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Exposure-effect relationships between aircraft noise and road traffic noise exposure at school and reading.. Clark, Charlotte; Martin, Rocio; van Kempen, Elise; Alfred, Tamuno; Davies, Hugh W.; Head, Jenny; Haines, Mary M.; Barrio Lopez, Isabel; Matheson, Mark; Stansfeld, Stephen A. 2005

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 Exposure-effect relationships between aircraft noise and road traffic noise exposure at school and reading comprehension: The RANCH Study.     Word count abstract: 206 Word count main text: 3,862  Clark. C., Martin. R., van Kempen. E., Alfred. T., Davies. H., Head. J., Haines. M.M., Barrio Lopez. I., Matheson. M., & Stansfeld. S.A.            MeSH headings: Child Psychology, Cognition, Environment and Public Health, Environmental exposure, Epidemiology, Noise, Reading.     1Abstract - Transport noise is an increasingly prominent feature of the urban environment, making noise pollution an important environmental public health issue. This paper reports on the RANCH study, the first cross-national epidemiological study to examine exposure-effect relationships between aircraft and road traffic noise exposure and reading comprehension.  2,010, 9-10 year old children from 89 schools around Amsterdam Schiphol, Madrid Barajas and London Heathrow airports participated. The data from the three countries was pooled and analysed using multilevel modelling. Aircraft noise exposure at school was linearly associated with impaired reading comprehension, maintained after adjustment for socioeconomic variables (ß=-0.008, p=0.012), aircraft noise annoyance and other cognitive abilities (episodic memory, working memory and sustained attention). Aircraft noise exposure at home was highly correlated with aircraft noise exposure at school and demonstrated a similar linear association with impaired reading comprehension. Road traffic noise exposure at school was not associated with reading comprehension, either in the absence or presence of aircraft noise (ß=0.003, p=0.509 ß =0.002, p=0.540, respectively. The findings were consistent across the three countries, which varied with respect to a range of socioeconomic and environmental variables, thus offering robust evidence of a direct exposure-effect relationship between aircraft noise and reading comprehension.  2 INTRODUCTION Exposure to transport noise is an increasing and prominent feature of the urban environment. The ubiquitous demand for air and road travel means that more people are being exposed to transport noise, making noise pollution an increasingly important environmental issue for public health. The effect of chronic aircraft noise exposure and road traffic noise exposure on reading comprehension in primary school children is established (1-6) but no exposure-effect relations for aircraft noise or road traffic noise and reading comprehension at the level of the individual have been established. This paper reports findings of the RANCH study (Road traffic and Aircraft Noise Exposure and Children’s Cognition and Health), the largest epidemiological study undertaken of noise exposure and children’s cognition and health (7), which examined exposure-effect relationships between noise exposure at school and reading comprehension in the Netherlands, Spain and the United Kingdom.   Most previous studies compared the performance of children exposed to high noise levels with children exposed to low noise levels. Whilst demonstrating an effect of chronic noise exposure on reading, these studies provide limited information in terms of the levels at which the effects of noise on children’s reading comprehension begin. Previous studies that examined exposure-effect relationships between aircraft noise exposure and reading assessed reading retrospectively from school records (8, 9) and therefore probably confounded chronic noise exposure with acute noise exposure during testing. The RANCH study examined children from schools from a wide range of noise exposures, making it possible to establish exposure-effect curves for aircraft  3and road traffic noise to examine the lowest observable effect level of noise on reading comprehension.   This is the first study to be able to make inter-country comparisons of the effect size of aircraft and road traffic noise on reading comprehension.  Employing the same methodology in each country enabled a large sample size to be achieved by pooling the data from each country, as well as comparing the effect size across countries.    Areas with high levels of environmental noise are often socially deprived and children from areas with high social deprivation perform poorly on reading comprehension tasks leading to potential confounding (10). Some studies have demonstrated an effect of environmental noise after adjusting for the influence of socioeconomic status (1) and other studies have not (4-6, 8, 10, 11). However, longitudinal studies (12, 13) have found that a reduction of noise exposure eliminated previously observed noise-related reading deficits, suggesting that socioeconomic status does not confound the relationship. This study collected comparable data on socioeconomic status in the Netherlands, Spain and the United Kingdom, to examine whether socioeconomic status confounds the relationship between chronic noise exposure and reading comprehension.   