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Noise Pollution Clearinghouse, April 25th, 1997.
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This report has been approved for general availability. The contents of this report reflect the views of the contractor, who is responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policy of EPA. This report does not constitute a standard, specification, or regulation. |
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III-1 Overview of Data |
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III-6 Differences Associated with Socioeconomic Level and Income
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III-7 Differences Associated with Neighborhood Satisfaction (Q. 4) |
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III-8 Differences Associated with Rated Noisiness of Neighborhoods |
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III-9
Differences Associated with Annoyance
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III-10 Differences Associated with Intensity of Annoyance (Q. 14) |
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III-14 Differences Associated with Sensitivity (Q. 41) |
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III-15 Differences Associated with Self Rated Health Effects |
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III-16 Differences
Associated with Duration of Exposure |
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III-17 Noise Sources |
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III. |
III-18
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III-19 Critical Level Analysis |
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III-20 Relationship Between
Noise Levels,
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III-22 Discussion of Sampling Bias |
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IV |
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IV-2 On the Predictability of Annoyance |
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IV-3 On Noise Sources |
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IV-4 On Complaints |
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IV-5 On The Relation Between Annoyance and Demographics Variables |
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IV-6 On the Relationship of Current Findings to Prior Findings |
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APPENDICES (** Note: The Noise Pollution Clearinghouse editors chose not to include this section. For information about the contents of this section please conact us using our web form or call the Noise Pollution Clearinghouse at 1-888-200-8332, or write us at P.O. Box 1137, Montpelier, VT 05601. **) |
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The author is indebted to colleagues at Bolt Beranek and Newman for discussions, suggestions, and assistance in the analysis of the data of the National Urban Noise Survey. In particular, Drs. William Galloway and David Green suggested statistical analyses; Dr. Theodore Schultz's work was the basis of comparisons with other survey data; Dr. Glenn Jones examined the attitudinal data for inflection points; Mr. Myles Simpson prepared much of the information on noise sources; Mr. Richard Horonjeff analyzed the relationship between noise levels and annoyance as a function of time of day; and Messrs. Karl Pearsons and Dwight Bishop commented on draft material. Mr. Suyeo Tomooka assisted extensively in data reduction.
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A major responsibility of the Environmental Protection Agency, Office of Noise Abatement and Control (EPA/ONAC), is to protect public health and welfare from the deleterious effects of noise by coordinating research activities, promulgating Federal noise emission standards, and providing information to the public regarding the effects and control of noise. Such activities must be based as firmly as possible upon scientific understanding of the effects of noise on people. EPA/ONAC has thus far relied extensively upon the information contained in the "Levels Document" (EPA, 1974) for information about the extent and severity of various impacts of noise.
The research from which these public health and welfare criteria were derived, however, was quite specialized and narrow. In particular, the great bulk of the data on community response to noise exposure (principally annoyance) concerned aircraft and airport related noise only. Since only a small proportion of the American population is exposed to such noise, a nationwide Urban Noise Survey (UNS) was undertaken in the Spring of 1974.
UNS differed from previous studies of noise pollution in several important ways:
(1) The survey was national rather than local in scope. Prior social surveys had generally been restricted to a small number of geographically related sites.
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(2) UNS did not place emphasis upon the evaluation of any single noise source. Almost all previous study of community reaction to noise exposure had been limited to transportation noise.
(3) UNS was specifically intended to investigate community reaction over broad ranges of noise exposure conditions and lifestyles.
(4) UNS was designed to take advantage of systematic a priori noise exposure information. The interviewing sites were selected from one hundred sites nationwide at which very detailed noise measurements had been made.
Thus, the data of UNS offer the most comprehensive sampling of public reaction to noise exposure yet available. The data cover virtually the entire range of noise exposure and population density conditions in non-rural America. Data were collected at twenty four sites in seven cities across the nation at which previous detailed noise measurements had been made for other purposes (Galloway et al., 1974). These sites, although exposed to occasional aircraft overflights, were intentionally selected to avoid significant airport and highway noise exposure. Human exposure to surface street traffic noise was nonetheless comparable in level to highway noise at some sites.
More than two thousand interviews of randomly selected respondents were conducted at these sites, with a comprehensive yet brief questionnaire that contained questions about all major effects of noise on people and all pre dominant sources of community noise. One unique feature of
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this survey was that a continuous set of 24 hour noise measurements was taken at the sites at the same time that interviewing was in progress. Another important difference in design was direct measurement of annoyance, as discussed by Rylander et al. (1972) inter alia. The prevalence of annoyance was not inferred from constructed statistical indices; it was determined from respondents' answers to specific questions.
This report presents the overall analysis of the data of the national Urban Noise Survey. Like the experimental design, the analysis departs from some prior analyses of social survey data. In particular, greater emphasis is placed on prevalence of noise effects in groups of people instead of individual attitudinal variables. Thus, little effort is made to "explain" individual attitudes by comparing their intensities. Rather, attention is concentrated on predicting population proportions affected in various ways by noise exposure.
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The following summary of procedures, excerpted in part from Simpson et al. (1974), is intended only as a brief summary. The reader is referred to Simpson et al. (l974) for more detailed information and a discussion of the rationale of the survey.
Four disjunctive criteria were employed for site selection.
