Tài liệu THE BURDEN OF DISEASE ATTRIBUTABLE TO ENVIRONMENTAL POLLUTION pptx

THE BURDEN OF DISEASE
ATTRIBUTABLE TO ENVIRONMENTAL POLLUTION


Professor Ian Mathews and Dr Sharon Parry
Department of Epidemiology, Statistics, Public Health
University of Wales College of Medicine
Cardiff University
Heath Park
Cardiff
CF14 4XN


The views presented in this paper are those of the authors and do not necessarily
represent HPA views







July 2005


The burden of disease attributable to environmental pollution
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Summary
This paper presents a summary of the information available in the literature aimed at
estimating the fraction of mortality and/or morbidity that can be attributed to

environmental factors. It is a first step in the process of quantifying the possible burden
of disease from environmental pollution. Current estimates are based on very uncertain
data and limited datasets and therefore need to be interpreted with extreme caution.

The extent to which environmental pollutants contribute to common diseases is not
accurately resolved. However, global estimates conservatively attribute about 8-9% of
the total burden of disease to pollution. Data is presented on the evidence available for
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. Health effects from environmental lead
exposure and disruption of the endocrine function are also presented.

1. Background

The need to estimate the burden of disease associated with pollutants is highlighted not
only by the evidence base on associations but also by the scale of use of chemicals in
our modern society. Fifteen thousand chemicals are produced in quantities in excess of
10,000 pounds annually and 2,800 are produced in annual quantities in excess of 1
million pounds. These high volume chemicals have the greatest potential to be
dispersed in environmental media and less than half of these have been tested for
human toxicity (US EPA, 1996; Goldman LR et al, 2000; NAS, 1984). There are
approximately 30,000 chemicals in common use and less than 1% of these have been
subject to assessment of toxicity and health risk (Royal Commission on Environmental
Pollution, 2003).

Environmental pollutants may be defined as chemical substances of human origin in air,
water, soil, food or the home environment. The extent to which such pollutants may
contribute to common diseases of multi-factorial aetiology is not accurately resolved.
However in recent years attempts have been made to estimate the environmentally
attributable burden of disease globally, in the USA and in regions of Europe. In the first

instance estimation has concentrated on health outcomes for which there is strong
evidence of an association with pollutants.

At a global level a summary of early estimates first appeared in the 1997 report ‘Health
and Environment in Sustainable Development’ by the World Health Organisation (WHO,
1997). In subsequent years further estimates have been made of the fraction of
mortality and morbidity that can be attributed to environmental factors (Smith KR et al,
1999; Ezzati M et al, 2002). Substantial proportions of global disease burden are
attributable to these major risks where developing countries bear the greatest burden,
unsafe water and indoor air pollution are the major sources of exposure and children
under five years of age seem to bear the largest environmental burden. Estimates vary
The burden of disease attributable to environmental pollution
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but conservatively about 8-9% of the total disease burden may be attributed to pollution
(Briggs D, 2003).

In the framework of the European Environment and Health Strategy various
Technical Working Groups on priority diseases reviewed the evidence base in
support of the development of the Children’s Environment and Health Action Plan
for the European region (CEHAPE) expressed in the Budapest declaration (WHO
2004a). It was considered that one sixth of the total burden of disease from birth
to 18 years is accounted for by exposure to contaminated air, food, soil and water
causing respiratory
diseases, birth defects, neuro-developmental disorders and
gastrointestinal disorders. Waterborne gastrointestinal disorders are not a major public
health problem in the UK. The remaining priority diseases identified by CEHAPE are
considered below for children.

In Section 2 two different methodologies are outlined by which burden of disease
attributable to environment can be estimated. In the first the health loss due to

environmental risk factor(s) is calculated as a time-indexed “stream” of disease burden
due to a time-indexed “stream” of exposure. Such a time-indexed “stream” of exposure
data is only available for environmental lead and ambient urban outdoor air pollution.
Therefore in Section 9 WHO estimates of the burden of disease attributable to
environmental lead exposure are presented. Similarly in section 10 and 11 estimates
are given of the burden of disease due to exposure to air pollution published by the
Committee on the Medical Effects of Air Pollution of the Department of Health.

Since population exposure data are lacking in connection with asthma, cancer and
neurobehavioral disorders a second methodology is employed in Sections 3, 5 and 6.
This was devised in the U.S. specifically for children and is outlined in Section 2. This
method is also used to infer the burden of allergy attributable to environment in
Section 4.

Finally the primary research literature was assessed to estimate the burden of
congenital malformations attributable to environment (Section 7) as well as effects of
ambient air pollution on birth weight (Section 8) and on children’s lung function (Section
10).

2. Methodology

The Global Burden of Disease (GBD) 1990 project stimulated debate about the crucial
role of risk factor assessment as a cornerstone of the evidence base for public health
action. It was affected by a lack of conceptual and methodological comparability across
risk factors but the Comparative Risk Assessment (CRA) project co-ordinated by WHO
was planned as one of the outputs of the GBD 2000 project to strengthen these aspects.
(WHO 2004b). In particular in the CRA framework:

• The burden of disease due to the observed exposure distribution in a
population is compared with the burden from a hypothetical distribution or

The burden of disease attributable to environmental pollution
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series of distributions, rather than a single reference level such as the non-
exposed population.

• The health loss due to risk factor(s) is calculated as a time-indexed
“stream” of disease burden due to a time-indexed “stream” of exposure.

• The burden of disease and injury is converted into a summary measure of
population health, which allows comparing fatal and non-fatal outcomes,
also taking into account severity and duration
.

The CRA framework has been used to investigate the burden of disease associated with
exposure to a limited number of environmental risk factors. These are: unsafe water,
sanitation and hygiene, urban air pollution and indoor air pollution from household use of
solid fuels as well as lead exposure (WHO 2004c).

To provide the knowledge base for the development of the Children’s Environment and
Health Action Plan for the European region (CEHAPE), the burden of disease
attributable to environmental factors (BODAE) was assessed in terms of deaths and
disability-adjusted life years (DALYS) among children and adolescents. The
assessment was restricted to outdoor and indoor air pollution, inadequate water and
sanitation and lead (Valent F et al, 2004). The methodology employed is outlined in
Appendix 1 and used the distribution of risk-factor exposure within the study population
and the exposure-response relation for the risk factor to calculate the impact fraction for
the particular health outcome.