The relationship between noise exposure and reading comprehension may be mediated by other cognitive abilities which are important in the development of children’s reading ability such as attention, episodic memory and working memory. Whilst environmental stressors can have a strong impact on the degree to which information can be processed, retained and recalled (14), a previous study found that  4attention did not mediate the relationship between aircraft noise and reading comprehension (1, 11). The current study collected data on attention, episodic memory and working memory, using the same non-verbal tests in each country, to examine whether these were intervening factors in the association between noise exposure and reading comprehension.  The aim of this study was to assess exposure-effect associations between chronic aircraft and road traffic noise and reading comprehension, using data from nationally standardised reading comprehension tasks completed by 9-10 year old children attending schools exposed to a range of aircraft noise and road traffic noise. It was hypothesised that there would be a linear exposure-effect relationship between aircraft and road traffic noise and reading comprehension: children exposed to high levels of noise would have poorer reading comprehension than children exposed to low levels of noise, after adjustment for socioeconomic factors. The same relationship was hypothesised for aircraft noise exposure at home.   5MATERIALS AND METHODS Sampling and design Children were selected to take part in this cross-sectional epidemiological field study on the basis of levels of noise exposure in schools around major airports in three European countries (Schiphol: Amsterdam, Barajas: Madrid and Heathrow: London).   In each country primary schools around the airport were identified: in Spain and the United Kingdom all non-state schools were excluded; this was not possible in the Netherlands. Within country, schools were matched according to socioeconomic status. In the Netherlands a neighbourhood-level indicator of property value and the percentage of non-Europeans were used to match schools. In Spain and the United Kingdom schools were matched according to the percentage of children in the school receiving free school meals and speaking the main language at home. Main language spoken at home reflects the number of children who are bilingual - who are taught in English or Spanish and who speak another language at home, for example Gujerati in the United Kingdom. Children who were recent immigrants who did not speak the main language of the country proficiently were excluded from the analysis according to a consistent protocol across all countries.   The schools were visited and a noise survey undertaken. Schools were classified in terms of noise exposure on a 4 by 4 grid ranging ordinally from low to high for aircraft noise and low to high for road traffic noise. In each country, two schools were then selected in each of the noise exposure grid cells and within schools mixed-ability classes of boys and girls, aged 9-10 years were selected to take part. No children were excluded from the selected classes.   6 Noise exposure assessment In all three countries, aircraft noise estimates were based on 16-hour outdoor LAeq contours, which gave the average continuous equivalent sound level of aircraft noise within an area from 7am to 11pm for a specified period. The aircraft noise contour data were available nationally and were not specifically derived for this study. In Spain and the United Kingdom the contours used were from July to September for the year 1999 and 2000 respectively; in the Netherlands the contours were from October 1999 to November 2000. These contours were used to estimate aircraft noise exposure at school and home for each participant.  In the Netherlands, outdoor road traffic noise estimates were provided by modelled data (15). In the United Kingdom and Spain, estimates of road traffic noise at school were based upon a combination of modelling the proximity to motorways, A-roads, B-roads, traffic flow data and noise measurements taken at the façade of the school building In all countries, acute noise measurements were taken internally in the classroom and externally during testing. In all analyses, chronic aircraft and road traffic noise were entered as continuous variables in dB (A).   Outcome and confounding factors assessment  Reading comprehension measures. Reading comprehension was measured using established, nationally standardised tests. In the United Kingdom the 86 item, Suffolk Reading Scale, Level 2 was used, which is suitable for children aged 8 years to 11 years 11 months (16). In the Netherlands the 42 item, CITO Readability Index for Elementary and Special Education was used (17). This test is designed for children aged 8 to 12 years. In Spain the 27 item, ECL-2 was used (18). This test is suitable for  7children aged 8 to 13 years.  Z-scores were computed which enabled comparisons to be made between each country’s test.  