zoeller.
WHO Regional office Europe, 2014. Identification of risks from exposure to endocrine
disrupting chemicals at the country level. Edited by: Dr Nida Besbelli, Dr lrina
Zastenskaya
European Environmental Agency (EEA), 2012. The impacts of endocrine disrupters on
wildlife, people and their environments. EEA Technical Report 02/12012. ISSN 1725-2237

With exception of the EDC-2 report published in November 2015, all other large reviews were several
years old at the time of writing this report. Due to the rapidly evolving scientific knowledge, we have
used additional, more recent literature to further specify two immunological categories of health
effects listed in the authoritative reviews above (‘increase of local infections’ and ‘autoimmune
diseases’).

2.3.

Resuits

Table 1 gives an overview of health effects that are associated with EDC exposure in the literature.
This list includes all diseases, disorders and conditions that were mentioned in at least one of the
studies described in paragraph 2.2. Some health effects were listed by (almost) all reviews, while
other effects were only considered by one or two of the peer-reviewed studies. StilI, there is a
considerable agreement on the categories of health effects that are linked to endocrine disruption.
Most consistency among reviews seems to exist within the group of reproductive health effects and
group of hormonal cancers. Listing of individual health effects is less consistent in the group of
immune system disorders and the group of “other” disorders and conditions. However, it is noted
that (almost) all groups of health effects are covered in the different reports. Annex A provides a
detailed overview with references to the different literature reviews per health effect and references
to more recent studies that were not captured in the reviews.
Clustering of health effects
A total of 82 health effects that may be associated with EDCs were identified from the literature.
These endpoints can be clustered into six major categories: reproductive health, hormonal cancers,
neurodevelopmental syndromes and conditions, effects on the metabolic system, immune system
disorders and one mixed group of “other” health endpoints. Some health endpoints could be placed
18

in more than one category, but for the sake of clarity the most prevailing option was chosen for this
report. For example, an autoimmune thyroid disease is listed among autoimmune diseases in the
group of immune disorders, but it could also be listed under thyroid diseases in the cluster of “other”
health endpoints.
Definitions of effects
The health effects in Table 1 predominantly reflect those mentioned in the various literature reviews.
As a result, there is some overlap between health endpoints, e.g. childhood Iymphoma (which could
be any type of lymphoma) and non-Hodgkin Iymphoma (found both in children and aduits).
Furthermore, health endpoints may arise from a similar underlying mechanism, e.g. the Testicular
dysgenesis syndrome (TDS) also comprises cryptorchidism, hypospadias, and reduced male fertility
resulting from abnormal fetal testosterone exposure. All these effects are now listed as separate
endpoints. Such a correlation can also be argued for e.g. obesity and the development of diabetes.
Finally, some health endpoints may be observed in different directions depending on the mechanism
of individual EDCs involved, e.g. female precocious puberty and delayed puberty. However, in order
to retain the possibility to compare studies, we used as much as possible the definitions of health
effects as defined in the reviews used.
Weight of scientific evidence for causation
One of the biggest topics of debate is the issue of causation, e.g. whether or not a causal link exists
between exposure to (a) certain chemical(s), hormonal disruption, and adverse effects in an intact
organism, or its progeny, or (sub) populations.
To provide a weil-founded statement for a chemical being an EDC, careful selection, evaluation and
combination of experimental in vitro and in vivo studies are needed. In view of the fact that current
animal studies do not cover all relevant endpoints observations, human epidemiological data are of
utmost importance. In vitro studies can for example provide mechanistic basis to describe the
potential of a chemical to bind or (ant)agonise the action of hormone receptors or other disruption
of endocrine pathways. Animal studies would give biological plausibility that endocrine disruption
may also occur in vivo, and could link exposure levels to certain apical health effects. However, many
suggested EDC-linked human adverse health effects, such as those listed in Table 1, are not covered
within current guidelines for chemical testing to obtain regulatory admission of chemicals to the
market. This is an acknowledged gap in current legislation. For example, the Endocrine Disrupters
Expert Advisory Group (ED EAG) of the Joint Research Centre (JRC) of the EU stated that existing
standardized assays might miss some endpoints sensitive to endocrine disruption, and acknowledged
that there was no standardized assay currently available in mammals that allows the investigation of
early life/in utero exposure on effects that may appear in later life stages, such as cancer, impact on
menopause and senescence (Munn & Goumenou, 2013).

19

Table 1. Inventory of LOC-associated health effects from peer-reviewed reviews on EDCs, and some recent studies (in
italic). The references can be found in Annex A. Health effects in blue represent effects for which socio-economic cost
have previously been quantified in other studies (Chapter 3). The health effects in green refer to effects for which costs
are addressed in this report (Chapter 4).
1. Reproductive health
Female reproductive problems
Eemale fecundity and fertility
Reduced female fecundity (Power number of offspring(
Reduced female fertility
Infertility
Adverse pregnancy outcomes
Ectopic pregnancy
Spontannous abortions (miscarriages(
Hypertensiee disorders of pregnancy, mcl. pregnancy-induced
hypertension and pre-eclampsia
Intrauterine growth restriction (IUGR(
Preterm delivery
Low birth weight or length
eirth defects
Disturbed (decreased( lactation period
Polycystic ovarias tyndrome (PC0S(
Endometriosis
Reproductive tract absormalities
Uterine fihroids
Abnormal vaginal, cervical, uterine, and oeiduct anatomy
Ovarien: Premature oearian failure (POEL decreased ovarian
reserve/increased atresia, aneuploidy, granulosa steroidogenesis,
altered primordial follicles, follicle growth, oocytn quality
Vaginal adenosis (benigs abnormality(
Premature thelarchn
Female idiopathic precocious puberty / early menarche
Female delayed pubnrty
Disturbed menstruation cycle (Oligomenorrhea(
Early age at menopause
Male reproductlve problemn
Cryptorchidism
Hypospad las
Other male reproductive organ abnormalities (reduced testis weïght,
ahnormal small penis, prohlems efferent ducts, altered AOO,
morphology of seminiferous tubules, nipple retention(
Oeclining fertility due to reduced semen quality (ahnormalities( and
quantity (oligoopermia(
Testicular dysgenesis syndrome (TOS(
Epididymal cystu (infection/inflammation of the tube that carries semen
out of the testicle(
Orchitis (infection/inflammation of testis)
Male delayed puberty
Prostatic ietraepithelial hyperplasia (PIN(
Prostatitis (prostate inflammation(
2. Neurodevelopmental syndromes and conditlons
Neurobehavioral disorders
Autism spectrum disorders (ASO(
AO(H(O; attention deficit (hyperactivity) disorder
111 lost
Mental retardation
Cerebral palsy
Neural tube defects
Psychomotor retardatios, memory, leareing problems
Depressiee disorders
Behavioral prohlems: social, aggression, anelety, seuual

4. Effects on the metabolic system
Metabolic syndromes
Ohesity (child and adult(
Diabetes mellitus (type 2)
Diabetes type 1
Metabolic syndrome

Cardiovascular system
Cardiovascular disease (direct and indirect(
Cardio protection
Hypertension

5. Immune system disorders
Immune function, immune dineases and disorders
lncrease of systemic mnfectious diseasee due to altered immune responte
lncreaee of local infectioes due to altered immune response
Periodontal diseate
Oriris medio
Respirotory rrocr infecrions
Exoerhemo tubirum
Allergies other than asthma: allergic rhinitis, allergic conjunctieitis and
atopic dermatitis (eczema(
Autoimmune diseates (mcl. thyroid disease(
Autoimmune thyroid disease (AITD( (eg. Hathimot&s thyroiditis,
Graees’ disease(
Multiple sclerosie (MS(
Systemic fupun eryfhemofosus (SLE)
Rheumotoid orrhrirms
Ufcerotiee cofitit
Asthma, childhood asthma, wheeze
Myalgic encephalopathy/chronic fatigue syndrome/post viral fatigue
syndrome (ME/CFS/PVFS)
Fihromyalgia (rheumatic dieorder(
Hematopoietic disorders and malignancies
Childhood lymphoma
Leukemia
Non-Hodgkin lymphoma
6. Other disorders and conditions
Population effectu
lncrement death rate among men due to lower testouterone
See ratio declinisg male population
-

Neuroendocrlne disruption
Vanious diseases that uffect the pituitary or hypothalamus
Adrenal disorders
Adrenocortical hyperplasia (growth, stress respoese(
Cushing’s disease
Thyroid disruptios
Adult (sub(hypothyroidism
Congenital hypothyroidism (causing mental retardation(
Thyroid resistance syndrome
Bone disorders
lncreased risk of bone fractures
Osteoporosie
Other hone diuorders (eg. orthopedic defecte, irregular calcifications(

3. Hormonal cancers
Hormone-related cancers
Breast cancer
Endometrial cancer
Oearian cancer
dear celI adenocarcïnoma of the vagina and cervia sten
Prostate cancer
Testis (testicular germ cell( cancer
Theroid cancer

20

Epidemiological evidence may reveal causal links with (not previously established) EDC-related
diseases, because in vitro and in vivo experiments may not cover relevant events as described above,
or effects from laboratory experiments are not representative of the human situation. As such,
epidemiological studies would provide insights whether health effects are seen under realistic
exposure conditions in human populations. Yet, considering the large variation in the human
population with respect to genetics, socio-economic impacts and environmental influences, including
dietary habits and chemical exposures, It is difficult to establish strong correlations between adverse
health effects and often low concentrations of potential EDCs. Moreover, epidemiological evidence
or data should not be a leading factor for identification of new EDCs, because epidemiological
evidence could only be generated for chemicals already placed on the market, and will not be
available for new chemicals. It would be unethical to wait for strong epidemiological evidence for
adverse and potentially irreversible health damage in intact organisms and/or (sub) populations
before a chemical is acknowledged to be an EDC.
For those chemicals that are currently in use and suspected of ED properties, a weight of evidence
(W0E) approach should ideally be applied that combines toxicological and epidemiological evidence.
However, this combined interpretation of toxicological and epidemiological evidence is complex and
challenging. Already in the 2002 WHO report, a collective WoE approach has been proposed based
on principles for defining cause-and-effects relationships (Damstra T. et al., 2002). Also in the 2012
report from the EU, the need for consensus on assessment of the WoE was stressed (Kortenkamp et
al., 2012) and a systematic element using tables with criteria was introduced. The UNEP/WHO
provided a narrative summary in their report on the proof of scientific evidence for endocrine
disruption for various health endpoints (UNEP/WHO, 2013). In parallel, industry members also made
scientific proposals for a WoE approach (Bars et al., 2011; Borgert et al., 2011). The EU set up an
Endocrine Disrupters Expert Advisory Group (ED EAG) that aimed to evaluate key scientific issues
relevant to the identification and characterization of endocrine disrupting substances (Munn &
Goumenou, 2013). The ED EAG supported consideration of mode of action and adversity (via adverse
outcome pathways: AOP) in parallel applying weight-of-evidence approaches, weighing all available
evidence, both positive and negative, inciuding human epidemiology data, field data, animal
experimental (eco)toxicology studies, in vitro data, (Q)SAR, analogue and category approaches to
reach a conclusion on ED properties (Munn & Goumenou, 2013). However, despite these efforts,
consensus on which chemicals could be identified as EDCs or a framework on the WoE, strength of
evidence, or proof for causation for adverse effects does still not exist. It is questionable whether
consensus in the near future can be expected due to differences in interpretations of evidence by
different groups of scientists and stakeholders such as chemical industries, NGOs and governments.
In addition, there are also other issues that hamper a consensus on a WoE approach for EDC-related
health effects, including the following:
-

-

-

Each health effect can be linked to various chemicals or even a specific mixture effect, each
with a different burden of scientific evidence;
The other way around, chemicals may interrupt various endocrine pathways, and could
therefore relate to different health effects;
In vitro, in vivo and epidemiological studies are hard to compare due to differences in e.g.
methodology, (sub)populations, exposure levels and conditions;

21

A flaw in methodology or analysis can result in a false negative or positive effect. For
instance, susceptible windows of exposure or effects at low exposure levels are often not
taken into consideration in both experimental and epidemiological studies, especially the
older studies. Consequently, a chemical may falsely be labeled as non-EDC.
For the majority, if not all, chemicals a robust toxicological dataset is lacking. None of the
current regulatory frameworks within the EU requires mechanistic information in their basic
requirements or crucial information on apical endpoints such as developmental neurotoxicity
and immunotoxicity;
For those (thousands of) chemicals currentiy in production and use there is a general lack of
biomonitoring data and weli-designed epidemiological studies that take into account
susceptible windows of exposure;
There is a risk for publication bias. Whether resuits on adverse effects of chemicals are
published or not might be influenced by the funding agency, such as governmental bodies or
industry. There are some illustrative examples for the so-called funding effect, e.g. for test
outcomes on BPA (Vom Saai & Hughes, 2005).

22

3. Evaluation of EDC-associated cost studies of The Nordic Council,
HEAL, and Trasande et al.
Recently, several reports have been published that quantify costs of health effects related to
exposure to (potential) EDCs. The Nordic Council has calculated for EDC-related male reproductive
health disorders only, the cost in the EU28 is € 600 million (€ 59-1200 million) per year of exposure
(Olsson et al., 2014). In the two other studies, the annual EDC cost estimates for various health
impacts in the EU28 had a range of € 13 to 31 billion (HEAL, 2014) and a best-cost estimate of € 157
billion (90% C.l. € 32-212 billion) (Trasande et al., 2015). Irrespective of the quantitatively different
outcomes, all three studies revealed that socio-economic cost of EDC-related health effects could
potentially be substantial and best estimates are in the range of billions of euros for the whole EU on
a yearly basis.

3.1.

Scope of evaluation

In this chapter, three previously published EDC-related socio-economic cost studies are compared
with regard to their methodology to quantify EDC-associated health cost and their results. We aim to
explain differences in estimated cost and to obtain an improved understanding and interpretation of
the health effects and socio-economic impacts of EDCs in the EU. For that, we have evaluated:
-

-

-

-

-

-

3.2.

The type of health effects studied;
The general methodology to quantify EDC-related health effects;
The results of the socio-economic costs per EDC-related health effect and in total;
The underlying data on cost of diseases, especially what type of cost (direct, indirect,
intangible) have been included in the estimate;
Cost corrections and adjustments made in the reports;
The underlying data for an estimate of population size affected (use of EDC-attributable
fractions, incidence- or prevalence rate).

Methodology

Table 2 presents the three main (series of) publications that have addressed the socio-economic
costs of EDC-related health effects. The Nordic Council report was commissioned by the Nordic
Council of Ministers and executed by Olsson and co-authors. The calculations in the HEAL report
were performed by Bath University. The Trasande series was written by various leading scientists in
the field and published, after peer-review, by the Endocrine Society. All studies share a common
scope, currency and timing: they all cover the EU28, and were published in 2014 and early 2015.

23

Table 2. Overview of studies that have evaluated socio-economic cost of EDC-associated health effects
Publication

Referred to in
this report as:

Full title of publication

Reference

(series)
The Nordic

The Nordic

The cost of inaction

Olsson et al., 2014

Council of

Council

linked to effects of endocrine disrupting substances on

Ministers
The Health and

—

A socio-economic analysis of costs

male reproductive health.
HEAL

Environment

Health cost in the European Union: How much is related to

HEAL, 2014

EDCs?

Alliance (HEAL)
Trasande and co-

Trasande et al.

authors

Estimating burden and disease cost of exposure to

Trasande et al., 2015

endocrine-disrupting chemicals in the European Union
Hauser et al.

Male reproductive disorders, diseases, and costs of

Hauser et al., 2015

exposure to endocrine-disrupting chemicals in the
European Union
Legler et al.

Obesity, diabetes, and associated costs of exposure to

Legler et al., 2015

endocrine-disrupting chemicals in the European Union
Bellanger et al.

Neurobehavioral deficits, diseases, and associated costs of
exposure to endocrine-disrupting chemicals in the
European Union

Behanger, Demeneix,
Grandjean, Zoeller, &
Trasande, 2015

For analysis of these studies, a coarse-to-fine evaluation approach was applied and no additional
modelling, adjustment or extrapolation was carried out. Firstly, general information and outcomes of
the three EDC-cost of disease studies were evaluated. This includes the type of quantified health
effects, the general methodology of the study, and the resuits on EDC-related cost estimates per
disease. Next, the origin and composition of the resulting costs were evaluated to explain possible
differences in cost estimates per disease and improve the understanding of presented socio
economic costs. To do so, the scope and study parameters from underlying cost-of-disease studies
from literature were collected. This inciudes the type of direct, indirect and intangible costs
quantified for the specific disease. Furthermore, some of the original studies have been adjusted by
the Nordic Council, HEAL, and Trasande and co-authors to suit their EDC-specific scope (e.g. adapted
to relevant currency, population etc.). Lastly, estimates of EDC-attributable cases (or fractions
potentially related to EDC-exposure) that could be associated with a specific disease and associated
cost-of-disease were evaluated. The parameters for which information was collected are shown in
Table 3.

24

Table 3. Parameters on which information has been collected to evaluate socio-economic cost of EDC-associated health
effects. These parameters are found in original cost-of-disease study used (source literature on disease costs, most often
not linked to EDCs) and EDC-cost studies that adapted original literature (HEAL, Nordic Council and Trasande et al.).
Type of parameter
General study
parameters

Relevance
These parameters provide
information on the context in
which the study was
performed

Parameters
Author
Publication year
Year of data collection
Country of study
Per person estimate or total disease cost for society
Methodology: bottom-up or top-down assessment of costs
Subpopulation / study perspective
Currency and currency-year
Time horizon (eg. lifetime cost, annual costs)
Discounting applied (yes/no and %)

-

-

-

-

-

-

-

-

-

-

Type of cost
included in the
cost estimate

The scope for the assessment
of costs: which kinds of costs
are included? Cost could be
direct, which means these are
‘real’ expenses. Other costs
are indirect, or even
intangible.