To date the estimates of burden of disease attributable to environmental factors
provided by the WHO are of limited value in a UK context with the exception of lead

exposure. Inadequate water and sanitation and indoor air pollution from household use
of solid fuel for cooking and heating are not major issues in the UK. Further the
population health effects arising from outdoor ambient air pollution have been estimated
by the Committee on the Medical Effects of Air Pollution (COMEAP) of the Department
of Health (COMEAP 1998).

However, a different methodology has been developed and employed in the USA to
estimate the morbidity and mortality for asthma, cancer and developmental disabilities in
children. (Landrigan P.J. et al 2002) For each disease, expert panels were convened
from prominent physicians and scientists with extensive research publication in the field.
Each panel member was supplied with an extensive collection of reprints of published
articles that discussed linkages between the disease in question and toxic
environmental exposures. A formal decision-making process, the modified Delphi
technique (Fink A. 1984), was then enacted by which the panel developed a best
estimate from 0% to 100% of the Environmentally Attributable Fraction (EAF) for the
disease in which they were expert. Panels chose deliberately not to consider outcomes
related to tobacco or alcohol that are the consequence, at least in part, of personal or
familial choice. It is these EAF’s which are used below in estimating the BODAE for the
The burden of disease attributable to environmental pollution
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population of children in England and Wales for asthma, cancer and developmental
disabilities.

3 Asthma

3.1 Evidence of environmental aetiology

It is reasonable to assume that the variations in asthma prevalence are largely
attributable to environmental factors. Although genetic differences could contribute to
the geographical pattern, it seems very unlikely that they could account for the great

variation that is found within Europe, and they obviously do not explain the time trends.

In children and young adults, asthma usually involves an allergic reaction to inhaled
allergens. The simplest explanation of variations in prevalence would be a
corresponding variation in exposure to the principal allergens. The house dust mite is
the source of the allergen to which asthmatic patients are most commonly sensitive. The
changes in asthma prevalence have therefore been ascribed to increased exposure to
house dust mites, consequent upon changes within houses such as more fitted carpets
and better insulation. But in fact there is little evidence that exposure to mites has risen,
apart from one study.

The effects of air pollution on children’s health has been reviewed (WHO, 2005) and it is
considered that air pollution exacerbates symptoms of asthma and that the respiratory
health of children, especially those with asthma, will benefit substantially from a
reduction in air pollution especially that from motor vehicle exhausts. Some air
pollutants (diesel particulates) appear to potentiate the effects of airborne allergens.
There is little evidence for a causal association between prevalence/incidence of asthma
and air pollution. There is some (rather inconsistent) evidence that asthma prevalence
is related to the proximity of peoples’ residence to roads

(Maynard RL, 2001). Asthma
attacks can certainly be provoked by episodes of acute air pollution.

Most people spend most of their time indoors, so the quality of indoor air is probably
more important than that of outdoor air. Oxides of nitrogen are produced by gas cookers
and in some studies (though not in others) have been associated with respiratory
symptoms

(Hasselblad V et al, 1992). There is some evidence that asthma is
associated with formaldehyde and other volatile organic compounds in the home

(Krzyzanowski M et al, 1990; Hosein HR et al, 1989)

or school

(Smedie G et al, 1997)

environment. These compounds are emitted by various sources used in furniture,
hobbies and other indoor activities; they may act as respiratory irritants or increase the
risk of allergy as represented by serum IgE levels. In numerous surveys, indoor mould
growth and dampness have been associated with respiratory symptoms (Burr ML,
2001). Environmental tobacco smoke (passive smoking) increases a child’s risk of
respiratory illness, and smoking during pregnancy has adverse effects on the lungs of
the unborn child. There is some uncertainty as to whether smoking (active or passive)
actually causes asthma, partly depending on how the disease is defined. It may be the
case that it aggravates rather than causes it

(Strachan DP et al, 1998).

The burden of disease attributable to environmental pollution
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3.2 Burden of disease

Asthma is a common disease. Although its mortality is fairly low, it gives rise to a great
deal of anxiety, particularly in childhood, when it is a major cause of hospital admission
and morbidity. The peak incidence is in the first five years of life, though the disease can
start at any age. The prevalence declines at adolescence, when remissions tend to
exceed incidence, but relapse often occurs during adult life after a symptom-free
interval. It is sometimes difficult to distinguish asthma from other common conditions,
such as respiratory infections in infants and chronic obstructive pulmonary disease in

later adult life. If asthma is defined more narrowly in some surveys than in others, large
differences in prevalence can be created quite artificially. Nevertheless, a useful body of
data has been produced by numerous surveys that have used similar methods, and
some fairly consistent patterns are now emerging.

The International Study of Asthma and Allergies in Childhood (ISAAC, 1998) was
conducted in 155 centres within 56 countries and the prevalence of wheeze in the last
12 months in 13-14 year olds was 29-32% in the UK. The European Community
Respiratory Health Survey (ECRHS) was conducted in 48 centres within 22 countries,
mostly in Western Europe

(Janson C et al, 2001). It showed a similar pattern to that
found by ISAAC. The prevalence of specific IgE, a marker of atopic sensitivity, which is
known to be associated with asthma was much higher in UK than in Iceland, Greece,
Norway, Italy and parts of Spain.

Wherever a survey has been repeated after an interval of 10 years or more, in the same
area using the same methods, the prevalence of asthma has been found to have risen.
Most of these surveys have used questionnaires enquiring about symptoms (particularly
wheeze) rather than asthma alone, so the increase is not merely attributable to a
change in diagnostic fashion.

One of these (in South Wales) used an exercise challenge test and from 1973 to 1988
asthma prevalence increased, as measured by symptoms and exercise challenge (Burr
ML et al, 1989).

A repeat survey in 2003 (unpublished) suggests that a further rise has
occurred in symptoms but not in the response to exercise. The consistency with which
increases have been reported from all parts of the world is remarkable. Some support
for a true increase is also provided by increases in related diseases such as allergic

rhinitis and eczema (although the data are largely derived from questionnaires);
successive surveys in Japan have shown a rise in the prevalence of specific IgE in
serum

(Nakagomi T et al, 1994).

The Welsh Health Survey recorded that in 2003/2004 10% of adults (aged over 16
years) and 12% of children reported that they were currently being treated for asthma
and 1% of children reported that they were currently being treated for other respiratory
conditions (Welsh Health Survey, 2003). The Health Survey for England (2002)
reported rates of doctor diagnosed asthma of 20.5% in 0-15 year olds and 14.5% for all
ages.