Potential confounding factors. Comparable measures of potential confounding factors were achieved across countries using a questionnaire completed by the child during testing, and in a parent-completed questionnaire. The questionnaires assessed socioeconomic status, parental and child health and noise-related annoyance. Due to the large number of potential confounders, variables were retained in the multivariate analysis if an analysis of covariance showed a significant relationship between the confounder and aircraft noise exposure and/or road traffic noise exposure (p<.05) (see Table 1).  Mediating cognitive factors. In all three countries, the same established non-verbal tests of cognition were examined (7). Standardised tests were selected, after pilot studies in each country, that could be group administered, were valid for the population being assessed in terms of the age and learning range and were suitable for children who did not speak the main language at home. Episodic memory (recognition, information recall and conceptual recall) was measured using a task from the Child Memory Scale (19) adapted for group administration. Sustained attention was assessed using the Toulouse Pieron Test adapted for classroom use (20). Working memory was assessed using a modified version of ‘The Search & Memory Task’ (21, 22).    Procedure  Group testing was carried out in the classroom and the cognitive tests were administered as part of a two-hour testing session conducted in the morning. Written  8consent was obtained from both parents and the children. Ethical approval was obtained in each country (7).   Analysis Data from all countries was pooled and analysed using MLwiN multilevel modelling software (23), which took into account the hierarchical nature of the data with pupils being clustered in schools. Statistical significance was tested by comparing the goodness of fit of different models using a chi square test of deviance.   Analyses for aircraft noise exposure at school and road traffic noise exposure at school were conducted separately to examine single-exposure effects. For each noise exposure type, two models were run: model 1 (unadjusted) contained only noise exposure (either aircraft or road traffic noise at school); model 2 included both noise exposures, and was adjusted for age, gender, country, mother’s educational attainment, parental employment status, crowding in the home, home ownership, long standing illness, main language spoken at home, parental support for school work and classroom glazing. Further analyses were then conducted additionally adjusting model 2 for acute noise exposure during testing, dyslexia, hearing impairment, noise annoyance, episodic memory (recognition, conceptual recall and information recall), working memory and sustained attention. Hearing impairment was defined as the child suffering recurrent (ear ache, ear infection, glue ear, temporary hearing loss) or serious hearing problems (adenoids removed, grommets fitted, long-term hearing loss, hearing aid). Models 1 and 2 were additionally run substituting aircraft noise exposure at home for aircraft noise exposure at school. To examine combined-exposure effects for aircraft noise, model 2 was additionally adjusted for aircraft noise exposure at  9school and home, using a measure where home aircraft noise exposure for each pupil was centred at their school aircraft noise exposure to assess the effect of the difference between a pupil’s home aircraft noise exposure and their exposure at school.   The possibility of a curvilinear exposure-effect relationship between noise (either aircraft or road traffic noise) and reading comprehension was investigated using fractional polynomial models (24). The best fitting model from a set of two degree fractional polynomials (of the form β1aircraft noisep1 +β2noisep2 where p1 and  p2 belong to the set -2, -1,-0.5,0,0.5,1,2,3) was chosen then the goodness of fit (deviance) of this model was compared with the goodness of fit of a straight line model to test for departure from a straight line relationship.  RESULTS Descriptive results Table 1 illustrates the characteristics of the overall RANCH sample. 2,844 children aged 9-10 (NL=762, Spain=908, UK=1174) from 89 schools (NL=33, Spain=27, UK=29) participated. The average age was 10 years, 6 months and 53 percent were female. The overall child response rate was 89 percent and for the parent questionnaire was 78 percent; participation rates did not vary significantly across noise exposure categories. Completed parent questionnaires were available for 2,380 (84%) of the children who participated. There were sociodemographic differences between the countries in terms of parental employment status, home ownership, crowding in the home and main language spoken at home. These findings reflect sociodemographic differences between the countries and were adjusted for in the analyses. Aircraft noise exposure ranged from 30 to 77dB (A), with Spain having  10lower mean aircraft noise exposure than the United Kingdom or Netherlands (see Table 1). Road traffic noise exposure ranged from 32-71dB (A) and was similar across the three countries.   Subjects with no missing values for the potential confounders outlined in Table 1  were included in the analysis. The sub-sample consisted of 85 percent of the overall sample (Total N=2,010, NL=583, Spain=572, UK=855) and did not differ significantly in terms of sociodemographic characteristics from the overall sample, or in terms of reading and cognitive test scores.    