Environmental noise is a significant risk factor for a range of short- and long-term adverse health outcomes such as annoyance, cognitive development impairment, sleep disturbance, cardiovascular effects, and psychiatric problems. The aim of this study was to gather standardized quality of life (QOL) data hitherto rarely correlated with noise annoyance by source category. To provide an evidence-base for environmental noise policy development, a representative state-based survey was undertaken in South Australia (SA). A total of 3015 face-to-face interviews were conducted, using a questionnaire addressing noise sources, distances to busy roads and standardized measures of perceived annoyance and QOL. Population weighted descriptive survey and regression analysis. The most common sources of noise annoyances were road transport (27.7%, using a Likert scale, aggregating "little" to "extreme" annoyance), neighbors (22.0%), construction noise (10.0%), air conditioner noise (5.8%), rail transport noise (4.7%), and industry (3.9%). Using the QOL instrument, all eight health dimensions were significantly decreased for those reporting high noise annoyance ("very much" to "extreme") in relation to road transport and neighbors compared to those reporting low annoyance ("none" to "moderate") from these sources. Noise annoyance is common in the SA general population, and the evidence for a strong association with QOL reinforces the need for environmental noise management at a population basis.
Keywords: Annoyance, environmental noise, quality of life, survey
|How to cite this article:|
Nitschke M, Tucker G, Simon DL, Hansen AL, Pisaniello DL. The link between noise perception and quality of life in South Australia. Noise Health 2014;16:137-42
| Introduction|| |
In 1999, the World Health Organization (WHO) concluded that environmental noise from various community sources poses a significant risk to health.  Noise guideline levels were introduced with the aim to prevent adverse health impacts on everyday life and health in the form of sleep disturbance, not being able to understand speech, delays in cognitive development in children and annoyance. Over time, more severe stress-related health endpoints were associated with noise exposure including hypertension and coronary artery disease.  Recently, meta-analyses of exposure response relationships from available studies confirmed the impact of noise on cardiovascular disease, and the WHO progressed noise prevention and management by quantifying population health outcomes in the form of healthy life years lost. 
Based on the concept that health is a state of complete physical, mental and social well-being, annoyance has been added to the relevant health endpoints considering that being annoyed can affect general well-being and more specifically, quality of life (QOL). , Noise annoyance has been widely studied at the community level and is considered a valid and straightforward first-line indicator for "unwanted noise". Annoyance links the concept of noise as an environmental stressor to health endpoints such as high blood pressure, impacts on hormone levels, and cardiovascular effects , On the other side of the noise stress model, annoyance is depicted as a mediator moderated by factors including personal characteristics such as noise sensitivity, measured auditory levels, and source-specific factors. , Information about annoyance at the population level enables comparison of concerns over time, in relation to different noise sources, and it can be used as a basis for management of noise. 
Adelaide is the capital of the state of South Australia (SA) and like other major Australian cities, is subject to densification alongside urban transport corridors. Consequently, exposure to environmental noise needs to be addressed at the planning stage. In understanding the noise issue, complaint registers kept by regulators may indicate potential concerns, but are not representative information sources.
One of the aims of this study was to quantify annoyance of the SA community to relevant noise sources using an internationally standardized noise annoyance survey tool that enables valid comparison to other cities and countries.  QOL assessment in the form of a survey of 36 health questions (short-form health survey with the trademark name of SF-36v2™) and covering eight health dimensions has been widely used to compare health profiles of sub populations with the population in general.  The QOL questions were included into a randomized population survey with the aim to explore the relationship between noise annoyance and QOL in SA.
| Methods|| |
The survey questions were included in the "Health Omnibus" Survey, which is conducted yearly and has been implemented to collect health data representative of the demographic profile of SA. , The methodology and completed questionnaire received ethical approval from the SA Health Omnibus Advisory Committee. In this survey, data are weighted according to the probability of selection, by sex, age group, and geographic area using the latest Australian Bureau of Statistics (ABS) estimated resident population figures. For the survey, 363 of the ABS collection districts were selected from the Adelaide metropolitan area and 107 from rural SA with their probability of selection proportional to their size. The person whose birthday was next in the selected households was interviewed face-to-face.
Questions about perceived annoyance to noise were based on a standardized survey tool constructed for the purpose of conducting community noise surveys. , The questions addressed seven noise sources, which were identified as significant to SA based on information from the complaints register of the SA Environment Protection Authority:
When you are here at home, how much does noise from (road, rail transport, factories or industrial premises, from neighbors, from building and construction, from domestic air conditioners) bother, annoy or disturb you? Responses were categorized into "not at all, a little, moderately, very much, and extremely".