The burden of disease attributable to environmental pollution
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The burden of disease registered in Primary Care is recorded by 371 practices across
the UK submitting data to the General Practice Research database. The prevalence of
asthma in different age groups is shown below.
The burden of disease attributable to environmental pollution
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Prevalence of treated asthma per 1000 patients
For Males (1998)


0-4
years
5-15
years
16-24

years
25-34
years
35-44
years
45-54
years
55-64
years
65-74
years
75-84
years
85+
years
crude
rate (all
years)
age
standardised
rate (all
years)
rate per
1000 97 132.1 72.8 55.3 47.2 44.5 59.2 80.7 89.4 61.8 72.3 73.2
LCL 93.8 129.9 70.7 53.8 45.8 43.1 57.4 78.3 85.9 55.7 71.7 72.5
UCL 100.2 134.3 74.8 56.8 48.5 45.9 61.1 83.2 92.9 67.9 73 73.9
No. of
Cases
3182 11979 4571 5020 4274 3779 3745 3809 2303 373 43035 43035

Prevalence of treated asthma per 1000 patients
For Females (1998)


0-4
years
5-15
years
16-24
years
25-34
years
35-44
years
45-54
years
55-64
years
65-74
years
75-84
years
85+
years
crude
rate (all
years)
age
standardised
rate (all

years)
rate per
1000 62.5 104.1 85.2 65.3 62.4 64.8 79.9 88 80 52.2 76.2 76.5
LCL 59.8 102 83 63.6 60.8 63.1 77.8 85.6 77.4 48.7 75.6 75.8
UCL 65.2 106.1 87.5 66.9 64 66.5 82 90.4 82.7 55.6 76.9 77.2
No. of
Cases
1946 9014 5066 5818 5473 5369 4965 4694 3174 829 46348 46348


LCL – Lower Confidence Level; UCL – Upper Confidence Level
The burden of disease attributable to environmental pollution
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Some information is available as part of the Hospital Episode Statistics detailing
episodes of admitted patient treatment delivered by NHS hospitals in England. The
most recent data is available for the 2003/2004 financial year when 63,949 episodes of
unspecified asthma (ICD10: J45.9) and 9,228 episodes of status asthmaticus (ICD10:
J46.X), 60 episodes of nonallergenic asthma (ICD10: J45.1), 26 cases of mixed asthma
(ICD10: J45.8), were recorded.

3.3 Burden of Asthma attributable to Environment

3.3.1 Asthma attributable to outdoor non-biologic pollution

The expert US panel on asthma considered only outdoor non-biologic pollutants from
sources potentially amenable to abatement such as vehicular exhausts and emissions
from stationary sources. Using this definition the panel estimated that 30% of acute
exacerbations of childhood asthma (range 10-35%) are environmentally related
(Landrigan PJ et al, 2002). Applying this EAF to national survey data, Primary Care
data and data on hospital inpatient episodes gives:

Total
Population
▲
Prevalence
rate
EAF BODAE
Number of children in England and Wales aged 10-14 years
with wheeze in last 12 months
3425023 29.0% 30% 297977
Number of children in England and Wales aged 0-9 years
with wheeze in last 12 months
6401995 29.0% 30% 556974
Number of children in England and Wales aged 0-15 years
currently being treated for asthma
10488736 12.0% 30% 377594
Number of children in England and Wales aged 0-15 years
with doctor diagnosed asthma
10488736 20.5% 30% 645057
Number of adults in England and Wales aged 16 and over
currently being treated for asthma
41553180 10.0% 30% 1246595
Number of adults in England and Wales aged 16 and over
with doctor diagnosed asthma
41553180 14.5% 30% 1807563

▲
Source: Census 2001 data.
(i) ISAAC survey data was for 13 to 14 year olds so it is assumed that the prevalence of wheeze in 10-12 year olds is

the same
(ii) Assuming the same prevalence in 0-10 year olds as in 12-13 year olds












The burden of disease attributable to environmental pollution
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Environmentally attributable prevalence of treated asthma per 1,000 patients in Primary Care

Age Sex BODAE per 1000 patients
0 – 4 Male 97 x 30% = 29
5 – 15 Male 132.1 x 30% = 40
0 – 4 Female 62.5 x 30% = 19
5 – 15 Female 104.1 x 30% = 31
All ages Male 72.3 x 30% = 22
All ages Female 76.2 x 30% = 23

Inpatient episodes in NHS hospitals in England in 2003/2004


Unspecified asthma ICD10:J45.9 63949 x 30% = 19185

Status asthmaticus ICD10:J46.X 9228 x 30% = 2768
Nonallergenic asthma ICD10:J45.1 60 x 30% = 18
Mixed asthma ICD10:J45.8 26 x 30% = 8

3.2.2 Proportion of asthma attributable to indoor biologic pollution.

There is strong evidence linking asthma exacerbations to derp 1 allergen indoors and relatively
strong evidence linking asthma exacerbations to contamination of the indoor environment with
moulds. Survey data demonstrates that 95% of asthmatics have derp 1 concentrations in their
mattress dust in excess of WHO guideline value of 2 µg/g
-1
. Survey data also demonstrates that
approximately 17% of homes are contaminated with mould. Since most people spend more
than 90% of their time indoors there is significant exposure of the asthmatic population to these
allergens. Although no estimates of EAF from these sources are available it is likely to be of
similar magnitude to that due to outdoor non biologic sources.

3.4 Conclusion

The burden of asthma exacerbations attributable to non-biologic air pollution is considerable.
Asthma exacerbations can be measured by the prevalence of wheeze in the last 12 months and
prevalence of current treatment for asthma. Using UK data on such prevalence and the EAF
cited above the burden of asthma exacerbations attributable to non-biologic pollution can be
estimated. This is 855,000 of those children reporting wheeze in the last twelve months and
378,000 of those children currently being treated for asthma as well as approximately one and a
quarter million of those adults currently reporting being treated for asthma and 22,000 of
inpatient episodes per annum.

The epidemiological evidence base linking asthma exacerbations to indoor allergens such as
der p1 and moulds is no less strong than that relating asthma to non-biologic outdoor air

pollution. It is, therefore, likely that the EAF used to obtain the above estimates could be
doubled to give a more realistic estimate of the burden of asthma exacerbations attributable to
environmental factors.



