PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Valuing impacts of noise on health –exposure response
relationships in current UK guidance and the WHO Environmental
Noise Guidelines 2018
Benjamin FENECH1; Georgia RODGERS1
1

Public Health England, UK

ABSTRACT
Following the publication of the Environmental Noise Guidelines for the European Region (ENG), a lot of
debate has focused on the Guideline Recommendations, in particular the specific guideline levels and thestrength of the recommendations. A sizeable proportion of the UK population is currently exposed to noiselevels above the WHO recommendations, and it is important that policy and decision makers have access toan accurate quantification of the associated burden of disease. From this perspective, the systematic reviewsof the scientific evidence, and the recommended exposure response functions are an equally important aspectof the ENG.
In the UK the current recommended methodology for valuing health impacts associated with environmental
noise is outlined in two documents published by the Department for Environment Food and Rural Affairs andthe Interdepartmental Group on Costs and Benefits Noise Subject Group. This paper will look into the studies
that informed the exposure response functions recommended by these two documents. A comparison is thenmade with the more recent studies that informed the ENG, followed by discussions of which aspects could
have led to differences in the exposure response functions.
Keywords: Noise, Health, WHO

1. INTRODUCTION
The publication of the World Health Organization (WHO) Environmental Noise Guidelines for theEuropean Region (ENG) in 2018 (1) stimulated a fair amount of debate amongst the UK acoustic
profession, particularly on the specific guideline levels and the strength of the recommendations.
Strategic noise mapping carried out by the Department for Environment Food and Rural Affairs(Defra) (2) shows that a sizeable proportion of the UK population is currently exposed to noise levels
above the WHO recommendations. It is important that policy and decision makers have access to an
accurate quantification of the associated burden of disease. From this perspective, the recommended
exposure response relationships derived from the systematic reviews commissioned by the WHO arean equally important aspect of the ENG. These systematic reviews focused predominantly on scientificevidence published since 2000.
In the UK the current recommended methodology for valuing health impacts associated withenvironmental noise is outlined in two documents published by Defra and the Interdepartmental Groupon Costs and Benefits Noise Subject Group (IGCBN) in 2010 and 2014 (3,4). The relevant healthoutcomes are annoyance, sleep disturbance, hypertension and acute myocardial infarction.
This paper presents a brief overview of the evidence that informed the exposure response functions(ERF) in the current UK guidance and the ENG. Aspects of the studies that could influence theirapplicability to a local population are discussed. For example, annoyance and self-reported sleep
disturbance depend to some extent on a cognitive appraisal of the stressor (in this case noise), and the
ERFs are only partially explained by the noise exposure (5). The ENG notes that (1):“This is especially true for noise annoyance, for which there is often considerable heterogeneity ineffect sizes of studies because estimates vary between noise sources and are to some degree dependent
on the situation and context. Furthermore, cultural differences around what is considered annoying
are significant, even within Europe.”
1

CRCE-Noise@phe.gov.uk

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Other aspects discussed are study design and situational factors. Many of the studies that inform thecurrent UK guidance are now 20-50 years old, and their relevance to current and future infrastructure
schemes may be questioned. Furthermore the heterogeneity in effect sizes of noise annoyance andsleep disturbance studies suggests that using a single averaged ERF may not be the best approach whencarrying out scheme-specific noise impact assessments.