The survey also asked participants about the approximate distance between their home and a major road (>10,000 cars/24 h).
The questions are designed to evaluate the self-perceived QOL status of populations and have been adopted and tested for validity and reliability worldwide, including in Australia. , In this study, the Australian adaptation of the SF-36 version two was used.  Eight health outcomes were measured: Physical functioning; role-physical (interference with work or other daily activities due to physical health); bodily pain; general health vitality; social functioning (interference with normal social activities); role-emotional (interference with work or other daily activities due to emotional problems); and mental health (symptoms associated with anxiety and depression and measures of positive affect). 
Responses to the SF-36 questions were transformed to the eight health dimensions using scores between 0 and 100, with higher scores indicating better health. The scores were weighted using the mean scores and standard deviations from the results of the survey. To enable comparison between subpopulations, the resulting z-scores were transformed to t-scores, such that the mean scores for the overall study population was 50 with a standard deviation of 10.  Statistical analysis was undertaken using Stata (version 12) and Stata survey commands were used to account for sampling weights, clustering and design. 
To assess the effect of noise annoyance on QOL scores, the ordered noise annoyance response was categorized into "low annoyance" (not at all-moderately) and "highly annoyed" (very much-extremely). The mean scores for all QOL dimensions were graphically compared by annoyance perception. Survey-specific regression analysis was used to test the difference of annoyance in relation to QOL scores, adjusted by socioeconomic score, age groups, distance to major road and gender. Logistic regression was used to estimate the risk of being highly annoyed for people living closer than 50 m to a major road, compared to those living further away. To adjust for confounding, variables for age, gender and socioeconomic index for area were used. 
| Results|| |
In total, there were 3015 interviews obtained from 4573 randomly selected households in SA. [Table 1] provides demographic information on the sample population.
[Table 2] indicates the responses from the surveyed South Australian locations regarding noise perception relating to the six relevant noise sources. The table includes estimated number of people in each noise and perception category based on census data of the SA population from 2001.
|Table 2: Percentage frequency (n = 3015) for noise perception in the general South Australian population, aged 15 and over and estimated number of people in South Australia by category of noise perception based on ABS data (census 2001) for the total population numbers (n) (total=1,467,261)|
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Noise from road transport was reported as a source of annoyance (little to extreme) by the highest proportion of respondents (27.7%), followed by noise from neighbors with 22.0%, construction noise with 10.0%, air conditioner noise with 5.8%, rail transport noise with 4.7%, and industrial noise with 3.9%.
In relation to the two highest scoring noise sources, the percentage of people being highly annoyed was established and the figures extrapolated to the whole of the SA population. Estimations showed 48,419 people (3.2%) are highly annoyed by road transport noise and 41,083 (2.8%) people are highly annoyed by neighborhood noise. There was no gender difference in relation to high annoyance from road transport, but a higher percentage of females (3.6%) were highly annoyed about neighborhood noise compared with males (2.0%), but this was statistically not significant.
An estimated 101,241 people (6.9%) in SA are highly annoyed by noise from one or more of the six noise sources. Females were more often highly annoyed than males (7.9% vs. 5.9%), but this difference was not statistically significant. There was no association between being highly annoyed by noise and age group.
The survey indicated that 25.1% of people live at a distance of <50 m from a major road in SA. When comparing metro and country areas, a higher percentage live near a major road (30.1%) in the country compared to the metro area (23.1%). More people (7.3%) were highly annoyed by traffic noise when living <50 m from a major road compared to further than 50 m (1.9%). The odds of being highly annoyed by transport noise is more than 4 times greater for those living within 50 m from a major road compared with living more than 50 m away (odds ratio: 4.2 confidence interval: 2.7-6.5; P < 0.001), adjusted for gender, age group and socioeconomic indicator.