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First, roughly equal numbers of respondents in each of six noise exposure ranges centered at Ldn values of 50, 55, 60, 65, 70 and 75 dB were. to be interviewed. This procedure was intended to produce equal expected precision of measurement over the sampled range of noise exposures. The second criterion for site selection was that opinion be sampled at sites characterized by widely varying population densities. For a given noise exposure, respondents were there fore interviewed in each of four different population density classes centered at 2000, 6300, 20,000 and 63,000 people per square mile. This criterion was adopted because the variable "population density" is associated with life styles, which may in turn influence opinions. High population densities imply apartment living, relatively little time spent outdoors, use of mass transit, etc. Low population densities imply suburban living, use of private automobiles, more outdoor noise exposure, etc. |
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The third criterion for selection of sites was that the number of interviews conducted within each population density class be roughly proportional to the national distribution of population density. The final criterion required selection of sites within cities representative of major geographic areas of the country. |
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The questionnaire (contained in Appendix A) was designed to gather information about the respondents' attitudes toward their environment, with the greatest emphasis on noise. Simple random sampling without replacement was elected as the sampling procedure. The sample frame most appropriate to the available resources was the reverse telephone directory. The target population of the survey was the adult American urban population habitually exposed to community noise not predominantly of aircraft or highway origin.
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Interview data were keypunched on tabulating cards and processed by computer. Numerous tabulations of these data may be found in Appendix B. They are of interest primarily to those who wish to make uses of the data beyond those reported here. This section proceeds from the general to the specific, through successively finer analyses of findings. Few readers will be equally interested in all sub-sections. Those satisfied with a descriptive account of "what happened" need not read beyond the preliminary sections for a narrative account of findings. For readers more interested in statistical analyses, the introductory sections may be tedious. Such readers may wish to proceed to Sections III-17 et seq. after reading Section III-1.
Section III-1 presents an overall view of the findings as a context within which other analyses may be understood. Sections III-2 and III-3 describe major effects associated with the two independent variables of UNS (noise exposure and population density). Sections III-4 through III-6 pre sent demographic differences associated with age, sex, and socioeconomic level. Sections III-7 through III-16 contrast response patterns associated with answers to key questions.
For the sake of clarity and brevity, most of these introductory sections contain contrasts between extreme sub samples; e.g., high vs. low noise exposure, high vs. low
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socioeconomic level, young vs. old respondents, etc. Differences not specifically mentioned are of small size or little relevance. Furthermore, percentages are reported rounded off to the nearest integer. The reader is also cautioned against drawing causal inferences about the simple relationships discussed in the first sixteen sub sections, since virtually all of these first order relation ships have strong higher order interactions.
Sections III-17 et seq. are given to statistical inference rather than simple description. Section III-17 presents findings pertaining to noise sources. Section III-18 summarizes regression analyses for key variables. Section III- 19 details a search for critical noise levels. Section III- 20 explores the relationship between noise exposure and annoyance as a function of time of day. Section III-21 addresses a methodological issue, the mode of interviewing. Section III-22 is concerned with another methodological issue, sampling bias.
A total of 2037 Persons (762 men, 1275 women) was interviewed, of whom 670 men and 1164 women were interviewed by telephone. The other respondents were interviewed in person. Table III-1 summarizes the number of interviews conducted at each site, as well as the noise level and population density of each site.
Nationwide, 69% of all respondents rated their neighborhoods as good or excellent places to live, with only 23% seriously thinking of moving within the next year. Of these people, only 1% cited noise as a reason for moving. Sixty two percent of all respondents regarded their neighborhoods
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NUMBER OF |
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POPULATION |
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Atlanta |
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Boston |
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Chicago |
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Los Angeles |
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Seattle |
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*Sites at which personal (face-to-face) interviews were conducted.
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as quiet, but 46% claimed to have been "bothered or annoyed" by
noise in their neighborhoods.*
Thirty-one percent of the ever-annoyed people were "highly annoyed"
(self-rated "very" or "extremely" on an adjective scale that also
included the terms "not at all", "slightly", and "moderately") by
noise in their neighborhoods. Neighborhood noise was thought to be
equally annoying at all times of day by 22% of the ever annoyed;
another 22% of these people found neighborhood noise more annoying in
the evening than at other times of day; and 27% found such noise more
annoying at night.
Over half of the ever-annoyed found noise more bothersome when inside the house than when outside; the others either found noise more bothersome outdoors or felt there was no difference outside or inside the house. The major findings with regard to time and place of annoyance are summarized in Figure III-1.
Table III-2 rank orders the frequency with which ever annoyed people reported hearing various noise sources. The table also indicates the average annoyance on an arbitrary 5 Point adjective scale (where 1 corresponds to "not at all annoyed" and 5 corresponds to "extremely annoyed") associated with each source. As the table shows, motor vehicle noise was the most pervasive noise source
*These latter respondents are referred to henceforth as the "ever-annoyed". Because the structure of the questionnaire concentrated attention on the ever-annoyed, most of the findings reported below concern this group of people. Figures based on the total sample are referred to as "percentages of all respondents".