Effects of aircraft noise at school on reading comprehension Increasing aircraft noise exposure at school was significantly related to poorer reading comprehension (χ2=6.62, df=1, p=0.012: Table 3). In the adjusted model, as noise increased by 5dB (A), performance on the reading test (measured by z-scores) decreased by -0.035 marks for the overall sample. Children scored lower on the reading test if they had a mother with a low educational attainment or if the child had a long standing illness and higher if their parent/s were homeowners, if the child spoke the main language of the country and if the child perceived a high level of parental support for schoolwork. The effect of aircraft noise exposure on reading comprehension remained when the model was further adjusted for dyslexia, hearing impairment and acute noise during testing, as well as for working memory, sustained attention and episodic memory (conceptual recall and information recall) (Table 4); the significance of the effect was borderline after adjustment for recognition memory (p=0.062) and noise annoyance (p=0.05).     11In all three countries the same inverse relationship between aircraft noise exposure at school and reading comprehension was found (Table 5, Test of heterogeneity p=0.9).  In the Netherlands and Spain, a 20dB (A) increase in aircraft noise was associated with a decrement of one-eighth of a standard deviation on the reading test; in the United Kingdom the decrement was one-fifth of a standard deviation. The size of the effect did not differ for high and low socioeconomic position. In terms of reading age, using the national data relating to the reading comprehension tests (16, 17), one-eighth of a standard deviation was equivalent to an 8 month difference in reading age in the UK and a 4 month difference in reading age in the Netherlands: no comparative national data was available for the Spanish ECL-2 test.     Figure 1 shows reading comprehension adjusted for age, gender and country by 5 dB (A) bands of aircraft noise. There was no significant departure from linearity when comparing straight line fit with best fitting fractional polynomial curve (p=0.99).   12Effect of aircraft noise exposure at home on reading comprehension Aircraft noise exposure at home was highly correlated with aircraft noise exposure at school (NL r=.93, Spain r=.85, UK r=.91,) (Figure 2). Increasing aircraft noise exposure at home was significantly and linearly related to poorer reading comprehension (χ2=5.88, df=1, p=0.015). There was no additional effect of home aircraft noise exposure, after adjustment for aircraft noise exposure at school (χ2=0.24, df=1, p=0.625) (Table 6).    Effect of road traffic noise at school on reading comprehension  Chronic road traffic noise exposure at school had no significant effect on reading comprehension either before (χ2=0.44, df=1, p=0.51, model not shown) or after adjustment for aircraft noise exposure at school (χ2=0.37, df=1, p=0.54, Table 2). There was no significant departure from linearity for reading comprehension adjusted for age, gender and country (p=0.90 for comparison of straight line fit with best fitting fractional polynomial curve).   DISCUSSION The aim of this study was to compare performance on a standardised reading comprehension task for children aged 9-10 years, attending schools exposed to varying levels of aircraft noise and road traffic noise around major airports in three European countries. There were three main findings. Firstly, there was a linear exposure-effect relationship between aircraft noise exposure at school and impaired reading comprehension, with a similar effect being observed in all three countries. Secondly, the effect of aircraft noise on reading comprehension could not be accounted for by sociodemographic variables, acute noise during testing, aircraft  13noise annoyance, episodic memory, working memory or sustained attention. Thirdly, there was no evidence of a relationship between road traffic noise and reading comprehension. These results raise concerns regarding the effect of chronic aircraft noise exposure on children’s reading ability.    This is the first study to establish that the exposure-effect relationship between aircraft noise and reading comprehension is linear. In all three countries there was a negative relationship between aircraft noise exposure at school and reading comprehension.  These results are consistent with previous studies (1, 3) but less consistent with the West London Schools and the Munich studies, which reported an effect for only the most difficult items on a standardised reading test (10, 12). The current study utilised an exposure-effect measure of aircraft noise exposure, examining a wider range of noise exposures, whilst the previous studies categorised children into low and high aircraft noise exposure thus limiting the power of the studies; the Munich study also categorised children on the basis of home noise exposure.    