The burden of disease attributable to environmental pollution
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4. ALLERGY

4.1 Evidence of environmental aetiology
The term allergy describes those immune responses that are potentially harmful to the
host but which are directed against external agents that in themselves are not
particularly harmful to us. Many individuals synthesise specific IgE antibodies against
common environmental allergens, and they are termed atopic. For example, grass or
tree pollens or nickel jewellery are indeed foreign material but pose no threat to us when
we come into contact with them. However many individuals mount an immunological
reaction to such structures which results in inflammation at the site of contact with the
allergen and hence symptoms and disease.

The targets against which most allergic diseases are directed (i.e. the allergens
themselves – house dust mite, cat, grass pollens etc) are not becoming particularly
more prevalent but the level of sensitization to them in the general population is. The
change in the biologic response to them is thought to reflect the effects of unidentified
factors (possibly dietary fats and air pollutants) involved in the process of sensitization
which occur at the level of the antigen presenting cell – T cell interaction in each
individual.

There would appear to be an increase in the numbers of the general population exposed

to some allergens, and possibly in their levels of exposures to some of these materials.

1. As consumers: toothpastes, household sprays, cleaning materials, perfumes
2. Indoor environmental agents: e.g. volatile organic compounds
3. Outdoor pollutants: diesel exhaust fumes

4.2 Burden of allergic disease

Up to 35% of the population demonstrate evidence upon testing of IgE immunological
reactivity to allergens, a high proportion of whom (5-10% of the population) show clinical
features of one or more allergic disorders (most commonly asthma, eczema or hay
fever).

Allergic rhinitis affects about 10% of the population, with nasal itching, sneezing,
congestion and rhinorrhoea, and it may be accompanied by allergic conjunctivitis
(itchy, lacrimating eyes). Mast cell degranulation resulting in inflammation and oedema
can be so severe as to block the sinus ostia and Eustachian tubes with resulting
secondary bacterial infection. Nasal polyps may occur (mucosal sacs containing
inflammatory fluid and cells) and allergen avoidance is difficult.

Welsh Health Survey (2003) show that 11% of children report skin complaints. Health
Survey for England (2001) data show that the rate of doctor diagnosed eczema was
13% for all ages in 2001:

The burden of disease attributable to environmental pollution
11
4.3 Burden of allergic disease attributable to environment

There is no evidence on the EAF for allergic disease. If it is assumed that the
exposures and mechanisms involved in the aetiology and exacerbation of asthma are

similar to those involved in allergy, then the EAF for asthma (i.e. 30%), the percent of
children with skin complaints (11%) and of adults with allergic rhinitis (10%), may be
used to infer the BODAE for allergy.

Allergic rhinitis (Total population of Eng & Wales) 52,041,916 x 10% x 30% = 1,561,257
Skin complaints (Population of children) 10,488,736 x 11% x 30% = 346,128

4.4 Conclusion
Environmental factors may be responsible for one and a half million cases of allergic
rhinitis and one third of a million cases of skin complaints in children.


5 CANCER

5.1 Environmental aetiology

Monozygotic and dizygotic twins have been studied in an attempt to apportion the
relative importance of genes and environment in the aetiology of cancer (Ahlbom A, et al
1997, Verkasalo PK 1999, Lichtenstein P et al 2000). The largest dataset used for
family studies is the nationwide Swedish Family – Cancer Database with more than
700,000 cancers and a population of 9.6 million. Modelling of this data gave estimates
that environment has a principal causative role in cancer at all studied sites except for
thyroid (Czene K 2002).
5.2 Burden of disease and Burden of disease attributable to Environment

To assess the environmentally attributable fraction of childhood cancer an expert panel
was convened in the US in paediatric oncology, epidemiology and environmental
medicine. The panel considered that extra genetic factors, defined broadly, caused 80-
90% of cancers but noted that the specific causes of childhood cancer are largely
unknown. It concluded that insufficient evidence exists to assign a best estimate of the

fraction of childhood cancer specifically attributable to toxic chemicals in the
environment (Robinson LL 1995). It agreed that the correct EAF would be in the range
5 to 90% (Landrigan PJ 2002). Therefore in calculating the environmental burden of
disease for childhood cancer for England and Wales the lowest estimate of 5% has
been used below.

Since Adult occupational exposure to chemicals, cigarette smoking and alcohol
consumption are prevalent confounders to environmental exposure, no attempt has
been made to quantify the BODAE for adult cancers.

Common Childhood (0-14 years) Cancers in England and Wales (2001)

Disease ICD10 code Cases EAF BODAE
The burden of disease attributable to environmental pollution
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(no. of cases)
Kidney C64-C66, C68 males 33 5% 1
females 40 5% 2
persons 73 5% 3
Brain and CNS C70-C72 males 173 5% 8
females 135 5% 6
persons 308 5% 15
NHL C82-C85, C96 males 54 5% 2
females 22 5% 1
persons 76 5% 3
Leukaemia C91-C95 males 202 5% 10
females 186 5% 9
persons 388 5% 19
All Malignancies (ex. skin) All C codes (ex. C44) males 660 5% 33
females 583 5% 29

persons 1243 5% 62


5.4 Conclusion

Currently the best available estimate is that between 5% and 90% of childhood cancers
may be attributable to toxic chemicals in the environment.

The burden of disease attributable to environmental pollution
13
6. Neuro-developmental disorders

6A Attention Deficit Hyperactivity Disorder (ADHD)

6A.1 Evidence of environmental aetiology

For all complex diseases, there is increasing evidence that genes may operate by
influencing sensitivity to environmental risk factors. There have been more than 14 twin
studies across the world that have shown that ADHD is highly heritable with reported
heritability estimates of between 60% and 91% (Thapar et al, 1999; Thapar 2002).
Finally adoption studies have also shown increased rates of ADHD amongst biological
but not adopted relatives of individuals affected by ADHD (Thapar, 2002). Most interest
to date has focussed on examining variants within genes coding for enzymes and
proteins in the dopamine neurotransmitter system. Association of a variant in the
dopamine D4 receptor gene (the 7 repeat allele of a 48 bp VNTR) with ADHD has been
widely replicated and shown to be significantly in a meta analysis of 14 studies (Faraone
et al, 2001).

There has been increased interest in gene-environment interaction effects in childhood
psychopathology. To date there have been virtually no published studies examining the

co-action and interaction of genes and environment in ADHD. However, preliminary
findings from one study suggest interaction between a dopamine transporter gene
variant (previously found to be associated with ADHD) and smoking in pregnancy (Kahn
et al, 2003).