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FIGURE III-1. SUMMARY OF FINDINGS WITH REGARD TO TIME AND PLACE OF ANNOYANCE
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heard nationwide (reported by 865 of these respondents), and also the most annoying. People and pets were the next most often noticed sources, followed by aircraft, construction, power garden equipment and electronic sources (radios, TVs, etc.).
Table III-3 rank orders the frequency with which people who had ever been annoyed by noise in their neighborhoods experienced various effects of noise. Sleep disturbance, the most common effect of noise exposure (reported by 60% of these respondents) was also the most annoying (with a mean value of 3.6). Startle and speech interference were somewhat less pervasive effects, and of lesser annoyance.
Nineteen percent of the ever-annoyed people (9% of all respondents) claimed to have complained to officials about noise in their neighborhoods. Twenty-four percent of all respondents felt themselves to be more sensitive to noise than most people, while only 6% of all respondents felt that noise exposure had affected their health.
III-2 Differences Associated with Noise Exposure
The numerous effects associated with noise exposure are most simply presented by comparing data from two extreme subsamples: one of six heavily exposed sites (mean Ldn = 70.0 dB) and one of seven lightly exposed sites (mean Ldn = 54.6 dB). All comparisons in this section are of averaged data from the high noise exposure subsample with respect to the low noise exposure subsample.
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% OF EVER-ANNOYED . |
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Startle or Fear |
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Speech Interference: |
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1These figures must be multiplied by .46 if extrapolated to the entire sample. For example, the 60% of the ever-annoyed people who reported sleep disturbance constitute 20% of the entire sample.
2Mean annoyance on an arbitrary five point scale.
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Neighborhood satisfaction was considerably lower in the high exposure subsample. Thirty four percent fewer people in the high exposure subsample described their neighborhoods as an excellent place to live, and 24% more people described their neighborhoods as only a fair place to live (Q. 4)*. Fifteen percent more people at the high exposure sites intended to move out of the neighborhood in the next year (Q. 9). Thirty eight percent fewer people regarded their neighborhoods as quiet (Q. 11). Seventeen percent more people had been annoyed by noise (Q. 13) at the high exposure sites; and twenty seven per cent more people were annoyed in their homes (Q. 18). Figure III-2 is a plot of the percentage of respondents at each of the 24 sites who were highly annoyed by noise exposure (i.e., rated themselves as "very" or "extremely" annoyed). The correlation coefficient between Ldn and annoyance, .70, is extremely unlikely to have arisen by chance alone from a sample of size 24. Its fiduciary limits (for a 95% confidence interval) are from 0.45 to 0.86.
Emphasis placed upon the annoyance of various noise sources differed considerably between the two subsamples, with smaller numbers of respondents in the high exposure sub sample reporting annoyance from pets (21% fewer), helicopters (33% fewer), power garden equipment (475 fewer), sports cars (11% fewer), and motorcycles (9% fewer). On the other hand, more respondents in the high noise exposure subsample reported annoyance from construction noise (9% more), people's voices (24% more), radio and TV sets (11%
*This number refers to questionnaire item 4, found in Appendix A.
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FIGURE III-2 |
RELATIONSHIP BETWEEN NOISE
LEVEL AND |
more), motor vehicle noise (13% more), large trucks (15% more), buses (19% more), and constant traffic (38% more).
Similarly, more respondents in the high exposure sub sample reported activity interference such as listening (25% more), speaking (20% more), and sleeping (8% more). Seven percent more respondents in the high exposure sub sample claimed to have registered complaints about noise with officials. Figure III-3 plots complaint rates as a function of noise exposure at the 24 sites. The correlation coefficient, .23, is likely to have arisen by chance alone. In general, the direction of differences between responses in the two subsamples were consistent with the position that noise exposure degrades the quality of life.
III-3 Differences Associated with Population Density
Effects of population density on response patterns were analyzed in the same fashion as in Section III-2, through comparisons between extreme subsamples. Data from five high population density sites (mean density = 44,920 people per square mile) are compared with data from five low population density sites (mean density = 1600 people per square mile). Comparisons in this section are of averaged data from the high density subsample with respect to the low density sample.
Response patterns in the extreme population density sub samples closely paralleled (within a few percent) those
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FIGURE III-3 |
RELATIONSHIP BETWEEN NOISE
LEVEL AND |
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associated with noise exposure. While neighborhood satisfaction was lower in the high density subsample, the incidence of noise induced annoyance was higher. The proportions of respondents reporting annoyance from various sources differed very little from those reported in Section III-1. Those sources more prevalent in highly urbanized areas were more often mentioned than was the case in high noise areas; e.g., people's voices, air planes, radio and TV sets, and automobiles.
Twenty percent more people in the high density subsample reported interference with listening, 9% more reported interference with talking, and 9% more reported sleep disturbance. These figures. hardly differ from those noted in Section III-2.
III-4 Differences Associated with Age
To assess differences in opinions associated with age, respondents were divided approximately into thirds on the basis of age, as estimated from the year in which formal schooling was completed. This section contrasts the opinions of the 30% of the respondents aged 30 years or younger with the 34% of the respondents aged 45 or older.
Differences in neighborhood satisfaction associated with noise between the two groups were negligible. Older respondents had lived longer in their neighborhoods, while younger respondents were more ready to move within the year. Nonetheless, differences in percentages of the two groups citing noise as a cause for discontent were mostly less than 5%.