Quality of life
[Figure 1], [Figure 2] and [Figure 3] illustrate mean SF-36 scores by annoyance status none-moderate (low annoyance) compared to very much-extreme (high annoyance). When comparing the two main noise sources, road transport and neighbors [Figure 1] and [Figure 2] and including confounders in the regression analysis, the highly annoyed responders had lower (P < 0.001) SF-36 scores indicating a poorer self-assessed QOL than the population who experienced low noise annoyance [Table 3]. [Figure 3] depicts the association between annoyance perception of any noise source (one or more of the six noise sources) and QOL scores indicating lower QOL scores for the highly noise annoyed population across all SF-36 dimensions (P < 0.001). Female SF-36 scores were consistently lower than male scores across both categories of annoyance, but this was not statistically significant.
|Figure 1: Comparison of mean social functioning-36 scores by annoyance status to road transport noise for the South Australian population aged 15 years and over for the eight health dimensions: PF = physical functioning, RP = Role physical, BP = Bodily pain, GH = General health, VT = Vitality, SF = Social functioning, RE = Role emotional and MH = Mental health|
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|Figure 2: Comparison of mean social functioning-36 scores by annoyance status to noise from neighbors for the South Australian population aged 15 years and over for the eight health dimensions: PF = physical functioning, RP = Role physical, BP = Bodily pain, GH = General health, VT = Vitality, SF = Social functioning, R ole emotional and MH = Mental health|
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|Figure 3: Comparison of mean social functioning-36 scores by annoyance status to noise from one or more noise sources for the South Australian population aged 15 years and over for the eight health dimensions: PF = physical functioning, RP = Role physical, BP = Bodily pain, GH = General health, VT = Vitality, SF = Social functioning, RE = Role emotional and MH = Mental health|
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|Table 3: SF36-adjusted regression coeffi cients, 95% CI and P value: Comparison between high and low noise annoyance in the South Australia population|
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| Discussion|| |
This is the first study in Australia to formally assess and rate environmental noise sources on the basis of annoyance, and links annoyance and health-related QOL scores at a state-basis to major environmental noise sources.
Noise sources and annoyance
Compared with noise surveys conducted in Europe and Australia, it appears that SA's environmental noise problem is relatively small. A nationwide representative survey in the UK showed that traffic noise was perceived to be annoying (a little - extremely) by 42% of the population (compared to 27.7% in our study), neighborhood noise by 38% (22%), building and construction noise by 15% (10%), and noise from factories by 5% (3.9%), respectively.  The score for high annoyance to road traffic noise was 3.2% in SA compared to 8% in the UK and 7.8% in Victoria, a more densely populated state in Australia.  Noise from neighbors was perceived to be highly annoying by 2.8% in SA, compared to 9% in the UK and 7.8% in Victoria. In both Australian states, traffic and neighborhood noise ranked on the top of the unwanted environmental noise ladder. In spite of a lower prevalence of noise annoyance it is important to note that, when the findings of the survey are extrapolated to the overall South Australian population, more than 100,000 people are potentially feeling highly annoyed about one or more noise sources.
The current survey was restricted to canvass community perception to noise rather than assess objective noise levels; therefore, it remains unknown whether in SA annoyance is associated with increasing objective noise measurements as has been documented in other studies. , In this survey, decreasing distance to a major road was associated with an increase in severe noise annoyance, suggesting a relationship between distance to major roads and road transport noise. The survey showed that 25.1% (366,815) of people live within 50 m of a major road in SA. Published exposure-response curves specify that 10% of exposed people are expected to be highly annoyed at 60 dB(A), and 16% at 65 dB(A), respectively.  Application of these exposure-response relationships to the Adelaide population living close to major roads would result in 36,681 (10% of 366,815) to 58,690 (16% of 366,815) highly annoyed people. This compares well to the findings of 48,419 people who were highly annoyed by road transport noise in this survey.
Quality of life and noise
This study also clarified the relationship between noise annoyance and health-related QOL showing a significant discrepancy in QOL scores in people highly annoyed by noise compared to low annoyance.
Annoyance in itself is not a direct health outcome, but conceptually has been positioned into the cause-effect pathway, where the cognitive and emotional responses to noise are thought to be translated into physiological reactions which in turn can eventually lead to stress-related chronic illnesses such as hypertension, arteriosclerosis and ischemic heart disease.  The biological plausibility of this stress reaction model is supported by numerous occupational and community noise studies indicating stress hormone levels and other relevant physiological endpoints for participants exposed to higher levels of noise. , More severe clinical manifestations of the noise stress model have been recently examined in a meta-analysis of epidemiological studies investigating the relationship between noise, blood pressure and ischemic heart disease concluding that road traffic noise increases risk for both health endpoints. The WHO has used the resulting exposure response relationships to calculate the burden of disease for environmental exposure to noise. ,
The SF-36 survey is generally recognized for its valid measure of the QOL status among respondents.  This study is one of only few population-based studies that investigates noise-related annoyance associated with health-related QOL using SF-36 questions. The findings of persistently and significantly lower QOL scores across all SF-36 dimensions in relation to road transport and neighborly noise demonstrated in this study raises the hypothesis that perceived highly annoying noise may affect health.