2. A BRIEF OVERVIEW OF THE UK’S METHODOLOGY FOR VALUING NOISE
IMPACTSIn the UK, a requirement to quantify the impacts of transportation noise has been in place since theearly 2000s (6). For example, an update to WebTAG (the Department for Transport’s Transport
Appraisal Guidance) Unit 3.3.2 in 2004 required the appraisal of noise impacts to include aquantitative assessment of noise annoyance. A monetary valuation of noise impacts was introduced in
2006, based on a hedonic pricing study carried out in Birmingham, UK (7). The resulting values weretransferred to UK average levels by Nellthorp et al. (8), and this approach was recommended for thevaluation of amenity impacts for residential receptors.
Meanwhile better quality scientific evidence on the effects of noise on sleep and the cardiovascularsystem was becoming available (9,10). Individuals exposed to noise may not be fully aware of these
health effects, and hence such impacts would not be reflected in property values. In recognition ofthese shortcomings, an Interdepartmental Group on Costs and Benefits, Noise Subject Group (IGCBN)
was convened by Defra. In their first report (11) the group recommended the application of an impact
pathway approach for quantifying noise impacts. The group commissioned Berry and Flindell toreview the state of the art evidence on noise impacts (12). Based on their findings, the IGCBN madeseveral recommendations in 2010 (4), including: to include the risk of acute myocardial infarction (AMI) into the monetary valuation;
 to continue using monetary values for annoyance based on a hedonic pricing approach; and to use indicative quantification of hypertension and sleep disturbance impacts.
Following the IGCBN’s 2010 report two major reports on noise and health were published by the
WHO – the Night Noise Guidelines in 2009 (13) and the Burden of Disease (BoD) from Environmental
Noise in 2011 (14). The latter provided a methodology (15) to quantify the burden of disease
attributable to noise in terms of Disability Adjusted Life Years (DALYs) (16). As a result, Defra
published the current appraisal methodology in 2014 (3), recommending: using a DALYs approach to quantify and monetise annoyance and sleep disturbance
impacts;
 using a two-step approach to monetise hypertension-related impacts; and using the methodology for valuing AMI outlined in the 2010 IGCBN report.

3. SLEEP DISTURBANCE
The current UK guidance recommends that sleep disturbance impacts are monetised where it is
proportionate to do so, in addition to presenting the number of people sleep disturbed (3). Sleep
disturbance is defined as “being aware that sleep has been disturbed and attributing the disturbance tothe effects of transport noise” (ibid.). The guidance acknowledges that this approach does not capture
any consequential impacts of sleep disturbance on productivity or physiological chronic healthimpacts (some of which may be captured by the appraisal of AMI and hypertension effects).
The equation for valuing sleep disturbance is:Value of sleep disturbance = S x B x C, whereS – number of people highly sleep disturbed
B – Disability Weight (DW) of the health outcome
C – Monetary value of one DALY
The recommended DW follows the recommendation in the WHO BoD methodology (14), i.e. 0.07
with an uncertainty range between 0.04-0.10. The monetary value of one DALY was set at £60,000 in
the IGCBN 2010 report (4) in accordance with the central estimate value of a QALY applied acrosscentral government departments in England.
The definition of “highly sleep disturbed” (HSD) used in the evidence underpinning the current UK
guidance is the percentage of responses about sleep disturbance that exceed a cutoff of 72 on a scale of
0 to 100 (19). The UK guidance provides three recommended exposure response functions (ERFs)