The magnitude of the effect of aircraft noise on reading comprehension did not differ among countries. In the Netherlands and Spain, a 20dB (A) increase in aircraft noise was associated with a decrement of one-eighth of a standard deviation on the reading test; in the United Kingdom the decrement was one-fifth of a standard deviation. Whilst the effect of aircraft noise on reading is small in magnitude, the consequences of long-term exposure on reading comprehension remain unknown. It is possible that children could be exposed to aircraft noise for many of their childhood years; in the United Kingdom and Spain high environmental noise exposure is often found in socially deprived areas where social mobility is low. Whilst the Munich study (12)  14demonstrated that the effects of aircraft noise exposure on reading comprehension are reversible if the noise ceases, studies have yet to examine the long-term developmental consequences of exposure that persists throughout the child’s education. Demand for air travel continues to increase and further knowledge about cumulative exposure would inform intervention strategies and policy decisions.     In some previous studies, the association between noise exposure and reading has been confounded by socioeconomic status (10). This study has examined a comprehensive set of individual level socioeconomic status variables in all three countries and found that the relationship between aircraft noise exposure and reading comprehension could not be accounted for by socioeconomic status or other individual level factors, such as long standing illness and parental social support. The United Kingdom sample, despite being from a lower socioeconomic group, responded in a similar way to noise exposure as the more affluent Dutch and Spanish samples, suggesting that socioeconomic factors do not explain the effect of aircraft noise on reading.   The relationship between aircraft noise exposure and reading comprehension was not mediated by sustained attention, working memory or episodic memory: the significance of the effect was borderline after adjustment for the recognition measure of episodic memory, but remained after adjustment for conceptual recall and information recall. There was limited support (1) that the relationship was not mediated by noise annoyance.  These results, together with previous findings (1, 12) suggest that noise may either directly effect reading comprehension or be accounted for by other mechanisms.  It is postulated that noise restricts attention to central cues  15during complex language related tasks (4, 25, 26). The current research has not examined the psycholinguistic mechanisms that may underlie the effect and further research on psycholinguistic mechanisms will inform the design of educational and environmental interventions for children in schools exposed to high levels of aircraft noise.   Aircraft noise exposure at school and home independently demonstrated a comparable association with reading comprehension. There was substantial collinearity between school and home aircraft noise exposure, which has been previously demonstrated (10), making it difficult to assess whether exposure at school or home differentially affected reading comprehension. We demonstrated that there was no additional effect of home aircraft noise exposure, after adjustment for aircraft noise exposure at school. It has not been possible to fully establish the relative contribution of home and school exposure over the 24 hours to cognitive deficits in children in this study and this is an important challenge for future research.   There was no significant effect of road traffic noise exposure on reading comprehension which refuted our hypothesis and is inconsistent with previous studies (4, 5). However, the levels of road traffic noise in this study were not as high as in some previous studies. In the Cohen et al study noise levels were typically above 80 dB (A), based on the mode of 5 minute measures at home. In this study the annual equivalent levels ranged from 32-71 dB (A) at school. It is also possible that exposure to road traffic noise at home may influence reading either in its own right or by interacting with exposure at school: unfortunately national data on road traffic noise exposure at home were not available. No definite conclusion about the effect of road  16traffic noise exposure can be drawn until the results of the current study are replicated and the effect of home road traffic noise exposure investigated.   Why should there be an effect for aircraft but not road traffic noise? Aircraft noise has a greater intensity and is less predictable than road traffic noise. The transient nature of aircraft flyovers, which have high short-term levels, may disrupt the child’s concentration and distract them from learning tasks, whilst the constant nature of road traffic noise may allow children to habituate and not be distracted. Banbury et al (27) suggest that sound which shows an appreciable variation over time will impair cognitive performance whereas sound that does not will show little or no impairment. Aircraft noise exposure may also cause higher arousal levels than road traffic noise and high arousal will interfere with performance tasks, such as reading comprehension (28). A further explanation for the lack of an effect for road traffic noise exposure is that differences between countries in estimating road traffic noise exposure may have resulted in a differential quality in exposure assessment; traffic flow may have been underestimated; exposure misclassification may also have occurred as classrooms were at varying distances from the façade of the school building.   