-

-

-

Direct healthcare cost (DHC): e.g. treatment (hospital, home care,
institutes), medication
Direct non-healthcare cost (DNHC): e.g. travel cost to a clinic,
childcare cost when receiving treatment, co-payments by patients
Indirect healthcare cost (IHC): loss of years living in good health
(e.g. measured in Disability Adjusted Life Years DALYs), cost of
diseases otherwise avoided
Indirect non-healthcare cost (INHC): productivity loss patients and
care-givers, social welfare payments (benefits)
Intangible cost (IC): dissatisfaction, loss of quality of life (eg.
measured in Quality-Adjusted Life Years QALYs)
To relevant currency and currency year
Adjustments for ratio of each country’s Purchasing Power Panty
(PPP) adjusted per-capita Gross Domestic Product (GDP) to create
a country-specific estimate
Correction for double counting
Weighting of averages of various cost
To suitable age/life-time
Discounting, if not already included in original cost study (e.g. to
calculate lifetime cost based on annual cost)
Use of incidence (newly diagnosed cases of a disease) or
prevalence (number of cases of disease existing in a population)
Relative amount of cases (% within population)
Total number of cases in EU28
Use of fixed or calculated estimate of an EDC-attributable fraction
Amount of cases with the disease attributed to EDC-exposure
-

-

-

-

Adjustment and
extrapolation
parameters

The original cost-of-disease
studies are adapted to suit the
scope for EDC-related costs in
the EU and enhances
comparison and
harmonization between
health effects modelled

-

-

-

-

-

-

Cases with the
disease
(incidence/
prevalence)

Costs are dependent on the
amount of cases with the
disease

Cases with the
disease, attributed
to EDC5

Amount of cases or fraction of
total costs related to EDCs

-

-

-

-

-

25

3.3.

Quantified EDC-associated health effects

A comparison between the three major studies (HEAL, 2014; Olsson et al., 2014; Trasande et al.,
2015) identified a total of thirteen common health effects that were quantified. Between the study
of HEAL and publication series of Trasande and co-authors there is a distinct overlap between the
endpoints that have been assessed (Table 4). It should be noted that HEAL considered the influence
of male and female fertility together, while the Nordic Council and Trasande and co-authors
considered only effects on male fertility.

Table 4. Overview of type of health endpoints quantified in the different EDC-related cost studies.
Cat.

Source publication

Nordic

HEAL

Council

Trasande and
co-authors

Reproductive tract and fertility
1

Reduced female fertility
x

Reduced male fertility due to reduced semen quality and quantlty

x

2

Cryptorchidism

x

3

Hypospadias

x

x
x

X

Neurobehavioral diseases and disorders
4

Autism spectrum disorders (ASD)

x

x

5

AD(H)D (attention deficit (hyperactivity) disorder)

x

x

6

lO.loss

x

7

Mental retardation

x

Hormone-related cancers
8

Breastcancer

X

9

Prostate cancer

x

10

Testis (testicular germ celi) cancer

x

x

x

Metabolic syndromes / other
11

Obesity

12

Diabetes mellitus (type 2)

13

lncrement death rate among men due to lower testosterone

Obesity child

x

Obesity adult

x
x

x
x
x

male and female reproductive effects were assessed together

3.4.

General comparison of methodology

The methodological approaches for calculations of the costs of EDC-associated health effects of the
three studies are presented in Table 5. This comparison of methodologies can explain some of the
differences in estimation of costs for similar endpoints and can also be used for comparison and
interpretation of the total cost estimates presented in our report.
EDC-related diseases modelled
The total cost estimate calculated by the Nordic Council is much lower compared to the other two
studies. This is because the Nordic Council took only male reproductive effects into account, while
the other two studies included many other potential EDC-associated health effects.

26

Table 5. Comparison of general methodological approaches between the selected studies that have addressed the socio
economic costs of EDC-associated health endpoints
Parameter

Nordic Council

HEAL

Trasande and co-authors

Health effects

Male reproductive

Various (see also table 4)

Various (see also table 4)

disorders only
Current / future losses?

current and future costs

main focus: current costs

current and future costs

Approach for cost modelling

Own calculation, largely
based upon Swedish

From secondary

From secondary literature

literature

patient registry.
Cost type

Direct cost

Yes

Ves

Yes

included

Indirect cost

Ves

where available

where available (included
for cryptorchidism,

(included for autism,
breast cancer, prostate
cancer and diabetes type

autism, AD(H)D, 10 loss
and testicular cancer)

2)
Intangible cost

Discounting
rate

Only for cost that
occur in the future

where possible

No

Where possible (included

(included for testicular

for testicular cancer,

cancer, hypospadias,
cryptorchidism)

cryptorchidism, obesity)

4% (direct+indirect

Depending on study: 0%,

Depending on study: 3%

cost)
1,5% (intangible cost)

3% or 3,5%

or 3,5%

Methodologyto estimate EDC-

Etiological fraction:

Etiological fraction:

Calculated based on

attributable cost

2%, 20%, 40%

2%-5%

exposure-response
relationships for specific
chemicals (between 0,16—
35,3% depending on
health effect)

Correction for strength of evidence

No

No

Yes

€1 2012

€1 2010 or 2012

Currency / currency year

€1 2013

Range of total resuits

€59 million 1.2 billion

€13- 32 billion

€45— 270 billion

Best estimate

€ 591 million

€ 13 32 billion

€ 157 billion

Dominant contributor to total cost

Testicular cancer (40%

Autism (35% of total

10 loss (69% of total cost)

of total cost)

cost)

-

-

Interpretation of costs
There is a slight difference in how costs should be interpreted between studies. For health effects
such as hypospadias (genital malformation in baby boys) costs for treatment will occur shortly after
birth. Here, assuming a role of EDCs in the origin of the disease, the time between exposure and
treatment is limited. However, for some diseases that have a developmental origin, costs will occur
after many years. Testicular cancer, for example, usually develops between the ages of 20 to 40,
leaving a few decades between prenatal exposure to EDCs and the moment when costs are carried.
Because future costs are generally valued lower than costs that are paid now, economist apply a rate
of “discounting” to costs that manifest in the future. The rate of discounting varies between studies,
and sometimes discounting is not applied at all.
The study of HEAL did not apply discounting rates to all cost estimates and mostly focused on the
cost we are carrying now from exposure to EDCs in the past (current costs). This is in contrast with
the studies of the Nordic Council and Trasande and co-authors, which assessed the effects of current

27

prenatal exposure to potential EDCs and the resulting health effects in the near and far future
thereby applying discounting rates (future costs).
Type of costs modelled
One can distinguish between direct, indirect and intangible costs. Direct costs have been included in
all studies, although it can vary what has been included as direct costs. It should be noted that
indirect and intangible costs have not always been included in calculations, which resuits in large
differences in actual costs. The composition of the costs is evaluated in more detail in paragraph 3.6.
Methodology to estlmate the attribution of EDCs
To quantify the attribution of EDCs it is essential to set an estimate for the etiological fraction (the
attributable fraction (AF) or the % of the cases with the disease that is attributed to EDCs). Two
distinct methodologies are used; HEAL and the Nordic Council used fixed estimates (2/5% and
2/20/40% respectively) while Trasande and co-authors calculated EDC-attributable cost based on
exposure-response relations (ERR) from epidemiological studies for specific compounds. The use of
calculations make the AF based on stronger evidence compared to the more generic estimates of
etiological fractions for EDC-attribution by HEAL and the Nordic Council. Unfortunately, this approach
using ERRs cannot be applied for all health effects and all compounds. Qualitatively good
epidemiological studies are not available for all of the health effects and suspected EDCs. To
guarantee adequate results, suitable studies are needed that apply to a relevant population and
exposure level, are corrected for confounders and consider potential selection bias. Therefore, it is
crucial to mention the underlying epidemiological data used for the assessment of an EDC
attributable factor from an ERR.
Etiological fractions from the Nordic Council are based on expert judgement from experts in the field
of male reproductive health. HEAL used the hypothetical 2-5% range as a conservative estimate for
all health effects (also referring to one pioneering study linking one EDC (BPA) to 1,8% of obesity
cases). As an advantage, these fixed fractions are estimated for the general impact of ED-effects
combined, compared to one EDC only using ERRs. All scientist acknowledge that the exact
contribution of EDCs to the total disease burden is unknown, as are other contributing genetic,
lifestyle and environmental factors.
Strength of evidence and probability of causation
Trasande and co-authors considered the strength of experimental (toxicological) and epidemiological
evidence according to predefined criteria and defined one probability of causation percentage range
for these two types of evidence combined. As a framework for evaluation of EDCs is not available
(see also paragraph 2.3), they adapted their approach after IPCC criteria that are used to evaluate
strength of evidence for climate change. As such, the EDC-attributable cost estimates presented in
the publications of Trasande and co-authors (Bellanger et al., 2015; Hauser et al., 2015; Legler et al.,
2015; Trasande et al., 2015) were accompanied by a probability estimate that combined a rating of
toxicological and epidemiological evidence (Trasande et al., 2015). The rating is provided for
exposure-response relationships between the health effect and a specific chemical only and not for
the overall strength of evidence for a role of EDCs in a specific health effect.
The strength of evidence of the exposure-response relations has been taken into account in the
modelling of the overall estimate (Trasande et al., 2015). Recognizing the EDC-attributable cost
estimates were accompanied by a probability arising from the combined rating of toxicological and
28

epidemiological evidence, a series of Monte Carlo simulations was performed to produce ranges of
probable cost across all of the exposure-outcome relationships. This resulted in a best estimate,
taken into account the different degrees of certainty. Across 1000 simulations, a median estimate of
€ 157 billion (annually for EUZ8) was derived (with a 90% C.l. between € 32 and 212 billion). A more
detailed description of this methodology is given in the original articles (Trasande et al., 2015).
The studies of HEAL and the Nordic Council did not apply such an approach to correct for evidence of
causation.

3.5.

Comparison of total cost of EDC-associated health effects

An overview of the different EDC-attributable socio-economic cost estimates per health effect is
provided in Table 6. In the HEAL report and the publications from Trasande and co-authors, where
multiple health effects were assessed, remarkably dominant contributors to the total costs were
found (Table 5 and 6). These are neurobehavioral disorders, more specifically autism (and related
disorders) in the HEAL report and loss of IQ points in the Trasande et al. study.
For some health effects, the socio-economic cost estimates are similar, which is noteworthy given
the fact that different methodologies and input parameters were used to obtain these results. For
instance, the estimation for cryptorchidism costs are very similar among the three studies. For male
reduced fertility, however, the costs calculated by the studies of Trasande and co-authors are more
than an order of magnitude higher compared to the results of HEAL and the Nordic Council. Similarly,
Trasande’s calculated cost of AD(H)D are much higher compared to the calculation of HEAL, while
HEAL’s calculation of autism is very high compared to Trasande’s estimate. Possible causes of these
differences in estimated socio-economic cost for different health-effects will be further explained in
section 3.6.

3.6.

Detailed evaluation of EDC-associated cost per disease

Per disease, the underlying cost-of disease studies, calculations, data on number of cases of disease
(incidence/prevalence) and adjustments of cost were evaluated. Detailed results on the evaluated
parameters (as listed in Table 5) are provided in Annex B. This section describes the main differences
and similarities between the socio-economic cost estimates. We aim to increase the understanding in
(dis)similarities in costs estimates and enhance interpretation of resuits.
3.6.1. Reduced fertility
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
Male Vs. female reduced fertility and associated ART-type

The reports of the Nordic Council (Olsson et al., 2014) and the group of Trasande (Hauser et al.,
2015) focused on reduced male fertility only, while the report of HEAL (HEAL, 2014) also included
decreased female fertility. The Nordic Council estimate is based on therapeutic costs and lost
working hours for the so-called “ICSI treatment” only. ICSI (intracytoplasmic sperm injection) is a
fertility treatment where one healthy sperm is selected and injected directly to an egg for
fertilization (IVF) in vitro. As such, it can bypass male infertility caused by a decline in quality and
quantity of sperm. However, it is often argued that the exact cause for infertility or subfertility of a
couple is unclear and might also be attributable to female infertility. As such, other forms of assisted
reproductive technology (ART) can be applied to treat infertility. HEAL inciuded all forms of ART and
presented a combined impact assessment of male and female infertility problems. While female
29

fertility is not the (main) scope of the Hauser study, a cost estimation for all kinds of ART treatments
(thus inciuding treatments to overcome female fertility) was inciuded. Other forms of ART (including
other forms of IVF) have a higher average cost compared to )CSI (Olssen et al., 2014). As a result, the
estimate by the Nordic Council based on ICSI only could be either an over- or underestimate of male
infertility.

Table 6. EDC-attributable cost per health effect and total EDC-attributable annual socio-economic cost the EU (in billion
as described by the Nordic Council, HEAL and Trasande et al..
Source
Etiological
estimate

Nordic Council
fraction

/

type

HEAL

Trasande et al.

of
2%

20%

40%

Total (2%)

Total (5%)

0,048

0,062

0,120 0,155

0,026

0,045

base
case

low

high

Reproductive tract and fertility
Reduced female fertility
Reduced male fertility

0,007

Cryptorchidism

0,018

0,181

0,363

Hypospadias

0,009

0,089

0,178

0,072

-

-

0,145

4,71
0,018

-

-

0,065

0,117

0,130

0,080

0,199

Neurobehavioral diseases and disörders
Autism spectrum disorders (ASD)

4,52

11,3

AD(H)D

0,014

0,035

0,399

2,62

4,14

4,93

IQ loss

4,22

133,4

183,6

Mental retardation

6,11

22,6

33,43

Hormone-related cancers
Breast cancer
Prostate cancer
Testis (testicular germ celI) cancer

0,025

0,249

0,320

0,800

0,180

0,450

0,499

0,3

Metabolic syndromes, other
Obesity child

1,62

4,05

6,0

15,0

Obesity adult

1,56
15,6

Diabetes mellitus (type 2)
lncrement death rate among men

56

1,44
7,96

TOTAL
0,059
0,591
1,185
12,7
31,6
44,7
192,6
270,4
TOTAL after correction for
probability of causation
NA
NA
NA
NA
NA
157,0 (90% C.l. 32-212)
Note: Celis have been merged if they reflect cost estimates ot combined health effects. For the studies of Trasande et al. the low and/or
high estimates are provided as sensitivity analysis; if these 0w and/or high estimates were not calculated, the base case estimate (in greyl
are taken as upper and lower boundary of total EDC-related healthcare cost.

Costs per case
The cost estimates for reduced fertility from HEAL (€ 4.470 € 5.920 per treatment cycle) and Hauser
et al. (€ 7.621 per infertile couple that seeks treatment) are somewhat higher compared to those of
the Nordic Council (€ 3.480 per infertile male, regardless whether treatment is sought or not).
It should be noted that costs are hard to compare due to differences in scope of studies. The Nordic
-

Council and Hauser et al. studies specified cost per infertile male. The estimate for infertility in the
HEAL study based on average cost per IVF/ET (Embryo Transfer) treatment cycle, which is
considerably more expensive than the cost per treatment cycle used by the Nordic Council and
Hauser et al. studies. The cost per case in the HEAL study might actually be higher due to the fact
30

that the cost estimate is based on an older study from 1995 (when ART treatment were more
uncommon). Another difference can be found in the infertile males included in the cost estimates.
Not all males who are infertile seek treatment, hence will not use healthcare and therefore do not
create societal cost. In its estimate, the Nordic Council study inciuded all infertile males and
calculated a weighted average cost including males that did not seek treatment as well as males who
did seek treatment (with and without success
a live birth resulting from the treatment), thus
—

dividing fertility treatment cost over all infertile males. Also, in contrast to the estimate of HEAL and
Hauser et al., the estimates in the Nordic Council study were discounted to correct for the time lap
between prenatal exposure to EDCs and the time fertility treatment is sought (see also paragraph
3.4). Therefore, the Nordic Council estimate (per case) is only half the cost estimate specified by
Hauser et al. This is despite the fact that indirect non-healthcare costs (such as productivity losses)
have been included in the Nordic Council estimate, while these have not been included in the cost in
the estimate of Hauser et al. nor in the HEAL study.
Main drivers of total cost
An important driver for the total cost estimate for infertility is the amount of cases or treatment
cycles used for calculations. The Nordic Council study used an incidence rate for male infertility of 4%
for newborns. In the HEAL study, the total amount of ART cycles in 2009 was used for the total cost
estimate, referring to a total number of ART cycles in the EU of about 500.000/year. The Nordic
council report referred to 100.000 infertility cases in the EU per cohort of which part will undergo
various ICSI treatments. Both studies applied an EDC-attributable factor, yielding a similar number of
attributable cases or cycles of around 10.000. Depending on the specific EDC-attributable factor, the
Nordic council report estimated ED-related male infertility cost between € 7 and 145 million and the
HEAL study estimated the ED-related male and female infertility cost between € 48 and 155 million.
In contrast, in the paper of Hauser et al., the amount of infertile males due to phthalate exposure
was estimated using the number of “EU women aged 20-44, living in consensual union, not using
contraception” as a proxy for couples who want to become pregnant. This suggests that a lifetime
timeframe of fertile years of a woman has (mistakenly) been used as an annual estimate for male
infertility cases. Next, this number, 11.8 million women, was multiplied by 9.38% (the total infertility
rate attributable to phthalate exposure) and 56% (the rate of couples who seek medical care for
infertility), yielding 618.000 attributable cases. This result is almost two orders of magnitudes higher
compared to the estimates in the other two studies. This explains the much higher cost estimate of €
4,71 billion for male fertility by Hauser et al. compared with the estimates of the studies of The
Nordic Council and HEAL.
Su mm a ry
-

Despite a different scope, cost per case or treatment cycle for infertility are within the same
order of magnitude;

-

Final estimates for ED-related infertility of the Nordic Council and HEAL are in the same range
(resp. € 7
145 million, and € 48
methodologies were used;
-

-

-

155 million) in spite of the fact that different

The high number of estimated infertility cases in the Hauser et al. study (compared to the
number of cases in the report of HEAL and the Nordic Council) explains the higher overall
costs of € 4.71 billion. Therefore, the estimates of HEAL and the Nordic Council are
considered more realistic.
31

3.6.2. Cryptorchidism
A detailed overview of the breakdown of costs and study parameters is given in Annex 8.
Cost per patient
Cryptorchidism or undescended testes is a birth defect where one or two testes are not in the

scrotum at birth. 1f the testes do not descent spontaneously, It will be treated by a surgery called
orchiopexy. One of the most important differences in the cost estimates for cryptorchidism in
different studies is whether the indirect and intangible costs were inciuded. The authors of the
Nordic Council (Olsson et al., 2014) inciuded all kinds of direct, indirect and intangible costs (see
Annex B), while the authors of HEAL (HEAL, 2014) only used direct costs of surgery to calculate
economic effects of cryptorchidism. In the paper of Hauser (Hauser et al., 2015), cost estimates were
based on the calculations presented in the Nordic Council report, and hence also inciude direct,
indirect and intangible costs.
The direct costs provided by the authors of the Nordic Council and HEAL are based on the Swedish
patient registry and a US study, respectively. The US study differentiates between surgery performed
soon after birth (€ 5715) and post pubertal surgery (€ 8415). In the Nordic Council report it is argued
that development of cryptorchidism in later life is rare, and not relevant for EDC-related illness
because its development depends on other factors than hormones. Thus, an average surgery cost per
child is obtained (€ 4429). This estimate is lower compared to the HEAL-estimate, however the
difference is less than a factor of two.
In the Nordic Council report, lost working hours of parents are added (€ 1000), as well as intangible
cost. Especially the intangible costs are large with an estimated cost of € 29.200, based upon a
discounted loss of 0,42 QALY (a measure of loss of quality of life). One QALY is valued at € 70.200,
which leads to high intangible cost. The intangible cost makes up the major part of the costs
associated with cryptorchidism in the Nordic Council report and Hauser study, and explains the large
difference between the total cost estimates per patient in different studies.
Incidence and EDC-attributable factor
There is a large difference in incidence of cryptorchidism used for calculations by the Nordic Council

and HEAL. The Nordic Council authors reason that a large part of the cases detected at birth will
resolve spontaneously, and therefore requires no treatment. Only one out of five cases is assumed to
be treated by surgery, which leads to an overall 1% of the total number of male births that require
surgical treatment for cryptorchidism. In contrast, the HEAL study uses an incidence rate of 6%, but
assumes for its calculations that all cases require surgery, either soon after birth or after puberty. In a
footnote, however, it is stated that the incidence should actually be 3% given the fact that by three
months of age the incidence is usually more than halved because of natural, spontaneous descend.
Vet, the latter aspect is not used for further calculations, thus creating an incidence that is six times
higher compared to the Nordic Council and the Hauser et al. studies.
For the amount of EDC-attributable cases, the HEAL report uses 2% and 5% of the total incidence in
the EU. This is considerably lower than the Nordic Council study that uses 2%, 20% and 40% as EDC
attributable factors and Hauser et al. who use 8,9%, calculated based on exposure-response
relatio nsh i p5.

