| Literature DB >> 25988003 |
Shamas Tabraiz1, Saeed Ahmad1, Iffat Shehzadi2, Muhammad Bilal Asif1.
Abstract
BACKGROUND: Noise pollution has increased to alarming extent in most of the urban areas in Pakistan. It is assumed even more perilous than air and water pollution due to its direct acute and chronic physio-psychological effects. The objective of this study is to analyze and evaluate the psychological and physiological effects caused by traffic noise on traffic wardens and to find relation type between exposure time and effect.Entities:
Keywords: Exposure-effect relation; Noise pollution; Physio-psychological effects; Traffic wardens
Year: 2015 PMID: 25988003 PMCID: PMC4434876 DOI: 10.1186/s40201-015-0187-x
Source DB: PubMed Journal: J Environ Health Sci Eng
Figure 1Noise levels (Leq 8hrs) at Taxila Underpass check post.
Figure 2Noise levels (Leq 8hrs) Tarnol check post.
Figure 3Noise levels (Leq 8hrs) Golra mor check post.
Figure 4Psychological effects of noise on traffic wardens.
Figure 5Exposure time wise psychological effects of noise on traffic wardens.
Figure 6Physiological effects of noise on traffic wardens.
Figure 7Exposure time wise Physiological effects of noise on traffic wardens.
Figure 8Exposure time wise Physiological effects of noise on traffic wardens.
Summary of simple regression statistics (exposure-effect relation)
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|
|
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|---|---|---|---|
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| 0.978 | 0.033 | Linear |
|
| 0.16 | 0.093 | Non-linear |
|
| 0.143 | 0.233 | Non-linear |
|
| 0.327 | 0.099 | Non-linear |
|
| 0.7 | 0.0388 | Non-linear |
|
| 0.4 | 0.349 | Non-linear |
|
| 0.976 | 0.001 | Linear |
|
| 0.945 | 0.0136 | Linear |
|
| 0.609 | 0.0312 | Linear |
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| 0.06 | 0.21 | Non-linear |
|
| 0.728 | 0.0396 | Linear |
|
| 0.6 | 0.089 | Linear |
|
| 0.786 | 0.020 | Linear |
|
| 0.896 | 0.0269 | Linear |
|
| 0.199 | 0.052 | Non-linear |
|
| 0.827 | 0.049 | Linear |
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| 0.05 | 0.0039 | Constant |
|
| 0.00588 | 0.025 | Non-linear |
*P-value is the probability of observing a test statistic more extreme than what was observed (if p < 0.05 then null hypothesis rejected).
*R2 is a coefficient of determination (measures the how accurate linear model is at predicting i.e. near to unity mean more linear relation).