The study had limitations: reading measures were not exactly equivalent across countries; a reliance on external measures of noise exposure; and lack of data about noise exposure over the 24 hours. However, this study represents an improvement on previous studies due to its size, both in terms of number of participants and schools. It is the largest study of noise exposure and cognition in children and is the only study able to compare the reading effect size in different countries across a wide range of  17noise exposures. The application of multilevel modelling has enabled the effect of both school level and individual level variables to be examined. A further strength of the study is the comprehensive number of individual level socioeconomic variables which have been examined.   In conclusion, our results suggest that aircraft noise exposure is linearly associated with impaired reading comprehension. No association was found between road traffic noise exposure and reading comprehension, either in the absence or presence of aircraft noise. However an effect at higher road traffic noise levels cannot be ruled out by this study. The consistent findings across the three countries, with substantial differences on a range of socioeconomic and environmental variables, offer robust evidence of an exposure-effect relationship between aircraft noise and reading comprehension.  Acknowledgements - The RANCH study was funded by the European Community (QLRT-2000-00197) in the Vth framework programme under Key Action 1999: /C 361/06 ‘Quality of life and management of living resources’. The RANCH study was co-funded by the Department of Environment, Food and Rural Affairs (UK), the Dutch Ministry of Public Health, Welfare and Sports, the Dutch Ministry of Spatial Planning, Housing and the Environment and the Dutch Ministry of Transport, Public Works and Water Management. In the United Kingdom, ethical approval was given by the East London and the City Local Research Ethics Committee, East Berkshire Local Research Ethics Committee, Hillingdon Local Research Ethics Committee and the Hounslow District Research Ethics Committee; in the Netherlands, by the medical ethics committee of TNO, Leiden and in Spain, by the CSIC Bioethical Commission,  18Madrid. We thank all the pupils, parents and teachers who participated and other members of the RANCH team: Rebecca Asker, Birgitta Berglund, Bernard Berry, Sarah Brentnall, Rachel Cameron, Paul Fischer, Anita Gidlöf Gunnarsson, Emina Hadzibajramovic, Maria Holmes, Staffan Hygge, Mats E Nilsson, E. Öhrström, Rebecca Stellato, Helena Svensson and Irene van Kamp.  19REFERENCES   1.  Haines MM, Stansfeld SA, Job RFS et al. Chronic aircraft noise exposure, stress responses, mental health and cognitive performance in school children. Psychol Med 2001;31:265-77.  2.  Evans GW, Hygge S, Bullinger M. Chronic noise and psychological stress. Psychol Sci 1995;6:333-8.  3.  Evans GW & Maxwell L. Chronic noise exposure and reading deficits: The mediating effect of language acquisition. Environ Behav 1997;29:638-56.  4.  Cohen S, Glass DC & Singer JE. Apartment noise, auditory discrimination, and reading ability in children. J Exp Soc Psychol 1973;9:407-22.  5.  Lukas JS, DuPree RB & Swing JW.  Report of a study on the effects of freeway noise on academic achievement of elementary school children.  1981. Sacramento, CA, California Department of Health Services.    6.  Shield B & Dockrell J.  The effects of noise on the attainments and cognitive performance of primary school children.  2002. UK, Department of Health.    7.  Stansfeld SA, Berglund B, Clark C et al. Aircraft and road traffic noise and children's cognition and health: exposure-effect relationships. The Lancet 2005; 365:1942-1949.  8.  Haines MM, Stansfeld SA, Head J et al. Multilevel modelling of aircraft noise on performance tests in schools around Heathrow Airport London. Journal Epidemiol  Community Health 2002;56:139-44.  9.  Green KB, Pasternack BS & Shore RE. Effects of aircraft noise on reading ability of school-age children. Arch Environ Health 1982;24-31.  10.  Haines MM, Stansfeld SA, Brentnall S et al. The West London Schools Study: the effects of chronic aircraft noise exposure on child health. Psychol Med 2001;31:1385-96.  11.  Haines MM, Stansfeld SA, Job RFS et al. A follow-up study of effects of chronic aircraft noise exposure on child stress responses and cognition. Int J Epidemiol 2001;30:839-45.  12.  Hygge S, Evans GW, Bullinger M. A prospective study of some effects of aircraft noise on cognitive performance in school children. Psychol Sci 2002;13:469-74.  13.  Bronzaft AL. The effect of a noise abatement program on reading ability. J Environ Psychol 1981;1:215-22.  14.  Cohen S, Evans GW, Stokols D et al. Behavior, Health and Environmental Stress. New York: Plenum Press, 1986.  20 15.  Dassen AG, Jabben J, Dolmans JHJ.  Development and use of EMPARA: a model for analysing the extent and effects of local environmental problems in the Netherlands.  2001. The Hague, Proceedings of the 2001 International Congress and Exhibition on Noise Control Engineering.    16.  Hagley F.  Suffolk Reading Scale 2.  