32

Total costs
Despite important differences in the types of costs included and the incidence of cryptorchidism

taken for calculations, the final cost estimates are remarkably similar. The use of higher costs per
patient in the calculations of the Nordic Council and Hauser et al., do not lead to higher estimates
compared to the HEAL calculations, because a lower incidence rate for surgery is used in the latter
study. Similarly, the higher incidence for surgery used by the authors of HEAL (not correcting for
cases that resolve naturally) does not lead to higher total cost because cost per patients are smaller,
and a lower attributable fraction for the relation between EDCs and cryptorchidism is used.
Su mm a ry
Despite differences in cost input parameters and incidence use, total cost are noticeable
-

-

-

-

si mi la r;
Intangible cost, taken into account in the study of the Nordic Council, have a large
contribution to the total cost per patient;
The HEAL study does not correct for cases that resolve naturally, and therefore uses an
incidence of 6% compared to 1% by the Nordic Council and Hauser et al. studies;
The total cost estimates for EDC-attributable cryptorchidism are in the same order of
magnitude with € 18 million and € 363 million (The Nordic Council), € 117
(Hauser et al.) and €18 —65 million (HEAL).

—

130 million

3.6.3. Hypospadias
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
Hypospadias is a male birth defect in which the opening of the urethra is on the underside of the
penis. Treatment requires surgical repair shortly after birth. Although the HEAL study (HEAL, 2014)
suggests that both hypospadias and cryptorchidism are quantified, in fact only costs of
cryptorchidism are estimated. Trasande et al. do not address EDC-related costs for hypospadias.
Consequently, only the Nordic Council study (Olsson et al., 2014) provides a cost estimate for
hypospadias. It is reported that costs are mainly medical cost, however there are also some potential
costs for sick leave of the parents, as well as costs related to secondary effects of hypospadias.
Intangible cost
The study of the Nordic Council includes direct, indirect and intangible costs. A total cost per case of
€39.616 is presented. Especially the intangible cost (0,4 QALY with a cost of € 28.080) makes up a
large part of the total costs (71%) when compared to direct costs (26%) and indirect costs (3%).
Direct costs are relatively straightforward, and include a surgery to correct the abnormally located

urethra opening of newborn boys. This calculation also includes treatment for secondary effects of
hypospadias (urethrocutaneous fistula and urethra stricture). 1f surgery is successful, these boys
should have little or no loss in quality of life due to possible psychosexual impairment. As a result the
authors argue that the discounted QALY value of 0,40, reflecting the intangible cost, should be
considered as a high estimate.
With EDC-attributable fractions of 2%, 20% and 40%, total cost in the EU for hypospadias are € 9
million, € 89 million and t 178 million per year, respectively.
3.6.4. Autism spectrum disorder, (ASD)
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
33

Autism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in
childhood and lasts throughout a person’s life. It affects how a person acts and interacts with others,
communicates and learns. It includes what used to be known as Asperger syndrome and pervasive
developmental disorders (U.S. National Library of Medicine, 2015).
Costs per case per annum
EDC-attributable autism costs were quantified in the HEAL study (HEAL, 2014) and Trasande studies
(Bellanger et al., 2015). Both use studies in which autism costs for the UK were estimated. Besides
cost studies from the US, there are no other cost of autism studies available. Due to a higher living
standard in the UK compared to other EU countries, there is a risk for overestimation of cost when
extra polating these cost to other EU countries.
The study on costs of autism used in the HEAL study is 5 years older, i.c. (Knapp, Romeo, & Beecham,
2009) compared to that of Bellanger et al. i.c. (Buescher, Cidav, Knapp, & Mandell, 2014). Both
studies inciude direct and indirect cost, e.g. accommodation costs, medical treatment and care,
special education, productivity loss from parents and individuals with ASD, voluntary organization
help, welfare benefits and family expenses. The quantification distinguishes between individuals with
and without intellectual disability (ID) and is also disaggregated for different age classes. In addition,
Knapp et al. (2009) also showed different estimations according to place of residence (e.g. living at
home, supported homes, or hospitals).
Costs per annum per case of autism are in a similar range: Kriapp et al. calculates a total cost range
for UK adults between £32.681 per annum (no ID; living in private household) and £97.863 (with ID,
living in a special accommodation or hospital). Buescher et al. (2014) quantify total cost for UK adults
between £47.947 (without ID) and £ 86.099 (with ID). Knapp et al. (2009) provide a wider range of
cost per annum because the study specifies the large difference in costs between individuals who live
in a private home, and those individuals who live in a supported accommodation, while Buescher et
al. inciudes only an average cost per individual for accommodation and residential care.
Lifetime cost and EDC-attributable costs
In both studies, lifetime costs have been estimated. The lifetime costs provided by Buescher et al
(2009) have been discounted with a rate of 3,5% per year, which results in an estimate of £ 0,92
million (no ID) to £ 1,5 million (with ID). In contrast, the lifetime estimate of Knapp et al (2014) is not
discounted and therefore much higher with £ 2,9 million (no ID) to £ 4,7 million (with ID).
Bellanger et al. (2015) used this discounted lifetime estimates to calculate an EU-average lifetime
cost of € 630.000 per individual with autism. An EDC-attributable fraction of 8,88% was calculated,
but finally a value from literature was used (2-10%), further reduced to 0,97%, 2,425% and 4,85% to
correct for double counting coexisting IDs. These fractions were applied to the total number of 8year old children diagnosed with autism (0,62% of the total population of 8 year olds). Accordingly,
these data should be interpreted as “current exposure to this cohort (one year) will lead to a socio
economic loss between € 80 million and 400 million in the future”.
The HEAL study did not use the lifetime estimate for its calculations, but used the total annual socio
economic cost burden for autism spectrum disorders in the UK, which was calculated by Knapp et al.
(2014) to be € 28,4 billion for adults, at present. This amount is based on an assumed prevalence of
ASD of 1%. The UK societal cost were extrapolated to the population size of the EU28, leading to
34

present annual cost of € 226 billion. 1f the EDC-attributable factors of 2% and 5% from the HEAL
study are used, this will yield a result of € 4,52 billion € 11,3 billion annually. This estimate should
therefore be interpreted as “annual costs that could potentially be attributed now to EDC-exposure
-

from the past”. The use of undiscounted values is a main driver for the difference seen with the
calculation of Bellanger et al. The use of higher prevalence rates for ASD and use of costs based on
UK living standards, which are higher than the EU average, provide additional explanation to the
difference between the results.
Clarifications for high lifetime costs for ASD
In general, costs per individual per annum and generated lifetime cost for ASD are very high as is

shown by the two independent studies evaluated above. These high costs can be explained by the
fact that autism is a complex pervasive mental disorder, which lasts throughout a person’s lifetime
and requires lifelong support. It should be noted, however, that cost-of-disease studies using a
bottom-up approach (calculating cost per individual and extrapolating this to the whole population)
tend to overestimate the burden of societal costs (as seen in top-down cost studies, where actual
healthcare expenditures are analyzed and broken down to cost per patient).
Su mm a ry
-

-

Lifetime costs for individuals with ASD are high, especially because of life-long institutional
and residential care are needed;
Behanger et al. estimated a cost of € 80— 400 million for EDC-related ASD, while the estimate
of HEAL is at east one order of magnitude higher with annual cost in the EU28 of € 4,52
billion € 11,3 bilhion;
-

-

Main driver for the difference in the final cost estimate seems to be the use of discounted
lifetime cost (future costs due to current EDC exposure) versus non-discounted hifetime costs
(current costs due to historical EDC exposure).

3.6.5. Attention Deficit (Hyperactivity) Disorder, AD(H)D
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
Attention Deficit (Hyperactivity) Disorder (AD(H)D) are characterized by problems with attention,
impulsivity and (in case of ADHD) hyperactivity. Childhood AD(H)D is likely to persist into adulthood
and may constitute a lifelong impairment.
Costs per case and costs per annum
The costs for EDC-attributable AD(H)D were calculated in the HEAL study (HEAL, 2014) and Bellanger

et al. (Bellanger et al., 2015). The HEAL report based its cahculation on the cost-of-disease study of
Schlander (Schlander, 2007). Bellanger et al. made two calculations for EDC-suspected substances,
one for OPs-attributable cost, and one for PBDE-attributable cost. Both calculations are based on a
recent cost study of Le and co-authors (Le et al., 2014).
There are large differences between these cost studies. The study of Schlander only provides the cost
for AD(H)D medication, which was estimated to be € 56,07 per person per year. In contrast, the study
from Le et al., used various direct and indirect costs derived from a review of seven scientific papers
to estimate the annual cost per individual with AD(H)D. This inclusion of direct cost other than
medication and indirect costs resulted in a much higher estimate, between € 9.860 and € 14.483 per
person with AD(H)D on an annual basis. Bellanger et al. adapted the cost per annum to a ten-year
35

long discounted and EU-wide, estimate per case. This resulted in a total cost of € 77.000 per
md ivid ua 1.
Prevalence and EDC-attributable factor
A prevalence rate of 6,1 % and an EDC-attributable factor of 10,76 % 17,28 % for OPs and 12,53 %
for PBDE was applied by Bellanger et al.. For the two chemicals combined, this resulted in an
estimate between € 2,62 and €4,93 billion annual cost for the EU28.
-

The study of Schlander et al., used a prevalence of 3,9% based on diagnosis among UK children and
adolescents from which 2,54% use medication. Total cost of medications for ADHD in the UK in 2005
was € 91 million (children and adolescents). 1f this extrapolated to EU28 situation and used with an
attributable factor of 2% and 5% for EDCs by HEAL, this results in an estimate of € 14 35 million.
This is only a fraction of the cost calculated by Bellanger and co-authors (approx. 20 times lower),
—

mainly because it does not inciude substantial other costs related to AD(H)D.
Su m ma ry
The large difference between the cost estimates for ADHD caused by EDCs is mostly
explained by the scope of the underlying cost studies (various direct and indirect costs vs.
-

cost for medication only).
-

-

In addition, Behanger and co-authors have used a much higher EDC-attributable factor than
HEAL.
Taken together the overall differences between both studies it may be concluded that the
cost estimations of ADHD in the EU28 by Bellanger et al. appear to be more reahistic,
although the used prevalence rate is rather high.

3.6.6.

IQ loss

A detailed overview of the breakdown of costs and study parameters is given in Annex B.
IQ loss calculations in the EU
The health and economic impacts of EDCs on IQ loss were quantified by Trasande and co-authors and

presented in the paper of Bellanger (Behanger et al., 2015) for two groups of compounds: PBDEs and
OPs. Previously a similar quantification was performed of PBDE- and OPs-related IQ loss in the
Netherlands (Rijk & van den Berg, 2015). The latter report was not published in peer-reviewed
hiterature, but is available onhine (Rijk & van den Berg, 2015). This estimate is used here for
comparison.
For both PBDE and OPs, exposure-response relationships (ERR) are only available from
epidemiological studies in the US. So far, European epidemiological studies have not revealed such
effects. The US ERRs were used to calculate the loss of 0 in Europe. It should be noted that overall
levels of PBDEs in the EU are significantly lower than in the US due to less stringent fire regulations
and less use of PBDEs in the EU. This might lead to uncertainty for estimation of European IQ loss in
the lower exposure regions when using high US PBDE exposure data. In contrast, OPs exposure is at a
similar or higher levels than the US.
In the paper of Bellanger et al., the impact of PBDEs on hO was modelled using an earlier ERR for BDE
47 in cord blood (Herbstman et al., 2010) in the base case scenario, and for sensitivity analysis (high
case scenario) BDE-47 in maternal serum (Eskenazi et al., 2013). PBDE exposure levels were based on

36

varlous studies. For the study of Rijk & van den Berg, there appeared to be insufficient data on BOE47 in cord blood in the Netherlands. Instead, BDE-47 exposure levels in maternal serum are available
(Meijer et al., 2008), which are lower than the reference levels used by Behanger et al. The Dutch
levels were applied to the ERR from Chen (Chen et al., 2014), as this ERR also holds at lower exposure
levels (compared to higher US PBDE levels). In the study of Bellanger et al., PBDE-associated loss per
newborn was estimated to be up to 1,94 10 points, depending on exposure level and scenario. IQ loss
was only expected in the highest exposure groups (75 and 90 percentile exposures). This is similar to
results for the Netherlands estimated by Rijk & van den Berg, were in the 95 percentile group a loss
of 0,96 10 points per newborn was expected (but in a smaller part of the population).
For OPs, Bellanger et al. used two ERRs based on total urinary dialkylphosphate (DAP, OP
metabolites) as a low case (Engel et al., 2011), and a high case (Bouchard et al., 2011). Furthermore,
the weighted average from these two studies was used as a base case estimate. In the Dutch study,
an ERR was used from the study of Bouchard only, as this ERR is based on exposure levels
comparable to the relatively high OP exposure levels observed in the Netherlands (Ye et al., 2009).
With 0 7,01 10 points, the OP-associated IQ loss was significantly higher than for PBDEs (Behanger
et al., 2015). For the Netherlands, a smaller loss of 1,69 to 5,12 10 points per newborn was calculated
-

(Rijk & van den Berg, 2015). One crucial difference is that in the Dutch study, loss of IQ was
calculated relatively to the median exposure level in the US, to correct for differences in exposure
levels and related responses between the Netherlands and the US. In the study of Bellanger et al.,
also effects at lower exposure levels were calculated.
Value of IQ points
The only available approach to value IQ loss is based on the lifetime economic productivity loss per
0 point, is based on US studies. There are no directs costs (such as healthcare costs) quantified, and
cost therefore do not represent actual expenditures. The comparison with the US might not be oneto-one applicable to the EU, as there is more heterogeneity in income in the US, however no
European approaches are available.
The loss of one 10 point has been related to a 2% decrement in lifetime economic productivity (1.762.39% sensitivity analysis). This value of 2% (US EPA, 1997) consists of a direct effect of 10 on wage of
0.5%, combined with two indirect effects, namely 1.0% forless schooling and 0.477% for reduced
labor force participation (Ashenfelter & Ham, 1979; Krupnick et al., 1989; Needleman, ScheI!,
Bellinger, Leviton, & AlIred, 1990).
Similar to earlier studies, Bellanger et al. valued one lQ point at $ 19.269, which is discounted and
adjusted for historical changes in the Consumer Price Index. This was further adjusted to country
specific purchasing power panty (PPP) adjusted per capita gross domestic product (GDP). This
resulted in an average value of € 9.600 lifetime loss per IQ point. In the Dutch study, the best
estimate for 2% loss of hifetime earnings in the Netherlands corresponded to a (not discounted) value
of€ 12.120 (Rijk & van den Berg, 2015).
Socio-economic impact of lQ loss
According to these calculations, billions of 10 points have been or will be lost in newborns that are
exposed to PBDEs and OPs. Bellanger et al. estimated the loss of 873 000 (149 000— 2,02 million) IQ
points due to exposure to PBDEs, and the loss of 13,0 million (4,24— 17,1 million) lQ points due to OP
exposure. This leads to cost estimates for the EU28 are in a range of € 1,43 19,4 billion for PBDEs
—

37

and €40,8— 164 billion for OPs, annually. Similarly, annual cost in the Netherlands were estimated to
be € 100 million (€ 2 196 million) due to PBDE exposure (Rijk & van den Berg, 2015). When this is
extrapolated to EU28 based on population only, this would be a total of cost of € 3 billion (€ 60
million 5,9 billion) on the basis of 248 000 10 points lost (5500 —484 000). For OPs, Dutch estimates
—

—

were € 2,7 billion (€ 1,1 4,4 billion) annually (Rijk & van den Berg, 2015). This would correspond to
annual cost of € 81,3 billion (€ 31,9 130,1 billion) for EU28, based on 6,7 million IQ points lost (2,6—
10,8 million). It should be noted that in the extrapolation from cost in the Netherlands towards EU28
-

—

costs, no correction factors for GDP-PPP were applied.
The socio-economic impacts of 10 loss are entirely based on indirect effects. Costs do not include
direct costs (actual expenditures). Nonetheless, these estimates indicate that EDCs can have a large
socio-economic impact on society via IQ loss.
Other trends in IQ
It is not dear how the EDC-attributable loss of IQ contribute with other trends that are seen for IQ.
For example, some studies have reported an increase in IQ over the last decades (Mingroni, 2007). t
could be argued that a definition of “foregone” 10 points would be better applicable instead of 10
points lost. As a result, a different methodology (e.g. Willingness To Pay (WTP)) to value socio
economic costs of EDCs might be needed in order to provide an estimate that takes into account the
reduced increase in IQ.
Su m ma ry
10 loss has been quantified for the EU in the paper of Bellanger et al. and for the Netherlands
-

-

by Rijk & van den Berg;
Based on different, but comparable ERRs and exposure levels, both studies showed that best
estimate for annual PBDE- and OPs- related 10 loss in the EU is expected of 248 000
000 10 points for PBDE and 6,7 million 13 million for OPs;

—

873

—

-

-

10 points are valued using US EPA approaches, calculating indirect costs only (lost lifetime
economic productivity);
Annual economic losses in the EU are estimated to be between € 60 million and € 19,4 billion
for PBDE, and between € 32 billion and € 164 billion for OPs.