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Six percent fewer of the younger group thought their neighborhoods were quiet, but 15% fewer reported being annoyed by noise in their neighborhoods. Eleven percent more of the younger respondents could not distinguish seasonal differences in annoyance, but 13% more of the older respondents thought neighborhood noise was more annoying in the summer. Greater percentages of the older respondents thought neighborhood noise was more annoying weekdays (13% more) and inside the house (15% more).
Fourteen percent fewer of the older respondents were annoyed by construction noise, but greater percentages of the older respondents reported annoyance from airplanes (11% more), helicopters (11% more), power garden equipment (15% more), sports cars (11% more), and motorcycles (11% more). Nonetheless, uniformly greater percentages of the younger respondents reported speech or listening interference (18% and 6% more, respectively), startle or fright (15% more), or sleep interference (19% more). Nine percent more of the older respondents felt they were more sensitive than most to noise. A gross relationship between age and complaint rates may be seen in Figure III-4.
III-5 Differences Associated with Sex
Differences between male and female respondents were small both in number and magnitude. For example, the largest difference between men and women among the neighborhood satisfaction questions was less than 6%. More men intended to move within the next year than women, but only about 1% of either sex respondents gave noise as a reason for moving.
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FIGURE III-4 |
RELATIONSHIP BETWEEN AND COMPLAINTS. |
Differences between the sexes with regard to assessment of noisiness and annoyance associated with neighborhood noise exposure were also trivial. The largest difference of opinion was an 8% difference on the issue of season of the year of greatest annoyance - more men than women felt that summer was the most annoying time.
Differences between men and women in ratings of noise sources were also inconsequential, rarely exceeding two or three percent. A sole exception was that 10% more women reported hearing construction noise in their neighborhoods. No differences on other substantive matters (such as activity interference, complaint rates, sensitivity to noise, or health effects) exceeded 5%, and most were on the order of one or two percent.
Perhaps the most notable difference between the sexes on the entire questionnaire was in time spent at home. Women reported spending about 3-1/2 more hours at home on both weekdays and weekends than men.
III-6 Differences Associated with Socioeconomic Level and Income
The subsamples contrasted in this subsection are respondents in the upper and lower halves of the Duncan scale of socioeconomic level. The observed differences tend to support the hypothesis that high socioeconomic level respondents suffer less from noise pollution than do low socioeconomic level respondents.
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For example, neighborhood satisfaction was higher among the high socioeconomic level respondents (18% more rated their neighborhoods as excellent places to live); 6% fewer of the high socioeconomic level respondents were thinking of moving within the year; 9% more of the high SEL respondents considered their neighborhoods quiet; and 19% more of the high socioeconomic level respondents were unable to distinguish differences in annoyance with neighborhood noise among the seasons.
Differences in rates of identification of various noise sources were relatively small but consistent; 8% fewer high socioeconomic level respondents reported hearing people's voices, 4% fewer reported airplanes, 6% fewer reported automobiles, and 7% fewer reported traffic. On the other hand, 6% more high socioeconomic level respondents reported hearing pets, 7% more reported power garden equipment, and 8% more reported sports cars.
Similarly, 9% fewer high socioeconomic level respondents reported interference with listening, and 6% fewer reported fear or startle. Seven percent more of the high socioeconomic level respondents reported complaining about neighborhood noise. High socioeconomic level respondents spent an average of an hour and a quarter more at home on weekdays, and two and a half hours more at home on weekends.
The pattern of differences associated with extreme income groups was predictably similar to those associated with extreme socioeconomic groups. The magnitudes of the differences tended to be greater, however. The two income subsamples
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contrasted here are those respondents reporting annual household incomes below $10,000 and those respondents reporting annual household incomes above $20,000.
Forty two percent more high income respondents rated their neighborhoods as excellent places to live; 15% fewer high income respondents were thinking of moving within the year; and 20% more of the high income respondents thought their neighborhoods were quiet. A relationship between income and exposure levels is seen in Figure III-5.
Differences in identification of noise sources were also similar to those associated with high socioeconomic levels. Twenty one percent more high income respondents reported power garden equipment, 18% reported more sports ears, and 12% reported more motorcycles. On the other hand, 11% fewer reported constant traffic noise.
Likewise, 16% fewer high income respondents reported that noise interfered with listening, and 9% fewer were startled or frightened by neighborhood noises. Nonetheless, 7% more high income respondents reported sleep disturbance. Seven percent more high income respondents also reported complaining about neighborhood noise. The high income respondents spent about an hour and forty minutes more time at home on weekdays than did the low income respondents, and an additional hour and a half on weekends.
III-7 Differences
Associated with Neighborhood Satisfaction
(Q. 4)
The 69% of all respondents who rated their neighborhoods as good or excellent places to live (the "highly satisfied") differed from the 31% of all respondents who rated their neighborhoods as
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FIGURE III-5 |
RELATIONSHIP BETWEEN
AVERAGE ANNUAL |
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Thirty six percent more of the respondents who thought their neighborhoods were good or excellent viewed their neighborhoods as quiet. Further, nineteen percent more of those highly satisfied with their neighborhoods had never been bothered or annoyed by noise in their neighborhoods. The highly satisfied who had been bothered or annoyed were not as aware of differences in annoyance as a function of time of day or season of the year. The highly annoyed identified fewer neighborhood noise sources as annoying, and were generally less annoyed by them.