Moreover, several studies have found a dose-response relationship between the
number of cigarettes smoked in pregnancy and ADHD symptom scores in offspring
(Linnet et al, 2003). There have been fewer studies examining the association of
alcohol and drug use in pregnancy and ADHD and the evidence for association is
mixed. (Linnet et al, 2003). There is evidence that exposure to PCBs in utero (resulting
from maternal ingestion of food contaminated with PCBs) may damage the child’s
developing nervous system and produce intelligence and behavioural deficits such as
inattention (Jacobson & Jacobson, 1996).

Ingestion of lead by children is known to lead to adverse neurocognitive consequences,
specifically lowered IQ (Schwartz 1994). Some studies have suggested an association
of lead levels and ADHD symptoms (Tuthill, 1996) but it is not clear that exposure to
lead is an important risk factor for the clinical diagnosis of ADHD.

There is some evidence that head injury maybe associated with ADHD (Gerring et al,
1998) but other studies have not found such an association (Max et al 1997). Moreover,
head injury appears to be associated with a range of behavioural problems rather than
showing a specific relationship with ADHD and the evidence of an association between
head injury and adverse cognitive and psychiatric sequelae is more compelling for
severe rather than mild head injury (Goodman, 2002).

The burden of disease attributable to environmental pollution
14
6A.2 Burden of disease
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that is

only diagnosed if the child meets stringent diagnostic criteria. Two main diagnostic
schemes are used in psychiatry, the International Classification of Diseases (ICD; WHO,
1993), more often used in Europe and the DSM (American Psychiatric Press, 1994)
from the United States. The diagnostic criteria in the current versions of the
classification systems are similar although DSM-IV ADHD remains a more broadly
defined category than ICD-10 Hyperkinetic disorder.

The key features of ADHD are early onset, significant symptoms of inattention,
impulsiveness and over activity. These symptoms need to be developmentally
inappropriate and associated with functional impairment (for example educational
failure, peer difficulties). Both ICD-10 and DSM-IV also require that the symptoms (or
impairment) are pervasive, that is occur in different settings (typically home and school).

Evidence of brain dysfunction in individuals with ADHD has been found in cerebral
imaging studies including functional MRI (Magnetic Resonance Imaging), PET (Positron
Emission Tomography) and SPECT (single photon computed emission tomography)
studies (Overmeyer et al, 2000, Volkow et al, 2001). A recent well designed controlled
study published in the Journal of the American Medical Association reported clear
evidence that drug naive children with ADHD had decreased grey and white matter
volume and significantly smaller cerebellar volume compared to control children
(Castellanos et al, 2002). Many of these neurobiological studies have suggested
involvement of the prefrontal cortex and basal ganglia and there has been considerable
interest in dopaminergic neurotransmitter system (Zametkin & Liotto 1998) but it is clear
that the neurobiological basis of ADHD is complex with involvement of many pathways.
The prevalence of ADHD has been estimated at between 2 % and 5% (Faraone &
Wilens, 2003) although prevalence figures vary according to the diagnostic criteria used
(Costello et al 1996; Barkley, 1998). For Hyperkinetic Disorder, prevalence rates in the
UK have varied between 0.5% (for boys only) (Taylor et. al, 1991) to 1.4% in the most
recent UK survey (Meltzer et al, 2000). ADHD is much commoner in boys with a 3:1 sex
ratio found in epidemiological studies and an even higher sex ratio in referred samples

(Taylor et al, 1991; Barkley, 1998). Childhood ADHD frequently persists into
adolescence with many symptoms of the disorder continuing into adulthood (Barkley,
1998; Manuzza et al, 1998) although it is not clear how many continue to meet full
diagnostic criteria and whether current diagnostic criteria are appropriate for adults.
Increased rates of subsequent difficulties with employment, antisocial behaviour, driving
offences, increased rates of criminal activity, as well as substance abuse have been
noted (Barkley, 1998; Farrington et al, 1990).

There is considerable evidence for both under - and over diagnosis of ADHD in clinical
practice (Thapar & Thapar, 2003). In the UK, only around 50% of children with HKD are
recognised as having the disorder (Ford et al, 2003) and those referred show increased
rates of co morbid psychiatric conditions and family adversity (Woodward et al, 1997).

To date, there is no convincing evidence of recent, increased prevalence rates of ADHD
from UK epidemiological studies.
The burden of disease attributable to environmental pollution
15

6A.3 Burden of ADHD attributable to Environment

An expert committee convened by the US National Academy of Sciences (NAS)
estimated in 2000 that 3% of neurobehavioural disorders in American children are
caused directly by toxic environmental exposures and that another 25% are caused by
interactions between environmental factors, defined broadly, and genetic susceptibility
of individual children (NAS, 2000). The authors of this paper consider this study the
most authoritative published estimate of the EAF for these disorders and therefore have
relied on the NAS estimate. Of the total 28% of neurobehavioral disorders thought by
the NAS committee to be caused wholly or partly by environmental factors, it was
estimated that 10% (range 5-20%) are at least partly caused by toxic exposures, not
including alcohol, tobacco, or drugs of abuse. Using this information, the BODAE for

England and Wales can be estimated as follows:

Disease No. of children
(0-14)*
Prevalence rate No. of
cases**
EAF BODAE
ADHD 9,827,018 1.40% 137578 10% 13757

* in England and Wales (Census 2001)
** in England and Wales

6B Autism
Autism is now commonly regarded as belonging to a group of neurodevelopmental
disorders that are sometimes called pervasive developmental disorders. These are
childhood onset conditions but problems nearly always persist into adulthood. The key
clinical features of autism include:
• onset in early childhood (some type of abnormality by 36 months of age)
• communication problems (both comprehension and expression and gesture as well
as spoken language)
• social interaction (reciprocal -includes features like poor eye contact, lack of interest
in people)
• restrictive, repetitive patterns of behaviour (includes routines and rituals and
preoccupations with restricted subjects).

Other autistic spectrum disorders, notably Asperger’s syndrome, have similar
manifestations to autism but are generally less severe and meet some but not all of the
diagnostic criteria for childhood autism. The majority of children with autism (around 2/3)
have learning disability (mental retardation) and many develop epilepsy in adolescence
.