3.6.7. Mental retardation
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
EDC-attributable cost for mental retardation
The economic loss for EDC-attributable mental retardation (also called intellectual disability ID) is
calculated using the same exposure-response relationships for PBDE- and OPs-related IQ as
described above for 0 loss, and presented in the paper of Bellanger (Bellanger et al., 2015) in the
series of Trasande and co-authors. However, there is no overlap in cost estimates for 10 loss (as
described in 3.6.6) and mental retardation. No other reports are available that estimate the socio
economic effect of EDCs via mental retardation.
-

The EDC-attributable cases of mental retardation are based on an increase in number of individuals
that can be classified as mentally retarded (10 < 70) if the whole 10 distribution curve shifts several
points to the left (lower side) due to an EDC-related decrease in 10. Using this approach, it was
modelled that 3290 (544-8080) extra cases of mental retardation would be attributable to PBDE. For
OPs, 59.300 (16.500-84.400) extra cases of mental retardation were estimated. This approach
38

assumes a normal distribution for 0 in the population and an equal effect of EDCs among all 10
levels. And similar to IQ loss calculations, an increasing trend in overall 10 is not taken into account
here.
Direct costs for mental retardation per individual
The total average cost of an individual with intellectual disability in EU28 is estimated to be € 360.000
(discounted lifetime cost per capita, assuming a mean life span of 50 years). This estimate is
calculated from annual direct costs of € 10.334 per individual based on several EU studies
(Gustavsson et al., 2011; Olesen, Gustavsson, Svensson, Wittchen, & Jönsson, 2012; Polder,
Meerding, Bonneux, & Van Der Maas, 2002). In contrast to the value of 10 points, the annual cost of
an individual with ID inciudes a wide range of direct cost (healthcare and non-healthcare), e.g.
pharmaceutical care, hospital care, institutions, activities, nursing/home care, and administration.
However, while only direct cost estimates are available, it is recognized that indirect costs (e.g.
income and productivity losses) are also substantial. Behanger et al. has also calculated indirect cost
as income loss due to lost 10 points (paragraph 3.6.6). Again, there is no overlap in cost estimates of
10 loss and mental retardation; in fact the costs are additive. Furthermore, there is also no overlap
with costs of ASD, as the calculations for ASD have been adjusted for double counting by coexisting
ID among individuals with ASD.

Cost for mental retardation in the EU related to PBDEs and OPs
Total aggregated cost for PBDE- and OPs-related intellectual disability were estimated by Behanger et
al. to be between € 6,1 and 33,4 bilhion (average of € 22,6 billion). 1f these costs are compared to cost
estimates of ID based on actual attributable expenditures within healthcare budgets, it was dear that
indeed the costs for ID are high and make up 9% of national health care budgets in the Netherlands
(Polder et al., 2002). In 2010, total cost for ID in the EU were found € 43,3 billion (Gustavsson et al.,
2011).
Su mm a ry
-

-

-

Intellectual disability (ID) has been quantified for the EU in the paper of Bellanger et al. only,
assuming a shift in IQ curve of the general population due to PBDE- and OPs related 10 loss;
It is calculated that 17 000 92 000 extra cases of ID are expected, with aggregated costs of
between € 6,1 and 33,4 billion (average of € 22,6 bilhion) for the EU per year;
—

Only direct costs are included in the estimate, therefore there is a risk that these costs are an
underestimate of real socio-economic costs of this effect.

3.6.8.

Breast cancer

A detailed overview of the breakdown of costs and study parameters is given in Annex 8.
Socio-economic loss due to EDC-attributable breast cancer, as well as prostate cancer, was calculated
by the authors of the HEAL study only (HEAL, 2014). It was based on calculations of a recent EU-wide
study (EU27) that estimated societal costs of four common cancers (breast, prostate, lung and
colorectal cancer) (Luengo-Fernandez, Leal, Gray, & Sullivan, 2013). In this study, direct healthcare
costs and indirect productivity losses from patients and caregivers were generated for each specific
country, as well as average costs for EU27 as a whole. The HEAL study included only minor
adjustments with respect to the extrapohation to EU28 (including Croatia) and an adjustment of the
costs from 2009 to 2012.

39

The annual economic cost in EU28 due to breast cancer was estimated € 16 billion. The HEAL study
set an EDC-attributable fraction of 2% and 5% for breast cancer, which amounts to an annual EDC
attributable cost estimate of € 320 to 800 million.
3.6.9. Prostate cancer
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
Similar to the calculation of the EDC-attributable costs for breast cancer, the HEAL report (HEAL,
2014) presented a calculation of EDC-attributable cost of prostate cancer using the study of Luengo
Fernandez et al. (Luengo-Fernandez et al., 2013). This study calculated annual economic cost in EU27
due to prostate cancer to be as € 9,04 billion, which is about half of the cost calculated for breast
cancer. This difference can be explained (at least partially) by higher productivity losses due to
morbidity and mortality for breast cancer, compared to prostate cancer. When using again an EDC
attributable fraction of 2% and 5%, the annual EDC-attributable cost estimate would be in the range
of € 180 to 450 million for prostate cancer.
The use of a recent, EU-wide paper on direct and indirect cancer costs certainly increases the
strength of the cost estimate for breast and prostate cancer.
3.6.10. Testicular cancer
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
The EDC-related costs of testicular cancer were provided in the studies by the Nordic Council (Olsson
et al., 2014) and in the paper of Hauser et al. (Hauser et al., 2015). The costs of testicular cancer used
in the publication of Hauser et al. were largely based on those calculated by the Nordic Council.
However, total annual costs for EUZ8 attributed to EDCs are substantially different: The Nordic
Council report estimates a range of € 25
range of € 313 —848 million.

—

499 million, whereas Hauser and co-authors calculates a

Cost calculations
The authors of the Nordic Council report used data from Swedish patient registers, which were
further extrapolated to the EU28 situation. It should be noted that these costs might not reflect cost
levels in other EU countries. Also direct healthcare (surgery and care), productivity loss, and
intangible cost were included in the cost estimate of the Nordic Council. All costs were discounted for
35 years, which is the average age at which testicular cancer occurs. Especially the intangible costs
are high, with a discounted value of 1,09 QALY valued at € 76.740 in total. This makes up over 90% of
the total lifetime cost per case of testicular cancer. Total cost per case was € 80.980.
Although Hauser et al. (2015) based their calculations on the Nordic Council study, the cost estimate
per case is with approximately € 124.000 per case 50% higher than in the Nordic Council study. The
exact cause to this difference is unknown. Some adjustments have been performed in the study of
Hauser et al., e.g. country-specific GDP and medical cost inflation. However, this cannot entirely
explain the difference between both studies. Another contributing factor might be that non
discounted QALYs have been used to estimate intangible cost in the Hauser et al. study.
EDC-attributable fraction
Hauser et al. (2015) calculated the EDC-attributable fraction (AF) to be 35,5% in its base case
scenario, and 13% in its low case scenario). The base case AF was calculated using PBDE
40

concentrations from one study only, which was considered to be representative for the EU
population. The EDC-AF at lower exposure levels was calculated combining PBDE concentrations
from nine studies. Despite the different approaches, the calculated EDC-attributable fraction of
Hauser et al. is similar to the generically chosen mid- and high estimate of 20% and 40% by the
Nordic Council.
Su mm a ry
There is a difference between cost estimates of the Nordic Council (range of € 25 499
million) and Hauser and co-authors (€ 313 848 million), while the estimate of Hauser et al.
is based upon the Nordic Council study. The exact explanation is not known;
-

—

—

-

-

The estimates include a large part of intangible costs (90%);
Attributable fractions based on calculation using ERRs (13% and 35,5%) are similar to those
based on estimations from the Nordic Council (2%, 20% and 40%).

3.6.11. Obesity
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
EDC-attributable cost for obesity was quantified in the studies by HEAL (HEAL, 2014) and Trasande
and co-authors as presented in the paper of Legler et al. (Legler et al., 2015).
Calculation of costs by HEAL
The calculation in the HEAL study is based on a European Commission working paper on nutrition,
overweight and obesity in which it was estimated that costs for obesity would be 0,3% of the GDP (in
2005). This includes direct healthcare cost and productivity loss from morbidity and mortality
(European Commission, 2007). For including overweight, this figure could be doubled. Applying this
percentage to EU25 and using the 2005 GDP, yields a cost estimate of € 81 billion for obesity and
overweight combined. The HEAL study proposed an EDC-attributable fraction of 2% and 5%, which
results in a cost range of € 1,62 billion —4,05 billion for obesity and overweight. This amount could be
an underestimation for various reasons, e.g. these costs were not further adjusted to the EU28
situation and present GDP. In addition, the costs of overweight and obesity for children were not
taken into account in the EC report. Cost of Iower wages, psychiatric disorders (e.g. depression) and
intangible costs are recognized in this reports as contributing factors, but were not taken into
account., It should also be noted that it is uncertain exactly what kind of obesity-attributed health
effects were taken into account. Part of the overweight costs were addressed to diabetes in the EC
report, while HEAL assumed that these costs are separate and additive.
Calculation of costs by Legler et al.
The approach followed by Legler and co-authors to calculate EDC-related costs for obesity is more
complex and requires further evaluation. Three situations are modelled: DDE-attributable child
obesity (based on an exposure-response relationship for children at the age 10 (Iszatt et al., 2015)),
BPA-attributable child obesity (for children at age 4 (Valvi et al., 2013)), and phthalate-attributable
aduft female obesity (relation only found for females, not for males (Song et al., 2014)). The three
situations use different cost studies and adjustments.
The cost estimate for child obesity is based on a recent meta-analysis (Finkelstein, Graham, &
Malhotra, 2014), which provides an estimate of incremental direct medical cost during the lifetime of
an obese child relative to a normal-weight child, who maintains normal weight throughout
adulthood. Indirect or nonmedical costs (e.g. productivity loss), and health-related quality of life
41

were not inciuded in this meta-analysis by Finkelstein et al.. For DDE-attributable child obesity
starting at age 10, direct medical incremental lifetime costs were € 15.820 per person (after
adjustments by Legler et al. for currency and PPP per capita-GDP). Using the same source study
(Finkelstein et al., 2014), BPA-attributable child obesity costs were estimated to be € 66.500 per
person. Because this was originally a cost estimate for obesity acquired at the age of 4, Legler and co
authors added additional years and costs that added up to a total of € 48.500 per child. Despite the
citation of four papers, It is not dear from the study of Legler et al. how and what type of costs were
added to account for additional obesity cost between age 4 and 10. Stili, it is a substantial addition to
the original cost as specified by Finkelstein, especially considering that annual obesity-related costs
have been shown to start small and increase with age (Finkelstein et al., 2014). Furthermore, for
DDE- and BPA attributable child obesity, different chemical-specific ORs and age-specific obesity
prevalence were used. A lower EDC-attributable factor was used for DDE-related child obesity at the
age of 10, which leads to a substantial difference in the cost estimates. As a result, the costs of
obesity for DDE were estimated between € 24,6 and 86,4 million, while those for BPA were
estimated € 1,54 billion.
To determine the cost of phthalate-attributable obesity for adult women two studies were used to
provide estimates on the total annual cost by direct health care cost (Cawley & Meyerhoefer, 2012)
and intangible cost (Muennig, Lubetkin, Jia, & Franks, 2006). The direct healthcare cost (medical
expenditures) were compared to those of a biological, non-obese, relative (Cawley & Meyerhoefer,
2012). Annual costs were aggregated over 15 years and discounted by 3% to produce an average
lifetime estimate for additive medical expenditures of€ 21.500 per person. In addition, it was found
that obese women lived 7,2 QALYs less (Muennig et al., 2006). These QALYs were incorrectly
mentioned in the Legler paper as DALYs. Legler valued one DALY (QALY) at $ 50.000. Although the
interpretation and use of a DALY (reduction in “healthy” years) is different from a QALY (gain of years
living in good quality of life) cost estimates for DALYs and UALYs are comparable. Therefore, this
confusion does not have an effect on the final cost estimate. Also, ten years of discounting was
applied to the QALYs, resulting in the total lifetime (intangible) cost of € 268.000 per female.
There is a large difference in the obesity cost estimate per person in the above three exposure
scenarios, which is caused by the different scope of the cost studies and the age of disease onset. By
taking QALYs into account, the cost estimate for phthalate-attributable female adult obesity is with €
15,6 billion much higher compared to DDE- and BPA-attributable childhood obesity (1,56 billion).
Su mma ry
The cost estimate per capita for phthalate-attributable female adult obesity is € 15,6 billion
while DDE- and BPA-attributable childhood obesity combined lead to annual costs in the EU
of 1,56 billion;
Calculations for EDC-related female adult obesity includes a large part (over 90%) of
intangible costs, therefore total costs for adult obesity are higher compared to childhood
obesity which includes only direct medical costs.
-

-

3.6.12. Diabetes type 2
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
Both the HEAL study (HEAL, 2014) and Trasande studies (Legler et al., 2015) combined in their
estimations on the costs of diabetes type 1 and 2. Per case, the economic burden of diabetes is
42

greater for type 1 than for type 2, and the difference increases with age (Dali et al., 2009). In total,
the prevalence of type 2 is significantly greater than the prevalence of type 1, so type 2 is responsible
for most of the economic burden of diabetes (91,4%) (Dall et al., 2009).
Annual cost and lifetime cost
The HEAL study based its estimate on a survey and study on direct healthcare and indirect non
healthcare costs of diabetes in five EU countries (Spain, UK, Germany, France and ltaly) (Kanavos, van
den Aardweg, & Schurer, 2012). The total cost for these countries is then extrapolated to EU28 based
on population size, leading to an estimate of€ 300 billion. The HEAL study estimates EDC attributable
costs between € 6 and € 15 billion annually, with EDC-contributable factors of respectively 2 and 5%.
As a result, the annual cost per person, using an EU prevalence of 6% (30 million individuals with an
age between 20 and 79) would be € 10.000.
Legler and co-authors estimated the costs for diabetes based on the results of a worldwide study on
diabetes in 193 countries (Zhang et al., 2014). Although the methodology and type of costs that were
included varied between countries, it can be expected that these costs mainly represent direct
healthcare expenditures (as it based on a top-down approach). The average annual cost per person
in the EU was calculated to be $ 1927 (in International Dollars), which is considerably Iess than the
annual cost of € 10.000 calculated in the HEAL study. Legler and co-authors converted this annual
amount to Euros and Iifetime cost (15 years with a discount rate of 3%) to € 29.600 per person.
EDC-attributable fraction
Next, in the HEAL study, EDC-attributable fraction was derived from two specific EDCs DDE and
phthalates for which there are epidemiological studies available (Sun et al., 2014; Wu et al., 2013).
The subsequent cost estimates in this study are for both compounds Iess than one billion Euro in the
base case exposure scenario (together € 1,44 billion), which is much lower compared to the total
estimates of the HEAL study (€ 6 15 billion).
-

—

—

In the publication of Legler and co-authors 20.500 phthalate-attributable cases of diabetes were
estimated, which amounts in a total arinual socio-economic cost burden of € 607 million in the EU28.
OnIy a base case scenario for phthalate-attributable diabetes was calculated, no sensitivity analysis
was provided.
For DDE, both a base-case and sensitivity analysis (high case) was provided in the Legler et al. study.
In the base case scenario an odds ratio (OR, a rate for increased risks compared to unexposed
groups) of 1,25 was used for DDE (Wu et al., 2013). This leads to 28.200 cases of diabetes in the EU
that were attributable to DDE, which results in total costs of € 835 million. However, in the sensitivity
analysis (high exposure scenario) of the Legler study, the DDE-attributed costs are even higher than
the upper estimate in the HEAL study. For this latter estimate for DDE-related diabetes, an OR of 7,1
was applied (Turyk, Anderson, Knobeloch, mm, & Persky, 2009), which results in 564.000 DDË
attributable cases at a cost of € 16,6 billion in total. This is a large difference between the ORs of
both studies. The EDC-attributable factors are derived from two different ERRs; the base case
attributable factor is derived from a near significant result from a meta-analysis on DDE (95% CI 0,941,66) (Wu et al., 2013), while the high scenario is based on one study by Turyk et al. (Turyk et al.,
2009). Therefore, the sensitivity analysis (high exposure scenario) should most likely be interpreted
as a worst-case scenario. Still, the amount of DDE-attributable cases (564.000) is similar to those

43

estimated in the HEAL study in its lower range, with 600.000 attributable cases (2% of 30 million
diabetics).
1f taking the base case scenarios from Legler and co-authors, the percentage of EDC-attributable
cases is much lower than the 2% or 5% used in the study of HEAL. This difference is the driving factor
between the distinct estimates for EDC-attributable cost of diabetes in both studies for the EU. (t
should be noted that the study of Legler only provides an estimate for two EDCs while HEALs
calculation estimates the combined effect for all EDCs.
Su m ma ry
The cost estimates per individual with diabetes are very different between HEAL (€ 10.000
-

per year), which inciudes both direct and indirect costs, and the study of Legler et al. (lifetime

-

-

-

cost of€ 29.600), including only direct cost;
HEAL calculated a total annual cost range for the EU of € 6— 15 billion for diabetes, while the
range calculated by Legler et al. was wider with € 1,44 and 17,2 billion;
In the base case scenario, Legler et al. calculated much lower attributable fractions leading to
much lower amount of cases compared to HEAL, and therefore much lower costs in the
lower estimate;
The large difference between the lower and upper estimate in the study of Legler is related
to a worst-case estimate amount of DDE-attributable cases (not related to phthalate). The
amount of cases, however, is similar to the amount of EDC-attributable diabetes cases
estimated by HEAL in its 2% estimate.