Not surprisingly, the respondents who were highly satisfied with their neighborhoods were of a higher socioeconomic level than those who were not (by about one and a half deciles on the Duncan scale), and reported average annual household incomes twice as great as respondents less satisfied with their neighborhoods ($11,500 VS. $5,700).
III-8 Differences
Associated with Rated Noisiness of
Neighborhoods (Q. 11)
Sixty two percent of all respondents described their neighborhoods as quiet when asked to characterize them as quiet, noisy, or
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neither quiet nor noisy during the preceding year. The responses of these respondents are contrasted with those of the 31% of all respondents who characterized their neighborhoods as noisy.
Thirty four percent more of those who thought their neighborhoods were quiet also rated them as excellent or good places to live. Sixteen percent more spontaneously mentioned the absence of noise as the most favored aspect of living in their neighborhoods. Fourteen percent more of those characterizing their neighborhoods as noisy were thinking of moving during the next year. Forty nine percent more of the respondents who thought their neighborhoods were quiet had never been annoyed by noise in their neighborhoods. Thirty seven percent more of the respondents who thought their neighborhoods were quiet reported that annoyance was only minimal (not at all or slightly), whereas 38% more of those respondents who thought their neighborhoods were noisy found their annoyance considerable (moderately, very, or extremely).
Twenty one percent more of the respondents who thought their neighborhoods were noisy thought that noise was more annoying in the evening or at night, while 15% more of the same respondents were more annoyed indoors than outdoors.
The predominant noise sources heard by people who thought they lived in quiet neighborhoods were peoples' voices (16% more than in noisy neighborhoods) and constant traffic (18 more than in noisy neighborhoods). Conversely, greater percentages of respondents who thought they lived in noisy neighborhoods reported hearing power garden equipment (17% more), helicopters (15% more), and motorcycles and sports cars (8% more each).
It is quite clear that people who thought they lived in quiet neighborhoods suffered fewer effects of noise exposure, since 25%
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fewer reported interference with listening, 18% fewer reported interference with speaking, 20% fewer reported sleep interference, 15% fewer reported startle or fear, and 22% fewer reported shutting windows because of intrusive noise. Slightly fewer (3%) of the respondents who thought they lived in quiet areas reported complaining about noise, while 11% more thought noise had not affected their health.
The mean annual household income was somewhat greater for those who thought they lived in quiet neighborhoods ($10,650 vs. $8,250).
III-9 Differences
Associated with Annoyance from.
Neighborhood Noise (Q. 13)
The major breakpoint in the interview was at Question 13, "Have you ever been bothered or annoyed by noise in your neighborhood?" If answered negatively (as 53% of all respondents did), the interview concluded quickly without questioning about noise sources or effects. This section contrasts the responses of the "never-annoyed" with those of the "ever-annoyed".
Seventeen percent more of the never-annoyed respondents thought their neighborhoods were good or excellent places to live. Ten percent more of the never-annoyed specifically mentioned a noise-related aspect of their neighborhoods (e.g., "peace and quiet", "no noise from ....", etc.) as the "first most liked thing" (Q. 5). Thirteen percent fewer of the never-annoyed specifically mentioned a noise related aspect of their neighborhoods as the "least liked thing" (Q. 7). Eleven percent fewer of the never annoyed were thinking of moving within the year.
Forty one percent more of the never-annoyed respondents described their neighborhoods as quiet places to live, and 11% fewer of them thought neighborhood noise had affected their health.
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III-10 Differences
Associated with Intensity of Annoyance
(Q. 14)
Fourteen percent of all respondents described noise in their neighborhoods as either very or extremely annoying over the past year. The relationship between annoyance so measured and average income at the 24 sites is seen in Figure III-6. Among the most notable differences between these highly annoyed respondents and the others were their self reports of the effects of noise exposure.
Twenty one percent more of the highly annoyed respondents judged their health to have been affected by neighborhood noise; specifically, in the form of hearing damage. Eleven percent more of the highly annoyed respondents thought themselves more sensitive to noise than most people. Twenty four percent more of the highly annoyed reported sleep interference, 20% more reported interference with listening, 21% more reported interference with speaking, 21% more reported shutting windows to keep out noise, and 12% more reported startle from noise. In general, greater numbers of highly annoyed respondents identified the various noise sources as annoying, and were consistently more greatly annoyed by each noise source then were the respondents who were not highly annoyed.
Fifty one percent more of the highly annoyed described their neighborhoods as noisy places to live, 26% fewer rated their neighborhoods as good or excellent places to live, 16% more spontaneously mentioned noise as the least liked aspect of their neighborhoods, and 14% more were thinking of moving.
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FIGURE III-6 |
RELATIONSHIP BETWEEN AVERAGE ANNUAL HOUSEHOLD INCOME AND PERCENTAGE OF RESPONDENTS HIGHLY ANNOYED BY NEIGHBORHOOD NOISE AT 24 SITES |
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III-11 Differences Associated with Startle
Thirteen percent of all respondents reported considerable annoyance from startle or fear produced by neighborhood noises. Their responses are contrasted in this section with those of a subsample of ever-annoyed respondents composed of those who were minimally annoyed by startle or fear (those who reported they were not at all or slightly annoyed) and those who reported no startle or fear at all.