6B.1 Evidence of Environmental aetiology
Twin studies have shown that autism is highly heritable with a heritability of liability of
greater than 90%, which is higher than other genetically influenced multifactorial
neuropsychiatric disorders (Folstein & Rutter 1977; Bailey et al 1995). These family and
twin studies also show that genetic factors do not entirely account for autism and that
autism appears to be aetiologically as well as phenotypically heterogeneous. There is
also evidence that non genetic factors play an important role in influencing the
The burden of disease attributable to environmental pollution
16
phenotypic manifestation of autism, in that there appears to be as much variability in
symptom expression within monozygote twin pairs as between monozygote pairs
(LeCouteur et al, 1996).

Whole genome linkage scans based on samples of multiply affected relatives are
beginning to yield significant findings thereby highlighting chromosomal regions that may
harbour susceptibility genes. The most widely replicated region of linkage is on
chromosome 7q (Thapar & Scourfield, 2002). However the identification of a
susceptibility gene variant within this region and others chromosomal regions of interest
is awaited.

Exposure to heavy metals in utero has also been suggested as a risk factor (Edelson &
Cantor, 1998) with recent interest in maternal dietary intake of fish during pregnancy.

6B.2 Burden of disease

There is an extremely wide variation in the reported rates of autism. Rates between
0.007 and 0.21% have been reported. A recent authoritative review gave the median
prevalence rate as 0.1% (Fombonne, 2003). Just as for attention deficit hyperactivity
disorder (ADHD) the disorder is much commoner in boys than in girls (ratio 3:1) but it is

not known why this is the case (Rutter et al, 2003).

An increased prevalence rate over time has been reported with studies between 1966
and 1991 reporting an average prevalence of 0.044% and studies between 1992 and
2001 reporting an average prevalence of 0.127% (Volkmar et al, 2004).

In the only instance where prevalence rates were derived from successive birth cohorts
no statistically significant changes in prevalence rates of the disorder were found
(although the relatively low prevalence rates found in these 2 studies have raised some
concern that cases may have been missed (Volkmar et al., 2004).

6B.3 Burden of Autism attributable to Environment

Disease
No of children
(0-14)*
Prevalence rate
No of
cases**
EAF BODAE
Autism 9,827,018 0.10% 9827 10% 982

* in England and Wales (Census 2001)
** in England and Wales

6C Learning disability

Definitions
The formal definition of ‘learning disabilities’ or ‘intellectual disabilities’ includes the
presence of:

• A significant intellectual impairment
The burden of disease attributable to environmental pollution
17
• Deficits in social functioning or adaptive behaviour (basic everyday skills) which
are present from childhood

‘Significant impairment of intelligence’, is usually defined as an intellectual quotient (IQ)
score more than two standard deviations below the general population mean (British
Psychological Society, 2000). This means an IQ below 70 on recognised IQ tests such
as the Adult Intelligence Scale (Wechsler D, 1998) or the Intelligence Scale for Children
(Wechsler D, 1992).

6C.1 Evidence of environmental aetiology

Biological, social and environmental factors are involved in causing learning disabilities.
Biological causes include genetic factors (e.g. Downs syndrome), antenatal factors (e.g.
lead intoxication), perinatal factors (e.g. birth asphyxia) and postnatal factors (e.g.
injury).

Between one in five and one in three children with severe learning disabilities have no
identifiable biological cause.

6C.2 Burden of disease

Studies across North America, Europe and Australia typically use IQ assessments to
classify persons as having mild (IQ 50 or 55 to 70) or severe (IQ <50 or 55) learning
disabilities. Comprehensive reviews of the literature indicate that the overall prevalence
rate for severe learning disabilities is between 3 and 4 people per 1,000 population.
This gives between 230,000 and 350,000 people in the UK with severe learning

difficulties.

Studies of mild learning disabilities have reported between less than 10 and 25-30
people per 1,000 population which suggests that between 580,000 and 1,750,000
people in the UK have a mild learning disability.

The latest figures (2002/2003) for children on the social services register of children with
learning disabilities in Wales are 2805.

The Welsh Assembly Government collates information on children in education with
special educational needs including those with a formal statement of special need. See
table below for numbers.

The UK education system uses the term ‘learning difficulties’, rather than ‘learning
disabilities’. The Warnock Committee proposed that the term ‘learning difficulties’ be
defined as:
• A greater difficulty in learning than the majority of children of the same age
• A disability which prevents or hinders the child from making use of ordinary
educational facilities.

The burden of disease attributable to environmental pollution
18
They suggested that about one in five children would have a learning difficulty at some
time in their lives, arising, for example, from medical problems, sensory impairments,
physical disabilities, emotional and behavioural difficulties, language impairments,
specific learning problems (such as dyslexia), autism or pervasive learning difficulties.

Pupils (of any age) with statements in schools, by type of school and need (Source
Statistical Directorate, 2004)

Primary Secondary Special All
Pupils with a special need but no statement:
47,335 27,289 . 74,624
Moderate learning difficulties 18,519
9,842
.
28,361
Severe learning difficulties 458
57 .
515
Profound & multiple learning difficulties 33
1 .
34
Specific learning difficulties 3,891
4,223
.
8,114
Autistic Spectrum Disorders 245
57 .
302
Physical disabilities 358
236 .
594
Hearing impairment 411
270 .
681
Visual impairment 206
117 .
323
Multiple sensory impairment 19

8 .
27
Speech, language & communication 4,017
521 .
4,538
Emotional & behavioral difficulties 3,437
4,010
.
7,447
Medical difficulties 384
158 .
542
Other 11,045
5,088
.
16,133
Not stated 4,312 2,701
.
7,013
Pupils with a statement of special need: 5,817 6,350 3,752 15,919
Moderate learning difficulties 1,464
2,124
680 4,268
Severe learning difficulties 427
280
1,239 1,946
Profound & multiple learning difficulties 152
38
519 709
Specific learning difficulties 485

1,465
15 1,965
Autistic Spectrum Disorders 452
185
526 1,163
Physical disabilities 413
319
89 821
Hearing impairment 194
203
10 407
Visual impairment 121
125
6 252
Multiple sensory impairment 16
8
5 29
Speech, language & communication 1,087
396
104 1,587
Emotional & behavioral difficulties 606
634
524 1,764
Medical difficulties 107
49
11 167
Other 248 296 17 561
Not stated 45 228 7 280

6C.3 Burden of Learning Difficulties attributable to Environment

Disease No children/
adults
Prevalence
rate
No. of cases
**
EAF BODAE
Learning difficulties
(children 0-14)
9,827,018 13.50% 1326647 10% 132664
Learning difficulties
(adults)
41553180 0.3% 124659.5 10% 12466

* in England and Wales (Census 2001); ** in England and Wales
The burden of disease attributable to environmental pollution
19

6.4 Conclusion
In children, approximately 133,000 cases of learning difficulty, 14,000 cases of ADHD
and 1000 cases of Autism may be attributable to environmental factors. However, these
estimates are very rough and should be treated with caution
.

