ABSTRACT
The assessment of effects on quality of life, annoyance, and health of transport noise at the community level is less straightforward than, for example, for the work site or for other, more closed acoustic spaces or products emitting noise; the results at the community level are much more varied. This often causes administrators and policy makers to wrongly conclude that the evidence for the effects of the acoustic environment on humans is weak. Research into these observed variations in effects
5.3 Medium-to Smaller-Scale Analyses of Sound-Related Health, Quality of Life, and Restoration Studies: Environmental Health Impact Assessment (EHIA) Study-Brenner Eisenbahn Gesellschaft (BEG) 104 5.3.1 Main Aims and Hypotheses 104 5.3.2 Outline of the Studies: Exposures and Outcomes Studied 105
5.3.2.1 Lower Inn Valley Studies (N = 2004, N = 807, and N = 570) 105
5.3.3 Results 108 5.3.3.1 Traffic Noise Exposure, Residential Context,
Emotion, and Health: UIT-1 (N = 2004) 108 5.3.3.2 Traffic Noise Exposure, Disturbance,
Coping, Restoration, and Neighbourhood Dissatisfaction: UIT-2 (N = 572) 109
5.3.3.3 Integrated Multivariate Model of Traffic Noise Exposure, Residential Satisfaction, and Health: UIT-2 (N = 572) 113
5.3.3.4 Fuzzy Model of Health-Related Quality of Life and Satisfaction: ALPNAP Study (N = 1643) 117
5.3.3.5 Integrated SEM of Traffic Noise Exposure, Residential Satisfaction, Restoration, and Health: UIT-2 (N = 572) 120
5.3.4 Discussion of Accomplishments and Limitations 121 5.3.4.1 Accomplishments 121 5.3.4.2 Limitations 123
5.4 Future Perspectives 124 5.4.1 Research Perspective 124 5.4.2 Policy Perspective 124
References 125
provides the key to understanding how adverse effects on health could be mitigated or even prevented by considering health-promoting and restorative aspects of the acoustic environment (healthy soundscapes) in environmental planning and land use assignments. We need, however, to admit that the main current approaches addressing the effects of the acoustic environment on health and quality of life have some inherent methodological limits. Only about 10%–20% of the variance in the community annoyance reactions is explained by typical acoustic indicators (Lden and Lnight) used in regulations. For health effects, the variance explained is even much less (below 5%), and we must ask what is lost and why do we lose essential information on the variance not explained. It is obvious that any preventive intervention or implementation of measures at the various scales will suffer from such a deficit. These facts underline the importance of developing approaches and analytic tools in research and practice that improve the predictions, particularly at the specific scales of inquiry and intervention.