2002. Windsor, NFER-NELSON.    17.  Staphorsius G. Leesbaarheid en leesvaardigheid. De ontwikkeling van een domeingericht meetinstrument. 1994. Arnhem: CITO.   18.  De La Cruz.V. ECL-2. 1999. Madrid: TEA Ediciones, S.A..   19.  Cohen MJ.  Children's Memory Scale Manual.  1997. San Antonio, The Psychological Corporation Harcout Brace and Company.    20.  Toulouse E& Pieron H.  Prueba Perceptiva y de Atencion (Test of perception and attention).  1986. Madrid, TEA Ediciones, S.A.    21.  Smith AP & Miles C. The combined effects of occupational health hazards: an experimental investigation of the effects of noise, nightwork and meals. Int Arch Occup Environ Health 1987;59:83-9.  22.  Hygge S, Boman E & Enmarker I. The effects of road traffic noise and meaningful irrelevant speech on different memory systems. Scand J Psychol 2003;44:13-21.  23.  Rasbash J, Brown W, Goldstein H et al. A user's guide to MLwiN. 2002. London: Centre for Multilevel Modelling, Institute of Education, University of London.   24.  Royston P & Altman DG. Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. App Stat 1994;43:429-67.  25.  Cohen S, Evans GW, Krantz DS et al. Physiological, motivational, and cognitive effects of aircraft noise on children. Am Psychol 1980;35:231-43.  26.  Evans GW & Lepore SJ. Non-auditory effects of noise on children. Children's Environments 1993;10:31-51.  27.  Banbury Macken WJ, Tremblay S et al. Auditory distraction and short-term memory: phenomena and practical implications. Hum Factors 2001;43:19-29.  28.  Yerkes RM & Dodson JD. The relation of strength of stimulus to rapidity of habit formation. J Comparative Neurological Psychology 1908;18:459-82.  29.     Mackenbach, J.P. & Kunst, A.E. Measuring the magnitude of socioeconomic  inequalities in health: an overview of available measures illustrated with two examples from Europe. Soc Sci Med 1997; 44:757-717.  21 Table 1: School and pupil level characteristics of the RANCH sample: overall and by country.   Sociodemographic characteristic* Pooled sample  UK sample  NL sample   Spanish sample  SCHOOL LEVEL DATA n=89 n=29 n=33 n=27Number of classes 129 47 34 48 Number of pupils invited  3207 1355 824 1028Number of pupils participating  2844  1174  762  908 Number of pupils & parents participating  2276  960  658  658 Aircraft noise exposure at school dB (A) Mean (SD) Range   52 (9.7) 30-77   52 (9.4) 34-68   54 (7.01) 41-68   43 (10.7) 30-77 Road traffic noise exposure at school dB (A) Mean (SD) Range   51 (7.57) 32-71   48 (7.25) 37-67   53 (8.87) 32-66   53  (5.98) 43-71 Classroom glazing (%) Single glazing Double glazing Triple glazing  59.0 38.3 2.7  61.0 39.0 0.0  43.4 47.2 9.4  72.0 28.0 0.0      PUPIL LEVEL DATA  n=2844 n=1174 n=762 n=908Response rate (%) Child Parent  89 80  87 82  92 86  88 72 Aircraft noise exposure at home Mean (SD) Range   50 (8.9) 31-76   53 (8.9) 33-76   49 (7.06) 34-65   46 (9.1) 31-73  22 23Age Mean  Range  10yrs, 6mth 8y10m -12y10m  10yrs, 3mth 8y10m -11y11m  10yrs,6mth  8y10m - 12y10m  10yrs,11mth 9y5m -12y4m Sex (%) Male Female  47.1 52.9  45.1 54.9  49.9  50.1   47.1 52.9 Employment status (%) Not employed Employed  14.9 85.1  22.7 77.3  7.4 92.6  11.1 88.9 Crowding (%) Not crowded Crowded   78.6 21.4  77.3 22.7  68.8 31.2  90.5 9.5 Home ownership (%) Not owned Owned  27.7 72.3  42.1 57.9  18.9 81.1  15.4 84.6 Long standing illness (%) No LSI LSI   75.9 24.1  73.6 26.4  73.2 26.8  81.8 18.2 Main language spoken at home (%) Other language Main language  11.9 88.1  22.0 78.0  6.6 93.4  2.4 97.6      Mother’s education  Mean  SD  .50 .28  .50 .28  .50 .28  .50 .28 Parental support scale  Mean SD Cronbach’s α  10.1 2.0 .650  10.1 1.9 .591  8.8 1.9 .582  11.1 1.5 .570 *UK=United Kingdom, NL=Netherlands, na=not applicable. Age was collected from both school records and parents. Employment status, whether the parent worked full-or part-time. Crowding, the number of people per room in the house, was defined as more than 1.5 people per room for the UK and Spain and equal to or more than one person per room in the Netherlands (The different cut off points reflect the different official definitions of this concept in each country). Home ownership, whether the home was rented or owned/mortgaged. Long standing illness was based on parental reports of the child having either attention deficit hyperactivity disorder (ADHD), asthma/bronchitis, eczema, epilepsy, depression, diabetes or dyslexia. Main language spoken at home indicated whether the child spoke the predominant language for the country at home, i.e. Dutch, Spanish or English. Classroom glazing was a measure of the glazing (single, double or triple) of the windows in the child’s classroom.  Mother’s educational attainment was measured using a relative inequality index based upon a ranked index of standard qualifications in each country (29). Parental support for school work was assessed by a self-report scale completed by the child. This table excludes missing values which were age 5%, gender <1%, crowding 7%, home ownership 6%, long standing illness 4%, main language spoken at home 5%, classroom glazing 0%, mother’s education 7%, parental support 6%.Table 2: Mean, standard deviation and range for the reading comprehension, episodic memory, working memory, sustained attention and annoyance tasks for the RANCH sample: overall and by country.    