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describing the percentage of people HSD (%HSD) from road, air or railway noise exposure, as afunction of the average outdoor nighttime level (L night ). The equations are equivalent to thosepresented in the WHO BoD (2011) report. These equations are polynomial approximations derived
from meta-analysis carried out by Miedema et al. (17,18), based on data from 28 original datasets from
24 field studies, including six from the UK (1967 – 1986). To be included, studies had to (19): quantify self-reported sleep disturbance to individual transportation noise sources;
 quantify noise exposure of respondents with sufficient accuracy such that average noise
exposure level during the nighttime period could be derived;
 not have been conducted after major changes to the noise situation.
Participants with exposure levels <45dB L night were excluded from the analyses because their
exposure data was deemed to be rather inaccurate, and exposures to other sources may have been more
important. Participants with exposure levels >65dB Lnight were excluded because the risk of
self-selection of people not bothered by noise was deemed to be relatively high at such exposures (19).
Nevertheless the WHO BoD suggests that the synthesized curves can be used within 40 – 70 dB L night .
Miedema et al. noted large variation in the wordings and scales used to measure sleep disturbanceacross studies. Many studies included more than one question regarding sleep disturbance; thesequestions could be broadly grouped into three categories: difficulty falling asleep due to noise; waking up or being disturbed by noise during the night; and waking up early in the morning due to noise.
For the pooled analysis Miedema & Vos used the “most general questions that did not refer to either
the beginning or the end of the night (i.e. the second category)” because the L night metric “pertains to
the whole night” (19).
The error variance in the resulting exposure response model was similar for road and rail, but amuch larger variance for aircraft noise was found. The authors suggest that the following factors may
have contributed to this larger variance (17,18):
 Larger differences in the time pattern of noise exposures around different airports, becauseof different regulations such as nighttime curfews;
 The sleep disturbance question wording for aircraft noise appears to be even more variable;
 A potential time trend towards higher self-reported sleep disturbance at the same L night . For
example the most recent study included in the analyses had the highest self-reported sleep
disturbance, and a more recent aircraft noise study from the Netherlands was excluded
from the analyses, because its results were so high that it was considered to be an outlier.
The authors also suggested that uncertainties regarding the nighttime noise exposure, fear of
aircraft accidents and expectations regarding future airport developments may have contributed to theindividual variance within the aviation noise studies (18).
Miedema et al. therefore concluded that the curves presented for aviation were only indicative of
the self-reported sleep disturbance, and that “recent trends lead to higher self-reported sleep
disturbance than indicated by these curves.” (18) These uncertainties were also echoed in the WHO
BoD (2011) report, which added that using the curves for aviation may result in “a possible
underestimation of the response at a given aircraft noise exposure level ” (14).
3.1 SLEEP DISTURBANCE EVIDENCE UNDERPINNING THE WHO ENG 2018
The WHO-commissioned systematic review on environmental noise and sleep (20) considered both
physiological outcomes (polysomnography-measured cortical awakenings) and self-reported sleep
outcomes. Only self-reported outcomes are considered here. The review focused on the “three mostcommon outcomes” of noise-induced sleep disturbance, i.e.
 Recalled awakenings from sleep during the period from sleep onset to final awakening; The process of falling asleep (the transition from wakefulness into sleep); and Sleep disturbance (internal/external interference with sleep onset or sleep continuity).
Most of the studies that satisfied the inclusion criteria used the ICBEN 5 -point verbal or 11-point
non-verbal scale (21). “Highly sleep disturbed” (HSD) was defined as responses in the top two (5pt)
and top three (11pt) categories. For the few questions that referred to the frequency of symptoms,
symptoms occurring three times or more per week were considered as an indication of high sleep
disturbance. The analysis was based on L night levels between 40 and 65dB. No studies from the UK
satisfied the systematic review inclusion criteria.

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3.2 COMPARISON BETWEEN ERFs IN UK GUIDANCE AND THE WHO ENG
The sleep disturbance systematic review presents a comparison between the exposure-response
functions (ERFs) derived from the more recent studies and the ERFs derived by Miedema & Vos(which feature in the current UK guidance). The Miedema & Vos ERF for road falls within theconfidence intervals of the new WHO ENG curve. For rail, the ENG ERF suggests a higher %HSD at
Lnight >48dB. For aviation, the ENG ERF suggests a higher %HSD throughout the entire noise
exposure range (40-65dB). Basner & McGuire provide the following potential reasons for theobserved increase in the %HSD by aircraft and railway noise (20): different methodologies used to derive the model;
 year of study – (≥ 2000 in the WHO systematic review; <2004 in the Miedema & Vos’s
analysis, with many of the studies dating back to the 1970’s and 80’s);
 location of studies – many of the studies in the WHO systematic review are from east Asia,
compared to a dominance of European studies in the analysis by Miedema & Vos; question wording – older studies tended to refer to annoyance due to sleep disturbance ingeneral, whereas more recent studies include questions on the severity/frequency of sleep
disturbance, awakenings and difficulty falling asleep; more night-time events reported in more recent railway noise studies.
Basner & McGuire also note that one included study occurred after the opening of a new terminalbuilding, where the Lnight increased by 2dB at nine of the 11 sites investigated. There was a
non-statistically significant difference in the odds ratio of being HSD when compared to the resultsfrom the study conducted before the new terminal was opened.