7 CONGENITAL ABNORMALITIES

7.1 Evidence for environmental aetiology

A large study in the UK revealed that 80% of the UK population reside within 2 Km of a

landfill site (Elliot P, et al 2001) and that the relative risk of a congenitally malformed
baby for mothers in this region in proximity was 1.01. Similar studies in Europe (Dolk H,
et al 1998) and Wales (Palmer SR et al, 2005; Nix B, et al 2005) give relative risk
estimates of 1.33, 1.39 and 1.19 respectively. Therefore by assuming that the increase
is due to environmental factors and if this was the only environmentally attributable risk
(a conservative estimate) the EAF may be chosen at a mid-range value of the above
relative risk estimates (i.e. 1.20).

7.2 Burden of disease

The following outlines the incidence and outcome for selected congenital anomalies in
the Welsh population recorded by the Congenital Anomaly Register and Information
Service (CARIS).
The burden of disease attributable to environmental pollution
20

Con Mals 1998-2003 Wales

Congenital Malformation
Cases
(n)
Gross rate(all
cases)/10,000
live&still
births
All cases 8146 429
Musculoskeletal 1429 75
Abdominal Wall Defects 192 10
Gastrochisis 94 5
Exomphalos 81 4

Cleft Lip and Cleft Palate 133 7
Cleft Lip 66 3
Cleft Palate 187 10
Upper Limb reduction defects 147 8
Lower Limb reduction defects 76 4
Anencephalus 143 8
Spina bifida 155 8
Encephalocele 39 2
Complex Cyanotic Disease (CHD) 134 7
Transpositional great vessels 79 4
Fallots 55 3
Ventricual septal defects (VSD) 945 50
Atrioventicual septal defects (AVSD) 113 6
Hypospadias 356 19
Chromosomal 908 48
trisomy 21 - Down syndrome 377 20
trisomy 18 - Edwards syndrome 89 5
trisomy 13 - Patau syndrome 53 3
triploidy / polyploidy 44 2
Turner's syndrome 83 4
Klinefelter's syndrome 19 1
other anomalies sex chromosomes 36 2
deletions 57 3
other chromosome anomalies 157 8


7.3 Burden of congenital malformations attributable to environment

Assuming that the observed increased risk in proximity to landfill sites is due to
environmental factors and using an EAF of 0.2 then the burden attributable to

environment would be a gross rate of 86 per 10,000 live and still births.

8. Effects on birth weight of ambient air pollution

Birth-weights for babies born in Wales between 1983 and 1997 indicate that at 32 weeks
gestation around 20% are born at a very low birth weight (<1500g) and around 95% are
born at a low birth weight (< 2,500g). At 36 weeks gestation less than 3% are born at
very low birth weight and around 25% are born at low birth weight. At 40 weeks less
The burden of disease attributable to environmental pollution
21
than 3% of babies are born below 2500g (Welsh Child Health System. All births in
Wales 1983-1997)

In a population-based case control study in the United States the combined effect on
very low birth rate (<1,500g) of SO
2
and total suspended particle (TSP) levels was
analysed, using annual exposure estimates [Rogers et al 2000]. Results showed that for
babies born to mothers who were exposed to concentrations of the combined pollutants
above the 95
th
percentile of the exposure distribution (56.8 g/m
3
), the relative risk was
2.88 (95% Confidence Interval; CI 1.16-7.13). Another study carried out in the United
States has found similar result – the authors examined the association between PM
10

and birth weight in northern Nevada between 1991 and 1999, and found that a 10µg/m
3

increase in mean PM
10
concentrations during the third trimester of pregnancy was
associated with a reduction in birth weight of 11g (95% CI 2.3-19.8) [Chen et al 2002]. A
European study carried out in the Czech Republic examined the relationship between
low birth weight, premature birth, and ambient TSP during each trimester in 108,000
singleton live births [Bobak 2000]. The effects of these adverse birth outcomes were
marginally stronger for exposures during the first trimester. Adjusted odds ratios of low
birth rate and prematurity were 1.15 (95% CI 1.07-1.24) and 1.18 (95% CI 1.05-1.31) for
a 50µg/m
3
increase in TSP respectively. In contrast, Landgren who studied the effects of
air pollution on delivery of 38,000 Swedish women in 1985-1990 [Landgren 1996], and
Maisonet et al who studied the effects of PM
10
in live births born in six northeastern
cities of the United States [Maisonet et al 2001], both showed results with no indication
of a positive association between prenatal exposure to particulate air pollution and low
birth weight.

8.1 Conclusion

To date, only a limited amount of epidemiological evidence has been collected and the
results are equivocal.

9. Environmental lead exposure


9.1 Exposure to environmental lead.

Lead is distributed in the environment via industrial and vehicular emissions, house paint
and plumbing. As a result lead is present in air, dust, soil and water and the general
population are exposed primarily via ingestion and inhalation (Valent et al., 2004).

Some of these exposures involve large sectors of the population (e.g. industrial activity,
use of lead in vehicle fuel) whilst others are more locally (lead water pipes) or culturally
(lead in ceramic food containers) specific (Fewtrell et al. 2004). In the UK, policies
reducing exposure by leaded petrol and house paints has increased the relative impact
of other sources namely food and beverages (crops grown in soils of high lead content,
food in soldered tins) (Moore et al. 1979) and water (lead piping) (Watt et al. 1996). The
release of lead to air in the UK has considerably reduced following the ban on lead
additives in petrol in the 1990s. However, lead is still present in soil as a result of
The burden of disease attributable to environmental pollution
22
deposition (particles falling to the ground or washed out by rain) from previous vehicular
emissions, old leaded paint and landfill. (EPAQS, 1998).


9.2 Measurements of exposure

The bulk of the human data on exposure to environmental lead are expressed in terms
of internal exposure, in particular blood lead levels. Internationally, most biomonitoring
studies, have been episodic rather than part of routine surveillance and are most
commonly conducted on populations at risk due to their occupation or vicinity to a highly
contaminated site. (ATSDR, 1999).