O n=2844 n=908 n=1174 n=762 R ding comprehension  (z core) MSta0.001.00-2.36-3.07 0.01.00-2.09-2.55 0.01.00-2.05-2.31 0.001.002.36-3.07 Recognition memory MStR2 2 2 2In  recall Meviation  17.68 18.6 16.7 17.33CMeviation  R 0-9 0- 0.5- 0-7MStaMR42.94 -9744.52 -971041.80 -940.33 -92Ai  noise annoyance at scMeviation  R 1-5 1- 1- 1-5    utcome       Pooled sample  UK sample  NL sample  Spain sample  ea-sean ndard deviation  Range       0    0      ean andard deviation  ange formation 5.08 2.46 13-30   4.94 2.64 14-30   5.35 2.03 18-30   5.04 2.51 13-30  ean Standard dRange  5.24 0-30.5 0 5.42 0-30.5 1 4.54 1-28  5.35 0-30.5 onceptual recall ean Standard dange Working memory  4.86 1.40    5.18 1.41 9   4.98 1.27 8   4.37 1.36   ean ndard deviation  Range 16.16 7.28 -13-35 14.82 7.39 -13-32 16.73 7.06 -10-33 17.32 7.06 -13-35 Sustained attention ean Standard deviation  ange rcraft 101.72 -222   94.96 -220   2.68 5-205   109.57 -222  hool ean Standard dange  2.01 1.02   2.17 1.08 5  1.96 0.93 5  1.82 0.98   24 Table 3: The mul ameter estimates for ai raft noise and road traffic noise and reading comprehension for the pooled data. tilevel model par rc       N=2010 Model →  Aircraft No ool Unadjusted Road Traffic Noise at School Unadjusted e at School & Road  School djusted ise at Sch Aircraft NoisTraffic Noise atAFixed coefficient B (SE) p-value B (SE) p-value p-values  B (SE)   Intercept 0.404 (0.167) -0.168 (0.223) -1.364 5) 0.02aircraft noise at s -0.007 (0.003) 0.013  -0.008 03) 0.012road noise at school  (0.004) 0.454 0.002 .004) 0.54Spain  ref refUK  0.272 (0.082) 0.001Netherlands  0.320 (0.084) <0.001age     0.162 (0.147) 0.271female  -0.056 (0.042) 0.18employed  0.080 (0.064) 0.21crowded  -0.073 (0.054) 0.18home owner    0.205 (0.053) <0.001mother’s education    -0.713 (0.077) <0.001long standing illness    -0.147 (0.004) 0.003speak main language at home    0.183 (0.076) 0.016parental support    0.084 (0.011) <0.001classroom glazing    0.001 (0.027) 0.95   Random Parameters ↓     Level 2: School 0.042 (0.013)  0.049 (0.014)  0.023 (0.010)  Level 1: Pupil 0.951 (0.030)  0.950 (0.030)  0.865 (0.279)         The adjusted models are evaluated against a model with the noise source excluded. Aircraft noise adjusted χ2=6.62, df=1, p=0.012, road traffic noise adjusted χ2=0.37, df=1, p=0.54. (0.62 (0.0chool 0.003 (0 25 Table 4: The multilevel model parameter estimates for aircraft noise at school on reading comprehension additionally adjusted for memory utcomes and aircraft noise annoyance.  o    Aircraft Noise at SchAdjusted ool  N B (SE) p-valueAdjusted*  2010 -0.008 (0. 0.012djusted + working memory  1920 -0.006 (0.002) 0.015+ recognition memory  -0.005 (0.002)ecall  -0.006 (0.00 0.018ion recall  1952 -0.006 (0.002)ed + sustained attention  1918 -0.008 (0.002) 0.003sted + aircraft noise annoyance  1926 -0.006 (0.003) 0.05 003)AAdjusted 1978 0.062Adjusted + conceptual r 1953 2)Adjusted + informat 0.028AdjustAdju*adju for age, gender, country, mother’s education, empl ment status, crowding, homeown ip, long-standing illne uage spoken me, parental support, class azing and road traffic noise exposure.    sted oy ersh ss, main lang  at horoom gl 26 Table 5: The effect size of aircraft noise and road traffic noise on reading comprehension for the pooled data and for each country.    B SE Confidence interval 95% p-value from χ2 Aircraft Noise at school     Pooled estimate* 0.003 -0.014, -0.002 0.012 0.005 -0.019, 0.001  0.007 -0.020, 0.008  0.00 -0.016 0.004 -0.008 UK  -0.009 NL  -0.006 Spain -0.006Road Traffic Noise at school     Pooled estimate* 0.002 0.004 -0.005, 0.009 0.54 0.004 0.005 -0.007, 0.014  Spain 0.008 0.008 -0.009 0.024 UK  -0.003 0.006 -0.014, 0.009  NL  *Test of heterogeneity: aircraft noise p=0.9, road traffic noise p=0.10.  27   4-.20.2.4.-Reading Z-score30 35 40 45 50 55 60 65 70  Figure 1: Adjusted mean reading Z-score and 95% confidence interval bars for 5 dB (A) bands of aircraft noise (adjusted for age, gender and country).       aircraft noise dB(A) 28                     Figure 2. Relationship between aircraft noise exposure at school and aircraft noise exposure at home for the pooled data.  3040506070Aircraft noise at home, dB(A)30 40 50 60 70 80Aircraft noise at school, dB(A) 29  Table 6. The multilevel model parameter estimates for aircraft noise at home and school and road traffic noise at school on reading omprehension for the pooled data.  Aircraft noise at home and road traffic noise at school adjusted† Aircraft noise at home and school, and road traffic noise at school adjusted†  B (SE) p-value B (SE) p-value aircraft noise at home  -0.008 (0.003) 0.015 -0.003 (0.006) 0.6 aircraft noise at school   -0.009 (0.003) 0.008 road traffic noise at chool 0.002 (0.004) 0.50 0.002 (0.004) 0.5 The adjusted models are evaluated against a model with the noise source excluded. Aircraft noise at home adjusted 2=5.88, df=1, p=0.015; aircraft noise at home and school adjusted χ2=0.24, df=1, p=0.625.  Both models additionally adjusted for country, age, gender, mother’s education, employment status, crowding, homeownership, long-standing illness, main language spoken at home, parental upport and classroom glazing. c  sχ†s    30 

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