3.6.13. Increment death rate
A detailed overview of the breakdown of costs and study parameters is given in Annex B.
The cost for this health effect has been modelled in the Trasande studies by Hauser et al. (2015). The
increment in death rate among men with a lower Testosterone (T) was based on the combination of
two relationships: two phthalates lowered T in men aged 40-60 (Meeker & Ferguson, 2014) and
decreased T leads to increased death rate among men aged 55-64 (Araujo et al., 2011). The phthalate
study did not find such health effects for other age groups, other phthalates (13 metabolites were
assessed in total), and for women. In addition, potential other effects of lower T levels on death rate,
such as possibly a lower incidence of prostate cancer, were not considered. The combination of these
two assumed relations, provide low strength to the link between phthalate and increased death rate
in man, decreasing the certainty of the cost calculation for this health effect.
Indirect socio-economic cost
Only indirect non-healthcare cost to the increment of deaths was estimated by calculating lifetime
economic productivity loss due to early death (Max, 2013). This paper was not published in peer
reviewed, public literature and was only cited in the supplemental material by the paper of Hauser et
al.. Therefore, we were unable to specify or verify these costs any further. Hauser et al. describe that
the cost was adjusted to an amount of € 320.700 per capita. The annual amount of deaths among
men in the age group 55-64 in the EU is 241.000, of which 10,3% was calculated by Hauser et al. to
be attributed to phthalate exposure based on the above mentioned assumptions. This leads to a
total cost estimate of approximately € 8 billiori.

44

4. Gaps and needs in “cost of EDC” estimates: a way forward using a
modular approach
So far, the existing modelled socio-economic impacts of EDC-attributable costs are only based on a
subset of the diseases that are linked to EDC exposure. Existing gaps in health-related cost estimates
are identified in this chapter. Here, we propose a so-called “modular approach” that consists of
“building blocks” of knowledge on certain EDC-related diseases and their socio-economic impacts.
We apply this approach to a selected group of EDC-related health endpoints that have not been
modelled before (endometriosis, neural tube defects and asthma), and two EDC-related health
endpoints quantified earlier (ADHD an ASD). As such, data is provided on EDC-attributable socio
economic cost that have (not) been addressed in earlier studies, as well as information is deemed
relevant for their interpretation. The modular approach provides a structured way to add new
information on socio-economic cost of EDC-related health impacts in the future.
We argue that more structure, transparency, uniformity and completeness of information on socio
economic cost estimates is needed to enhance interpretation and comparability between estimated
cost of different health effects. However, this methodology could also be applied in a broader
perspective, to analyze any other health impact, potentially causal agent, and associated socio
economic costs.

4.1.

Why a modular approach?

The existing modelled socio-economic burdens of EDC-associated health effects are based on a
subset of the diseases that have been associated with EDC exposure (see Table 1). Hence, it could be
argued that current EDC-related cost estimates represent “the tip of the iceberg” only. Additionally,
the attributable fraction of EDCs to the onset of a disease might an over- or underestimation.
Therefore, a flexible method is needed to implement progressing knowledge in these cost estimates
and add novel cost estimates for EDC-associated health effects.
In the previous chapter, we have provided explanation on the (differences) in cost estimates for EDC
associated diseases and the uncertainties around these estimates. In this chapter, we introduce a
modular approach to improve the transparency and understanding of socio-economic cost
estimation of EDC-related health impacts. For that, we will:
Identify gaps and needs on disease- and EDC-related information that is relevant for the
-

-

-

modelling of socio-economic cost of various EDC-related health effects;
Propose a standardized approach for presenting socio-economic costs, that allows inclusion
of information that is relevant for the interpretation of data on socio-economic cost;
Apply and provide this information for a selection of EDC-related health effects.

Considering the increasing knowledge of EDCs and their potential health impact, new diseases,
disorders and conditions can be added to this overview, along with an estimate of their potential
socio-economic costs. As such, this modular approach can gradually lead to a more complete
understanding of the (potential) socio-economic costs of EDCs in Europe.

45

4.2.

Methodology

The quantified health endpoints in other EDC-cost studies (Table 4) are compared to the total list of
identified potential EDC-related health endpoints (Table 1) in order to identify main gaps in types of
quantified endpoints. Next, an explorative literature search of cost-of-disease studies was performed
to identify whether healthcare cost of these identified health effects have ever been quantified
before, irrespective of the link with EDCs. For that, Scopus and Google were searched for the health
effect + “socio-economic”/ “economic” + “cost” / “burden” / “impact”. Then, an assessment was
carried out to identify what information would be needed to enhance the understanding of the
disease itself, the potential link between the disease, EDCs and ED-modulation, and an interpretation
of socio-economic cost of health effects. This modular approach of information gathering was
exemplified with three health effects that not have been modelled 50 far, ie. endometriosis, asthma
and neural tube defects, and two health effects that have been modelled before, i.e. AD(H)D and
ASD. The relevant information was aggregated in a single fact sheet per health effect to provide a
dear overview.

4.3.

Data gaps in cost of health effects

As mentioned in Chapter 2 (Table 1), we have identified more than 80 different (potentially) EDC
related health endpoints, of which 13 health endpoints were quantified in previous studies of cost of
EDC-related health effects (Chapter 3) (Behanger et al., 2015; Hauser et al., 2015; HEAL, 2014; Legler
et al., 2015; Olsson et al., 2014; Trasande et al., 2015). This leaves a large part of the potential EDC
related health effects from Table 1 unquantified. These mainly comprise of:
-

Female reproductive effects: only female sub- and infertility was partially included in the
calculation of HEAL;

-

Immune-related disorders: no health effects quantified;
“Other” EDC-related disorders (such as thyroid effects and neuroendocrine diseases): only
one population effect on earlier death of males was quantified (Hauser et al., 2015).

The lack of quantified endpoints for immune-related disorders and the group of “other” EDC
associated effects could partiahly be attributed to the fact that the role of EDCs in immune diseases
did not come into focus until recently and/or are more debated. Consequently, there are large data
gaps regarding the effects of potential EDCs on immune disorders. However, for female reproductive
effects there are many studies available assessing the relation to EDCs, also in humans, such as
female reproduction effects in relation to DES exposure.
For most of the identified EDC-associated health effects, cost estimates were available. However, for
21 health endpoints no or limited studies were identified that quantified socio-economic costs of
health effects. These endpoints are listed in Table 7. Due to the challenging character for providing a
cost estimate for some endpoints, it is reasonable to assume that not all health effects will be
quantified in the future. For instance, socio-economic costs of a shift in sex ratio (decline in male
population) will be extremely difficult to quantify.

46

Table

7.

Resuits

(potentially)

No

(N)

of

related

the

to

quick

EDCs,

scan’

to

of which

no

identify

or

limited

gaps

in

studies

data

are

availability

available

of

or limited (L) cost estimate available

Female

Reproductive

cost-of-disease

that quantify

studies:

health

effects

costs.

Comment

problems

—

Reduced female fecundity (lower number of offspring

N

Disturbed (decreased( lactation period

N

Abnormal vaginal, cervical, uterine, and oviduct anatomy

N

Reproductive tract abnormalities at the ovaries.

L

Premature thelarche

N

Female idiopathic precocious puberty / early menarche

L

Female delayed puberty

L

Disturbed menstruation cycle (Oligomenorrhea)

N

no cost estimate, but might be related to IVF
and pregnancy outcomes
1 direct cost estimate (abstract only)
Not available, but potentially such costs
have been modelled as a side effect of
diabetes/obesity

Male reproductive problems
Male reproductive organ abnormalities other than hypospadias and cryptorchidism
(reduced testis weight, abnormal small penis, problems efferent ducts, altered AGD,
morphology of seminiferous tubules, nipple retention)
Testicular dysgenesis syndrome (TDS)

N

1

N

Neurobehavioral disorders

—

Psychornotor retardation, memory, learning problems

L

one paper cost learning problems from 1995

N

Is a positive effect, not a disease

N

should be further specified what kind of
infections

Hormone-related cancers (none(

Metabolic syndromes
Cardio protection

Immune function, immune diseases and disorders
lncrease of systemic infectious diseases due to altered immune response (as a
whole)

—

lncrease of local infections due to altered immune response (as a whole)

N

Exanthema subitum

N

Autoimmune thyroid disease (AITD( (e.g. Hashimotos thyroiditis, idiopathic
myxedema, asymptomatic thyroiditis, endocrine exophthalmus, and Graves’

N

should be further specified what kind of
infections

disease(’

Other
Sex ratio

-

declining male population

N

Neuroendocrine disruption: Various diseases that affect the pituitary or
hypothalamus

N

should be further specified

Adrenocortical hyperplasia (growth, stress response(

L

congenital variant; cost-effectiveness

Adult (sub)hypothyroidism

N

to be further specified by impacts

Thyroid resistance syndrome

N

neonatal screening

47

4.4.

Identification of relevant information for the set-up of a modular
approach for EDCs

An essential point within the modular approach is the presentation of socio-economic cost.
Therefore, the health effects for which no or very limited data is available on socio-economic cost
(Table 7) were not considered further in this report. For the other EDC-related health effects, general
information on healthcare cost is available. Below we propose information deemed relevant for the
interpretation of cost:
-

-

-

-

-

A general description of the disease, such as development of the disease, key characteristics
and diagnosis;
Possible treatment of the disease (this could be, but is not necessarily related to what has
been included as socio-economic cost, as literature sources used for both elements might
differ);
Endocrine mechanisms or pathway(s) involved in the diseases (as mentioned in prevailing
reviews on EDCs and health effects, such as EU, UNEP/WHO);
Statements on the role of EDCs and (potential) strength of the link with endocrine disruption
(as mentioned in prevailing reviews on EDCs and health effects, such as EU, UNEP/WHO);
Potential EDCs (or groups of EDC5) that have been associated to the health effect, their key
references (from source epidemiological studies) and comments on observed relations. This
information is relevant because it could provide a starting point for defining priorities for
further studies and actions;

-

Comorbidities. These are additional disorders or diseases (or their effect) potentially co
occurring with the primary disease or disorder. They provide an insight to possible relations
between health effects. Comorbidities could be, but are not always, taken into account in the
cost-of-disease estimates. Accounting for comorbidities will increase the risk for double
counting of costs. On the other hand, information on co-morbidities is very relevant to
provide a complete estimate of potential socio-economic costs of health effect of specific
compounds;

-

-

Current incidence (newly diagnosed cases of a disease) or prevalence (number of cases of
disease existing in a population). This provides information on the extent of the disease
burden (population affected). Preferably, a recent, aggregate estimate of incidence or
prevalence for the EU28 is available, as it varies between countries and among time. In
addition, trends in incidence or prevalence could also be provided;
Socio-economic cost estimate, which provides an indication on the impact of the disease on

society. It is recommended that the cost information includes:
o Key Iiterature reference, for traceability of presented numbers;
o Type of costs taken into account (direct, indirect and intangible cost) in order to
interpret completeness of the cost data and compare results with other studies and
health effects;
o Cost estimate, as reported in the original study without adjustments;
o Extrapolation to total annual cost in the EU28, so that the quality and extent of
modification of the original study can be judged;
o EDC-attributable fraction to be applled (see comments below);
o Annual EDC-attributable cost for EU28. Finally, this present a best estimate (range)
towards the potential socio-economic impact of EDCs.

48

All the presented information, such as cost data, incidence/prevalence, is based on a selection from
available literature. Together, this information presents a summary and an overview of the current
state of knowledge from prevailing literature, without pretending to be ali-inclusive.
Presentation of modular approach: factsh eet
We propose to visualize the information in a structured manner by means of a factsheet per health
effect. In the factsheet, a concise summary of the relevant information (as identified above) can be
provided. Over time and to meet specific needs, different types of information (categories) could be
added, deleted or changed on the factsheets. Furthermore, the information on the factsheets need
to be updated on a regular basis. This is especially the case for progressive scientific insights on EDCs,
endocrine disruption and endocrine pathways/mechanisms. It is recommended to update the EDC
related information in concordance with updated publications on large, authoritative reviews, such
as from the Endocrine Society, the EU (or EU bodies), and UN organizations such as the UNEP and the
WHO. Regular update of information on disease incidence/prevalence, and socio-economic costs is
also recommended.
Estimation of disease-specific socio-econoinic cost
The use of an EU-wide cost estimate is preferred. However, EU-wide studies are scarce and the
quantification and extrapolation of non-EU or single country cost data towards the entire EU leads to
high uncertainties. 1f a single-country estimate is available, an EU-wide can be generated by scaling to
population size only. This approach was used previously by HEAL and the Nordic Council in their EU
estimate of EDC-attributable cost. We used this approach also in this report for the selected diseases
(neural tube defects, asthma and endometriosis). Extrapolation could be improved in the future by
using more evidence-based correction factors such as medical inflation, GDP-PPP, EU
prevalence/incidence rates and combining and weighting of different EU studies.
Range in EDC attributablefractions proposed for this modular approach
As discussed in section 3.4, one of the key challenges is to attribute a certain etiological fraction of
the total disease cost, to a single cause, in our case exposure to EDCs in general or of specific
chemicals. This is challenging because exact causes of disease development are usually not known,
and often considered to be a complex interaction of e.g. genetic, dietary, environmental,
occupational, behavioral aspects.
Previously, institutes have estimated the contribution of environmental factors to disease. In 2006,
the WHO estimated that globally, nearly one quarter of all deaths and of the total disease burden can
be attributed to environmental factors (WHO, 2006). This included modifiable parts (or impacts) of a
wide range of environmental factors, such as pollution of air, water, or soil with chemical or
biological agents, UV and ionizing radiation, noise, electromagnetic fields (EMF), occupational risks,
the built environment, agricultural methods, climate- and ecosystem change, and hygiene (behavior).
In contrast, a study on OECD countries concluded that 2.1% 5.0% of the overall disease burden was
attributable to the environment (Melse & De Hollander, 2001). The differences are, at least partially,
explained by differences in methodology used and research scope, as well as differences in risk
factors between industrialized and developing countries.
-

Only considering attributable fractions for chemical exposures, t was estimated in 2004 that globally
8.3% of deaths and 5.7% of DALYs were attributable to environmental exposure and management of
selected chemicals (Prüss-Ustün, Vickers, Haefliger, & Bertollini, 2011). However, chemicals with
49

known health effects, such as dioxins, cadmium, mercury or chronic exposure to pesticides, were not
included in that study due to data limitations. Another, earlier study on the environmental
attribution of pollution, provided a similar estimate of 8—9% of the total disease burden (Briggs,
2003). Furthermore, disease-specific estimates towards the attribution of pollution were made,
including diseases such as asthma, allergies, cancer, neuro-developmental disorders, congenital
malformations, effects of ambient air pollution on birth weight, respiratory and cardiovascular
diseases and mesothelioma (Mathews 1., 2005), thereby providing a more disease-specific insight in
the role of environmental pollution. However, it should be noted that most of the literature on EDCs
and its role in the development of diseases has been generated in the past 10 years. The inciusion of
these new insights could substantially improve the estimations of attributable fractions.
The estimates of environmental attributable fractions (EAF), or if available attributable fraction
estimates for (chemical) pollution, can be used as a kind of upper limit to EDC-attributable fractions.
For our modular approach, we chose 1%, 2,5% and 10% as best estimate EDC-attributable fractions.
The 1 and 2,5% point estimates are well within the (lower) EAF ranges presented in the previous
mentioned papers of WHO and OECD, both for general environmental factors as for the contribution
of pollution or chemicals specifically (Briggs, 2003; Melse & De Hollander, 2001; Prüss-Ustün et al.,
2011; WHO, 2006). Beside the lower estimates, it must be recognized that for some diseases,
environmental factors play a larger role in disease development and/or there is a stronger plausibility
for hormone-related effects and evidence for the contribution of hormone disruption (e.g. certain
hormone-related birth defects). Therefore, as an upper limit of the EDC-attributable fraction, we
used a 10% EDC-attributable factor. This range accounts for uncertainties for the role of EDCs in
disease development, yet recognizes that for some diseases the role of environmental factors is
stronger than for other diseases. For the three diseases evaluated in this report, the best estimate
EDC-attributable factors are well in line with reported EDC-attributable factors from the literature for
these diseases (see also Table 8). t should be noted that, if more reliable information to underpin
the EDC attributable fraction is available for specific health endpoints or of potential EDC substances
related to health endpoints (as in the studies of Bellanger, Hauser, Legler and Trasande and co
authors) one can decide to use these estimates instead of or together with the values presented
h ere.

50

Table 8. Breakdown of estimated EDC-attributable socio-economic cost for neural tube defects, endometriosis and
asthma. Total potential annual EDC-attributable socio-economic costs for the EU28 are calculated using an EDC
attributable fraction.
Health endpoint

Neural Tube Defects

Endometriosis

Asthma

Reference

(Jentink, Van De Vrie-Hoekstra, De
Jong-Van Den Berg, & Postma, 2008)

(Simoens et al., 2012)

(Suijkerbuijk et al,, 2013)

Country of study

Netherlands

9 EU countries (DK+DE+NL+
BE+FR+lT+UK+HU+CH) + USA

Netherlands

Study population

Netherlands (in 2005 200.000 births
per year of which 200 with NTDs)

society

541.943

currency / currency year

€1 2005

€1 2009

€1 2007

Study perspective

Lifetime cost per child,
disaggregated for different leasons
4%

Societal cost and average cost
per person
0% )annual cost)

Societal cost (in the report also
costs per person are provided)
0% (annual cost)

Direct Healthcare Cost

Lifetime costs per child: Thoracal: €
107.263 Lumbal: € 108.178 Sacral: €
101.514

€ 15,9 billion
(€3113! person)

€ 287 million / society (€ 529 per
person)

Direct Healthcare Coat

Total hospital care, paramedic care

Physician visits, medication,
monitoring tests, surgery,
other treatments, informal

Physician visits, physiotherapy,
hospital care, hospitalization,

Discounting

approach

care, hospitalization

medication, nursing, influenza
vaccination.

Direct Non Healthcare
Cost

Lifetime costa per child: Thoracal:
€19.272 Lumbal: € 21.317
Sacral: €498

€ 0,9 billion )€ 168/person)

Direct Non Healthcare
Cost approach

Travel and parking cost for parents,
wheelchair, house adaptions

Transportation, support
household activities

NA

Indirect Healthcare Cost

NA

NA

NA

Indirect Non Healthcare
Coat

Lifetime costa per child: Thoracal: €
151.663, Lumbal: € 146.377
Sacral: € 37.004

€ 32,4 billion
(€6298! person)

Absence )illness): € 258,9 milVon/
society. Occupational disability: €
29,1 million € 363 million !society

Indirect Non Healthcare
Coat approach

Special education, productivity loss

Productivity loss

Intangible coat

Age-specific quality of life, per year
(cost not calculated)
Thoracal: 0-10 years 0,3 / 11-21
years 0,18 / >21 years 0,3 Lumbal:
0-10 years 0,45 / 11-21 years 0,42/
>21 years 0,42 Sacral: 0-10 years
0,83 / 11-21 years 0,73!> 21 years
0,79

An average of 0.809 QALY was
reported in the first year after
diagnosis (cost not calculated)

Productivity loss due to absence
and occupational disability (10w
estimate: Friction method, high
estimate Human Capital Approach)
NA

NA

-

Intangible Cost approach

Uses O,ALY5 from earlier reports

QALY from questionnaire

NA

Total

€128774/ case (weighted average
cost per child, excluding Q.ALY cost)

€ 49,2 billion / 9 EU countries
combined (€9579! per5on)

€ 575 million / society (occupational
disability based on friction method)

Calculation /
extrapolation (based on
Eurostat 1 jan 2013)

25,755 million / year for NL. NL
births= (176/5231) = 3,365% of total
EU28 births in 2012.