4. ANNOYANCE
The current UK guidance recommends the use of DALYs to quantify the value of community
annoyance from environmental noise (3). The equation to value annoyance is:Value of annoyance = A x B x C, whereA – number of people highly annoyed
B – Disability Weight (DW) of the health outcome
C – Monetary value of one DALYThe DW follows the recommendations in the WHO BoD (2011) methodology, i.e. 0.02 with anuncertainty range between 0.01-0.12. The definition of “highly annoyed” (HA) is the percentage of
responses about annoyance that exceed a cutoff of 72 on a scale of 0 to 100 (22). The UK guidance
provides three exposure response functions (ERFs) describing the %HA from road, air or railway noise
exposure, as a function of day-evening-night level (L den ). These equations are polynomial
approximations derived from a meta-analysis carried out by Miedema & Oudshoorn for a Position
Paper for the European Commission (23), based on data from 54 field studies, including nine from theUK (1967 – 1984). The study inclusion criteria reported were (24): noise exposure and annoyance pertain to only one source of transportation noise; %HA is directly derived from responses to a question about the general noise annoyancefrom the source concerned (i.e. it is not based on, for example, an index constructed frommultiple questions concerning specific disturbances or a ranking of sources by
respondents); and %HA is derived with a cutoff point sufficiently close to 72 on a scale from 0 (no annoyanceat all) to 100 (very high annoyance).
The references do not clarify whether any of the studies included in the meta-analysis took place
during a change in noise exposure. As for sleep disturbance, upper and lower exposure cutoffs of 65dB
and 45dB L den , respectively, were used.
In recent years a number of studies, including the cross-European HYENA study (25), and asubsequent meta-analysis of aviation studies by Janssen et al. (26) – have shown an increase inannoyance over the years for aviation noise. This was acknowledged in the WHO BoD (2011)
guidance (14):“there are strong indications that the exposure–response relationships for aircraft noise havechanged, so that the curves presented here probably underestimate the annoyance at a given aircraft
noise exposure level.”
One group of researchers supporting the use of the Community Tolerance Level (CTL)
methodology disagree, arguing that they did not observe a significant temporal trend in CTL values in7140

an analysis of studies carried out over the past 50 years (27). Instead they attribute changes in the ERF
for aircraft noise to a larger number of studies carried out during or after changes to airport
infrastructure in recent years. As the CTL-approach assumes that the shape of the %HA curve follows
the duration-corrected loudness estimated from L dn , it is not clear whether this method is able toidentify small differences in the slope of ERFs of recent vs earlier studies arising from a temporal trend
in annoyance (28).
4.1 ANNOYANCE EVIDENCE UNDERPINNING THE WHO ENG 2018
The WHO-commissioned systematic review on environmental noise and annoyance looked atstudies published between 2000 and 2014 (29). The inclusion criteria were: cross-sectional or longitudinal surveys with an explicit protocol for selecting participants;
 study participants that are members of the general population (residential noise exposure); studies reporting long-term outside noise levels expressed as L Aeq,24h , Ldn, Lden (or can beeasily converted from similar acoustic variable) noise levels determined from reliable calculation procedures or based on measurements fora minimum of one week; individual annoyance response (outcome measure) measured by a survey question andresponse format that followed (or very close to) the recommendations in ICBEN (21)and/or ISO TS 156666;
 paper or author provided at least one original table, formula or graph representing an
exposure response relationship; and study published in English, French, Dutch or German language.
In total 57 studies were included in the meta-analysis. Only one study from the UK satisfied theinclusion criteria (HYENA, 2003). The fifth criterion led to a much more consistent wording of theannoyance question across studies when compared to the studies analysed by Miedema & Oudshoorn(22). The exposure range varied by source, but results are typically presented between 40 – 80dB L den.
4.2 COMPARISON BETWEEN ERFs IN UK GUIDANCE AND THE WHO ENG
For road traffic noise, Guski et al. presented two ERFs: one curve derived from all 25 studies, andone curve from a subset of 10 studies excluding Alpine and Asian studies. The justification for thelatter is that Alpine studies are characterized by a rather unique topography, and the housing stock in
Asia is predominantly air conditioned; therefore one can argue whether these studies are generalisable.
The curve derived from the full set of studies shows higher %HA at lower exposure levels (40-60dB
Lden ) when compared to the curve by Miedema & Oudshoorn. The curve excluding the Alpine andAsian studies is similar to the Miedema & Oudshoorn curve up to 70 dB L den, and higher above thislevel.
The ERF for rail traffic presented in the WHO systematic review shows a steeper increase in %HA
with increasing L den when compared to the corresponding curve by Miedema & Oudshoorn.
For aviation noise, the ERF in the WHO systematic review shows considerably higher %HA thanthe curve by Miedema & Oudshoorn. The ERF in the systematic review is based on 12 surveys, six ofwhich are from the HYENA study (29).
Guski et al. identify a number of potential reasons that could have led to differences in the ERFs
when compared to the older curves derived by Miedema and Oudshoorn, including (29):• Several studies took place in the context of an abrupt change to the relevant infrastructure
and/or number of vehicular movements and/or public debate about the associated noise .
• The six HYENA-studies (air and road) only included residents aged 45–70. There isconflicting evidence on the relation between age and annoyance (30,31), however theauthors suggest that this may have introduced a certain bias towards higher annoyance.
• The road traffic data set includes five studies from Alpine valleys in Austria. The rail traffic
data set includes three studies in the same setting. The propagation of sound in valleys isdifferent from flat areas. Three of the five Alpine road studies used 60% o f the annoyancescale as a criterion for being highly annoyed, as opposed to the 72% cutoff used byMiedema and Oudshoorn. Some of the Alpine research sites were subject to long-lasting
discussions about heavy transalpine road and rail traffic, and a large increase of freighttraffic was reported on these routes.
• The full road traffic data set includes ten studies from Asia, where many participants live in
air-conditioned homes. This may have contributed to a lower degree of annoyance .