The opinions of respondents who were considerably annoyed by startle and fear differed from those who were not in many ways. Twenty percent more of them thought their neighborhoods were noisy, and 13% more were thinking of moving. Those experiencing considerable annoyance with startle or fear also suffered more from other noise effects: 16% more were highly annoyed by neighborhood noises, 21% more experienced interference with listening, 31% more experienced interference with speaking, 30% more reported sleep disturbance, and 21% more kept their windows shut because of noise. Nineteen percent more felt that noise had affected their health, and 8% more felt that they were more sensitive to noise than most people. In short, these 13% of all respondents represent an extreme subsample both in terms of effects of noise and opinions about exposure.
III-12 Differences Associated with Sleep Disturbance
Twenty one percent of all respondents expressed considerable annoyance from sleep disturbance caused by neighborhood noises. The opinions of these people are contrasted with those who experienced no annoyance or only slight annoyance from sleep disturbance, or whose sleep was not disturbed by noise.
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Twenty one percent more of the people considerably annoyed by sleep disturbance considered their neighborhoods noisy, and 17% of them considered their neighborhoods more noisy at night than at other times of day. Eighteen percent more reported that they were more annoyed inside their homes. More of the people who were considerably annoyed by sleep disturbance also heard construction noise (17% more), people's voices (16%more), pets (l4% more), and radio and TV sounds (12% more). Fifteen percent more of these people experienced interference with listening, while 20% more experienced interference with speaking. Twenty three percent more reported startle or fear, and 27% more shut their windows to keep out noise. Although 16% more of these considerably annoyed people felt that noise had affected their health, only 1% more had complained to officials. Six percent more of these people felt themselves to be more sensitive than most to noise exposure.
III-13 Differences Associated with Complaints
Nationwide, 9% of all respondents (13% of the ever-annoyed) said they had complained about noise in their neighborhoods. The views of these people are contrasted with those of respondents who had not complained about noise in this section.
Twenty percent fewer of the complainers thought their neighborhoods were good or excellent places to live, and 13% more of them spontaneously mentioned noise as the least liked aspect of their neighborhoods. Thirty two percent more of the complainers rated their neighborhoods as noisy during the previous year, while 57% more were annoyed by neighborhood noise. The intensity of their annoyance was greater as well; 22% more of the complainers were highly annoyed. Nine percent more of the complainers found neighborhood noise more annoying on weekdays than weekends.
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Greater percentages of the complainers identified every neighborhood noise source (except for light trucks) as sources of annoyance. These differences, however, were generally on the order of 5%. Similarly, greater percentages of the complainers reported every noise effect: speech interference (8%), listening interference (75), startle or fear (10%), and sleep disturbance (23%). Eleven percent more of the complainers kept their windows shut because of neighborhood noise.
On average, complainers spent an additional 25 minutes at home weekdays, but 13 minutes fewer on weekends. Twelve percent more of the complainers described themselves as more sensitive than most to noise, while 17% more felt that noise had affected their health. Complainers averaged about ½ decile higher on the Duncan Scale of socioeconomic level, and enjoyed about $1000 more annual household income.
III-14 Differences Associated with Sensitivity
Twenty four percent of all respondents judged themselves to be more sensitive to noise than most other people. This section contrasts their opinions with those of the respondents who judged themselves to be about as sensitive or less sensitive than most.
In demographic terms, the respondents who judged themselves more sensitive than most included 7% more women, had an average annual income $1250 higher, and averaged half a decile higher in socioeconomic level than other respondents. Differences in neighborhood satisfaction between the two groups of respondents were minimal. Although only two percent more of the more
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sensitive respondents judged their neighborhoods to be noisy, it more had been annoyed by neighborhood noise. Eight percent more of the more sensitive respondents found neighborhood noise more annoying on weekdays than on weekends. Nine percent more of the more sensitive respondents were unable to distinguish whether neighborhood noise was more bothersome inside or outside the house. More of the more sensitive respondents identified all neighborhood noise sources (except automobiles and small trucks) as annoying. These differences, however, were relatively small (on the order of 5%).
Perhaps the greatest differences observed were in susceptibility to noise effects. Eleven percent more of the more sensitive respondents reported listening interference, 18% more reported startle or fear, 6% more reported sleep disturbance, 8% more reported speech interference, and 11% more reported keeping windows shut because of neighborhood noise. Seven percent more of the more sensitive respondents reported complaining about noise.
III-15 Differences Associated with Self Rated Health Effects
Five percent of all respondents thought that noise in their neighborhoods had affected their health in some way. This section contrasts their opinions with the 95% of the respondents who did not think noise had affected their health.
It is clear that the health-affected respondents are an extreme group: 28% more of them experienced interference with listening, 31% more suffered sleep disturbance, 36% more experienced speech interference, and 29% more shut their windows to keep out neighborhood noise. Twenty percent more had complained
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about noise, and 22% more felt more sensitive to noise than most people.