9 EU countries population =
321,2 million = (321,2/505,7)

NL population = (16,8/505,7) 3,32%
of total EU28.

EU28 total

€ 765,4 million

€ 77,5 billion

EDC-attributable fraction

1%! 2,5% / 10%

1%/ 2,5%! 10%

1% / 2,5% / 10%

Reference and
explanation of EDCattributable fraction

An EAF for birth defecte is estimated

EAF for maternal conditions
(1-5%) in high income
countries (Melse & De
Hollander, 2001)

EAF of 10-35% (Landrigan,
Schechter, Lipton, Fahs, & Schwartz,
2002). Coincides with estimate of
11% of chemical-attributable
fraction (Prüss-Ustün et al., 2011)

€ 0,775 / 1,94 / 7,75 billion

€ 0,173! 0,432! 1,73 billion

Potential EDCattributable coat

5-10% )Smith, Corvaln, &
Kjellstrom, 1999). 2,5% was used
)Davies, 2006) correcting for other
environmental causes and
differences between developed and
developing countries
€7,65! 19,1 / 76,5 million

=

51

63,5%
€ 17,3 billion

4.5.

Selection of health effects to test the modular approach

A qualitative approach was chosen to select health effects for further evaluation. The selection was
based on expert judgement and team discussions on severity of the disease, incidence or prevalence,
observations in the trends of incidence or prevalence, and availability of good-quality cost studies
and other cost expertise. For none of the health effects, a detailed analysis for causation with EDC
exposure was performed. A short rationale for the selected diseases is provided below.
-

Asthma. Asthma is one of the most common immunological diseases for which cost
estimates are readily available. t is generally recognized that, at least in genetically
predisposed persons, environmental factors play a role in the development of asthma
(Umetsu, Mclntire, Akbari, Macaubas, & DeKruyff, 2002). Asthma IS 0fl the rise in developed
countries. In the US, the prevalence of pediatric asthma has more than doubled over the past
20 years, and is now the leading cause of hospitalizations and school absenteeism (Landrigan

-

& Goldman, 2011). As such, asthma is accounting for substantial healthcare and social cost.
Endometriosis. Endometriosis is a common female reproductive tract disease (and important
cause of female infertility) for which cost estimates are widely available in literature. The
prevalence of endometriosis is high, affecting an estimated 6-15% of women in reproductive
age (Kortenkamp et al., 2012), thereby potentially having a high societal impact.

-

-

-

Neural Tube defects. Neural tube defects are rare birth defects but with severe implications
for later life. Birth defects are the leading cause of infant death and are associated with
substantial health and education costs (Landrigan & Goldman, 2011). Good quality cost
studies are available that have quantified the socio-economic costs for neural tube defects.
Autism / Autism Spectrum Disorders (ASD). A large number of children is affected by
neurobehavioral disorders, including ASD and ADHD. ASD has been on the rise in the last
decades (UNEP/WHO, 2013). Since it is not possible to cure ASD, the impacts on society are
long-lasting and consequently very high.
Attention Deficit (Hyperactivity) Disorder (AD(H)D). Similar to ASD, ADHD prevalence has
been on the rise in the past decades (UNEP/WHO, 2013). It has now a high prevalence rate
among children: about 4,5% in Europe (Polanczyk, de Lima, Horta, Biederman, & Rohde,
2007).

4.6.

Appilcation of the modular approach

For the socio-economic cost analysis, literature searches were performed to select the best
applicable cost studies (recently published, relevant country, direct and indirect costs included). As
an essential aspect of the modular approach, a breakdown of socio-economic cost for the three
newly calculated EDC-associated effects is shown in Table 8. The various contributors to the cost are
shown in a way that a distinction between varlous types of costs can be made. The information
improves transparency and facilitates comparison between costs of different health effects. As
clearly demonstrated in Table 8, EDC-attributable costs are strongly dependent on the total socio
economic cost. Therefore, t is of utmost importance to have a correct estimate of a disease-related
health cost estimate. According to the presented calculations, the highest EDC-attributable socio
economic impact is expected for endometriosis. It should be noted, however, that there is a risk for
double counting of socio-economic impacts of endometriosis. Female infertility is a secondary effect
of endometriosis, and is partially included in cost estimate, as well as pelvic pain (Simoens et al.,

52

2012). It was shown that prevalence of endometriosis among infertile women was 47% (Meuleman
et al., 2009). For an evaluation and breakdown of cost of ASD and AD(H)D, the reader is referred to
chapter 3 and Annex B. A summary of the costs (for all five EDC-associated effects) is provided in the
factsheets.
For the cost of asthma, the results of a recent Dutch study (Suijkerbuijk et al., 2013) were
extrapolated to the EU28 population. The result, € 17,3 billion, seems to reflect a median cost
estimate as opposed to other cost data available from literature that represent worst-case scenarios:
€ 3 billion for EU25 (van den Akker-van Marie, ME, Bruil, & Detmar, 2005) and € 72,2 billion for EU28
(European Lung Foundation, 2013). All studies include direct and indirect cost. In addition, the latter
study includes indirect healthcare cost measured by DALYs. However, the inclusion of DALYs as well
as the addition of three extra EU countries and use of more recent data can only partially explain the
large difference between the studies.

43.

Factsheets

A summary of all information considered relevant for the interpretation of the relation between the
health effect, potential EDC-link, and socio-economic cost is provided hereafter in a summarizing
factsheet per disease. These include three health effects that have not been quantified before, and
two health effects of which EDC cost was previously quantified. Per disease, socio-economic cost is
provided in the factsheet. For the three health effects addressed in this report (endometriosis,
asthma and neural tube defects), a summary is presented on the breakdown of cost from table 8. For
ADHD and ASD, a summary is presented on the cost estimated in studies of HEAL and Trasande and
co-authors. An evaluation and breakdown of cost is given in chapter 3 and Annex B.

53

Neural tube defects (NTD5)
General description:
Neural tube defects are birth defects of the bram, spine, or spinal cord. They happen in the first month of pregnancy, often before a woman even knows that
she is pregnant. The two mont common neural tube defects are spina bifida and anencephaly. in spina bifida, the fetal spinal column doesnt close
completely. There is usually nerve damage that causes at least some paralysis of the legs. in anencephaly, most of the bram and skuii do not develop. Babies
with anencephaly are usually either stillborn or die shortly after birth. Another type of defect, Chiari malformation, causes the bram tissue to extend into the
spinal canal (0.5. National Library of Medicine, 2015)

Treatment:
Getting enough folic acid, before and during pregnancy prevents most neural tube defects. There is no cure for neural tube defects. The nerve damage and
loss of function that are present at birth are usually permanent. However, a variety of treatments can sometimes prevent further damage and help with
complications (OS. National Library of Medicine, 2015)

Statements on the role of EDCs:

Endocrine mechanisms / pathways:
According to (Kortenkamp et al., 2012):
•
Thyroid disruption
•
Sex hormone disruption
•
Neuroendocrine disruption

The biological plausibility of a role for chemicals in developmental
neurotoxicity [inciuding neural tube defects] is strong (Kortenkamp
et al., 2012)

Potential EDCs linked to health effect:
Chemkal(s)
Pesticides: amide, benzimidazole, methyl
carbamate,_organophosphorus_pesticides
POPs: o,p’-DDT and metabolites, a-HCH, yHCH,_and_a-endosulfan
PCB5,
dioxins,
BFRs
(mcl
PBDE5),
perchlorate,
pesticides,
BPA,
PFCs,
phthalates, 0V

Comorbidities:
•

Key references epidemoIogy
(Ruil, Ritz, & Shaw, 2006)

Note
One study only

(Ren et al., 2011)

One study only

(Boas, Feldt-Rasmussen, Skakkebk, & Main,
2006; Boa5, Main, & Feldt-Rasmussen, 2009; T. R.
Zoeller, 2010)

Reviews on effect of environmental chemicals on
thyroid function. Which chemicais are linked to NTDs
are not specified

Incidence / prevalence:

Severe disability (Copp, 2008)
Survival after birth (Copp, 2008)

•
•

0.5-2 per 1000 births for severe NTDs (Copp, 2008)
Mild NTDs mnclude spina bifida occulta, incomplete formation of
the neural arches of several vertebrae, which is usually
asymptomatic and may be present in up to 10% of people (Copp,
2008)

Socio-economic cost estimate:
Total lifetime cost / individual
Type of cost inciuded
EU28 cost / year
EDC-attributable fraction
EDC-attributable cost / year

€128 774 discounted (4%) (Jentink et al. 2008)
Direct and indirect healthcare and non-healthcare
€ 765,4 million
1% / 2,5% / 10%
€ 7,65 / 19,1/ 76,5 million

54

Endometriosis

General

description:

Endometriosis is a common gynaecological disorder characterized by ectopic endometrium (presence of endometrial glands and stroma outside the uterus)
causing benign endometrium-like inflammatory lesions outside the uterine cavity and is a major cause of chronic pelvic pain and infertility (Kortenkamp et al.,
2012). Other symptoms inciude very heavy periods and pain in the lower back and abdomen. Some women have no symptoms at all (Kortenkamp et al.,
2012; 0.5. National Library of Medicine, 2015).
Treatment:

Oiagnosis requires the identification of presence of endometrial glands and stroma outside the uterus on histologic inspection of biopsies obtained after
laparoscopy. There is no non-invasive diagnostic tool available (adapted from (Kortenkamp et al., 2012). Treatment includes pain medicines and hormone
therapy. Severe cases may need surgery. There are also treatments to improve fertility in women with endometriosis (Kortenkamp et al., 2012; U.5. National
Library of Medicine, 2015).
Statements

•

•

•

on

the

role

of EDCs:

Recent developments implicate developmental exposures to
exogenous chemicals in heritable epigenetic changes that may
contribute the disease development (Kortenkamp et al., 2012).
Exposure to oestrogen or to oestrogenic EDC5 is an accepted risk
factor for breast cancer, endometriosis, fibroids and polycystic
ovarian syndrome (PCOS) in women (European Environment
Agency, 2012)
The evidence is accumulating of correlations between EOC5 in the
circulation of women with endometriosis, although a cause-and
effect relationship has yet to be established, which is not
uncommon in reproductive environmental toxicity )Oiamanti
Kandarakis et al., 2009)

Potential

EDCs

linked to

Chemicaijs)
Phthalates

health

•

There are sufficient data linking exposure to EDCs )phthalates,
PCBs and dioxins) with endometriosis. Stili it is classified as
“limited and conflicting experimental and epidemiologic
evidence” (UNEP/WHO, 2013).

Endocrine

•
•

mechanisms

/

pathways:

Estrogen dependent (role in apoptosis, invasion and adhesion,
angiogenesis, proliferation).
Progresterone (role in invasion and adhesion of endometrial
tissue), role of estradiol and progresterone in angiogenesis of
endometriotic lesions (Kortenkamp et al., 2012)

effect:

Key references Epidemiology
Buck Louis et al., 2013; Calafat et
al., 2010

Note
Various studies with and without association:
at least 6 studies with positive association
at least 2 studies with smail/indicative association
at least 4 studies without association/no conciusion possible
Various studies with and without association
Various studies with and without association
-

-

-

Oioxins
OCP: -HCH, y-HCFI, Mirex

Tsukino et al., 2005
Upson et al., 2013, Buck Louis et al.,
2012
Buck Louis et al., 2012; Porpora et
al., 2009
Matalliotakis et al., 2008

PCB5
OES

Various studies with and without association

Comorbidities:
•

•
•

•

Incidence / prevalence:

PCOS, uterine fibroids and endometriosis are leading causes of sub fecundity
and infertility )UNEP/WHO, 2013). 47% of infertile women had
endometriosis (Meuleman et al., 2009)
lncreased risk of endometrial and dear celi ovarian cancer, non-Hodgkin’s
lymphoma, and atopic disorders (Giudice, 2010)
The pelvic pain associated with endometriosis is a major cause of disability
and compromised quality of life. Early menarche, short and heavy menstrual
cycles, and cycle irregularity are risk factors for endometriosis (UNEP/WHO,
2013)
Prevalence of immune disorders such as rheumatoid arthritis, systemic lupus
erythematosus, hypo- or hyperthyroidism, and multiple scierosis was higher
in women with endometriosis than the general population (McLeod &
Retzloff, 2010; Viganô, Parazzini, Somigliana, & Vercellini, 2004)

Socio-economic

cost

Occurs in 10-15% of women of reproductive age (1549) and a minimum of 176 million women woridwide
)UNEP/WHO, 2013)
It occurs in 6—10% of women (Diamanti-Kandarakis et
al., 2009)
Estimates of the prevalence of endometriosis vary
widely between 6-15% of women of reproductive age
(Kortenkamp et al., 2012; Meuleman et al., 2009).

estimate:

Annual average cost / women
Type of cost inciuded
EU9 total cost / year
EU2B cost / year
EDC-attributable fraction
EDC-attributable cost

€ 9.579 (Simoens et al., 2012) (weighted average 9 EU countries)
Direct healthcare and indirect non-healthcare
€ 49,2 billion
€ 77,5 billion
1% / 2,5% / 10%
€ 0,775/ 1,94/ 7,75 billion

55

Asthma
General description:
Asthma is a chronic infiammatory disorder of the airways in which many celis and cellular elements play a role: in particular, mast ceils, eosinophils,
neutrophils (especially in sudden onset, fatal exacerbations, occupational asthma, and patients who smoke), T lymphocytes, macrophages, and epithelial
cells. In susceptible individuals, this infiammation causes recurrent episodes of coughing (particularly at night or early in the morning), wheezing,
breathlessness, and chest tightness. These episodes are usually associated with widespread but variable airflow obstruction that is often reversible either
spontaneously or with treatment.
The development of asthma appears to involve the interplay between host factors (particularly genetics) and environmental exposures that occur at a crucial
time in the development of the immune system. A definitive cause of the inflammatory process leading to asthma has not yet been established. Considering
innate immunity, numerous factors may affect the balance between Thl-type and Th2- type cytokine responses in early life and increase the likelihood that
the immune response will downregulate the Thi immune response that fights infection and instead will be dominated by Th2 cells, leading to the espression
of allergic diseases and asthma. This is known as the “hygiene hypothesis”. )NIH: National Heart, Lung, and Blood Institute, 2007)

Treatment:
Medications for asthma are categorized into two general classes: long-term control medication used daily to achieve and maintain control of persistent
asthma, and quick-relief medication to treat acute symptoms and exacerbations. )NIH: National Heart, Lung, and Blood Institute, 2014)

Statements on the role of EDCs:
•

•

Endocrine mechanisms / pathways:

There are also some indications that esposure in ufero and during
early life may increase the likelihood and severity of asthma
development (Kortenkamp et al., 2012).
There are good epidemiological data associating exposure to
phthalates with asthma and other airway disorders. Endocrine
mechanisms are not, however, dear. )UNEP/WHO, 2013)

•

Developmental immunotoxicity (DIT) caused by EDC exposure
may be one early-life immune insult. Exact endocrine
mechanisms are, however, not dear )UNEP/WHO, 2013).
The three major endocrine ases influence the immune system
(hypothalamic—pituitary—adrenal
)HPA),
hypothalamic—pituitary—thyroid
)HPT)
and
hypothalamic—pituitary—gonadal )HPG) axes), as well as several
other neuroendocrine factors (Kortenkamp et al., 2012)

•

Potential EDCs linked to health effect:
Chemical(s)
Phthalates

Key references Epidemiology
)Bornehag et al., 2004; Jaakkola et al., 1999; Cie, Hersoug, &
Madsen, 1997)

Triclosan,
parabens
PCBs, dioxins

(Bertelsen et al., 2013; Savage, Johns, Hauser, & Litonjua, 2014;
Spanier, Fausnight, Camacho, & Braun, 2014)
)Stølevik et al., 2011; Weisglas-Kuperus, Vreugdenhil, & Mulder,
2004)Stolevik_2013_)PCBs,_dioxins),_Weisglas-Kuperus_2004_)PCB5
)Midoro-Horiuti, Tiwari, Watson, & Coldblum, 2010)

BPA

Comorbidities:
•

Type of cost inciuded
Annual total cost / Netherlands
EU2B cost / year
EDC-attributable fraction
EDC-attributable cost

Toxicological and in vivo evidence only

Incidence / prevalence:

Respiratory conditions for which a pathophysiologic link to asthma is
believed to exist are allergic rhinitis, sinusitis and otitis media. >25% of
children have one or more of these comorbidities vs <10% of nonasthmatic children )Grupp-Phelan, Lozano, & Fishman, 2001)

Socio-economic cost estimate:
Annual total cost / person

Note
Various studies found a relation with residential presence to
PVC, as well two studies describe a correlation with DEHP in
indoor dust and asthma
Suggested via evidence for allergic sensitization and coincidence
with asthma exacerbations
Suggested via increase of wheeze and infections

•

It is one of the most common long-term diseases of children.
In the US in 2009, 1 in 11 children had asthma and 1 in 12
adults )CDC, 2014)
A total EU prevalence of 7,2% is reported )van den Akker-van
MarIe, ME et al., 2005)

€ 1.058 (Suijkerbuijk et al., 2013)
Direct healthcare and indirect non-healthcare )based upon friction method)
€ 575 million
€ 17,3 billion
1% / 2,5% / 10%
€ 0,173/ 0,432 / 1,73 billion

56

Autism & Autism Spectrum Disorder (ASD)

General description:

Autism spectrum disorder (ASD) is a neurological and developmental disorder that begins early in childhood and Iasts throughout a person’s life. It affects
how a person acts and interacts with others, communicates, and learns. t includes what used to be known as Asperger syndrome and pervasive
developmental disorders (U.5. National Library of Medicine, 2015).

Treatment:

There is no one standard treatment for ASD. Treatments include behavior and communication therapies, skills training, and medicines to control symptoms
(U.S. National Library of Medicine, 2015). Individuals with ASD5 can differ greatly in their clinical and functional presentation, resulting in potentially
substantial differences in costs of treatment, care, and support. Typical cost includes special education, residential care and/or supported accommodation,
and employment support (Buescher et al., 2014).