However, blood lead levels in England were recorded in a sample of the population
between April-June and between September-December 1995. A multi-stage stratified
probability sampling design was used as part of the Health Survey for England to obtain

representative data. For subjects aged over 11 years, a geometric mean blood lead
level of 2.0 µg/dl was recorded. Blood lead levels were higher in males than females,
increased with age and were highest in adults having higher consumptions of cigarettes
and alcohol. No differences between urban and non-urban populations were identified.
(Institute for Environment and Health, 1998)

Despite differences in methodology between this and previous UK surveys, blood lead
levels appeared to have fallen since the 1984-1987 period (Delves et al. 1996) with a
long term downward trend of around 4% per year (DoE, 1988).

The Avon Longitudinal Study of Pregnancy and Childhood (ALSPAC) included a
measurement of blood lead levels in 584 two year old children in 1994 so that future
follow up could assess the impact of lead exposure on their IQ. Levels ranged from 0.8
to 27.6 µg/dl with a geometric mean of 3.44 µg/dl. Children of younger mothers, children
exposed to environmental tobacco smoke, children with pets in the home, children living
close to higher levels of traffic and children who were not breast fed had statistically
significantly higher blood lead levels. Furthermore, children living in inner city areas had
the highest levels whilst those living in outer areas had the lowest levels. (Golding et al.,
1996; Institute for Environment and Health, 1998).

9.3 Health effects

At high levels of exposure (blood lead level > 60µg/dl) acute effects are recorded
ranging from gastrointestinal problems, lethargy and irritability, encephalopathy and
death. Chronic low level toxicity can remain asymptomatic. However, in infants and
young children the developing brain is particularly vulnerable and blood lead levels as
low as 10 µg/dl or less can cause neurological deficits (Needleman and Gastonis, 1990;
Canfield et al. 2003).

Milder disease outcomes, in particular hypertension in adults and the loss of IQ points

and the resultant increase in mild mental retardation (MMR) in children are of increasing
concern at levels of exposure that were previously considered safe (ATSDR 1999).
The burden of disease attributable to environmental pollution
23


9.4 Burden of disease

The World Health Organisation has assessed the disease burden from lead exposure
for the year 2000 at global level, categorised by geographic region using the ‘exposure-
based approach’ (WHO/ILO, 1998). The disease burden has been calculated by
evaluating the population exposure distributions based on recorded blood lead levels in
combination with estimates of disease rates. (Fewtrell et al. 2004).

Geometric mean and standard deviation blood lead levels were obtained for individual
countries using population exposure data identified through a literature search.
Occupational exposures and studies of ‘hotspots’ were excluded. Countries were
grouped into 14 WHO regions (WHO, 2002). WHO European Region A includes the
UK. Separate levels were compiled for children and adults where data was available.

Two health outcomes were considered.



9.4.1 Loss of IQ points and increase in mild mental retardation (MMR).

This was based on a linear relationship between blood lead levels and loss of IQ points
established by a meta-analysis of cross sectional and longitudinal studies (Schwartz
1994). A loss of 1.3 IQ points per 5 µg/dL blood lead interval for blood lead levels
between 5 and 20 µg/dL was assumed. MMR was defined as having an IQ score of

between 50 and 69 and estimates were calculated using the ratio of those who already
had a low IQ score and for whom a loss of a few points would result in them being
categorised as having MMR.

Using studies from 6 European Region A countries (which did not include any studies
from the UK) the mean blood level for urban children was 3.5 µg/dl and the mean blood
level for urban adults was 3.7 µg/dl. It was calculated that for Region A, 227 people per
1000 population had a loss of 0.65 IQ points as a result of lead exposure. Higher IQ
losses affected smaller proportions of the population i.e 41/1000 population had losses
of 1.95 IQ points, 10/1000 population had losses of 3.25 IQ points and 5/1000
population had losses of 3.5 IQ points.

It was estimated that 1.1 persons per 1000 population were affected by MMR and that
55,000 DALYS were lost as result of lead exposure.

Using a similar calculation, the burden of disease in children expressed as the presence
of MMR in the age group 0-4 years, attributable to lead exposure was calculated.
(Valent et al. 2004). Using studies from 11 European Region A countries including one
from the UK (O’Donohoe et al. 1998), the best estimate blood lead level in children aged
0-4 years was 2.9 µg/dl. It was calculated that, 93 children per 1000 population had a
loss of 0.65 IQ points as a result of lead exposure. Higher IQ losses affected smaller
The burden of disease attributable to environmental pollution
24
proportions of the child population i.e 1/1000 population had losses of 1.95 IQ points,
none had losses of 3.25 IQ points or above. It was estimated that 0.5 children per 1000
population were affected by MMR and that 14,000 DALYS were lost as result of lead
exposure. (Valent et al. 2004).

9.4.2 Cardiovascular disease

Firstly, a linear relationship between blood lead levels and increases in systolic blood
pressure was established from literature sources. For men, a 1.25-mm Hg increase was
associated with each 5 µg/dL increase between 5 and 20 µg/dL and an increase of 3.75
mm Hg was assumed above 20 µg/dL. For women, a 0.8-mm Hg increase was
associated with each 5 µg/dL increase between 5 and 20 µg/dL and an increase of 2.4
mm Hg was assumed above 20 µg/dL. In order to calculate the proportion of
cardiovascular disease attributable to lead, the distribution of blood lead levels causing
increased blood pressure was combined with the relative risk for each blood pressure
level, again derived from the literature.

For European region A, the following disease burden was attributed to lead exposure:
ischaemic heart disease (30,000 DALYs), cerebrovascular disease (25,000 DALYS),
hypertensive disease (3,000 DALYS) and other cardiac diseases (4,000 DALYS). In
total 63,000 DALYS and 5,000 deaths due to cardiovascular disease were attributable
to lead exposure.

9.5 Conclusion

As a result of lead exposure, 93 children per 1000 population had a loss of 0.65 IQ
points, 1 in 1000 had losses of 1.95 IQ points and 0.5 children per 1000 were affected
by MMR
.

10 Respiratory Disease

10.1 Evidence of environmental aetiology
There are a large number of epidemiological studies which have investigated hospital
admissions and mortality from respiratory disease subsequent to excursions in ambient
outdoor air pollution. These have been reviewed by the Committee on the Medical
Effects or Air Pollution (COMEAP) of the Department of Health who have published risk

estimates (see section 10.3).