Larger percentages of the health-affected respondents reported various neighborhood noise sources as annoying: these included construction noise (7% more), people's voices (11% more), radios or TV sets (16% more), sports ears (13% more), small trucks (10% more), large trucks (l4% more), constant traffic (l4% more), and so forth.
Although 23% fewer of the health-affected viewed their neighborhoods as good or excellent places to live, 19% fewer were considering moving within the year. Forty two percent more of the health-affected thought their neighborhoods were noisy, and 48% more had been bothered-or annoyed by noises in their neighborhoods. The health-affected respondents had no clear consensus on the time of day or season of the year when noise was more annoying, nor on whether noise was. more annoying indoors or outdoors.
III-16 Differences
Associated with Duration of Exposure
to Neighborhood Noise
This section examines differences observed as a function of duration of exposure to neighborhood noise. In Part I, comment is made on differences associated with short vs. long daily exposure. In Part 2, comment is made on differences associated with short vs. long duration of residence.
All respondents were divided into two groups: those who spent 20 or more hours at home daily, and those who spent
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l4 or fewer hours at home daily. This division corresponded to approximately + or - .50 from the grand mean for all respondents (17 hours) spent at home daily.
Four times as many women as men spent more time at home (81% vs. 19%). Five to ten percent more of the respondents who spent more time at home experienced all of the noise effects (speech and sleep interference and fear or startle). Greater percentages of these respondents (about 6% more on average) also reported hearing most of the noise sources. The respondents who spent more time at home tended to be of slightly lower socioeconomic level (about half a decile, on average).
Understandably, more of the respondents who spent less time at home found noise in the mornings and evenings to be more annoying than at other times of day, and noise inside the house to be more annoying than outside the house. Most of the above differences in extensity were relatively small (on the order of 10% or less). Differences in intensity of opinions were even smaller, rarely exceeding 0.3 of a response category.
The overall distribution of respondents' duration of residence is seen in Figure III-7; an exponential fit to the distribution is remarkably good. Ail respondents were divided into two groups: those who had lived in their neighborhoods for six months or less, and those who had lived in their neighborhoods for five years or more. Because only, 2% of the sample fell into the former category, the reliability of comparisons between the two categories of respondents is poor.
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FIGURE III-7 |
DISTRIBUTION OF DURATION OF RESIDENCE OF RESPONDENTS |
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Thus, it is not surprising that there is no clear trend of differences apparent in comparisons of response patterns for the two groups. New residents of a neighborhood tended to differ from long term residents considerably in which noise sources they heard and found annoying; they reported more construction noise, pets, airplanes, helicopters, power garden equipment, specific vehicles, and miscellaneous sources, but fewer peoples' voices, radios and TVs, and less motor vehicle noise in general.
No generalization about sensitization vs. habituation to neighborhood noise sources seems to be supportable on the basis of differences observed between the two groups. Although differences in intensity of annoyance produced by various sources were relatively large (approaching a full category on a five point scale in some eases), they were inconsistent in direction. Similarly, there were sizable differences but no consistent trends in reported effects of noise. For example, twenty three percent more of the newcomers reported having been annoyed by noise in their neighborhoods, but nine percent fewer reported interference with listening to TV and radio.
Questions 19-34 posed the question "Over the past year have you heard ... in your neighborhood?" for major community noise sources. Respondents who had heard one of these sources were asked to rate how annoying the source had been over the year on a five-point adjective scale. Table III-4 rank orders these noise sources within population density strata. Table III-5 is an overall ranking of noise sources that affect the
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Motorcycles Autos Large Trucks Construction Sport Cars Constant Traffic Buses Small Trucks Helicopters Airplanes Power Garden
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Motorcycles Large Trucks Autos Construction Sport Cars Helicopters Constant Traffic Airplanes Small Trucks Buses Power Garden Equipment |
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urban population, calculated by weighting the responses by the percentage of the total population living in each population density stratum. Table III-6 rank orders other outdoor noise sources mentioned in response to Question 34 by number of occurrences.
B. Relationship Between Source Identification and Level
At each of 23 sites the outdoor noise environment was estimated by making an 8-minute long analog recording once an hour for a full day*. These recordings were processed to yield a time-history plot of the A-weighted noise level. During playback the sources of discrete noise events were identified by listening. Each noise event with peak level 5 dB or more above the total hourly equivalent level for that site for that hour (as determined from digital noise data) was considered to be a noise "intrusion". All intrusions were tabulated by level and source type, with peak levels classified into 5 dB increments and sources categorized as automobiles, trucks, buses, motorcycles, aircraft, sirens or horns, people, animals, mechanical equipment, telephones, radios or stereos, door slams, thunder, or rain. According to this definition, automobile and truck intrusions were observed at all sites; aircraft were observed at twenty two sites; and motorcycles were observed at seventeen sites.
Several physical indices of these noise intrusions were developed from the tabulated data at each site. The two basic indices were the daily number of intrusions by a specific source and the maximum level of the source at any time during the day (i.e., the peak level of the greatest noise intrusion). An energy-averaged peak level (determined by logarithmic addition of
*No such recordings were available at Site 1001.
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Sirens Fire Trucks Ice Cream Trucks Trash Pickup Gun Shots Trains Burglar Alarms Auto Horns Chain Saws Hot Rods - Drag Racing Defective Mufflers Defective Pump Refrigerator Truck Air Conditioner Model Airplanes Cement Mix Truck Welding Equipment |
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all the peak levels occurring during the day less 10 times the logarithm of the number of these intrusions) was also developed.