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• The rail traffic data set includes one study where trains generated both noise andperceptible vibration.
The systematic review includes comprehensive sub-analyses and/or discussions on how thesefactors may have influenced the results.
In a subsequent analysis (32) of annoyance from aviation noise by the same authors, the resultsfrom seven additional studies published after 2014 were added. No significant changes to the averaged
annoyance response function derived in the ENG systematic review were observed. This analysis
included the results from the Survey of (Aviation) Noise Attitudes (SONA) 2014 study from the UK(33).

5. CARDIOVASCULAR OUTCOMES
The current UK guidance recommends the valuation of Acute Myocardial Infarction (AMI) and two
hypertension-related outcomes: stroke and dementia. The AMI valuation methodology, outlined in the
IGCBN 2010 report (4), mirrors the methodology proposed in the WHO BoD (2011) (14). The
exposure response function used to estimate the incidence of AMI as a function of daytime noise isfrom a meta-analysis (34) of studies carried out in Caerphilly and Speedwell, UK and in Berlin,
Germany. These studies investigated the association between the road traffic noise level during the day
and the incidence of AMI. The study subjects were all men. The common set of covariates consideredin all the studies were age, sex (males only), social class, school education, employment status, shift
work, smoking and body mass index. Some of the studies also considered physical activity during
leisure time, family history of ischaemic heart disease or myocardial infarction, prevalence ofpre-existing diseases, noise exposure at work and marital status. In one study, the effect estimates were
further adjusted for hypertension and diabetes mellitus. Although the meta-analysis only included
studies on road traffic noise, the UK guidance recommends that the ERF is used for road, rail andaircraft noise sources.
For noise-related hypertension, the current UK guidance recommends that the consequential impact
on dementia and stroke is quantified and valued. The methodology is based on a study by the Healthand Safety Laboratory (35). The attributable cases of hypertension are calculated using the following
odds ratios within the noise exposure range 50-75dB L den : Road: 1.07 per 10dB increase in L den (from van Kempen & Babisch 2012 (36))
 Aircraft: 1.13 per 10dB increase in L den (from Babisch & van Kamp 2009 (37))
 Rail: 1.07 per 10dB increase in L den.
5.1 CARDIOVASCULAR EVIDENCE UNDERPINNING THE WHO ENG 2018
The WHO-commissioned systematic review on environmental noise and cardiovascular effects
looked at studies published between 2000 and 2015 (38). The review evaluated 22 studies thatinvestigated the association between exposure to noise from air, road, and rail traffic and ischaemic
heart disease (IHD). The association between aircraft noise and the incidence of IHD was statisticallysignificant, and a risk ratio (RR) of 1.09 per 10 dB was estimated after aggregating the results of two
ecological studies. An increase in road traffic noise was associated with statistically-significant
increases in the prevalence and incidence of IHD. A RR of 1.08 per 10 dB (L den ) was estimated for the
association between road traffic noise and the incidence of IHD, after combining the results of threecohort studies and four case-control studies. The data suggested that the risk of IHD increases
continuously for road traffic noise levels from about 50 dB Lden . There were no studies to allow an
estimate for the risk of incidence of IHD from railway noise.
The authors evaluated 37 studies that investigated the impact of transportation noise on the risk ofhypertension. The strongest associations were observed in cross-sectional studies, which formed thelargest part of the available evidence. Only the association between road traffic noise and theprevalence of hypertension was statistically significant: after aggregating the results of 26 studies, a
RR of 1.05 per 10 dB L den was derived. No increased risk of hypertension due to transportation noise
was observed in the two cohort studies investigating the association between transportation noise andthe incidence of hypertension. The reason for the apparent discrepancy in the findings between the
cross-sectional studies and the cohort studies was unclear.