Statements on the role of EDCs:

•

•

The biological plausibility of a role for chemicals in developmental
neurotoxicity [including ASD] is strong (Kortenkamp et al., 2012). However,
the complexities of studying human conditions and the issues of species
extrapolation mean that strong evidence to link complex human disorders,
like autism, to single chemicals or mixtures of chemicals has not emerged
Sufficient evidence that environmental factors contribute to the increases in
ASD. Sufficient evidence that exposure to some industrial chemicals is
plausibly related to the production of neurobehavioral disorders
(UNEP/WHO, 2013).

•

Low strength of human evidence; moderate strength of
toxicological evidence )Bellanger et al., 2015; Trasande
et al., 2015)

Endocrine mechanisms

/ pathways:

•
Thyroid disruption
•
Sex hormone disruption
•
Neuroendocrine disruption
(Kortenkamp et al., 2012; UNEP/WI-lO, 2013; WHO, 2014)

Potential EDCs linked to health effect:*

Chemkal(s)
Reference
Low molecular weight (LMW)
)Miodovnik et al., 2011)
phthalates
Pesticides
(Roberts et al., 2007)
Perinatal exposure, reviewed (De Cock, Maas, & Van De Bor, 2012)

Comorbidities:

•
•

Note
This study also included other chemicals, and showed
no effect of BPA on ASD
Specific EDC-component not specified

Incidence

40% to 60% of people with ASDs also have intellectual disability
(ID) (Buescher et al., 2014)
Other comorbidities include ADHD, epilepsy, gastrointestinal
symptoms, sleep problems, feeding problems and toileting
problems (reviewed in (Mannion & Leader, 2013))

•

/ prevalence:

Autism spectrum disorders now occur at a rate that approaches
1% )UNEP/WHO, 2013)
‘Classical autism’ in the EU could be estimated as varying from 3.3
to 16.0 per 10 000. But these rates could increase to a range
estimated between 30 and 63 per 10 000 when all forms of ASD
are included )EC, 2005)

Socio-economic cost estimate:

Reference
Cost estimate
Type of coat included
EU28 coat / year
EDC-attributable fraction

HEAL (HEAL, 2014)
UK: aggregate costa for adults amount to £25 billion eech
year )Knapp et al., 2009)
Direct healthcare and indirect non-healthcare
€ 226 billion
25’°
-

EDC-attributable coat

€ 4,52

.

—

.

11,3 billion

57

Trasande and co-authors (Bellanger et al., 2015)
€ 630.000 discounted (3,5%) lifetime coat per
individual (adapted from )Buescher et al., 2014))
Direct healthcare and indirect non-healthcare
Not calculated
0,97% )low), 2,425% (base case), 4,85% (high) =
respectively 126, 316 and 631 cases/year in the EU
€80 million (10w) € 199 million (base case)
€ 399 rnillion (high)

Attention Deficit (Hyperactivity) Disorder (AD(H)D)
General description:
ADHD and ADD are characterized by problems with attention, impulsivity and (in case of ADHD) hyperactivity. Childhood ADHD is likely to persist into
adulthood and may constitute a lifelong impairment. The diagnostic criteria for disorders such as ADHD are variable, and changes in diagnostic practice are
the probable reason for any apparent increase in incidence over time (Kortenkamp et al., 2012)

Treatment:
Treatment may include medicine to control symptoms, therapy, or both. (U.S. National Library of Medicine, 2015).

Statements on the role of EDCs:
•
•
•

Endocrine mechanisms / pathways:

The biological plausibility of a role for chemicals in developmental
neurotoxicity [including ADHDJ is strong (Kortenkamp et al., 2012).
Low-to-moderate strength of human evidence; strong strength of
toxicological evidence (Bellanger et al., 2015; Trasande et al., 2015)
Sufficient evidence that exposure to some industrial chemicals is
plausibly related to the production of neurobehavioral disorders.
(UNEP/WHO, 2013).

•
Thyroid disruption
•
Sex hormone disruption
•
Neuroendocrine disruption
(Kortenkamp et al., 2012; UNEP/WHO, 2013; WHO, 2014)

Potential EDCs linked to health effect:*
Chemical(s)
Polychlorinated biphenyls (PCB5(
OPs (dialkyl phosphate (DAP) in urine)
chlorpyrifos
BPA
Polybrominated diphenylethers (PBDEs)

Key references Epidemiology
(Sagiv et al., 2010)
(Marks et al., 2010)
(Rauh et al., 2006)
(Braun et al., 2009)
(Chen et al., 2014; Eskenazi et al., 2013)

Low molecular weight (LMW) phthalates

(Engel et al., 2010)

Note
PCB 118, 138, 153, 180

Non-significant result

Non-significant result

Perinatal exposure, reviewed (De Cock et al., 2012)

Comorbidities:
•

Incidence / prevalence:

In children: oppositional defiant disorder and developmental
coordination disorder (Kadesjö & Gillberg, 2001)
In adults: alcohol and drug abuse, antisocial personality disorder and
depression (Torgersen, Gjervan, & Rasmussen, 2006)

ADHD and ADD have a worldwide pooled prevalence
estimate of about 5,3%; pooled prevalence in Europe is 4,5%
(Polanczyk et al., 2007)

Socio-economic cost estimate:
Reference
Cost estimate
Type of cost included
EU28 cost / year
EOC-attributable fraction

HEAL (HEAL, 2014)
UK: £ 78 million / year (€ 56 per person)
(Schlander, 2007)
Medication only
€ 0,72 billion
2% 5%
-

EDC-attributable cost

.

.

€14— 35 million

58

Trasande and co-authors (Bellanger et al., 2015)
€ 9860- €14483! person per year (Le et al., 2014) adapted to
€ 77.000 discounted (3%) lifetime cost per individual
Direct healthcare and indirect non-healthcare for individuals
with AD(H(D and their family members
Not calculated
For OPs: 10,76% (10w), 17,28% (base case),
For PBDE: 12,53% (base case(
Together 42.000— 54.0000 cases/year in the EU
For OPs and PBDE combined: € 2,62 billion (low) €4,14 billion
(base case) € 4,93 billion (high)

5. Evaluation

In this chapter, an overall evaluation of the available data on EDC-associated health endpoints and
possible EDC-related cost is made. In addition, newly modelled costs estimates are provided in this
report. This resuits in a range for potential annual EDC-related socio-economic cost for the EU28.
With an improved understanding of the socio-economic costs associated with EDCs, we discuss which
areas might have highest estimated health impact and priorities that may be addressed in risk
governance and research.

5.1.

Range for EDC-attributable cost in EU28

In Table 9, a range is presented for EDC-attributable socio-economic cost per health effect and a total
for the EU28 that were calculated in this report and previously by others. The socio-economic cost
estimates include estimates for the three health effects that were added in the modular approach in
this report as well as an additional estimate for IQ loss (Rijk & van den Berg, 2015). The lowest and
highest estimates available from the various studies reflected in this report have been used to
determine a cost range for each health effect. Taking into account the overlap and differences
between the quantified health effects, the range of total socio-economic cost for EDC-attributable
health effects is estimated to be between €61 billion and € 293 billion annually for the EU28.
In the evaluation of the composition of cost in Chapter 3.6, we have identified some discrepancies in
cost estimates that affect the overall cost estimates. Below, we argue to adjust some of these low
and/or high base estimates in order to align cost estimate assumptions across diseases and justify
the addition of EDC-attributable health costs in our modular approach. Consequently, this will ideally
—

lead to a more realistic estimate of healthcare cost that are associated with EDC exposure in EU28.
Proposals for adjustments of the cost range
In Table 9 we propose adjustments to certain EDC-attributable cost. The first cost estimate that is
likely overestimated is the cost for male fertility. The highest range estimate is based on the number
of couples of reproductive age and the assumption that they all want to become pregnant if not
using (documented) contraception. The other estimates are based on the number of registered
infertile couples from healthcare registries or the amount of ART treatment cycles. The latter
estimates seem to better represent the number of infertile cases. Therefore, we believe it is
reasonable to take the second highest estimate as upper limit for EDC-attributable cost of male
infertility.
The highest contributors to the total cost are the neurodevelopmental and -behavioral diseases and
disorders. Here, especially the contribution of 10 loss (or foregone 0 points) is driving the cost
estimate. It was shown that almost every newborn child could lose some lQ points due to (mostly)
prenatal exposure to EDCs. It should be noted, however, that socio-economic impact of 10 loss is
calculated based on indirect loss, i.e. income loss due to lower lQ and hence does not represent
actual expenditures (such as medications and treatments). In both cost estimates, the costs for IQ
loss were estimated according to the best applicable knowledge and accepted methodology for
valuation of 10 points from the US EPA (US EPA, 1997) for environmental impacts. Somewhat lower
resuits were derived from a study in the Netherlands (Rijk & van den Berg, 2015), replacing the lower
estimate from Trasande et al. (2015). Possibly, the EDC-attributable cost for 10 loss is overestimated

59

due to differences in income structure between the EU and the US. Also, a potential interaction with
the increasing trend in IQ over the past decades is not taken into account. However, there is
insufficient data available to propose a further adjustment of the presented socio-economic impact
due to loss of IQ.
Apart from IQ loss, the cost for other neurodevelopmental and -behavioral health effects are also
relatively high compared to other groups of health effects that have been linked to EDCs. These cost
largely comprise of direct healthcare cost, provided by specialized institutes and residential care. The
lowest estimate for AD(H)D, however, is most certainly an underestimation because it only takes into
account cost of medication, while the amount of expected other direct and indirect treatment costs
related to AD(H)D is substantial, as argued in the paper of Behanger et al. (2015). Therefore, t is
proposed to replace this how estimate with a higher estimate that is based on a more representative
set of costs.
The increment in death rate due to a lower level of Testosterone (T), is based on two assumed links,
making the cost estimate more uncertain. The EDC-attributable factor for this health endpoint was
calculated 10,3%. As described in paragraph 4.4, we used 1% (low), 2,5% (base) and 10% (high) as
estimate EDC-attributable fraction in our modular approach. Applying a similar approach, the 10,3%
would categorize as high case estimate for increment death rate due to EDC exposure. We propose
to add a 1% AF as how case estimate, which amounts to € 0.8 billion.
When taking the adjusted EDC-attributable cost estimates into account, the range of EDC-related
costs amounts to €46— 288 billion for EU28, annually. Especially the contribution of IQ loss (€ 32-184
billion) dominates the cost estimate. With the modular approach applied in this report, the EDC
related health effects endometriosis, neural tube effects and asthma possibly add € 2,4 bilhion (€ 1-10
bilhion) to the total cost estimate range. However, considering the uncertainties in cost calculations
and potential EDC-attributable fraction, these estimates should be considered with care.

5.2.

Availability and (un)certainty of data

Gaps in quantified health effects
In Table 10, an overview of health effects is presented for which EDC-associated costs were
quantified in this and other reports, and health effects of which no or himited cost data was available
in the public literature. It is dear that especially the costs of female reproductive health effects,
immunological effects and “other” effects (e.g. neuroendocrine diseases, thyroid effects, bone
disorders) are underrepresented in the recent cost estimate papers. There might be several reasons
why these have not been quantified. A reason might be that the link with EDCs is not well specified
(Vet) or has only recently become focus of scientific studies. This is for example the case with
immune-related disorders. In addition, for some health effects it might difficult to quantify socio
economic costs, because there is no published literature available on healthcare costs or cost
calculations are in a prehiminary stage, e.g. for altered onset of puberty and menopause or for altered
sex ratio.

60

Table 9. Range of EDC-attributable cost per health effect and total EDC-attributable socio-economic cost estimates for EU28 (in billion €).
Outliers in cost estimates and their proposed adjustments are indicated in red.
.

.

Nordic Council

Source
etiological fraction / type
of estimate

2%

20%

HEAL
40%

.

Trasande et al.

Total
(2%)

Total
(5%)

0,0480,062

0,1200,155

0,0180,026

0,0450,065

low

base
case

This report
high

1%

2,5%

overall range

Adjusted
range

10% lowest highest lowest highest

Reproductive tract and ferti ity
Reduced female fertility
Reduced male fertility

0,007

0,072

0,145

Cryptorchidism

0,018

0,181

0,363

Hypospadias

0,009

0,089

0,178

Endometriosis
Neurobehavioral diseases and disorders
Autism spectrum disorders
(ASD)

4,52

11,3

AD(H)D

0,014

0,035

0,117

4,71

0,007

4,71

0,007

0,130

0,018

0,363

0,018

0,363

0,009

0,178

0,009

0,178

0,775

7,75

0,775

7,75

0,080

11,3

0,080

11,3

0,014

4,93

2,62

4,93

42,2

183,6

32

183,6

6,11

33,4

6,11

33,4

0,008

0,077

0,008

0,077

0,775

0,080

0,199

1,94

7,75

0,399

2,62

4,14

4,93

lQloss

42,2

133,4

183,6

Mental retardation

6,11

22,6

33,43

Neural tube defects
Hormone-related cancers

32,0

0,008

84,3

0,019

136

0,077

0,155

Breast cancer

0,320

0,800

0,320

0,800

0,320

0,800

Prostate cancer
Testis (testicular germ ceil)
cancer
0,025 0,249 0,499
Metabolic syndromes, immune disorders, other

0,180

0,450

0,180

0,450

0,180

0,450

0,025

0,848

0,025

0,848

1,62

17,2

1,62

17,2

1,44

17,2

1,44

17,2

7,96

7,96

0,80

7,96

0,173

1,73

0,173

1,73

Obesity child
—

0,313

1,62

1,56

4,05

Obesity adult
Diabetes mellitus (type 2)
lncrement death rate
among men

0,848

1,63

15,6
6,0

15,0

1,44
7,96

Asthma

17,2
0,80
0,173

0,432

1,73

TOTAL (billion €)
0,059 0,591 1,185
12,7
31,6
44,7 192,6 270,4
NA
NA
NA
60,9 292,6
46,2 288,0
TOTAL (billion €) after
157
NA
NA
NA
NA
NA
correction
(90% C.l. 32— 212)
Note; CeIls have been merged jE they reflect cost estimates of combined health effects. For the studies of Trasande et al. the 10w and/or hign estimates are
provided as kind of sensitivity analysis; t these low and/or high estimates were not given, the base case estimate has been noted (in grey) to calculate an
upper and lower boundary of total EDC-related healthcare cost.

61

Type of cost data inciuded in socio-economic cost estimates and methodology to calculate
costs
In general, the types of costs taken into account and the methods used to calculate costs largely
influence socio-economic cost estimates. For instance, a cost estimate including direct, indirect and
intangible costs is likely to be significantly different from a cost estimate only inciuding direct costs,
as has been illustrated by various examples within this report. For example, the direct cost for female
adult obesity is estimated about € 20.000, while intangible costs were valued at almost € 270.000,
thus adding a significant amount.
For health endpoints for which cost studies are available, all cost studies have addressed direct cost
of healthcare (except for IQ loss), such as medication and hospital treatment. For most endpoints,
also indirect non-healthcare effects are quantified, which are mainly productivity losses due to
morbidity and mortality of patients and their caregivers. Less often, direct non-healthcare effects are
quantified, such as travel cost and childcare cost when treatment is received. However, the majority
of these costs are negligible compared to medical cost and productivity losses. Other types of costs
that are not often included in socio-economic cost evaluations are indirect healthcare cost and
intangible cost. Indirect healthcare costs are most often expressed in DALYs. Intangible costs are
most often expressed in QALY5, and are valued using a standard cost per QALY lost. QALYs represent
the opposite of DALYs (a gain in years living in good quality of health, versus a loss of years due to
living in disability or early mortality). DALYs and QALYs can therefore not be added up. DALYs and
QALY5, when quantified, usually result in high total costs because both are often valued at
approximately € 70.000 per year.
Since there is a difference in interpretation in types of costs, it would be interesting to separate costs
relateci to direct cost (“real” expenditures) from indirect costs and intangible costs (cost that place a
burden on society or on the quality of lives, that usually do not represent real expenditures). As a
result, it would be easier to interpret individual disease-related cost estimates and compare them
with other similar cost estimates (e.g. national of European health care budgets).
Furthermore, the methodology used to calculate costs influence the results as well. Cost-of-disease
studies using a bottom-up approach (calculating cost per individual and extrapolating this to the
whole population) tend to overestimate the burden of societal costs (as seen in top-down cost
studies, where actual healthcare expenditures are analyzed and broken down to cost per patient).
Furthermore, if lifelong health impacts are calculated (e.g. for ASD), or effects that will occur in the
future (e.g. for cancer risk) t makes a large difference whether costs have been discounted and what
rate for discounting is used. For instance, if costs will occur 30 years after exposure, discounting at a
rate of 4% may lower annual cost with approximately 50%. With regard to indirect costs, there are
two main methods to estimate productivity loss: the friction method and the human capital
approach. In most cases, the human capital approach (neglecting replacement of ilI workers by new
workers) leads to much higher cost for productivity losses. Other parameters, including currency,
year of study and geographic differences, apparently have a minor influence on estimated cost, when
applied to relatively similar scenarios of cost estimation.
European-wide data isfavorable but often not available
The use of data on incidence or prevalence of a disease usually does not contribute to a high
uncertainty in cost estimates. In general, these data are available from reliable disease registers.