A fourth index, partial day-night sound level for noise sources, Ldn , was computed as well. The notation Ldnp was used to distinguish the partial Ldn values for each source from the total Ldn at a site*. The absolute value of the partial day-night level for different sources is relatively unimportant. It suffices for current purposes that the relative magnitude of Ldnp be reasonably accurate across sites for each source, so that relationships between response data and Ldnp values remain consistent.
For each of the four major intruding sources (aircraft,
automobiles, motorcycles and large trucks), a linear regression
was
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
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(1)
where SELdi and SELni are the sound exposure levels of individual events during daytime (7 a.m. to 10 p.m.) and nighttime (10 p.m. to 7 a.m.) periods respectively. These SEL values depend on the duration of the noise intrusion and its distance (level). For point sources traveling in a straight line with a velocity v (in ft/sec) and distance r (in feet) from an observer, the sound exposure level can be approximated by:
(2)
The ratio of r to v can be assumed constant for sources at all sites. A factor of two error will result in a difference of only 3 dB. Since the peak level itself is only known to within + or - 2.5 dB, such an error is acceptable. Equations (1) and (2) can be combined to:
(3)
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performed with the percentage of annoyed respondents as the dependent variable and the four indices of intrusion as independent variables: the number of noise intrusions (N)*, the maximum peak level during the day (max Lp), the average peak level during the day (Lp ), and the partial day-night level (Ldnp). Correlations were calculated for both the percentage of respondents highly annoyed by each source, and the percentage annoyed to any degree by each source. Table III-7 contains only those correlations unlikely to have arisen by chance alone (p < .05, n = approximately 20, rc > approximately 0.4).
As maybe seen in Table III-7, the day-night average sound level
has a correlation coefficient comparable to or better than that of
most other noise measures. Considering the degree of uncertainty
associated with the individual Ldnp values, a correlation
coefficient of the order of 0.5 between annoyance responses and the
day-night average level for each source is a useful finding. It
suggests that annoyance associated with intrusive noise sources can
be related to measurable noise exposure from such sources in the
community, even when the magnitude of noise exposure from an
intrusive source is below the total Ldn for a measurement
site.
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A ratio of r to v of 1:1 was assumed for present purposes. For typical values for r and v, the partial day-night levels, based only on the peak levels of noise intrusions, are well below the total Ldn at each site.
*N is the number of noise intrusions measured during the 24-hour 8-minute samples. The total number of noise intrusions that might have occurred during a full 24-hour day could be approximated by multiplying N by 7.5.
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CORRELATIONS BETWEEN THE PERCENTAGE OF RESPONDENTS EITHER ANNOYED OR HIGHLY ANNOYED AND VARIOUS NOISE INTRUSION MEASURES FOR INTRUSIVE NOISE SOURCES
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III-18 Correlational and Regression Analyses
The simple (linear) correlations among all respondents' answers to all major questionnaire items were computed as a first step. An alphabetized and cross indexed listing prepared from the correlation matrix is included in Appendix C, only those coefficients greater than 0.2 in absolute size appear in the listing. All of the coefficients are statistically significant (in the sense that they are extremely unlikely to have arisen by chance alone), primarily because of the very large sample size.
Perusal of this list of correlations yields few surprises: the composition of clusters of related variables (noise sources, attitudes, effects, etc.) are all similar to those predictable from the relationships observed in comparisons of extreme sub-samples. Among the demographic variables, for example, Population density and income correlated -.30, and age and duration of residence correlated .29. Among the situational variables, noise level correlated .36 with traffic as an identifiable noise source, but -.29 with power garden equipment. Among the attitudinal variables, responses to the ever-bothered question (Q, 13) correlated .50 with responses to the neighborhood noisiness judgment question (Q, 12), while responses to the latter question correlated .42 with the degree of annoyance question (Q, l4).
By themselves, the simple correlations are of little predictive value, since they are all confounded by their large numbers of
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significant partial correlations with one another. For example, the observed correlation of .27 in the individual data between responses to the questions "has noise made you keep your windows shut" (Q. 39) and "has noise affected your health" (Q. 45) does not imply any causal relationship. It is not clear from the simple relationship whether the attitude (noise affects health) produces the behavior (keeping windows shut), whether the behavior (keeping windows shut) reinforces the attitude (noise affects health), or whether the degree of association between answers to the two questions is attributable to common associations with one or more other attitudes, behaviors, and/or noise effects.
Policy making agencies are more properly concerned with how their decisions will affect proportions of populations than with the prediction of interrelationships among individual attitudes. Thus, no further efforts were made to interpret the simple correlations among individual intensive variables.
A second set of correlation matrices was therefore computed by grouping respondents within sites. This treatment of the social survey data concentrates on extensity of attitudes and behaviors. The variables of interest in the analyses reported below are therefore percentages of respondents holding common views, rather than the fervor of individual beliefs.
Table III-8 shows the simple correlations among the two major independent variables of this study (noise exposure and population density), three demographic variables (mean age, duration of residence, and annual household income), and three related measures of annoyance, computed site by site for all respondents
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