6. FINAL REMARKSThis paper provides a brief overview of the evidence that informed the current UK guidance on

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valuing noise impacts, published in 2010 and 2014. A comparison is made with the systematic reviews
that underpin the latest WHO Environmental Noise Guidelines for the European Region.
For annoyance and sleep disturbance, the WHO-commissioned systematic reviews looked atstudies published between 2000-2014/5, whereas the current UK guidance is based largely on studies
published before 2000. The studies included in the WHO systematic reviews tended to measure therelevant health outcomes in a more consistent way – both in terms of the question wording and thescale. However, a large heterogeneity in effect size continues to be observed across studies. The WHO
systematic reviews identified only one study (annoyance) that took place in the UK since 2000 (roadand aviation). A more recent study (SONA 2014) was not included because it was published in 2017.
Given the uncertainties associated with transferability of exposure response functions there is a clear
need for new research on noise annoyance and sleep disturbance effects in the UK population.
The WHO systematic reviews suggest that some of the exposure response relationships forannoyance and sleep disturbance have changed when compared with those in the current UK guidance.
This is particularly the case for aviation and railway noise, and potential reaso ns for the observedchanges have been proposed. This conclusion has sparked some debate, despite similar conclu sions
being drawn for aviation noise in the past (14,25,26). There seems to be a consensus that annoyancearound airports undergoing significant change is higher (27,28,29). The disagreement appears to bewhether there has been a temporal shift in annoyance, irrespective of change. There are many reasonsthat may lead to people’s perceptions and appraisal of the noise environment to change, for example:• changes in the temporal and frequency characteristics of the noise source (e.g. quieter vehicles,
but more of them; more/less low and high frequency content);• changes in the distribution of the noise throughout the day and week (e.g. 24hr economies), andchanges to the periods of relative quiet in between vehicle passbys;• changes in housing stock (where houses are built, housing density and housing construction);• changes in societal values (including a growing awareness of the influence of the environmenton health, people’s perceptions of the environmental credentials of specific modes of transport,
people’s dependence on a specific mode of transport);• changes in the need for quiet when at home; and• changes in people’s activities when at home (e.g. shift work (sleeping during the day), working
from home, etc).
For the cardiovascular health outcomes, the evidence on road traffic noise and ischæmic heartdiseases (IHD) has strengthened considerably since the UK valuation methodology was publi shed in2010. Despite recent improvements, IHD is still the top cause of death and disability in the UK (39),and the certainty of the effect estimate is very important for national burden of disease calculations.
Equally relevant is the emerging evidence of associations between environmental noise and stroke anddiabetes – ranked as the 5 th and 9th top causes of death and disability in the UK, respectively (39).

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