62

However, differences in healthcare organization (eg. how a diagnosis is made, methods of treatment
applied), environment, income and lifestyle can influence prevalence and incidence rates and the
health care expenditures per case and consequently the related total healthcare costs. This could
lead to problems when extrapolating from one subpopulation or country to another. To eliminate a
potential extrapolation error, It is therefore preferred to use not only European estimates for
prevalence or incidence for a certain health effects, but also a European-wide cost estimates.
However, to our knowledge, recent European-wide cost estimates for cost of EDC-related diseases
are limited, with the exception of relatively recent cost data for cancer (Luengo-Fernandez et al.,
2013), various bram disorders (Gustavsson et al., 2011; Olesen et al., 2012), cardiovascular disease
(Leal, Luengo-Fernandez, & Gray, 2012), obesity (Müller-Riemenschneider, Reinhold, Berghöfer, &
Willich, 2008), and osteoporosis (Hernlund et al., 2013). For some EDC-related diseases, cost
estimates have been published and aggregated for multiple countries, e.g. diabetes (5 EU countries)
(Kanavos et al., 2012) and endometriosis (9 EU countries) (Simoens et al., 2012). The use of recent
European-wide estimates would clearly improve reliability of the cost estimates of EDC-related
health effects.
No standardized approach for socio-economic cost evaluation
Although the type of costs taken into account strongly influences the resulting cost estimate, there is
no standardized approach for socio-economic cost evaluations of health effects. This clearly hampers
interpretation and comparison of costs for different diseases.
When considered in a cost-effectiveness evaluation (cost-benefit analysis), such cost estimates may
provide input for certain policy decisions. Therefore an inclusion or exclusion of certain cost aspects
may have a high impact. In such cases, the scope of study is of high importance. A general
recommendation is to develop a standardized cost estimate approach for cost-benefit evaluations in
the context of hazardous substances. It would be desirable to set criteria what kind of cost should be
inciuded and what methodology should be used in order to assure the validity of the cost estimate.
At least, for transparency, background parameters for the cost of disease study should be provided,
as is proposed in the modular approach presented in this report. As such, differences can be
explained by looking to crucial parameters and type of costs taken into account.
Use of an EDC-attrîbutablefraction versus exposure-response relations
One of the major challenges is to use a reliable EDC-attributable fraction to estimate the fraction of
total cost that could be related to EDC exposure. To establish an attributable or etiological fraction
for a single cause to a disease, is not only a challenge for EDCs and their attribution to health effects,
but is a general scientific challenge for all factors influencing development of diseases. Diseases
usually have a multifactorial origin, and the exact onset of disease remains unexplained in most of
the cases. An estimation of socio-economic cost based on a single factor, whether this is exposure to
EDCs or another cause, remains a simplification of reality. For quantification of the socio-economic
costs, the EDC-attributable fraction remains a very influential parameter that highly influences the
final outcome of a socio-economic cost evaluation. A substantial over- or underestimation of EDC
attributable cost due to a wrong estimate of the attributable fraction is therefore realistic.
As explained in Chapter 3.6 and 4.4, EDC-attributable fractions can be calculated from selected
exposure-response relations (ERR5) in epidemiological studies. This approach was followed in the
studies of Trasande and co-authors. Unfortunately, not for all of the health effects and suspected

63

compounds is epidemiological evidence available. The estimates are highly dependent on availability
of exposure and (human) effect studies, general quality, representativeness to the desired
population, and selection (bias) to determine an ERR. Not unimportantly, with the available research
budgets and time needed to establish ERRs in high quality studies, it is highly unlikely that
biomonitoring data and epidemiological resuits will become available for all chemicals (and mixtures)
on the market and all types of EDC-associated diseases.
Furthermore, there is currently no (legislative) framework that requires studies on the mode of
action of a chemical when it is brought to the market. At present, the required toxicological data
within regulatory frameworks is not sufficient to establish an attributable fraction of a chemical to a
disease. The alternative, i.e. to wait for epidemiological data to become available, is clearly
impossible and unethical. Therefore, assumptions will have to be made to establish an etiological
fraction for the contribution of EDCs to disease. Using a best estimate of a predefined etiological
fraction could be criticized as being a “wild guess” but is a transparent approach, easy to interpret
and modify if needed (e.g. as new insights on EDCs arise providing arguments for adjustments
upwards or downwards), aggregates the effects of EDC mixtures, and is widely applicable to all
diseases in absent of better information.
lnterestingly, most ERR-derived EDC-attributable fractions that were evaluated in this report were
well in line with EDC-attributable best estimates applied in other studies as well as acknowledged
estimates for environmental contributions to disease burden. Therefore, we believe that even when
there is limited information available, it is valid to use (a range of) best estimates as starting point to
determine the EDC-attributable fraction of a health effect.

5.3.

Highest cost and possible implications for priority setting

In this report, we have shown that even at low-range estimates, the socio-economic impact on
society might be substantial and that the financial burden for the EU and its future generations is
potentially high. In view of the potentially high socio-economic costs associated with EDCs, further
action might be warranted. It could be stressed that uncertainties and discussions about (potential)
health effects should not hamper or delay further actions or interventions on EDCs.
Actions based on measured effects and (in case of data limitations) on precautionary principles,
might be warranted, yet are currently hampered by a variety of reasons as also depicted in this
report. The phenomenon of uncertainty hampering public health policy action on toxic chemicals and
their health effects was well described by Michaels in the context of hazardous chemicals (Michaels,
2006): “Absolute certainty in the realm of medicine and public health is rare. Scientists must
extrapolate from study-specific evidence to make causal inferences and recommend protective
measures. Absolute certainty is rarely an option. Our regulatory programs will not be effective ifsuch
proof is required before we act; the best available evidence must be sufficient”.
Also, 1f applying the International Risk Governance Council (IRGC) risk management framework
(introduced in Chapter 1) it can be said that for EDCs, the ‘precautionary approach’ of risk
management could be appropriate. The IRGC defines generic risk management strategies to classes
of risks based on the distinction between complexity, uncertainty, and ambiguity. According to the
IRGC, a complex risk is often associated with major scientific dissent about complex dose-effect
relationships. According to the IRGC, the management of risks characterized by multiple and high
uncertainties should be guided by the precautionary approach. Since high uncertainty implies that
64

the (true) dimensions of the risks are not (Vet) known, one should pursue a cautious strategy that
allows learning by restricted errors (IRGC, 2012). Besides uncertain and complex, the issue of EDCs
can also be categorized as an ambiguous risk according to the IRGC as divergent or contested
perspectives on the justification exist, severity or wider meanings associated with a given threat.
According to the IRGC this requires a “discourse-based’ strategy, which seeks to create tolerance and
mutual understanding of conflicting views and values with a view to eventually reconciling them.’
Although not all EDC-associated health effects have been or can be quantified, this report might help
prioritization of further areas for research and actions on EDCs.
When considering measures, more research to identify EDC-related effects, strength of evidence,
endocrine mechanisms, mode of actions, and attributable fractions to a certain effect could be very
relevant to reduce uncertainty and improve understanding. Standard tests that are requested for
chemicals on the market do not cover many apical endpoints that have been associated with EDCs,
such as irnmunotoxic effects, neurotoxic effects and diseases of the thyroid. As a result, this type of
information will not become available within the legislative frameworks and existing data gaps will
remain unsolved.
The highest cost of EDC-associated health effects, are found in the group of neurobehavioral
diseases, disorders and cognitive conditions. This group of neurobehavioral disorders includes
several pervasive disorders that remain during a person’s whole lifetime, thereby resultirig in
substantial costs. The group of metabolic-related health effects (obesity, diabetes) also has relatively
high cost estimates. This is especially due to a large prevalence of diabetes and obesity within
society. The group of immunological diseases, disorders and conditions is not sufficiently quantified
to draw conclusions for this purpose, and clearly need further study. Especially considering the
increasing incidence in immunological diseases, such as asthma and allergies, and likely contribution
of EDCs in disease etiology.
Using this cost-based approach, t can be recommended to give priorities on the development and
regulatory inciusion of test guidelines for EDCs that are associated with neurodevelopmental toxicity,
diabetes and obesity, as well as to decrease the uncertainty related to immunological disorders. It
could be highly valuable, for instance, to evaluate if current information requirements in the various
regulatory frameworks sufficiently cover endpoints related to e.g. neurotoxic, metabolic and immune
diseases. At present, the common tests used to evaluate the safety of chemicals in the legislative
framework (such as the Extended One-Generation Reproductive Toxicity Study, OECD TG-443), does
not oblige to test for developmental neurotoxicity endpoints, nor immunological endpoints. This can
easily be solved since for developmental neurotoxicity and immunological endpoints, the OECD TG
443 provides relevant cohorts for these endpoints. Yet at present, this is not standard procedure to
incorporate these cohorts. In addition, the human relevance of some apical endpoints in animal
studies is limited. A more mechanism-based assessment of (new) chemicals, thereby focusing on
human-relevant effects, could greatly strengthen current chemical risk assessment processes. An
additional merit here would be that these types of studies can very well be performed in humanrelevant, in vitro assays, without the additional need of animal experiments and potentially even
reduce the need of animal tests in chemical risk assessment.

65

Table 10. An overview on the degree/extent of cost quantification of EDC-associated health effects: EDC-associated
socio-economic costs in this and other reports (bright green); literature on costs available: may be subject for future EDC
associated socio-economic cost analysis (medium grey); no or limited literature on costs available (dark grey). Names of
health effects clusters/categories that are not assessed are depicted in white.
EDC-Related health effects
1. Reproductive health
Female reproductive problems
Female fecundity and fertility
Reduced female fecundity (lower nu

foffspdng)
ReducedfemaleIit

Adverse pregnancy outcomes
Ectopic pregnancy
Spontaneous abortions (miscarrlages)
1-lypertensive disorders of pregnancy, mcl. pregnancy-induced
hypertension and pre.eclampsia
Intrauterine growth restriction (IUGR)
Preterm delivery
1.0w blith weight or length
Birth defects
Dlsturbed (decreased) lactation perlod
Polycystic ovarian syndrome (PCOS)

4. Effects on the metabollc system
Metabolic syndromes
Obesity (child and ad
Ojg)gyejijtut (typ
Diabetes type 1
Metabolic syndrome
Cardiovascular system
Cardiovascular disease (direct and indirect)
Cardio protection
Hypertension

5. Immune system disorders
Immune function, immune diseases and disorders
lncrease of systernic lnfectlous diseases due to altered Immune response
lncrease of local Infections due to altered Inimune response
Periodontal disease

En4s

‘1

Reproductive tract abnormalities
Uterlne fibroids
Abnormal vaglnal, cervlcal, uteririe, and oviduct anatomy
Ovaries: Premature ovarlars failure (PaF), decreased ovarlan

Respiratory tract in!ections
Exonthema subitum
Allergies other than asthma: allergic rhinitis allergic conjunctivitis and
atopic dermatitis (eczema)
Autoimmune diseases (mcl. thyroid disease(
Autolmmtme thyroid disease (AITD) (eg. Hashimoto’s thyroiditis,
Graven disease)
Multiple sclerosis (MS(
Systemic lupus erythemotosus (SLE)
Rheumatoid arthritis
Ulcerative colitis

reserve/lncreased atresla, aneuploldy, granulosa steroldogenesls,
ahered primordlal follicles, follicle growth, oocyte quality
Vaginal adenosis (benign abnormality)

Premature thelarche
Female idlopathlc precocious puberty / early menarche
Female delayed puberty
Dlsturbed menstruatlon cycle (Oligomenorrhea)

Early age at menopause

Isoia, childhood astlw(,.
Myalgic encephalopathy/chronic fatigue syndrome/post viral fatigue
syndrome (ME/CFS/PVF5)
Fibromyalgia (rheumatlc disorder(

Male reproductive problems
Hypospadws
Other male reproductive organ abnormalltles lreduced testis weight,
abnormal small penls, problems efferent ducts, altered AGD,
morphology of semlnlferous tubules, nippie retentlonl
Declmsirig fertility due to reduced semen quallty (abnormalities( and
quantity (oligospermia(
Testicular dysgenesis syndrome (TOS)
Epididymal cysts (infection/iriflammation of the tube that carries semen
Out of the testicle)
Orchitls (infectlon/inflammation of testis(
Male delayed puberty
Prostatic intraepithelial hyperplasla (PIN(
Prostatitis (prostate Inflammation)

Hematopoietic disorders and malignancies
Childhood lymphoma
Leukemfa
Non-Hodgkmn lymphoma
5. Other dlsorders and condltions
Population effects
lncrement death rate among menAse to lower testosterone
Sex rstio decllnlng male populatlon
-

Neuroendocrine disruption
Varlous dlseases that affect the pitultary or hypothalamus

2. Neurodevelopmental syndromes and conditlons
Neurobehavioral disorders

Adrenal disorders

Adrenocortlcal hyperplasla (growth, stress resporise)

Autisrn spectrum disorders A$Oj

Cushing’s disease

AD(H(D;attention deficit (hyperactivity),dlsorder

lQlass

—

Tisyroid disruption
Adult (sub)hypothyroldlsm

f

“

Cerebral palsy

Congenital hypothyroidism (causing mental retardation)

Nè(1f,EeWfects

Thyroid resistance syndrome

Psychomotor retardation, memory, learning problems
Depressive disorders
Behavioral problems: social, aggression, ansiety, sexual

Bone disorders
lncreased risk of bone fractures

Osteoporosis
Other bone disorders (eg. orthopedic defects, Irregular calcifications(

3. Hormonal cancers
Hormone-related cancers
Breast cancer
Endometrial cancer

Ovarian cancer
dear ceil adenocarcinoma of the vagina and cervin uteti
Prostate
Testis (testicular germ ceancer
Thyroid cancer

66

5.4.

Recommendations

Socio-econoinic cost estimates of EDCs
Use socio-economic cost estimates to show the extent of the potential impact of EDC
related health effects on society;
-

-

-

Use and further develop the modular approach that was introduced in this report to provide
context for interpretation of a disease and related costs, endocrine mechanisms and its
(potential) link with EDCs. This will provide more structure, transparency, uniformity and
completeness of information. The modular approach could also be applied in a broader
perspective to analyze other health impacts, a potentially causal agent, and associated socio
economic costs;
For transparency, provide background study parameters of source cost-of-disease studies, as
proposed in the modular approach presented in this report (providing a breakdown of costs
such as proposed in Table 8). As such, differences and similarities can easily be detected by
looking at crucial parameters and type of costs taken into account;

-

-

Develop a standardized cost estimate approach for cost-benefit evaluations in the context of
hazardous substances. Set criteria what kind of cost should be included and (best applicable)
methodology to be used, as a minimum, in order to declare validity of the results;
Since there is a difference in interpretation in types of costs, It would be preferred to
separate costs related to direct cost (“real” expenditures) from indirect and intangible costs
(cost that place a burden on society or on the quality of lives).

Socio-econoinic research
More research is needed towards costs of EDC-effects that are not yet quantified;
It seems valuable to perform European studies on the socio-economic impact of IQ loss. At
the moment only US studies are available. Furthermore, t would be valuable to further
reflect upon the meaning of this loss or value forgone in the context of societies in which
average 0 level is increasing;
More European-wide cost-of-disease studies are needed, to avoid uncertainties resulting
from extrapolating from one subpopulation or country to another. This will become even
more relevant since European policy will become increasingly important.
-

-

-

Research on EDCs
-

-

-

-

-

There is a need to generate more data on the EDC-attributable factor to disease burden and
individual health effects, as well as the (general) hormonal attribution to diseases;
More weil-designed epidemiological and toxicological studies should be performed, e.g.
that inciude sensitive window of exposure to EDCs, such as the developing child;
Especially for EDC-associated immunological effects, there is a need to generate more data
to close the information gap on adverse effects, mechanisms, and contribution of EDCs;
As neurodevelopmental disorders and metabolic disorders appear to have a high socio
economic burden, it is recommended to focus on these health effects in current testing
frameworks and develop and/or implement adequate screening methods;
More efforts are needed that could bridge the gap between academic research and
regulatory health risk assessment. For example in types of endpoints evaluated, a validated
or (in some cases) more uniform study design, relevance of studies, and how results are
re p0 rte d.
67

68

Financing and acknowledgements
This report has been financed by the Dutch Ministry of lnfrastructure and the Environment (IenM).
We thank Julia Verhoeven (RIVM), Betty Hakkert (RIVM), and Ronald Flipphi (lenM) for their support
and guidance.
We also would like to thank the reviewers of the draft version of the report and other contributors:
Lisette van Vliet (Health and Environment Alliance), Maria Noring and Mattias Carisson Feng
(Swedish Chemicals Agency), Stavros Georgiou (UK Health and Safety Executive), Leonardo Trasande
(New York University), Fleur van Broekhuizen, Paul van Gils and ZhiChao Dang (RIVM), Ardine de Wit
(RIVM, University Medical Centre Utrecht) and Cees Luttikhuizen (lenM).
The views expressed in this publication reflect the views of the authors and do not necessarily reflect
the views of the reviewers and other contributors.

69

OL

List of Abbreviations
AD(H)D
AGD
AITD
ART
ASD
BPA
CFS
DALY
DAP
DAP
DDE
DDT
DHC
DNHC
EAF
EC
ED
EDC
EDC-1
EDC-2
Chemicals
EEA
EME
EPA
ERR
EU
GDP
HEAL
IC
ICSI
lD
IHC
INHC
IPCC
IPCS
IQ
IRAS
IUGR
IVE
ME
MS
NGO
OECD
OP
OR
PBDE
PCB
PCOS

Attention Deficiency (Hyperactivity) Disorder
Anogenital distance
Autoimmune thyroid disease
Assisted reproductive technology
Autism Spectrum Disc rders
Bisphenol-A
Chronic fatigue syndrome
Disability Adjusted Life Year
dialkyl phosphate
dialkylphosphate
Dichlorodiphenyldichioroethylene
Dichiorodiphenyltrichloroethane
Direct Healthcare Cost
Direct Non Healthcare Cost
environmental attributable fraction
European Commission
Endocrine Disrupting
Endocrine Disrupting Chemical
The Endocrine Society’s Scientific Statement on Endocrine Disrupting Chemicals
The Endocrine Society’s Second Scientific Statement on Endocrine Disrupting
European Environmental Agency
electromagnetic fields
(US) Environmental Protection Agency
Exposure response relationship
European Union
Gross Domestic Product
Health and Environment Alliance
Intangible Cost
Intracytoplasmatic sperm injection
Intellectual Disability
Indirect Healthcare Cost
Indirect Non Healthcare Cost
Intergovernmental Panel on Climate Change
International Programme on Chemical Safety
Intelligence Quotient
Institute for Risk Assessment Sciences
Intrauterine growth restriction
In vitro fertilization
Myalgic encephalopathy
Multiple Sclerosis
Nongovernmental Organization
Organisation for Economic Co-operation and Development
Organophosphate (or: organophosphorous) pesticide
Odds Ratio
Polybrominated diphenyl ether
Polychlorinated biphenyl
Polycystic ovarian syndrome
71

PIN
POF
POP
PPP
PPPR
PVFS
QALY
REACH
RIVM
SLE
T
TDS
UNEP
UU
WHO

Prostatic intraepithelial hyperplasia
Premature ovarian failure
Persistent Organic Pollutant
Purchasing Power Panty
Plant Protection Products Regulation
Post viral fatigue syndrome
Quality Adjusted Life Year
Registration, Evaluation, Authorisation and Restriction of Chemicals in the EU
(Dutch) National Institute for Public Health and the Environment
Systemic lupus erythematosus
Testosterone
Testicular dysgenesis syndrome
United Nations Environment Programme
Utrecht University
World Health Organization

72

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Detailed evaluation of parameters relating to EDC
attributable cost per disease
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Institute for Risk Assessment Sciences
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