The SF-36 questions have in the main been used to study the impact of chronic diseases on QOL. ,, Recently, the SF-36 survey was also used to assess impacts of environmental exposures on health and well-being in Norway. A short-form of the survey (physical and mental functioning) demonstrated a significant reduction in the physical functioning scale for women who were living in higher traffic density compared to in low traffic areas.  In a similar study to this, Dratva et al. associated noise annoyance in a population based sample of 5,021 residents participating in the Swiss cohort study, documenting lower scores for all SF-36 dimensions except for general health.  The QOL reductions were in the same order of magnitude as observed in this study. A further study conducted in New Zealand found similar reductions in QOL correlated to annoyance perceptions for transportation and neighborhood noise and offered the additional finding of positive QOL outcomes for quiet versus noisy areas and rural versus city locality. 
This study has limitations. The QOL score reductions associated with environmental noise in this and the cross-sectional study mentioned previously require cautious interpretation, as in both cases the study design only offers a snapshot of associations which preclude the detection of exposure-response relationships that preceded the development of the health status. Hence, the lower SF-36 scores in the highly annoyed population in this study may not directly indicate a causal relationship with noise as QOL decreases, but may be associated with preexisting chronic disease and hence a predisposition and susceptibility to potential noise impacts on health. In the Swiss cohort study, availability of preexisting chronic disease data made it possible to assess this modification indicating higher traffic-related annoyance in this vulnerable subgroup.  Other known and unknown confounders may contribute to the noise health association including health impacts associated with higher pollution alongside major roads and socioeconomic factors. In this study, adjustment for socioeconomic factors has not changed the results.
The finding of QOL in the highly noise-annoyed population ties in with the overall evidence gathered about health and road transport noise and suggests that the health-related QOL survey is sensitive to environmental exposures and that people may experience real impacts on health and well-being. It is therefore possible that stress-related small changes in well-being have the potential to accumulate and add to the burden of more severe stress-related clinical outcomes.
In a recent review of the use of questions on annoyance in relation to noise interventions, it was recommended to expand the evaluation of the changed noise scape by using health endpoints other than levels of annoyance.  The application of a health and well-being survey before and after preventive noise interventions and parallel to noise annoyance questions may be an excellent way of investigating changes in noise-related health impacts.
More conclusive results between noise exposure and health outcomes require cohort and intervention studies that include confounding information such as individual health status, behavior data, air quality and/or traffic-related measures. Future noise studies could benefit from inclusion of QOL and annoyance outcomes to explore the extent of noise problems in specific environments such as for inner city dwellers, for communities along major highways or for those living under flight paths.
This representative noise annoyance survey has assessed the extent of the environmental noise problem on the health-related QOL in SA and the contribution of specific sources providing a valid comparison to noise attitudes in other parts of the world. Noise from road transport and from neighbors attracted the highest percentage of noise annoyance, and proximity to a major road explained some of the high annoyance. The data of this first representative noise attitude survey in SA serves as a baseline for assessing future development and noise abatement proposals.
| Conclusion|| |
The use of QOL scores alongside noise perception questions has been a novel approach and the results complement the findings from the few studies which also used SF-36 measures in connection with noise annoyance. These self-assessed health outcomes could become useful indicators for successful noise mitigation. The results of this cross-sectional study support several hypotheses, which on the basis of current knowledge are not mutually exclusive or exhaustive:
- Preexisting disease may be exacerbating noise perception,
- Environmental noise may have a detrimental effect on health, and
- Lower socioeconomic status, and/or higher air pollution in noisy transport corridors may contribute to poorer QOL.
Taking into account that the WHO has conclusively declared noise pollution to cause significant health effects on populations, it is prudent to embrace good noise management to protect public health and well-being.
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Dr. Monika Nitschke
Department for Health and Ageing, 11 Hindmarsh Square, Adelaide SA 5000
Source of Support: South Australian Environment Protection Authority and the Department of planning, Department of Planning, Transport and Infrastructure (DPTI) and Department of Health and Ageing,, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3]